Robust long term neural signal decoding by estimating unobserved features

Vijay Aditya Tadipatri, Ahmed H. Tewfik, James Ashe

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

Abstract

Chronic effects of electrode implantation in the brain tissue alter the neural channel signal-to-noise ratio (SNR) over time. Variability of signal quality over time poses a difficult challenge in long-term decoding of neural signals for Brain Computer Interface (BCI). Specifically, all channels observed during a neural recording session may not be observed during the next recording session. This paper describes a novel approach that effectively overcomes these challenges by identifying reliable channels and features in any given trial, estimating unobservable or unreliable features and adapting the neural signal classifier with no user input in real time. The proposed decoder predicts one of eight arm directions with an accuracy, unmatched in the literature, of above 90% in two monkeys over 4-6 weeks, achieving robustness against time and also varying environmental conditions. Application of these decoders reduces neural prosthetic training time and user frustration thus improving the usability of BCI.

Original languageEnglish (US)
Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages862-866
Number of pages5
ISBN (Electronic)9781467369978
DOIs
StatePublished - Aug 4 2015
Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
Duration: Apr 19 2014Apr 24 2014

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2015-August
ISSN (Print)1520-6149

Other

Other40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
CountryAustralia
CityBrisbane
Period4/19/144/24/14

Keywords

  • Brain Computer Interface
  • Local Field Potentials
  • Partial Observations
  • Signal Variability

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