Optimal Canceling of the Physiological Tremor for Rehabilitation in Parkinson’s Disease

Document Type : Research Paper


1 Department of Electrical and Biomedical Engineering, Faculty of Biomedical Engineering, University College of Rouzbahan, Sari, Iran.

2 Department of Electrical Engineering, University of Alborg, Alborg, Denmark.

3 Department of Mathematics, Faculty of Applied Mathematics, Yazd University, Yazd, Iran.

4 Department of Sport Biomechanics and Technology, Sport Science Research Institute, Tehran, Iran.


Introduction: This study was conducted to control hand tremors and decrease adverse effects due to the high field intensity in advanced Parkinson’s disease. We aimed at concurrently controlling two areas of Basal Ganglia (BG) in a closed-loop strategy.
Methods: In the present research, two nuclei of BG, namely subthalamic nucleus and globus pallidus internal were simultaneously controlled. Furthermore, to enhance the feasibility of the suggested control strategy, the coefficients of the controller were determined using a hybrid version of the harmony search and cuckoo optimization algorithm.
Results: The advantages of the applied method include decreasing hand tremors and applied electric field intensity to the brain; consequently, it leads to reducing adverse effects, such as muscle contraction and speech disorders. Moreover, the purposed controller has achieved superior performance against changing the parameters of the model (robustness analysis) and under noise tests, compared to other conventional controllers, such as Proportional Integrator (PI) and Proportional Derivative (PD).
Conclusion: The employed approach provided an effective strategy to reduce hand tremors. It also decreased the delivered high field intensity to the brain; consequently, it reduced adverse effects, such as memory loss and speech disorders. It is important to ascertain the superior performance of the suggested closed-loop control scheme in different conditions and levels of tremor. Such a function was examined in terms of robustness against the variation of parameters and uncertainties. We also obtained time domain outcomes, i.e., compared with the state-of-the-art approaches.