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Detecting epileptic seizures with electroencephalogram via a context-learning model

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Figure

Fig. 1 Schematic illustration of the overall framework. In this framework, we focus on extracting representative features from EEG signals
Fig. 2 The scalp EEG of patient A. The red bar marks the onset of a seizure. The EEG signals before this red bar are of non-seizure states and the EEGsignals after this red bar are of seizure states
Fig. 4 An example of EEG segmentation. Given a 5 second long EEG signal, it is segmented into three EEG fragments by a 3 second sliding windowwhen the step length is 1 second
Fig. 6 An example of EEG sequence translation. Each EEG fragment can be decomposed into a combination of EEG words in the EEG dictionary.Each EEG word corresponds to a hidden unit of the sparse autoencoder in the dictionary learning step, and the distribut
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