Review on Electromyography Signal Acquisition, Processing and Its Applications

Abstract

Electromyography (EMG) signal is the type of biomedical signal, which is obtained from the neuromuscular activities. Typically, an electromyogram instrument is used to capture the EMG signals. These signals are used to monitor medical abnormalities, activation level, and also to analyze the biomechanics of any animal movements. In this current work, we provide a short review of EMG signal acquisition and processing techniques. We found that the average efficiency to capture EMG signals with the current technologies is around 70 %. Once the signal is captured, the signal processing algorithms applied decides the recognition accuracy, with which signals are decoded for their corresponding purpose (e.g. moving robotic arm, speech recognition, gait analysis, etc). The recognition accuracy can go as high as 99.8 %. The accuracy with which the EMG signal is decoded has already crossed 99 %, and with the upcoming deep learning technology, there is a scope of improvement to design hardware, that can efficiently capture EMG signals.