Document Type

Conference Proceeding


Bloomsbury Publishing India Pvt. Ltd.


Faculty of Computing, Health and Science


Electron Science Research Institute




This article was originally published as: Tiporlini, V. , Nguyen, H. N., & Alameh, K. (2012). Noise Suppression in Unshielded Magnetocardiography: Least-Mean Squared Algorithm versus Genetic Algorithm. Proceedings of The International Symposium on Macro- and Supramolecular architectures and materials (MAM-12) . (pp. 109-114). Coimbatore,Tamil Nadu,India. Bloomsbury Publishing India Pvt. Ltd.


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 suppressing 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.

Access Rights


Included in

Engineering Commons