A wide range of different research activities is carried out to study the human brain and, more generally, the Central Nervous System (CNS), with applications to neurorehabilitation, and the assessment of electroceutical therapies (e.g., Deep Brain Stimulation in Parkinson’s disease patients).

From the development of algorithms to control Brain Computer Interfaces (BCIs) to the design and validation of digital biomarkers for the evaluation of the motor control in neurological patients, the group has a solid experience in the acquisition and processing of CNS signals, including electroencephalography (EEG), electromyography (EMG), and Near-Infrared Spectroscopy (NIRS). Artificial Intelligence (AI) techniques are adopted to cope with the complexities of neurorehabilitation challenges.

Human behavioral states such as stress, meditation, and sleep stages can be thoroughly analyzed, and neuro-feedback can be provided during breathing or mental exercises. In addition, how the brain controls movements can be investigated non-invasively, thanks to the reconstruction of the neural commands expressed during a motor task (examples of applications: ergonomics, workload assessment, gait Holter, postural balance analysis, sports gesture analysis, and exoskeletons control). Furthermore, the design, implementation, and validation of “dual task” protocols allows for evaluating the performance of subjects synchronously involved in motor and cognitive tasks, to assess possible modifications of their attentional resources.

Multisensory integration in balance control

Brief Description: Balance control is a complex motor skill, which involves the integration of many types of sensory information (sight, vestibular system and proprioception). Postural control can be modified by sensory input alterations consequent to a pathology: vision ...read more...