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Quantifying cortical activity during general anesthesia using wavelet analysis.
IEEE Trans Biomed Eng. 2006 Apr; 53(4):617-32.IT

Abstract

This paper reports on a novel method for quantifying the cortical activity of a patient during general anesthesia as a surrogate measure of the patient's level of consciousness. The proposed technique is based on the analysis of a single-channel (frontal) electroencephalogram (EEG) signal using stationary wavelet transform (SWT). The wavelet coefficients calculated from the EEG are pooled into a statistical representation, which is then compared to two well-defined states: the awake state with normal EEG activity, and the isoelectric state with maximal cortical depression. The resulting index, referred to as the wavelet-based anesthetic value for central nervous system monitoring (WAV(CNS)), quantifies the depth of consciousness between these two extremes. To validate the proposed technique, we present a clinical study which explores the advantages of the WAV(CNS) in comparison with the BIS monitor (Aspect Medical Systems, MA), currently a reference in consciousness monitoring. Results show that the WAV(CNS) and BIS are well correlated (r = 0.969) during periods of steady-state despite fundamental algorithmic differences. However, in terms of dynamic behavior, the WAV(CNS) offers faster tracking of transitory changes at induction and emergence, with an average lead of 15-30 s. Furthermore, and conversely to the BIS, the WAV(CNS) regains its preinduction baseline value when patients are responding to verbal command after emergence from anesthesia. We conclude that the proposed analysis technique is an attractive alternative to BIS monitoring. In addition, we show that the WAV(CNS) dynamics can be modeled as a linear time invariant transfer function. This index is, therefore, well suited for use as a feedback sensor in advisory systems, closed-loop control schemes, and for the identification of the pharmacodynamic models of anesthetic drugs.

Authors+Show Affiliations

Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Clinical Trial
Journal Article

Language

eng

PubMed ID

16602568

Citation

Zikov, Tatjana, et al. "Quantifying Cortical Activity During General Anesthesia Using Wavelet Analysis." IEEE Transactions On Bio-medical Engineering, vol. 53, no. 4, 2006, pp. 617-32.
Zikov T, Bibian S, Dumont GA, et al. Quantifying cortical activity during general anesthesia using wavelet analysis. IEEE Trans Biomed Eng. 2006;53(4):617-32.
Zikov, T., Bibian, S., Dumont, G. A., Huzmezan, M., & Ries, C. R. (2006). Quantifying cortical activity during general anesthesia using wavelet analysis. IEEE Transactions On Bio-medical Engineering, 53(4), 617-32.
Zikov T, et al. Quantifying Cortical Activity During General Anesthesia Using Wavelet Analysis. IEEE Trans Biomed Eng. 2006;53(4):617-32. PubMed PMID: 16602568.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Quantifying cortical activity during general anesthesia using wavelet analysis. AU - Zikov,Tatjana, AU - Bibian,Stéphane, AU - Dumont,Guy A, AU - Huzmezan,Mihai, AU - Ries,Craig R, PY - 2006/4/11/pubmed PY - 2006/5/4/medline PY - 2006/4/11/entrez SP - 617 EP - 32 JF - IEEE transactions on bio-medical engineering JO - IEEE Trans Biomed Eng VL - 53 IS - 4 N2 - This paper reports on a novel method for quantifying the cortical activity of a patient during general anesthesia as a surrogate measure of the patient's level of consciousness. The proposed technique is based on the analysis of a single-channel (frontal) electroencephalogram (EEG) signal using stationary wavelet transform (SWT). The wavelet coefficients calculated from the EEG are pooled into a statistical representation, which is then compared to two well-defined states: the awake state with normal EEG activity, and the isoelectric state with maximal cortical depression. The resulting index, referred to as the wavelet-based anesthetic value for central nervous system monitoring (WAV(CNS)), quantifies the depth of consciousness between these two extremes. To validate the proposed technique, we present a clinical study which explores the advantages of the WAV(CNS) in comparison with the BIS monitor (Aspect Medical Systems, MA), currently a reference in consciousness monitoring. Results show that the WAV(CNS) and BIS are well correlated (r = 0.969) during periods of steady-state despite fundamental algorithmic differences. However, in terms of dynamic behavior, the WAV(CNS) offers faster tracking of transitory changes at induction and emergence, with an average lead of 15-30 s. Furthermore, and conversely to the BIS, the WAV(CNS) regains its preinduction baseline value when patients are responding to verbal command after emergence from anesthesia. We conclude that the proposed analysis technique is an attractive alternative to BIS monitoring. In addition, we show that the WAV(CNS) dynamics can be modeled as a linear time invariant transfer function. This index is, therefore, well suited for use as a feedback sensor in advisory systems, closed-loop control schemes, and for the identification of the pharmacodynamic models of anesthetic drugs. SN - 0018-9294 UR - https://www.unboundmedicine.com/medline/citation/16602568/Quantifying_cortical_activity_during_general_anesthesia_using_wavelet_analysis_ L2 - https://doi.org/10.1109/TBME.2006.870255 DB - PRIME DP - Unbound Medicine ER -