Enhancements for a Robust Fuzzy Detection of Stress

  • Asier Salazar-RamirezEmail author
  • Eloy Irigoyen
  • Raquel Martinez
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 299)


Improving psychologically disabled people’s life quality and integration in society is strongly linked with providing them higher levels of autonomy. Occasionally, these people suffer from emotional blockages produced by situations that can be overwhelming for them. Thus, detecting whether the person is entering a mental blockage produced by stress can facilitate to mitigate the symptoms of that blockage. This work presents different enhancements and variations for an existing fuzzy logic stress detection system based on monitoring different physiological signals (heart rate and galvanic skin response). It proposes a method based on wavelet processing to improve the detection of R peaks of electrocardiograms. It also proposes to decompose the galvanic response signal into two components: the average value and the variations.


fuzzy logic physiological signal processing wavelets 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bradley, M., et al.: Measuring emotion: The self-assessment manikin and the semantic differential. J. Behavioral Therapy & Experimental Psychiatry 25, 49–59 (1994)CrossRefGoogle Scholar
  2. 2.
    Parkka, J., Ermes, M., Van Gils, M.: Automatic feature selection and classification of physical and mental load using data from wearable sensors. In: 10th IEEE Int. Conf. on Information Technology and Applications in Biomedicine (ITAB), pp. 1–5 (2010)Google Scholar
  3. 3.
    Sharma, N., Gedeon, T.: Artificial Neural Network Classification Models for Stress in Reading. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part IV. LNCS, vol. 7666, pp. 388–395. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  4. 4.
    Gonzalez, J.: Providing telecommunications access to people with special needs. IEEE J. on Selected Areas in Communication 9(4), 601–604 (1991)CrossRefGoogle Scholar
  5. 5.
    de Santos Sierra, A., et al.: A Stress-Detection System Based on Physiological Signals and Fuzzy Logic. IEEE Trans. on Ind. Electronics 58(10), 4857–4865 (2011)CrossRefGoogle Scholar
  6. 6.
    Sato, W., et al.: Emotion Elicitation Effect of Films in a Japanese Sample. Social Behavior and Personality 35(7), 863–874 (2007)CrossRefGoogle Scholar
  7. 7.
    Bloch, S., et al.: Specific respiratory patterns distinguish among human basic emotions. International Journal of Psychophysiology 11, 141–154 (1991)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Ekman, P., et al.: Autonomic nervous system activity distinguishes among emotions. Science 221, 1208–1210 (1983)CrossRefGoogle Scholar
  9. 9.
    Coan, J., Allen, J.: Frontal EEG asymmetry as a moderator and mediator of emotion. Biological Psychology 67, 7–50 (2004)CrossRefGoogle Scholar
  10. 10.
    Martínez, R., et al.: First results in modelling stress situations by analysing physiological human signals. In: Proc. of IADIS Int. Conf. on e-Health, pp. 171–175 (2012)Google Scholar
  11. 11.
    Sakr, G.E., et al.: Subject independent agitation detection. In: IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics (AIM 2008), pp. 200–204 (2008)Google Scholar
  12. 12.
    Lee, C.K., et al.: Using Neural Network to Recognize Human Emotions from Heart Rate Variability and Skin Resistance. In: IEEE 27th Annual Int. Conf. of the Engineering in Medicine and Biology Society, pp. 5523–5525 (2006)Google Scholar
  13. 13.
    Woźniak, M., Graña, M.: Emilio Corchado A survey of multiple classifier systems as hybrid systems. Information Fusion 16, 3–17 (2014)CrossRefGoogle Scholar
  14. 14.
    Luís Calvo-Rolle, J., Corchado, E.: A Bio-inspired knowledge system for improving combined cycle plant control tuning. Neurocomputing 126, 95–105 (2014)CrossRefGoogle Scholar
  15. 15.
    Mokhayeri, F., Akbarzadeh-T, M.-R.: Mental Stress Detection Based on Soft Computing Techniques. In: IEEE Int. Conf. on Bioinformatics and Biomedicine, pp. 430–433 (2011)Google Scholar
  16. 16.
    Sakr, G.E., et al.: Support Vector Machines to Define and Detect Agitation Transition. IEEE Trans. on Affective Computing 1(2), 98–108 (2010)CrossRefGoogle Scholar
  17. 17.
    Nelson, R.J.: An Introduction to Behavioral Endocrinology. Massachussets. Sinauer Associates 11, 557–591 (2000)Google Scholar
  18. 18.
    Sasikala, P., Wahidabanu, R.S.D.: Robust R Peak and QRS detection in Electrocardiogram using Wavelet Transform. In: Int. J. of Advanced C. Science and Applications, vol. 1 (2010)Google Scholar
  19. 19.
    Hong-tu, Z., Jing, Y.: The Wavelet Decomposition and Reconstruction Based on The Matlab. In: Proc. of the Third Int. Symposium on Electronic Commerce and Security Workshops (ISECS 2010), China (2010)Google Scholar
  20. 20.
    Talbi, et al.: New Method of R-Wave Detection by Continuous Wavelet Transform. Signal Processing: An International Journal (SPIJ) 5, 165–173 (2011)Google Scholar
  21. 21.
    de Lannoy, G., et al.: A Supervised Wavelet Transform Algorithm for R Spike Detection in Noisy ECGs. In: Fred, A., Filipe, J., Gamboa, H. (eds.) BIOSTEC 2008. CCIS, vol. 25, pp. 256–264. Springer, Heidelberg (2008)Google Scholar
  22. 22.
    Martis, R.J., Chakraborty, C., Ray, A.K.: Wavelet Based Machine Learning Techniques for ECG Analysis. In: Machine Learning in Healthcare Informatics, pp. 25–45 (2014)Google Scholar
  23. 23.
    Gross, J.J., Levenson, R.W.: Emotion Elicitation Using Films. Cognition and Emotion 9, 87–108 (1995)CrossRefGoogle Scholar
  24. 24.
    CSEA-NIMH: The international affective picture system: Digitalized photographs. The Center of Research in Psychophysiology, Florida (1999)Google Scholar
  25. 25.
    Lang, P.J.: Behavioral treatment and bio-behavioral assessment: Computer applications. In: Technology in Mental Health and Delivery Systems, pp. 119–137 (1980)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Asier Salazar-Ramirez
    • 1
    Email author
  • Eloy Irigoyen
    • 1
  • Raquel Martinez
    • 1
  1. 1.University of the Basque Country (UPV/EHU)BilbaoSpain

Personalised recommendations