Effect of Missing Inter-Beat Interval Data on Heart Rate Variability Analysis Using Wrist-Worn Wearables.

Abstract

Most of the wrist-worn devices on the market provide a continuous heart rate measurement function using photoplethysmography, but have not yet provided a function to measure the continuous heart rate variability (HRV) using beat-to-beat pulse interval. The reason for such is the difficulty of measuring a continuous pulse interval during movement using a wearable device because of the nature of photoplethysmography, which is susceptible to motion noise. This study investigated the effect of missing heart beat interval data on the HRV analysis in cases where pulse interval cannot be measured because of movement noise. First, we performed simulations by randomly removing data from the RR interval of the electrocardiogram measured from 39 subjects and observed the changes of the relative and normalized errors for the HRV parameters according to the total length of the missing heart beat interval data. Second, we measured the pulse interval from 20 subjects using a wrist-worn device for 24h and observed the error value for the missing pulse interval data caused by the movement during actual daily life. The experimental results showed that mean NN and RMSSD were the most robust for the missing heart beat interval data among all the parameters in the time and frequency domains. Most of the pulse interval data could not be obtained during daily life. In other words, the sample number was too small for spectral analysis because of the long missing duration. Therefore, the frequency domain parameters often could not be calculated, except for the sleep state with little motion. The errors of the HRV parameters were proportional to the missing data duration in the presence of missing heart beat interval data. Based on the results of this study, the maximum missing duration for acceptable errors for each parameter is recommended for use when the HRV analysis is performed on a wrist-worn device.