Depth image data-based non-contact respiration monitoring method

Abstract

The invention discloses a non-contact respiration monitoring method. The method comprises the following steps: positioning the thoracic-abdominal area of a monitored person in a depth video stream; carrying out dimension reduction on data in the thoracic-abdominal area of each frame image in the depth video stream; calculating variance of the dimension reduced data to obtain a thoracic-abdominal variation extent sequence; carrying out low-pass filtering on the thoracic-abdominal variation extent sequence to obtain a denoised respiration variation sequence; calculating a respiration frequency and a respiration pause time according to the respiration variation sequence. According to the method, the problem that the respiration process of the monitored person is possibly interfered by the contact type respiration monitoring is solved, the hardware cost and the equipment complexity are reduced.

Description

technical field [0001] This application relates to the medical field, image processing, computer vision and other fields, and in particular to a method for non-contact monitoring of breathing through depth images. Background technique [0002] Respiration is an important physiological process, and monitoring respiration is one of the basic means for diagnosing some respiratory diseases in medicine. For example, obstructive sleep apnea syndrome (OSA) mainly relies on monitoring breathing to diagnose. OSA is clinically manifested as more than 30 repeated episodes of apnea during 7 hours of sleep per night. By monitoring the sleep breathing state of the test subject, it can be judged whether the test subject suffers from OSA. Specifically, by monitoring the patient's respiratory rate, number of apneas, and apnea time, it is judged whether the monitored person suffers from OSA. Monitoring breathing can enable patients with the disease to obtain medical treatment in time, avoi...

AI Technical Summary

Problems solved by technology

The use of infrared cameras to monitor breathing has the advantages of not being affected by ambient light and high precision, but in general, infrared cameras are relatively expensive, which is not conducive to large-scale applications

[0005] To sum up, the contact respiratory monitoring solution may interfere with the normal breathing process of the monitored person, and the hardware platform on which the non-contact respiratory monitoring solution is implemented using an infrared camera is not cheap, which limits the ability of non-contact respiratory monitoring. Popularity of Surveillance

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