Research On The Sensing Boundary Of Human Breathing Based On WiFi

With the rapid development of Internet of Things(Io T)technology,the era of internet of everything has arrived,and human gradually becomes the center of interaction in the information world.In order to achieve better interaction between humans and devices,sensor-based sensing technology and radio frequency based sensing technology have emerged.Since sensor-base sensing methods bring inconvenience and privacy violation to users,RF-based sensing technologies have better development trends and application prospects.This thesis mainly focues on the sensing technology based on WiFi Channel State Information(CSI),and focuses on the related research of WiFi-based human breathing sensing boundary with a brief description of the current technology development and applications.Breathing is not only one of the most fundamental human life activities,the human body can exhaust metabolic substances from the body through the human breathing system,providing the body with the required oxygen,which provides the body with nutrients and the required energy.In addition to this,the breathing rate is coordinated with heart rate and body temperature/blood pressure,which is an important vital feature for monitoring human health.At the same time,changes in breathing patterns are powerful predictive molecules for the development of chronic diseases,such as cardiac arrest and chronic kidney disease.Therefore,a constant monitoring of breathing rate is very necessary in daily life.Traditional human breathing detection methods were usually specialized medical equipment,which were expensive and not suitable for breathing monitoring in daily life.In order to achieve convenient and low-cost contactless breathing rate monitoring,this thesis propose a CSI-based human breathing sensing boundary system.Firstly,the relevant theoretical knowledge of CSI is introduced,and the influence of breathing on wireless channel is explained from the perspective of wireless channel,and the related theoretical analysis model is given.Then,according to the connection between them,this thesis also derives the breathing sensing boundary model,and gives the theoretical value of the breathing sensing boundary.Finally,a series of the experiments have been carried out to verify the effectiveness and robustness of the proposed system by inviting multiple experimenters to participate in the experiments in different environments.At the same time,considering the actual daily life scene,people usually have covers such as quilts and blankets in the process of sleep,which can cause blocking of wireless signal,resulting in serious attenuation of extracted breathing signals,which causes interference to human breathing rate monitoring and reduces the range of breathing sensing distance.To solve such problems and make human breathing monitoring universal in daily life environment,this thesis extends the above breathing sensing model.The specific solution approach is as follows: first,the signal reflected from the dynamic target is enhanced combining the channel state information of the two antennas in an optimal weighting way.Then,the combined CSI is processed to extract the human respiratory signal from signal.Finally,combined with the concept of relative error of breathing rate,we compare the experimental results caused by different factors,and then verify the effectiveness and accuracy of the system’s reflected signal enhancement for respiration detection.