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Bioengineering 2016, 3(4), 21; doi:10.3390/bioengineering3040021

Optimal Signal Quality Index for Photoplethysmogram Signals

1
Department of Obstetrics & Gynecology, University of British Columbia, Vancouver, BC V6Z 2K5, Canada
2
Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
Academic Editor: Gou-Jen Wang
Received: 24 August 2016 / Revised: 18 September 2016 / Accepted: 19 September 2016 / Published: 22 September 2016
View Full-Text   |   Download PDF [540 KB, uploaded 23 September 2016]   |  

Abstract

A photoplethysmogram (PPG) is a noninvasive circulatory signal related to the pulsatile volume of blood in tissue and is typically collected by pulse oximeters. PPG signals collected via mobile devices are prone to artifacts that negatively impact measurement accuracy, which can lead to a significant number of misleading diagnoses. Given the rapidly increased use of mobile devices to collect PPG signals, developing an optimal signal quality index (SQI) is essential to classify the signal quality from these devices. Eight SQIs were developed and tested based on: perfusion, kurtosis, skewness, relative power, non-stationarity, zero crossing, entropy, and the matching of systolic wave detectors. Two independent annotators annotated all PPG data (106 recordings, 60 s each) and a third expert conducted the adjudication of differences. The independent annotators labeled each PPG signal with one of the following labels: excellent, acceptable or unfit for diagnosis. All indices were compared using Mahalanobis distance, linear discriminant analysis, quadratic discriminant analysis, and support vector machine with leave-one-out cross-validation. The skewness index outperformed the other seven indices in differentiating between excellent PPG and acceptable, acceptable combined with unfit, and unfit recordings, with overall F 1 scores of 86.0%, 87.2%, and 79.1%, respectively. View Full-Text
Keywords: pulse oximeter; mobile health; global health; pulsatile signal; affordable healthcare; telemonitoring; wearable sensors; signal segmentation; point-of-care device; noise detection pulse oximeter; mobile health; global health; pulsatile signal; affordable healthcare; telemonitoring; wearable sensors; signal segmentation; point-of-care device; noise detection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Elgendi, M. Optimal Signal Quality Index for Photoplethysmogram Signals. Bioengineering 2016, 3, 21.

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