Application of rough set-based neuro-fuzzy system in NIRS-based BCI for assessing numerical cognition in classroom

Kai Keng ANG, Cuntai GUAN, Kerry LEE, Jie Qi LEE, Shoko NIOKA, Britton CHANCE

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Near-infrared spectroscopy (NIRS) studies have revealed that performing mental arithmetic tasks have associated event-related hemodynamic responses that are detectable. Thus NIRS-based Brain Computer Interface (BCI) has the potential for investigating how to best teach mathematics in a classroom setting. This paper presents a novel computational intelligent method of applying rough set-based neuro-fuzzy system (RNFS) in NIRS-based BCI for assessing numerical cognition. A study is performed on 20 healthy subjects to measure 32 channels of hemoglobin responses in performing three difficulty levels of mental arithmetic. The accuracy is then presented using 5×5-fold cross-validations on the data collected. The results of applying RNFS and its Mutual Information-based Rough Set Reduction (MIRSR) for feature selection is then compared against the Naïve Bayesian Parzen Window classifier and other MI-based feature selection algorithms. The results of applying RNFS yielded significantly better accuracy of 75.7% compared to the other methods, thus demonstrating the potential of RNFS in NIRS-based BCI for assessing numerical cognition. Copyright © 2010 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Original languageEnglish
Title of host publication2010 International Joint Conference on Neural Networks (IJCNN 2010)
Place of PublicationSpain
PublisherIEEE
Pages977-983
ISBN (Electronic)9781424469185
ISBN (Print)9781424469178, 9781424469161
DOIs
Publication statusPublished - 2010

Citation

Ang, K. K., Guan, C., Lee, K., Lee, J. Q., Nioka, S., & Chance, B. (2010). Application of rough set-based neuro-fuzzy system in NIRS-based BCI for assessing numerical cognition in classroom. In 2010 International Joint Conference on Neural Networks (IJCNN 2010) (pp. 977-983). Spain: IEEE.

Keywords

  • Classification algorithms
  • Optical filters
  • Optical attenuators
  • Hemodynamics
  • Entropy
  • Cognition
  • Pragmatics

Fingerprint Dive into the research topics of 'Application of rough set-based neuro-fuzzy system in NIRS-based BCI for assessing numerical cognition in classroom'. Together they form a unique fingerprint.