Early Detection of Alzheimer's Disease by Blind Source Separation, Time Frequency Representation, and Bump Modeling of EEG Signals

@inproceedings{Vialatte2005EarlyDO,
  title={Early Detection of Alzheimer's Disease by Blind Source Separation, Time Frequency Representation, and Bump Modeling of EEG Signals},
  author={François B. Vialatte and Andrzej Cichocki and G{\'e}rard Dreyfus and Toshimitsu Musha and Sergei L. Shishkin and R{\'e}mi Gervais},
  booktitle={ICANN},
  year={2005}
}
The early detection Alzheimer’s disease (AD) is an important challenge. In this paper, we propose a novel method for early detection of AD using electroencephalographic (EEG) recordings: first a blind source separation algorithm is applied to extract the most significant spatio-temporal components; these components are subsequently wavelet transformed; the resulting time-frequency representation is approximated by sparse “bump modeling”; finally, reliable and discriminant features are selected… CONTINUE READING

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