Design Of Software System For Wearable Physiological Multi-parameter Dynamic Monitor

Wearable monitoring equipment is helpful to realize the monitoring of human longterm signs,which is of great significance for the analysis of human health.At present,the wearable monitoring equipment in the market has the problems of single monitoring parameters,incomplete display of monitoring information to users,and noise interference of monitoring data.This thesis designs and implements an embedded software system for wearable physiological multi-parameter dynamic monitor.Aiming at the problem of motion artifact noise in wearable ECG acquisition,a variety of noise reduction algorithms are investigated,and a preprocessing method and an improved particle filter algorithm are proposed.The effectiveness of the algorithm is verified by the measured data of the monitor.The specific work of this article is as follows:1.Design and implement an embedded software of wearable multi-parameter dynamic monitor,it includes the collection of ECG,respiration,temperature,acceleration and angular velocity,local storage of data,real-time communication with upper computer,switching of working mode and power management.2.Human motion detection software design and implementation.The common detection methods of ECG R wave,human posture,activity and fall detection are analyzed.According to the characteristics of ECG and motion data,the real-time detection software of ECG R wave,human posture,activity and fall is realized in the upper computer.3.Design and implementation of particle filter motion artifact suppression algorithm based on variational mode decomposition and laguerre expansion model.Through the study of MA characteristics and classical ECG noise reduction algorithms,an improved ECG noise reduction algorithm is proposed.The algorithm realizes the ECG noise reduction through the ECG preprocessing method based on VMD and LET model and the improved particle filter algorithm based on motion data.4.Function and performance test of embedded software of monitor and human motion detection software.According to the design scheme,the function and performance of embedded software and human motion detection software are tested.The final experiment shows that the embedded software designed in this thesis can collect,store and transmit four kinds of physiological signals in real time,and different modes work normally.Human motion detection effect is good,to meet the needs of use.5.Measured data analysis and algorithm comparison.Using the ECG data collected by the monitor,the noise reduction algorithm proposed in this thesis is compared with five classical ECG noise reduction algorithms.The experimental results show that the proposed algorithm can effectively suppress the motion artifact noise caused by three common actions.Compared with the five classical ECG denoising algorithms,the proposed algorithm has better denoising effect.