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

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Electrical and Computer Engineering in Medicine Group, University of British Columbia and BC Children’s Hospital, Vancouver, BC V6H 3N1, Canada
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Department of Computing Science, University of Alberta, Edmonton, AB T6G 2E8, Canada
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National Critical Care and Trauma Response Centre, Darwin, NT 0810, Australia
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D-Lab, Massachusetts Institute of Technology, Boston, MA 02139, USA
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School of Electrical and Electronic Engineering, University of Adelaide, Adelaide, SA 5005, Australia
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Graduate School of Biomedical Engineering, UNSW, Sydney, NSW 2052, Australia
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Author to whom correspondence should be addressed.
Academic Editor: Paul B. Tchounwou
Int. J. Environ. Res. Public Health 2015, 12(10), 12776-12791; https://doi.org/10.3390/ijerph121012776
Received: 11 August 2015 / Revised: 29 September 2015 / Accepted: 8 October 2015 / Published: 14 October 2015
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 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. View Full-Text
Keywords: exercise; hot environment; affordable healthcare; photoplethysmography exercise; hot environment; affordable healthcare; photoplethysmography
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Elgendi, M.; Norton, I.; Brearley, M.; Fletcher, R.R.; Abbott, D.; Lovell, N.H.; Schuurmans, D. Towards Investigating Global Warming Impact on Human Health Using Derivatives of Photoplethysmogram Signals. Int. J. Environ. Res. Public Health 2015, 12, 12776-12791.

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