Classifying Intracortical Brain-Machine Interface Signal Disruptions Based on System Performance and Applicable Compensatory Strategies: A Review

Brain-machine interfaces (BMIs) record and translate neural activity into a control signal for assistive or other devices. Intracortical microelectrode arrays (MEAs) enable high degree-of-freedom BMI control for complex tasks by providing fine-resolution neural recording. However, chronically implan...

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Veröffentlicht in:	Frontiers in neurorobotics Jg. 14; S. 558987
Hauptverfasser:	Dunlap, Collin F., Colachis, Samuel C., Meyers, Eric C., Bockbrader, Marcia A., Friedenberg, David A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Switzerland Frontiers Research Foundation 09.10.2020 Frontiers Media S.A
Schlagworte:	Algorithms Arrays biocompatibility brain-computer interface Electrodes Etiology Interfaces intracortical electrode array Learning algorithms Machine learning microelectrode failure Neural coding neuroprosthetics Neuroscience recording disruptions Regulatory approval Scanning electron microscopy Spectroscopy Statistical analysis Transplants & implants Usability United States > US Utah signal quality neuroprosthetics biocompatibility brain-computer interface recording disruptions microelectrode failure intracortical electrode array
ISSN:	1662-5218, 1662-5218
Online-Zugang:	Volltext
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