The Design Of Wearable Intelligent Terminal Nodes For Home Rehabilitation Of The Stroke Patients

As the aging phenomenon getting worse,the number of patients represented by stroke with physical disabilities is also increasing.Lots of modern clinical studies show that after scientific and effective rehabilitation training,the patient's physical coordination ability can be recovered to some extent.While the traditional treatment method has a restriction that patients need to test their recovery situation at a specific time and place,so doctors cannot accurately grasp the patient's condition in real time.To solve the problems,this paper designs a set of wearable smart terminal node system for home rehabilitation towards stroke patients based on the analysis of the existing rehabilitation system.The main research contents are as follows:First of all,this paper analyzes the development and background significance of the topic at home and abroad to determine the feasibility.This design will figure out the characteristics of stroke patients systematically,and select exercise posture,electromyography and pulse.These three physiological data could best describe the physiological information of patients,further analyze the functional requirements of the system,and determine a design scheme.According to requirements,communication chip CC2538 that ensure normal system logic control is adopted.We will also choose various sensors and related peripheral systems that meet system delay and accuracy.For the schematic diagrams and PCBs of intelligent terminal nodes,while ensuring the characteristics of high stability,high accuracy,strong anti-interference,the miniaturization of the node is needed.To ensure the stable and persistent data propagation of wireless node,we choose mesh topology and IEEE802.15.4 communication protocol.Secondly,for EMG and pulse signal,while Wave filtering in hardware design,wavelet threshold and heuristic threshold wavelet are used to remove the interference mixed in the acquisition process in software.A multi-node fusion algorithm is used for the motion gesture data to unite the data in the human body coordinate system.Finally,we did physiological parameter monitoring experiments on the experimenter after each intelligent sensor node is independently debugged with mature products.The experimental results show that the designed system has high stability and accuracy,and can be applied to the physical information monitoring of patients with stroke in the home,providing scientific data for doctors to develop appropriate rehabilitation training programs.