Abstract
Non-contact heart rate and respiratory rate monitoring systems were derived using the facial detection algorithm. Using a video image extracted from the forehead as the region of interest (ROI), histogram of oriented gradient was used. This was based on Photoplethysmography (PPG), an optical method for detecting volumetric changes in blood in the peripheral circulation. Webcam measured the fluctuations of the HSV color space to determine the heart rate and extract respiratory rate using Fast Fourier transform (FFT). The ideal distance between the subject and the webcam must be 50cm for minimum error. Likewise, the required illuminance value must be between 250 lux to 300 lux. Based on the results, the proposed method was able to produce an overall detection accuracy of 96.05% and an average processing time of 30 seconds. The output shows very promising results for noninvasive biomedical devices in the field of heart rate and respiratory rate monitoring.
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