Key result
The proposed non-contact heart rate monitoring method utilizing facial skin color intensity variation achieved an average accuracy of 89.25%, which was 1.94% higher than the traditional method.
Why the study?
Traditional contact-based heart rate measurement can be inconvenient for long-term monitoring due to subject discomfort.
Does a non-contact remote heart rate measuring approach using color intensity variation improve measurement accuracy compared to traditional average color value methods in healthy adults?
Observational (n=10)
No
Does a non-contact remote heart rate measuring approach using color intensity variation improve measurement accuracy compared to traditional average color value methods in healthy adults?
Absolute Event Rate: 89.25% vs 87.31%
A non-contact heart rate monitoring method utilizing facial skin color intensity variation and FastICA algorithm achieved over 92% accuracy, outperforming traditional average color value methods.
Supports refinement of video-based remote monitoring; leaves open clinical adoption pending prospective validation.
Heart Rate is a crucial physiological parameter that provides basic information about the state of the human body in the cardiovascular system, as well as in medical diagnostics and fitness assessments. At present day, it has been demonstrated that facial video-based photoplethysmographic signal captured using a low-cost RGB camera is possible to retrieve remote heart rate. Traditional heart rate measurement is mostly obtained by direct contact with the human body, therefore, it can result inconvenient for long-term measurement due to the discomfort that it causes to the subject. In this paper, we propose a non-contact-based remote heart rate measuring approach of the subject which depends on the color intensity variation of the subject’s facial skin. The proposed method is applied in two regions of the subject’s face, forehead and cheeks. For this, three different algorithms are used to measure the heart rate. i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The average accuracy for the three algorithms utilizing the proposed method was 89.25% in both regions. It is also noteworthy that the FastICA algorithm showed a higher average accuracy of more than 92% in both regions. The proposed method obtained 1.94% higher average accuracy than the traditional method based on average color value.
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Sahin et al. (2021) conducted an observational in Healthy (Heart Rate Monitoring) (n=10). Non-contact heart rate monitoring utilizing facial skin color intensity variation vs. Traditional method based on average color value was evaluated on Average heart rate measurement accuracy across three algorithms (FFT, FastICA, PCA). The proposed non-contact heart rate monitoring method utilizing facial skin color intensity variation achieved an average accuracy of 89.25%, which was 1.94% higher than the traditional method.
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