An Investigation of Decision Analytic Methodologies for Stress Identification

[1]H. Abdi, L.J. Williams, “Principal Components Analysis”, Wiley Interdisciplinary Reviews: Computational Statistics, Vol. 2, No. 4, 2010, pp. 433–459.10.1002/wics.101 Search in Google Scholar

[2]A. Akbas, “Evaluation of the Physiological Data Indicating the Dynamic Stress Level of Drivers”, Scientific Research and Essays, Vol. 6, No. 2, 2011, pp. 430-439. Search in Google Scholar

[3]APA (American Psychological Association), “Stress in America: Our Health at Risk”, Accessed on June 2012. URL: http://www.apa.org/news/press/releases/stress/index.aspx Search in Google Scholar

[4]F. Angus, J. Zhai, “Front-end Analog Pre-processing for Real Time Psychophysiological Stress Measurements”, Proceedings of the 9^th World Multi-Conference on Systematics, Cybernetics and Informatics (WMSCI05), 2005, pp. 218-221. Search in Google Scholar

[5]J. Bakker, M. Pechenizkiy, N. Sidorava, “What’s Your Current Stress Level? Detection of Stress Patterns from GSR Sensor Data”, Proceedings of the11^th IEEE International Conference on Data Mining Workshops, 2011, pp. 573-580.10.1109/ICDMW.2011.178 Search in Google Scholar

[6]L. Bergman, P. Corabian, C. Harstall, “Effectiveness of Organisational Interventions for the Prevention of Occupational Stress”, Alberta: Institute of Health Economics, Accessed on June 2012. URL: http://www.ihe.ca/publications/library/2009/effectiveness-of-organizational- interventions-for-the-prevention-of-workplace-stress/ Search in Google Scholar

[7]A.-M. Cretu, and P. Payeur, “Biologically-inspired Visual Attention Features for a Vehicle Classification Task”, The International Journal on Smart Sensing and Intelligent Systems, Vol. 4, No. 3, 2011, pp. 402-423.10.21307/ijssis-2017-447 Search in Google Scholar

[8]J. R.T. Davidson, S.W. Book, “Assessment of a New Self-Rating Scale for Post-traumaticStress Disorder”, Psychological Medicine, Vol. 27, No. 1, 1997, pp.153-160.10.1017/S00332917960042299122295 Search in Google Scholar

[9]R. Duda, P. Hart., D. Stork, “Pattern Classification”, (2nd Ed.).Wiley Inter-science, 2001 Search in Google Scholar

[10]FlexComp, “ProComp Software Version 1.41 User’s Manual”, Thought Technology Ltd., Montreal, QC, Canada, 1994. Search in Google Scholar

[11]M. Hall, “Correlation Based Feature Selection for Machine Learning”, Doctoral Dissertation, University of Waikato, 1999. Search in Google Scholar

[12]S. Haykin, “Neural Networks: A Comprehensive Foundation (2^nd Ed.)”, Englewood Cliffs, NJ: Prentice-Hall, 1998. Search in Google Scholar

[13]J.A. Healey, “Wearable and Automotive Systems for Affect Recognition from Physiology”, Doctoral Dissertation, Massachusetts Institute of Technology, MA, 2000. Search in Google Scholar

[14]J.A. Healy, R.W. Picard, “Detecting Stress During Real-World Driving Tasks Using Physiological Sensors”, IEEE Transaction on Intelligent Transportation System, Vol. 6, No. 2, 2005, pp.156-166.10.1109/TITS.2005.848368 Search in Google Scholar

[15]E. Jovanov, A. O’Donnell Lords, D. Raskovic, P.G. Cox, R. Adhami, F. Andrasik, "Stress Monitoring Using a Distributed Wireless Intelligent Sensor System", IEEE Engineering in Medicine and Biology Magazine, Vol. 22, No. 3, 2003, pp. 49-55.10.1109/MEMB.2003.121362612845819 Search in Google Scholar

[16]A. Kaklauskas, E.K. Zavadskas, V. Pruskus, A. Vlasenko, L. Bartkiene, “Recommended Biometric Stress Management System”, Expert Systems with Applications, Vol. 38, 2011, pp.14011-14025.10.1016/j.eswa.2011.04.209 Search in Google Scholar

[17]A. Malhi, R. Gao, “Feature Selection for Defect Classification in Machine Condition Monitoring”, 20^th IEEE Instrumentation Measurement Technology Conf., Vol. 1, 2003, Vail, CO, pp. 36-41. Search in Google Scholar

[18]A. Moosavian, H. Ahmadi, A. Tabatabaeefar, B. Sakhaei, “An Appropriate Procedure for Detection of Journal-Bearing Fault Using Power Spectral Density, K-Nearest Neighbor and Support Vector Machine”, The International Journal on Smart Sensing and Intelligent Systems, Vol.5, No. 3, 2012, pp.685-700.10.21307/ijssis-2017-502 Search in Google Scholar

[19]M. Nako, “Work-related Stress and Psychosomatic Medicine”, BioPsycho Social Medicine, Vol. 4, No. 4, 2010, Doi:10.1186/1751-0759-4-4.10.1186/1751-0759-4-4288289620504368 Search in Google Scholar

[20]Office for National Statistics, Social and Vital Statistics Division and Northern Ireland Statistics and Research Agency. Central Survey Unit, 2010. “Labour Force Survey, 1975-2010”, Colchester, Essex: UK Data Archive. URL:http://www.esds.ac.uk/government/lfs/ Search in Google Scholar

[21]PHYSIONET, “Stress Recognition in Automobile Drivers (drivedb)”, Accessed on June 2012. URL: http://physionet.org/cgi-bin/atm/ATM/. Search in Google Scholar

[22]K. Polat, S. Güne?, “A Novel Hybrid Intelligent Method Based on C4.5 Decision Tree Classifier and One-against-all Approach for Multi-Class Classification Problems”, Expert Systems with Applications, Vol. 36, 2009, pp. 1587-1592.10.1016/j.eswa.2007.11.051 Search in Google Scholar

[23]I. Rish, “An Empirical Study of the Naive Bayes Classifier”, Proceedings of IJCAI-01 workshop on Empirical Methods in AI, 2001, pp. 41-46, Sicily, Italy. Search in Google Scholar

[24]S. Ruggieri, “Efficient C4.5”, IEEE Transactions on Knowledge and Data Engineering, Vol. 14, No. 2, 2002, pp. 438-444.10.1109/69.991727 Search in Google Scholar

[25]V. Vapnik, “The Nature of Statistical Learning Theory”, Springer-Verlag, New York, NY, USA. 1995. ISBN: 0-387-94559-8.10.1007/978-1-4757-2440-0 Search in Google Scholar

[26]D. Watson, J.W. Pennebaker, “Health Complaints, Stress, and Distress: Exploring the Central Role of Negative Affectivity”, Psychological Review, Vol. 96, No. 2, 1989, pp. 234-254.10.1037/0033-295X.96.2.234 Search in Google Scholar

[27]S. Wold, “Principal Component Analysis”, Chemometrics and Intelligent Laboratory Systems, Vol. 2, No. 1-3, 1987, pp. 37-52.10.1016/0169-7439(87)80084-9 Search in Google Scholar

[28]K.Y. Yeung, W.L. Ruzzo, “Principal Component Analysis for Clustering Gene Expression Data”, Bioinformatics, Vol. 17, No. 9, 2001, pp. 763-774.10.1093/bioinformatics/17.9.76311590094 Search in Google Scholar

[29]L. Yu, H. Liu, “Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution”, Proceedings of the 20^th International Conference on Machine Learning (ICML- 2003), Washington, DC, Vol. 3, 2003, pp. 856-863. Search in Google Scholar

[30]J. Zhai, A. Barreto, “Stress Detection in Computer Users Through Non-Invasive Monitoring of Physiological Signals”, Biomedical Science Instrumentation, Vol. 42, 2006, pp. 495-500. Search in Google Scholar

[31]L. Zhang, T. Tamminedi, A. Ganguli, G. Yosiphon, J. Yadegar, “Hierarchical Multiple Sensor Fusion Using Structurally Learned Bayesian Network”, Proceedings of Wireless Health, 2010, pp. 174-183.10.1145/1921081.1921102Search in Google Scholar