Video-based heartbeat rate measuring method using ballistocardiography

Video-based heartbeat rate measurement is a rapidly growing application in remote health monitoring. Video-based heartbeat rate measuring methods operate mainly by estimating photoplethysmography or ballistocardiography signals. These methods operate by estimating the microscopic color change in the...

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Main Authors: Hassan, M.A., Malik, A.S., Fofi, D., Saad, N.M., Ali, Y.S., Meriaudeau, F.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.19435 /
Published: Institute of Electrical and Electronics Engineers Inc. 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021636444&doi=10.1109%2fJSEN.2017.2708133&partnerID=40&md5=d539767a27f888d1b6efa6821b329948
http://eprints.utp.edu.my/19435/
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spelling utp-eprints.194352018-04-20T05:56:01Z Video-based heartbeat rate measuring method using ballistocardiography Hassan, M.A. Malik, A.S. Fofi, D. Saad, N.M. Ali, Y.S. Meriaudeau, F. Video-based heartbeat rate measurement is a rapidly growing application in remote health monitoring. Video-based heartbeat rate measuring methods operate mainly by estimating photoplethysmography or ballistocardiography signals. These methods operate by estimating the microscopic color change in the face or by estimating the microscopic rigid motion of the head/ facial skin. However, the robustness to motion artifacts caused by illumination variance and motion variance of the subject poses main challenge. We present a video-based heartbeat rate measuring framework to overcome these problems by using the principle of ballistocardiography. In this paper, we proposed a ballistocardiography model based on Newtons third law of force and dynamics of harmonic oscillation. We formulate a framework based on the ballistocardiography model to measure the rigid involuntary head motion caused by the ejection of the blood from the heart. Our proposed framework operates by estimating the motion of multivariate feature points to estimate the heartbeat rate autonomously. We evaluated our proposed framework along with existing video-based heartbeat rate measuring methods with three databases, namely; MAHNOB HCI database, human-computer interaction database, and driver health monitoring database. Our proposed framework outperformed existing methods by reporting a low mean error rate of 4.34 bpm with a standard deviation of 3.14 bpm, root mean square error of 5.29 with a high Pearson correlation coefficient of 0.91. The proposed method also operated robustly in the human-computer interaction database and driver health monitoring database by overcoming the issues related to illumination and motion variance. © 2001-2012 IEEE. Institute of Electrical and Electronics Engineers Inc. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021636444&doi=10.1109%2fJSEN.2017.2708133&partnerID=40&md5=d539767a27f888d1b6efa6821b329948 Hassan, M.A. and Malik, A.S. and Fofi, D. and Saad, N.M. and Ali, Y.S. and Meriaudeau, F. (2017) Video-based heartbeat rate measuring method using ballistocardiography. IEEE Sensors Journal, 17 (14). pp. 4544-4557. http://eprints.utp.edu.my/19435/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Video-based heartbeat rate measurement is a rapidly growing application in remote health monitoring. Video-based heartbeat rate measuring methods operate mainly by estimating photoplethysmography or ballistocardiography signals. These methods operate by estimating the microscopic color change in the face or by estimating the microscopic rigid motion of the head/ facial skin. However, the robustness to motion artifacts caused by illumination variance and motion variance of the subject poses main challenge. We present a video-based heartbeat rate measuring framework to overcome these problems by using the principle of ballistocardiography. In this paper, we proposed a ballistocardiography model based on Newtons third law of force and dynamics of harmonic oscillation. We formulate a framework based on the ballistocardiography model to measure the rigid involuntary head motion caused by the ejection of the blood from the heart. Our proposed framework operates by estimating the motion of multivariate feature points to estimate the heartbeat rate autonomously. We evaluated our proposed framework along with existing video-based heartbeat rate measuring methods with three databases, namely; MAHNOB HCI database, human-computer interaction database, and driver health monitoring database. Our proposed framework outperformed existing methods by reporting a low mean error rate of 4.34 bpm with a standard deviation of 3.14 bpm, root mean square error of 5.29 with a high Pearson correlation coefficient of 0.91. The proposed method also operated robustly in the human-computer interaction database and driver health monitoring database by overcoming the issues related to illumination and motion variance. © 2001-2012 IEEE.
format Article
author Hassan, M.A.
Malik, A.S.
Fofi, D.
Saad, N.M.
Ali, Y.S.
Meriaudeau, F.
spellingShingle Hassan, M.A.
Malik, A.S.
Fofi, D.
Saad, N.M.
Ali, Y.S.
Meriaudeau, F.
Video-based heartbeat rate measuring method using ballistocardiography
author_sort Hassan, M.A.
title Video-based heartbeat rate measuring method using ballistocardiography
title_short Video-based heartbeat rate measuring method using ballistocardiography
title_full Video-based heartbeat rate measuring method using ballistocardiography
title_fullStr Video-based heartbeat rate measuring method using ballistocardiography
title_full_unstemmed Video-based heartbeat rate measuring method using ballistocardiography
title_sort video-based heartbeat rate measuring method using ballistocardiography
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021636444&doi=10.1109%2fJSEN.2017.2708133&partnerID=40&md5=d539767a27f888d1b6efa6821b329948
http://eprints.utp.edu.my/19435/
_version_ 1741196206270316544
score 11.62408

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