Towards incorporating affective feedback into context-aware intelligent environments

2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015

Volumn , Issue , 2015, Pages 49-55

  Saha, Deba Pratim ^a   Martin, Thomas L ^a   Knapp, R Benjamin ^a  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

Intelligent Environment; Stroop Test; Technostress

Indexed keywords

INTELLIGENT AGENTS; INTELLIGENT SYSTEMS;

AMBIENT INTELLIGENCE; AMBIENT INTELLIGENT SYSTEMS; COGNITIVE RESOURCES; GROUND TRUTH DATA; IMPLICIT COMMUNICATIONS; INTELLIGENT ENVIRONMENT; STROOP TEST; TECHNOSTRESS;

INTELLIGENT COMPUTING;

EID: 84964012153     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ACII.2015.7344550     Document Type: Conference Paper

References (36)

1. F. Doctor, R. Iqbal, and V. Zamudio, "Introduction to the thematic issue on Affect Aware Ubiquitious Computing," Journal of Ambient Intelligence and Smart Environments, vol. 7, no. 1, pp. 3-4, Jan. 2015.
2. R. Cowie, E. Douglas-Cowie, N. Tsapatsoulis, G. Votsis, S. Kollias, W. Fellenz, and J. Taylor, "Emotion recognition in human-computer interaction," IEEE Signal Processing Magazine, vol. 18, no. 1, pp. 32-80, Jan. 2001.
3. Z. Hammal and M. Teodosia Suarez, "Towards Context Based Affective Computing," in 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction (ACII), Sep. 2013, pp. 802-802.
4. S.-I. Yang and S.-B. Cho, "Recognizing human activities from accelerometer and physiological sensors," in IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2008. MFI 2008, Aug. 2008, pp. 100-105.
5. F.-T. Sun, C. Kuo, H.-T. Cheng, S. Buthpitiya, P. Collins, and M. Griss, "Activity-Aware Mental Stress Detection Using Physiological Sensors," Mobile Computing, Applications, and Services, pp. 211-230, Jan. 2012.
6. M. Baldauf, S. Dustdar, and F. Rosenberg, "A Survey on Context-Aware Systems," Int. J. Ad Hoc Ubiquitous Comput., vol. 2, no. 4, pp. 263-277, Jun. 2007.
7. T. Hofer, M. Pichler, G. Leonhartsberger, J. Altmann, and W. Retschitzegger, "Context-awareness on mobile devices the hydrogen approach," in Proceedings of the 36th Annual Hawaii International Conference on System Sciences, 2002, pp. 292-302.
8. P. Prekop and M. Burnett, "Activities, context and ubiquitous computing," Computer Communications, vol. 26, no. 11, pp. 1168-1176, Jul. 2003.
9. J. C. Augusto, V. Callaghan, D. Cook, A. Kameas, and I. Satoh, "Intelligent Environments: A manifesto," Human-centric Computing and Information Sciences, vol. 3, no. 1, p. 12, 2013.
10. R. Riedl, H. Kindermann, A. Auinger, and A. Javor, "Computer Breakdown as a Stress Factor during Task Completion under Time Pressure: Identifying Gender Differences Based on Skin Conductance," Advances in Human-Computer Interaction, vol. 2013, p. e420169, Oct. 2013.
11. R. Riedl, "On the Biology of Technostress: Literature Review and Research Agenda," SIGMIS Database, vol. 44, no. 1, pp. 18-55, Nov. 2012.
12. J. J. Braithwaite, D. G. Watson, R. Jones, and M. Rowe, "A Guide for Analysing Electrodermal Activity (EDA) &Skin Conductance Responses (SCRs) for Psychological Experiments," Psychophysiology, vol. 49, pp. 1017-1034, 2013.
13. S. H. Fairclough, "Fundamentals of physiological computing," Interacting with Computers, vol. 21, no. 1-2, pp. 133-145, Jan. 2009.
14. D. Novak, A. Nagle, and R. Riener, "Linking recognition accuracy and user experience in an affective feedback loop," IEEE Transactions on Affective Computing, pp. 1-1, 2014.
15. R. Calvo and S. D'Mello, "Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications," IEEE Transactions on Affective Computing, vol. 1, no. 1, pp. 18-37, Jan. 2010.
16. K.-I. Benta, A. Hoszu, L. Vcariu, and O. Cre, "Agent Based Smart House Platform with Affective Control," in Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to Increase Digital Citizenship, ser. EATIS '09. New York, NY, USA: ACM, 2009, pp. 18:1-18:7.
17. Z. Zeng, M. Pantic, G. Roisman, and T. Huang, "A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 1, pp. 39-58, Jan. 2009.
18. S. D. Kreibig, "Autonomic nervous system activity in emotion: A review," Biological Psychology, vol. 84, no. 3, pp. 394-421, Jul. 2010.
19. K. Plarre, A. Raij, S. Hossain, A. Ali, M. Nakajima, M. al'Absi, E. Ertin, T. Kamarck, S. Kumar, M. Scott, D. Siewiorek, A. Smailagic, and L. Wittmers, "Continuous inference of psychological stress from sensory measurements collected in the natural environment," in 2011 10th International Conference on Information Processing in Sensor Networks (IPSN), Apr. 2011, pp. 97-108.
20. J. Jaimovich, "Emotion recognition from physiological indicators for musical applications," Ph.D., Queen's University Belfast, 2013.
21. K. H. Kim, S. W. Bang, and S. R. Kim, "Emotion recognition system using short-term monitoring of physiological signals," Medical and Biological Engineering and Computing, vol. 42, no. 3, pp. 419-427, May 2004.
22. J. Kim and E. Andre, "Emotion recognition based on physiological changes in music listening," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 12, pp. 2067-2083, Dec. 2008.
23. A. Guo, S. Raghu, X. Xie, S. Ismail, X. Luo, J. Simoneau, S. Gilliland, H. Baumann, C. Southern, and T. Starner, "A Comparison of Order Picking Assisted by Head-up Display (HUD), Cart-mounted Display (CMD), Light, and Paper Pick List," in Proceedings of the 2014 ACM International Symposium on Wearable Computers, ser. ISWC '14. New York, NY, USA: ACM, 2014, pp. 71-78.
24. D. F. Barbosa, F. J. A. Prada, M. F. Glanner, O. d. T. Nbrega, and C. Crdova, "Cardiovascular response to Stroop test: comparison between the computerized and verbal tests," Arquivos Brasileiros de Cardiologia, vol. 94, no. 4, pp. 507-511, Apr. 2010.
25. J. Zhai and A. Barreto, "Stress Detection in Computer Users Based on Digital Signal Processing of Noninvasive Physiological Variables," in 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2006. EMBS '06, Aug. 2006, pp. 1355-1358.
26. P. Renaud and J.-P. Blondin, "The stress of Stroop performance: physiological and emotional responses to colorword interference, task pacing, and pacing speed," International Journal of Psychophysiology, vol. 27, no. 2, pp. 87-97, Sep. 1997.
27. Y. Shi, M. H. Nguyen, P. Blitz, B. French, S. Fisk, O. D. L. Torre, A. Smailagic, D. P. Siewiorek, M. A. Absi, E. Ertin, T. Kamarck, and S. Kumar, "Personalized Stress Detection from Physiological Measurements," in 2010 International Symposium on Quality of Life Technology, 2010.
28. B. Figner and R. Murphy, "Using skin conductance in judgment and decision making research," in A Handbook of Process Tracing Methods for Decision Research: A Critical Review and Users Guide. Psychology Press, May 2011.
29. A. H. H. Ngu, Q. Z. Sheng, D. Q. Huynh, and R. Lei, "Combining Multi-visual Features for Efficient Indexing in a Large Image Database," The VLDB Journal, vol. 9, no. 4, pp. 279-293, Apr. 2001.
30. J. Hernandez, R. R. Morris, and R. W. Picard, "Call Center Stress Recognition with Person-Specific Models," in Affective Computing and Intelligent Interaction, ser. Lecture Notes in Computer Science, S. DMello, A. Graesser, B. Schuller, and J.-C. Martin, Eds. Springer Berlin Heidelberg, 2011, pp. 125-134.
31. C. Setz, B. Arnrich, J. Schumm, R. La Marca, G. Troster, and U. Ehlert, "Discriminating Stress From Cognitive Load Using a Wearable EDA Device," IEEE Transactions on Information Technology in Biomedicine, vol. 14, no. 2, pp. 410-417, Mar. 2010.
32. J. Zhai, A. Barreto, C. Chin, and C. Li, "Realization of stress detection using psychophysiological signals for improvement of human-computer interactions," in IEEE SoutheastCon, 2005. Proceedings, Apr. 2005, pp. 415-420.
33. M. Kubat and S. Matwin, "Addressing the Curse of Imbalanced Training Sets: One-Sided Selection," in In Proceedings of the Fourteenth International Conference on Machine Learning. Morgan Kaufmann, 1997, pp. 179-186.
34. M. Kubat, R. C. Holte, and S. Matwin, "Machine Learning for the Detection of Oil Spills in Satellite Radar Images," Machine Learning, vol. 30, no. 2-3, pp. 195-215, Feb. 1998.
35. Y. Sasaki, "The truth of the F-measure," Teach Tutor mater, pp. 1-5, 2007.
36. J. Wijsman, B. Grundlehner, J. Penders, and H. Hermens, "Trapezius Muscle EMG As Predictor of Mental Stress," in Wireless Health 2010, ser. WH '10. New York, NY, USA: ACM, 2010, pp. 155-163.