mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
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
Non-contact heart rate monitoring using lab color space
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
2016 (English)In: Studies in Health Technology and Informatics, 2016, Vol. 224, 46-53 p.Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

Research progressing during the last decade focuses more on non-contact based systems to monitor Heart Rate (HR) which are simple, low-cost and comfortable to use. Most of the non-contact based systems are using RGB videos which is suitable for lab environment. However, it needs to progress considerably before they can be applied in real life applications. As luminance (light) has significance contribution on RGB videos HR monitoring using RGB videos are not efficient enough in real life applications in outdoor environment. This paper presents a HR monitoring method using Lab color facial video captured by a webcam of a laptop computer. Lab color space is device independent and HR can be extracted through facial skin color variation caused by blood circulation considering variable environmental light. Here, three different signal processing methods i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA) have been applied on the color channels in video recordings and blood volume pulse (BVP) has been extracted from the facial regions. In this study, HR is subsequently quantified and compare with a reference measurement. The result shows that high degrees of accuracy have been achieved compared to the reference measurements. Thus, this technology has significant potential for advancing personal health care, telemedicine and many real life applications such as driver monitoring.

Place, publisher, year, edition, pages
2016. Vol. 224, 46-53 p.
Keyword [en]
Heart rate, Lab color space, Signal processing, blood volume, circulation, driver, face, Fourier transformation, human, independent component analysis, luminance, monitoring, principal component analysis, quantitative study, skin color, telemedicine, videorecording
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-32175DOI: 10.3233/978-1-61499-653-8-46ISI: 000385238500008Scopus ID: 2-s2.0-84973483708ISBN: 9781614996521 (print)OAI: oai:DiVA.org:mdh-32175DiVA: diva2:941968
Conference
13th International Conference on Wearable Micro and Nano Technologies for Personalised Health, pHealth 2016; Heraklion, Crete; Greece; 29 May 2016 through 31 May 2016; Code 121852
Available from: 2016-06-23 Created: 2016-06-23 Last updated: 2017-01-25Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Rahman, HamidurAhmed, Mobyen UddinBegum, Shahina
By organisation
Embedded Systems
Medical Engineering

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 5 hits
CiteExportLink to record
Permanent link

Direct link
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