Radio frequency respiration monitoring system and compressive sensing implementing method

Abstract

The invention discloses a radio frequency respiration monitoring system and a compressive sensing implementing method. A radio frequency sensing network is formed by radio frequency nodes of the system; the radio frequency network is connected with a server through a base station; and the server is used for data storage and processing. The compressive sensing implementing method comprises the following steps of carrying out compressive sampling on a radio frequency link Received Signal Strength (RSS) signal in a random manner; reconstructing a respiratory movement signal by a sparse reconstruction algorithm; and extracting a respiration frequency value. According to the invention, thoracico-abdominal respiratory movement information is acquired by detecting the radio frequency link RSS signal; passive respiration monitoring is implemented; detection comfort is obviously improved; and respiration monitoring is simpler and more humanized. The radio frequency sensing network has low price, is convenient to deploy, is suitable for ubiquitous deployment and can be widely applied to places such as hospitals, clinics, nursing homes and families. A compressive sensing mechanism is introduced so as to not only limit data acquisition scale and reduce data transmission and storage cost, but also reduce energy consumption of the radio frequency sensing network and meet the application requirement for continuously monitoring for a long time.

Description

technical field [0001] The invention relates to the technical field of radio frequency sensing, and more specifically, to a respiratory monitoring system realized by radio frequency sensing and a method for realizing compressed sensing. Background technique [0002] Respiratory monitoring is one of the most important means of assessing vital status, and its importance is self-evident. Due to the unpredictability of breathing disorders, once breathing disorders occur, life-threatening will be in danger in a short time. Therefore, high-risk groups of breathing disorders, including patients after surgery, are prone to sudden infant death syndrome (Sudden Infant Death Syndrome, SIDS) Infants with sleep apnea and patients with sleep apnea have urgent and extensive application requirements for respiratory monitoring systems. [0003] According to the differences in detection methods, the existing respiratory monitoring systems mainly include several types based on respiratory air...

AI Technical Summary

Problems solved by technology

The abdominal belt detection method uses the sensing element installed on the abdominal belt to detect the breathing movement of the chest and abdomen, which also brings about the problem of comfort, and the tightness of the abdominal belt has a great influence on the detection effect

The X-ray fluoroscopy detection method uses X-ray fluoroscopy imaging to obtain the position change information of the marker points implanted in the human body and then infers the breathing parameters, which is invasive and brings additional pain to the subject.

In addition, the current commercial respiratory monitoring system is expensive and is generally only installed in the Intensive Care Unit (ICU) of the hospital, which is difficult to meet the ubiquitous monitoring and daily monitoring needs of people with respiratory disorders

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