@inproceedings{0f5bb3229ce149c8ba8b37c5cdc7b2e8,
title = "cHRV uncovering daily stress dynamics using bio-signal from consumer wearables",
abstract = "Knowing the dynamics of one's daily stress is essential to effective stress management in the context of smart and connected health. However, there lacks a practical and unobtrusive means to obtain real-time and longitudinal stress information. In this paper, we attempt to derive a convenient HRV-based (heart rate variability) biomarker named cHRV, which can be used to reliably reflect stress dynamics. cHRV's key advantage lies in its low maintenance and high practicality. It can be efficiently calculated only using data from photoplethysmography (PPG) sensors, the mainstream heart rate sensor embedded in most of the consumer wearables like Apple Watch. Benefiting from the proliferation of wearables, cHRV is ideal for day-to-day stress monitoring. To evaluate its feasibility and performance, we have conducted 14 in-lab controlled experiments. The result shows that the proposed cHRV has strong correlation with the stress dynamics (r>0.95), therefore exhibits great potential for continuous stress assessment.",
keywords = "Biomarkers, Heart rate, Psychological, Stress",
author = "Tian Hao and Henry Chang and Ball, {Marion J.} and Kun Lin and Xinxin Zhu",
year = "2017",
month = jan,
day = "1",
doi = "10.3233/978-1-61499-830-3-98",
language = "English (US)",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "98--102",
booktitle = "MEDINFO 2017",
note = "16th World Congress of Medical and Health Informatics: Precision Healthcare through Informatics, MedInfo 2017 ; Conference date: 21-08-2017 Through 25-08-2017",
}