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Abstract

People with Tetraplegia will typically require costly, round-the-clock care over the course of their lives due to lack of motor function. Brain computer interfaces (BCIs) are capable of identifying imagined motor intention for individual limbs; however, high-cost electroencephalography (EEG) devices are typically used. In this paper, a comparison of 4 published motor imagery (MI) BCIs is undertaken. BCI Competition IV Dataset 2b is used to benchmark the four and the relatively low-cost OpenBCI EEG cap is then used with each, in a custom experiment. Results obtained from the OpenBCI EEG cap suggest that it is suitable for MI tasks, though this should be confirmed with a larger sample. Also, 2 of the 4 MI BCI’s stand out for decoding accuracy, though all performed well.

Original languageEnglish
Title of host publicationConverging Clinical and Engineering Research on Neurorehabilitation V. (ICNR 2024)
Subtitle of host publicationProceedings of the 6th International Conference on Neurorehabilitation - Volume 1
EditorsJ. L. Pons, J. Tornero, M. Akay
Place of PublicationCham, Switzerland
PublisherSpringer
Chapter136
Pages694-698
Number of pages5
Volume1
Edition1st
ISBN (Electronic)9783031775888
ISBN (Print)9783031775871
DOIs
Publication statusPublished - 27 Feb 2025
EventInternational Conference on Neurorehabilitation - La Granja, Spain
Duration: 5 Nov 20248 Nov 2024

Publication series

NameBiosystems and Biorobotics
Volume31
ISSN (Print)2195-3562
ISSN (Electronic)2195-3570

Conference

ConferenceInternational Conference on Neurorehabilitation
Abbreviated title(ICNR 2024)
Country/TerritorySpain
CityLa Granja
Period5/11/248/11/24

ASJC Scopus subject areas

  • Biomedical Engineering
  • Mechanical Engineering
  • Artificial Intelligence

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