VLSI Implementation of Median Filter for Noise Removal in EMG Signal

The most important requirement in processing real world signals is using less computational time and energy efficient processing to minimizing the noise in the signals. The Electromyography (EMG) signal is a type of physiological signal produced by muscles when they are contracting. EMG data are frequently required to assist diagnose or rule out a variety of diseases, including Muscle diseases like muscular dystrophy and polymyositis. However, EMG signals are easily affected by environmental noise like inherent noise in electronics equipment, motion artifact, inherent instability of signal. This noise should be eliminated to obtain accurate results from the diagnosis. The existing architecture utilizes a sorting method to sort the input samples either in increasing or decreasing order and determine the median value it needs a lot of comparators. Meanwhile the dynamic power consumption and computational time is high. A novel median filter design based on a ID filter using a low-power design is proposed. At the end of each machine cycle, it produces a median output after receiving an input sample through a two-stage pipelined filter. The circuit’s power utilization is decreased by reducing the signal transitions. The gating method is used to decrease dynamic power usage. The outcome result of the proposed architecture showed that it has lower power utilization of S6 mW in S-bit sample width, while the current method has 19SmW power consumption. It shows that the power consumption of proposed architecture is reduced by 56.56% while comparing with the existing method.