Non-linear analysis of EEG signals at various sleep stages

  title={Non-linear analysis of EEG signals at various sleep stages},
  author={U. Rajendra Acharya and Oliver Faust and N. Kannathal and TjiLeng Chua and Swamy Laxminarayan},
  journal={Computer methods and programs in biomedicine},
  volume={80 1},
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… CONTINUE READING


Publications citing this paper.
Showing 1-10 of 129 extracted citations

Automatic detection of sleep spindles with the use of STFT, EMD and DWT methods

Neural Computing and Applications • 2016
View 4 Excerpts
Highly Influenced

Analysis of Brain Wave Due to Stimulus Using EEG

2018 International Conference on Computer, Communication, and Signal Processing (ICCCSP) • 2018
View 1 Excerpt

Analysis on Non-Linear Features of Electroencephalogram (EEG) Signal for Neuromarketing Application

2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA) • 2018

Chaotic Analysis of Hippocampal and Cortical Sleep EEG during Various Vigilance States

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) • 2018
View 1 Excerpt

Similar Papers

Loading similar papers…