论文信息 - Automatic detection of epileptic seizure using time-frequency distributions

Automatic detection of epileptic seizure using time-frequency distributions

The aim of this work is to introduce a new method based on time frequency distribution for classifying the EEG signals. Some parameters are extracted using time-frequency distribution as inputs to a Feed-Forward Backpropagation Neural Networks (FBNN). The proposed method had better results with 98.25% accuracy compared to previously studied methods such as Wavelet transform, Entropy, Logistic regression and Lyapanov Exponent.

Javad Hashemi | Arash Maghsoudi | Arian Ashourvan | Hamid R. Mohseni | Mo Kadbi

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