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Non-contact, imaging photoplethysmography (IPPG) uses video sequence to measure variations in light absorption, caused by blood volume pulsations, to extract cardiopulmonary parameters including heart rate (HR), pulse rate variability, and respiration rate. Previous researches most focused on extraction of these vital signs base on the focus video, which require a static and focusing environment. However, little has been reported about the influence of defocus blur on IPPG signal’s extraction. In this research, we established an IPPG optical model in defocusing motion conditions. It was found that the IPPG signal is not sensitive to defocus blur by analysis the light intensity distribution in the defocus images. In this paper, a real-time measurement of heart rate in defocus and motion conditions based on IPPG was proposed. Automatically select and track the region of interest (ROI) by constructing facial coordinates through facial key points detection, obtained the IPPG signal. The signal is de-noised to obtain the spectrum by the wavelet filtering, color-distortion filter (CDF) and fast Fourier transform (FFT). The peak of the spectrum is corresponded to heartbeats. Experimental results on a data set of 30 subjects show that the physiological parameters include heart rate and pulse wave, derived from the defocus images captured by the IPPG system, exhibit characteristics comparable to conventional the blood volume pulse (BVP) sensor. Contrast experiment show that the difference between the results measured by both methods is within 3 beat per minute (BPM). This technology has significant potential for advancing personal health care and telemedicine in motion situation.
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