Non-linear analysis of EEG signals at various sleep stages

Authors:
Rajendra Acharya U.;Oliver Faust;N. Kannathal;TjiLeng Chua;Swamy Laxminarayan
Affiliations:
Department of Electronics and Computer Engineering, School of Engineering, Ngee Ann Polytechnic, 535 Clementi Road, Singapore 599489, Singapore;Department of Electronics and Computer Engineering, School of Engineering, Ngee Ann Polytechnic, 535 Clementi Road, Singapore 599489, Singapore;Department of Electronics and Computer Engineering, School of Engineering, Ngee Ann Polytechnic, 535 Clementi Road, Singapore 599489, Singapore;Department of Electronics and Computer Engineering, School of Engineering, Ngee Ann Polytechnic, 535 Clementi Road, Singapore 599489, Singapore;Biomedical Research Institute & Institute of Rural Health, Idaho Sate University, USA
Venue:
Computer Methods and Programs in Biomedicine
Year:
2005

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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.