Abstract

In order to meet the mobility and physical activity needs of people with impaired limbs function, a novel limbs-free variable structure wheelchair system controled by face-computer interface (FCI) was developed in this study. FCI used facial electromyography (fEMG) as a human intention recognition method from 6 facial movements, and the accuracy of intent recognition reached 97.6% under a series of offline optimization including channel optimization based on the Hilbert transform to obtain the envelope of fEMG, features optimization, and channel-independent model optimization. A collection of finite state machines (FSM) was used to control the movement and structural changes of the wheelchair. A shared control strategy called “ Keep Action after Take Over (KAaTO) “ that can reduce user fatigue while increasing safety was used in long-distance movement control of wheelchair. To test the performance of the system, in the braking distance test experiment, the result of 0.429m under KAaTO was better than the EMG-based discrete command control and speech command control method. Finally, an outdoor long-distance control pilot experiment proved the superior performance of the developed system.

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