TY - GEN
T1 - Personalized health monitoring via vital sign measurements leveraging motion sensors on AR/VR headsets
AU - Zhang, Tianfang
AU - Shi, Cong
AU - Zhao, Tianming
AU - Ye, Zhengkun
AU - Walker, Payton
AU - Saxena, Nitesh
AU - Wang, Yan
AU - Chen, Yingying
N1 - Publisher Copyright:
© 2022 Owner/Author.
PY - 2022/6/27
Y1 - 2022/6/27
N2 - Augmented reality/virtual reality (AR/VR) headsets have attracted millions of users and gained predictable popularity. However, long-period usage of immersive technology may lead to health issues (e.g., cybersickness, anxiety). In this poster, we design a low-cost and personalized healthcare monitoring system grounded on vital sign tracking (i.e., breathing and heartbeat rate tracking), by exploiting built-in AR/VR motion sensors. The key insight is that the conductive vibrations induced by chest and heart movements can propagate through the user's cranial bones, thereby vibrating the AR/VR headset mounted on the user's head. To realize this system, we design signal processing techniques to cancel the human motions and derive the periods of breathing and heartbeat through frequency-domain analyses. We further design a user identification scheme based on respiratory and cardiac biometrics, which works with vital sign monitoring to provide personalized healthcare recommendations. Our experiment shows that the proposed scheme can achieve less than 5.7% error rate on breathing/heartbeat rate estimation and 95% accuracy on user identification.
AB - Augmented reality/virtual reality (AR/VR) headsets have attracted millions of users and gained predictable popularity. However, long-period usage of immersive technology may lead to health issues (e.g., cybersickness, anxiety). In this poster, we design a low-cost and personalized healthcare monitoring system grounded on vital sign tracking (i.e., breathing and heartbeat rate tracking), by exploiting built-in AR/VR motion sensors. The key insight is that the conductive vibrations induced by chest and heart movements can propagate through the user's cranial bones, thereby vibrating the AR/VR headset mounted on the user's head. To realize this system, we design signal processing techniques to cancel the human motions and derive the periods of breathing and heartbeat through frequency-domain analyses. We further design a user identification scheme based on respiratory and cardiac biometrics, which works with vital sign monitoring to provide personalized healthcare recommendations. Our experiment shows that the proposed scheme can achieve less than 5.7% error rate on breathing/heartbeat rate estimation and 95% accuracy on user identification.
KW - AR/VR headsets
KW - user identification
KW - vital sign monitoring
UR - http://www.scopus.com/inward/record.url?scp=85134014654&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134014654&partnerID=8YFLogxK
U2 - 10.1145/3498361.3538768
DO - 10.1145/3498361.3538768
M3 - Conference contribution
AN - SCOPUS:85134014654
T3 - MobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services
SP - 529
EP - 530
BT - MobiSys 2022 - Proceedings of the 2022 20th Annual International Conference on Mobile Systems, Applications and Services
PB - Association for Computing Machinery, Inc
T2 - 20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022
Y2 - 27 June 2022 through 1 July 2022
ER -