Depression and Fatigue Analysis Using a Mental-Physical Model

  • Conference paper
  • First Online:
IT Convergence and Security 2012

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 215))

  • 730 Accesses

Abstract

Recent research has indicated a significant association between depression and fatigue. To analyze depression and fatigue, an experiment was conducted that provided the subjects with affective content to induce a variety of emotions and heart rate variability (HRV). This paper presents a mental–physical model that describes the relationship between depression and fatigue by using a neuro-fuzzy network with a weighted fuzzy membership function using two time-domain and four frequency-domain features of HRV. HRV data were collected from 24 patients. At the end of the experiment, we determined the relationship between depression and fatigue with the mental–physical model, and our analysis results had an accuracy of 95.8 %.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 117.69
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 160.49
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
EUR 160.49
Price includes VAT (Germany)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhang ZX, Tian XW, Lim JS (2012) Neuro-fuzzy network-based depression diagnosis algorithm using optimal features of HRV. J Korea Contents Acad 12(2):1–9

    Article  Google Scholar 

  2. Edgerton JE, Campbell RE (1994) American psychiatric glossary, 7th edn. American Psychiatric Press, Washington DC

    Google Scholar 

  3. American Psychiatric Association (2000) Diagnostic and statistical manual of mental disorders, 4th edn. Text Revision: DSM-IV-TR, American Psychiatric Publishing, Washington

    Google Scholar 

  4. Uetake A, Murata A (2000) Assessment of mental fatigue during VDT task using event related potential (P300). In: Proceedings of the 2000 IEEE international workshop on robot and human interactive communication, pp 235–240

    Google Scholar 

  5. Atsuo M, Atsushi U, Yosuke T (2005) Evaluation of mental fatigue using feature parameter extracted from event related potential. Int J Ind Ergon 35:761–770

    Article  Google Scholar 

  6. Zung WW (1965) A self-rating depression scale. Arch Gen Psychiatry 12:63–70

    Article  Google Scholar 

  7. Lim JS (2009) Finding features for real-time premature ventricular contraction detection using a fuzzy neural network system. IEEE Trans Neural Netw 20(3):522–527

    Article  Google Scholar 

Download references

Acknowledgments

This research was supported by the MKE (The Ministry of Knowledge Economy), Korea, under the Convergence-ITRC (Convergence Information Technology Research Center) support program (NIPA-2012-H0401-12-1001) supervised by the NIPA (National IT Industry Promotion Agency).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joon S. Lim .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Tian, XW., Zhang, ZX., Lee, SH., Yoon, HJ., Lim, J.S. (2013). Depression and Fatigue Analysis Using a Mental-Physical Model. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_97

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-5860-5_97

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-5859-9

  • Online ISBN: 978-94-007-5860-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Navigation