Abstract
Image photoplethysmography can realize low-cost and easy-to-operate non-contact heart rate detection from the facial video, and effectively overcome the limitations of traditional contact method in daily vital sign monitoring. However, it is hard to obtain more accurate heart rate detection values under the conditions of subject’s facial movement, weak ambient light intensity and long detection distance, etc. In this article, a non-contact heart rate detection method based on face tracking is proposed, which can effectively improve the accuracy of non-contact heart rate detection method in practical application. The corner tracker algorithm is used to track the human face to reduce the motion artifact caused by the movement of the subject’s face and enhance the use value of the signal. And the maximum ratio combining algorithm is used to weight the pixel space pulse wave signal in the facial region of interest to improve the pulse wave extraction accuracy. We analyzed the facial images collected under different experimental distances and action states. This proposed method significantly reduces the error rate compared with the independent component analysis method. After theoretical analysis and experimental verification, this method effectively reduces the error rate under different experimental variables and has good consistency with the heart rate value collected by the medical physiological vest. This method will help to improve the accuracy of non-contact heart rate detection in complex environments.
Highlights
It is difficult for these algorithms to obtain a higher accuracy of heart rate estimation in the case of detection distance and face movement [11], this paper proposes to use Kanade-Lucas-Tomasi (KLT) feature tracker [12] to track the detected face parts and improve the segmentation efficiency of region of interest extracted from pulse wave signals, enhance the signal value of the region of interest (ROI)
Statistical test and error analysis were carried out based on the experimental data, and the results showed that the method presented in this paper could reduce errors in different experimental scenarios and improve the accuracy of heart rate detection
The experimental results obtained by this method are shown in the Figures 6-8, in this experiment, three subjects were tested, and the distance and motion were taken as experimental variables. 18 video images with a duration of 1 min were sorted out as experimental samples, the average heart rate within 10 s of the stabilization time was recorded as the effective value
Summary
Traditional Electrocardiogram (ECG) as the gold standard when it comes to the current heart rate measurement, is widely used in clinical diagnosis and physiological monitoring, but this method requires complicated professional operation and multiple electrodes to connect with the human body during use. In view of the shortcomings of traditional heart rate detection methods for contact subjects, researchers have proposed non-contact heart rate detection methods based on microwave radar [2], thermodynamic image [3], video image processing [4] and so on in recent years. The heart rate detection method based on video image processing has the advantages of simple equipment, stable system and fast operation, which has become a research hotspot and has received extensive attention
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