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Published in: Journal of Clinical Monitoring and Computing 5/2018

Open Access 01-10-2018 | Original Research

Video-based heart rate monitoring across a range of skin pigmentations during an acute hypoxic challenge

Authors: Paul S. Addison, Dominique Jacquel, David M. H. Foo, Ulf R. Borg

Published in: Journal of Clinical Monitoring and Computing | Issue 5/2018

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Abstract

The robust monitoring of heart rate from the video-photoplethysmogram (video-PPG) during challenging conditions requires new analysis techniques. The work reported here extends current research in this area by applying a motion tolerant algorithm to extract high quality video-PPGs from a cohort of subjects undergoing marked heart rate changes during a hypoxic challenge, and exhibiting a full range of skin pigmentation types. High uptimes in reported video-based heart rate (HRvid) were targeted, while retaining high accuracy in the results. Ten healthy volunteers were studied during a double desaturation hypoxic challenge. Video-PPGs were generated from the acquired video image stream and processed to generate heart rate. HRvid was compared to the pulse rate posted by a reference pulse oximeter device (HRp). Agreement between video-based heart rate and that provided by the pulse oximeter was as follows: Bias = − 0.21 bpm, RMSD = 2.15 bpm, least squares fit gradient = 1.00 (Pearson R = 0.99, p < 0.0001), with a 98.78% reporting uptime. The difference between the HRvid and HRp exceeded 5 and 10 bpm, for 3.59 and 0.35% of the reporting time respectively, and at no point did these differences exceed 25 bpm. Excellent agreement was found between the HRvid and HRp in a study covering the whole range of skin pigmentation types (Fitzpatrick scales I–VI), using standard room lighting and with moderate subject motion. Although promising, further work should include a larger cohort with multiple subjects per Fitzpatrick class combined with a more rigorous motion and lighting protocol.
Footnotes
1
The original 18 s window was chosen from experience. We did not conduct a parametric study because, as we have such limited data, we would be prone to overtraining the algorithm. Typically, a commercial pulse oximeter would have a dynamic window which can be anything in length from around 10 s upwards, and can be relatively long during prolonged noise i.e. > 60 s. In addition, many algorithms use an IIR filter where the new information is added to a weighted average from a sequence of data of increasing length at which point a statistical estimate of the ‘history’ of the utilized data is required, i.e. no fixed window.
 
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Metadata
Title
Video-based heart rate monitoring across a range of skin pigmentations during an acute hypoxic challenge
Authors
Paul S. Addison
Dominique Jacquel
David M. H. Foo
Ulf R. Borg
Publication date
01-10-2018
Publisher
Springer Netherlands
Published in
Journal of Clinical Monitoring and Computing / Issue 5/2018
Print ISSN: 1387-1307
Electronic ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-017-0076-1

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