Research On Methods For Photoplethysmographic Imaging Detection And Their Application For Detection Of Physiologial Signal

Pulse wave includes a lot of physiological information. Physiological and pathological features can be acquired from analysis of waveform, strength, speed, and rhythm of pulse wave. Photoplethysmography(PPG) signal can be acquired using camera under ambient light. The variation of blood volume can be detected by means of Photoplethysmographic imaging(PPGi) which transform two-dimensional signal into a one-dimensional signal by calculating pixels. Smartphones and portable personal terminal equipments with cameras are becoming increasingly popular hence serving as low-cost and health platform. This makes easy and dynamically accessing health status of individuals in non-hospital in real time, for earlier detection, fore-prevention or treatment of chronic diseases. Vaguely, prospects from application of PPGi were expected to detect physiological information under the drive of huge market potential for smart terminal equipments. This new technique has important practical significance for promotion and popularization of mobile medical as a new method for detection of vital signs in medicine.However, current application of PPGi signals were confined to the detection of heart and respiration rates due to some socio-limitations such as light environment, sensitivity of the camera, low sampling rate, and motion artifact. As a result, this thesis studied germane features of PPGi signals under different light conditions, developed a detection method of character points based on PPGi. At last, the methods of heart rate detection, pulse transit time(PTT) and Blood Oxygen Saturation(Sp O2) detection were proposed. This paper has carried out the following research:(1) The study of the PPGi features under different lighting conditions. The wavelength of the light source and the camera has an important impact on PPGi, and the experiment evaluated the PPGi-based features using light with different wavelength and intensity. Results show that: There is good consistency between the heart rate calculated according to PPGi and the heart rate acco rding to the gold standard(the gold standard refers to the most reliable and accurate, and the best diagnostic method currently acknowledged by clinical practice). Only with illumination light at the wavelengths of 470 nm, 490 nm, 505 nm, 585 nm, 600 nm, 610 nm, 625 nm, 660 nm and white light there was good correlation between the PPGi-based volume pulse waveform and gold standard PPGi signal waveform; When light at 600 nm, 610 nm, 625 nm, 660 nm wavelength and white light were used as illumination, as the light intensity increases, the DC strength of the PPGi-based volume pulse wave increases. However the AC strength increases first and then there is a trend of decrease. These results indicate that the wavelength of the illumination light does not affect the heart rate value calculated with PPGi, yet the illumination light wavelength and intensity can affect the PPGi feature, which provides a theoretical basis for digging PPGi-based physiological information detection.(2) Studying the volume pulse wave feature point extraction method based on PPGi. Because PPGi-based volume pulse wave has problems such as relatively large baseline drift, low sampling rate and splitting phenomenon, etc., we proposed several methods for the extraction of PPGi-based volume pulse wave: the use of rearranged smoothed pseudo Wigner-Ville distribution method to calculate the AC and DC strength of the PPGi-based volume pulse wave; the use of the “self-adaptive conic threshold” method to detect the peaks and valleys of the PPGi-based volume pulse wave; the use of the “quadratic curve fit” approach to improve the detection accuracy of the peaks and valleys of the PPGi-based volume pulse wave; the method of “self-adaptive region change” to avoid the PPGi splitting phenomenon. By calculating the PPGi-based heart rate and pulse transit time from several surface sites(fingertips and temples), it is verified that this method can improve the PPGi-based volume pulse wave feature point detection accuracy.(3) Studying the heart rate detection method based on PPGi. First, we assessed the feasibility of treating heart rate value calculated based on PPGi as the face region features. PPGi extracted from the face can serve as a unique feature, differentiating face contour and its similar background color. Then, based on this principle, we detected the images containing PPGi characteristics and used a 4-pixel adjacent area method to strengthen the reliability of the face region, and the face shape of the region was created using Robert operator. Results indicate that the PPGi-based face detection method can improve with human face detection robustness under complex and similar background scene.(4) Studying the method for detecting Sp O2 based on PPGi. Firstly, light with 660 nm and 800 nm wavelength were chosen as illumination light based on the analysis of PPGi-based volume pulse wave feature with different wavelengths. In the meanwhile, PPGi of the human body’s right hand index finger end and right hand thumb end were extracted. Then, based on the PPGi-based volume pulse wave feature point extraction method developed previously, the AC and DC strength of the PPGi-based volume pulse wave were obtained and Sp O2 was calculated thereafter. Compared with gold standard, results reveals a good consistency of ?%2 distribution within the 95% confidence interval.