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Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes
The analysis of cardiac activity is one of the most common elements for evaluating the state of a subject, either to control possible health risks, sports performance, stress levels, etc. This activity can be recorded using different techniques, with electrocardiogram and photoplethysmogram being th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10209290/ https://www.ncbi.nlm.nih.gov/pubmed/36877361 http://dx.doi.org/10.1007/s13246-023-01235-6 |
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author | Merino-Monge, Manuel Castro-García, Juan Antonio Lebrato-Vázquez, Clara Gómez-González, Isabel María Molina-Cantero, Alberto Jesús |
author_facet | Merino-Monge, Manuel Castro-García, Juan Antonio Lebrato-Vázquez, Clara Gómez-González, Isabel María Molina-Cantero, Alberto Jesús |
author_sort | Merino-Monge, Manuel |
collection | PubMed |
description | The analysis of cardiac activity is one of the most common elements for evaluating the state of a subject, either to control possible health risks, sports performance, stress levels, etc. This activity can be recorded using different techniques, with electrocardiogram and photoplethysmogram being the most common. Both techniques make significantly different waveforms, however the first derivative of the photoplethysmographic data produces a signal structurally similar to the electrocardiogram, so any technique focusing on detecting QRS complexes, and thus heartbeats in electrocardiogram, is potentially applicable to photoplethysmogram. In this paper, we develop a technique based on the wavelet transform and envelopes to detect heartbeats in both electrocardiogram and photoplethysmogram. The wavelet transform is used to enhance QRS complexes with respect to other signal elements, while the envelopes are used as an adaptive threshold to determine their temporal location. We compared our approach with three other techniques using electrocardiogram signals from the Physionet database and photoplethysmographic signals from the DEAP database. Our proposal showed better performances when compared to others. When the electrocardiographic signal was considered, the method had an accuracy greater than 99.94%, a true positive rate of 99.96%, and positive prediction value of 99.76%. When photoplethysmographic signals were investigated, an accuracy greater than 99.27%, a true positive rate of 99.98% and positive prediction value of 99.50% were obtained. These results indicate that our proposal can be adapted better to the recording technology. |
format | Online Article Text |
id | pubmed-10209290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-102092902023-05-26 Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes Merino-Monge, Manuel Castro-García, Juan Antonio Lebrato-Vázquez, Clara Gómez-González, Isabel María Molina-Cantero, Alberto Jesús Phys Eng Sci Med Scientific Paper The analysis of cardiac activity is one of the most common elements for evaluating the state of a subject, either to control possible health risks, sports performance, stress levels, etc. This activity can be recorded using different techniques, with electrocardiogram and photoplethysmogram being the most common. Both techniques make significantly different waveforms, however the first derivative of the photoplethysmographic data produces a signal structurally similar to the electrocardiogram, so any technique focusing on detecting QRS complexes, and thus heartbeats in electrocardiogram, is potentially applicable to photoplethysmogram. In this paper, we develop a technique based on the wavelet transform and envelopes to detect heartbeats in both electrocardiogram and photoplethysmogram. The wavelet transform is used to enhance QRS complexes with respect to other signal elements, while the envelopes are used as an adaptive threshold to determine their temporal location. We compared our approach with three other techniques using electrocardiogram signals from the Physionet database and photoplethysmographic signals from the DEAP database. Our proposal showed better performances when compared to others. When the electrocardiographic signal was considered, the method had an accuracy greater than 99.94%, a true positive rate of 99.96%, and positive prediction value of 99.76%. When photoplethysmographic signals were investigated, an accuracy greater than 99.27%, a true positive rate of 99.98% and positive prediction value of 99.50% were obtained. These results indicate that our proposal can be adapted better to the recording technology. Springer International Publishing 2023-03-06 2023 /pmc/articles/PMC10209290/ /pubmed/36877361 http://dx.doi.org/10.1007/s13246-023-01235-6 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Scientific Paper Merino-Monge, Manuel Castro-García, Juan Antonio Lebrato-Vázquez, Clara Gómez-González, Isabel María Molina-Cantero, Alberto Jesús Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes |
title | Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes |
title_full | Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes |
title_fullStr | Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes |
title_full_unstemmed | Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes |
title_short | Heartbeat detector from ECG and PPG signals based on wavelet transform and upper envelopes |
title_sort | heartbeat detector from ecg and ppg signals based on wavelet transform and upper envelopes |
topic | Scientific Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10209290/ https://www.ncbi.nlm.nih.gov/pubmed/36877361 http://dx.doi.org/10.1007/s13246-023-01235-6 |
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