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Extraction of heart rate variability from smartphone photoplethysmograms.

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

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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Related in: MedlinePlus

An example of outlier removal. (a) A raw smartphone photoplethysmogram with abrupt change. (b) The difference of the signal in panel (a). The circle shows the location of the outlier. (c) The outlier was removed and replaced with a new value using cubic spline interpolation. (d) The new smartphone photoplethysmogram without abrupt change.
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fig1: An example of outlier removal. (a) A raw smartphone photoplethysmogram with abrupt change. (b) The difference of the signal in panel (a). The circle shows the location of the outlier. (c) The outlier was removed and replaced with a new value using cubic spline interpolation. (d) The new smartphone photoplethysmogram without abrupt change.

Mentions: Table 3 shows the Bland-Altman analysis of HRV parameters derived from the smartphone and the ECG. For the sake of simplicity, we speak of good/moderate agreement if three of the five algorithms were in good/moderate agreement. It was found that all the time-domain parameters showed insufficient agreements (BAR ≥ 20%), but the AVNN showed excellent agreement (BAR < 1%), indicating that smartphone-derived HR can be a surrogate of ECG-derived HR. This result was in line with Gregoski et al.'s [20] and Matsumura and Yamakoshi's [21]. It was also found that all the frequency-domain parameters were in moderate agreement (BAR < 20%) except for TP and nLF which were in good agreement (BAR < 10%). TP, VLF, HF, and nHF were overestimated (bias > 0), while LF, LF/HF, and nLF were underestimated (bias < 0), implying that the smartphone-derived HRV contains more noise, which can be observed in detail in Figure 1. For nonlinear parameters, SD2 showed good agreement (BAR < 10%) and SD1 showed insufficient agreement (BAR ≥ 20%).


Extraction of heart rate variability from smartphone photoplethysmograms.

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

An example of outlier removal. (a) A raw smartphone photoplethysmogram with abrupt change. (b) The difference of the signal in panel (a). The circle shows the location of the outlier. (c) The outlier was removed and replaced with a new value using cubic spline interpolation. (d) The new smartphone photoplethysmogram without abrupt change.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4309304&req=5

fig1: An example of outlier removal. (a) A raw smartphone photoplethysmogram with abrupt change. (b) The difference of the signal in panel (a). The circle shows the location of the outlier. (c) The outlier was removed and replaced with a new value using cubic spline interpolation. (d) The new smartphone photoplethysmogram without abrupt change.
Mentions: Table 3 shows the Bland-Altman analysis of HRV parameters derived from the smartphone and the ECG. For the sake of simplicity, we speak of good/moderate agreement if three of the five algorithms were in good/moderate agreement. It was found that all the time-domain parameters showed insufficient agreements (BAR ≥ 20%), but the AVNN showed excellent agreement (BAR < 1%), indicating that smartphone-derived HR can be a surrogate of ECG-derived HR. This result was in line with Gregoski et al.'s [20] and Matsumura and Yamakoshi's [21]. It was also found that all the frequency-domain parameters were in moderate agreement (BAR < 20%) except for TP and nLF which were in good agreement (BAR < 10%). TP, VLF, HF, and nHF were overestimated (bias > 0), while LF, LF/HF, and nLF were underestimated (bias < 0), implying that the smartphone-derived HRV contains more noise, which can be observed in detail in Figure 1. For nonlinear parameters, SD2 showed good agreement (BAR < 10%) and SD1 showed insufficient agreement (BAR ≥ 20%).

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.

Show MeSH
Related in: MedlinePlus