Abstract—To examine the basic characteristics of Pulse Rate Variability (PRV) during work, pulse wave signals during work hours were recorded by wristband-type wearable sensors in 8 office workers for 1-3 months together with the signals of physical activity, skin temperature, and the amount of conversation and with subjective emotions. A total of 1,544 hours of data were obtained. Pulse rate increased during physical activity and decreased during dozing. Although High Frequency (HF) component of Heart Rate Variability (HRV) is known as an index of parasympathetic function and increases during rest and sleep, HF amplitude of PRV during work increased with mild physical movement detected at the wrist and decreased during dozing. Factor analysis revealed that there were two factors, reflecting slow and fast variations, respectively, among the indices of PRV indices (the amplitude of very low, low, and HF components and their standard deviations). While factor 1 score decreased during walking and increased with mild physical movement, it also increased when subjects reported angry emotion. While factor 2 score also increased with mild physical movement, it also increased with happiness and relax compared with sad and angry emotions. This study suggests on one hand that HF amplitude of PRV at least that obtained through wristband-type sensors during work cannot be used as the indices of parasympathetic function and resting. On the other hand, PRV may provide unique information from that of HRV. The HF amplitude of PRV may reflect positive feeling for work, while an increase in slow variation of PRV may reflect their conflict and dissatisfaction during work.

 

Index Terms—wearable sensor, biosignal, pulse wave, pulse rate variability, heart rate variability, work, job stress, physical activity, emotion
 

Cite: Emi Yuda, Junichiro Hayano, Tetsuya Tanabiki, Shinichiro Iwata, and Katsumi Abe, "Unique Characteristics of Heart Rate Variability Obtained from Pulse Wave Signals during Work," Journal of Advances in Information Technology, Vol. 10, No. 4, pp. 131-136, November 2019. doi: 10.12720/jait.10.4.131-136