Development of a filtering algorithm to demodulate electromyogram signal of essential tremor patients

Essential tremor is a disorder that causes involuntary oscillations in patients both while they are engaged in actions and when maintaining a posture. Such patients face serious difficulties in performing such daily living activities as eating, drinking, and writing. We have been developing an electromyogram (EMG)-controlled exoskeleton to suppress tremors and to support the movements of these patients. In this paper, we proposed a novel signal processing method to demodulate the patients´ EMG signal, which contains the voluntary movement signal and the tremor noise. This is a real-time signal processing method for multiple types of noise. From a technical point of view, this processing is essential because, at present, there are no real-time methods addressing the multiple noise sources. Also, from an application point of view, this method is essential for the accurate control of the exoskeleton depending on the patients´ voluntary movement intention. We confirmed that the proposed method showed feasibility to demodulate the EMG signal which is modulated by the tremor signal.