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Non-contact Physiological Parameters Extraction Using Camera

  • Conference paper
Internet of Things. IoT Infrastructures (IoT360 2015)

Abstract

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.

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Notes

  1. 1.

    http://stressmedicin.se/neuro-psykofysilogiska-matsystem/cstress-matsystem/.

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Acknowledgement

The authors would like to acknowledge the Swedish Knowledge Foundation (KKS), Swedish Governmental agency for innovation Systems (VINNOVA), Volvo Car Corporation, The Swedish National Road and Transport Research Institute, Autoliv AB, Hök instrument AB, and Prevas AB Sweden for their support of the research projects in this area.

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Correspondence to Hamidur Rahman .

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Rahman, H., Ahmed, M.U., Begum, S. (2016). Non-contact Physiological Parameters Extraction Using Camera. In: Mandler, B., et al. Internet of Things. IoT Infrastructures. IoT360 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 169. Springer, Cham. https://doi.org/10.1007/978-3-319-47063-4_47

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  • DOI: https://doi.org/10.1007/978-3-319-47063-4_47

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47062-7

  • Online ISBN: 978-3-319-47063-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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