VitaMon: Measuring heart rate variability using smartphone front camera

Sinh Huynh, Rajesh Krishna Balan, Jeong Gil Ko, Youngki Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationSenSys 2019 - Proceedings of the 17th Conference on Embedded Networked Sensor Systems
EditorsMi Zhang
PublisherAssociation for Computing Machinery
Pages1-14
Number of pages14
ISBN (Electronic)9781450369503
DOIs
Publication statusPublished - 2019 Nov 10
Event17th ACM Conference on Embedded Networked Sensor Systems, SenSys 2019 - New York, United States
Duration: 2019 Nov 102019 Nov 13

Publication series

NameSenSys 2019 - Proceedings of the 17th Conference on Embedded Networked Sensor Systems

Conference

Conference17th ACM Conference on Embedded Networked Sensor Systems, SenSys 2019
Country/TerritoryUnited States
CityNew York
Period19/11/1019/11/13

Bibliographical note

Publisher Copyright:
© 2019 ACM.

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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