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Real-time Closed Loop Neural Decoding on a Neuromorphic chip

  • Shoeb Shaikh
  • , Rosa So
  • , Tafadzwa Sibindi
  • , Camilo Libedinsky
  • , Arindam Basu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

This paper presents for the first time a real-time closed loop neuromorphic decoder chip-driven intra-cortical brain machine interface (iBMI) in a non-human primate (NHP) based experimental setup. Decoded results show trial success rates and mean times to target comparable to those obtained by hand-controlled joystick. Neural control trial success rates of ≈ 96% of those obtained by hand-controlled joystick have been demonstrated. Also, neural control has shown mean target reach speeds of ≈ 85% of those obtained by hand-controlled joystick. These results pave the way for fast and accurate, fully implantable neuromorphic neural decoders in iBMIs.

Original languageEnglish
Title of host publication9th International IEEE EMBS Conference on Neural Engineering, NER 2019
PublisherInstitute of Electrical and Electronics Engineers
Pages670-673
Number of pages4
ISBN (Electronic)9781538679210
DOIs
StatePublished - 16 May 2019
Externally publishedYes
Event9th International IEEE EMBS Conference on Neural Engineering, NER 2019 - San Francisco, United States
Duration: 20 Mar 201923 Mar 2019

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2019-March
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Conference

Conference9th International IEEE EMBS Conference on Neural Engineering, NER 2019
Country/TerritoryUnited States
CitySan Francisco
Period20/03/1923/03/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering

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