Extraction of heart rate variability from smartphone photoplethysmograms.

Peng RC, Zhou XL, Lin WH, Zhang YT - Comput Math Methods Med (2015)

Related In: Results  -  Collection

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fig4: Bland-Altman plots of HRV parameters derived from the smartphone and the electrocardiograph. For each plot, the horizontal axis represents the mean of HRV parameters derived from smartphone and electrocardiograph, while the vertical axis represents the difference between HRV parameters derived from smartphone and electrocardiograph. The five columns correspond to five different algorithms: PP, peak point; VP, valley point; M1D, maximum first derivative; M2D, maximum second derivative; and TI, tangent intersection. LF, low frequency power; HF, high frequency power; LF/HF, ratio of LF to HF; nLF, normalized LF = LF/(TP − VLF); and nHF, normalized HF = HF/(TP − VLF).
Mentions: As shown in Table 3, a total number of 7 parameters (AVNN, TP, VLF, LF, HF, nLF, and nHF) were within the acceptable limits. Figure 4 shows the Bland-Altman plots of different frequency components of HRV which are commonly used for assessing the autonomic functions. It was found that the limits of agreement for LF, HF, nLF, and nHF were all within their corresponding acceptable limits, meaning that the discrepancies between the smartphone PPG and the ECG for LF, HF, nLF, and nHF were not considerable. It was also found that the lower limit of agreement for LF/HF is out of the range of acceptable limits.

Bottom Line: 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 results showed that M2D and TI algorithms had the best performance.These results suggest that the smartphone might be used for HRV measurement.

View Article: PubMed Central - PubMed

Affiliation: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 1068 Xueyuan Road, Xili Nanshan, Shenzhen, Guangdong 518055, China ; Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, 1068 Xueyuan Road, Xili Nanshan, Shenzhen, Guangdong 518055, China ; Key Laboratory for Health Informatics of the Chinese Academy of Sciences (HICAS), 1068 Xueyuan Road, Xili Nanshan, Shenzhen, Guangdong 518055, China.

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 (r > 0.7, P < 0.001) 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.

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