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Computational and Mathematical Methods in Medicine
Volume 2015, Article ID 516826, 11 pages
http://dx.doi.org/10.1155/2015/516826
Research Article

Extraction of Heart Rate Variability from Smartphone Photoplethysmograms

1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Road, Xili Nanshan, Shenzhen, Guangdong 518055, China
2Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Road, Xili Nanshan, Shenzhen, Guangdong 518055, China
3Key Laboratory for Health Informatics of the Chinese Academy of Sciences (HICAS), 1068 Xueyuan Road, Xili Nanshan, Shenzhen, Guangdong 518055, China
4Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong

Received 9 October 2014; Accepted 21 December 2014

Academic Editor: Dong Song

Copyright © 2015 Rong-Chao Peng et al. 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.

Abstract

Heart rate variability (HRV) is a useful clinical tool for autonomic function assessment and cardiovascular diseases diagnosis. It is traditionally calculated from a dedicated medical electrocardiograph (ECG). In this paper, we demonstrate that HRV can also be extracted from photoplethysmograms (PPG) obtained by the camera of a smartphone. Sixteen HRV parameters, including time-domain, frequency-domain, and nonlinear parameters, were calculated from PPG captured by a smartphone for 30 healthy subjects and were compared with those derived from ECG. The statistical results showed that 14 parameters (AVNN, SDNN, CV, RMSSD, SDSD, TP, VLF, LF, HF, LF/HF, nLF, nHF, SD1, and SD2) from PPG were highly correlated (, ) with those from ECG, and 7 parameters (AVNN, TP, VLF, LF, HF, nLF, and nHF) from PPG were in good agreement with those from ECG within the acceptable limits. In addition, five different algorithms to detect the characteristic points of PPG wave were also investigated: peak point (PP), valley point (VP), maximum first derivative (M1D), maximum second derivative (M2D), and tangent intersection (TI). The results showed that M2D and TI algorithms had the best performance. These results suggest that the smartphone might be used for HRV measurement.