A Power-Efficient Brain-Machine Interface System With a Sub-mw Feature Extraction and Decoding ASIC Demonstrated in Nonhuman Primates-Reference-Cited by-同舟云学术

A Power-Efficient Brain-Machine Interface System With a Sub-mw Feature Extraction and Decoding ASIC Demonstrated in Nonhuman Primates

Published:2022-06 Issue:3 Volume:16 Page:395-408
ISSN:1932-4545
Container-title:IEEE Transactions on Biomedical Circuits and Systems
language:
Short-container-title:IEEE Trans. Biomed. Circuits Syst.

Author:

An Hyochan¹^ORCID,Nason-Tomaszewski Samuel R.²^ORCID,Lim Jongyup¹^ORCID,Kwon Kyumin¹,Willsey Matthew S.²^ORCID,Patil Parag G.²,Kim Hun-Seok¹^ORCID,Sylvester Dennis¹^ORCID,Chestek Cynthia A.²^ORCID,Blaauw David¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, MI, USA

2. Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA

Funder

NIH

NSF

Craig H. Neilsen Foundation

A. Alfred Taubman Medical Research Institute

MCubed

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Biomedical Engineering

Link

https://ieeexplore.ieee.org/ielam/4156126/9827619/9779542-aam.pdf

Reference74 articles.

1. A brain-computer interface that evokes tactile sensations improves robotic arm control

2. Ten-dimensional anthropomorphic arm control in a human brain−machine interface: difficulties, solutions, and limitations

3. Cortical control of a tablet computer by people with paralysis

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5. High-performance brain-to-text communication via handwriting

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