Design of LMS algorithm for noise canceller based on FPGA

Abstract

This paper presents the design of an adapting filtering method to remove the noise in the biomedical signal records. The major concern about analyze the presence of various artifacts in ECG records and modular artifacts in EEG records caused due to various noise factors. Here, we have proposed a design based on LMS (Least Mean Square) algorithm to remove the artifacts from biomedical signal using Verilog HDL based on been mapped on  commercially available FPGAs (Field Programmable Gate Arrays). In this design the LMS algorithm used as a noise canceller and the reference signal was adaptively filtered and subtracted from primary signal to obtain the estimated biomedical signal. The original biomedical signal can be reconstructed by passing the digital bit stream through a low pass filter. This design is suitable for its low power biomedical instrument design and it reduces the whole system cost.

Keywords: LMS algorithm, noise canceller, Verilog HDL, artifacts, biomedical signal, Low power application.