Published February 2016
| public
Journal Article
Recording and Decoding for Neural Prostheses
Abstract
This paper reviews technologies and signal processing algorithms for decoding peripheral nerve and electrocorticogram signals to interpret human intent and control prosthetic arms. The review includes a discussion of human motor system physiology and physiological signals that can be used to decode motor intent, electrode technology for acquiring neural data, and signal processing methods including decoders based on Kalman filtering and least-squares regressors. Representative results from human experiments demonstrate the progress that has been made in neural decoding and its potential for developing neuroprosthetic arms that act and feel like natural arms.
Additional Information
© 2016 IEEE. Manuscript received May 17, 2015; revised October 5, 2015; accepted November 19, 2015. Date of current version January 19, 2016. This work was supported in part by the Defense Advanced Research Project Agency (DARPA) under Award N6600115C4017 and in part by the Space and Naval Warfare Systems Center Pacific (SSC Pacific) under Contract N66001-15-C-4017. The authors wish to thank Bradley Gregor, Heather Wark and David Page for their role in acquiring some of the data reported in this paper.Additional details
- Eprint ID
- 64596
- DOI
- 10.1109/JPROC.2015.2507180
- Resolver ID
- CaltechAUTHORS:20160218-155326576
- N6600115C4017
- Defense Advanced Research Project Agency (DARPA)
- N66001-15-C-4017
- Space and Naval Warfare Systems Center Pacific
- Created
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2016-02-18Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field