Parkinsonian oscillations and their suppression by closed-loop deep brain stimulation based on fuzzy concept |
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| Affiliation: | School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China |
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| Abstract: | This paper provides an adaptive closed-loop strategy for suppressing the pathological oscillations of the basal ganglia based on a variable universe fuzzy algorithm. The pathological basal ganglia oscillations in the theta (4-9 Hz) and beta (12-35 Hz) frequency bands have been demonstrated to be associated with the tremor and rigidity/bradykinesia symptoms in Parkinson's disease (PD). Although the clinical application of open-loop deep brain stimulation (DBS) is effective, the stimulation waveform with the fixed parameters cannot be self-adjusted as the disease progresses, and thus the stimulation effects go poor. To deal with this difficult problem, a variable universe fuzzy closed-loop strategy is proposed to modulate different PD states. We establish a cortico-basal ganglia-thalamocortical network model to simulate pathological oscillations and test the control effect. The results suggest that the proposed closed-loop control strategy can accommodate the variation of brain states and symptoms, which may become an alternative method to administrate the symptoms in PD. |
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| Keywords: | deep brain stimulation Parkinson's disease basal ganglia closed-loop control variable universe fuzzy |
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