Towards the control of an active hand orthosis for people with Duchenne muscular dystrophy: Comparison of intuitive to non-intutive SEMG control

Duchenne Muscular Dystrophy (DMD) is a progressive muscular disease. Active hand orthoses can greatly improve the quality of life of people with DMD. One way to control such devices is via forearm sEMG control. Normally sEMG from the forearm is mapped to a gesture in a physiologically relevant way (intuitive). Often, in complex orthoses with many degrees-of-freedom, this imposes extra burden on the user. This research aims to compare the performance of non-intuitive control against intuitive for future use on the control of hand orthoses for people with DMD. We hypothesize that non-intuitive classification can achieve better results and reduce the burden on the user. The experiment was designed in such a way, that difficult gestures for the classifier were mapped to simpler gestures. The easy gestures are: extend wrist, flex wrist, close hand and supination, while the difficult grips are side grip, fine grip, point and agree.Seven healthy subjects were asked to control a virtual hand using both a non-intuitively trained classifier and an intuitively trained. The performance was evaluated based on completion time and completion rate of gestures. It was found that non-intuitive control performed better on completion time and completion rate (p<0.001), however this statement is supported by a limited number of subjects and trials. The subjects also showed a general preference towards the non-intuitive control via a questionnaire. We conclude that non-intuitive control has a great potential for simplifying the control of active hand orthoses and reduce the burden on the user.