Accessing Tele-Services using a Hybrid BCI Approach

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

3 Citations (Scopus)

Abstract

Brain Computer Interface (BCI) technology has achievedlimited success outside of laboratory conditions. This technology is hinderedby practical considerations of set up, lack of robustness and low InformationTransfer Rate (ITR). There are two interfaces in a BCI system:the brain's interface with the computer and the computer-environmentinterface, which provides access to applications for the user. Three userservices were implemented: control of the smart home, entertainmentand communication. These may be accessed through a graphical user interfacecontrolled by a BCI. The paper contrasts the performance of anSSVEP based system with a hybrid BCI comprising eye gaze and muscleresponse (measured at the scalp). The hybrid developed utilizes theEPOC for recording electrical potential and an EyeTribe gaze tracker;these can be combined to provide more robust interaction with applications.Average ITR for the eye tracker and hybrid approaches (190-200bpm) are higher than for our SSVEP approach (approx. 15 bpm), for thesame applications. The poor performance of our SSVEP system was dueto the temporal duration of the stimulation (7s) and partly because notall participants could achieve an accuracy of greater than 50%. The currentchallenge is the replacement of the scalp recorded muscle componentwith a reliable user modi able EEG measure.
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages110-123
Number of pages14
VolumeLNCS
DOIs
Publication statusPublished - 10 Jun 2014
Event13th International Work-Conference on Artificial Neural Networks, IWANN 2015, - Palma de Mallorca, Spain
Duration: 10 Jun 2014 → …

Conference

Conference13th International Work-Conference on Artificial Neural Networks, IWANN 2015,
Period10/06/14 → …

Fingerprint

Brain computer interface
Interfaces (computer)
Electroencephalography
Muscle
Brain
Computer systems
Communication

Keywords

  • Applications
  • Brain-Computer Interface (BCI)
  • Communication
  • Control
  • Entertainment
  • Eye-tracking
  • hBCI
  • Hybrid

Cite this

Brennan, CP ; McCullagh, PJ ; Lightbody, G ; Galway, L ; Feuser, D ; Martin, Suzanne. / Accessing Tele-Services using a Hybrid BCI Approach. Unknown Host Publication. Vol. LNCS 2014. pp. 110-123
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Brennan, CP, McCullagh, PJ, Lightbody, G, Galway, L, Feuser, D & Martin, S 2014, Accessing Tele-Services using a Hybrid BCI Approach. in Unknown Host Publication. vol. LNCS, pp. 110-123, 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, 10/06/14. https://doi.org/10.1007/978-3-319-19258-1_10

Accessing Tele-Services using a Hybrid BCI Approach. / Brennan, CP; McCullagh, PJ; Lightbody, G; Galway, L; Feuser, D; Martin, Suzanne.

Unknown Host Publication. Vol. LNCS 2014. p. 110-123.

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

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AB - Brain Computer Interface (BCI) technology has achievedlimited success outside of laboratory conditions. This technology is hinderedby practical considerations of set up, lack of robustness and low InformationTransfer Rate (ITR). There are two interfaces in a BCI system:the brain's interface with the computer and the computer-environmentinterface, which provides access to applications for the user. Three userservices were implemented: control of the smart home, entertainmentand communication. These may be accessed through a graphical user interfacecontrolled by a BCI. The paper contrasts the performance of anSSVEP based system with a hybrid BCI comprising eye gaze and muscleresponse (measured at the scalp). The hybrid developed utilizes theEPOC for recording electrical potential and an EyeTribe gaze tracker;these can be combined to provide more robust interaction with applications.Average ITR for the eye tracker and hybrid approaches (190-200bpm) are higher than for our SSVEP approach (approx. 15 bpm), for thesame applications. The poor performance of our SSVEP system was dueto the temporal duration of the stimulation (7s) and partly because notall participants could achieve an accuracy of greater than 50%. The currentchallenge is the replacement of the scalp recorded muscle componentwith a reliable user modi able EEG measure.

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