Literature DB >> 19101669

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

T Nguyen-Ky1, Peng Wen, Yan Li.   

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.

Mesh:

Year:  2008        PMID: 19101669     DOI: 10.1016/j.compbiomed.2008.10.007

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  3 in total

1.  A novel empirical wavelet SODP and spectral entropy based index for assessing the depth of anaesthesia.

Authors:  Thomas Schmierer; Tianning Li; Yan Li
Journal:  Health Inf Sci Syst       Date:  2022-06-06

2.  A novel spectral entropy-based index for assessing the depth of anaesthesia.

Authors:  Jee Sook Ra; Tianning Li; Yan Li
Journal:  Brain Inform       Date:  2021-05-12

Review 3.  Evolution of electroencephalogram signal analysis techniques during anesthesia.

Authors:  Mahmoud I Al-Kadi; Mamun Bin Ibne Reaz; Mohd Alauddin Mohd Ali
Journal:  Sensors (Basel)       Date:  2013-05-17       Impact factor: 3.576

  3 in total

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