Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain–Computer Interfaces

Mikito Ogino, Suguru Kanoga, Masatane Muto, Yasue Mitsukura

Research output: Contribution to journalArticle

Abstract

An electroencephalogram (EEG)-based brain-computer interface (BCI) is a tool to non-invasively control computers by translating the electrical activity of the brain. This technology has the potential to provide patients who have severe generalized myopathy, such as those suffering from amyotrophic lateral sclerosis (ALS), with the ability to communicate. Recently, auditory oddball paradigms have been developed to implement more practical event-related potential (ERP)-based BCIs because they can operate without ocular activities. These paradigms generally make use of clinical (over 16-channel) EEG devices and natural sound stimuli to maintain the user's motivation during the BCI operation; however, most ALS patients who have taken part in auditory ERP-based BCIs tend to complain about the following factors: (i) total device cost and (ii) setup time. The development of a portable auditory ERP-based BCI could overcome considerable obstacles that prevent the use of this technology in communication in everyday life. To address this issue, we analyzed prefrontal single-channel EEG data acquired from a consumer-grade single-channel EEG device using a natural sound-based auditory oddball paradigm. In our experiments, EEG data was gathered from nine healthy subjects and one ALS patient. The performance of auditory ERP-based BCI was quantified under an offline condition and two online conditions. The offline analysis indicated that our paradigm maintained a high level of detection accuracy (%) and ITR (bits/min) across all subjects through a cross-validation procedure (for five commands: 70.0 ± 16.1 and 1.29 ± 0.93, for four commands: 73.8 ± 14.2 and 1.16 ± 0.78, for three commands: 78.7 ± 11.8 and 0.95 ± 0.61, and for two commands: 85.7 ± 8.6 and 0.63 ± 0.38). Furthermore, the first online analysis demonstrated that our paradigm also achieved high performance for new data in an online data acquisition stream (for three commands: 80.0 ± 19.4 and 1.16 ± 0.83). The second online analysis measured online performances on the different day of offline and first online analyses on a different day (for three commands: 62.5 ± 14.3 and 0.43 ± 0.36). These results indicate that prefrontal single-channel EEGs have the potential to contribute to the development of a user-friendly portable auditory ERP-based BCI.

Original languageEnglish
Article number250
JournalFrontiers in Human Neuroscience
Volume13
DOIs
Publication statusPublished - 2019 Jul 25

Fingerprint

Brain-Computer Interfaces
Evoked Potentials
Electroencephalography
Amyotrophic Lateral Sclerosis
Equipment and Supplies
Technology
Aptitude
Muscular Diseases
Motivation
Healthy Volunteers
Communication
Costs and Cost Analysis
Brain

Keywords

  • auditory event-related potential
  • brain–computer interface
  • electroencephalogram
  • portable measurement device
  • single-channel data

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Neurology
  • Psychiatry and Mental health
  • Biological Psychiatry
  • Behavioral Neuroscience

Cite this

Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain–Computer Interfaces. / Ogino, Mikito; Kanoga, Suguru; Muto, Masatane; Mitsukura, Yasue.

In: Frontiers in Human Neuroscience, Vol. 13, 250, 25.07.2019.

Research output: Contribution to journalArticle

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