Non-contact human respiration and heart beat signal detection method based on infrared sequence image

Abstract

The invention relates to a non-contact human respiration and heart beat signal detection method based on an infrared sequence image. According to the technical scheme, the method comprises the followings steps: 1, in an appropriate environment, collecting the infrared sequence image on the side of a subject, and in the process, controlling the moving of a head of the subject; 2, using an Ostu method to realize binaryzation of the image, extracting a time series signal at a barycenter (one step interval) of the sequence image, and obtaining a respiration signal of the subject; 3, selecting a superficial temporal artery upstream region (the temple area) and an area around the nostrils as interesting regions. The mean of the area around the nostrils is calculated to obtain the respiration signal of the subject; the time series signal of the temple interesting region needs to be decomposed through an integrated empirical mode, and then is subjected to AR power spectrum analysis so as to detect the respiration and heart beat signals. According to the method, the non-contact heart beat and respiration detection is realized by using the infrared sequence image, and the method has better application value in the identification of facial physiological information and monitoring of clinical physiological characteristics during an operation.

Description

technical field [0001] The invention relates to a method for non-contact detection of human respiration and heart rate physiological parameters using infrared sequence images. The infrared sequence images of the side of the subject's face are obtained through infrared sensing, and then two regions of interest, the temple and the lower end of the nostrils, are selected to construct time-series signals for numerical calculation. Finally, three methods are realized to measure the respiratory signal and accompanied by the heart rate signal. Background technique [0002] Respiration and heart rate are the most important physiological parameters of the human body, which reflect the physiological state and health information of the human body in real time. Obstructive sleep apnea syndrome is a common disease that has a great impact on human health. Its prevalence rate in adults is about 2% to 4%. The clinical symptoms are mainly snoring and apnea during sleep. Clinical research us...

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Problems solved by technology

[0008] Empirical mode decomposition was proposed by Huang in 1998. It is based on the local characteristics of the data. It can decompose complex data into limited intrinsic mode function components. Since the decomposition is based on the local characteristics of the time domain of the signal, the decomposition is adaptive. , is especially suitable for analyzing non-stationary nonlinear time series signals. It can clearly distinguish the intrinsic patterns of overlapping complex data, but its main defect is the generation of pattern confusion. The integrated empirical pattern decomposition using white noise can To overcome the problem of schema confusion, this method has been effectively applied in many fields

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