Measure of the electroencephalographic effects of sevoflurane using recurrence dynamics.
This paper proposes a novel method to interpret the effect of anesthetic agents (sevoflurane) on the neural activity, by using recurrence quantification analysis of EEG data. First, we reduce the artefacts in the scalp EEG using a novel filter that combines wavelet transforms and empirical mode decomposition. Then, the determinism in the recurrence plot is calculated. It is found that the determinism increases gradually with increasing the concentration of sevoflurane. Finally, a pharmacokinetic and pharmacodynamic (PKPD) model is built to describe the relationship between the concentration of sevoflurane and the processed EEG measure ('determinism' of the recurrence plot). A test sample of nine patients shows the recurrence in EEG data may track the effect of the sevoflurane on the brain.
Li
Xiaoli
X
Cercia, School of Computer Science, The University of Birmingham, Birmingham B15 2TT, UK. xiaoli.avh@gmail.com
Sleigh
Jamie W
JW
Voss
Logan J
LJ
Ouyang
Gaoxiang
G
D018685:Anesthetics, Inhalation / Q000493:pharmacokinetics*; D016477:Artifacts; D001921:Brain / Q000187:drug effects* / Q000502:physiology; D004305:Dose-Response Relationship, Drug; D004569:Electroencephalography / Q000187:drug effects* / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008738:Methyl Ethers / Q000493:pharmacokinetics*; D008959:Models, Neurological; D017711:Nonlinear Dynamics; D000077149:Sevoflurane
D018685:Anesthetics, Inhalation; D008738:Methyl Ethers; D000077149:Sevoflurane