Epilepsy detection in 121 patient populations using hypercube pattern from EEG signals.

Inf. Fusion(2023)

引用 15|浏览3
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摘要
•Automated detection of epilepsy using EEG signals from 121 participants.•Hypercube-based feature extractor and multilevel discrete wavelet transform techniques are employed.•Neighborhood component analysis (NCA) is used as a feature selector.•Attained 87.78% classification accuracy using voting and 79.07% with LOSO CV.
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关键词
Hypercube pattern,Feature fusion,Feature selection,Epilepsy detection,Fusion -based feature engineering
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