This project explores the extent to which muscles in the hand and forearm can learn to generate novel co-contraction patterns (aka muscle synergies) because natural synergies may be disrupted by amputation. The insight gained from this experimental work will inform the design of novel algorithms to enable simultaneous control of multiple joints (degrees of freedom) movements. These algorithms can self-tune, to improve performance, as the user interacts with the prosthesis. The project will culminate in a pre-clinical trial in which four amputee subjects test the prototyped control algorithm with a prosthesis. The performance of the proposed paradigm will be compared to that of the conventional prosthesis on-off control method.

Conference Papers:

Comparison of Hand and Forearm Muscle Pairs in Controlling of a Novel Myoelectric Interface Jessica Barnes, Matthew Dyson & Kianoush Nazarpour IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2016

Pre-Clinical Application of Abstract Muscle Synergies for Myoelectric Control Matthew Dyson & Kianoush Nazarpour ISPO Trent International Prosthetic Symposium (TIPS) 2016