A Close Loop Multi-Area Brain Stimulation Control for Parkinson’s Patients Rehabilitation

Abstract

In recent years, deep brain stimulation (DBS) has been one of the most effective methods for treating movement disorders, including hand tremor in advanced Parkinson’s disease (PD). In order to decrees the Parkinson’s tremor, a model of basal ganglia (BG) is often used to design a closed-loop control scheme for DBS. First, a feedback signal is provided using a sensor mounted to the patient’s finger to measure the tremor values. Then, a controller sends the appropriate control commands to the actuator, and finally, the BG areas of the brain actuator are simulated by the actuator. In the present paper, to control Parkinson’s tremor and reduce the value of stimulation intensity efficiently, two areas of BG such as subthalamic nucleus (STN) and globus pallidus internal (GPi) were controlled simultaneously. This strategy provides a reduction in the applied field and side-effects (e.g. muscle contraction and speech disorder) resulting from stimulation intensity. In particular, a new model-free scheme, called intelligent single input interval type-2 fuzzy logic (iSIT2-FL) combined with non-integer sliding mode control (SMC), is proposed to control two areas of BG. In the suggested strategy, an extended state observer (ESO) is established to approximate the unknown BG dynamics, whereas the non-integer SMC is applied to remove the ESO estimation error. Comparative simulation explorations are performed subsequently to ascertain the superior performance of the suggested intelligent control scheme over that of the state-of-the-art approaches.