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

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2010, Pages

  Ang, Kai Keng ^a   Guan, Cuntai ^a   Lee, Kerry ^b   Lee, Jie Qi ^b   Nioka, Shoko ^c   Chance, Britton ^c  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN COMPUTER INTERFACE; CALCULATIONS; CLASSIFICATION (OF INFORMATION); FEATURE SELECTION; FUZZY INFERENCE; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; INFRARED DEVICES; INTERFACES (COMPUTER); NUMERICAL METHODS; ROUGH SET THEORY; TEACHING;

ARITHMETIC TASKS; CLASSROOM SETTINGS; HAEMODYNAMIC RESPONSE; HAEMOGLOBINS; HEALTHY SUBJECTS; INTELLIGENT METHOD; MENTAL ARITHMETIC; NEUROFUZZY SYSTEM; NUMERICAL COGNITION; ROUGH-SET BASED;

NEAR INFRARED SPECTROSCOPY;

EID: 79959481690     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2010.5596921     Document Type: Conference Paper

References (23)

1. L. Zamarian, A. Ischebeck, and M. Delazer, "Neuroscience of learning arithmetic - Evidence from brain imaging studies," Neuroscience & Biobehavioral Reviews, vol. 33, no. 6, pp. 909-925, 2009.
2. A. Villringer and B. Chance, "Non-invasive optical spectroscopy and imaging of human brain function," Trends Neurosci., vol. 20, no. 10, pp. 435-442, 1997.
3. A. F. Abdelnour and T. Huppert, "Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model," NeuroImage, vol. 46, no. 1, pp. 133-143, 2009.
4. J. R. Wolpaw, N. Birbaumer, D. J. McFarland, G. Pfurtscheller, and T. M. Vaughan, "Brain-computer interfaces for communication and control," Clin. Neurophysiol., vol. 113, no. 6, pp. 767-791, Jun. 2002.
5. S. Coyle, T. Ward, C. Markham, and G. McDarby, "On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces," Physiol. Meas., vol. 25, no. 4, p. 815, Aug. 2004.
6. R. Sitaram, H. Zhang, C. Guan, M. Thulasidas, Y. Hoshi, A. Ishikawa, K. Shimizu, and N. Birbaumer, "Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface," NeuroImage, vol. 34, no. 4, pp. 1416-1427, Feb. 2007.
7. S. M. Coyle, T. E. Ward, and C. Markham, M., "Brain-computer interface using a simplified functional near-infrared spectroscopy system," J. Neural Eng., vol. 4, no. 3, p. 219, Sep. 2007.
8. M. Tanida, K. Sakatani, R. Takano, and K. Tagai, "Relation between asymmetry of prefrontal cortex activities and the autonomic nervous system during a mental arithmetic task: near infrared spectroscopy study," Neurosci. Lett., vol. 369, no. 1, pp. 69-74, 2004.
9. E. Unlu, H. Bolay, and A. Akin, "Hemodynamic correlates of mental arithmetic task in migraine," in Proc. BIYOMUT, 2009, pp. 1-4.
10. K. Ciftci, B. Sankur, Y. Kahya, and A. Akin, "Complexity and functional clusters of the brain during mental arithmetic," in Proc. SIU, 2008, pp. 1-4.
11. L. Hirshfield, K. Chauncey, R. Gulotta, A. Girouard, E. Solovey, R. Jacob, A. Sassaroli, and S. Fantini, "Combining Electroencephalograph and Functional Near Infrared Spectroscopy to Explore Users' Mental Workload," in Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, 2009, pp. 239-247.
12. L. M. Hirshfield, E. T. Solovey, A. Girouard, J. Kebinger, R. J. K. Jacob, A. Sassaroli, and S. Fantini, "Brain measurement for usability testing and adaptive interfaces: an example of uncovering syntactic workload with functional near infrared spectroscopy," in Proc. ACM CHI, 2009, pp. 2185-2194.
13. M. H. Ashcraft, M. M. Guillaume, and H. R. Brian, "Chapter 4 Mathematical Cognition and the Problem Size Effect," in Psychology of Learning and Motivation: Academic Press, 2009, vol. Volume 51, pp. 121-151.
14. M. I. Núñez-Peña, M. L. Honrubia-Serrano, and C. Escera, "Problem size effect in additions and subtractions: an event-related potential study," Neurosci. Lett., vol. 373, no. 1, pp. 21-25, 2004.
15. N. Kwak and C.-H. Choi, "Input feature selection by mutual information based on Parzen window," IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 12, pp. 1667-1671, Dec. 2002.
16. E. Parzen, "On Estimation of a Probability Density Function and Mode," Annals Math. Statist., vol. 33, no. 3, pp. 1065-1076, Sep. 1962.
17. A. K. Jain, R. P. W. Duin, and J. Mao, "Statistical pattern recognition: a review," IEEE Trans. Pattern Anal. Mach. Intell., vol. 22, no. 1, pp. 4-37, 2000 2000.
18. R. Battiti, "Using mutual information for selecting features in supervised neural net learning," IEEE Trans. Neural Netw., vol. 5, no. 4, pp. 537-550, 1994 1994.
19. K. K. Ang and C. Quek, "Rough Set-based Neuro-Fuzzy System," in Proc. IJCNN'06, 2006, pp. 742-749.
20. L. A. Zadeh, "Fuzzy logic, neural networks, and soft computing," Communications of the ACM, vol. 37, no. 3, 1994 1994.
21. K. K. Ang and C. Quek, "RSPOP: Rough Set-Based Pseudo Outer-Product Fuzzy Rule Identification Algorithm," Neural Comput., vol. 17, no. 1, pp. 205-243, Jan. 2005.
22. K. E. Jang, S. Tak, J. Jung, J. Jang, Y. Jeong, and J. C. Ye, "Wavelet minimum description length detrending for near-infrared spectroscopy," Journal of Biomedical Optics, vol. 14, no. 3, pp. 1-13, May 2009.
23. T. J. Huppert, S. G. Diamond, M. A. Franceschini, and D. A. Boas, "HomER: a review of time-series analysis methods for near-infrared spectroscopy of the brain," Appl. Opt., vol. 48, no. 10, pp. D280-D298, 2009.