Classification of multiclass EEG signal related to mental task using higuchi fractal dimension and 10-Statistic Parameters-Support Vector Machine

Abdullah Basuki Rahmat, Keiji Iramina

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

1 Citation (Scopus)

Abstract

Nowadays, Not only the accuracy of a classification system but also a feature extraction method is an important matter in a Brain Computer Interface Application. In this paper, we investigated the multiclass classification of mental task using EEG signal. Higuchi Fractal Dimension and 10-Statistic Parameters were used as feature extraction method. The 10-statistic parameters are central tendency type that is, maximum value, minimum value, mean, standard deviation, median, mode, variance, first-quartile, third-quartile, interchange quartile. Multiclass Support Vector Machine with One-against-All strategy is applied to classify EEG signal related to the mental task. The result shows that the Multiclass SVM classifier with 1-against-All strategy using 10-Statistic Parameters has a higher accuracy when compared to Higuchi Fractal Dimension-SVM, Extreme Learning Machine, Back Propagation Neural Network, both of Support Vector Machine 1-versus-1 strategy and 1-versus-All strategy. The average accuracy ranging between 99.2% and 100% for 10-Statistic Parameters-SVM and HFD-SVM ranging from 60.22% to 91.91% were gained for five mental task classes.

Original languageEnglish
Title of host publicationTENCON 2015 - 2015 IEEE Region 10 Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479986415
DOIs
Publication statusPublished - Jan 5 2016
Event35th IEEE Region 10 Conference, TENCON 2015 - Macau, Macao
Duration: Nov 1 2015Nov 4 2015

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume2016-January
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Other

Other35th IEEE Region 10 Conference, TENCON 2015
CountryMacao
CityMacau
Period11/1/1511/4/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering

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    Rahmat, A. B., & Iramina, K. (2016). Classification of multiclass EEG signal related to mental task using higuchi fractal dimension and 10-Statistic Parameters-Support Vector Machine. In TENCON 2015 - 2015 IEEE Region 10 Conference [7372967] (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2016-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2015.7372967