Two stress detection schemes based on physiological signals for real-time applications

Proceedings - 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIHMSP 2010

Volumn , Issue , 2010, Pages 364-367

  De Santos Sierra, Alberto ^a   Avila, Carmen Sanchez ^a   Casanova, Javier Guerra ^a   Del Pozo, Gonzalo Bailador ^a   Vera, Vicente Jara ^a  

^a Centro de Domótica Integral CeDInt   (Spain)

Author keywords

Fisher lineal discriminant; Galvanic Skin Response; Heart Rate; K NN classification; Real time applications; Security systems; Stress detection

Indexed keywords

FISHER LINEAL DISCRIMINANT; GALVANIC SKIN RESPONSE; HEART RATE; K-NN CLASSIFICATION; REAL-TIME APPLICATION; STRESS DETECTION;

ELECTROPHYSIOLOGY; MULTIMEDIA SIGNAL PROCESSING; PHYSIOLOGICAL MODELS; SECURITY SYSTEMS; SIGNAL DETECTION; SIGNAL PROCESSING; STRESSES; YIELD STRESS;

REAL TIME SYSTEMS;

EID: 78650467491     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IIHMSP.2010.95     Document Type: Conference Paper

References (21)

1. J. A. Healey and R. W. Picard, "Detecting stress during real-world driving tasks using physiological sensors," IEEE Transactions on Intelligent Transportation Systems, vol. 6, no. 2, pp. 156-166, Jun. 2005.
2. W. Picard, J. A. Healey, and J. A. Healey, "Wearable and automotive systems for affect recognition from physiology," MIT, Tech. Rep., 2000.
3. C. L. Lisetti and F. Nasoz, "Using noninvasive wearable computers to recognize human emotions from physiological signals," EURASIP Journal on Applied Signal Processing:, vol. 11, pp. 1672-1687, 2004.
4. A. Barreto and J. Zhai, "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. EMBS '06., August 2006, pp. 1355-1358.
5. J. Zhai, A. Barreto, C. Chin, and C. Li, "Realization of stress detection using psychophysiological signals for improvement of human-computer interactions," in SoutheastCon, 2005. Proceedings., April 2005, pp. 415-420.
6. A. Barreto, J. Zhai, and M. Adjouadi, "Non-intrusive physiological monitoring for automated stress detection in human-computer interaction," in Human-Computer Interaction, ser. Lecture Notes in Computer Science, vol. 4796. Springer Berlin / Heidelberg, 2007, pp. 29-38.
7. J. Zhai and A. Barreto, "Stress recognition using non-invasive technology," in Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA., 2006, pp. 395-401.
8. N. Sarkar, "Psychophysiological control architecture for human-robot coordination-concepts and initial experiments," in IEEE International Conference on Robotics and Automation, 2002. Proceedings. ICRA'02., vol. 4, 2002, pp. 3719-3724.
9. A. Cano-Vindel, J. J. Miguel-Tobal, H. Gonzalez-Ordi, and I. Iruarrizaga-Diez, "Hyperventilation and anxiety experience," Anxiety and stress, vol. 13, no. 2-3, pp. 291-302, 2007.
10. M. J. Zvolensky and G. H. Eifert, "A review of psychological factors/processess affecting anxious responding during voluntary hyperventilation and inhalations of carbon dioxide-enriched," Clinical Psychological Review, vol. 21, pp. 375-400, 2001.
11. R. A. Fisher, "The use of multiple measurements in taxo-nomic problems," Annals Eugen., vol. 7, pp. 179-188, 1936.
12. T. Cover and P. Hart, "Nearest neighbor pattern classification, " Information Theory, IEEE Transactions on, vol. 13, no. 1, pp. 21-27, 1967.
13. R. M. Yerkes and J. D. Dodson, "The relation of strength of stimulus to rapidity of habit-formation," Journal of Comparative Neurology and Psychology, pp. 459-482, 1908.
14. J. Wagner, N. J. Kim, and E. Andre, "From physiological signals to emotions: Implementing and comparing selected methods for feature extraction and classification," IEEE Computer Society, pp. 940-943, 2005.
15. H. Cai and Y. Lin, in An experiment to non-intrusively collect physiological parameters towards driver state detection. Academic Press, 2007.
16. L. Guang-yuan and H. Min, "Emotion recognition of physiological signals based on adaptive hierarchical genetic algorithm," World Congress on Computer Science and Information Engineering, vol. 4, pp. 670-674, 2009.
17. D. Kulic and E. Croft, "Anxiety detection during human-robot interaction," in 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. (IROS 2005)., Aug. 2005, pp. 616-621.
18. M. S. Sharawi, M. Shibli, and M. I. Sharawi, "Design and implementation of a human stress detection system: A biomechanics approach," in 5th International Symposium on Mechatronics and Its Applications, 2008. ISMA 2008., Amman, May 2008, pp. 1-5.
19. N. Sarkar, "A novel interface system for seamlessly integrating human-robot cooperative activities in space," NASA Institute for Advanced Concepts, Tech. Rep., 2002.
20. E. Jovanov, A. O'Donnell Lords, D. Raskovic, P. G. Cox, R. Adhami, and F. Andrasik, "Stress monitoring using a distributed wireless intelligent sensor system," Engineering in Medicine and Biology Magazine, IEEE, vol. 22, no. 3, pp. 49-55, 2003.
21. E. Jovanov, D. Raskovic, A. O. Lords, P. Cox, R. Adhami, and F. Andrasik, "Synchronized physiological monitoring using a distributed wireless intelligent sensor system," in Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE, vol. 2, Sep. 2003, pp. 1368-1371.