Functional near infrared spectroscopy based congitive task classification using support vector machines

Berdakh Abibullaev, Won Seok Kang, Seung Hyun Lee, Jinung An

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

Abstract

the present study analyzes brain hemodynamic concentration of frontal cortex during four cognitive mental tasks. The analysis procedure consists of three sequential steps. First, the strong brain activation regions have been investigated thoroughly from all subjects in order to And a proper electrode location that generates important brain stimuli. Second, a feature extraction method that is based on wavelet transforms and denoising technique for extraction of important task-relevant features. Finally, support vector machines have been using in the classification of mental tasks with wavelet input coefficients. By applying the methodology for 4-subjects in average we achieved 92 % classification rates. However, the results depend on the type of the task that subject were performing. It is expect that the proposed method can be a basic technology for brain-computer interface by combining wavelets with support vector machines.

Original languageEnglish
Title of host publication2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010
Pages7-12
Number of pages6
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010 - Antalya, Turkey
Duration: Apr 20 2010Apr 22 2010

Other

Other2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010
CountryTurkey
CityAntalya
Period4/20/104/22/10

Fingerprint

Near infrared spectroscopy
Near-Infrared Spectroscopy
Support vector machines
Brain
Brain-Computer Interfaces
Wavelet Analysis
Brain computer interface
Hemodynamics
Frontal Lobe
Wavelet transforms
Feature extraction
Electrodes
Chemical activation
Technology
Support Vector Machine

Keywords

  • BCI
  • Component
  • Functional near-infrared spectroscopy
  • Mental task classification
  • Support vector machines
  • Wavelets

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Abibullaev, B., Kang, W. S., Lee, S. H., & An, J. (2010). Functional near infrared spectroscopy based congitive task classification using support vector machines. In 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010 (pp. 7-12). [5478913] https://doi.org/10.1109/HIBIT.2010.5478913

Functional near infrared spectroscopy based congitive task classification using support vector machines. / Abibullaev, Berdakh; Kang, Won Seok; Lee, Seung Hyun; An, Jinung.

2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010. 2010. p. 7-12 5478913.

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

Abibullaev, B, Kang, WS, Lee, SH & An, J 2010, Functional near infrared spectroscopy based congitive task classification using support vector machines. in 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010., 5478913, pp. 7-12, 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010, Antalya, Turkey, 4/20/10. https://doi.org/10.1109/HIBIT.2010.5478913
Abibullaev B, Kang WS, Lee SH, An J. Functional near infrared spectroscopy based congitive task classification using support vector machines. In 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010. 2010. p. 7-12. 5478913 https://doi.org/10.1109/HIBIT.2010.5478913
Abibullaev, Berdakh ; Kang, Won Seok ; Lee, Seung Hyun ; An, Jinung. / Functional near infrared spectroscopy based congitive task classification using support vector machines. 2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010. 2010. pp. 7-12
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