eprintid: 4328
rev_number: 7
eprint_status: archive
userid: 331
dir: disk0/00/00/43/28
datestamp: 2020-12-26 09:07:33
lastmod: 2020-12-26 09:07:33
status_changed: 2020-12-26 09:07:33
type: article
metadata_visibility: show
creators_name: Hoang, Van Manh
creators_name: Pham, Manh Thang
creators_id: manhhv87@vnu.edu.vn
creators_id: thangpm@vnu.edu.vn
title: Adaptive Noise Filter for Real-Time Stress ECG Signal Analysis
ispublished: pub
subjects: ElectronicsandComputerEngineering
divisions: fac_fema
abstract: The stress Electrocardiogram (ECG) gives more efficient results for the diagnosis of cardiovascular diseases, which may not be apparent when the patients are at rest. However, the noise produced by the movement of the patient and the environment often contaminates the ECG signal. Motion artifact is the most prevalent and difficult type of interference to filter in stress test ECG. It corrupts the quality of the desired signal thus reducing the reliability of the stress test. In this work, we first describe a quantitative study of adaptive filtering for processing the stress ECG signals. The proposed method uses the motion information obtained from a 3-axis accelerometer as a noise reference signal for the adaptive filter and the optimal weight of the adaptive filter is adjusted by the Modified Error Data Normalized Step-Size (MEDNSS) algorithm. Finally, the performance of the proposed algorithm is tested on the stress ECG signal from the subject.
date: 2020-12
date_type: published
official_url: http://jst.hust.edu.vn/
full_text_status: public
publication: Journal of Science & Technology of Technical Universities
number: 147
pagerange: 59-64
refereed: FALSE
issn: 2354-1083
citation:   Hoang, Van Manh and Pham, Manh Thang  (2020) Adaptive Noise Filter for Real-Time Stress ECG Signal Analysis.  Journal of Science & Technology of Technical Universities  (147).   pp. 59-64.  ISSN 2354-1083     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4328/1/Adaptive%20noise%20filter%20for%20real-time%20stress%20ECG%20signal%20analysis.pdf