Measuring academic affective states of students via brainwave signals

Proceedings - 2011 3rd International Conference on Knowledge and Systems Engineering, KSE 2011

Volumn , Issue , 2011, Pages 226-231

  Mampusti, Ella T ^a   Ng, Jose S ^a   Quinto, Jarren James I ^a   Teng, Grizelda L ^a   Suarez, Merlin Teodosia C ^a   Trogo, Rhia S ^a  

^a DE LA SALLE UNIVERSITY   (Philippines)

Author keywords

academic emotions; affect models; affective computing; electroencephalography; induced emotions; statistical features

Indexed keywords

ACADEMIC EMOTIONS; AFFECTIVE COMPUTING; AFFECTIVE STATE; CARD-SORTING; CROSS VALIDATION; EEG SIGNALS; ELECTROENCEPHALOGRAM SIGNALS; INDUCED EMOTIONS; K-NEAREST NEIGHBORS; MULTI LAYER PERCEPTRON; STANDARD DEVIATION; STATISTICAL FEATURES;

BANDPASS FILTERS; ELECTROENCEPHALOGRAPHY; ELECTROPHYSIOLOGY; SYSTEMS ENGINEERING;

EDUCATION;

EID: 81255177622     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/KSE.2011.43     Document Type: Conference Paper

References (23)

1. M. Teplan, "Fundamentals of EEG measurement," Measurement Science Review, vol. 2, 2002.
2. C. Niemic, "Studies of emotion: A theoretical and empirical review of psychophysiological studies of emotion," J. Undergraduate Research, vol. 1, no. 1, pp. 15-18, 2002.
3. M. Murugappan et al., "Lifting scheme for human emotion recognition using EEG," in Int.Symp.Information Technology, 2008, pp. 1-7.
4. M. Li and B.-L. Lu, "Emotion classification based on gamma-band EEG," in Conf. Proc. IEEE Eng. Med. Biol. Soc., 2009, pp. 1223-1226.
5. A. Heraz et al., "Using machine learning to predict learner emotional state from brainwaves," in 7th IEEE Int. Conf. on Advanced Learning Technologies, 2007, pp. 853-857.
6. D. O. Bos,"EEG-based emotion recognition (Tech. Rep.)," Enschede, The Netherlands, 2007.
7. A. D. Vicente and H. Pain, "Motivation diagnosis in intelligent tutoring systems," in Proc. 4th Int.Conf. on Intelligent Tutoring Systems, London, UK, 1998, pp. 86-95.
8. S. D'Mello et al., "Integrating affect sensors in an intelligent tutoring system," in Int. Conf. on Intelligent User Interfaces, 2005, pp. 7-13.
9. D. P. Goleman, Emotional Intelligence: Why It Can Matter More Than IQ for Character, Health and Lifelong Achievement. New York: Bantam Books, 1995.
10. P. Brusilovsky and E. Millan, "User models for adaptive hypermedia and adaptive educational systems," in The Adaptive Web. Pittsburgh: Springer, 2007.
11. K. W. Lindsay and I. Bone, Neurology and Neurosurgery Illustrated, 4th ed. Churchill Livingstone, 2004.
12. A. Heraz and C. Frasson, "Predicting the three major dimensions of the learner's emotions from brainwaves," Int. J. of Comput. Sci., 2007.
13. (2009). Emotiv [Online]. Available: http://www.emotiv.com
14. E. A. Berg, "A simple objective technique for measuring flexibility in thinking," J. General Psychology, vol. 39, pp. 15-22, 1948.
15. S. D'Mello et al., "AutoTutor detects and responds to learners affective and cognitive states," in Int. Conf. of the Intelligent Tutoring Systems, 2008.
16. A. Graesser et al., " Question asking and eye tracking during cognitive disequilibrium: Comprehending illustrated texts on devices when the devices break down," Memory & Cognition, vol. 33, no. 7, pp. 1235-1247, 2005. (Pubitemid 46202377)
17. M. Csikszentmihalyi, Beyond Boredom and Anxiety: Experiencing Flow in Work and Play. San Francisco: Jossey-Bass, 1975.
18. B. Woolf et al., "Emotional intelligence for computer tutors," Learning, pp. 6-15, 2007.
19. M. Murugappan et al., "Classification of human emotion from EEG using discrete wavelet transform," J. Biomedical Sci. and Eng., vol. 3, no. 4, pp. 390-396, 2010.
20. P. Petrantonakis and L. Hadjileontiadis, "Emotion recognition from brain signals using hybrid adaptive filtering and higher order crossings analysis," IEEE Trans. Affective Computing, vol. 1, pp. 81-97, July-Dec. 2010.
21. J. W. Eaton. (2002). Octave [Online]. Available: http://www.octave.org
22. P. Petrantonakis and L. Hadjileontiadis, "Emotion recognition from EEG using higher order crossings," IEEE Trans. Inf. Technol. Biomed., vol. 14, pp. 186-197, Mar. 2010.
23. I. Mierswa et al., "YALE: Rapid prototyping for complex data mining tasks," in Proc. 12th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, 2006.