Dynamic stopping using eSVM scores analysis for event-related potential brain-computer interfaces

Vo Anh Kha, Diep N. Nguyen, Ha Hoang Kha, Eryk Dutkiewicz

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

2 Citations (Scopus)

Abstract

In brain-computer interface (BCI) research, there must be a trade-off between accuracy and speed of the BCI system, especially those based on event-related potentials (ERPs). This paper proposes a novel method which can significantly increase the spelling bit rate while also maintaining the desired accuracy. We provide an adaptive real-time stopping method based on the scores of ensemble support vector machine classifiers. We apply a criteria assessment process on the classifiers' scores to dynamically stop the ERP-evoked paradigms at any flashing sequence. Our experiments were conducted on three different P300-Speller data sets (BCI Competition II, BCI Competition III and Akimpech). Our proposed framework significantly outperformed the related state-of-the-art studies in terms of character output accuracy and elicitation bit rate rise between static and dynamic stopping schemes. We improve the average bit rate by over 80% while perfectly maintaining the best original static accuracy of over 96%.

Original languageEnglish
Title of host publication2017 11th International Symposium on Medical Information and Communication Technology (ISMICT)
Subtitle of host publicationproceedings
Place of PublicationPiscataway , NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages82-85
Number of pages4
ISBN (Electronic)9781509054640
ISBN (Print)9781509054657
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event11th International Symposium on Medical Information and Communication Technology, ISMICT 2017 - Lisbon, Portugal
Duration: 6 Feb 20178 Feb 2017

Other

Other11th International Symposium on Medical Information and Communication Technology, ISMICT 2017
CountryPortugal
CityLisbon
Period6/02/178/02/17

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  • Cite this

    Kha, V. A., Nguyen, D. N., Kha, H. H., & Dutkiewicz, E. (2017). Dynamic stopping using eSVM scores analysis for event-related potential brain-computer interfaces. In 2017 11th International Symposium on Medical Information and Communication Technology (ISMICT): proceedings (pp. 82-85). Piscataway , NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ISMICT.2017.7891773