Adaptive noise canceller for magnetocardiography

Author

Tiporlini, Valentina ; Nguyen, Nghia ; Alameh, Kamal

Author_Institution

Electron Sci. Res. Inst., Edith Cowan Univ., Joondalup, WA, Australia

fYear

2011

fDate

19-21 Dec. 2011

Firstpage

359

Lastpage

363

Abstract

This paper discusses the use of adaptive noise cancellation in magnetocardiography system within unshielded environment using three algorithms: Least-Mean Squared (LMS) algorithm; normalized LMS (nLMS) algorithm and Genetic Algorithms (GA). Simulation results show that for low signal-to-noise ratio (SNR) values, the GA algorithm outperforms the other algorithms, displaying an improvement in SNR of 51.155 dB and completely suppressing the noise sources at 60 Hz and at low frequencies. However, the convergence time of the GA algorithm is longer due to the high computational complexity.

Keywords

computational complexity; genetic algorithms; least mean squares methods; magnetocardiography; adaptive noise canceller; computational complexity; frequency 60 Hz; genetic algorithms; least mean squared algorithm; magnetocardiography; normalized LMS algorithm; Indexes; Least squares approximation; Signal to noise ratio; Adaptive noise cancellation; Genetic algorithms; Least-Mean Squared algorithms; Magnetocardiography; Telehealth;

fLanguage

English

Publisher

ieee

Conference_Titel

High Capacity Optical Networks and Enabling Technologies (HONET), 2011

Conference_Location

Riyadh

Print_ISBN

978-1-4577-1170-1

Type

conf

DOI

10.1109/HONET.2011.6149770

Filename

6149770