Multiscale rescaled range analysis of EEG recordings in sevoflurane anesthesia

Clinical Neurophysiology

Volumn 123, Issue 4, 2012, Pages 681-688

  Liang, Zhenhu ^a   Li, Duan ^a   Ouyang, Gaoxiang ^a   Wang, Yinghua ^a   Voss, Logan J ^b   Sleigh, Jamie W ^b   Li, Xiaoli ^a,c  

^a YANSHAN UNIVERSITY   (China)

^b WAIKATO HOSPITAL   (New Zealand)

^c BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Anesthesia; Electroencephalography; Hurst exponent; Maximal overlap discrete wavelet transform

Indexed keywords

SEVOFLURANE;

ADULT; ANESTHESIA LEVEL; ARTICLE; CLINICAL ARTICLE; DRUG EFFECT; ELECTIVE SURGERY; ELECTROENCEPHALOGRAM; GENERAL ANESTHESIA; GENERAL SURGERY; GYNECOLOGIC SURGERY; HUMAN; HURST EXPONENT; MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM; NONLINEAR SYSTEM; ORTHOPEDIC SURGEON; PRIORITY JOURNAL; WAVELET ANALYSIS;

ADOLESCENT; ADULT; ALGORITHMS; ANESTHESIA, INHALATION; ANESTHETICS, INHALATION; ARTIFACTS; BRAIN; CONSCIOUSNESS; DATA INTERPRETATION, STATISTICAL; DOSE-RESPONSE RELATIONSHIP, DRUG; ELECTROENCEPHALOGRAPHY; ENTROPY; FEMALE; FRACTALS; HALF-LIFE; HUMANS; MALE; METHYL ETHERS; MIDDLE AGED; NONLINEAR DYNAMICS; PREDICTIVE VALUE OF TESTS; WAVELET ANALYSIS; YOUNG ADULT;

EID: 84857782099     PISSN: 13882457     EISSN: 18728952     Source Type: Journal    
DOI: 10.1016/j.clinph.2011.08.027     Document Type: Article

References (45)

1. Acharya U. Non-linear analysis of EEG signals at various sleep stages. Comput Methods Programs Biomed 2005, 80:37-45.
2. Alvarez-Ramirez J., Echeverria J., Rodriguez E. Performance of a high-dimensional R/S method for Hurst exponent estimation. Phys Stat Mech Appl 2008, 387:6452-6462.
3. Balasis G, Daglis I, Papadimitriou C, Kalimeri M, Anastasiadis A, Eftaxias K. Investigating dynamical complexity in the magnetosphere using various entropy measures. J Geophys Res 2009;114.
4. Barunik J, Kristoufek L. On Hurst exponent estimation under heavy-tailed distributions. Phys Stat Mech Appl 2010.
5. Bassingthwaighte J., Raymond G. Evaluating rescaled range analysis for time series. Ann Biomed Eng 1994, 22:432-444.
6. Bruhn J. Depth of anaesthesia monitoring: what's available, what's validated and what's next?. Br J Anaesth 2006, 97:85-94.
7. Bruhn J., Röpcke H., Rehberg B., Bouillon T., Hoeft A. Electroencephalogram approximate entropy correctly classifies the occurrence of burst suppression pattern as increasing anesthetic drug effect. Anesthesiology 2000, 93:981.
8. Cao Y., Tung W., Gao J., Protopopescu V., Hively L. Detecting dynamical changes in time series using the permutation entropy. Phys Rev E 2004, 70:46217.
9. ćulić M., Stojadinović G., Martać L., Soković M. Use of the Hurst exponent for analysis of electrocortical epileptiform activity induced in rats by administration of camphor essential oil or 1,8-cineole. Neurophysiology 2010, 42:57-62.
10. Delorme A., Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 2004, 134:9-21.
11. DePetrillo P., Speers A., Ruttimann U. Determining the Hurst exponent of fractal time series and its application to electrocardiographic analysis. Comput Biol Med 1999, 29:393-406.
12. Jacobs J. Analytical solution to the three-compartment pharmacokinetic model. IEEE Trans Biomed Eng 2002, 35:763-765.
13. Jameson L.C., Sloan T.B. Using EEG to monitor anesthesia drug effects during surgery. J Clin Monit Comput 2006, 20:445-472.
14. Johansen J., Sebel P., Sigl J. Clinical impact of hypnotic-titration guidelines based on EEG Bispectral Index (BIS) monitoring during routine anesthetic care. J Clin Anesth 2000, 12:433-443.
15. Jospin M., Caminal P., Jensen E., Litvan H., Vallverdu M., Struys M., et al. Detrended fluctuation analysis of EEG as a measure of depth of anesthesia. IEEE Trans Biomed Eng 2007, 54:840-846.
16. Kapiris P., Polygiannakis J., Li X., Yao X., Eftaxias K. Similarities in precursory features in seismic shocks and epileptic seizures. Europhys Lett 2005, 69:657.
17. Krishnaveni V., Jayaraman S., Anitha L., Ramadoss K. Removal of ocular artifacts from EEG using adaptive thresholding of wavelet coefficients. J Neural Eng 2006, 3:338.
18. Lalitha V., Eswaran C. Automated detection of anesthetic depth levels using chaotic features with artificial neural networks. J Med Syst 2007, 31:445-452.
19. Li X., Polygiannakis J., Kapiris P., Peratzakis A., Eftaxias K., Yao X. Fractal spectral analysis of pre-epileptic seizures in terms of criticality. J Neural Eng 2005, 2:11.
20. Li X., Cui S., Voss L. Using permutation entropy to measure the electroencephalographic effects of sevoflurane. Anesthesiology 2008, 109:448.
21. Li X., Li D., Liang Z., Voss L., Sleigh J. Analysis of depth of anesthesia with Hilbert-Huang spectral entropy. Clin Nephrol 2008, 119:2465-2475.
22. Li L., Hu J., Chen Y., Zhang Y. PCA based Hurst exponent estimator for fBm signals under disturbances. IEEE Trans Signal Process 2009, 57:2840-2846.
23. Li D., Li X., Liang Z., Voss L., Sleigh J. Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia. J Neural Eng 2010, 7:046010.
24. Lister P., Sanders C. Pharmacodynamics of trovafloxacin, ofloxacin, and ciprofloxacin against Streptococcus pneumoniae in an in vitro pharmacokinetic model. Antimicrob Agents Chemother 1999, 43:11-18.
25. Liu H., Zhang T., Yang F. A multistage, multimethod approach for automatic detection and classification of epileptiform EEG. IEEE Trans Biomed Eng 2002, 49:1557-1566.
26. Maksimow A., Snapir A., Särkelä M., Kentala E., Koskenvuo J., Posti J., et al. Assessing the depth of dexmedetomidine induced sedation with electroencephalogram (EEG)-based spectral entropy. Acta Anaesthesiol Scand 2007, 51:22-30.
27. Mandelbrot B., Wallis J. Some long-run properties of geophysical records. Water Resources Res 1969, 5(2):321-340.
28. Matos J., Gama S., Ruskin H., Sharkasi A., Crane M. Time and scale Hurst exponent analysis for financial markets. Phys Stat Mech Appl 2008, 387:3910-3915.
29. McKay I.D.H., Voss L.J., Sleigh J.W., Barnard J.P., Johannsen E.K. Pharmacokinetic-pharmacodynamic modeling the hypnotic effect of sevoflurane using the spectral entropy of the electroencephalogram. Anesth Analg 2006, 102:91-97.
30. Mitra S., Kuo Y. Digital signal processing: a computer-based approach 1998, McGraw-Hill, New York.
31. Naslund M., Russell A. Extraction of optimally unbiased bits from a biased source. IEEE Trans Inform Theor 2002, 46:1093-1103.
32. Natarajan K., Acharya U., Alias F., Tiboleng T., Puthusserypady S. Nonlinear analysis of EEG signals at different mental states. Biomed Eng Online 2004, 3:7.
33. Nguyen-Ky T., Wen P., Li Y. An improved detrended moving-average method for monitoring the depth of anesthesia. IEEE Trans Biomed Eng 2010, 57:2369-2378.
34. Olofsen E., Sleigh J., Dahan A. Permutation entropy of the electroencephalogram: a measure of anaesthetic drug effect. Br J Anaesth 2008, 101:810.
35. Percival D., Walden A. Wavelet methods for time series analysis 2006, Cambridge Univ Pr, London.
36. Podobnik B., Stanley H. Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series. Phys Rev Lett 2008, 100:84102.
37. Rampil I. A primer for EEG signal processing in anesthesia. Anesthesiology 1998, 89:980.
38. Room Hall D., Area J. Hurst exponent classifies determinism in the EEG and separates consciousness from unconsciousness. Anesthesiology 2007, 107:A805.
39. Smith W., Dutton R., Smith N. Measuring the performance of anesthetic depth indicators. Anesthesiology 1996, 84:38.
40. Vakkuri A. Effects of sevoflurane anesthesia on EEG patterns and hemodynamics: Citeseer; 2000.
41. Vakorin V., Ross B., Krakovska O., Bardouille T., Cheyne D., McIntosh A. Complexity analysis of source activity underlying the neuromagnetic somatosensory steady-state response. NeuroImage 2010, 51:83-90.
42. Viertiö-Oja H., Maja V., Särkelä M., Talja P., Tenkanen N., Tolvanen-Laakso H., et al. Description of the Entropy™ algorithm as applied in the Datex-Ohmeda S/5™ Entropy module. Acta Anaesthesiol Scand 2004, 48:154-161.
43. Watters P., Martin F. A method for estimating long-range power law correlations from the electroencephalogram. Biol Psychol 2004, 66:79-89.
44. Weron R. Estimating long-range dependence: finite sample properties and confidence intervals. Phys Stat Mech Appl 2002, 312:285-299.
45. Zikov T., Bibian S., Dumont G., Huzmezan M., Ries C. Quantifying cortical activity during general anesthesia using wavelet analysis. IEEE Trans Biomed Eng 2006, 53:617-632.