NANOSYSTEMS: PHYSICS, CHEMISTRY, MATHEMATICS, 2013, 4 (3), P. 417–424
NOISE CANCELLATION IN UNSHIELDED MAGNETOCARDIOGRAPHY BASED ON LEASTMEANSQUARED ALGORITHM AND GENETIC ALGORITHM
Valentina Tiporlini – Electron Science Research Institute, Edith Cowan University, Joondalup, Western Australia; v.tiporlini@ecu.edu.au
Hoang N. Nguyen – Electron Science Research Institute, Edith Cowan University, Joondalup, Western Australia; h.nguyen@ecu.edu.au
Kamal Alameh – Electron Science Research Institute, Edith Cowan University, Joondalup, Western Australia; k.alameh@ecu.edu.au
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 muchstronger 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.
Keywords: Magnetocardiography, adaptive noise cancellation, Least-Mean-Squared algorithm, genetic algorithms.
PACS 87.85.d