Noise Cancellation in Unshielded Magnetocardiography based on Least-Mean-Squared Algorithm and Genetic Algorithm
Abstract
This paper discusses adaptive noise cancellation in magnetocardiographic systems within unshielded environment using two algorithms, namely, the Least-Mean-Squared (LMS) algorithm and the Genetic Algorithm (GA). Simu- lation results show that the GA algorithm outperforms the LMS algorithm in extracting a weak heart signal from a much-stronger magnetic noise, with a signal-to-noise ratio (SNR) of -35.8 dB. The GA algorithm displays an improvement in SNR of 37.4 dB and completely suppresses the noise sources at 60Hz and at low frequencies; while the LMS algorithm exhibits an improvement in SNR of 33 dB and noisier spectrum at low frequencies. The GA algorithm is shown to be able to recover a heart signal with the QRS and T features being easily extracted. On the other hand, the LMS algorithm can also recover the input signal, however, with a lower SNR improvement and noisy QRS complex and T wave.
About the Authors
V. Tiporlini
Edith Cowan University
Joondalup
Australia
Australia
Electron Science Research Institute
Hoang N. Nguyen
Edith Cowan University
Joondalup
Australia
Australia
Electron Science Research Institute
K. Alameh
Edith Cowan University
Joondalup
Australia
Australia
Electron Science Research Institute
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Review
For citations:
Tiporlini V., Nguyen H.N., Alameh K. Noise Cancellation in Unshielded Magnetocardiography based on Least-Mean-Squared Algorithm and Genetic Algorithm. Nanosystems: Physics, Chemistry, Mathematics. 2013;4(3):417-424.
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