Camera-based heart rate variability and stress measurement from facial videos

被引：2
|
作者：
Odinaev, Ismoil [1 ]
Prae-arporn, Kunnipa [1 ]
Wong, Kwan Long [1 ]
Chin, Jing Wei [1 ]
Chan, Tsz Tai [1 ]
Goyal, Raghav [1 ]
So, Richard H. Y. [1 ]
机构：
[1] HKUST, PanopticAI, Hong Kong, Peoples R China
来源：
2022 IEEE/ACM CONFERENCE ON CONNECTED HEALTH: APPLICATIONS, SYSTEMS AND ENGINEERING TECHNOLOGIES (CHASE 2022) | 2022年
关键词：
Remote Photoplethysmography; SDNN; RMSSD; Baevsky Stress Index;
D O I：
10.1145/3551455.3564750
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Remote measurement of physiological signals through facial videos is an emerging and significant field of research. Through remote photoplethysmography (rPPG), RGB cameras can measure a person's heart rate variability (HRV) by analyzing subtle light variations on the skin. Fluctuations in HRV readings are caused by imbalances in the autonomic nervous system, such as experiencing a stressful event. This paper presents a novel method for HRV measurement from rPPG signals. We tested the model on 14 subjects participating in stress-inducing tasks. We compared our results against a contact-based ground truth device and demonstrated the potential for an off-the-shelf webcam to provide robust HRV measurement and subsequent stress estimation.
引用
收藏
页码：168 / 169
页数：2
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