Multilevel Feature Learning Method for Accurate Interictal Epileptiform Spike Detection

Multilevel Feature Learning Method for Accurate Interictal Epileptiform Spike Detection

Interictal epileptiform spike (referred to as spike) detected from electroencephalograms lasting only 20- to 200-ms can provide a reliable evidence-based indicator for clinical seizure type diagnosis. Recent feature representation approaches focus either on the concrete-level or abstract-level infor...

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Bibliographic Details
Main Authors: Chenchen Cheng, Yan Liu, Bo You, Yuanfeng Zhou, Fei Gao, Liling Yang, Yakang Dai
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Transactions on Neural Systems and Rehabilitation Engineering
Subjects:
Interictal epileptiform spike
multilevel feature learning
spike detection
spatio-temporal-frequency multidomain long-term dependent feature representation
Online Access:https://ieeexplore.ieee.org/document/9839382/

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https://ieeexplore.ieee.org/document/9839382/

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