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Proceedings Paper

Real-time heart rate measurement for multi-people using compressive tracking
Author(s): Lingling Liu; Yuejin Zhao; Ming Liu; Lingqin Kong; Liquan Dong; Feilong Ma; Zongguang Pang; Zhi Cai; Yachu Zhang; Peng Hua; Ruifeng Yuan
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Paper Abstract

The rise of aging population has created a demand for inexpensive, unobtrusive, automated health care solutions. Image PhotoPlethysmoGraphy(IPPG) aids in the development of these solutions by allowing for the extraction of physiological signals from video data. However, the main deficiencies of the recent IPPG methods are non-automated, non-real-time and susceptible to motion artifacts(MA). In this paper, a real-time heart rate(HR) detection method for multiple subjects simultaneously was proposed and realized using the open computer vision(openCV) library, which consists of getting multiple subjects’ facial video automatically through a Webcam, detecting the region of interest (ROI) in the video, reducing the false detection rate by our improved Adaboost algorithm, reducing the MA by our improved compress tracking(CT) algorithm, wavelet noise-suppression algorithm for denoising and multi-threads for higher detection speed. For comparison, HR was measured simultaneously using a medical pulse oximetry device for every subject during all sessions. Experimental results on a data set of 30 subjects show that the max average absolute error of heart rate estimation is less than 8 beats per minute (BPM), and the processing speed of every frame has almost reached real-time: the experiments with video recordings of ten subjects under the condition of the pixel resolution of 600× 800 pixels show that the average HR detection time of 10 subjects was about 17 frames per second (fps).

Paper Details

Date Published: 19 September 2017
PDF: 11 pages
Proc. SPIE 10396, Applications of Digital Image Processing XL, 1039621 (19 September 2017); doi: 10.1117/12.2272644
Show Author Affiliations
Lingling Liu, Beijing Institute of Technology (China)
Yuejin Zhao, Beijing Institute of Technology (China)
Ming Liu, Beijing Institute of Technology (China)
Lingqin Kong, Beijing Institute of Technology (China)
Liquan Dong, Beijing Institute of Technology (China)
Feilong Ma, Beijing Institute of Technology (China)
Zongguang Pang, Beijing Institute of Technology (China)
Zhi Cai, Beijing Institute of Technology (China)
Yachu Zhang, Beijing Institute of Technology (China)
Peng Hua, Beijing Institute of Technology (China)
Ruifeng Yuan, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 10396:
Applications of Digital Image Processing XL
Andrew G. Tescher, Editor(s)

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