Approach to develop a remote vital sign estimation method using facial videos
Develop a vital sign measurement method from instantaneous estimations by maximizing quasi-periodic information
Develop a method for heart rate estimation method at low-light situations
Investigate the application of remote heart rate estimation for infectious disease screening in public spaces
We present a novel health monitoring method by estimating heart and respiratory rates using an RGB camera. The method mainly operates by using the green spectrum of the RGB camera to generate a multivariate PPG signal to perform multivariate de-noising on the video signal to extract the resultant PPG signal. A periodicity-based voting scheme was used to measure the heart rate and respiratory rates from the estimated PPG signal. Our proposed method operated robustly during the experiments and outperformed the state of the art heart rate measuring methods by compensating for the effects of the naturalistic environment.
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.
The paper presents a feasibility study for heart rate measurement using a digital camera to perform health monitoring. The feasibility study investigates the reliability of the state of the art heart rate measuring methods in realistic situations. Therefore, an experiment was designed and carried out on 45 subjects to investigate the effects caused by illumination, motion, skin tone, and distance variance. The experiment was conducted for two main scenarios; the human-computer interaction scenario and health monitoring scenario. The human-computer scenario investigated the effects caused by illumination variance, motion variance, and skin tone variance. The health monitoring scenario investigates the feasibility of health monitoring at public spaces (i.e. airports, subways, malls).
M. A. Hassan, et al.,Towards health monitoring using remote heart rate measurement using a digital camera: A feasibility study, Measurement, 2020
M. A. Hassan, et al., Novel health monitoring method using an RGB camera, Biomedical Optics Express, 2017
M. A. Hassan, Video-based heartbeat rate measuring method using ballistocardiography, IEEE Sensors, 2017
M. A. Hassan, et al., Heart rate estimation using facial video: a review, Biomedical Signals, and Controls, 2017
M. A. Hassan, et al., Effect of motion artifact on digital camera based heart rate measurement, EMBC 2017
M. A. Hassan, et al., Optimal source selection for image photoplethysmography, IEEE IMTC 2016
M. A. Hassan, et al., Towards Health Monitoring in Visual Surveillance, IEEE ICIAS 2016
Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7126755/
December 17th 2020
