Why the study?
Sensor-based physiological recording can cause bodily discomfort, especially during prolonged periods, motivating remote non-contact monitoring methods that address generalization and light variations.
A novel non-contact heart rate monitoring system using facial video analysis and light equalization provides an accurate, sensor-free method for physiological tracking.
Supports contactless HR tracking development; leaves open clinical validation before routine use.
Healthcare is a crucial part of human beings; thus, keeping a check by recording and monitoring certain essential functions of the body is important. Using sensors to record multiple physiological processes can be discomforting for the body. This is especially true if the recording is done for a prolonged period, due to this reason that methods for remote physiological monitoring are becoming popular. These methods do not involve the physical interaction of any sensors with the human body or skin. Several studies have proposed the detection of Blood Volume Pulse, or BVP, to calculate Heart Rate and Heart Rate Variability. In this particular study, the main focus is on measuring the Heart Rate (HR). The algorithm utilized in this study is Independent Component Analysis (ICA). The primary function of this algorithm is to separate the main source signal essential for measurement from the noise in the RGB channels of the facial video. In this paper, the generalization of existential methods is addressed. In addition, the process considered in this approach is much more accurate. It is possible due to the implementation of a light equalization scheme. This scheme helps reduce issues of unequal facial light and minimize the effect of shadows—the selection of the best and most accurate signal as outputted by the ICA module.
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Balaraman et al. (2023) studied this question.
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