Removal of Power Line Interference from Electrocardiograph (ECG) using Proposed Adaptive Filter Algorithm

Removal of Power Line Interference from Electrocardiograph (ECG) using Proposed Adaptive Filter Algorithm

Article ID

CSTSDER521V

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Removal of Power Line Interference from Electrocardiograph (ECG) using Proposed Adaptive Filter Algorithm

Duong Trong Luong Hanoi University of science and Technology

Nguyen Duc Thuan

Dang Huy Hoang

DOI

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Abstract

ECG signals in measurements are contaminated by noises including power line interference. In recent years, adaptive filters with different approaches have been investigated to remove power line interference in ECG.In this paper, an adaptive filter is proposed to cancel power line interference in ECG signals. The proposed algorithm is experimented with MIT-BIH ECG signals data base. The algorithm’s results are compared with the results of other adaptive filter algorithms using Least Mean Square (LMS), Normalized Least Mean Square (NLMS) by Signal to Noise (SNR). Theses works are performed by LabVIEW software.

Removal of Power Line Interference from Electrocardiograph (ECG) using Proposed Adaptive Filter Algorithm

Authors

Duong Trong Luong Hanoi University of science and Technology

Nguyen Duc Thuan

Dang Huy Hoang

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How to Cite

Duong Trong Luong. 2015. “. Global Journal of Computer Science and Technology – C: Software & Data Engineering GJCST-C Volume 15 (GJCST Volume 15 Issue C2): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

GJCST Volume 15 Issue C2
Pg. 11- 14

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Classification

GJCST-C Classification: H.3.5

Submission Received December 14, 2014
Accepted January 1, 2015
Published January 15, 2015

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Article Matrices

Total Score: 103

Country: Unknown

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Duong Trong Luong, Nguyen Duc Thuan, Dang Huy Hoang (PhD/Dr. count: 0)

View Count (all-time): 229

Total Views (Real + Logic): 8121

Total Downloads (simulated): 2157

Publish Date: 2015 03, Mon

Monthly Totals (Real + Logic):

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Total Views: 8121

Total Downloads: 2157

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