EMG Based Muscle Force Estimation using Motor Unit Twitch Model and Convolution Kernel Compensation

Abstract — In this paper we introduce a new method for muscle force estimation from multi-channel surface electro-myograms. The method combines a motor unit twitch model with motor unit innervation pulse trains, which are estimated from multi-channel surface electromyograms. The motor unit twitches are then aligned to the innervation pulse trains and summed up to obtain the total muscle force. The method was tested on real surface EMG signals acquired during force ramp contractions of abductor pollicis brevis muscle in 8 male subjects. With 22 ± 5 (mean ± std. dev.) motor units identified per subject, the force estimation error of our method was 16 ± 4 % RMS. These results were compared to the method which uses the EMG amplitude processing to estimate muscle force. The results of our new concept proved to be completely com-parable to those of EMG amplitude processing