An improved multiple LASSO model for steady-state visual evoked potential detection

Ruimin Wang, Keiji Iramina, Sheng Ge

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

Abstract

Improving the classification accuracy in brain–computer interface (BCI) with a short data length is important to increase the BCI system’s information transfer rate. Least absolute shrinkage and selection operator (LASSO) has been examined to be an effective way to detect the steady-state visual evoked potential (SSVEP) signals with a short time window. In this paper, an improved multiple LASSO model for SSVEP detection is proposed, which can process multichannel electroencephalogram (EEG) signals without electrode selection. EEG data from twelve healthy volunteers were used to test the improved multiple LASSO model. Compared with the traditional LASSO model, the improved multiple LASSO model gives a significantly better performance with multichannel EEG data.

Original languageEnglish
Title of host publication6th International Conference on the Development of Biomedical Engineering in Vietnam, BME6
EditorsToi Vo Van, Thanh An Nguyen Le, Thang Nguyen Duc
PublisherSpringer Verlag
Pages427-430
Number of pages4
ISBN (Print)9789811043604
DOIs
Publication statusPublished - Jan 1 2018
Event6th International Conference on the Development of Biomedical Engineering in Vietnam, BME 2016 - Ho Chi Minh, Viet Nam
Duration: Jun 27 2016Jun 29 2016

Publication series

NameIFMBE Proceedings
Volume63
ISSN (Print)1680-0737

Other

Other6th International Conference on the Development of Biomedical Engineering in Vietnam, BME 2016
CountryViet Nam
CityHo Chi Minh
Period6/27/166/29/16

All Science Journal Classification (ASJC) codes

  • Bioengineering
  • Biomedical Engineering

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  • Cite this

    Wang, R., Iramina, K., & Ge, S. (2018). An improved multiple LASSO model for steady-state visual evoked potential detection. In T. Vo Van, T. A. Nguyen Le, & T. Nguyen Duc (Eds.), 6th International Conference on the Development of Biomedical Engineering in Vietnam, BME6 (pp. 427-430). (IFMBE Proceedings; Vol. 63). Springer Verlag. https://doi.org/10.1007/978-981-10-4361-1_72