Edit CHB-MIT (CHB-MIT Scalp EEG) The CHB-MIT dataset is a dataset of EEG recordings from pediatric subjects with intractable seizures. Subjects were monitored for up to several days following withdrawal of anti-seizure mediation in order to characterize their seizures and assess their candidacy ...
327CHB-MIT Scalp EEG Database 218Sleep Heart Health Study PSG Database 209心理健康数据集 2010PPG DaLiA是基于PPG的心率估计的公开数据集 × 帕依提提提温馨提示 该数据集正在整理中,为您准备了其他渠道,请您使用 点击前往新渠道下载 注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。 暂无相关...
We proposed a patient-specific deep learningbased single-channel seizure detection approach using the long-term scalp EEG recordings of the Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) dataset, in conjunction with neurologists' confirmation of spatial s...
Collection of EEG recordings of 22 pediatric subjects with intractable seizuresData CardCode (24)Discussion (0)Suggestions (0)Suggestions search tuneAll FiltersClear Allclose Typeexpand_morePendingexpand_more Recently updated No results found To see more results, try reducing the number of ...
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由于癫痫发作时不是整个大脑区域都有相关的反映,因此 EEG 信号在不同的 EEG 通道上有着不同的表现形式。癫痫发作时的 EEG 信号表现也并不是存在于所有的 EEG 通道,如果能设计一种算法来筛选出最能反应患者癫痫发作的 EEG 通道,不仅能减少模型的计算量,还能减少模型的硬件资源开销,同时还能提高癫痫预测的效率。
In this study, using EEG signals of patients from CHB-MIT dataset, we were able to achieve sensitivity of 90.76%.Ali EsmaeilpourShaghayegh Shahiri TabarestaniAlireza NiaziEngineering Reports
Deep learning‐based seizure prediction using EEG signals: A comparative analysis of classification methods on the CHB‐MIT datasetdoi:10.1002/eng2.12918Esmaeilpour, AliTabarestani, Shaghayegh ShahiriNiazi, AlirezaEngineering Reports