Development of a start-stop signal for a directional BMI

Byron Olson, Jing Hu, Jennie Si, Jiping He

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

1 Scopus citations

Abstract

While BMI systems abound, little care has been exercised over practical considerations in the day to day use of such systems. This paper proposes to learn a Start-Stop switch to augment a directional BMI. Taken together, the hope is that a BMI could be constructed that would be able to signal the appropriate directional intent when called upon and be virtually silent when not needed. Using data from rats utilizing a simple directional BMI, an attempt is made to test several possible methods for integrating a Start-Stop decision. Three methods, a 3-class SVM, directional classifier with probabilistic output, and a directional classifier with Start-Stop modulated probabilistic output are constructed and compared. Results show that the directional classifier with Start-Stop performs well with a significant reduction in signaling outside the task period.

Original languageEnglish (US)
Title of host publicationProceedings of the First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob 2006
Pages502-506
Number of pages5
DOIs
StatePublished - Dec 22 2006
Event1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob 2006 - Pisa, Italy
Duration: Feb 20 2006Feb 22 2006

Publication series

NameProceedings of the First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob 2006
Volume2006

Other

Other1st IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob 2006
Country/TerritoryItaly
CityPisa
Period2/20/062/22/06

Keywords

  • Brain machine interface
  • Brain vehicle interface
  • Support vector machines

ASJC Scopus subject areas

  • General Engineering

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