CONFERENCE / ICICMCT'23

Suppression of noise is the basic operation needed by most modern systems for biomedical signal processing. To achieve this objective, the main idea is to set a criterion which provide the distinction between the true component and the noise. In the real-world scenario, Electromyography (EMG) signals often affect by different noises. The EMG signal demands noise reduction to accomplish an accurate diagnosis process. In this paper, Han-Carlson Adder (HCA) based Median Filter (MF) architecture is used for the removal of noise from the EMG signal. The proposed HCA-MF method is simulated in the ModelSim software and Xilinx tool to evaluate the performance in terms of power, delay and area. The objective of this work is to design an efficient median architecture for the de- noising process of EMG signal. This helps to reduce the hardware resources of the entire median filter architecture. The simulation result of HCA-MF architecture shows less area, power consumption and delay parameters when compared to existing system.