Simulation And Optimization Design Of Functional Electrical Stimulation Applying Surface Array Electrode

Functional electrical stimulation (FES) is a technique that uses electrical currents toactivate nerves innervating extremities affected by paralysis resulting from spinal cordinjury (SCI), head injury, stroke and other neurological disorders. FES is primarily used torestore function in people with disabilities. It is sometimes referred to as neuromuscularelectrical stimulation (NMES). We call the device neural prostheses,which uses electricalstimulation to activate the nervous system, neural prostheses consist primarily of two parts,i.e., the stimulator and stimulus electrodes.The former processes the data of externaloptical signal or electrical image information to be encoded into a sequence of electricalpulses to stimulate the nervous tissue of the nervous system via the latter, which still haspart of the function, resulting in creating neural electrophysiological signals to restore itsfunction. There are three main stimulus types of FES: surface electrical stimulation,percutaneous electrical stimulation and fully implantable electrical stimulation. SurfaceFNS has advantages of being non-invasive, painless and indications wide, but also havedefects in stimulating effect and target selectivity. The subject is mainly studied tooptimize and design the surface array electrodes used in FES and comparatively analyzethe stimulus effect of different types of stimulation waveforms,, aiming to design idealarray electrode and select the appropriate stimulus waveform, and that lay a theoreticalfoundation to optimize and design the FES system.Firstly, the electrophysiological principles of FES are described in this thesis. Then,based on the previous theories, the author of this paper has built the geometry andmathematical models of the human forearm FES system using surface array electrode(SAE), the finite element method (FEM) could be used to simulate the distribution ofelectric fields within the forearm. Moreover, the activation function (AF) indicates theeffect of applied electric field on the activity of the nerve axon, and then the ratio of the maximum to the multiplication of half-widths of AF for the deep axon in the forearm isused as performance evaluation function. In order to achieve perfect performance andoptimal SAE parameters, the particle swarm optimization (PSO) algorithm is used tooptimize the size and spacing of electrode element of SAE. In addition, differentstimulation waveforms are investigated based on the time-varying maximum of AF for thedeep axon in the forearm. Compared with other stimulation waveforms, the biphasiccharge-balanced rectangular pulse produced a slightly larger maximum of AF, which has abeneficial effect on the activation of axons. Therefore, the FEM simulations lay a goodfoundation for the design of SAE and clinical application.