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On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress
There are a limited number of studies on heat stress dynamics during exercise using the photoplethysmogram (PPG) and its second derivative (APG). However, we investigate the most suitable index from short PPG signal recordings for heat stress assessment. The APG waveform consists of a, b, c and d wa...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634460/ https://www.ncbi.nlm.nih.gov/pubmed/26404271 http://dx.doi.org/10.3390/s151024716 |
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author | Elgendi, Mohamed Fletcher, Rich Norton, Ian Brearley, Matt Abbott, Derek Lovell, Nigel H. Schuurmans, Dale |
author_facet | Elgendi, Mohamed Fletcher, Rich Norton, Ian Brearley, Matt Abbott, Derek Lovell, Nigel H. Schuurmans, Dale |
author_sort | Elgendi, Mohamed |
collection | PubMed |
description | There are a limited number of studies on heat stress dynamics during exercise using the photoplethysmogram (PPG) and its second derivative (APG). However, we investigate the most suitable index from short PPG signal recordings for heat stress assessment. The APG waveform consists of a, b, c and d waves in systole and an e wave in diastole. Our preliminary results indicate that the use of the energy of [Formula: see text] area, derived from PPG signals measured from emergency responders in tropical conditions, is promising in determining the heat stress level using 20-s recordings. After examining 14 time domain features using leave-one-out cross-validation, we found that the [Formula: see text] energy extracted from PPG signals is the most informative feature for classifying heat-stressed subjects, with an overall accuracy of 79%. Moreover, the combination of the [Formula: see text] energy with the traditional heart rate variability index of heat stress (i.e., the square root of the mean of the squares of the successive [Formula: see text] intervals) improved the heat stress detection to an overall accuracy of 83%. |
format | Online Article Text |
id | pubmed-4634460 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-46344602015-11-23 On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress Elgendi, Mohamed Fletcher, Rich Norton, Ian Brearley, Matt Abbott, Derek Lovell, Nigel H. Schuurmans, Dale Sensors (Basel) Article There are a limited number of studies on heat stress dynamics during exercise using the photoplethysmogram (PPG) and its second derivative (APG). However, we investigate the most suitable index from short PPG signal recordings for heat stress assessment. The APG waveform consists of a, b, c and d waves in systole and an e wave in diastole. Our preliminary results indicate that the use of the energy of [Formula: see text] area, derived from PPG signals measured from emergency responders in tropical conditions, is promising in determining the heat stress level using 20-s recordings. After examining 14 time domain features using leave-one-out cross-validation, we found that the [Formula: see text] energy extracted from PPG signals is the most informative feature for classifying heat-stressed subjects, with an overall accuracy of 79%. Moreover, the combination of the [Formula: see text] energy with the traditional heart rate variability index of heat stress (i.e., the square root of the mean of the squares of the successive [Formula: see text] intervals) improved the heat stress detection to an overall accuracy of 83%. MDPI 2015-09-25 /pmc/articles/PMC4634460/ /pubmed/26404271 http://dx.doi.org/10.3390/s151024716 Text en © 2015 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 license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Elgendi, Mohamed Fletcher, Rich Norton, Ian Brearley, Matt Abbott, Derek Lovell, Nigel H. Schuurmans, Dale On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress |
title | On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress |
title_full | On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress |
title_fullStr | On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress |
title_full_unstemmed | On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress |
title_short | On Time Domain Analysis of Photoplethysmogram Signals for Monitoring Heat Stress |
title_sort | on time domain analysis of photoplethysmogram signals for monitoring heat stress |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4634460/ https://www.ncbi.nlm.nih.gov/pubmed/26404271 http://dx.doi.org/10.3390/s151024716 |
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