TY  - JOUR
Y1  - 2017///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021636444&doi=10.1109%2fJSEN.2017.2708133&partnerID=40&md5=d539767a27f888d1b6efa6821b329948
A1  - Hassan, M.A.
A1  - Malik, A.S.
A1  - Fofi, D.
A1  - Saad, N.M.
A1  - Ali, Y.S.
A1  - Meriaudeau, F.
JF  - IEEE Sensors Journal
VL  - 17
IS  - 14
N2  - 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.
KW  - Correlation methods; Database systems; Health; Mean square error; Photoplethysmography
KW  -  Ballistocardiography; Ballistocardiography signals; Harmonic oscillation; Non-contact; Pearson correlation coefficients; Remote health monitoring; Root mean square errors; Video analytics
KW  -  Human computer interaction
ID  - scholars8508
SN  - 1530437X
PB  - Institute of Electrical and Electronics Engineers Inc.
EP  - 4557
AV  - none
N1  - cited By 22
SP  - 4544
TI  - Video-based heartbeat rate measuring method using ballistocardiography
ER  -