EMG cancellation from ECG signals using modified NLMS adaptive filters

Author

Hashim, Fakroul R. ; Soraghan, John J. ; Petropoulakis, Lykourgor ; Daud, Nik G. N.

Author_Institution

Fac. of Eng., Nat. Defense Univ. of Malaysia, Sungai Besi, Malaysia

fYear

2014

Firstpage

735

Lastpage

739

Abstract

In this study, improved normalized LMS adaptive filters are proposed to reduce the electromyogram (EMG) noise from ECG signals. The proposed technique mainly uses simple addition and shift operations and achieves considerable speed over other methods based on the LMS method. Simulation result gives by the improved versions of adaptive filter (NLMS, PNLMS, IPNLMS and MPNLS) show superior performance to be compared with other technique such as wavelet and empirical mode decomposition.

Keywords

adaptive filters; electrocardiography; electromyography; least mean squares methods; medical signal processing; signal denoising; ECG signal; EMG cancellation; IPNLMS; LMS method; MPNLS; electromyogram noise reduction; empirical mode decomposition; improved normalized LMS adaptive filters; modified NLMS adaptive filters; shift operations; wavelet; Adaptive filters; Conferences; Electrocardiography; Electromyography; Filtering algorithms; Signal to noise ratio; μ-law; ECG signal; adaptive filter; improved proportionate; proportionate;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Engineering and Sciences (IECBES), 2014 IEEE Conference on

Type

conf

DOI

10.1109/IECBES.2014.7047605

Filename

7047605

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3565507