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English(EN) Epileptic Seizure Detection in Separate Frequency Bands Using Feature Analysis and Graph Convolutional Neural Network (GCN) from Electroencephalogram (EEG) Signals

撤稿论文详述基于GCN的EEG癫痫发作检测

作者 PulseAugur 编辑部 · [1 个来源] ·

一项已被撤稿的研究论文提出了一种使用图卷积神经网络（GCN）应用于脑电图（EEG）信号来检测癫痫发作的框架。该方法包括将EEG信号分解为五个频带并提取特征，然后将这些特征输入GCN以模拟空间依赖性。在CHB-MIT数据集上的实验显示出高精度，尤其是在中频带，这表明与传统的宽带方法相比，可解释性和诊断精度有所提高。 AI

排序理由 该集群包含一篇被撤稿的学术论文，其中详细介绍了一种新的研究方法。[lever_c_demoted from research: ic=1 ai=1.0]

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撤稿论文详述基于GCN的EEG癫痫发作检测

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该集群包含一篇被撤稿的学术论文，其中详细介绍了一种新的研究方法。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Ferdaus Anam Jibon, Fazlul Hasan Siddiqui, F. Deeba, Gahangir Hossain ·

    使用特征分析和图卷积神经网络（GCN）从脑电图（EEG）信号中检测不同频带的癫痫发作

    arXiv:2604.00163v2 Announce Type: replace-cross Abstract: Epileptic seizures are neurological disorders characterized by abnormal and excessive electrical activity in the brain, resulting in recurrent seizure events. Electroencephalogram (EEG) signals are widely used for seizure …

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