Key result
The proposed adaptive pulse signal extraction algorithm using smartphone fingertip video images accurately measured heart rate with a maximum error of ±2 beats/min and an average relative error of 1.59%.
Why the study?
To address the saturation distortion phenomenon of the R component in fingertip video images for pulse signal extraction.
Effect estimate: Average relative error 1.59%
A novel adaptive algorithm using smartphone fingertip video images can accurately extract human heart rate information, offering potential for mobile physiological monitoring.
In order to solve the saturation distortion phenomenon of R component in fingertip video image, this paper proposes an iterative threshold segmentation algorithm, which adaptively generates the region to be detected for the R component, and extracts the human pulse signal by calculating the gray mean value of the region to be detected. The original pulse signal has baseline drift and high frequency noise. Combining with the characteristics of pulse signal, a zero phase digital filter is designed to filter out noise interference. Fingertip video images are collected on different smartphones, and the region to be detected is extracted by the algorithm proposed in this paper. Considering that the fingertip's pressure will be different during each measurement, this paper makes a comparative analysis of pulse signals extracted under different pressures. In order to verify the accuracy of the algorithm proposed in this paper in heart rate detection, a comparative experiment of heart rate detection was conducted. The results show that the algorithm proposed in this paper can accurately extract human heart rate information and has certain portability, which provides certain theoretical help for further development of physiological monitoring application on smartphone platform.
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Yu et al. (2020) studied Healthy volunteers (heart rate detection) (n=10). Adaptive pulse signal extraction algorithm (R component iterative threshold segmentation) vs. Finger-clip pulse oximeter (YK-83C) was evaluated on Heart rate measurement accuracy (average relative error) (Average relative error 1.59%). The proposed adaptive pulse signal extraction algorithm using smartphone fingertip video images accurately measured heart rate with a maximum error of ±2 beats/min and an average relative error of 1.59%.
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