Respiratory data calculation method and related equipment

Abstract

The embodiment of the invention discloses a respiratory data acquisition method. The method is applied to a respiratory detection technology and comprises the following steps that: radar signals are sent; the reflection signals of the radar signals are received; a distance Fourier spectrum and a plurality of amplitude data are calculated according to the reflection signals; a reflection intensitypeak value corresponding to a target object is obtained from the one or more reflection intensity peak values, wherein the reflection intensity peak value corresponds to a target distance value; and aplurality of first distance values are determined from a plurality of distance values, and the respiratory sampling point data of the target object is calculated based on amplitude data correspondingto the plurality of first distance values, distances between each first distance value and the target distance value are smaller than a first preset value. Through the above mode, the amplitude datais extracted from the plurality of first distance values near the reflection intensity wave peaks, and the respiratory sampling point data of the target object is calculated based on the plurality ofobtained amplitude data, so that respiratory signal extraction stability is improved.

Description

technical field [0001] The present application relates to the field of artificial intelligence, and in particular to a calculation method of breathing data and related equipment. Background technique [0002] Breathing is the only way to exchange gas between the inside and the outside of the human body. It is an important vital sign of the human body. Abnormal breathing often indicates problems in certain parts of the body. Severe breathing abnormalities such as apnea are life-threatening. [0003] Abnormal breathing during sleep is often not easy to detect. Some breathing abnormalities even only occur during sleep and do not occur when awake. Human body consciousness is weak during sleep, and people often do not notice when abnormalities occur, thus missing the opportunity to discover physical problems. The current mainstream breathing detection methods include contact measurement and non-contact measurement. Contact measurement refers to the measurement method that uses de...

AI Technical Summary

Problems solved by technology

The current mainstream breathing detection methods include contact measurement and non-contact measurement. Contact measurement refers to the measurement method that uses detection tools to touch the human body, including breathing belts, bracelets, watches, etc. It is suitable for home use, but the comfort is poor. Non-contact Abnormal breathing detection, high comfort, can be detected for a long time, will not interfere with people's physical condition, and can record the most real breathing situation

[0004] At present, the non-contact measurement method mainly adopts microwave radar breathing monitoring. The micro-movement of the chest and abdomen during breathing will act on the radar reflection signal, and the breathing signal is extracted by analyzing the radar transmission signal and reflection signal, and the range-bin position extracts the breathing signal. If the position is not accurate, the respiratory signal may not be extracted or the amplitude of the respiratory signal is too low, which is susceptible to noise interference

[0005] Due to hardware computing power, antenna shape, price and other reasons, the distance and angle resolution of the FMCW-based radar breathing monitoring method cannot be improved without limit, and coupled with reflection, refraction, multipath superposition and other effects, it is difficult to accurately locate and measure the human body The position of the Range-FFT frequency point corresponding to the respiratory signal, if the frequency point position is not accurate, it will affect the acquisition of the respiratory signal

The existing technology extracts the respiratory signal based on a single frequency point Range-bin position. If the frequency point Range-bin position is inaccurate, the respiratory signal may not be extracted or the amplitude of the respiratory signal is too low.

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