Edoardo Ferraro
Multi-channel integration and analysis of an sEMG-based hand gestures recognition systems for rehabilitation applications.
Rel. Danilo Demarchi, Fabio Rossi, Andrea Prestia. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2024
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Abstract
Hand rehabilitation represents a significant priority for individuals with tetraplegia and stroke survivors, given the debilitating impacts of these conditions that persist in 45% of cases after 18 months. However, current rehabilitation practices, e.g. repetitive Transcranial Magnetic Stimulation (rTMS), show limited evidence of their effectiveness. Therefore, the need for new approaches, such as using Functional Electrical Stimulation (FES) systems, emerges. This active rehabilitation technique uses low-intensity electrical pulses to stimulate skeletal muscles, acting on the nervous system by promoting new synaptic connections. The purpose of the thesis is the development of an event-driven sEMG-based system for real-time FES control, aimed at recovering hand functionalities.
The project focused on identifying the muscles required for hand motor control, defining the integration of the devices into the acquisition system, and their placement
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