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Non-Contact Physiological Parameters Extraction Using Camera
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. (Intelligent Future technology)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: Internet of Things. IoT Infrastructures: Second International Summit, IoT 360° 2015 Rome, Italy, October 27–29, 2015. Revised Selected Papers, Part I, 2016, Vol. 169, 448-453 p.Conference paper, Published paper (Refereed)
Abstract [en]

Physiological parameters such as Heart Rate (HR), Beat-to-Beat Interval (IBI) and Respiration Rate (RR) are vital indicators of people’s physiological state and important to monitor. However, most of the measurements methods are connection based, i.e. sensors are connected to the body which is often complicated and requires personal assistance. This paper proposed a simple, low-cost and non-contact approach for measuring multiple physiological parameters using a web camera in real time. Here, the heart rate and respiration rate are obtained through facial skin colour variation caused by body blood circulation. Three different signal processing methods such as Fast Fourier Transform (FFT), independent component analysis (ICA) and Principal component analysis (PCA) have been applied on the colour channels in video recordings and the blood volume pulse (BVP) is extracted from the facial regions. HR, IBI and RR are subsequently quantified and compared to corresponding reference measurements. High degrees of agreement are achieved between the measurements across all physiological parameters. This technology has significant potential for advancing personal health care and telemedicine. 

Place, publisher, year, edition, pages
2016. Vol. 169, 448-453 p.
Series
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, ISSN 1867-8211 ; 169
Keyword [en]
Autonomous Car Driver Monitoring Physiological signals Camera Non contact
National Category
Other Engineering and Technologies
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:mdh:diva-30021DOI: 10.1007/978-3-319-47063-4_47ISI: 000398616500047Scopus ID: 2-s2.0-85000783926ISBN: 978-331947062-7 (print)OAI: oai:DiVA.org:mdh-30021DiVA: diva2:885633
Conference
Second International Summit, IoT 360° 2015 Rome, Italy, October 27–29, 2015. 1st Workshop on Embedded Sensor Systems for Health.
Projects
ESS-H - Embedded Sensor Systems for Health Research ProfileVDM - Vehicle Driver MonitoringSafeDriver: A Real Time Driver's State Monitoring and Prediction System
Available from: 2015-12-20 Created: 2015-12-18 Last updated: 2017-01-25Bibliographically approved

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Rahman, HamidurAhmed, Mobyen UddinBegum, Shahina

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Citation style
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