Development of algorithms for hand movements classification based on optical fiber force myography signals

Resumo

Force myography (FMG) is the mechanical counterpart of the surface electromyography, providing a low-cost and straightforward alternative for tracking the hand movements in applications related to rehabilitation and robotics. This project proposes the development of a modularized and scalable algorithm for classification of hand postures based on the FMG signals measured by an optical fiber sensor, with artificial neural networks design and implementation in embeeded system.