Analysis of a Pulse Rate Variability Measurement Using a Smartphone Camera

Author:

Bánhalmi András1ORCID,Borbás János2,Fidrich Márta1,Bilicki Vilmos1,Gingl Zoltán1,Rudas László3

Affiliation:

1. Institute of Informatics, University of Szeged, Szeged, 2 Árpád Square 6720, Hungary

2. 2nd Department of Internal Medicine and Cardiology Clinic, University of Szeged, Szeged, 6 Semmelweis Street 6725, Hungary

3. Department of Anesthesiology and Intensive Therapy, University of Szeged, Szeged, 6 Semmelweis Street 6725, Hungary

Abstract

Background. Heart rate variability (HRV) provides information about the activity of the autonomic nervous system. Because of the small amount of data collected, the importance of HRV has not yet been proven in clinical practice. To collect population-level data, smartphone applications leveraging photoplethysmography (PPG) and some medical knowledge could provide the means for it. Objective. To assess the capabilities of our smartphone application, we compared PPG (pulse rate variability (PRV)) with ECG (HRV). To have a baseline, we also compared the differences among ECG channels. Method. We took fifty parallel measurements using iPhone 6 at a 240 Hz sampling frequency and Cardiax PC-ECG devices. The correspondence between the PRV and HRV indices was investigated using correlation, linear regression, and Bland-Altman analysis. Results. High PPG accuracy: the deviation of PPG-ECG is comparable to that of ECG channels. Mean deviation between PPG-ECG and two ECG channels: RR: 0.01 ms–0.06 ms, SDNN: 0.78 ms–0.46 ms, RMSSD: 1.79 ms–1.21 ms, and pNN50: 2.43%–1.63%. Conclusions. Our iPhone application yielded good results on PPG-based PRV indices compared to ECG-based HRV indices and to differences among ECG channels. We plan to extend our results on the PPG-ECG correspondence with a deeper analysis of the different ECG channels.

Funder

European Regional Development Fund

Publisher

Hindawi Limited

Subject

Health Informatics,Biomedical Engineering,Surgery,Biotechnology

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