Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy?

@article{Rossini2008IsIP,
  title={Is it possible to automatically distinguish resting EEG data of normal elderly vs. mild cognitive impairment subjects with high degree of accuracy?},
  author={Paolo Maria Rossini and Massimo Buscema and Massimiliano Capriotti and Enzo Grossi and Claudio Babiloni},
  journal={Clinical Neurophysiology},
  year={2008},
  volume={119},
  pages={1534-1545}
}
OBJECTIVE It has been shown that a new procedure (implicit function as squashing time, IFAST) based on artificial neural networks (ANNs) is able to compress eyes-closed resting electroencephalographic (EEG) data into spatial invariants of the instant voltage distributions for an automatic classification of mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects with classification accuracy of individual subjects higher than 92%. METHODS Here we tested the hypothesis that this is… CONTINUE READING

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 39 extracted citations

Similar Papers

Loading similar papers…