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Modulation of neural activity through electrical stimulation of tissue is an effective therapy for neurological diseases such as Parkinson's disease and essential tremor. Researchers are exploring improving therapy through adjustment of stimulation parameters based upon sensed data. This requires classifiers to extract features and estimate patient state. It also requires algorithms to appropriately map the state estimation to stimulation parameters. The latter, known as the control policy algorithm, is the focus of this work. Because the optimal control policy algorithms for the nervous system are not fully characterized at this time, we have implemented a generic control policy framework to facilitate exploratory research and rapid prototyping of new neuromodulation strategies.

Original publication




Journal article


Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

Publication Date





6146 - 6150


Humans, Nervous System Diseases, Parkinson Disease, Movement Disorders, Essential Tremor, Neurotransmitter Agents, Electric Stimulation, Algorithms, Models, Theoretical, Computer Graphics, Computer Simulation, User-Computer Interface, Online Systems