Biomedical Signal and Data Processing

The recent advances in modern signal processing techniques have improved the accuracy and reliability of medical diagnoses. The most recent trends in data-based diagnostic tools include three principal keywords: big-data, multichannel analysis and radiomics. The main goal is the ability of processing larger and more heterogeneous information, which is extracted from high-dimensional digital data, to solve more and more complex diagnostic problems.

Our research group is focused on the development of new theoretical frameworks and innovative algorithms applied to biomedical signals, motivated by the concept that the analyzed signals contain information that reflects underlying pathophysiology and that these relationships can be revealed via quantitative signal analysis.

EEG signal decomposition in sleep analysis

Brief Description: Sleep quality can be compromised by sleep-related disorders such as sleep apnea, depression, insomnia or narcolepsy and the chronic restriction has negative consequences both on the health of individual and on public security. The development of new techn ...read more...

Innovative techniques for ultrasound beamforming

Brief Description: Ultrasound imaging can be effective for analysing pathological and normal tissues, by studying both the structure and texture in B-mode images. The output B-mode image is influenced by several technical aspects during acquisition, such as the probe freque ...read more...

Statistical gait analysis

Brief Description: Gait analysis is widely used in clinics to study walking abnormalities for surgery planning, definition of therapeutic and rehabilitation protocols, and objective evaluation of clinical outcomes. Among the principal applications of clinical gait ...read more...