Stress evaluation index based on Poincaré plot for wearable health devices

Abstract

Objective evaluation method for stress level analysis is important for disease prevention, health promotion, and improvement of quality of life. The past few years witnessed rapid progress in wearable health devices. Recently, many wearable devices are capable of measuring pulse rate (PR) data that reflect stress level. The rise of these wearable devices brings exciting possibilities of monitoring one's stress level and its variation in his/her everyday life. However, sampling characteristics of such wearable health devices, e.g., sampling frequency, are usually not comparable with those of instruments for clinic or research usage. For this reason, it is difficult to achieve stress evaluation by simply applying traditional methods, such as spectral analysis for heart rate variability, to the PR data measured with these wearable devices. This study aims to develop a novel evaluation index for stress analysis. The proposed method is based on Poincare plots of PR data, which may be measured using wearable health devices, and the proposed index is developed based on inter-point distance measure. Experiments with mental stress induction were conducted with seven subjects to validate the proposed stress evaluation index. In order to evaluate dynamic change of stress level, short-term, one-minute length of duration, PR data was investigated.