Efficient real-time camera based estimation of heart rate and its variability

Conference paper (2019)

Authors

A.A. Gudi Vicarious Perception Technologies, Pattern Recognition and Bioinformatics - EEMCS
M. Bittner Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering , Vicarious Perception Technologies
Roelof Lochmans Eindhoven University of Technology
J.C. van Gemert Pattern Recognition and Bioinformatics - EEMCS
Research Group
Pattern Recognition and Bioinformatics (EEMCS) (TU Delft)
Copyright: © 2019 A.A. Gudi, M. Bittner, Roelof Lochmans, J.C. van Gemert
DOI: https://doi.org/10.1109/ICCVW.2019.00196
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Published Date

2019

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Pattern Recognition and Bioinformatics

Abstract

Remote photo-plethysmography (rPPG) uses a remotely placed camera to estimating a person's heart rate (HR). Similar to how heart rate can provide useful information about a person's vital signs, insights about the underlying physio/psychological conditions can be obtained from heart rate variability (HRV). HRV is a measure of the fine fluctuations in the intervals between heart beats. However, this measure requires temporally locating heart beats with a high degree of precision. We introduce a refined and efficient real-time rPPG pipeline with novel filtering and motion suppression that not only estimates heart rate more accurately, but also extracts the pulse waveform to time heart beats and measure heart rate variability. This method requires no rPPG specific training and is able to operate in real-time. We validate our method on a self-recorded dataset under an idealized lab setting, and show state-of-the-art results on two public dataset with realistic conditions (VicarPPG and PURE).

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