Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
11-2019
Abstract
We present VitaMon, a mobile sensing system that can measure the inter-heartbeat interval (IBI) from the facial video captured by a commodity smartphone's front camera. The continuous IBI measurement is used to compute heart rate variability (HRV), one of the most important markers of the autonomic nervous system (ANS) regulation. The underlying idea of VitaMon is that video recording of human face contains multiple cardiovascular pulse signals with different phase shift. Our measurement on 10 participants shows the significant time delay (36.79 ms) between the pulse signals measured at the jaw region and forehead region. VitaMon leverages deep neural network models to extract both spatial and temporal information of the video to reconstruct a pulse waveform signal that is optimized for estimating IBI. We evaluated VitaMon with a dataset collected from 30 participants under various conditions involving different light intensity levels and motion artifacts. With the 15 fps video input (66.67 ms time resolution), VitaMon can measure IBI with an average error of 14.26 ms and 21.65 ms using personal and general model respectively. HRV features including geometry Poincare plot, time- and frequency-domain features extracted from the IBI measurement all have high correlation with the reference signal.
Keywords
Heart Rate Variability, Photoplethysmography (PPG), Remote PPG, Mobile Sensing
Discipline
Computer Sciences | Health Information Technology | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
SenSys '19: Proceedings of the 17th Conference on Embedded Networked Sensor Systems, New York, November 10-13
First Page
1
Last Page
14
ISBN
9781450369503
Identifier
10.1145/3356250.3360036
Publisher
ACM
City or Country
New York
Citation
HUYNH, Sinh; BALAN, Rajesh Krishna; KO, JeongGil; and LEE, Youngki.
VitaMon: Measuring heart rate variability using smartphone front camera. (2019). SenSys '19: Proceedings of the 17th Conference on Embedded Networked Sensor Systems, New York, November 10-13. 1-14.
Available at: https://ink.library.smu.edu.sg/sis_research/4933
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/3356250.3360036