EEG signal classification method based on fractal features and neural network

@article{Phothisonothai2008EEGSC,
  title={EEG signal classification method based on fractal features and neural network},
  author={Montri Phothisonothai and Masahiro Nakagawa},
  journal={2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society},
  year={2008},
  pages={3880-3883}
}
  • M. Phothisonothai, M. Nakagawa
  • Published 2008
  • Mathematics, Medicine
  • 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
In this paper, we propose a method to classify electroencephalogram (EEG) signal recorded from left- and right-hand movement imaginations. Three subjects (two males and one female) are volunteered to participate in the experiment. We use a technique of complexity measure based on fractal analysis to reveal feature patterns in the EEG signal. Effective algorithm, namely, detrended fluctuation analysis (DFA) has been selected to estimate embedded fractal dimension (FD) values between relaxing and… Expand
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