Designing closed-loop brain-machine interfaces using optimal receding horizon control

Gautam Kumar, Marc H. Schieber, Nitish V. Thakor, Mayuresh V. Kothare

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We develop a control-theoretic analysis of a brain-machine interface (BMI)-based neuroprosthetic system for voluntary single joint reaching task in the absence of visual feedback. Using synthetic data obtained through the simulation of an experimentally validated psycho-physiological cortical circuit model, an adapted Weiner filter based linear decoder is developed. We analyze the performance of the decoder in the presence and the absence of natural proprioceptive feedback information. Through simulation, we show that the decoder performance degrades significantly in the absence of the natural proprioception. Finally, an optimal artificial sensory feedback is designed in the receding horizon control framework to stimulate appropriate cortical sensory area neurons. Our results show the recovery of natural performance of the reaching task during the online operation of the designed BMI.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5029-5034
Number of pages6
ISBN (Print)9781479901777
DOIs
StatePublished - Jan 1 2013
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2013 1st American Control Conference, ACC 2013
CountryUnited States
CityWashington, DC
Period6/17/136/19/13

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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