Research On Multi-physiological Parameter Monitoring System For Drug Abusers

In recent years,drugs have spread in China.As an important place to carry out compulsory detoxification,the drug rehabilitation center has played a very important role in drug rehabilitation.Drug users have longterm drug use and drug dependence.After leaving the drug,some abnormal psychological and physiological conditions will occur.In severe cases,behaviors that endanger the safety of others will be made.Therefore,continuous real-time monitoring of their physiological parameters and activity status is very necessary.At present,the mode of measuring and managing artificial physiological parameters is inefficient,and there are many dead angles in the method of monitoring the activity state of drug addicts by video camera.At the same time,this management mode requires a lot of manpower,so wireless,real-time,continuous physiological parameters and condition monitoring are urgently needed now.In recent years,along with advances in micro-sensor technology,the emergence of Internet of Things and artificial intelligence technology has made it possible to realize wireless intelligent monitoring of the physiology and state of drug users in drug rehabilitation centers.In response to the above requirements,with the support of the National Key Research and Development Program(No.2018YFC0807405),this paper proposed a system for intelligent monitoring of wireless physiological parameters.The designed monitoring terminal has the functions of measuring four basic physiological parameters of blood oxygen saturation,blood pressure,heart rate and body temperature,and can intelligently evaluate individual mental stress according to physiological parameters.The monitoring terminal also has a wireless ranging and positioning function,so that the police officer can monitor the location of the drug addicts in real time,especially when going out to the field,which can effectively prevent the drug addict from escaping.All physiological parameter data will be transmitted to the server for storage and processing via the network and can be transmitted to the police officer’s mobile phone or tablet.In this paper,the physiological significance of the four basic physiological parameters is firstly described.The most suitable measurement scheme is determined according to the measurement principle.The hardware design and algorithm research are carried out,and the design method is discussed in detail.In this paper,using the collected physiological parameters as characteristics,a mental stress assessment model based on convolutional neural network is established,which is used as a supplement to the physiological parameter monitoring system to predict and evaluate the stress situation of drug addicts and provide evaluation for their rehabilitation process.Strong basis.Subsequently,based on the ultra-wideband communication technology,the wireless ranging and positioning function module was developed.The module design includes three main components: ranging theory analysis,communication protocol development,and ranging and positioning model.Finally,the function of the designed module is verified.The verification results show that the measurement accuracy and resolution of the physiological parameters reach the expected target,the blood oxygen saturation module achieves the measurement accuracy of ±2.6%,the measurement error of the blood pressure measurement module is limited to within ±8mmHg,and the error of the heart rate calculation is within 3bpm.The classification accuracy of CNN mental stress assessment model for the four stress states is as high as 97.0%,which has important reference value for the rehabilitation assessment of drug rehabilitation personnel.The ranging positioning module using UWB technology has higher precision than the traditional positioning technology.The absolute error of the Ranging system designed in this paper is within 20 cm.This paper innovatively uses the new sensing technology to design a physiological parameter monitoring system and a personnel positioning system with multiple physiological parameters.Combined with deep learning technology,it uses a variety of physiological parameters to evaluate the stress status of drug addicts.Although the system meets the required accuracy requirements,there are still some shortcomings.At the end of this paper,the shortcomings of the system design are analyzed and summarized,and the future direction of the work is improved.