Non-linear analysis of EEG signals at various sleep stages

ACHARYA, Rajendra, FAUST, Oliver, KANNATHAL, N, CHUA, TjiLeng and LAXMINARAYAN, Swamy (2005). Non-linear analysis of EEG signals at various sleep stages. Computer methods and programs in biomedicine, 80 (1), 37-45.

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Official URL: http://www.sciencedirect.com/science/article/pii/S...
Link to published version:: https://doi.org/10.1016/j.cmpb.2005.06.011
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    Abstract

    Application of non-linear dynamics methods to the physiological sciences demonstrated that non-linear models are useful for understanding complex physiological phenomena such as abrupt transitions and chaotic behavior. Sleep stages and sustained fluctuations of autonomic functions such as temperature, blood pressure, electroencephalogram (EEG), etc., can be described as a chaotic process. The EEG signals are highly subjective and the information about the various states may appear at random in the time scale. Therefore, EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. The sleep data analysis is carried out using non-linear parameters: correlation dimension, fractal dimension, largest Lyapunov entropy, approximate entropy, Hurst exponent, phase space plot and recurrence plots. These non-linear parameters quantify the cortical function at different sleep stages and the results are tabulated.

    Item Type: Article
    Identification Number: https://doi.org/10.1016/j.cmpb.2005.06.011
    Page Range: 37-45
    Depositing User: Oliver Faust
    Date Deposited: 17 Feb 2016 10:21
    Last Modified: 13 Jun 2017 13:33
    URI: http://shura.shu.ac.uk/id/eprint/11369

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