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Towards Investigating Global Warming Impact on Human Health Using Derivatives of Photoplethysmogram Signals

Bibliographic Data

ID15514056
AuthorsMohamed Elgendi (0000-0003-1831-0202, University of Alberta, corresponding author), Ian Norton (National Critical Care and Trauma Response Centre), Matt Brearley (0000-0002-6655-3914, National Critical Care and Trauma Response Centre), Richard Fletcher (0000-0002-5496-2112, Massachusetts Institute of Technology), Derek Abbott (0000-0002-0945-2674, The University of Adelaide), Nigel H Lovell (0000-0003-1637-1079, UNSW Sydney), Nigel Lovell (UNSW Sydney), Dale Schuurmans (University of Alberta)
Year2015
Volume12
Issue10
Pages12776-12791
Publication date2015-10-14
Open AccessYes
TypeARTICLE
VenueInternational Journal of Environmental Research and Public Health (JOURNAL)
Journal identifiersISSN: 1661-7827 • E-ISSN: 1660-4601
PublisherMultidisciplinary Digital Publishing Institute (PUBLISHER • CH)
DOI10.3390/ijerph121012776
PMID26473907
OpenAlexW2124107914
LanguageEN
References cited24

Recent clinical studies show that the contour of the photoplethysmogram (PPG) wave contains valuable information for characterizing cardiovascular activity. However, analyzing the PPG wave contour is difficult; therefore, researchers have applied first or higher order derivatives to emphasize and conveniently quantify subtle changes in the filtered PPG contour. Our hypothesis is that analyzing the whole PPG recording rather than each PPG wave contour or on a beat-by-beat basis can detect heat-stressed subjects and that, consequently, we will be able to investigate the impact of global warming on human health. Here, we explore the most suitable derivative order for heat stress assessment based on the energy and entropy of the whole PPG recording. The results of our study indicate that the use Int. J. Environ. Res. Public Health 2015, 7 12777 of the entropy of the seventh derivative of the filtered PPG signal shows promising results in detecting heat stress using 20-second recordings, with an overall accuracy of 71.6%. Moreover, the combination of the entropy of the seventh derivative of the filtered PPG signal with the root mean square of successive differences, or RMSSD (a traditional heart rate variability index of heat stress), improved the detection of heat stress to 88.9% accuracy

Climate change · Environmental health · Global warming · Human health · Photoplethysmogram · Telecommunications · Computer Science · Environmental Science · Heart Rate Variability and Autonomic Control · Hemodynamic Monitoring and Therapy · Medicine · Non-Invasive Vital Sign Monitoring · Geology · Oceanography

Highly citedNo

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