Real-time Continuous Heart Rate Detection And Visualization Based On Videos

Human heart rate(HR) is an important physiological parameter with numerous applications, including clinical diagnosis. Besides, Remote measurements of the cardiac pulse can provide comfortable physiological assessment without electrodes. However, attempts so far are non-automated, susceptible to motion artifacts and typically expensive.For these studies, this paper introduces a new heart rate computational formula based on video which we name it linear discriminant method based on context and builds a system to realize the real-time, continuous heart rate detection. For every tester, the system first detects face region from each frame of the video and gains the RGB channels’ data, then smooths the data and calculates input signal, and makes the input signal Fast Fourier Transform from spatial domain to frequency domain after band-pass filtering, at last obtains the final heart rate through computational formula mentioned before. After the experimental design and verification, our system can realize real-time human face recognition and signal extraction, and our results gained from code are similar compared to the results measured by ECG equipment, also our heart rate detection method is stable, and the precision rate can reach 90 percent and above.Based on the conclusion gained by former researchers, add analysis of the long time video data, optimize the heart rate calculation method, then we obtain a better continuous, real-time, non-contact heart rate monitor method based on videos.This paper has carried on the flow field visualization field exploration, based on the principle of service for visualizing heart rate, mainly related to the two dimensional flow field visualization technology, and based on this, a kind of two-dimensional flow field visualization method based on image fusion and information theory is proposed.