Motion Artifact Cancellation from ECG Signals using NLMS based Adaptive Filters
Fakroul Ridzuan Hashim1, Ja’afar Adnan2, Anis Shahida Niza Mokhtar3, Amir Firdaus Rashidi4, Nik Ghazali Nik Daud5
1Fakroul Ridzuan Hashim, Faculty of Engineering, National Defense University of Malaysia, Kuala Lumpur, Malaysia.
2Ja’afar Adnan, Faculty of Engineering, National Defense University of Malaysia, Kuala Lumpur, Malaysia.
3Anis Shahida Niza Mokhtar, Faculty of Engineering, National Defense University of Malaysia, Kuala Lumpur, Malaysia.
4Amir Firdaus Rashidi, Faculty of Engineering, National Defense University of Malaysia, Kuala Lumpur, Malaysia.
5Nik Ghazali Nik Daud, Faculty of Engineering, National Defense University of Malaysia, Kuala Lumpur, Malaysia.
Manuscript received on 14 December 2018 | Revised Manuscript received on 26 December 2018 | Manuscript Published on 24 January 2019 | PP: 259-261 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: ES20109017519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the research, the normalized LMS adaptive filters is improved and proposed to reduce the motion artifact (MA) noise from ECG signals. The simulation result gives by the improved versions of adaptive filter (NLMS, PNLMS and IPNLMS) show superior performance when compared to other technique such as wavelet and empirical mode decomposition. Among adaptive filter, the PNLMS adaptive filter give the best performance among NLMS and IPNLMS adaptive filters.
Keywords: ECG Signal, Adaptive Filter, Proportionate, Improved Proportionate, μ-law.
Scope of the Article: Adaptive Systems