Cross-subject workload classification with a hierarchical Bayes model

NeuroImage

Volumn 59, Issue 1, 2012, Pages 64-69

  Wang, Ziheng ^a   Hope, Ryan M ^a   Wang, Zuoguan ^a   Ji, Qiang ^a   Gray, Wayne D ^a  

^a RENSSELAER POLYTECHNIC INSTITUTE   (United States)

Author keywords

Artificial neural network; EEG; Hierarchical Bayes model; Workload classification

Indexed keywords

ACCURACY; ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; CLASSIFIER; ELECTROENCEPHALOGRAPHY; FEMALE; HUMAN; HUMAN EXPERIMENT; MALE; MATHEMATICAL ANALYSIS; MENTAL LOAD; NORMAL HUMAN; PRIORITY JOURNAL; PROBABILITY; QUALITY CONTROL; TASK PERFORMANCE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; ELECTROENCEPHALOGRAPHY; FEMALE; HUMANS; MALE; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; TASK PERFORMANCE AND ANALYSIS; WORKLOAD; YOUNG ADULT;

EID: 80054712832     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.07.094     Document Type: Article

References (34)

1. Axelsson S. Combining a Bayesian classifier with visualisation: understanding the ids. Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security. VizSEC/DMSEC '04 2004, 99-108. ACM, New York, NY, USA.
2. Benferhat S., Kenaza T., Mokhtari A. A naive Bayes approach for detecting coordinated attacks. Computer Software and Applications Conference, Annual International 0 2008, 704-709.
3. Byrne E., Parasuraman R. Psychophysiology and adaptive automation. Biol. Psychol. 1996, 42:249-268.
4. Comstock, J. Raymond, Arnegard, R. J., 1992. The multi-attribute task battery for human operator workload and strategic behavior research. NASA Technical Memorandum 104174, Langley Research Center.
5. Dempster A., Laird N., Rubin D. Maximum likelihood from incomplete data via the em algorithm. J. R. Stat. Soc. 1977, 39:1-38.
6. Domingos P., Pazzani M. On the optimality of the simple Bayesian classifier under zero-one loss 1997.
7. Fairclough S., Venables L., Tattersall A. The influence of task demand and learning on the psychophysiological response. Int. J. Psychophysiol. 2005, 56:171-184.
8. Gaillard A.W. Comparing the concepts of mental load and stress. Ergonomics 1993, 36:991-1005.
9. Gelman A., Hill J. Data Analysis Using Regression and Multilevel/Hierarchical Models 2006, Cambridge University Pression. 1st ed.
10. Gevins A., Smith M.E. Neurophysiological measures of cognitive workload during human-computer interaction. Theoretical Issues in Ergonomics Science 2003, 4:113-131.
11. Gevins A., Smith M.E., Leong H., McEvoy L., Whitfield S., Du R., G.R. Monitoring working memory load during computer-based tasks with eeg pattern recognition methods. Hum. Factors 1998, 40:79-91.
12. Gowadia V., Farkas C., Valtorta M. Paid: a probabilistic agent-based intrusion detection system. computers and security 24(7):529-545. In Computers and Security 2005, 529-545.
13. Harris W.C., Hancock P., Arthur E., Caird J. Performance, workload, and fatigue changes associated with automation. Int. J. Aviat. Psychol. 1995, 5:169-185.
14. Hart S.G., Staveland L.E. Development of nasa-tlx (task load index): results of empirical and theoretical research. Human mental workload 1988, 139-183. North-Holland, Amsterdam. P.A. Hancock, N. Meshkati (Eds.).
15. Jasper H.H. Report of the committee on methods of clinical examination. Electroencephalogr. Clin. Neurophysiol. 1958, 10:370-375.
16. Kamruzzaman S.M., Rahman C.M. Text categorization using association rule and naive Bayes classifier, 9 2010.
17. Laufs H., Kleinschmidt A., Beyerle A., Salek-Haddadi A., Preibisch C., Krakow K. EEG-correlated fMRI of human alpha activity. NeuroImage 2003, 19(4):1463-1476.
18. Lysaght R.J., Hill S.G., Dick A., Plamondon B.D., Linton P.M., Wierwille W.W., Zaklad A.L., Alvah C., Bittner J., Wherry R.J. Operator workload: comprehensive review and evaluation of operator workload methodologies. AFI Technical Report 1989, 851. U.S. Army Research Institute.
19. Moller M.F. A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw. 1993, 6(4):525-533.
20. Norman D.A., Bobrow D.G. On data-limited and resource-limited processes. Cogn. Psychol. 1976, 7.
21. Norman D.A., Bobrow D.G. On the analysis of performance operating characteristics. Psychol. Rev. 1976, 83.
22. Noyes J.M., Bruneau D.P.J. A self-analysis of the nasa-tlx workload measure. Ergonomics 2007, 50:514-519.
23. P.M., Patra M.R. Network intrusion detection using naïve Bayes 2007.
24. Puttini R.S., Marrakchi Z., Me L. Bayesian classification model for real-time intrusion detection. In 22th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering 2002.
25. Qu L., Vetter V., Bird G., Qiu H., White P. A naive Bayes classifier for differential diagnosis of long qt syndrome in children. Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on 2010, 433-437.
26. Rish I. An empirical study of the naive Bayes classifier. International Joint Conference on Artificial Intelligence 2001.
27. Rubio S., Diaz E., Martin J., Puente J.M. Evaluation of subjective mental workload: a comparison of swat, nasa-tlx, and workload profile methods. Appl. Psychol. Int. Rev. 2004, 53:61-86.
28. Wilson G.F., Russel C.A. Operator functional state classification using psychophysiological features in an air traffic control task. Hum. Factors 2003, 45:381-389.
29. Wilson G.F., Russel C.A. Real-time assessment of mental workload using psychophysiological measures and artificial neural networks. Hum. Factors 2003, 45:635-643.
30. Wilson G.F., Russell C.A. Performance enhancement in an uninhabited air vehicle task using psychophysiologically determined adaptive aiding. Hum. Factors 2007, 49:1005-1018.
31. Wilson G.F., Estepp J., Davis I. A comparison of performance and psychophysiological classification of complex task performance. Human Factors and Ergonomics Society Annual Meeting Proceedings 2009, 53:141-145.
32. Wilson G.F., Estepp J., Christensen J.C. How does day-to-day variability in psychophysiological data affect classifier accuracy. Human Factors and Ergonomics Society Annual Meeting Proceedings 2010, 54:264-268.
33. Xu L., Jordan M. On convergence properties of the em algorithm for gaussian mixtures. Neural Comput. 1996, 8:129-151.
34. Zhang H. The optimality of naive Bayes. The International FLAIRS Conference 2004, Vol. 17.