Towards Paradigm-Independent Brain Computer Interfaces

Albina Li, Kanat Alimanov, Siamac Fazli, Min Ho Lee

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

1 Citation (Scopus)

Abstract

Brain-computer interfaces (BCIs) provide an alternative pathway of communication between humans and external devices. There are three major paradigms that are commonly employed for BCI: Motor-imagery (MI), event-related potential (ERP), and steady-state visually evoked potential (SSVEP). Three individual paradigms each have their own pros and cons in terms of the available number of classes, eye/mental fatigue, illiteracy rate, and etc. When designing BCI applications a whole range of factors need to be taken into account, such as the patient's psychological and physical condition, environmental limitations, necessary number of classes and required accuracy level, among others. Given the limitations of the individual paradigms, it may not always be possible to satisfy all requirements with a current unimodal paradigm. In this study, we propose the concept of a paradigm-independent BCI framework, in which all three paradigms are available at the same time and can be used interchangeably. To do this, task-related features from the individual paradigms were extracted and cross-validated. Average classification accuracy for three-paradigm decoding was 74.84%(±8.49) across 49 subjects. By considering the three major BCI paradigms, namely MI, ERP and SSVEP and by creating a machine learning framework, which is able to successfully decode the paradigm from individual trials, we pave the way towards new and more complex applications, where the limitations of unimodal BCI paradigms are alleviated.

Original languageEnglish
Title of host publication8th International Winter Conference on Brain-Computer Interface, BCI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728147079
DOIs
Publication statusPublished - Feb 2020
Event8th International Winter Conference on Brain-Computer Interface, BCI 2020 - Gangwon, Korea, Republic of
Duration: Feb 26 2020Feb 28 2020

Publication series

Name8th International Winter Conference on Brain-Computer Interface, BCI 2020

Conference

Conference8th International Winter Conference on Brain-Computer Interface, BCI 2020
CountryKorea, Republic of
CityGangwon
Period2/26/202/28/20

Keywords

  • BCI
  • EEG
  • ERP
  • MI
  • paradigm-independent
  • SSVEP

ASJC Scopus subject areas

  • Behavioral Neuroscience
  • Cognitive Neuroscience
  • Artificial Intelligence
  • Human-Computer Interaction

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