Skip to main content
SpringerLink
Log in

Investigation of Chronic Stress Differences between Groups Exposed to Three Stressors and Normal Controls by Analyzing EEG Recordings

  • Conference paper
Neural Information Processing (ICONIP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8227))

Included in the following conference series:

Abstract

Despite clear evidence of connections between chronic stress, brain patterns, age and gender, few studies have explored stressor differences in stress detection. This paper presents a stressor-specific evaluation model conducted between stress levels and electroencephalogram(EEG) features. The overall complexity, chaos of EEG signals, and spectrum power of certain EEG bands from pre-frontal lobe(Fp1, Fp2 and Fpz) was analyzed. The results showed that different stressors can lead to varying degree of changes of frontal EEG complexity. Future study will build the stressor-specific evaluation model under considering the effects of gender and age.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hoffmann, E.: Brain Training Against Stress: Theory, Methods and Results from an Outcome Study. Stress Report 4, 1–24 (2005)

    Google Scholar 

  2. Chen, F., et al.: A New Measurement of Complexity for Studying EEG Mutual Information. Shengwu Wuli Xuebao 14(3), 508–512 (1998)

    Google Scholar 

  3. Mnnroe, S.M., Slavich, G.M., Georgiades, K.: The Social Environment and Life Stress in Depression. In: Handbook of Depression, pp. 340–360 (2009)

    Google Scholar 

  4. Thakor, N.V., Tong, S.: Advances in Quantitative Electroencephalogram Analysis Methods. Annual Review of Biomedical Engineering 6(1), 453–495 (2004)

    Article  Google Scholar 

  5. Davidson, R.J., et al.: Depression: Perspectives from Affective Neuroscience. Annual Review of Psychology 53(1), 545–574 (2002)

    Article  Google Scholar 

  6. Thibodeau, R., Jorgensen, R.S., Kim, S.: Depression, Anxiety, and Resting Frontal EEG Asymmetry: A Meta-analytic Review (0021-843X (Print))

    Google Scholar 

  7. Allen, J.J.B., et al.: The Stability of Resting Frontal Electroencephalographic Asymmetry in Depression. Psychophysiology 41(2), 269–280 (2004)

    Article  Google Scholar 

  8. Nandrino, J.-L., et al.: Decrease of Complexity in EEG as a Symptom of Depression. NeuroReport 5(4), 528–530 (1994)

    Article  Google Scholar 

  9. Peng, H., et al.: A Method of Identifying Chronic Stress by EEG. Personal and Ubiquitous Computing, 1–7 (2012)

    Google Scholar 

  10. Zhang, X., Hu, B., Moore, P., Chen, J., Zhou, L.: Emotiono: An Ontology with Rule-Based Reasoning for Emotion Recognition. In: Lu, B.-L., Zhang, L., Kwok, J. (eds.) ICONIP 2011, Part II. LNCS, vol. 7063, pp. 89–98. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  11. Carvalho, A., Moraes, H., et al.: EEG Frontal Asymmetry in the Depressed and Remitted Elderly: Is It Related to the Trait or to the State of Depression? (1573-2517 (Electronic))

    Google Scholar 

  12. Bin, H., et al.: EEG-Based Cognitive Interfaces for Ubiquitous Applications: Developments and Challenges. IEEE Intelligent Systems 26(5), 46–53 (2011)

    Article  Google Scholar 

  13. Schaffer, C.E., Davidson, R.J., Saron, C.: Frontal and Parietal Electroencephalogram Asymmetry in Depressed and Nondepressed Subjects. Biological Psychiatry 18, 753–762 (1983)

    Google Scholar 

  14. Smit, D.J.A., et al.: The Relation between Frontal EEG Asymmetry and the Risk for Anxiety and Depression. Biological Psychology 74(1), 26–33 (2007)

    Article  MathSciNet  Google Scholar 

  15. Lempel, A., Ziv, J.: On the Complexity of Finite Sequences. IEEE Transactions on Information Theory 22(1), 75–81 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  16. Grassberger, P., Procaccia, I.: Measuring the Strangeness of Strange Attractors. Physica D: Nonlinear Phenomena 9(1-2), 189–208 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  17. Stam, C.J., van Woerkom, T.C.A.M., Pritchard, W.S.: Use of Non-linear EEG Measures to Characterize EEG Changes during Mental Activity. Electroencephalography and Clinical Neurophysiology 99(3), 214–224 (1996)

    Article  Google Scholar 

  18. Rosenstein, M.T., Collins, J.J., De Luca, C.J.: A Practical Method for Calculating Largest Lyapunov Exponents from Small Data Sets. Physica D: Nonlinear Phenomena 65(1-2), 117–134 (1993)

    Article  MathSciNet  MATH  Google Scholar 

  19. Kulish, V., Sourin, A., Sourina, O.: Human Electroencephalograms Seen As Fractal Time Series: Mathematical Analysis and Visualization. Computers in Biology and Medicine 36(3), 291–302 (2006)

    Article  Google Scholar 

  20. Tang, Y., et al.: Entropy Analysis of the EEG Alpha Activity in Depression Patients. Journal of Biomedical Engineering 26(4), 739–742 (2009)

    Google Scholar 

  21. Hugdahl, K.R., Rishovd, B., Lund, A., Asbjørnsen, A., Egeland, J., Ersland, L., Landrø, N.I., Roness, A., Stordal, K.I., Sundet, K., Thomsen, T.: Brain Activation Measured With fMRI During a Mental Arithmetic Task in Schizophrenia and Major Depression. The American Journal of Psychiatry 161(2), 286–293 (2004)

    Article  Google Scholar 

  22. Field, T., Pickens, J., et al.: Targeting Adolescent Mothers with Depressive Symptoms for Early Intervention (0001-8449 (Print))

    Google Scholar 

  23. Debener, S., et al.: Is Resting Anterior EEG Alpha Asymmetry a Trait Marker for Depression? Findings for Healthy Adults and Clinically Depressed Patients. Neuropsychobiology 41(1), 31–37 (2000)

    Article  Google Scholar 

  24. Bruder, G.E., et al.: Electroencephalographic and Perceptual Asymmetry Differences between Responders and Nonresponders to an SSRI Antidepressant. Biological Psychiatry 49(5), 416–425 (2001)

    Article  Google Scholar 

  25. Hinrikus, H., Suhhova, A., et al.: Spectral Features of EEG in Depression (1862-278X (Electronic))

    Google Scholar 

  26. Tomarken, A.J., et al.: Resting Frontal Brain Activity: Linkages to Maternal Depression and Socio-economic Status among Adolescents. Biological Psychology 67(1-2), 77–102 (2004)

    Article  Google Scholar 

  27. Coan, J.A., et al.: The Heritability of Trait Frontal EEG Asymmetry and Negative Emotionality: Sex Differences and Genetic Nonadditivity. The University of Arizona (2003)

    Google Scholar 

  28. Minati, L., Grisoli, M., Bruzzone, M.G.: MR Spectroscopy, Functional MRI, and Diffusion-tensor Imaging in the Aging Brain: A Conceptual Review. Journal of Geriatric Psychiatry and Neurology 20(1), 3–21 (2007)

    Article  Google Scholar 

  29. Bruder, G.E., et al.: Regional Brain Asymmetries in Major Depression with or without an Anxiety Disorder: A Quantitative Electroencephalographic Study. Biological Psychiatry 41(9), 939–948 (1997)

    Article  Google Scholar 

  30. Reid, S.A., Duke, L.M., Allen, J.J.B.: Resting Frontal Electroencephalographic Asymmetry in Depression: Inconsistencies Suggest the Need to Identify Mediating Factors. Psychophysiology 35(4), 389–404 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. The School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000, China

    Na Li, Bin Hu, Jing Chen, Hong Peng, Qinglin Zhao & Mingqi Zhao

  2. The School of Computing, Telecommunications and Networks, Birmingham City University, Birmingham, B42 2SU, UK

    Bin Hu

Authors
  1. Na Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bin Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jing Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hong Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qinglin Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mingqi Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  2. The University of Tokyo, 7-3-1 Hongo, 113-8656, Bunkyo-ku, Tokyo, Japan

    Akira Hirose

  3. Institute of Automation, Key Laboratory of Complex Systems and Intelligence Science, Chinese Academy of Sciences, 100190, Beijing, China

    Zeng-Guang Hou

  4. Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, 440-746, Suwon, Korea

    Rhee Man Kil

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, N., Hu, B., Chen, J., Peng, H., Zhao, Q., Zhao, M. (2013). Investigation of Chronic Stress Differences between Groups Exposed to Three Stressors and Normal Controls by Analyzing EEG Recordings. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42042-9_64

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-42042-9_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-42041-2

  • Online ISBN: 978-3-642-42042-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation