EEG parameters and their combination as indicators of depth of anaesthesia

Biomedizinische Technik

Volumn 51, Issue 2, 2006, Pages 89-94

  Jordan, Denis ^a   Schneider, Gerhard ^a   Hock, Andreas ^a   Hensel, Thomas ^b   Stockmanns, Gudrun ^b   Kochs, Eberhard F ^a  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITY OF DUISBURG ESSEN   (Germany)

Author keywords

Anaesthesia; Approximate entropy; EEG; Fuzzy logic; Lempel Ziv complexity; qWSMF; WSMF

Indexed keywords

BIOMEDICAL ENGINEERING; FUZZY SETS; PARAMETER ESTIMATION; SIGNAL PROCESSING;

ANAESTHESIA; APPROXIMATE ENTROPY; LEMPEL-ZIV COMPLEXITY; QWSMF; WSMF;

ELECTROENCEPHALOGRAPHY;

ADULT; ANESTHESIA INDUCTION; ANESTHESIA LEVEL; ARTICLE; CONTROLLED STUDY; ELECTROENCEPHALOGRAM; ENTROPY; HUMAN; HUMAN EXPERIMENT; SIGNAL PROCESSING; STATISTICAL ANALYSIS; UNCONSCIOUSNESS; WAKEFULNESS;

ALGORITHMS; ANESTHESIA; ANESTHETICS; ARTIFICIAL INTELLIGENCE; AWARENESS; BRAIN; DIAGNOSIS, COMPUTER-ASSISTED; DRUG THERAPY, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; FUZZY LOGIC; HUMANS; PATTERN RECOGNITION, AUTOMATED; WAKEFULNESS;

EID: 33747248151     PISSN: 00135585     EISSN: None     Source Type: Journal    
DOI: 10.1515/BMT.2006.016     Document Type: Article

References (16)

1. Bruhn J. Vergleich verschiedener EEG-Parameter: spektrale Eckfrequenz 95, approximate Entropie und Bispektral-Indikator. Forum Moderner Inhalationsanästhesie (FMI) 2003; 44: 17-21.
2. Bruhn J, Röpcke H, Hoeft A. Approximate entropy as an electroencephalographic measure of anesthetic drug effect during desflurane anesthesia. Anesthesiology 2000; 92: 715-726.
3. 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: 981-985.
4. Fell J, Röschke J, Mann K, Schaffner C. Discrimination of sleep stages: a comparison between spectral and nonlinear EEG measures. Electroencephalogr Clin Neurophysiol 1996; 98: 401-410.
5. Gurman GM. Assessment of depth of general anesthesia. Observations on processed EEG and spectral edge frequency. Int J Clin Monit Comput 1994; 11: 185-189.
6. Hsieh F, Turnbull BW. Nonparametric and semi-parametric estimation of the receiver operating characteristic curve. Ann Stats 1996; 24: 25-40.
7. Kaspar F, Shuster HG. Easily calculable measure for the complexity of spatiotemporal patterns. Phys Rev A 1987; 36: 842-848.
8. Kaufmann A, Gupta MM. Introduction to fuzzy arithmetic: theory and applications. New York: Van Nostrand Reinhold 1985.
9. Lempel A, Ziv J. On the complexity of finite sequences. IEEE Trans Inf Theory 1976; 22: 75-81.
10. Metz CE. Basic principles of ROC analysis. Semin Nucl Med 1978; 8: 283-298.
11. Niedermayer E, da Silva FL. Electroencephalography, basic principles, clinical applications, and related fields. 3rd ed. London: Williams & Wilkins 1993: 829-836.
12. Pincus S, Singer HB. Randomness and degree of irregularity. Proc Natl Acad Sci USA 1996; 93: 2083-2088.
13. Rampil IJ. A Primer for EEG signal processing in anesthesia. Anesthesiology 1998; 89: 980-1002.
14. Schneider G, Hollweck R, Ningler M, Stockmanns G, Kochs E. Detection of consciousness by electroencephalogram and auditory evoked potentials. Anesthesiology 2005; 103: 934-943.
15. Thakor NV, Tong S. Advances in quantitative electroencephalogram analysis methods. Annu Rev Biomed Eng 2004; 6: 453-495.
16. Zhang XS, Roy RJ, Weber JE. EEG complexity as a measure of depth of anesthesia for patients. IEEE Trans Biomed Eng 2001; 48: 1424-1433.