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Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter

A novel R-peak detection algorithm suitable for wearable electrocardiogram (ECG) devices is proposed with four objectives: robustness to noise, low latency processing, low resource complexity, and automatic tuning of parameters. The approach is a two-pronged algorithm comprising (1) triangle templat...

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Detalles Bibliográficos
Autores principales: Nguyen, Tam, Qin, Xiaoli, Dinh, Anh, Bui, Francis
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767021/
https://www.ncbi.nlm.nih.gov/pubmed/31527502
http://dx.doi.org/10.3390/s19183997
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author Nguyen, Tam
Qin, Xiaoli
Dinh, Anh
Bui, Francis
author_facet Nguyen, Tam
Qin, Xiaoli
Dinh, Anh
Bui, Francis
author_sort Nguyen, Tam
collection PubMed
description A novel R-peak detection algorithm suitable for wearable electrocardiogram (ECG) devices is proposed with four objectives: robustness to noise, low latency processing, low resource complexity, and automatic tuning of parameters. The approach is a two-pronged algorithm comprising (1) triangle template matching to accentuate the slope information of the R-peaks and (2) a single moving average filter to define a dynamic threshold for peak detection. The proposed algorithm was validated on eight ECG public databases. The obtained results not only presented good accuracy, but also low resource complexity, all of which show great potential for detection R-peaks in ECG signals collected from wearable devices.
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spelling pubmed-67670212019-10-02 Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter Nguyen, Tam Qin, Xiaoli Dinh, Anh Bui, Francis Sensors (Basel) Article A novel R-peak detection algorithm suitable for wearable electrocardiogram (ECG) devices is proposed with four objectives: robustness to noise, low latency processing, low resource complexity, and automatic tuning of parameters. The approach is a two-pronged algorithm comprising (1) triangle template matching to accentuate the slope information of the R-peaks and (2) a single moving average filter to define a dynamic threshold for peak detection. The proposed algorithm was validated on eight ECG public databases. The obtained results not only presented good accuracy, but also low resource complexity, all of which show great potential for detection R-peaks in ECG signals collected from wearable devices. MDPI 2019-09-16 /pmc/articles/PMC6767021/ /pubmed/31527502 http://dx.doi.org/10.3390/s19183997 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Nguyen, Tam
Qin, Xiaoli
Dinh, Anh
Bui, Francis
Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter
title Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter
title_full Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter
title_fullStr Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter
title_full_unstemmed Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter
title_short Low Resource Complexity R-peak Detection Based on Triangle Template Matching and Moving Average Filter
title_sort low resource complexity r-peak detection based on triangle template matching and moving average filter
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6767021/
https://www.ncbi.nlm.nih.gov/pubmed/31527502
http://dx.doi.org/10.3390/s19183997
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