Research And Testing Of Intelligent Functional Electrical Stimulation Control Technology For Lower Limbs

With the aging population and the number of spinal cord injurypatients grow year after year, the number of paralyzed patients is alsoincreasing. Functional Electrical Stimulation (FES) is an effective meansto help these patients recover their motor function, and it has importantsignificance and application of good prospects. However, the domesticresearch on FES system is not mature, especially in terms of lowerextremity FES systems.Inspired by bionic control theory and electromyograph (EMG)generation hypothesis, the author combines central pattern generator (CPG)with muscle synergy, and use the combined idea to design an intelligentFES control system. With a small number of CPG outputs we can controlmultiple muscles, and keep the control effect while greatly simplify theCPG network.In this paper, the basis of FES is described firstly. The way how muscle tension generated under electrical stimulation is introduced. Thenthe muscle synergy during rhythmic movement is studied. The temporalcomponents are obtained by identifying the principal components of EMG,and then are useded to reconstruct EMG. Comparing the temporalcomponents under different load or speed, we conclude that the temporalcomponets are essentially the same in one pattern. In the following,Hindmarsh-Rose model (HR model) is proposed to be used as a generalCPG and is explored in detail. This idea is proved both in theory and inpractice. Then, genetic algorithm is used to optimize the parameters of HRmodel and Matsuoka model. The fitted temporal components genereatedby HR model and Matsuoka model are compared and utilized toreconstruct EMG. In which, the EMG reconstructed by HR model are usedas the control signal to control FES. Finally, experiments both on healthysubjects and patients are implemented to prove the effectiveness of thecontrol system.