High Frequency Electromyogram Noise Removal from Electrocardiogram Using FIR Low Pass Filter Based On FPGA

With improvements in capacity and performance and a decrease in cost, FPGAs have become a viable solution for making custom chips and programmable DSP devices. This paper presents an efficient implementation of Finite Impulse Response Filter (FIR) using Distributed Arithmetic (DA) architecture based on FPGA with the help of Xilinx system generator software. Here, the multipliers in FIR filter are replaced with multiplier less DA based technique to remove high frequency Electrocardiogram (EMG) noise from ECG signal. As digital filters plays very significant role in the analysis of the low frequency components in Electrocardiogram (ECG) signal. The ECG is susceptible to noise and it is essential to remove the noise to support decision making for specialist and automatic heart disorder diagnosis systems. We proposed that the signals under experiment has been added with muscle noise and after applying different FIR method, the signals according to signal noise ratio (SNR) and MSE(mean square error) are evaluated. It introduces an effective technique for the denoising of ECG signals corrupted by High frequency muscles contraction noise. The performances of the system were evaluated using the Massachusetts Institute of Technology University and Beth Israel Hospital (MIT-BIH) database. Muscle noise is taken from MIT-BIH noise stress database. Simulation results shows that High frequency EMG noise from ECG was removed effectively by using FIR low pass filter. The implementation is done on a Xilinx chip of Spartan 3E XC3S500e-4fg320 using Xilinx system generator 10.1 with Matlab version7.4.0 (2007a). (C) 2016 The Authors. Published by Elsevier Ltd.