Advertisement

A Real Time Human Emotion Recognition System Using Respiration Inhale-Exhale Temperature Patterns and ECG

  • C. M. Naveen KumarEmail author
  • G. ShivakumarEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 26)

Abstract

A major requirement for human health monitoring in real time is the capability to evaluate their perceptual state. This paper presents a real time monitoring system for human emotions recognition using respiration inhale and exhale temperature patterns and ECG data, which is obtained by the sensors in real time interfaced with arduino. Our system is capable of evaluating three basic emotions (Happy, Sad, Fear) for adults and aged, using low cost and non-invasive physiological sensors. The sensors data is used by Neural Networks for training and classification of human emotions. To achieve automatic evaluation of the affective states of the human and to detect emotions; a novel system which integrates state of art hardware and software system is developed. The anatomical variables considered here actually have a very strong association with the changes in state of emotions with the subjects in our experiments as indicated by results. The experimental results shows the accuracy achieved approximately 75%, 71.87 and 70% for emotions happy, sad and fear in adults and 62.5%, 70% and 75% in aged people.

Keywords

Real time Emotions Respiration inhale exhale temperature patterns ECG Neural networks Arduino 

References

  1. 1.
    Picard, R.W.: Affective computing: challenges. Int. J. Hum Comput Stud. 59(1), 55–64 (2003)MathSciNetCrossRefGoogle Scholar
  2. 2.
    James, W.: What is an emotion? Mind 9(34), 188–205 (1884)CrossRefGoogle Scholar
  3. 3.
    Cannon, W.B.: The James-Lange Theory of Emotion: a critical examination and an alternative theory. Am. J. Psychol. 39, 106–124 (1927)CrossRefGoogle Scholar
  4. 4.
    Schechter, S., Singer, J.E.: Cognitive, social, and physiological determinants of emotional state. Psychol. Rev. 69(5), 379–399 (1962)CrossRefGoogle Scholar
  5. 5.
    Madre, S.S.: Understanding Human Anatomy & Physiology, 4th edn. McGraw-Hill, Boston (2000)Google Scholar
  6. 6.
    Goldman, M.J.: Principles of Clinical Electrocardiography, 12th edn. Lange Medical Publications, New York (1989)Google Scholar
  7. 7.
    Li, L., Chen, J.: Emotion recognition using physiological signals. In: ICAT, Hangzhou, China (2006)Google Scholar
  8. 8.
    Picard, R.W., et al.: Toward machine emotional intelligence: analysis of affective physiological state. IEEE Trans. Pattern Anal. Mach. Intell. 23, 1175–1191 (2001)CrossRefGoogle Scholar
  9. 9.
    Kim, K.H., et al.: Emotion recognition system using short-term monitoring of physiological signals. Med. Biol. Eng. Comput. 42, 419–427 (2004)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Drummond, P.D., Quah, S.H.: The effect of expressing anger on cardiovascular reactivity and facial blood flow in Chinese and Caucasians. Psychophysiology 38, 1906 (2001)CrossRefGoogle Scholar
  11. 11.
    Andreassi, J.L.: Psychophysiology: Human Behavior and Physiological Response. Lawrence Erlbaum Associates, New Jersey (2000)Google Scholar
  12. 12.
    Boucsein, W.: Electrodermal Activity. Plenum Press, New York (1992)CrossRefGoogle Scholar
  13. 13.
    Kreibig, S.D.: Autonomic nervous system activity in emotion: a review. Biol. Psychol. 84, 394–421 (2010)CrossRefGoogle Scholar
  14. 14.
    Mohammad, M., et al.: Artificial neuro fuzzy logic system for detecting human emotions. HCIS, 1–13 (2013). Springer Open JournalGoogle Scholar
  15. 15.
    Wu, N., et al.: Emotion recognition based on physiological signals. In: BICS, LNAI 7366, pp. 311–320. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  16. 16.
    Shivakumar, G., Vijaya, P.A.: Analysis of human emotions using galvanic skin response and finger tip temperature. Int. J. Synth. Emot. 2(1), 15–25 (2011)CrossRefGoogle Scholar
  17. 17.
    Jerritta, S., et al.: Physiological signals based human emotion recognition: a review. In: 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications (2011)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of E&I EngineeringMalnad College of EngineeringHassanIndia

Personalised recommendations