The benign epilepsy with spinous waves in the 1 central temporal region (BECT) is the one of the most common 2 epileptic syndromes in children, that seriously threaten the ner-3 vous system development of children. The most obvious feature of BECT is the existence of a large number of electroencephalogram 5 (EEG) spikes in the Rolandic area during the interictal period, 6 that is an important basis to assist neurologists in BECT diag-7 nosis. With this regard, the paper proposes a novel BECT spike 8 detection algorithm based on time domain EEG sequence features 9 and the long short-term memory (LSTM) neural network. Three time domain sequence features, that can obviously characterize the spikes of BECT, are extracted for EEG representation. The 12 synthetic minority oversampling technique (SMOTE) is applied to 13 address the spike imbalance issue in EEGs, and the bi-directional 14 LSTM (BiLSTM) is trained for spike detection. The algorithm is 15 evaluated using the EEG data of 15 BECT patients recorded from 16 the Children's Hospital, Zhejiang University School of Medicine 17 (CHZU). The experiment shows that the proposed algorithm can obtained an average of 88.54% F1 score, 92.04% sensitivity, and 19 85.75% precision, that generally outperforms several state-of-the-20 art spike detection methods.

Accurate eye blink artifact detection is essential for electroencephalogram (EEG) analysis and auxiliary analysis of nervous system diseases, especially in the presence of the frontal epileptiform discharges. In this paper, we develop a novel eye blink artifact detection algorithm based on optimally selected multi-dimensional EEG features. Specific efforts have been paid to filtering the frontal epileptiform discharges, where an unsupervised learning exploiting the EEG signal physiological characteristics and smooth nonlinear energy operator (SNEO) based on the K-means clustering has been firstly proposed. Multiple statistical EEG features derived from the frontal electrodes and other electrodes are then extracted to characterize eye blink artifacts. Discriminative feature selection scheme based on the variance filtering and Relief algorithms has been respectively studied, and the average correlation coefficient (ACC) is applied for feature optimization evaluation. The eye blink artifact detection is finally achieved based on the support vector machine (SVM) trained on the optimized EEG features. The effectiveness of the proposed algorithm is demonstrated by experiments carried out on the EEG database of 11 subjects recorded from the Children's Hospital, Zhejiang University School of Medicine (CHZU). Comparisons to several state-of-the-art (SOTA) eye blink artifact detection methods are also presented.

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Aim This study aimed to evaluate the efficacy and retention rate of a ketogenic diet (KD) and assess factors that influence the efficacy of KD therapy in children with refractory epilepsy (RE). Methods We retrospectively studied the efficacy and retention rate of 56 RE children who accepted KD therapy from January 2013 to December 2019. Patients who had a ≥50% reduction in seizure frequency were defined as responders. The retention rate was calculated as the proportion of children who continued KD/the total number of children who were followed up at the time of enrollment. We also analyzed the effects of different factors (such as gender, KD initial age, KD duration, the type of epilepsy syndrome, and others) on the efficacy of the KD. Results (1) The efficacy rates for the KD at 3, 6, 12, and 18 months were 51.8%, 53.6%, 39.2%, and 23.2%, respectively. (2) The retention rates for the KD at 3, 6, 12 and 18 months were 100%, 69.6%, 41.1% and 23.2%, respectively. (3) There was no correlation between efficacy and gender, epilepsy onset age, the type of epilepsy syndrome, EEG improvement, or the number of antiseizure medications (ASMs), while cranial magnetic resonance imaging (MRI) abnormalities, KD duration, and KD initial age affected its efficacy at three months. Conclusion (1) KD therapy for refractory childhood epilepsy was effective and produced a high retention rate. (2) MRI abnormalities and the initial age and duration of KD influenced its short-term efficacy in RE children.

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