Research Areas:

Artificial Intelligence in Healthcare

An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements

Authors:
Gregorio Dotti, Marco Ghislieri, Cristina Castagneri, Valentina Agostini, Marco Knaflitz, Gabriella Balestra and Samanta Rosati
Journal:
IOP Physiological Measurement
DOI:
10.1088/1361-6579/ad814f
Year:
2024
Abstract:

Dynamic muscle activity can be quantitatively and non-invasively investigated during several cyclical movements by acquiring surface electromyographic (sEMG) signals. The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in the clinical practice. To overcome this limitation, specific algorithms are needed to help scientists to easily characterize and assess muscle activation patterns during cyclical movements. In this perspective, CIMAP (Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment muscle activation pattern. The toolbox can be flexibly modified to comply with the necessities of the scientist. CIMAP is addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub (https://github.com/Biolab-PoliTO/CIMAP).

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Carotid Ultrasound Boundary Study (CUBS): Technical considerations on an open multi-center analysis of computerized measurement systems for intima-media thickness measurement on common carotid artery longitudinal B-mode ultrasound scans

Authors:
K. M. Meiburger, F. Marzola, G. Zahnd, F. Faita, C. P. Loizou, N. Lainé, C. Carvalho, D. A. Steinman, L. Gibello, R.M. Bruno, R. Clarenbach, M. Francesconi, A. N. Nicolaides, H. Liebgott, A. Campilho, R. Ghotbi, E. Kyriacou, N. Navab, M. Griffin, A. G. Pa
Journal:
Computers in Biology and Medicine
DOI:
10.1016/j.compbiomed.2022.105333
Year:
2022
Abstract:

After publishing an in-depth study that analyzed the ability of computerized methods to assist or replace human experts in obtaining carotid intima-media thickness (CIMT) measurements leading to correct therapeutic decisions, here the same consortium joined to present technical outlooks on computerized CIMT measurement systems and provide considerations for the community regarding the development and comparison of these methods, including considerations to encourage the standardization of computerized CIMT measurements and results presentation. A multi-center database of 500 images was collected, upon which three manual segmentations and seven computerized methods were employed to measure the CIMT, including traditional methods based on dynamic programmingdeformable models, the first order absolute moment, anisotropic Gaussian derivative filters and deep learning-based image processing approaches based on U-Net convolutional neural networks. An inter- and intra-analyst variability analysis was conducted and segmentation results were analyzed by dividing the database based on carotid morphology, image signal-to-noise ratio, and research center. The computerized methods obtained CIMT absolute bias results that were comparable with studies in literature and they generally were similar and often better than the observed inter- and intra-analyst variability. Several computerized methods showed promising segmentation results, including one deep learning method (CIMT absolute bias = 106 ± 89 μm vs. 160 ± 140 μm intra-analyst variability) and three other traditional image processing methods (CIMT absolute bias = 139 ± 119 μm, 143 ± 118 μm and 139 ± 136 μm). The entire database used has been made publicly available for the community to facilitate future studies and to encourage an open comparison and technical analysis (https://doi.org/10.17632/m7ndn58sv6.1).

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Integration of Deep Learning and Active Shape Models for More Accurate Prostate Segmentation in 3D MR Images

Authors:
Massimo Salvi, Bruno De Santi, Bianca Pop, Martino Bosco, Valentina Giannini, Daniele Regge, Filippo Molinari, and Kristen M. Meiburger
Journal:
Journal of Imaging
DOI:
https://doi.org/10.3390/jimaging8050133
Year:
2022
Abstract:

Magnetic resonance imaging (MRI) has a growing role in the clinical workup of prostate cancer. However, manual three-dimensional (3D) segmentation of the prostate is a laborious and time-consuming task. In this scenario, the use of automated algorithms for prostate segmentation allows us to bypass the huge workload of physicians. In this work, we propose a fully automated hybrid approach for prostate gland segmentation in MR images using an initial segmentation of prostate volumes using a custom-made 3D deep network (VNet-T2), followed by refinement using an Active Shape Model (ASM). While the deep network focuses on three-dimensional spatial coherence of the shape, the ASM relies on local image information and this joint effort allows for improved segmentation of the organ contours. Our method is developed and tested on a dataset composed of T2-weighted (T2w) MRI prostatic volumes of 60 male patients. In the test set, the proposed method shows excellent segmentation performance, achieving a mean dice score and Hausdorff distance of 0.851 and 7.55 mm, respectively. In the future, this algorithm could serve as an enabling technology for the development of computer-aided systems for prostate cancer characterization in MR imaging.

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Deep learning segmentation of transverse musculoskeletal ultrasound images for neuromuscular disease assessment

Authors:
Francesco Marzola, Nens van Alfen, Jonne Doorduin, Kristen M. Meiburger
Journal:
Computers in Biology and Medicine
DOI:
10.1016/j.compbiomed.2021.104623
Year:
2021
Abstract:

Ultrasound imaging is a patient-friendly and robust technique for studying physiological and pathological muscles. An automatic deep learning (DL) system for the analysis of ultrasound images could be useful to support an expert operator, allowing the study of large datasets requiring less human interaction. The purpose of this study is to present a deep learning algorithm for the cross-sectional area (CSA) segmentation in transverse musculoskeletal ultrasound images, providing a quantitative grayscale analysis which is useful for studying muscles, and to validate the results in a large dataset. The dataset included 3917 images of biceps brachii, tibialis anterior and gastrocnemius medialis acquired on 1283 subjects (mean age 50 ± 21 years, 729 male). The algorithm was based on multiple deep-learning architectures, and its performance was compared to a manual expert segmentation. We compared the mean grayscale value inside the automatic and manual CSA using Bland-Altman plots and a correlation analysis. Classification in healthy and abnormal muscles between automatic and manual segmentation were compared using the grayscale value z-scores. In the test set, a Precision of 0.88 ± 0.12 and a Recall of 0.92 ± 0.09 was achieved. The network segmentation performance was slightly less in abnormal muscles, without a loss of discrimination between healthy and abnormal muscle images. Bland-Altman plots showed no clear trend in the error distribution and the two readings have a 0.99 Pearson’s correlation coefficient (p < 0.001, test set). The ICC(A, 1) calculated between the z-score readings was 0.99. The algorithm achieves robust CSA segmentation performance and gives mean grayscale level information comparable to a manual operator. This could provide a helpful tool for clinicians in neuromuscular disease diagnosis and follow-up. The entire dataset and code are made available for the research community.

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A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images

Authors:
J. Panic; A. Defeudis; S. Mazzetti; S. Rosati; G. Giannetto; L. Vassallo; D. Regge; G. Balestra; V. Giannini
Journal:
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
DOI:
10.1109/EMBC44109.2020.9175804
Year:
2020
Abstract:

The aim of the study is to present a new Convolutional Neural Network (CNN) based system for the automatic segmentation of the colorectal cancer. The algorithm implemented consists of several steps: a pre-processing to normalize and highlights the tumoral area, the classification based on CNNs, and a post-processing aimed at reducing false positive elements. The classification is performed using three CNNs: each of them classifies the same regions of interest acquired from three different MR sequences. The final segmentation mask is obtained by a majority voting. Performances were evaluated using a semi-automatic segmentation revised by an experienced radiologist as reference standard. The system obtained Dice Similarity Coefficient (DSC) of 0.60, Precision (Pr) of 0.76 and Recall (Re) of 0.55 on the testing set. After applying the leave-one-out validation, we obtained a median DSC=0.58, Pr=0.74, Re=0.54. The promising results obtained by this system, if validated on a larger dataset, could strongly improve personalized medicine.

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Radiomics predicts response of individual HER2-amplified colorectal cancer liver metastases in patients treated with HER2-targeted therapy

Authors:
V. Giannini, S. Rosati, A. Defeudis, G. Balestra, L. Vassallo, G. Cappello, S. Mazzetti, C. De Mattia, F. Rizzetto, A. Torresin, A. Sartore-Bianchi, S. Siena, A. Vanzulli, F. Leone, V. Zagonel, S. Marson
Journal:
International journal of cancer
DOI:
10.1002/ijc.33271
Year:
2020
Abstract:

The aim of our study was to develop and validate a machine learning algorithm to predict response of individual HER2-amplified colorectal cancer liver metastases (lmCRC) undergoing dual HER2-targeted therapy. Twenty-four radiomics features were extracted after 3D manual segmentation of 141 lmCRC on pretreatment portal CT scans of a cohort including 38 HER2-amplified patients; feature selection was then performed using genetic algorithms. lmCRC were classified as nonresponders (R-), if their largest diameter increased more than 10% at a CT scan performed after 3 months of treatment, responders (R+) otherwise. Sensitivity, specificity, negative (NPV) and positive (PPV) predictive values in correctly classifying individual lesion and overall patient response were assessed on a training dataset and then validated on a second dataset using a Gaussian naïve Bayesian classifier. Per-lesion sensitivity, specificity, NPV and PPV were 89%, 85%, 93%, 78% and 90%, 42%, 73%, 71% respectively in the testing and validation datasets. Per-patient sensitivity and specificity were 92% and 86%. Heterogeneous response was observed in 9 of 38 patients (24%). Five of nine patients were carriers of nonresponder lesions correctly classified as such by our radiomics signature, including four of seven harboring only one nonresponder lesion. The developed method has been proven effective in predicting behavior of individual metastases to targeted treatment in a cohort of HER2 amplified patients. The model accurately detects responder lesions and identifies nonresponder lesions in patients with heterogeneous response, potentially paving the way to multimodal treatment in selected patients. Further validation will be needed to confirm our findings.

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Radiomics for Identification of Active Bone Marrow from CT: An Exploratory Study

Authors:
S. Rosati; G. Balestra; P. Franco; C. Fiandra; F. Arcadipane; P. Silvetti; U. Ricardi; E. Gallio
Journal:
2018 IEEE Life Sciences Conference (LSC)
DOI:
10.1109/LSC.2018.8572154
Year:
2018
Abstract:

The radiation dose received by the pelvic Bone Marrow (BM) is a predictive factor for Hematologic Toxicity (HT) occurrence in the treatment of anal cancer. For this reason it is important to avoid BM during radiotherapy. In particular, the standard strategy in these cases consists in the identification of hematopoietically active BM (actBM), i.e. the part of BM in charge of blood cells generation, on 18 FDG-PET, FLT-PET or MRI, but no approached have been developed for identifying actBM from CT images. This exploratory study aims to use radiomics for detecting actBM on CT sequences. Our approach is based on the extraction of 36 first-order and texture (second-order) features for each CT slice. These features are used as input of a Decision Tree (DT) classifier able to discriminate between active and inactive BM regions on the images. This method was applied to five patients affected by carcinoma of the anal canal and the obtained actBM segmentation was compared with the standard actBM identification from 18 FDG-PET (reference standard, RS). Our results show that actBM identification in lumbosacral and iliac structures using radiomics overlaps the RS for more than 75% in 4 out of 5 patients.

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Biomedical Signal And Data Processing

A comparative study of muscle activity and synergies during walking in baboons and humans

Authors:
Francois Druelle*, Marco Ghislieri*, Pablo Molina-Vila, Brigitte Rimbaud, Valentina Agostini, Gilles Berillon
Journal:
Journal of Human Evolution
DOI:
10.1016/j.jhevol.2024.103513
Year:
2024
Abstract:

Bipedal locomotion was a major functional change during hominin evolution, yet, our understanding of this gradual and complex process remains strongly debated. Based on fossil discoveries, it is possible to address functional hypotheses related to bipedal anatomy, however, motor control remains intangible with this approach. Using comparative models which occasionally walk bipedally has proved to be relevant to shed light on the evolutionary transition toward habitual bipedalism. Here, we explored the organization of the neuromuscular control using surface electromyography (sEMG) for six extrinsic muscles in two baboon individuals when they walk quadrupedally and bipedally on the ground. We compared their muscular coordination to five human subjects walking bipedally. We extracted muscle synergies from the sEMG envelopes using the nonnegative matrix factorization algorithm which allows decomposing the sEMG data in the linear combination of two non-negative matrixes (muscle weight vectors and activation coefficients). We calculated different parameters to estimate the complexity of the sEMG signals, the duration of the activation of the synergies, and the generalizability of the muscle synergy model across species and walking conditions. We found that the motor control strategy is less complex in baboons when they walk bipedally, with an increased muscular activity and muscle coactivation. When comparing the baboon bipedal and quadrupedal pattern of walking to human bipedalism, we observed that the baboon bipedal pattern of walking is closer to human bipedalism for both baboons, although substantial differences remain. Overall, our findings show that the muscle activity of a nonadapted biped effectively fulfills the basic mechanical requirements (propulsion and balance) for walking bipedally, but substantial refinements are possible to optimize the efficiency of bipedal locomotion. In the evolutionary context of an expanding reliance on bipedal behaviors, even minor morphological alterations, reducing muscle coactivation, could have faced strong selection pressure, ultimately driving bipedal evolution in hominins.

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A Statistical Approach for Functional Reach-to-Grasp Segmentation Using a Single Inertial Measurement Unit

Authors:
Gregorio Dotti, Marco Caruso, Daniele Fortunato, Marco Knaflitz, Andrea Cereatti and Marco Ghislieri
Journal:
Sensors
DOI:
10.3390/s24186119
Year:
2024
Abstract:

The aim of this contribution is to present a segmentation method for the identification of voluntary movements from inertial data acquired through a single inertial measurement unit placed on the subject’s wrist. Inertial data were recorded from 25 healthy subjects while performing 75 consecutive reach-to-grasp movements. The approach herein presented, called DynAMoS, is based on an adaptive thresholding step on the angular velocity norm, followed by a statistics-based post-processing on the movement duration distribution. Post-processing aims at reducing the number of erroneous transitions in the movement segmentation. We assessed the segmentation quality of this method using a stereophotogrammetric system as the gold standard. Two popular methods already presented in the literature were compared to DynAMoS in terms of the number of movements identified, onset and offset mean absolute errors, and movement duration. Moreover, we analyzed the sub-phase durations of the drinking movement to further characterize the task. The results show that the proposed method performs significantly better than the two state-of-the-art approaches (i.e., percentage of erroneous movements = 3%; onset and offset mean absolute error < 0.08 s), suggesting that DynAMoS could make more effective home monitoring applications for assessing the motion improvements of patients following domicile rehabilitation protocols.

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An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements

Authors:
Gregorio Dotti, Marco Ghislieri, Cristina Castagneri, Valentina Agostini, Marco Knaflitz, Gabriella Balestra and Samanta Rosati
Journal:
IOP Physiological Measurement
DOI:
10.1088/1361-6579/ad814f
Year:
2024
Abstract:

Dynamic muscle activity can be quantitatively and non-invasively investigated during several cyclical movements by acquiring surface electromyographic (sEMG) signals. The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in the clinical practice. To overcome this limitation, specific algorithms are needed to help scientists to easily characterize and assess muscle activation patterns during cyclical movements. In this perspective, CIMAP (Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment muscle activation pattern. The toolbox can be flexibly modified to comply with the necessities of the scientist. CIMAP is addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub (https://github.com/Biolab-PoliTO/CIMAP).

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Foot–Floor Contact Sequences: A Metric for Gait Assessment in Parkinson’s Disease after Deep Brain Stimulation

Authors:
Marco Ghislieri, Valentina Agostini, Laura Rizzi, Chiara Fronda, Marco Knaflitz, Michele Lanotte
Journal:
Sensors
DOI:
10.3390/s24206593
Year:
2024
Abstract:

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is to analyze the changes in the foot–floor contact sequences of Parkinson’s Disease (PD) patients in the year following the implantation of Deep Brain Stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months after subthalamic nucleus DBS neurosurgery (T1), and at 12 months (T2) after subthalamic nucleus DBS neurosurgery. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5 min walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in their UPDRS-III scores from 19.4 ± 1.8 to 10.2 ± 1.0 (T0 vs.T2) (p < 0.001). In straight-line walking, the percentages of atypical cycles of PD on the more affected side were 11.1 ± 1.5% (at T0), 3.1 ± 1.5% (at T1), and 5.1 ± 2.4% (at T2), while in controls it was 3.1 ± 1.3% (p < 0.0005). In turnings, this percentage was 13.7 ± 1.1% (at T0), 7.8 ± 1.1% (at T1), and 10.9 ± 1.8% (at T2), while in controls it was 8.1 ± 1.0% (p < 0.001). Therefore, in straight-line walking, the atypical cycles decreased by 72% at T1, and by 54% at T2 (with respect to baseline), while, in turnings, atypical cycles decreased by 43% at T1, and by 20% at T2. The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

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Balance and Muscle Synergies during a Single-Limb Stance Task in Individuals with Chronic Ankle Instability

Authors:
M. Ghislieri, L. Labanca, M. Mosca, L. Bragonzoni, M. Kanflitz & V. Agostini
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2023.3328933
Year:
2023
Abstract:

The aim of this study was to investigate balance performance and muscle synergies during a Single-Limb Stance (SLS) task in individuals with Chronic Ankle Instability (CAI) and a group of healthy controls. Twenty individuals with CAI and twenty healthy controls were asked to perform a 30-second SLS task in Open-Eyes (OE) and Closed-Eyes (CE) conditions while standing on a force platform with the injured or the dominant limb, respectively. The activation of 13 muscles of the lower limb, hip, and back was recorded by means of surface electromyography. Balance performance was assessed by identifying the number and the duration of SLS epochs, and the Root-Mean-Square (RMS) in Antero-Posterior (AP) and Medio-Lateral (ML) directions of the body-weight normalized ground reaction forces. The optimal number of synergies, weight vectors, and activation coefficients were also analyzed. CAI group showed a higher number and a shorter duration of SLS epochs and augmented ground reaction force RMS in both AP and ML directions compared to controls. Both groups showed an increase in the RMS in AP and ML forces in CE compared to OE. Both groups showed 4 optimal synergies in CE, while controls showed 5 synergies in OE. CAI showed a significantly higher weight of knee flexor muscles in both OE and CE. In conclusion, muscle synergies analysis provided an in–depth knowledge of motor control mechanisms in CAI individuals. They showed worse balance performance, a lower number of muscle synergies in a CE condition and abnormal knee flexor muscle activation compared to healthy controls.

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Muscle synergies in Parkinson’s disease before and after the deep brain stimulation of the bilateral subthalamic nucleus

Authors:
Marco Ghislieri, Michele Lanotte, Marco Knaflitz, Laura Rizzi, and Valentina Agostini
Journal:
Scientific Reports
DOI:
10.1038/s41598-023-34151-6
Year:
2023
Abstract:

The aim of this study is to quantitatively assess motor control changes in Parkinson’s disease (PD) patients after bilateral deep brain stimulation of the subthalamic nucleus (STN-DBS), based on a novel muscle synergy evaluation approach. A group of 20 PD patients evaluated at baseline (before surgery, T0), at 3 months (T1), and at 12 months (T2) after STN-DBS surgery, as well as a group of 20 age-matched healthy control subjects, underwent an instrumented gait analysis, including surface electromyography recordings from 12 muscles. A smaller number of muscle synergies was found in PD patients (4 muscle synergies, at each time point) compared to control subjects (5 muscle synergies). The neuromuscular robustness of PD patients—that at T0 was smaller with respect to controls (PD T0: 69.3 ± 2.2% vs. Controls: 77.6 ± 1.8%, p = 0.004)—increased at T1 (75.8 ± 1.8%), becoming not different from that of controls at T2 (77.5 ± 1.9%). The muscle synergies analysis may offer clinicians new knowledge on the neuromuscular structure underlying PD motor types of behavior and how they can improve after electroceutical STN-DBS therapy.

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Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review

Authors:
M. Ghislieri, L. Gastaldi, S. Pastorelli, S. Tadano, and V. Agostini
Journal:
Sensors
DOI:
10.3390/s19194075
Year:
2019
Abstract:

Wearable sensors are de facto revolutionizing the assessment of standing balance. The aim of this work is to review the state-of-the-art literature that adopts this new posturographic paradigm, i.e., to analyse human postural sway through inertial sensors directly worn on the subject body. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 73 full-text articles, selecting 47 high-quality contributions. A good inter-rater reliability was obtained (Cohen’s kappa = 0.79). This selection of papers was used to summarize the available knowledge on the types of sensors used and their positioning, the data acquisition protocols and the main applications in this field (e.g., “active aging”, biofeedback-based rehabilitation for fall prevention, and the management of Parkinson’s disease and other balance-related pathologies), as well as the most adopted outcome measures. A critical discussion on the validation of wearable systems against gold standards is also presented.

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Automated Assessment of the Quality of Phonocardographic Recordings through Signal-to-Noise Ratio for Home Monitoring Applications

Authors:
N. Giordano, S. Rosati, and M. Knaflitz
Journal:
Sensors
DOI:
10.3390/s21217246
Year:
2021
Abstract:

The signal quality limits the applicability of phonocardiography at the patients’ domicile. This work proposes the signal-to-noise ratio of the recorded signal as its main quality metrics. Moreover, we define the minimum acceptable values of the signal-to-noise ratio that warrantee an accuracy of the derived parameters acceptable in clinics. We considered 25 original heart sounds recordings, which we corrupted by adding noise to decrease their signal-to-noise ratio. We found that a signal-to-noise ratio equal to or higher than 14 dB warrants an uncertainty of the estimate of the valve closure latencies below 1 ms. This accuracy is higher than that required by most clinical applications. We validated the proposed method against a public database, obtaining results comparable to those obtained on our sample population. In conclusion, we defined (a) the signal-to-noise ratio of the phonocardiographic signal as the preferred metric to evaluate its quality and (b) the minimum values of the signal-to-noise ratio required to obtain an uncertainty of the latency of heart sound components compatible with clinical applications. We believe these results are crucial for the development of home monitoring systems aimed at preventing acute episodes of heart failure and that can be safely operated by naïve users.

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Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index

Authors:
S. Rosati, M. Ghislieri, G. Dotti, D. Fortunato, V. Agostini, M.Knaflitz, and G. Balestra
Journal:
Sensors
DOI:
10.3390/s21217186
Year:
2021
Abstract:

Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination; (2) the lack of user-independent tools; (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics

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Long short-term memory (LSTM) recurrent neural network for muscle activity detection

Authors:
M. Ghislieri, G. L. Cerone, M. Knaflitz, & V. Agostini
Journal:
Journal of NeuroEngineering and Rehabilitation
DOI:
10.1186/s12984-021-00945-w
Year:
2021
Abstract:

Background

The accurate temporal analysis of muscle activation is of great interest in many research areas, spanning from neurorobotic systems to the assessment of altered locomotion patterns in orthopedic and neurological patients and the monitoring of their motor rehabilitation. The performance of the existing muscle activity detectors is strongly affected by both the SNR of the surface electromyography (sEMG) signals and the set of features used to detect the activation intervals. This work aims at introducing and validating a powerful approach to detect muscle activation intervals from sEMG signals, based on long short-term memory (LSTM) recurrent neural networks.

Methods

First, the applicability of the proposed LSTM-based muscle activity detector (LSTM-MAD) is studied through simulated sEMG signals, comparing the LSTM-MAD performance against other two widely used approaches, i.e., the standard approach based on Teager–Kaiser Energy Operator (TKEO) and the traditional approach, used in clinical gait analysis, based on a double-threshold statistical detector (Stat). Second, the effect of the Signal-to-Noise Ratio (SNR) on the performance of the LSTM-MAD is assessed considering simulated signals with nine different SNR values. Finally, the newly introduced approach is validated on real sEMG signals, acquired during both physiological and pathological gait. Electromyography recordings from a total of 20 subjects (8 healthy individuals, 6 orthopedic patients, and 6 neurological patients) were included in the analysis.

Results

The proposed algorithm overcomes the main limitations of the other tested approaches and it works directly on sEMG signals, without the need for background-noise and SNR estimation (as in Stat). Results demonstrate that LSTM-MAD outperforms the other approaches, revealing higher values of F1-score (F1-score > 0.91) and Jaccard similarity index (Jaccard > 0.85), and lower values of onset/offset bias (average absolute bias < 6 ms), both on simulated and real sEMG signals. Moreover, the advantages of using the LSTM-MAD algorithm are particularly evident for signals featuring a low to medium SNR.

Conclusions

The presented approach LSTM-MAD revealed excellent performances against TKEO and Stat. The validation carried out both on simulated and real signals, considering normal as well as pathological motor function during locomotion, demonstrated that it can be considered a powerful tool in the accurate and effective recognition/distinction of muscle activity from background noise in sEMG signals.

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Muscle synergies for the control of single-limb stance with and without visual information in young individuals

Authors:
L. Labanca, M. Ghislieri, M. Knaflitz, G. Barone, L. Bragonzoni, V. Agostini & M. G. Benedetti
Journal:
BMC Sports Science, Medicine and Rehabilitation
DOI:
10.1186/s13102-021-00392-z
Year:
2021
Abstract:

Purpose

Single-limb stance is a demanding postural task featuring a high number of daily living and sporting activities. Thus, it is widely used for training and rehabilitation, as well as for balance assessment. Muscle activations around single joints have been previously described, however, it is not known which are the muscle synergies used to control posture and how they change between conditions of normal and lack of visual information.

Methods

Twenty-two healthy young participants were asked to perform a 30 s single-limb stance task in open-eyes and closed-eyes condition while standing on a force platform with the dominant limb. Muscle synergies were extracted from the electromyographical recordings of 13 muscles of the lower limb, hip, and back. The optimal number of synergies, together with the average recruitment level and balance control strategies were analyzed and compared between the open- and the closed-eyes condition.

Results

Four major muscle synergies, two ankle-dominant synergies, one knee-dominant synergy, and one hip/back-dominant synergy were found. No differences between open- and closed-eyes conditions were found for the recruitment level, except for the hip/back synergy, which significantly decreased (p = 0.02) in the closed-eyes compared to the open-eyes condition. A significant increase (p = 0.03) of the ankle balance strategy was found in the closed-eyes compared to the open-eyes condition.

Conclusion

In healthy young individuals, single-limb stance is featured by four major synergies, both in open- and closed-eyes condition. Future studies should investigate muscle synergies in participants with other age groups, as well as pathological conditions.

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Statistical Gait Analysis Based on Surface Electromyography

Authors:
Agostini, V., Ghislieri, M., Rosati, S., Balestra, B., Dotti, G., & Knaflitz, M.
Journal:
Medicine-Based Informatics and Engineering
DOI:
10.1007/978-3-030-87845-0_2
Year:
2021
Abstract:

To help neurologists, physicians, and physical therapists in the management of patients with altered locomotion patterns, it is of the uttermost importance relying on accurate measurements of gait. Gait analysis becomes even more informative if the electrical activity of muscles is recorded, non-invasively, during the dynamic task of walking, through surface electromyography (sEMG) probes. However, sEMG signals must be processed through advanced techniques to obtain reliable results, easily interpretable by healthcare practitioners. Indeed, the study of how muscles are activated during natural walking (in unconstrained environments) is complex for several reasons, including a high stride-to-stride variability, even more pronounced in pathological subjects. On the other hand, it is crucial to provide clinicians with aggregated information relying on validated parameters and easily usable representations that can be effectively included in clinical reports. This chapter is aimed at introducing: (1) Statistical Gait Analysis (SGA) to automatically analyze hundreds of gait cycles collected during a physiological or pathological walk lasting several minutes, (2) the extraction of principal and secondary muscle activations to obtain consistent clinical indexes, (3) the extraction of “muscle synergies” to quantitatively study motor control strategies. Each of these techniques are based on state-of-the-art processing algorithms of the sEMG signal. A brief review of the recent literature published in this field will be presented and discussed.

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Does texting while walking really affect gait in young adults?

Authors:
V. Agostini, F. Lo Fermo, G. Massazza and M. Knaflitz
Journal:
Journal of NeuroEngineering and Rehabilitation
DOI:
10.1186/s12984-015-0079-4
Year:
2015
Abstract:

Background: Texting on a smartphone while walking has become a customary task among young adults. In recent literature many safety concerns on distracted walking have been raised. It is often hypothesized that the allocation of attentional resources toward a secondary task can influence dynamic stability. In the double task of walking and texting it was found that gait speed is reduced, but there is scarce evidence of a modified motor control strategy compromising stability. The aim of this study is twofold: 1) to comprehensively examine the gait modifications occurring when texting while walking, including the study of the lower limb muscle activation patterns, 2) to specifically assess the co-contraction of ankle antagonist muscles. We hypothesized that texting while walking increases co-contractions of ankle antagonist muscles when the body weight is transferred from one lower limb to the other, to improve the distal motor control and joint stabilization.

Methods: From the gait data collected during an instrumented walk lasting 3 min, we calculated the spatio-temporal parameters, the ankle and knee kinematics, the muscle activation patterns of tibialis anterior, gastrocnemius lateralis, peroneus longus, rectus femoris, and lateral hamstrings, and the co-contraction (occurrence and duration) of the ankle antagonist muscles (tibialis anterior and gastrocnemius lateralis), bilaterally.

Results: Young adults showed, overall, small gait modifications that could be mainly ascribable to gait speed reduction and a modified body posture due to phone handling. We found no significant alterations of ankle and knee kinematics and a slightly delayed activation onset of the left gastrocnemius lateralis. However, we found an increased co-contraction of tibialis anterior and gastrocnemius lateralis, especially during mid-stance. Conversely, we found a reduced co-contraction during terminal stance.

Conclusions: Our results suggest that, in young adults, there is an adjustment of the motor control strategy aimed at increasing ankle joint stability in a specific and “critical” phase of the gait cycle, when the body weight is transferred from one leg to the other.

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Instrumented Gait Analysis for an Objective Pre-/Postassessment of Tap Test in Normal Pressure Hydrocephalus

Authors:
V. Agostini, M. Lanotte, M. Carlone, M. Campagnoli, I. Azzolin, R. Scarafia, G. Massazza, M. Knaflitz
Journal:
Archives of Physical Medicine and Rehabilitation
DOI:
10.1016/j.apmr.2015.02.014
Year:
2015
Abstract:

Objective

To present an objective method to evaluate gait improvements after a tap test in idiopathic normal pressure hydrocephalus (INPH).

Design

Retrospective analysis of gait data.

Setting

Public tertiary care center, day hospital. The gait analysis was performed before and 2 to 4 hours after the tap test.

Participants

Participants included patients with INPH (n=60) and age- and sex-matched controls (n=50; used to obtain reference intervals). From an initial referred sample of 79 patients (N=79), we excluded those unable to walk without walking aids (n=9) and those with incomplete (pre-/posttap test) gait data (n=10). Thirteen out of 60 patients were shunted and then reappraised after 6 months.

Interventions

Not applicable.

Main Outcome Measures

Mahalanobis distance from controls, before and after the tap test. Eleven gait parameters were combined in a single quantitative score. Walking velocity was also evaluated because it is frequently used in tap test assessment.

Results

Patients were classified into 2 groups: tap test responders (n=22, 9 of them were shunted) and not suitable for shunt (n=38, 4 of them were shunted). In the tap test responders group, 9 out of 9 patients improved after shunt. In the not suitable for shunt group, 3 out of 4 patients did not improve. Gait velocity increased after the tap test in 53% of responders and in 37% of patients not suitable for shunt.

Conclusions

The new method is applicable to clinical practice and allows for selecting tap test responders in an objective way, quantifying the improvements. Our results suggest that gait velocity alone is not sufficient to reliably assess tap test effects.

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Clinical Process Modelling

Agent-Based Modeling and Simulation of Care Delivery for Patients with Thrombotic and Bleeding Disorders

Authors:
N. Giordano, S. Rosati, F. Valeri, A. Borchiellini, G. Balestra
Journal:
STUDIES IN HEALTH TECHNOLOGY AND INFORMATICS, MIE 2020
DOI:
10.3233/SHTI200358
Year:
2020
Abstract:

The quality of patients care delivery is thought to be strongly affected by the physicians’ workload. In this study we present an Agent-Based model of the processes during a typical working day. We simulated the current scenario and a possible scenario concerning the introduction of a second ambulatory as a potential improvement in the center organization. Our results validated the reliability of the model and showed that the introduction of a second ambulatory averagely reduces the daily physician’ workload.

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An Approach Based on Process Modeling for Implementing a Health Information Technology in Clinical Practice

Authors:
G.M. Zaccaria; S. Rosati; M. Zema; V. Agostini; G. Balestra
Journal:
Journal of Medical Imaging and Health Informatics
DOI:
10.1166/jmihi.2018.2353
Year:
2018
Abstract:

The introduction of a new Health Information Technology (HIT) in a healthcare context is a very complex process. The aim of this study is to propose a completely original approach for the implementation a new HIT in a healthcare facility or department. This novel approach is made of four steps and based on process modeling. The first step is the identification of all the stakeholders involved. The second step consists in performing a detailed description of all clinical and administrative processes that will use the new HIT in order to understand how people, resources and documents interact among them. The third step allows the analysis of the HIT functionalities in order to highlight potential problems or risks that could emerge during its daily usage and guarantee its interoperability with other software. The fourth step concerns the construction of an adoption plan, in order to avoiding sharp transitions. A set of tools were associated to each step to guarantee a correct design and implementation. An application concerning the implementation of a new commercial HIT for Computerized Provider Order Entry (CPOE) in the oncology department of a large Italian hospital is reported as an example of the proposed approach. Furthermore, the user satisfaction about the introduction of the new CPOE in the oncology department was evaluated by means of a set of questionnaires. A positive evaluation of the process emerged from this analysis, confirming the goodness of the proposed approach. Moreover, the questionnaires results showed a high level of user satisfaction.

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Characterization of Physicians Workload in a Reference Center for the Treatment of Thrombotic and Bleeding Disorders

Authors:
S. Rosati; F. Valeri; A. Borchiellini; C. M. Gianfreda; G. Balestra
Journal:
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2019.8856820
Year:
2019
Abstract:

Heavy workloads in healthcare have been often associated to adverse clinical outcomes. To reduce workloads, an optimal scheduling of clinical staff resources is not enough, but particular attention must be payed to work organization and task characteristics. Moreover, interruptions during the clinical practice contribute to increase perceived workloads. In this study we analyzed and characterized the physicians’ workload in an Italian center for the treatment of thrombotic and bleeding disorders. First, all clinical and administrative processes performed in the center were analyzed by means of two process modelling tools. Then, the quantification of the physicians’ workload and the characterization of interruptions during practice were conducted. From our results it emerged that the task that mainly impacts on the workload is ambulatory care (42% of total workload) while interruptions produce a delay of almost 15 minutes per day and mainly occur during visits. Including all activities, the total daily workload per physician was 8 hours on average. In this time breaks were not taken into account. Concluding, from our analysis it is evident that the physicians’ workload in the analyzed center is heavy and interruptions represent a source of delay in the workflow, that impact the physicians’ workload.

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Developing medical device software in compliance with regulations

Authors:
M. Zema; S. Rosati; V. Gioia; M. Knaflitz; G. Balestra
Journal:
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2015.7318614
Year:
2015
Abstract:

In the last decade, the use of information technology (IT) in healthcare has taken a growing role. In fact, the adoption of an increasing number of computer tools has led to several benefits related to the process of patient care and allowed easier access to social and health care resources. At the same time this trend gave rise to new challenges related to the implementation of these new technologies. Software used in healthcare can be classified as medical devices depending on the way they are used and on their functional characteristics. If they are classified as medical devices they must satisfy specific regulations. The aim of this work is to present a software development framework that can allow the production of safe and high quality medical device software and to highlight the correspondence between each software development phase and the appropriate standard and/or regulation.

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Modelling and analysis of four telemedicine Italian experiences

Authors:
S. Rosati; M. Zema; C. Castagneri; F. Marchetti; G. Balestra
Journal:
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2017.8037398
Year:
2017
Abstract:

In the last 10 years the European population aged 65 years and over grew of 2.3%, with Italy having the highest share of elderly persons in the total population. OPLON (OPportunities for active and healthy LONgevity) is a project supported by the Italian Ministry of Education, Universities, and Research aiming to identify and prevent frailty and to improve the life quality of elderly subjects. The main goal of OPLON is to develop a “Care&Cure” model for the management of subjects with different morbidities and co-morbidities, adaptable to the subject’s risk level and to the regional contexts. In this study we analyzed four Italian telemedicine experiences addressed to chronic, geriatric or partially self-sufficient subjects. Each of them was exhaustively described by means of three process modelling tools (synopsis, workflow and swimlane activity diagrams). Starting from this analysis, we defined a general model of tele-monitoring and tele-assistance of frail and pre-frail people with different needs and pathologies. The proposed model was characterized by three macro processes (enrollment, assessment and assistance) and four groups of actors (patient, general practitioner/specialist physician, multidisciplinary team, and healthcare professionals). Combining this model with a detailed analysis of regulations and legislations in force both at local and national level, it will be possible to design the complete and efficient “Care&Cure” model.

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Design of Biomedical Instrumentation

Automated Assessment of the Quality of Phonocardographic Recordings through Signal-to-Noise Ratio for Home Monitoring Applications

Authors:
N. Giordano, S. Rosati, and M. Knaflitz
Journal:
Sensors
DOI:
10.3390/s21217246
Year:
2021
Abstract:

The signal quality limits the applicability of phonocardiography at the patients’ domicile. This work proposes the signal-to-noise ratio of the recorded signal as its main quality metrics. Moreover, we define the minimum acceptable values of the signal-to-noise ratio that warrantee an accuracy of the derived parameters acceptable in clinics. We considered 25 original heart sounds recordings, which we corrupted by adding noise to decrease their signal-to-noise ratio. We found that a signal-to-noise ratio equal to or higher than 14 dB warrants an uncertainty of the estimate of the valve closure latencies below 1 ms. This accuracy is higher than that required by most clinical applications. We validated the proposed method against a public database, obtaining results comparable to those obtained on our sample population. In conclusion, we defined (a) the signal-to-noise ratio of the phonocardiographic signal as the preferred metric to evaluate its quality and (b) the minimum values of the signal-to-noise ratio required to obtain an uncertainty of the latency of heart sound components compatible with clinical applications. We believe these results are crucial for the development of home monitoring systems aimed at preventing acute episodes of heart failure and that can be safely operated by naïve users.

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A wearable device to assess postural sway

Authors:
V. Agostini, E. Aiello, D. Fortunato, M. Knaflitz, and L. Gastaldi
Journal:
2019 IEEE 23rd International Symposium on Consumer Technologies (ISCT)
DOI:
10.1109/ISCE.2019.8901019
Year:
2019
Abstract:

The maintenance of balance in upright stance is traditionally evaluated using heavy and expensive force platforms. The aim of this work is to prove the usefulness of a low-cost wearable sensor (an actigraph) to assess postural sway. We compared the performance of the device to a gold standard force platform. We analyzed measurements of postural sway in four conditions differently challenging the subject: with eyes open or closed, while keeping a small or large base of support. We estimated the main postural parameters (ellipse area, mediolateral and antero-posterior root-mean square, eccentricity, sway path length) considering: 1) acceleration data recorded by the actigraph, and 2) traditional COP data obtained from the force platform. We found that it is possible to clearly distinguish the differences among the postural parameters, obtained in the various balance conditions, also using acceleration data. Our results show that the wearable device allows for obtaining information similar to those achievable by the force platform. This support the use of wearable devices to assess postural balance, in a handy and cheap manner.

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Human Motion Analysis

A comparative study of muscle activity and synergies during walking in baboons and humans

Authors:
Francois Druelle*, Marco Ghislieri*, Pablo Molina-Vila, Brigitte Rimbaud, Valentina Agostini, Gilles Berillon
Journal:
Journal of Human Evolution
DOI:
10.1016/j.jhevol.2024.103513
Year:
2024
Abstract:

Bipedal locomotion was a major functional change during hominin evolution, yet, our understanding of this gradual and complex process remains strongly debated. Based on fossil discoveries, it is possible to address functional hypotheses related to bipedal anatomy, however, motor control remains intangible with this approach. Using comparative models which occasionally walk bipedally has proved to be relevant to shed light on the evolutionary transition toward habitual bipedalism. Here, we explored the organization of the neuromuscular control using surface electromyography (sEMG) for six extrinsic muscles in two baboon individuals when they walk quadrupedally and bipedally on the ground. We compared their muscular coordination to five human subjects walking bipedally. We extracted muscle synergies from the sEMG envelopes using the nonnegative matrix factorization algorithm which allows decomposing the sEMG data in the linear combination of two non-negative matrixes (muscle weight vectors and activation coefficients). We calculated different parameters to estimate the complexity of the sEMG signals, the duration of the activation of the synergies, and the generalizability of the muscle synergy model across species and walking conditions. We found that the motor control strategy is less complex in baboons when they walk bipedally, with an increased muscular activity and muscle coactivation. When comparing the baboon bipedal and quadrupedal pattern of walking to human bipedalism, we observed that the baboon bipedal pattern of walking is closer to human bipedalism for both baboons, although substantial differences remain. Overall, our findings show that the muscle activity of a nonadapted biped effectively fulfills the basic mechanical requirements (propulsion and balance) for walking bipedally, but substantial refinements are possible to optimize the efficiency of bipedal locomotion. In the evolutionary context of an expanding reliance on bipedal behaviors, even minor morphological alterations, reducing muscle coactivation, could have faced strong selection pressure, ultimately driving bipedal evolution in hominins.

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A Statistical Approach for Functional Reach-to-Grasp Segmentation Using a Single Inertial Measurement Unit

Authors:
Gregorio Dotti, Marco Caruso, Daniele Fortunato, Marco Knaflitz, Andrea Cereatti and Marco Ghislieri
Journal:
Sensors
DOI:
10.3390/s24186119
Year:
2024
Abstract:

The aim of this contribution is to present a segmentation method for the identification of voluntary movements from inertial data acquired through a single inertial measurement unit placed on the subject’s wrist. Inertial data were recorded from 25 healthy subjects while performing 75 consecutive reach-to-grasp movements. The approach herein presented, called DynAMoS, is based on an adaptive thresholding step on the angular velocity norm, followed by a statistics-based post-processing on the movement duration distribution. Post-processing aims at reducing the number of erroneous transitions in the movement segmentation. We assessed the segmentation quality of this method using a stereophotogrammetric system as the gold standard. Two popular methods already presented in the literature were compared to DynAMoS in terms of the number of movements identified, onset and offset mean absolute errors, and movement duration. Moreover, we analyzed the sub-phase durations of the drinking movement to further characterize the task. The results show that the proposed method performs significantly better than the two state-of-the-art approaches (i.e., percentage of erroneous movements = 3%; onset and offset mean absolute error < 0.08 s), suggesting that DynAMoS could make more effective home monitoring applications for assessing the motion improvements of patients following domicile rehabilitation protocols.

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An open-source toolbox for enhancing the assessment of muscle activation patterns during cyclical movements

Authors:
Gregorio Dotti, Marco Ghislieri, Cristina Castagneri, Valentina Agostini, Marco Knaflitz, Gabriella Balestra and Samanta Rosati
Journal:
IOP Physiological Measurement
DOI:
10.1088/1361-6579/ad814f
Year:
2024
Abstract:

Dynamic muscle activity can be quantitatively and non-invasively investigated during several cyclical movements by acquiring surface electromyographic (sEMG) signals. The accurate temporal analysis of muscle activations is of great importance in several research areas spanning from the assessment of altered muscle activation patterns in orthopaedic and neurological patients to the monitoring of their motor rehabilitation. Several studies have highlighted the challenge of understanding and interpreting muscle activation patterns due to the high cycle-by-cycle variability of the sEMG data. This makes it difficult to interpret results and to use sEMG signals in the clinical practice. To overcome this limitation, specific algorithms are needed to help scientists to easily characterize and assess muscle activation patterns during cyclical movements. In this perspective, CIMAP (Clustering for the Identification of Muscle Activation Patterns) is an open-source Python toolbox based on agglomerative hierarchical clustering that aims at characterizing muscle activation patterns during cyclical movements by grouping movement cycles showing similar muscle activity. From muscle activation intervals to the graphical representation of the agglomerative hierarchical clustering dendrograms, the proposed toolbox offers a complete analysis framework for enabling the assessment muscle activation pattern. The toolbox can be flexibly modified to comply with the necessities of the scientist. CIMAP is addressed to scientists of any programming skill level working in different research areas such as biomedical engineering, robotics, sports, clinics, biomechanics, and neuroscience. CIMAP is freely available on GitHub (https://github.com/Biolab-PoliTO/CIMAP).

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Foot–Floor Contact Sequences: A Metric for Gait Assessment in Parkinson’s Disease after Deep Brain Stimulation

Authors:
Marco Ghislieri, Valentina Agostini, Laura Rizzi, Chiara Fronda, Marco Knaflitz, Michele Lanotte
Journal:
Sensors
DOI:
10.3390/s24206593
Year:
2024
Abstract:

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is to analyze the changes in the foot–floor contact sequences of Parkinson’s Disease (PD) patients in the year following the implantation of Deep Brain Stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months after subthalamic nucleus DBS neurosurgery (T1), and at 12 months (T2) after subthalamic nucleus DBS neurosurgery. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5 min walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in their UPDRS-III scores from 19.4 ± 1.8 to 10.2 ± 1.0 (T0 vs.T2) (p < 0.001). In straight-line walking, the percentages of atypical cycles of PD on the more affected side were 11.1 ± 1.5% (at T0), 3.1 ± 1.5% (at T1), and 5.1 ± 2.4% (at T2), while in controls it was 3.1 ± 1.3% (p < 0.0005). In turnings, this percentage was 13.7 ± 1.1% (at T0), 7.8 ± 1.1% (at T1), and 10.9 ± 1.8% (at T2), while in controls it was 8.1 ± 1.0% (p < 0.001). Therefore, in straight-line walking, the atypical cycles decreased by 72% at T1, and by 54% at T2 (with respect to baseline), while, in turnings, atypical cycles decreased by 43% at T1, and by 20% at T2. The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

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Balance and Muscle Synergies during a Single-Limb Stance Task in Individuals with Chronic Ankle Instability

Authors:
M. Ghislieri, L. Labanca, M. Mosca, L. Bragonzoni, M. Kanflitz & V. Agostini
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2023.3328933
Year:
2023
Abstract:

The aim of this study was to investigate balance performance and muscle synergies during a Single-Limb Stance (SLS) task in individuals with Chronic Ankle Instability (CAI) and a group of healthy controls. Twenty individuals with CAI and twenty healthy controls were asked to perform a 30-second SLS task in Open-Eyes (OE) and Closed-Eyes (CE) conditions while standing on a force platform with the injured or the dominant limb, respectively. The activation of 13 muscles of the lower limb, hip, and back was recorded by means of surface electromyography. Balance performance was assessed by identifying the number and the duration of SLS epochs, and the Root-Mean-Square (RMS) in Antero-Posterior (AP) and Medio-Lateral (ML) directions of the body-weight normalized ground reaction forces. The optimal number of synergies, weight vectors, and activation coefficients were also analyzed. CAI group showed a higher number and a shorter duration of SLS epochs and augmented ground reaction force RMS in both AP and ML directions compared to controls. Both groups showed an increase in the RMS in AP and ML forces in CE compared to OE. Both groups showed 4 optimal synergies in CE, while controls showed 5 synergies in OE. CAI showed a significantly higher weight of knee flexor muscles in both OE and CE. In conclusion, muscle synergies analysis provided an in–depth knowledge of motor control mechanisms in CAI individuals. They showed worse balance performance, a lower number of muscle synergies in a CE condition and abnormal knee flexor muscle activation compared to healthy controls.

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Muscle synergies in Parkinson’s disease before and after the deep brain stimulation of the bilateral subthalamic nucleus

Authors:
Marco Ghislieri, Michele Lanotte, Marco Knaflitz, Laura Rizzi, and Valentina Agostini
Journal:
Scientific Reports
DOI:
10.1038/s41598-023-34151-6
Year:
2023
Abstract:

The aim of this study is to quantitatively assess motor control changes in Parkinson’s disease (PD) patients after bilateral deep brain stimulation of the subthalamic nucleus (STN-DBS), based on a novel muscle synergy evaluation approach. A group of 20 PD patients evaluated at baseline (before surgery, T0), at 3 months (T1), and at 12 months (T2) after STN-DBS surgery, as well as a group of 20 age-matched healthy control subjects, underwent an instrumented gait analysis, including surface electromyography recordings from 12 muscles. A smaller number of muscle synergies was found in PD patients (4 muscle synergies, at each time point) compared to control subjects (5 muscle synergies). The neuromuscular robustness of PD patients—that at T0 was smaller with respect to controls (PD T0: 69.3 ± 2.2% vs. Controls: 77.6 ± 1.8%, p = 0.004)—increased at T1 (75.8 ± 1.8%), becoming not different from that of controls at T2 (77.5 ± 1.9%). The muscle synergies analysis may offer clinicians new knowledge on the neuromuscular structure underlying PD motor types of behavior and how they can improve after electroceutical STN-DBS therapy.

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Wearable Inertial Sensors to Assess Standing Balance: A Systematic Review

Authors:
M. Ghislieri, L. Gastaldi, S. Pastorelli, S. Tadano, and V. Agostini
Journal:
Sensors
DOI:
10.3390/s19194075
Year:
2019
Abstract:

Wearable sensors are de facto revolutionizing the assessment of standing balance. The aim of this work is to review the state-of-the-art literature that adopts this new posturographic paradigm, i.e., to analyse human postural sway through inertial sensors directly worn on the subject body. After a systematic search on PubMed and Scopus databases, two raters evaluated the quality of 73 full-text articles, selecting 47 high-quality contributions. A good inter-rater reliability was obtained (Cohen’s kappa = 0.79). This selection of papers was used to summarize the available knowledge on the types of sensors used and their positioning, the data acquisition protocols and the main applications in this field (e.g., “active aging”, biofeedback-based rehabilitation for fall prevention, and the management of Parkinson’s disease and other balance-related pathologies), as well as the most adopted outcome measures. A critical discussion on the validation of wearable systems against gold standards is also presented.

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An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking

Authors:
R. Ballarini, M. Ghislieri, M. Knaflitz and V. Agostini
Journal:
Sensors
DOI:
10.3390/s21103311
Year:
2021
Abstract:

In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds

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Atypical Gait Cycles in Parkinson’s Disease

Authors:
M. Ghislieri, V. Agostini, L. Rizzi, M. Knaflitz, and M. Lanotte
Journal:
Sensors
DOI:
10.3390/s21155079
Year:
2021
Abstract:

It is important to find objective biomarkers for evaluating gait in Parkinson’s Disease (PD), especially related to the foot and lower leg segments. Foot-switch signals, analyzed through Statistical Gait Analysis (SGA), allow the foot-floor contact sequence to be characterized during a walking session lasting five-minutes, which includes turnings. Gait parameters were compared between 20 PD patients and 20 age-matched controls. PDs showed similar straight-line speed, cadence, and double-support compared to controls, as well as typical gait-phase durations, except for a small decrease in the flat-foot contact duration (−4% of the gait cycle, p = 0.04). However, they showed a significant increase in atypical gait cycles (+42%, p = 0.006), during both walking straight and turning. A forefoot strike, instead of a “normal” heel strike, characterized the large majority of PD’s atypical cycles, whose total percentage was 25.4% on the most-affected and 15.5% on the least-affected side. Moreover, we found a strong correlation between the atypical cycles and the motor clinical score UPDRS-III (r = 0.91, p = 0.002), in the subset of PD patients showing an abnormal number of atypical cycles, while we found a moderate correlation (r = 0.60, p = 0.005), considering the whole PD population. Atypical cycles have proved to be a valid biomarker to quantify subtle gait dysfunctions in PD patients

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Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index

Authors:
S. Rosati, M. Ghislieri, G. Dotti, D. Fortunato, V. Agostini, M.Knaflitz, and G. Balestra
Journal:
Sensors
DOI:
10.3390/s21217186
Year:
2021
Abstract:

Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination; (2) the lack of user-independent tools; (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics

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Long short-term memory (LSTM) recurrent neural network for muscle activity detection

Authors:
M. Ghislieri, G. L. Cerone, M. Knaflitz, & V. Agostini
Journal:
Journal of NeuroEngineering and Rehabilitation
DOI:
10.1186/s12984-021-00945-w
Year:
2021
Abstract:

Background

The accurate temporal analysis of muscle activation is of great interest in many research areas, spanning from neurorobotic systems to the assessment of altered locomotion patterns in orthopedic and neurological patients and the monitoring of their motor rehabilitation. The performance of the existing muscle activity detectors is strongly affected by both the SNR of the surface electromyography (sEMG) signals and the set of features used to detect the activation intervals. This work aims at introducing and validating a powerful approach to detect muscle activation intervals from sEMG signals, based on long short-term memory (LSTM) recurrent neural networks.

Methods

First, the applicability of the proposed LSTM-based muscle activity detector (LSTM-MAD) is studied through simulated sEMG signals, comparing the LSTM-MAD performance against other two widely used approaches, i.e., the standard approach based on Teager–Kaiser Energy Operator (TKEO) and the traditional approach, used in clinical gait analysis, based on a double-threshold statistical detector (Stat). Second, the effect of the Signal-to-Noise Ratio (SNR) on the performance of the LSTM-MAD is assessed considering simulated signals with nine different SNR values. Finally, the newly introduced approach is validated on real sEMG signals, acquired during both physiological and pathological gait. Electromyography recordings from a total of 20 subjects (8 healthy individuals, 6 orthopedic patients, and 6 neurological patients) were included in the analysis.

Results

The proposed algorithm overcomes the main limitations of the other tested approaches and it works directly on sEMG signals, without the need for background-noise and SNR estimation (as in Stat). Results demonstrate that LSTM-MAD outperforms the other approaches, revealing higher values of F1-score (F1-score > 0.91) and Jaccard similarity index (Jaccard > 0.85), and lower values of onset/offset bias (average absolute bias < 6 ms), both on simulated and real sEMG signals. Moreover, the advantages of using the LSTM-MAD algorithm are particularly evident for signals featuring a low to medium SNR.

Conclusions

The presented approach LSTM-MAD revealed excellent performances against TKEO and Stat. The validation carried out both on simulated and real signals, considering normal as well as pathological motor function during locomotion, demonstrated that it can be considered a powerful tool in the accurate and effective recognition/distinction of muscle activity from background noise in sEMG signals.

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Muscle activations during functional tasks in individuals with chronic ankle instability: a systematic review of electromyographical studies

Authors:
L. Labanca, M. Mosca, M. Ghislieri, V. Agostini, M. Knaflitz, & M. G. Benedetti
Journal:
Gait & Posture
DOI:
10.1016/j.gaitpost.2021.09.182
Year:
2021
Abstract:

Background

It has been reported that individuals with chronic ankle instability (CAI) show motor control abnormalities. The study of muscle activations by means of surface electromyography (sEMG) plays a key role in understanding some of the features of movement abnormalities.

Research question

Do common sEMG activation abnormalities and strategies exists across different functional movements?

Methods

Literature review was conducted on PubMed, Web-of-Science and Cochrane databases. Studies published between 2000 and 2020 that assessed muscle activations by means of sEMG during any type of functional task in individuals with CAI, and used healthy individuals as controls, were included. Methodological quality was assessed using the modified Downs&Black checklist. Since the methodologies of different studies were heterogeneous, no meta-analysis was conducted.

Results

A total of 63 articles investigating muscle activations during gait, running, responses to perturbations, landing and hopping, cutting and turning; single-limb stance, star excursion balance task, forward lunges, ball-kicking, y-balance test and single-limb squatting were considered. Individuals with CAI showed a delayed activation of the peroneus longus in response to sudden inversion perturbations, in transitions between double- and single-limb stance, and in landing on unstable surfaces. Apparently, while walking on ground there are no differences between CAI and controls, walking on a treadmill increases the variability of muscles activations, probably as a “safety strategy” to avoid ankle inversion. An abnormal activation of the tibialis anterior was observed during a number of tasks. Finally, hip/spine muscles were activated before ankle muscles in CAI compared to controls.

Conclusion

Though the methodology of the studies herein considered is heterogeneous, this review shows that the peroneal and tibialis anterior muscles have an abnormal activation in CAI individuals. These individuals also show a proximal muscle activation strategy during the performance of balance challenging tasks. Future studies should investigate whole-body muscle activation abnormalities in CAI individuals.

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Muscle synergies for the control of single-limb stance with and without visual information in young individuals

Authors:
L. Labanca, M. Ghislieri, M. Knaflitz, G. Barone, L. Bragonzoni, V. Agostini & M. G. Benedetti
Journal:
BMC Sports Science, Medicine and Rehabilitation
DOI:
10.1186/s13102-021-00392-z
Year:
2021
Abstract:

Purpose

Single-limb stance is a demanding postural task featuring a high number of daily living and sporting activities. Thus, it is widely used for training and rehabilitation, as well as for balance assessment. Muscle activations around single joints have been previously described, however, it is not known which are the muscle synergies used to control posture and how they change between conditions of normal and lack of visual information.

Methods

Twenty-two healthy young participants were asked to perform a 30 s single-limb stance task in open-eyes and closed-eyes condition while standing on a force platform with the dominant limb. Muscle synergies were extracted from the electromyographical recordings of 13 muscles of the lower limb, hip, and back. The optimal number of synergies, together with the average recruitment level and balance control strategies were analyzed and compared between the open- and the closed-eyes condition.

Results

Four major muscle synergies, two ankle-dominant synergies, one knee-dominant synergy, and one hip/back-dominant synergy were found. No differences between open- and closed-eyes conditions were found for the recruitment level, except for the hip/back synergy, which significantly decreased (p = 0.02) in the closed-eyes compared to the open-eyes condition. A significant increase (p = 0.03) of the ankle balance strategy was found in the closed-eyes compared to the open-eyes condition.

Conclusion

In healthy young individuals, single-limb stance is featured by four major synergies, both in open- and closed-eyes condition. Future studies should investigate muscle synergies in participants with other age groups, as well as pathological conditions.

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Statistical Gait Analysis Based on Surface Electromyography

Authors:
Agostini, V., Ghislieri, M., Rosati, S., Balestra, B., Dotti, G., & Knaflitz, M.
Journal:
Medicine-Based Informatics and Engineering
DOI:
10.1007/978-3-030-87845-0_2
Year:
2021
Abstract:

To help neurologists, physicians, and physical therapists in the management of patients with altered locomotion patterns, it is of the uttermost importance relying on accurate measurements of gait. Gait analysis becomes even more informative if the electrical activity of muscles is recorded, non-invasively, during the dynamic task of walking, through surface electromyography (sEMG) probes. However, sEMG signals must be processed through advanced techniques to obtain reliable results, easily interpretable by healthcare practitioners. Indeed, the study of how muscles are activated during natural walking (in unconstrained environments) is complex for several reasons, including a high stride-to-stride variability, even more pronounced in pathological subjects. On the other hand, it is crucial to provide clinicians with aggregated information relying on validated parameters and easily usable representations that can be effectively included in clinical reports. This chapter is aimed at introducing: (1) Statistical Gait Analysis (SGA) to automatically analyze hundreds of gait cycles collected during a physiological or pathological walk lasting several minutes, (2) the extraction of principal and secondary muscle activations to obtain consistent clinical indexes, (3) the extraction of “muscle synergies” to quantitatively study motor control strategies. Each of these techniques are based on state-of-the-art processing algorithms of the sEMG signal. A brief review of the recent literature published in this field will be presented and discussed.

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Muscle synergies extracted using principal activations: improvement of robustness and interpretability

Authors:
M. Ghislieri, V. Agostini, and M. Knaflitz
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2020.2965179
Year:
2020
Abstract:

The muscle synergy theory has been widely used to assess the modular organization of the central nervous system (CNS) during human locomotion. The pre-processing approach applied to the surface electromyographic (sEMG) signals influences the extraction of muscle synergies. The aim of this contribution is to assess the improvements in muscle synergy extraction obtained by using an innovative pre-processing approach. We evaluate the improvement in terms of the possible variation in the number of muscle synergies, of the intra-subject consistency, of the robustness, and of the interpretability of the results. The pre-processing approach presented in this paper is based on the extraction of the muscle principal activations (muscle activations strictly necessary to accomplish a specific biomechanical task) from the original sEMG signals, to then obtain muscle synergies using principal activations only. The results herein presented show that the application of this novel approach for the extraction of the muscle synergies provides a more robust and easily interpretable description of the modular organization of the CNS with respect to the standard pre-processing approach.

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Muscle Synergy Assessment During Single-Leg Stance

Authors:
M. Ghislieri, M. Knaflitz, L. Labanca, G. Barone, L. Bragonzoni, M. G. Benedetti, and V. Agostini
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2020.3030847
Year:
2020
Abstract:

In the study of muscle synergies during the maintenance of single-leg stance there are several methodological issues that must be taken into account before muscle synergy extraction. In particular, it is important to distinguish between epochs of surface electromyography (sEMG) signals corresponding to “well-balanced” and “unbalanced” single-leg stance, since different motor control strategies could be used to maintain balance. The aim of this work is to present and define a robust procedure to distinguish between “well-balanced” and “unbalanced” single-leg stance to be chosen as input for the algorithm used to extract muscle synergies. Our results demonstrate that the proposed approach for the selection of sEMG epochs relative to “well-balanced” and “unbalanced” single-leg stance is robust with respect to the selection of the segmentation threshold, revealing a high consistency in the number of muscle synergies and high similarity among the weight vectors (correlation values range from 0.75 to 0.97). Moreover, differences in terms of average recruitment levels and balance control strategies were detected, suggesting a slightly different modular organization between “well-balanced” and “unbalanced” single-leg stance. In conclusion, this approach can be successfully used as a pre-processing step before muscle synergy extraction, allowing for a better assessment of motor control strategies during the single-leg stance task.

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How to improve robustness in muscle synergy extraction

Authors:
M. Ghislieri, V. Agostini, and M. Knaflitz
Journal:
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2019.8856438
Year:
2019
Abstract:

The muscle synergy theory was widely used in literature to assess the modular organization of the central nervous system (CNS) during human locomotion. The extraction of muscle synergies may be strongly influenced by the preprocessing techniques applied to surface electromyographic (sEMG) signals. The aim of this contribution is to assess the robustness improvement in muscle synergy extraction obtained using an innovative pre-processing technique with respect to the standard procedure. The new pre-processing technique that we propose is based on the extraction of principal muscle activation intervals (necessary to accomplish a specific biomechanical task during gait) from the original sEMG signals, discarding the secondary muscle activation intervals (activations that occur only in some strides with auxiliary functions). Results suggest that the extraction of the principal activation intervals from sEMG provide a more consistent and stable description of the modular organization of the CNS with respect to the standard pre-processing procedure.

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The Effect of Signal-to-Noise Ratio on Muscle Synergy Extraction

Authors:
M. Ghislieri, V. Agostini, and M. Knaflitz
Journal:
2018 IEEE Life Sciences Conference (LSC)
DOI:
10.1109/LSC.2018.8572075
Year:
2018
Abstract:

The modular organization of the central nervous system (CNS) during motor tasks was widely assessed by means of muscle synergies. The aim of this work was to assess the impact of the Signal-to-Noise Ratio (SNR) on muscle synergies extracted from synthetic surface electromyographic (sEMG) signals that simulate the muscle activity of the lower limb during walking. To evaluate the effect of the SNR, the similarity between the weights vectors and the activation coefficients extracted from real sEMG signals and from simulated sEMG signals at different values of SNR was computed. Results reveal that muscle synergy extraction is strongly dependent upon the quality of the sEMG signals simulated.

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The role of central vision in posture: Postural sway adaptations in Stargardt patients

Authors:
V. Agostini, A. Sbrollini, C. Cavallini, A. Busso, G. Pignata and M. Knaflitz
Journal:
Gait & Posture
DOI:
10.1016/j.gaitpost.2015.10.003
Year:
2016
Abstract:

The role of central and peripheral vision in the maintenance of upright stance is debated in literature. Stargardt disease causes visual deficits affecting the central field, but leaving unaltered a patient’s peripheral vision. Hence, the study of this rare pathology gives the opportunity to selectively investigate the role of central vision in posture. Postural sway in quiet stance was analyzed in 10 Stargardt patients and 10 control subjects, in three different conditions: (1) eyes closed, (2) eyes open, gazing at a fixed target, and (3) eyes open, tracking a moving target. Stargardt patients outperformed controls in the condition with eyes closed, showing a reduced root mean square (RMS) of the medio-lateral COP displacement, while their performance was not significantly different from controls in the antero-posterior direction. There were no significant differences between patients and controls in open eyes conditions. These results suggest that Stargardt patients adapted to a different visual-somatosensory integration, relying less on vision, especially in the medio-lateral direction. Hence, the central vision seems to affect mostly the medio-lateral direction of postural sway. This finding supports the plausibility of the “functional sensitivity hypothesis”, that assigns complementary roles to central and peripheral vision in the control of posture.

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Does texting while walking really affect gait in young adults?

Authors:
V. Agostini, F. Lo Fermo, G. Massazza and M. Knaflitz
Journal:
Journal of NeuroEngineering and Rehabilitation
DOI:
10.1186/s12984-015-0079-4
Year:
2015
Abstract:

Background: Texting on a smartphone while walking has become a customary task among young adults. In recent literature many safety concerns on distracted walking have been raised. It is often hypothesized that the allocation of attentional resources toward a secondary task can influence dynamic stability. In the double task of walking and texting it was found that gait speed is reduced, but there is scarce evidence of a modified motor control strategy compromising stability. The aim of this study is twofold: 1) to comprehensively examine the gait modifications occurring when texting while walking, including the study of the lower limb muscle activation patterns, 2) to specifically assess the co-contraction of ankle antagonist muscles. We hypothesized that texting while walking increases co-contractions of ankle antagonist muscles when the body weight is transferred from one lower limb to the other, to improve the distal motor control and joint stabilization.

Methods: From the gait data collected during an instrumented walk lasting 3 min, we calculated the spatio-temporal parameters, the ankle and knee kinematics, the muscle activation patterns of tibialis anterior, gastrocnemius lateralis, peroneus longus, rectus femoris, and lateral hamstrings, and the co-contraction (occurrence and duration) of the ankle antagonist muscles (tibialis anterior and gastrocnemius lateralis), bilaterally.

Results: Young adults showed, overall, small gait modifications that could be mainly ascribable to gait speed reduction and a modified body posture due to phone handling. We found no significant alterations of ankle and knee kinematics and a slightly delayed activation onset of the left gastrocnemius lateralis. However, we found an increased co-contraction of tibialis anterior and gastrocnemius lateralis, especially during mid-stance. Conversely, we found a reduced co-contraction during terminal stance.

Conclusions: Our results suggest that, in young adults, there is an adjustment of the motor control strategy aimed at increasing ankle joint stability in a specific and “critical” phase of the gait cycle, when the body weight is transferred from one leg to the other.

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Instrumented Gait Analysis for an Objective Pre-/Postassessment of Tap Test in Normal Pressure Hydrocephalus

Authors:
V. Agostini, M. Lanotte, M. Carlone, M. Campagnoli, I. Azzolin, R. Scarafia, G. Massazza, M. Knaflitz
Journal:
Archives of Physical Medicine and Rehabilitation
DOI:
10.1016/j.apmr.2015.02.014
Year:
2015
Abstract:

Objective

To present an objective method to evaluate gait improvements after a tap test in idiopathic normal pressure hydrocephalus (INPH).

Design

Retrospective analysis of gait data.

Setting

Public tertiary care center, day hospital. The gait analysis was performed before and 2 to 4 hours after the tap test.

Participants

Participants included patients with INPH (n=60) and age- and sex-matched controls (n=50; used to obtain reference intervals). From an initial referred sample of 79 patients (N=79), we excluded those unable to walk without walking aids (n=9) and those with incomplete (pre-/posttap test) gait data (n=10). Thirteen out of 60 patients were shunted and then reappraised after 6 months.

Interventions

Not applicable.

Main Outcome Measures

Mahalanobis distance from controls, before and after the tap test. Eleven gait parameters were combined in a single quantitative score. Walking velocity was also evaluated because it is frequently used in tap test assessment.

Results

Patients were classified into 2 groups: tap test responders (n=22, 9 of them were shunted) and not suitable for shunt (n=38, 4 of them were shunted). In the tap test responders group, 9 out of 9 patients improved after shunt. In the not suitable for shunt group, 3 out of 4 patients did not improve. Gait velocity increased after the tap test in 53% of responders and in 37% of patients not suitable for shunt.

Conclusions

The new method is applicable to clinical practice and allows for selecting tap test responders in an objective way, quantifying the improvements. Our results suggest that gait velocity alone is not sufficient to reliably assess tap test effects.

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Postural sway in volleyball players

Authors:
V. Agostini, E. Chiaramello, L. Canavese, C. Bredariol and M. Knaflitz
Journal:
Human Movement Science
DOI:
10.1016/j.humov.2013.01.002
Year:
2013
Abstract:

The aim of this work was to analyze the postural sway of volleyball players in bipedal quiet stance. The center of pressure (CoP) was measured in 46 athletes and 42 non-athlete controls. Each subject was tested in 10 different conditions, 5 with their eyes open and 5 with their eyes closed. Volleyball players showed greater CoP ellipses, suggesting a different model of sensory integration in their postural stability. A multivariate approach to data analysis demonstrated that the postural sway of the two groups was different when the subjects kept their eyes open, but it was not with visual deprivation. This could partially be explained by the better ‘dynamic’ visual acuity of athletes, since possible (‘static’) refractive errors were corrected for both groups. Furthermore, we expected that national players, engaged in more intensive training programs, were more different from controls than regional ones, and that defensive players, whose role requires the quickest reaction times, were more different from controls than hitters. Our results confirmed these hypothesis. The protocol presented might be useful to assess the efficacy of intensive sport training programs and/or to select elite players with an aptitude for a specific playing position.

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Postural control after traumatic brain injury in patients with neuro-ophthalmic deficits

Authors:
V. Agostini, E. Chiaramello, C. Bredariol, C. Cavallini and M. Knaflitz
Journal:
Gait & Posture
DOI:
10.1016/j.gaitpost.2011.05.008
Year:
2011
Abstract:

Postural instability is a common and devastating consequence of traumatic brain injury (TBI). The majority of TBI patients also suffer from neuro-ophthalmic deficits that can be an important contributing element to their sensation of vertigo and dizziness. Static posturography aims at the objective evaluation of patient balance impairment, but is usually affected by large inter- and intra-subject variability. Here we propose a protocol based on 10 randomized trials stimulating in different ways the visual and vestibular systems. Due to its completeness, our protocol highlights the specific residual difficulties of each patient in the various conditions. In this way, it was possible to evidence significant balance abnormalities in TBI patients with respect to controls. Moreover, by means of a multivariate analysis we were able to discriminate different levels of residual neuro-ophthalmic impairment.

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Medical Device Software

An Approach Based on Process Modeling for Implementing a Health Information Technology in Clinical Practice

Authors:
G.M. Zaccaria; S. Rosati; M. Zema; V. Agostini; G. Balestra
Journal:
Journal of Medical Imaging and Health Informatics
DOI:
10.1166/jmihi.2018.2353
Year:
2018
Abstract:

The introduction of a new Health Information Technology (HIT) in a healthcare context is a very complex process. The aim of this study is to propose a completely original approach for the implementation a new HIT in a healthcare facility or department. This novel approach is made of four steps and based on process modeling. The first step is the identification of all the stakeholders involved. The second step consists in performing a detailed description of all clinical and administrative processes that will use the new HIT in order to understand how people, resources and documents interact among them. The third step allows the analysis of the HIT functionalities in order to highlight potential problems or risks that could emerge during its daily usage and guarantee its interoperability with other software. The fourth step concerns the construction of an adoption plan, in order to avoiding sharp transitions. A set of tools were associated to each step to guarantee a correct design and implementation. An application concerning the implementation of a new commercial HIT for Computerized Provider Order Entry (CPOE) in the oncology department of a large Italian hospital is reported as an example of the proposed approach. Furthermore, the user satisfaction about the introduction of the new CPOE in the oncology department was evaluated by means of a set of questionnaires. A positive evaluation of the process emerged from this analysis, confirming the goodness of the proposed approach. Moreover, the questionnaires results showed a high level of user satisfaction.

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Developing medical device software in compliance with regulations

Authors:
M. Zema; S. Rosati; V. Gioia; M. Knaflitz; G. Balestra
Journal:
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2015.7318614
Year:
2015
Abstract:

In the last decade, the use of information technology (IT) in healthcare has taken a growing role. In fact, the adoption of an increasing number of computer tools has led to several benefits related to the process of patient care and allowed easier access to social and health care resources. At the same time this trend gave rise to new challenges related to the implementation of these new technologies. Software used in healthcare can be classified as medical devices depending on the way they are used and on their functional characteristics. If they are classified as medical devices they must satisfy specific regulations. The aim of this work is to present a software development framework that can allow the production of safe and high quality medical device software and to highlight the correspondence between each software development phase and the appropriate standard and/or regulation.

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Modelling and analysis of four telemedicine Italian experiences

Authors:
S. Rosati; M. Zema; C. Castagneri; F. Marchetti; G. Balestra
Journal:
2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2017.8037398
Year:
2017
Abstract:

In the last 10 years the European population aged 65 years and over grew of 2.3%, with Italy having the highest share of elderly persons in the total population. OPLON (OPportunities for active and healthy LONgevity) is a project supported by the Italian Ministry of Education, Universities, and Research aiming to identify and prevent frailty and to improve the life quality of elderly subjects. The main goal of OPLON is to develop a “Care&Cure” model for the management of subjects with different morbidities and co-morbidities, adaptable to the subject’s risk level and to the regional contexts. In this study we analyzed four Italian telemedicine experiences addressed to chronic, geriatric or partially self-sufficient subjects. Each of them was exhaustively described by means of three process modelling tools (synopsis, workflow and swimlane activity diagrams). Starting from this analysis, we defined a general model of tele-monitoring and tele-assistance of frail and pre-frail people with different needs and pathologies. The proposed model was characterized by three macro processes (enrollment, assessment and assistance) and four groups of actors (patient, general practitioner/specialist physician, multidisciplinary team, and healthcare professionals). Combining this model with a detailed analysis of regulations and legislations in force both at local and national level, it will be possible to design the complete and efficient “Care&Cure” model.

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Medical Image Analysis Using Innovative Intelligent Systems

Carotid Ultrasound Boundary Study (CUBS): Technical considerations on an open multi-center analysis of computerized measurement systems for intima-media thickness measurement on common carotid artery longitudinal B-mode ultrasound scans

Authors:
K. M. Meiburger, F. Marzola, G. Zahnd, F. Faita, C. P. Loizou, N. Lainé, C. Carvalho, D. A. Steinman, L. Gibello, R.M. Bruno, R. Clarenbach, M. Francesconi, A. N. Nicolaides, H. Liebgott, A. Campilho, R. Ghotbi, E. Kyriacou, N. Navab, M. Griffin, A. G. Pa
Journal:
Computers in Biology and Medicine
DOI:
10.1016/j.compbiomed.2022.105333
Year:
2022
Abstract:

After publishing an in-depth study that analyzed the ability of computerized methods to assist or replace human experts in obtaining carotid intima-media thickness (CIMT) measurements leading to correct therapeutic decisions, here the same consortium joined to present technical outlooks on computerized CIMT measurement systems and provide considerations for the community regarding the development and comparison of these methods, including considerations to encourage the standardization of computerized CIMT measurements and results presentation. A multi-center database of 500 images was collected, upon which three manual segmentations and seven computerized methods were employed to measure the CIMT, including traditional methods based on dynamic programmingdeformable models, the first order absolute moment, anisotropic Gaussian derivative filters and deep learning-based image processing approaches based on U-Net convolutional neural networks. An inter- and intra-analyst variability analysis was conducted and segmentation results were analyzed by dividing the database based on carotid morphology, image signal-to-noise ratio, and research center. The computerized methods obtained CIMT absolute bias results that were comparable with studies in literature and they generally were similar and often better than the observed inter- and intra-analyst variability. Several computerized methods showed promising segmentation results, including one deep learning method (CIMT absolute bias = 106 ± 89 μm vs. 160 ± 140 μm intra-analyst variability) and three other traditional image processing methods (CIMT absolute bias = 139 ± 119 μm, 143 ± 118 μm and 139 ± 136 μm). The entire database used has been made publicly available for the community to facilitate future studies and to encourage an open comparison and technical analysis (https://doi.org/10.17632/m7ndn58sv6.1).

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Integration of Deep Learning and Active Shape Models for More Accurate Prostate Segmentation in 3D MR Images

Authors:
Massimo Salvi, Bruno De Santi, Bianca Pop, Martino Bosco, Valentina Giannini, Daniele Regge, Filippo Molinari, and Kristen M. Meiburger
Journal:
Journal of Imaging
DOI:
https://doi.org/10.3390/jimaging8050133
Year:
2022
Abstract:

Magnetic resonance imaging (MRI) has a growing role in the clinical workup of prostate cancer. However, manual three-dimensional (3D) segmentation of the prostate is a laborious and time-consuming task. In this scenario, the use of automated algorithms for prostate segmentation allows us to bypass the huge workload of physicians. In this work, we propose a fully automated hybrid approach for prostate gland segmentation in MR images using an initial segmentation of prostate volumes using a custom-made 3D deep network (VNet-T2), followed by refinement using an Active Shape Model (ASM). While the deep network focuses on three-dimensional spatial coherence of the shape, the ASM relies on local image information and this joint effort allows for improved segmentation of the organ contours. Our method is developed and tested on a dataset composed of T2-weighted (T2w) MRI prostatic volumes of 60 male patients. In the test set, the proposed method shows excellent segmentation performance, achieving a mean dice score and Hausdorff distance of 0.851 and 7.55 mm, respectively. In the future, this algorithm could serve as an enabling technology for the development of computer-aided systems for prostate cancer characterization in MR imaging.

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Automatic Segmentation and Classification Methods Using Optical Coherence Tomography Angiography (OCTA): A Review and Handbook

Authors:
Kristen M. Meiburger, Massimo Salvi, Giulia Rotunno, Wolfgang Drexler and Mengyang Liu
Journal:
Applied Sciences
DOI:
10.3390/app11209734
Year:
2021
Abstract:
Optical coherence tomography angiography (OCTA) is a promising technology for the non-invasive imaging of vasculature. Many studies in literature present automated algorithms to quantify OCTA images, but there is a lack of a review on the most common methods and their comparison considering multiple clinical applications (e.g., ophthalmology and dermatology). Here, we aim to provide readers with a useful review and handbook for automatic segmentation and classification methods using OCTA images, presenting a comparison of techniques found in the literature based on the adopted segmentation or classification method and on the clinical application. Another goal of this study is to provide insight into the direction of research in automated OCTA image analysis, especially in the current era of deep learning.
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Carotid Ultrasound Boundary Study (CUBS): An Open Multicenter Analysis of Computerized Intima–Media Thickness Measurement Systems and Their Clinical Impact

Authors:
Kristen M.Meiburger, Guillaume Zahnd, Francesco Faita, Christos P. Loizou, Catarina Carvalho, David A. Steinman, Lorenzo Gibello, Rosa Maria Bruno, Francesco Marzola, Ricarda Clarenbach, Martina Francesconi, Andrew N. Nicolaides, Aurelio Campilho, Reza Gh
Journal:
Ultrasound in Medicine and Biology
DOI:
10.1016/j.ultrasmedbio.2021.03.022
Year:
2021
Abstract:

Common carotid intima–media thickness (CIMT) is a commonly used marker for atherosclerosis and is often computed in carotid ultrasound images. An analysis of different computerized techniques for CIMT measurement and their clinical impacts on the same patient data set is lacking. Here we compared and assessed five computerized CIMT algorithms against three expert analysts’ manual measurements on a data set of 1088 patients from two centers. Inter- and intra-observer variability was assessed, and the computerized CIMT values were compared with those manually obtained. The CIMT measurements were used to assess the correlation with clinical parameters, cardiovascular event prediction through a generalized linear model and the Kaplan–Meier hazard ratio. CIMT measurements obtained with a skilled analyst’s segmentation and the computerized segmentation were comparable in statistical analyses, suggesting they can be used interchangeably for CIMT quantification and clinical outcome investigation. To facilitate future studies, the entire data set used is made publicly available for the community at http://dx.doi.org/10.17632/fpv535fss7.1.

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Deep learning segmentation of transverse musculoskeletal ultrasound images for neuromuscular disease assessment

Authors:
Francesco Marzola, Nens van Alfen, Jonne Doorduin, Kristen M. Meiburger
Journal:
Computers in Biology and Medicine
DOI:
10.1016/j.compbiomed.2021.104623
Year:
2021
Abstract:

Ultrasound imaging is a patient-friendly and robust technique for studying physiological and pathological muscles. An automatic deep learning (DL) system for the analysis of ultrasound images could be useful to support an expert operator, allowing the study of large datasets requiring less human interaction. The purpose of this study is to present a deep learning algorithm for the cross-sectional area (CSA) segmentation in transverse musculoskeletal ultrasound images, providing a quantitative grayscale analysis which is useful for studying muscles, and to validate the results in a large dataset. The dataset included 3917 images of biceps brachii, tibialis anterior and gastrocnemius medialis acquired on 1283 subjects (mean age 50 ± 21 years, 729 male). The algorithm was based on multiple deep-learning architectures, and its performance was compared to a manual expert segmentation. We compared the mean grayscale value inside the automatic and manual CSA using Bland-Altman plots and a correlation analysis. Classification in healthy and abnormal muscles between automatic and manual segmentation were compared using the grayscale value z-scores. In the test set, a Precision of 0.88 ± 0.12 and a Recall of 0.92 ± 0.09 was achieved. The network segmentation performance was slightly less in abnormal muscles, without a loss of discrimination between healthy and abnormal muscle images. Bland-Altman plots showed no clear trend in the error distribution and the two readings have a 0.99 Pearson’s correlation coefficient (p < 0.001, test set). The ICC(A, 1) calculated between the z-score readings was 0.99. The algorithm achieves robust CSA segmentation performance and gives mean grayscale level information comparable to a manual operator. This could provide a helpful tool for clinicians in neuromuscular disease diagnosis and follow-up. The entire dataset and code are made available for the research community.

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A Convolutional Neural Network based system for Colorectal cancer segmentation on MRI images

Authors:
J. Panic; A. Defeudis; S. Mazzetti; S. Rosati; G. Giannetto; L. Vassallo; D. Regge; G. Balestra; V. Giannini
Journal:
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
DOI:
10.1109/EMBC44109.2020.9175804
Year:
2020
Abstract:

The aim of the study is to present a new Convolutional Neural Network (CNN) based system for the automatic segmentation of the colorectal cancer. The algorithm implemented consists of several steps: a pre-processing to normalize and highlights the tumoral area, the classification based on CNNs, and a post-processing aimed at reducing false positive elements. The classification is performed using three CNNs: each of them classifies the same regions of interest acquired from three different MR sequences. The final segmentation mask is obtained by a majority voting. Performances were evaluated using a semi-automatic segmentation revised by an experienced radiologist as reference standard. The system obtained Dice Similarity Coefficient (DSC) of 0.60, Precision (Pr) of 0.76 and Recall (Re) of 0.55 on the testing set. After applying the leave-one-out validation, we obtained a median DSC=0.58, Pr=0.74, Re=0.54. The promising results obtained by this system, if validated on a larger dataset, could strongly improve personalized medicine.

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Radiomics predicts response of individual HER2-amplified colorectal cancer liver metastases in patients treated with HER2-targeted therapy

Authors:
V. Giannini, S. Rosati, A. Defeudis, G. Balestra, L. Vassallo, G. Cappello, S. Mazzetti, C. De Mattia, F. Rizzetto, A. Torresin, A. Sartore-Bianchi, S. Siena, A. Vanzulli, F. Leone, V. Zagonel, S. Marson
Journal:
International journal of cancer
DOI:
10.1002/ijc.33271
Year:
2020
Abstract:

The aim of our study was to develop and validate a machine learning algorithm to predict response of individual HER2-amplified colorectal cancer liver metastases (lmCRC) undergoing dual HER2-targeted therapy. Twenty-four radiomics features were extracted after 3D manual segmentation of 141 lmCRC on pretreatment portal CT scans of a cohort including 38 HER2-amplified patients; feature selection was then performed using genetic algorithms. lmCRC were classified as nonresponders (R-), if their largest diameter increased more than 10% at a CT scan performed after 3 months of treatment, responders (R+) otherwise. Sensitivity, specificity, negative (NPV) and positive (PPV) predictive values in correctly classifying individual lesion and overall patient response were assessed on a training dataset and then validated on a second dataset using a Gaussian naïve Bayesian classifier. Per-lesion sensitivity, specificity, NPV and PPV were 89%, 85%, 93%, 78% and 90%, 42%, 73%, 71% respectively in the testing and validation datasets. Per-patient sensitivity and specificity were 92% and 86%. Heterogeneous response was observed in 9 of 38 patients (24%). Five of nine patients were carriers of nonresponder lesions correctly classified as such by our radiomics signature, including four of seven harboring only one nonresponder lesion. The developed method has been proven effective in predicting behavior of individual metastases to targeted treatment in a cohort of HER2 amplified patients. The model accurately detects responder lesions and identifies nonresponder lesions in patients with heterogeneous response, potentially paving the way to multimodal treatment in selected patients. Further validation will be needed to confirm our findings.

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Radiomics for Identification of Active Bone Marrow from CT: An Exploratory Study

Authors:
S. Rosati; G. Balestra; P. Franco; C. Fiandra; F. Arcadipane; P. Silvetti; U. Ricardi; E. Gallio
Journal:
2018 IEEE Life Sciences Conference (LSC)
DOI:
10.1109/LSC.2018.8572154
Year:
2018
Abstract:

The radiation dose received by the pelvic Bone Marrow (BM) is a predictive factor for Hematologic Toxicity (HT) occurrence in the treatment of anal cancer. For this reason it is important to avoid BM during radiotherapy. In particular, the standard strategy in these cases consists in the identification of hematopoietically active BM (actBM), i.e. the part of BM in charge of blood cells generation, on 18 FDG-PET, FLT-PET or MRI, but no approached have been developed for identifying actBM from CT images. This exploratory study aims to use radiomics for detecting actBM on CT sequences. Our approach is based on the extraction of 36 first-order and texture (second-order) features for each CT slice. These features are used as input of a Decision Tree (DT) classifier able to discriminate between active and inactive BM regions on the images. This method was applied to five patients affected by carcinoma of the anal canal and the obtained actBM segmentation was compared with the standard actBM identification from 18 FDG-PET (reference standard, RS). Our results show that actBM identification in lumbosacral and iliac structures using radiomics overlaps the RS for more than 75% in 4 out of 5 patients.

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Neuroengineering

A comparative study of muscle activity and synergies during walking in baboons and humans

Authors:
Francois Druelle*, Marco Ghislieri*, Pablo Molina-Vila, Brigitte Rimbaud, Valentina Agostini, Gilles Berillon
Journal:
Journal of Human Evolution
DOI:
10.1016/j.jhevol.2024.103513
Year:
2024
Abstract:

Bipedal locomotion was a major functional change during hominin evolution, yet, our understanding of this gradual and complex process remains strongly debated. Based on fossil discoveries, it is possible to address functional hypotheses related to bipedal anatomy, however, motor control remains intangible with this approach. Using comparative models which occasionally walk bipedally has proved to be relevant to shed light on the evolutionary transition toward habitual bipedalism. Here, we explored the organization of the neuromuscular control using surface electromyography (sEMG) for six extrinsic muscles in two baboon individuals when they walk quadrupedally and bipedally on the ground. We compared their muscular coordination to five human subjects walking bipedally. We extracted muscle synergies from the sEMG envelopes using the nonnegative matrix factorization algorithm which allows decomposing the sEMG data in the linear combination of two non-negative matrixes (muscle weight vectors and activation coefficients). We calculated different parameters to estimate the complexity of the sEMG signals, the duration of the activation of the synergies, and the generalizability of the muscle synergy model across species and walking conditions. We found that the motor control strategy is less complex in baboons when they walk bipedally, with an increased muscular activity and muscle coactivation. When comparing the baboon bipedal and quadrupedal pattern of walking to human bipedalism, we observed that the baboon bipedal pattern of walking is closer to human bipedalism for both baboons, although substantial differences remain. Overall, our findings show that the muscle activity of a nonadapted biped effectively fulfills the basic mechanical requirements (propulsion and balance) for walking bipedally, but substantial refinements are possible to optimize the efficiency of bipedal locomotion. In the evolutionary context of an expanding reliance on bipedal behaviors, even minor morphological alterations, reducing muscle coactivation, could have faced strong selection pressure, ultimately driving bipedal evolution in hominins.

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An Algorithm for Choosing the Optimal Number of Muscle Synergies during Walking

Authors:
R. Ballarini, M. Ghislieri, M. Knaflitz and V. Agostini
Journal:
Sensors
DOI:
10.3390/s21103311
Year:
2021
Abstract:

In motor control studies, the 90% thresholding of variance accounted for (VAF) is the classical way of selecting the number of muscle synergies expressed during a motor task. However, the adoption of an arbitrary cut-off has evident drawbacks. The aim of this work is to describe and validate an algorithm for choosing the optimal number of muscle synergies (ChoOSyn), which can overcome the limitations of VAF-based methods. The proposed algorithm is built considering the following principles: (1) muscle synergies should be highly consistent during the various motor task epochs (i.e., remaining stable in time), (2) muscle synergies should constitute a base with low intra-level similarity (i.e., to obtain information-rich synergies, avoiding redundancy). The algorithm performances were evaluated against traditional approaches (threshold-VAF at 90% and 95%, elbow-VAF and plateau-VAF), using both a simulated dataset and a real dataset of 20 subjects. The performance evaluation was carried out by analyzing muscle synergies extracted from surface electromyographic (sEMG) signals collected during walking tasks lasting 5 min. On the simulated dataset, ChoOSyn showed comparable performances compared to VAF-based methods, while, in the real dataset, it clearly outperformed the other methods, in terms of the fraction of correct classifications, mean error (ME), and root mean square error (RMSE). The proposed approach may be beneficial to standardize the selection of the number of muscle synergies between different research laboratories, independent of arbitrary thresholds

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Atypical Gait Cycles in Parkinson’s Disease

Authors:
M. Ghislieri, V. Agostini, L. Rizzi, M. Knaflitz, and M. Lanotte
Journal:
Sensors
DOI:
10.3390/s21155079
Year:
2021
Abstract:

It is important to find objective biomarkers for evaluating gait in Parkinson’s Disease (PD), especially related to the foot and lower leg segments. Foot-switch signals, analyzed through Statistical Gait Analysis (SGA), allow the foot-floor contact sequence to be characterized during a walking session lasting five-minutes, which includes turnings. Gait parameters were compared between 20 PD patients and 20 age-matched controls. PDs showed similar straight-line speed, cadence, and double-support compared to controls, as well as typical gait-phase durations, except for a small decrease in the flat-foot contact duration (−4% of the gait cycle, p = 0.04). However, they showed a significant increase in atypical gait cycles (+42%, p = 0.006), during both walking straight and turning. A forefoot strike, instead of a “normal” heel strike, characterized the large majority of PD’s atypical cycles, whose total percentage was 25.4% on the most-affected and 15.5% on the least-affected side. Moreover, we found a strong correlation between the atypical cycles and the motor clinical score UPDRS-III (r = 0.91, p = 0.002), in the subset of PD patients showing an abnormal number of atypical cycles, while we found a moderate correlation (r = 0.60, p = 0.005), considering the whole PD population. Atypical cycles have proved to be a valid biomarker to quantify subtle gait dysfunctions in PD patients

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Balance and Muscle Synergies during a Single-Limb Stance Task in Individuals with Chronic Ankle Instability

Authors:
M. Ghislieri, L. Labanca, M. Mosca, L. Bragonzoni, M. Kanflitz & V. Agostini
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2023.3328933
Year:
2023
Abstract:

The aim of this study was to investigate balance performance and muscle synergies during a Single-Limb Stance (SLS) task in individuals with Chronic Ankle Instability (CAI) and a group of healthy controls. Twenty individuals with CAI and twenty healthy controls were asked to perform a 30-second SLS task in Open-Eyes (OE) and Closed-Eyes (CE) conditions while standing on a force platform with the injured or the dominant limb, respectively. The activation of 13 muscles of the lower limb, hip, and back was recorded by means of surface electromyography. Balance performance was assessed by identifying the number and the duration of SLS epochs, and the Root-Mean-Square (RMS) in Antero-Posterior (AP) and Medio-Lateral (ML) directions of the body-weight normalized ground reaction forces. The optimal number of synergies, weight vectors, and activation coefficients were also analyzed. CAI group showed a higher number and a shorter duration of SLS epochs and augmented ground reaction force RMS in both AP and ML directions compared to controls. Both groups showed an increase in the RMS in AP and ML forces in CE compared to OE. Both groups showed 4 optimal synergies in CE, while controls showed 5 synergies in OE. CAI showed a significantly higher weight of knee flexor muscles in both OE and CE. In conclusion, muscle synergies analysis provided an in–depth knowledge of motor control mechanisms in CAI individuals. They showed worse balance performance, a lower number of muscle synergies in a CE condition and abnormal knee flexor muscle activation compared to healthy controls.

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Foot–Floor Contact Sequences: A Metric for Gait Assessment in Parkinson’s Disease after Deep Brain Stimulation

Authors:
Marco Ghislieri, Valentina Agostini, Laura Rizzi, Chiara Fronda, Marco Knaflitz, Michele Lanotte
Journal:
Sensors
DOI:
10.3390/s24206593
Year:
2024
Abstract:

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is to analyze the changes in the foot–floor contact sequences of Parkinson’s Disease (PD) patients in the year following the implantation of Deep Brain Stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months after subthalamic nucleus DBS neurosurgery (T1), and at 12 months (T2) after subthalamic nucleus DBS neurosurgery. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5 min walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in their UPDRS-III scores from 19.4 ± 1.8 to 10.2 ± 1.0 (T0 vs.T2) (p < 0.001). In straight-line walking, the percentages of atypical cycles of PD on the more affected side were 11.1 ± 1.5% (at T0), 3.1 ± 1.5% (at T1), and 5.1 ± 2.4% (at T2), while in controls it was 3.1 ± 1.3% (p < 0.0005). In turnings, this percentage was 13.7 ± 1.1% (at T0), 7.8 ± 1.1% (at T1), and 10.9 ± 1.8% (at T2), while in controls it was 8.1 ± 1.0% (p < 0.001). Therefore, in straight-line walking, the atypical cycles decreased by 72% at T1, and by 54% at T2 (with respect to baseline), while, in turnings, atypical cycles decreased by 43% at T1, and by 20% at T2. The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

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How to improve robustness in muscle synergy extraction

Authors:
M. Ghislieri, V. Agostini, and M. Knaflitz
Journal:
2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
DOI:
10.1109/EMBC.2019.8856438
Year:
2019
Abstract:

The muscle synergy theory was widely used in literature to assess the modular organization of the central nervous system (CNS) during human locomotion. The extraction of muscle synergies may be strongly influenced by the preprocessing techniques applied to surface electromyographic (sEMG) signals. The aim of this contribution is to assess the robustness improvement in muscle synergy extraction obtained using an innovative pre-processing technique with respect to the standard procedure. The new pre-processing technique that we propose is based on the extraction of principal muscle activation intervals (necessary to accomplish a specific biomechanical task during gait) from the original sEMG signals, discarding the secondary muscle activation intervals (activations that occur only in some strides with auxiliary functions). Results suggest that the extraction of the principal activation intervals from sEMG provide a more consistent and stable description of the modular organization of the CNS with respect to the standard pre-processing procedure.

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Muscle activations during functional tasks in individuals with chronic ankle instability: a systematic review of electromyographical studies

Authors:
L. Labanca, M. Mosca, M. Ghislieri, V. Agostini, M. Knaflitz, & M. G. Benedetti
Journal:
Gait & Posture
DOI:
10.1016/j.gaitpost.2021.09.182
Year:
2021
Abstract:

Background

It has been reported that individuals with chronic ankle instability (CAI) show motor control abnormalities. The study of muscle activations by means of surface electromyography (sEMG) plays a key role in understanding some of the features of movement abnormalities.

Research question

Do common sEMG activation abnormalities and strategies exists across different functional movements?

Methods

Literature review was conducted on PubMed, Web-of-Science and Cochrane databases. Studies published between 2000 and 2020 that assessed muscle activations by means of sEMG during any type of functional task in individuals with CAI, and used healthy individuals as controls, were included. Methodological quality was assessed using the modified Downs&Black checklist. Since the methodologies of different studies were heterogeneous, no meta-analysis was conducted.

Results

A total of 63 articles investigating muscle activations during gait, running, responses to perturbations, landing and hopping, cutting and turning; single-limb stance, star excursion balance task, forward lunges, ball-kicking, y-balance test and single-limb squatting were considered. Individuals with CAI showed a delayed activation of the peroneus longus in response to sudden inversion perturbations, in transitions between double- and single-limb stance, and in landing on unstable surfaces. Apparently, while walking on ground there are no differences between CAI and controls, walking on a treadmill increases the variability of muscles activations, probably as a “safety strategy” to avoid ankle inversion. An abnormal activation of the tibialis anterior was observed during a number of tasks. Finally, hip/spine muscles were activated before ankle muscles in CAI compared to controls.

Conclusion

Though the methodology of the studies herein considered is heterogeneous, this review shows that the peroneal and tibialis anterior muscles have an abnormal activation in CAI individuals. These individuals also show a proximal muscle activation strategy during the performance of balance challenging tasks. Future studies should investigate whole-body muscle activation abnormalities in CAI individuals.

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Muscle synergies extracted using principal activations: improvement of robustness and interpretability

Authors:
M. Ghislieri, V. Agostini, and M. Knaflitz
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2020.2965179
Year:
2020
Abstract:

The muscle synergy theory has been widely used to assess the modular organization of the central nervous system (CNS) during human locomotion. The pre-processing approach applied to the surface electromyographic (sEMG) signals influences the extraction of muscle synergies. The aim of this contribution is to assess the improvements in muscle synergy extraction obtained by using an innovative pre-processing approach. We evaluate the improvement in terms of the possible variation in the number of muscle synergies, of the intra-subject consistency, of the robustness, and of the interpretability of the results. The pre-processing approach presented in this paper is based on the extraction of the muscle principal activations (muscle activations strictly necessary to accomplish a specific biomechanical task) from the original sEMG signals, to then obtain muscle synergies using principal activations only. The results herein presented show that the application of this novel approach for the extraction of the muscle synergies provides a more robust and easily interpretable description of the modular organization of the CNS with respect to the standard pre-processing approach.

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Muscle synergies for the control of single-limb stance with and without visual information in young individuals

Authors:
L. Labanca, M. Ghislieri, M. Knaflitz, G. Barone, L. Bragonzoni, V. Agostini & M. G. Benedetti
Journal:
BMC Sports Science, Medicine and Rehabilitation
DOI:
10.1186/s13102-021-00392-z
Year:
2021
Abstract:

Purpose

Single-limb stance is a demanding postural task featuring a high number of daily living and sporting activities. Thus, it is widely used for training and rehabilitation, as well as for balance assessment. Muscle activations around single joints have been previously described, however, it is not known which are the muscle synergies used to control posture and how they change between conditions of normal and lack of visual information.

Methods

Twenty-two healthy young participants were asked to perform a 30 s single-limb stance task in open-eyes and closed-eyes condition while standing on a force platform with the dominant limb. Muscle synergies were extracted from the electromyographical recordings of 13 muscles of the lower limb, hip, and back. The optimal number of synergies, together with the average recruitment level and balance control strategies were analyzed and compared between the open- and the closed-eyes condition.

Results

Four major muscle synergies, two ankle-dominant synergies, one knee-dominant synergy, and one hip/back-dominant synergy were found. No differences between open- and closed-eyes conditions were found for the recruitment level, except for the hip/back synergy, which significantly decreased (p = 0.02) in the closed-eyes compared to the open-eyes condition. A significant increase (p = 0.03) of the ankle balance strategy was found in the closed-eyes compared to the open-eyes condition.

Conclusion

In healthy young individuals, single-limb stance is featured by four major synergies, both in open- and closed-eyes condition. Future studies should investigate muscle synergies in participants with other age groups, as well as pathological conditions.

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Muscle synergies in Parkinson’s disease before and after the deep brain stimulation of the bilateral subthalamic nucleus

Authors:
Marco Ghislieri, Michele Lanotte, Marco Knaflitz, Laura Rizzi, and Valentina Agostini
Journal:
Scientific Reports
DOI:
10.1038/s41598-023-34151-6
Year:
2023
Abstract:

The aim of this study is to quantitatively assess motor control changes in Parkinson’s disease (PD) patients after bilateral deep brain stimulation of the subthalamic nucleus (STN-DBS), based on a novel muscle synergy evaluation approach. A group of 20 PD patients evaluated at baseline (before surgery, T0), at 3 months (T1), and at 12 months (T2) after STN-DBS surgery, as well as a group of 20 age-matched healthy control subjects, underwent an instrumented gait analysis, including surface electromyography recordings from 12 muscles. A smaller number of muscle synergies was found in PD patients (4 muscle synergies, at each time point) compared to control subjects (5 muscle synergies). The neuromuscular robustness of PD patients—that at T0 was smaller with respect to controls (PD T0: 69.3 ± 2.2% vs. Controls: 77.6 ± 1.8%, p = 0.004)—increased at T1 (75.8 ± 1.8%), becoming not different from that of controls at T2 (77.5 ± 1.9%). The muscle synergies analysis may offer clinicians new knowledge on the neuromuscular structure underlying PD motor types of behavior and how they can improve after electroceutical STN-DBS therapy.

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Muscle Synergy Assessment During Single-Leg Stance

Authors:
M. Ghislieri, M. Knaflitz, L. Labanca, G. Barone, L. Bragonzoni, M. G. Benedetti, and V. Agostini
Journal:
IEEE Transactions on Neural Systems and Rehabilitation Engineering
DOI:
10.1109/TNSRE.2020.3030847
Year:
2020
Abstract:

In the study of muscle synergies during the maintenance of single-leg stance there are several methodological issues that must be taken into account before muscle synergy extraction. In particular, it is important to distinguish between epochs of surface electromyography (sEMG) signals corresponding to “well-balanced” and “unbalanced” single-leg stance, since different motor control strategies could be used to maintain balance. The aim of this work is to present and define a robust procedure to distinguish between “well-balanced” and “unbalanced” single-leg stance to be chosen as input for the algorithm used to extract muscle synergies. Our results demonstrate that the proposed approach for the selection of sEMG epochs relative to “well-balanced” and “unbalanced” single-leg stance is robust with respect to the selection of the segmentation threshold, revealing a high consistency in the number of muscle synergies and high similarity among the weight vectors (correlation values range from 0.75 to 0.97). Moreover, differences in terms of average recruitment levels and balance control strategies were detected, suggesting a slightly different modular organization between “well-balanced” and “unbalanced” single-leg stance. In conclusion, this approach can be successfully used as a pre-processing step before muscle synergy extraction, allowing for a better assessment of motor control strategies during the single-leg stance task.

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Postural control after traumatic brain injury in patients with neuro-ophthalmic deficits

Authors:
V. Agostini, E. Chiaramello, C. Bredariol, C. Cavallini and M. Knaflitz
Journal:
Gait & Posture
DOI:
10.1016/j.gaitpost.2011.05.008
Year:
2011
Abstract:

Postural instability is a common and devastating consequence of traumatic brain injury (TBI). The majority of TBI patients also suffer from neuro-ophthalmic deficits that can be an important contributing element to their sensation of vertigo and dizziness. Static posturography aims at the objective evaluation of patient balance impairment, but is usually affected by large inter- and intra-subject variability. Here we propose a protocol based on 10 randomized trials stimulating in different ways the visual and vestibular systems. Due to its completeness, our protocol highlights the specific residual difficulties of each patient in the various conditions. In this way, it was possible to evidence significant balance abnormalities in TBI patients with respect to controls. Moreover, by means of a multivariate analysis we were able to discriminate different levels of residual neuro-ophthalmic impairment.

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Postural sway in volleyball players

Authors:
V. Agostini, E. Chiaramello, L. Canavese, C. Bredariol and M. Knaflitz
Journal:
Human Movement Science
DOI:
10.1016/j.humov.2013.01.002
Year:
2013
Abstract:

The aim of this work was to analyze the postural sway of volleyball players in bipedal quiet stance. The center of pressure (CoP) was measured in 46 athletes and 42 non-athlete controls. Each subject was tested in 10 different conditions, 5 with their eyes open and 5 with their eyes closed. Volleyball players showed greater CoP ellipses, suggesting a different model of sensory integration in their postural stability. A multivariate approach to data analysis demonstrated that the postural sway of the two groups was different when the subjects kept their eyes open, but it was not with visual deprivation. This could partially be explained by the better ‘dynamic’ visual acuity of athletes, since possible (‘static’) refractive errors were corrected for both groups. Furthermore, we expected that national players, engaged in more intensive training programs, were more different from controls than regional ones, and that defensive players, whose role requires the quickest reaction times, were more different from controls than hitters. Our results confirmed these hypothesis. The protocol presented might be useful to assess the efficacy of intensive sport training programs and/or to select elite players with an aptitude for a specific playing position.

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The Effect of Signal-to-Noise Ratio on Muscle Synergy Extraction

Authors:
M. Ghislieri, V. Agostini, and M. Knaflitz
Journal:
2018 IEEE Life Sciences Conference (LSC)
DOI:
10.1109/LSC.2018.8572075
Year:
2018
Abstract:

The modular organization of the central nervous system (CNS) during motor tasks was widely assessed by means of muscle synergies. The aim of this work was to assess the impact of the Signal-to-Noise Ratio (SNR) on muscle synergies extracted from synthetic surface electromyographic (sEMG) signals that simulate the muscle activity of the lower limb during walking. To evaluate the effect of the SNR, the similarity between the weights vectors and the activation coefficients extracted from real sEMG signals and from simulated sEMG signals at different values of SNR was computed. Results reveal that muscle synergy extraction is strongly dependent upon the quality of the sEMG signals simulated.

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The role of central vision in posture: Postural sway adaptations in Stargardt patients

Authors:
V. Agostini, A. Sbrollini, C. Cavallini, A. Busso, G. Pignata and M. Knaflitz
Journal:
Gait & Posture
DOI:
10.1016/j.gaitpost.2015.10.003
Year:
2016
Abstract:

The role of central and peripheral vision in the maintenance of upright stance is debated in literature. Stargardt disease causes visual deficits affecting the central field, but leaving unaltered a patient’s peripheral vision. Hence, the study of this rare pathology gives the opportunity to selectively investigate the role of central vision in posture. Postural sway in quiet stance was analyzed in 10 Stargardt patients and 10 control subjects, in three different conditions: (1) eyes closed, (2) eyes open, gazing at a fixed target, and (3) eyes open, tracking a moving target. Stargardt patients outperformed controls in the condition with eyes closed, showing a reduced root mean square (RMS) of the medio-lateral COP displacement, while their performance was not significantly different from controls in the antero-posterior direction. There were no significant differences between patients and controls in open eyes conditions. These results suggest that Stargardt patients adapted to a different visual-somatosensory integration, relying less on vision, especially in the medio-lateral direction. Hence, the central vision seems to affect mostly the medio-lateral direction of postural sway. This finding supports the plausibility of the “functional sensitivity hypothesis”, that assigns complementary roles to central and peripheral vision in the control of posture.

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Telemedicine

Automated Assessment of the Quality of Phonocardographic Recordings through Signal-to-Noise Ratio for Home Monitoring Applications

Authors:
N. Giordano, S. Rosati, and M. Knaflitz
Journal:
Sensors
DOI:
10.3390/s21217246
Year:
2021
Abstract:

The signal quality limits the applicability of phonocardiography at the patients’ domicile. This work proposes the signal-to-noise ratio of the recorded signal as its main quality metrics. Moreover, we define the minimum acceptable values of the signal-to-noise ratio that warrantee an accuracy of the derived parameters acceptable in clinics. We considered 25 original heart sounds recordings, which we corrupted by adding noise to decrease their signal-to-noise ratio. We found that a signal-to-noise ratio equal to or higher than 14 dB warrants an uncertainty of the estimate of the valve closure latencies below 1 ms. This accuracy is higher than that required by most clinical applications. We validated the proposed method against a public database, obtaining results comparable to those obtained on our sample population. In conclusion, we defined (a) the signal-to-noise ratio of the phonocardiographic signal as the preferred metric to evaluate its quality and (b) the minimum values of the signal-to-noise ratio required to obtain an uncertainty of the latency of heart sound components compatible with clinical applications. We believe these results are crucial for the development of home monitoring systems aimed at preventing acute episodes of heart failure and that can be safely operated by naïve users.

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A wearable device to assess postural sway

Authors:
V. Agostini, E. Aiello, D. Fortunato, M. Knaflitz, and L. Gastaldi
Journal:
2019 IEEE 23rd International Symposium on Consumer Technologies (ISCT)
DOI:
10.1109/ISCE.2019.8901019
Year:
2019
Abstract:

The maintenance of balance in upright stance is traditionally evaluated using heavy and expensive force platforms. The aim of this work is to prove the usefulness of a low-cost wearable sensor (an actigraph) to assess postural sway. We compared the performance of the device to a gold standard force platform. We analyzed measurements of postural sway in four conditions differently challenging the subject: with eyes open or closed, while keeping a small or large base of support. We estimated the main postural parameters (ellipse area, mediolateral and antero-posterior root-mean square, eccentricity, sway path length) considering: 1) acceleration data recorded by the actigraph, and 2) traditional COP data obtained from the force platform. We found that it is possible to clearly distinguish the differences among the postural parameters, obtained in the various balance conditions, also using acceleration data. Our results show that the wearable device allows for obtaining information similar to those achievable by the force platform. This support the use of wearable devices to assess postural balance, in a handy and cheap manner.

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