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Please use this identifier to cite or link to this item: http://dyuthi.cusat.ac.in/purl/4515

Title: ECG Noise Removal using GA tuned Sign-Data Least Mean Square Algorithm
Authors: Mythili, P
Baby, Paul
Keywords: Adaptive filter
Baseline wander
Genetic Algorithm
Power line inteiference
Sign Data LMS algorithm.
Issue Date: 23-Aug-2012
Publisher: IEEE
Abstract: Adaptive filter is a primary method to filter Electrocardiogram (ECG), because it does not need the signal statistical characteristics. In this paper, an adaptive filtering technique for denoising the ECG based on Genetic Algorithm (GA) tuned Sign-Data Least Mean Square (SD-LMS) algorithm is proposed. This technique minimizes the mean-squared error between the primary input, which is a noisy ECG, and a reference input which can be either noise that is correlated in some way with the noise in the primary input or a signal that is correlated only with ECG in the primary input. Noise is used as the reference signal in this work. The algorithm was applied to the records from the MIT -BIH Arrhythmia database for removing the baseline wander and 60Hz power line interference. The proposed algorithm gave an average signal to noise ratio improvement of 10.75 dB for baseline wander and 24.26 dB for power line interference which is better than the previous reported works
Description: 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT)
URI: http://dyuthi.cusat.ac.in/purl/4515
Appears in Collections:P Mythili

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