Estimating heart rate variability using facial video photoplethysmography: a pilot validation study

Abstract

Video photoplethysmography (vPPG) uses a digital camera to detect pulsations in the blood vessels of the skin, which can be used to estimate various physiological parameters. The aim of this study was to investigate the accuracy and precision of heart rate variability (HRV) indices estimated using a smartphone camera and facial vPPG technology. The study group included 35 healthy volunteers (17 females) with median age 25 years (range 20–42 years). The subjects were in a sitting position, keeping their heads relatively still. A smartphone mounted on a tripod was used to acquire 1-min video recordings of participants’ faces. In parallel, a 1-lead chest electrocardiogram (ECG) was recorded to obtain reference values of two analysed time-domain HRV indices: SDNN and lnRMSSD. For SDNN, the median absolute error was 3.0 ms (7.1% in relative terms), and the root-mean-square error was 4.5 ms (15.7%). For lnRMSSD, the median absolute error was 0.20 (5.6%) and the root-mean-square error was 0.31 (9.9%). Correlations between the vPPG-based and ECG-based HRV values were strong, with the Pearson correlation coefficient of 0.98 for SDNN and 0.88 for lnRMSSD ( P  < 0.001 in both cases). In a young, white population, the tested vPPG technology estimated the HRV indices (SDNN and lnRMSSD) with good overall accuracy, with a slight systematic overestimation, especially for low values. The results should be confirmed in a larger study with greater diversity in age and skin tone.