Heart Rate Measurement System using Facial Video Processing

Yuvraj D. Patil, Gyankamal J. Chhajed


In recent years, new advanced technologies introduced for providing clinical health care remotely have appeared and have huge advancements experienced in new fields like telemedicine. New techniques for techniques for measuring physiological parameters out of the hospital, as well as monitoring patients automatically, have been developed. One of these parameters is the heart rate, and it is usually used by medical professionals to assist in diagnosis. For measuring heart rate there are different standard techniques available such as Electrocardiogram which is expensive and discomforts. Another commercial device is oximetry sensor that needs attachment to fingertips, is also inconvenient. For this heart rate is one of the simplest and most important cardiovascular parameter which is identified as an independent risk factor. During the cardiac cycle,because of volumetric changes in the facial blood vessels, the path length of the incident ambient light is modified. And the timing of cardiovascular events are indicated because of the subsequent changes in the amount of reflected light. By recording facial image region with a webcam, the RGB color sensors pick up a mixture of the reflected photoplethysmographic(PPG) signal along with other sources of fluctuations in light due to artifacts such as changes in ambient lighting and motion conditions. These observed signals from the red, green and blue color sensors are used for the further process. Applying Signal Separation algorithm techniques on those signals and green band signals are extracted. In this contribution Independent Component Analysis(ICA) algorithm is used for getting accurate results. After extracting green band signals select the Region of Interest(ROI) by using bucketing technique. And finally, obtain Inter Beat Interval(IBI) and calculate heart rate..

Full Text:



L. Septiana, F.Hariyanto and K.P.Lin, Comparison of Independent Component

Analysis (ICA) Algorithm for Heart Rate Measurement Based on

Facial Imaging, in Springer,2015.

S. Cook, M. Togni, M. C. Schaub, P. Wenaweser, and O. M. Hess, High

heart rate: a cardiovascular riskfactor?, Eur. Heart J. 27(20),23872393


M.Z. Poh, D.J. McDuff, and R.W. Picard, Noncontact, automated cardiac

pulse measurements using video imaging and blind source separation,

M.Z. Poh, D. McDuff, and R. Picard,A medical mirror for non-contact

health monitoring, in ACM SIGGRAPH 2011 Emerging Technologies.

ACM, 2011, p. 2.

H. Trotter,An elementary proof of the central limit theorem, Math. 10(1),


M. Garbey, N. Sun, A. Merla, and I. Pavlidis,Contact-free measurement

of cardiac pulse based on the analysis of thermal imagery, IEEE Trans.

Biomed. Eng. 54(8), 14181426 (2007).

C. Takano and Y. Ohta, Heart rate meaurement based on a timelapse

image, Med. Eng. Phys. 29(8), 853857 (2007).

T. W. Lee, M. S. Lewicki, and T. J. Sejnowski,ICA mixture models for

unsupervised classification of nongaussian classes and automatic context

switching in blind signal separation, IEEE Trans. Pattern Anal. Mach.

Intell. 22(10), 10781089 (2000).

T. Pursche, J. Krajewski, and R. Moeller,Video-based heart rate measurement

from human faces, in Proceedings of IEEE International Conference

on Consumer Electronics (IEEE, 2012), pp. 544545).

S. Xu, L. Sun, and G. K. Rohde,Robust eficient estimation of heart rate

pulse from video, Biomed. Opt. Express 5(4), 11241135 (2014).

Y. P. Yu, B. H. Kwan, C. L. Lim, S. L. Wong, and P. Raveendran,Videobased

heart rate measurement using short-time Fourier transform, in

Proceedings of International Symposium on Intelligent Signal Processing

and Communications Systems, (IEEE, 2013), pp. 704707.

Y. P. Yu, P. Raveendran, and C. L. Lim, Heart rate estimation from facial

images using filter bank, in Proceedings of 6th International Symposium

on Communications, Control and Signal Processing (IEEE, 2014), pp.

N. Tsumura, O. Nobutoshi, S. Kayoko, S. Mitsuhiro, S. Hideto, N.

Hirohide, A. Syuuichi, H. Kimihiko, and Y. Miyake, Image-based skin

color and texture analysis/synthesis by extracting hemoglobin and melanin

information in the skin, in Proceedings of ACM Transactions on Graphics

(TOG) (ACM, 2003), pp. 770779.

Shruti Madan Kshirsagar, Gyankamal J. Chhajed, Heart Rate, Respiration

Rate and Oxygen Saturation Level Monitoring from Video Recording

by Smart phone camera, in IJEDR(2014),Volume 2,Issue 2.


  • There are currently no refbacks.


Copyright © IJETT, International Journal on Emerging Trends in Technology