Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2013
A flexible algorithm framework for closed-loop neuromodulation research systems.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
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Carlson Dave, Linde Dave, Isaacson Ben, Afshar Pedram, Bourget Duane, Stanslaski Scott, Stypulkowski Paul, Denison Tim
Аннотация
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.