eprintid: 8508
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/85/08
datestamp: 2023-11-09 16:20:25
lastmod: 2023-11-09 16:20:25
status_changed: 2023-11-09 16:12:49
type: article
metadata_visibility: show
creators_name: Hassan, M.A.
creators_name: Malik, A.S.
creators_name: Fofi, D.
creators_name: Saad, N.M.
creators_name: Ali, Y.S.
creators_name: Meriaudeau, F.
title: Video-based heartbeat rate measuring method using ballistocardiography
ispublished: pub
keywords: Correlation methods; Database systems; Health; Mean square error; Photoplethysmography, Ballistocardiography; Ballistocardiography signals; Harmonic oscillation; Non-contact; Pearson correlation coefficients; Remote health monitoring; Root mean square errors; Video analytics, Human computer interaction
note: cited By 22
abstract: 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.
date: 2017
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021636444&doi=10.1109%2fJSEN.2017.2708133&partnerID=40&md5=d539767a27f888d1b6efa6821b329948
id_number: 10.1109/JSEN.2017.2708133
full_text_status: none
publication: IEEE Sensors Journal
volume: 17
number: 14
pagerange: 4544-4557
refereed: TRUE
issn: 1530437X
citation:   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.  ISSN 1530437X