Upper Extremity Motor Function Rebuilding System With Feedback Of Hand Movemnts

As the rapid growth in the numbers of paralysed patients around the world,the research of paralytic limb movement function reconstruction gradually became a hot research topic in the field of rehabilitation medicine.At present,the neuromuscular electrical stimulation(NMES)method is widely ?sed in most kinds of medical instruments,in which applying electrical stimulation on peripheral nervo?s system,producing artificial action potential in the surrounding m?scles,and then accomplishing the set action.Compared with other biomedical approaches,functional electrical stimulation(FES)is easier to ?se and has the more remarkable effect.Our research group developed a movement function reconstruction system based on communication principle and the electromyographic(EMG)signal control,and put forward the concept of "Electromyographic Bridge"(EMGB)to overcome the weakness of traditional NMES system in single stimulation mode and the low active participation of paralytic.However,this system is not portable and lack of afeedback function of the hand movements,which results to no corresponding evaluation mechanism.In this paper,based on the early research in EMGB system,we transplanted the limb movement function reconstruction system into Intel's Edison embedded platform,which makes the system wearable and greatly improve the portable performance of the system.In addition,we add a data glove module into the system.The data glove can detect and return the state information of hand movements,which will create a closed loop system structure,enrich the system functions and optimize the ?ser experience.This paper will divide the wearable upper extremity motor function rebuilding system into the next three subsystems:The EMGB subsystem depends on the EMGB concept of.It is composed of an EMG-signal detection module and an electrical stimulation module,which ?ses the Socket for network communication.In this subsystem,we get the real-timeEMG signal,which will experience algorithm processing and channel mapping,according to the EMG-signal detection module.Then,it drives the electrical stimulation module to produce electrical stimulation pulses,whose parameters such as amplitude,frequency,etc.can be controlledThe automatically-point-searching subsystem is based on the "Multi-pad" concept.It is composed of an array of multi-pad electrodes,an electrode-driving module,an electrical stimulation module and a data glove,which still ?ses the Socket for network communications between modules.At first,the electrode driving module controls polling the multi-pad electrodes and chooses a single electrode to connect which can output the electrical stimulation pulse.Then,a real-time evaluation is obtained according to the feedback from data glove.Finally,the best stimulation sites can be automatically found out for the patient to perform the proper hand movement.The human-computer interaction subsystem is based on the Android device,which has a series of APPs to cooperate with each module.For example,the APP cooperated with the electrical detection module can realize the function as simple EMG signal oscilloscope;The APP cooperated with data glove module can show the hand motions in three-dimension;The APP cooperated with the electrical stimulation module can set argues to output arbitrary adj?stable stimul?s pulse current.These three subsystems are j?st typical applications of wearable upper extremity motor function rebuilding system.This system has strong scalability,which can be expanded to more application directions based on the basic function of each module.In addition,the openness of Edison platform can also help the system step into the mobile Internet medical domain.Under the background of big data and cloud computing,the system can get huge amounts of recovery data,which will greatly accelerate the optimization and innovation process of the system.