A method of identifying chronic stress by EEG

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• 作者：Hong Peng ; Bin Hu ; Fang Zheng ; Dangping Fan ; Wen Zhao…
• 关键词：Chronic stress ; Electroencephalogram (EEG) ; Complexity ; Alpha asymmetry
• 刊名：Personal and Ubiquitous Computing
• 出版年：2013
• 出版时间：October 2013
• 年：2013
• 卷：17
• 期：7
• 页码：1341-1347
• 全文大小：346KB
• 参考文献：1. Heim C, Nemeroff CB (2002) Neurobiology of early life stress: clinical studies. Semin Clin Neuropsychiatry 7(2):147-59 CrossRef
  2. Schneiderman N, Gail Ironson G, Siegel SD (2005) Stress and health: psychological, behavioral and biological determinant. Annu Rev Clin Psychol 1:607-28 CrossRef
  3. van Praag HM (2004) Can stress cause depression? Prog Neuropsychopharmacol Biol Psychiatry 28(5):891-07 CrossRef
  4. Cate Miller A, Gordon RM, Daniele RJ, Diller L (1992) Stress, appraisal, and coping in mothers of disabled and nondisabled children. J Pediatr Psychol 17(5):587-05 CrossRef
  5. Nunez PL (2006) Electric fields of the brain, 2nd edn. Oxford University Press, USA CrossRef
  6. Thakor NV, Tong S (2004) Advances in quantitative electroencephalogram analysis methods. Annu Rev Biomed Eng 6:453-95 CrossRef
  7. Stam CJ (2005) Nonliear dynamical analysis of EEG and EMG: review of an emerging field. Clin Neurophysiol 116(10):2266-301 CrossRef
  8. Hammen C (2005) Stress and depression. Ann Rev Clin Psychol 1:293-19 CrossRef
  9. McGonagle KA, Kessler RC (1990) Chronic stress, acute stress, and depressive symptoms. Am J Commun Psychol 18(5):681-06 CrossRef
  10. Blackhart GC, Minnix JA, Kline JP (2006) Can EEG asymmetry patterns predict future development of anxiety and depression? A preliminary study. Biol Psychol 72(1):46-0 CrossRef
  11. Kemp AH, Griffiths K, Felmingham KL, Shankman SA, Drinkenburg W, Arns M, Clark CR, Bryant RA (2010) Disorder specificity despite comorbidity: resting EEG alpha asymmetry in major depressive disorder and post-traumatic stress disorder. Biol Psychol 85(2):350-54 CrossRef
  12. Li Y, Tong S, Liu D, Gai Y, Wang X, Wang J, Qiu Y, Zhu Y (2008) Abnormal EEG complexity in patients with schizophrenia and depression. Clin Neurophysiol 119(6):1232-241 CrossRef
  13. Davidson RJ (1995) Cerebral asymmetry, emotion, and affective style. In: Davidson RJ, Hugdahl K (eds) Brain asymmetry. MIT Press, Cambridge, pp 361-87
  14. Chen F, Gu F, Xu J, Liu Z, Liu R (1998) A new measurement of complexity for studying EEG mutual information. Biophys Sinica 14(3):435-37
  15. Cai Z, Sun H (2008) Improved C0-complexity and its applications. J Fudan Univ 47(6):133-40
  16. Lempel A, Ziv J (1976) On the complexity of finite sequences. Inf Theory 22(1):75-1 CrossRef
  17. Nagarajan R, Szczepanski J, Wajnryb E (2008) Interpreting non-random signatures in biomedical signals with Lempel–Ziv complexity. Phys D Nonlinear Phenom 237(3):359-64 CrossRef
  18. Stam CJ, van Woerkom TCAM, Pritchard WS (1996) Use of non-linear EEG measures to characterize EEG changes during mental activity. Electroencephalogr Clin Neurophysiol 99(3):214-24 CrossRef
  19. Lee Y-J, Zhu Y-S, Xu Y-H, Shen M-F, Zhang H-X, Thakor NV (2001) Detection of non-linearity in the EEG of schizophrenic patients. Clin Neurophysiol 112(7):1288-294 CrossRef
  20. Kulish V, Sourin A, Sourina O (2006) Human electroencephalograms seen as fractal time series: mathematical analysis and visualization. Comput Biol Med 36(3):291-02 CrossRef
  21. Rosenstein MT, Collins JJ, De Luca CJ (1993) A practical method for calculating Largest Lyapunov exponents from small data sets. Phys D Nonlinear Phenom 65(1-):117-34 CrossRef
  22. Tang Y, Li Y, Tong S, Li Y, Zhu Y (2009) Entroy analysis of the EEG alpha activity in depression patients. J Biomed Eng 26(4):739-42
  
• 作者单位：Hong Peng (1)
  Bin Hu (1) (2)
  Fang Zheng (1)
  Dangping Fan (1)
  Wen Zhao (1)
  Xuebin Chen (3)
  Yongxia Yang (4)
  Qingcui Cai (4)
  
  1. The School of Information Science and Engineering, Lanzhou University, Lanzhou, China
  2. School of CTN, TEE, Birmingham City University, Birmingham, UK
  3. Department of Mental Health, The First Affiliated Hospital of Lanzhou University, Lanzhou, China
  4. The Special Education School, Lanzhou, China
  
• ISSN：1617-4917

文摘

There are a lot of studies on chronic stress assessment applying psychology instruments or hormones analysis. However, there are only few studies using electroencephalogram (EEG), which is a non-invasive method providing objective inspection on brain functioning. In this paper, we analyzed overall complexity and spectrum power of certain EEG bands (theta, alpha and beta) collected from two groups of human subjects—high stress versus moderate stress at prefrontal sites (Fp1, Fp2 and Fpz). The results showed that the differences of nonlinear features (C0, LZC, D2, L1 and RE) and linear features (power and alpha asymmetry score) between two groups are significant. C0, LZC and D2 significantly increased in stress group at Fp1 and Fp2, while L1 and RE significantly decreased. And those with chronic stress have higher left prefrontal power. Finally, we suggest that it may be effective to discriminate the high-stress people from moderate-stress people by EEG.