Control of Artificial Hand via Recognition of EMG Signals

The paper presents a concept of bioprosthesis control via recognition of user intent on the basis of myopotentials acquired from his body. The EMG signals characteristics and the problems of their measurement have been discussed. The contextual recognition has been considered and three description method for such approach (respecting 1st and 2nd -order context), using: Markov chains, fuzzy rules, neural networks, as well as the involved decision algorithms have been described. The algorithms have been experimentally tested as far as the decision quality is concerned.