Non-contact remote estimation of cardiovascular parameters

Cardiovascular disease is a serious threat to human health. It is crucial to monitor the cardiovascular parameters reliably and conveniently. Non-contact measurement has been widely studied. However, there are some inevitable factors that limit the use of the platform and even lead to inaccuracy estimation. Hence, a novel non-contact method that estimates cardiovascular parameters under ambient light is proposed. The most suitable region of interest (ROI) is determined by a colormap, which is a map consists of Fast Fourier Transform (FFT) peak amplitude of every pixel. Comparisons suggest that the region includes cheeks and nose is the most appropriate, followed by the forehead. To remove the motion artifacts caused by body movement, face detection and tracking algorithms are performed. Further, a multi-step signal process that combines independent component analysis (ICA) and wavelet de-noising is utilized to extract clean signal from the noise-corrupted raw waveform. Moreover, various distance between subject and camera and the change of ambient light intensity are considered, where statistics results reveal that this non-contact methodology is blind to these factors. Compared with the gold standard pulse oximeter, the proposed method shows a high accuracy even in the presence of motion artifacts.