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Abstract:
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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 |