The hybrid BCI: Closing the Performance Gap between Standard Input Devices and the BCI

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Brain Computer Interface and eye tracking technologies may be used asalternative computer inputs for controlling a menu structure. 12 participantstook part in an experiment comparing three input modalities: the conventionalmouse and keyboard; EyeTribe Tracker alone; and Emotiv EPOCcombined with EyeTribe Tracker as a hybrid technology. The participants interactedwith a virtual environment controlled by a graphical user interfacemenu, completing three tasks: (i) Domotic control: participants navigatedthe menu to turn on the dining room light (via an actuator); (ii) Multimediacontrol: participants navigated the menu to play a video located in the livingroom and then stop playback; and (iii) Communication by iconography: participantsnavigated the menu and select the appropriate icon, in this case torequest food. Each task was timed and selections were recorded for computationof accuracy and efficiency. Using the mouse and keyboard the meanInformation Transfer Rate (ITR) for all three tasks was computed as 76.92bits/min. The eye tracker obtained a mean ITR of 41.16 bits/min. Thecollaborative input modalities consisting of eye tracking and BCI obtaineda mean ITR of 40.51 bits/min. Conventional control is clearly superior,however, the hybrid BCI closes the performance gap when compared to theuse of eye tracker alone. This technology offers a communication channelin niche areas such as computer gaming and can act as an assistive technology,but further applications to the wider population may be possible as thetechnology becomes more robust.
LanguageEnglish
Title of host publicationEEG-based Brain-Computer Interfaces for Healthcare Applications
EditorsIvan Volosyak
Place of PublicationAachen, Germany
Pages37-52
Publication statusPublished - 1 Jan 2016

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Brain computer interface
Communication
Virtual reality
Actuators
Experiments

Keywords

  • BCI

Cite this

Brennan, C., McCullagh, PJ., Galway, L., & Lightbody, G. (2016). The hybrid BCI: Closing the Performance Gap between Standard Input Devices and the BCI. In I. Volosyak (Ed.), EEG-based Brain-Computer Interfaces for Healthcare Applications (pp. 37-52). Aachen, Germany.
Brennan, C ; McCullagh, PJ ; Galway, Leo ; Lightbody, G. / The hybrid BCI: Closing the Performance Gap between Standard Input Devices and the BCI. EEG-based Brain-Computer Interfaces for Healthcare Applications. editor / Ivan Volosyak. Aachen, Germany, 2016. pp. 37-52
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Brennan, C, McCullagh, PJ, Galway, L & Lightbody, G 2016, The hybrid BCI: Closing the Performance Gap between Standard Input Devices and the BCI. in I Volosyak (ed.), EEG-based Brain-Computer Interfaces for Healthcare Applications. Aachen, Germany, pp. 37-52.

The hybrid BCI: Closing the Performance Gap between Standard Input Devices and the BCI. / Brennan, C; McCullagh, PJ; Galway, Leo; Lightbody, G.

EEG-based Brain-Computer Interfaces for Healthcare Applications. ed. / Ivan Volosyak. Aachen, Germany, 2016. p. 37-52.

Research output: Chapter in Book/Report/Conference proceedingChapter

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Brennan C, McCullagh PJ, Galway L, Lightbody G. The hybrid BCI: Closing the Performance Gap between Standard Input Devices and the BCI. In Volosyak I, editor, EEG-based Brain-Computer Interfaces for Healthcare Applications. Aachen, Germany. 2016. p. 37-52