Fuzzy Control of Model-based Beta Band Power

Deep brain stimulation (DBS) is an effective method to treat Parkinson's disease (PD). However, continuous open-loop (OL) stimulation not only consumes a lot of energy but also easily brings other side effects to patients. Therefore, the main goal of this paper is to select the appropriate feedback signal and controller to construct the closed-loop (CL) control system. Many studies show that PD symptoms are related to the oscillation power in beta band (13-35Hz), so the beta power of globus pallidus internus (GPi) neurons is selected as the feedback signal. In the CL control system, we choose the fuzzy controller as the model controller to track the beta power according to the dynamic change of the reference signal. In the simulation experiment, we tested to track a constant beta power equal to that obtained by constant 115Hz OL DBS. The average frequency of the CL is 104.92Hz, with low energy consumption. Besides the robustness of the fuzzy controller was also proved to track the other beta band power without changing the parameters of the controller. The performance of tracking constant beta power by fuzzy controller and PI controller is compared. It is found that the average tracking error of fuzzy controller is small and the robustness is better than PI controller.