Estimation of Hand Gestures Using EMG and Bioimpedance

근전도와 임피던스를 이용한 손동작 추정

Kim, Soo-Chan

  • Received : 2015.10.12
  • Accepted : 2015.12.04
  • Published : 2016.01.01


EMG has specific information which is related to movements according to the activities of muscles. Therefore, users can intuitively control a prosthesis. For this reason, biosignals are very useful and convenient in this kind of application. Bioimpednace also provides specific information about movements like EMG. In this study, we used both EMG and bioimpedance to classify the typical hand gestures such as hand open, hand close, no motion (rest), supination, and pronation. Nine able-bodied subjects and one amputee were used as experimental data set. The accuracy was $98{\pm}1.9%$ when 2 bio-impedance and 8 EMG channels were used together for normal subjects. The number of EMG channels affected the accuracy, but it was stable when more than 5 channels were used. For the amputee, the accuracy is higher when we use both of them than when using only EMG. Therefore, accurate and stable hand motion estimation is possible by adding bioimepedance which shows structural information and EMG together.


EMG;Bioimpedance;Prosthesis control;Amputee;Classification;Upper limb


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Supported by : 한경대학교