Theoretical basis for identification of different anesthetic states based on routinely recorded EEG during operation

Nguyen-Ky, T. and Wen, Peng and Li, Yan (2009) Theoretical basis for identification of different anesthetic states based on routinely recorded EEG during operation. Computers in Biology and Medicine, 39 (1). pp. 40-45. ISSN 0010-4825

Abstract

In this paper, we present a new method to identify anesthetic states based on routinely recorded electroencephalogram (EEG). The identification of anesthesia stages are conducted using fast Fourier transform (FFT) and modified detrended fluctuation analysis (DFA) method. Simulation results demonstrate that this new method can clearly discriminate all five anesthesia states: very deep anesthesia, deep anesthesia, moderate anesthesia, light anesthesia and awake.


Statistics for USQ ePrint 4878
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2008 Elsevier Ltd. Permanent restricted access to published version due to publisher copyright policy.
Depositing User: Dr Tai Nguyen-Ky
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 28 Jan 2009 01:43
Last Modified: 12 Feb 2015 04:15
Uncontrolled Keywords: depth of anesthesia; EEG; detrended fluctuation analysis; FFT
Fields of Research (FOR2008): 01 Mathematical Sciences > 0101 Pure Mathematics > 010106 Lie Groups, Harmonic and Fourier Analysis
09 Engineering > 0903 Biomedical Engineering > 090303 Biomedical Instrumentation
11 Medical and Health Sciences > 1103 Clinical Sciences > 110301 Anaesthesiology
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970111 Expanding Knowledge in the Medical and Health Sciences
Identification Number or DOI: 10.1016/j.compbiomed.2008.10.007
URI: http://eprints.usq.edu.au/id/eprint/4878

Actions (login required)

View Item Archive Repository Staff Only