Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap

Isaac J C Jordan; Benjamin Metcalfe; Virginia Ruiz Garate; Dan Withey

doi:10.1007/978-3-031-77588-8_136

Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap

Isaac J C Jordan^*, Benjamin Metcalfe, Virginia Ruiz Garate, Dan Withey

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

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Abstract

People with tetraplegia typically require costly, round-the-clock care throughout their lives due to the lack of motor function. Brain-computer interfaces (BCIs) are capable of detecting imagined motor intention for individual limbs, but high-cost electroencephalography (EEG) devices are typically used. This paper compares four published motor imagery (MI) BCIs using the BCI Competition IV Dataset 2b as a benchmark. The relatively low-cost OpenBCI EEG cap is then used with each BCI 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. Additionally, two of the four MI BCIs stand out for their decoding accuracy, although all performed well.

Original language	English
Title of host publication	Converging Clinical and Engineering Research on Neurorehabilitation V
Subtitle of host publication	Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024)
Editors	Jose L. Pons, Jesus Tornero, Metin Akay
Publisher	Springer Nature
Pages	694-698
Number of pages	5
Volume	1
ISBN (Electronic)	9783031775888
ISBN (Print)	9783031775871
DOIs	https://doi.org/10.1007/978-3-031-77588-8_136
Publication status	E-pub ahead of print - 27 Feb 2025
Event	6th International Conference on Neurorehabilitation (ICNR 2024) - La Granja, Spain Duration: 5 Nov 2024 → 8 Nov 2024 https://2024.icneurorehab.org/

Publication series

Name	Biosystems & Biorobotics
Publisher	Springer
Volume	31
ISSN (Print)	2195-3562
ISSN (Electronic)	2195-3570

Conference

Conference	6th International Conference on Neurorehabilitation (ICNR 2024)
Abbreviated title	ICNR 2024
Country/Territory	Spain
City	La Granja
Period	5/11/24 → 8/11/24
Internet address	https://2024.icneurorehab.org/

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Keywords

BCI
Motor Imagery
Tetraplegia

Access to Document

10.1007/978-3-031-77588-8_136

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Accepted author manuscript, 88.5 KBLicence: CC BY

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Jordan, I. J. C., Metcalfe, B., Garate, V. R., & Withey, D. (2025). Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap. In J. L. Pons, J. Tornero, & M. Akay (Eds.), Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024) (Vol. 1, pp. 694-698). (Biosystems & Biorobotics; Vol. 31). Springer Nature. Advance online publication. https://doi.org/10.1007/978-3-031-77588-8_136

Jordan, Isaac J C ; Metcalfe, Benjamin ; Garate, Virginia Ruiz et al. / Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap. Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024). editor / Jose L. Pons ; Jesus Tornero ; Metin Akay. Vol. 1 Springer Nature, 2025. pp. 694-698 (Biosystems & Biorobotics).

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title = "Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap",

abstract = "People with tetraplegia typically require costly, round-the-clock care throughout their lives due to the lack of motor function. Brain-computer interfaces (BCIs) are capable of detecting imagined motor intention for individual limbs, but high-cost electroencephalography (EEG) devices are typically used. This paper compares four published motor imagery (MI) BCIs using the BCI Competition IV Dataset 2b as a benchmark. The relatively low-cost OpenBCI EEG cap is then used with each BCI 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. Additionally, two of the four MI BCIs stand out for their decoding accuracy, although all performed well.",

keywords = "BCI, Motor Imagery, Tetraplegia",

author = "Jordan, {Isaac J C} and Benjamin Metcalfe and Garate, {Virginia Ruiz} and Dan Withey",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 6th International Conference on Neurorehabilitation (ICNR 2024), ICNR 2024 ; Conference date: 05-11-2024 Through 08-11-2024",

year = "2025",

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doi = "10.1007/978-3-031-77588-8_136",

language = "English",

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volume = "1",

series = "Biosystems & Biorobotics",

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editor = "Pons, {Jose L.} and Jesus Tornero and Metin Akay",

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Jordan, IJC, Metcalfe, B, Garate, VR & Withey, D 2025, Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap. in JL Pons, J Tornero & M Akay (eds), Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024). vol. 1, Biosystems & Biorobotics, vol. 31, Springer Nature, pp. 694-698, 6th International Conference on Neurorehabilitation (ICNR 2024), La Granja, Spain, 5/11/24. https://doi.org/10.1007/978-3-031-77588-8_136

Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap. / Jordan, Isaac J C; Metcalfe, Benjamin; Garate, Virginia Ruiz et al.
Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024). ed. / Jose L. Pons; Jesus Tornero; Metin Akay. Vol. 1 Springer Nature, 2025. p. 694-698 (Biosystems & Biorobotics; Vol. 31).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap

AU - Jordan, Isaac J C

AU - Metcalfe, Benjamin

AU - Garate, Virginia Ruiz

AU - Withey, Dan

PY - 2025/2/27

Y1 - 2025/2/27

N2 - People with tetraplegia typically require costly, round-the-clock care throughout their lives due to the lack of motor function. Brain-computer interfaces (BCIs) are capable of detecting imagined motor intention for individual limbs, but high-cost electroencephalography (EEG) devices are typically used. This paper compares four published motor imagery (MI) BCIs using the BCI Competition IV Dataset 2b as a benchmark. The relatively low-cost OpenBCI EEG cap is then used with each BCI 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. Additionally, two of the four MI BCIs stand out for their decoding accuracy, although all performed well.

AB - People with tetraplegia typically require costly, round-the-clock care throughout their lives due to the lack of motor function. Brain-computer interfaces (BCIs) are capable of detecting imagined motor intention for individual limbs, but high-cost electroencephalography (EEG) devices are typically used. This paper compares four published motor imagery (MI) BCIs using the BCI Competition IV Dataset 2b as a benchmark. The relatively low-cost OpenBCI EEG cap is then used with each BCI 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. Additionally, two of the four MI BCIs stand out for their decoding accuracy, although all performed well.

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A2 - Pons, Jose L.

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Jordan IJC, Metcalfe B, Garate VR, Withey D. Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap. In Pons JL, Tornero J, Akay M, editors, Converging Clinical and Engineering Research on Neurorehabilitation V: Proceedings of the 6th International Conference on Neurorehabilitation (ICNR 2024). Vol. 1. Springer Nature. 2025. p. 694-698. (Biosystems & Biorobotics). Epub 2025 Feb 27. doi: 10.1007/978-3-031-77588-8_136

Comparison of Motor Imagery Brain Computer Interfaces and Validation with the OpenBCI EEG Electrode Cap

Abstract

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Keywords

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