Title

Noise cancellation in unshielded magnetocardiography based on least-mean-squared algorithm and genetic algorithm

Document Type

Journal Article

Publisher

St. Petersburg National Research University of Information Technologies, Mechanics and Optics

Faculty

Faculty of Health, Engineering and Science

School

Electron Science Research Institute/Electron Science Research Institute

RAS ID

16713

Comments

This article was originally published as: Tiporlini, V. , Nguyen, H. N., & Alameh, K. (2013). Noise cancellation in unshielded magnetocardiography based on least-mean-squared algorithm and genetic algorithm. Nanosystems: Physics, Chemistry, Mathematics, 4 (3), 417-424. Original article available here

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). Simulation 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.

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