Abstract
The control of multifunctional myoelectric prostheses is commonly limited due to the lack of sufficient electromyography (EMG) signals after amputation. With a goal of developing easy-to-use and flexibly controlled multifunctional prostheses, the authors propose two control strategies that fuse EMG and speech signals. In the first, speech signals switch the joint-mode, and EMG signals determine a motion class to actuate the target movement. In the second, speech signals select a motion class directly, and EMG signals actuated the movement. Experimental results showed that the proposed strategies could improve control performance and enhance the operational efficiency significantly, suggesting that signal fusion is a feasible way to effectively strengthen interactions between humans and machines.
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