Real Time Adaptive Filter based EMG Signal Processing and Instrumentation Scheme for Robust Signal Acquisition Using Dry EMG Electrodes

Bio signals provide us with information which gives us valuable insight into the natural processes occurring inside the human body. This makes it absolutely imperative for the signal to be free of noise so that it provides a worthy estimate of the information provided by the bio signals. This paper focuses on the signal processing aspect of electromyography. We propose an adaptive filter based signal processing scheme in real time to remove noise from the EMG signal taking into account the unpredictable nature and changing dynamics of noise picked up from the surrounding environment while using dry EMG electrodes. In addition, we also propose an instrumentation scheme which not only cancels noise using analogue filters and Driven Right Leg circuit, but also provides a signal offset without the use of adder circuits to enable an ADC to acquire the signal. In order to validate the performance of the proposed signal processing and instrumentation scheme, we perform an analysis of the filtered EMG signal in time and frequency domains in terms of signal to noise ratio, discrete Fourier transform, and cross spectral density. In the end, we will come to a conclusion that the signal acquisition scheme proposed provides an EMG signal which sufficiently reduces noise and can be useful for various EMG applications.