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Vision-Based Remote Heart Rate Variability Monitoring using Camera
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1547-4386
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3802-4721
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1212-7637
2017 (English)In: 4th EAI International Conference on IoT Technologies for HealthCare HealthyIOT'17, 2017Conference paper, Published paper (Refereed)
Abstract [en]

Heart Rate Variability (HRV) is one of the important physiological parameter which is used to early detect many fatal disease. In this paper a non-contact remote Heart Rate Variability (HRV) monitoring system is developed using the facial video based on color variation of facial skin caused by cardiac pulse. The lab color space of the facial video is used to extract color values of skin and signal processing algorithms i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA), Principle Component Analysis (PCA) are applied to monitor HRV. First, R peak is detected from the color variation of skin and then Inter-Beat-Interval (IBI) is calculated for every consecutive R-R peak. HRV features are then calculated based on IBI both in time and frequency domain. MySQL and PHP programming language is used to store, monitor and display HRV parameters remotely. In this study, HRV is quantified and compared with a reference measurement where a high degree of similarities is achieved. This technology has significant potential for advancing personal health care especially for telemedicine.

Place, publisher, year, edition, pages
2017.
Keyword [en]
Physiological signals, Heart Rate, Inter-beat-Interval, Heart-Rate-Variability, Non-contact, Remote Monitoring.
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-37072OAI: oai:DiVA.org:mdh-37072DiVA: diva2:1153827
Conference
4th EAI International Conference on IoT Technologies for HealthCare HealthyIOT'17, 24 Oct 2017, Angers, France
Projects
SafeDriver: A Real Time Driver's State Monitoring and Prediction System
Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2017-10-31Bibliographically approved

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Rahman, HamidurAhmed, Mobyen UddinBegum, Shahina

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf