Using common spatial pattern algorithm for unsupervised real-time estimation of fingertip forces from sEMG signals

Abstract

In this paper, a method to extract the fingertip forces of the index and middle fingers from surface electromyography (sEMG) signals is studied by adopting the known common spatial pattern (CSP) approach. For unsupervised estimation of fingertip forces in real-time, CSP filtering is shown to be a notably effective method compared with known approaches for handling sEMG signals. The results of the proposed method are comparable to those of supervised estimations, such as linear regression and artificial neural network. The efficacy of the proposed method is validated by experiments.