Cited 0 time in webofscience Cited 0 time in scopus

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

Title
Functional near infrared spectroscopy based congitive task classification using support vector machines
Authors
Abibullaev, BerdakhKang, Won SeokLee, Seung HyunAn, Jin Ung
DGIST Authors
Abibullaev, Berdakh; Kang, Won SeokAn, Jin Ung
Issue Date
2010
Citation
2010 5th International Symposium on Health Informatics and Bioinformatics, HIBIT 2010, 7-12
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
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. ©2009 IEEE.
URI
http://hdl.handle.net/20.500.11750/1867
DOI
10.1109/HIBIT.2010.5478913
Publisher
Institute of Electrical and Electronics Engineers
Related Researcher
Files:
There are no files associated with this item.
Collection:
ETC2. Conference Papers
Convergence Research Center for Wellness2. Conference Papers
Division of IoT∙Robotics Convergence Research2. Conference Papers


qrcode mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE