Remote measurement of heart rate from facial video in different scenarios

Pulmonary rehabilitation is an effective treatment for people with chronic obstructive pulmonary disease. However, access to these services is limited especially in rural and remote areas. Telerehabilitation has the potential to deliver pulmonary rehabilitation programs to these communities. The aim of this study was threefold: to establish the technical feasibility of transmitting real-time pulse oximetry data, determine the validity of remote measurements compared to conventional face-to-face measures, and evaluate the participants’ perception of the usability of the technology. Thirty-seven healthy individuals participated in a single remote pulmonary rehabilitation exercise session, conducted using the eHAB telerehabilitation system. Validity was assessed by comparing the participant's oxygen saturation and heart rate with the data set received at the therapist’s remote location. There was an 80% exact agreement between participant and therapist data sets. The mean absolute difference and Bland and Altman’s limits of agreement fell within the minimum clinically important difference for both oxygen saturation and heart rate values. Participants found the system easy to use and felt confident that they would be able to use it at home. Remote measurement of pulse oximetry data for a pulmonary rehabilitation exercise session was feasible and valid when compared to conventional face-to-face methods.

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Is It Possible to Estimate Average Heart Rate from Facial Thermal Imaging?

Engineering Proceedings ◽

10.3390/engproc2021008010 ◽

2021 ◽

Vol 8 (1) ◽

pp. 10

Author(s):

David Perpetuini ◽

Andrea Di Credico ◽

Chiara Filippini ◽

Pascal Izzicupo ◽

Daniela Cardone ◽

...

Keyword(s):

Machine Learning ◽

Heart Rate ◽

Correlation Coefficient ◽

Infrared Thermography ◽

Thermal Imaging ◽

Remote Measurement ◽

Average Heart Rate

The remote measurement of heart rate (HR) could have many applications, such as health and emotional conditions monitoring. Currently, methods based on visible cameras have been developed for HR estimation. However, the employment of such techniques with scarce illumination conditions could be challenging. Infrared Thermography (IRT) could be a valuable tool to overcome this limitation. This study investigated the possibility of estimating average HR with facial IRT through a cross-validated machine learning (ML) approach. The correlation coefficient between the estimated and the measured HR was 0.7. Although preliminary, these results demonstrate the feasibility of estimating HR with IRT.

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Operation Optimization of a Chariot Operator Using Remote Measurement of Heart Rate

Lecture Notes in Electrical Engineering - Proceedings of the 15th International Conference on Man–Machine–Environment System Engineering ◽

10.1007/978-3-662-48224-7_9 ◽

2015 ◽

pp. 69-75

Author(s):

Hongyan Ou ◽

Honglei Li ◽

Zhingbing Pang ◽

Shuai Mu ◽

Chenhui Li

Keyword(s):

Heart Rate ◽

Remote Measurement ◽

Operation Optimization

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Non-Contact Remote Measurement of Heart Rate Variability using Near-Infrared Photoplethysmography Imaging

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) ◽

10.1109/embc.2018.8512451 ◽

2018 ◽

Author(s):

Xinchi Yu ◽

Michael Paul ◽

Christoph Hoog Antink ◽

Boudewijn Venema ◽

Vladimir Blazek ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Near Infrared ◽

Remote Measurement

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Automated, high-accuracy, remote measurement of heart rate

10.1101/2021.05.13.443967 ◽

2021 ◽

Author(s):

Yiming Yang ◽

Hongyu Zhang ◽

Chao Lian ◽

YuLiang Zhao ◽

Liming Xin ◽

...

Keyword(s):

Heart Rate ◽

Public Space ◽

Pulse Wave ◽

Remote Measurement ◽

Community Clinic ◽

Surveillance Camera ◽

Environmental Suitability ◽

Changing Light ◽

Volume Pulse ◽

Blood Volume Pulse

Arrhythmia is a marked symptom of many cardiovascular diseases. The accurate and in time detection of heart rate can greatly reduce its harm to people. However, it is still a challenge to automatedly and remotely measure the heart rate in daily life, because the environment factor of the measurement changes variously, such as the changing light intensity, the movement of people, and the uncertain distance from sensor to people. In this study, we accurately measured the heart rate of people at the distance of 4.8 meters under different intensity of light just by using a surveillance camera. After a short color video (20 sec) of a person's hand was captured by this camera, a method based on Fast Fourier Transform Algorithm (FFT) is proposed to extract the blood volume pulse wave to calculate the heart rate. By comparing the real heart rate with the results measured by electrocardiography (ECG), the accuracy of heart rate measurement using the method proposed in this study is 98.65% within 4.0 meters, and the accuracy can reach 90% within 5.6 meters. Our experiments also demonstrated that this method can accurately obtain the heart rate even when the intensity of light is below 32 LUX ( office environment 300-500 LUX). The strong environmental suitability makes this method can be applied to many occasions, such as community clinic, old peoples' home, classroom, and other public space.

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