Comparison of electromyography and mechanomyogram in control of prosthetic system in multiple limb positions

Like commonly used electromyography (EMG), mechanomyogram (MMG) is another type of important signal that represents muscle activities in the form of muscle vibrations. A number of studies have showed that both EMG and MMG have great prospect in the application of prosthetic control system. Most previous studies using either EMG or MMG signals mainly focus on improving the control performance of prosthetic system or investigating the signal´s metrics. The differences of these two types of signals associated with the muscle activities remain unclear in classifying multiple motion classes. In addition, limb position variation may be one of important factors which would cause classification performance degradation. In this study, we analyzed and compared the metrics of these two kinds of biomedical signals by motion classification and position classification in terms of classification error. The results showed that the similar motion classification performance could be achieved using both EMG and MMG, having the classification errors of 7.4% and 9.9%, respectively. When it comes to position classification, MMG achieved significantly lower classification error of 0.7% versus 16.5% when using EMG.