Identifying engineering, clinical and patient's metrics for evaluating and quantifying performance of brain-machine interface (BMI) systems

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

6 Scopus citations

Abstract

Brain-machine interface (BMI) devices have unparalleled potential to restore functional movement capabilities to stroke, paralyzed and amputee patients. Although BMI systems have achieved success in a handful of investigative studies, translation of closed-loop neuroprosthetic devices from the laboratory to the market is challenged by gaps in the scientific data regarding long-term device reliability and safety, uncertainty in the regulatory, market and reimbursement pathways, lack of metrics for evaluating and quantifying performance in BMI systems, as well as patientacceptance challenges that impede their fast and effective translation to the end user. This review focuses on the identification of engineering, clinical and user's BMI metrics for new and existing BMI applications.

Original languageEnglish (US)
Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1489-1492
Number of pages4
Volume2014-January
EditionJanuary
DOIs
StatePublished - 2014
Event2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014 - San Diego, United States
Duration: Oct 5 2014Oct 8 2014

Other

Other2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014
CountryUnited States
CitySan Diego
Period10/5/1410/8/14

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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