Detection and classification of multiple finger movements using a chronically implanted Utah Electrode Array

Joshua Egan, Justin Baker, Paul House, Bradley Greger

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

2 Scopus citations

Abstract

The ability to detect and classify individual and combined finger movements from neural data is rapidly advancing. The work that has been done has demonstrated the feasibility of decoding finger movements from acutely recorded neurons. There is a need for a recording model that meets the chronic requirements of a neuroprosthetic application and to address this need we have developed an algorithm that can detect and classify individual and combined finger movements using neuronal data acquired from a chronically implanted Utah Electrode Array (UEA). The algorithm utilized the firing rates of individual neurons and performed with an average sensitivity and an average specificity that were both greater than 92% across all movement types. These results lend further support that a chronically implanted UEA is suitable for acquiring and decoding neuronal data and also demonstrate a decoding method that can detect and classify finger movements without any a priori knowledge of the data, task, or behavior.

Original languageEnglish (US)
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages7320-7323
Number of pages4
DOIs
StatePublished - Dec 26 2011
Externally publishedYes
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

Keywords

  • Arrays
  • decoding
  • microelectrodes
  • neural engineering
  • neural prosthesis

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Egan, J., Baker, J., House, P., & Greger, B. (2011). Detection and classification of multiple finger movements using a chronically implanted Utah Electrode Array. In 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 (pp. 7320-7323). [6091707] (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). https://doi.org/10.1109/IEMBS.2011.6091707