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Автор Rouse, A G
Автор Stanslaski, S R
Автор Cong, P
Автор Jensen, R M
Автор Afshar, P
Автор Ullestad, D
Автор Gupta, R
Автор Molnar, G F
Автор Moran, D W
Автор Denison, T J
Дата выпуска 2011-06-01
dc.description A bi-directional neural interface (NI) system was designed and prototyped by incorporating a novel neural recording and processing subsystem into a commercial neural stimulator architecture. The NI system prototype leverages the system infrastructure from an existing neurostimulator to ensure reliable operation in a chronic implantation environment. In addition to providing predicate therapy capabilities, the device adds key elements to facilitate chronic research, such as four channels of electrocortigram/local field potential amplification and spectral analysis, a three-axis accelerometer, algorithm processing, event-based data logging, and wireless telemetry for data uploads and algorithm/configuration updates. The custom-integrated micropower sensor and interface circuits facilitate extended operation in a power-limited device. The prototype underwent significant verification testing to ensure reliability, and meets the requirements for a class CF instrument per IEC-60601 protocols. The ability of the device system to process and aid in classifying brain states was preclinically validated using an in vivo non-human primate model for brain control of a computer cursor (i.e. brain–machine interface or BMI). The primate BMI model was chosen for its ability to quantitatively measure signal decoding performance from brain activity that is similar in both amplitude and spectral content to other biomarkers used to detect disease states (e.g. Parkinson's disease). A key goal of this research prototype is to help broaden the clinical scope and acceptance of NI techniques, particularly real-time brain state detection. These techniques have the potential to be generalized beyond motor prosthesis, and are being explored for unmet needs in other neurological conditions such as movement disorders, stroke and epilepsy.
Формат application.pdf
Издатель Institute of Physics Publishing
Копирайт 2011 IOP Publishing Ltd
Название A chronic generalized bi-directional brain–machine interface
Тип paper
DOI 10.1088/1741-2560/8/3/036018
Electronic ISSN 1741-2552
Print ISSN 1741-2560
Журнал Journal of Neural Engineering
Том 8
Первая страница 36018
Последняя страница 36036
Аффилиация Rouse, A G; Department of Biomedical Engineering, Washington University, St Louis, MO, USA
Аффилиация Stanslaski, S R; Neural Engineering, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Cong, P; Neural Engineering, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Jensen, R M; Neural Engineering, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Afshar, P; Neural Engineering, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Ullestad, D; Neural Engineering, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Gupta, R; Neurostimulation Research, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Molnar, G F; Neurostimulation Research, Medtronic Neuromodulation, Minneapolis, MN, USA
Аффилиация Moran, D W; Department of Biomedical Engineering, Washington University, St Louis, MO, USA
Аффилиация Denison, T J; Neural Engineering, Medtronic Neuromodulation, Minneapolis, MN, USA
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