ArticleComputational intelligence and neuroscience2017
Epileptic Seizure Prediction Using CSP and LDA for Scalp EEG Signals.
Article in Computational intelligence and neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Directed graph neural networks with partial directed coherence for seizure prediction and epileptogenic network characterization.iScience · 2026Article
- Unlocking Insights from Postictal EEGs: Investigating Predictive Markers of Seizure Recurrence.Annals of biomedical engineering · 2026Article
- An Attention-Residual Convolutional Network for Real-Time Seizure Classification on Edge Devices.Sensors (Basel, Switzerland) · 2025Article
- Artificial intelligence in preclinical epilepsy research: Current state, potential, and challenges.Epilepsia open · 2025Review
- A hierarchical trait and state model for decoding dyadic social interactions.Scientific reports · 2025Article
- Feature fusion ensemble classification approach for epileptic seizure prediction using electroencephalographic bio-signals.Frontiers in medicine · 2025Article
- Epilepsy Prediction and Detection Using Attention-CssCDBN with Dual-Task Learning.Sensors (Basel, Switzerland) · 2024Article
- Research progress of epileptic seizure prediction methods based on EEG.Cognitive neurodynamics · 2024Review
- Optimizing motion imagery classification with limited channels using the common spatial pattern-based integrated algorithm.Medical & biological engineering & computing · 2024Article
- A scheme combining feature fusion and hybrid deep learning models for epileptic seizure detection and prediction.Scientific reports · 2024Article
- A fused multi-subfrequency bands and CBAM SSVEP-BCI classification method based on convolutional neural network.Scientific reports · 2024Article
- Parameterized aperiodic and periodic components of single-channel EEG enables reliable seizure detection.Physical and engineering sciences in medicine · 2024Article
- The applied principles of EEG analysis methods in neuroscience and clinical neurology.Military Medical Research · 2023Review
- Combining temporal and spatial attention for seizure prediction.Health information science and systems · 2023Article
- Wearable Electromyography Classification of Epileptic Seizures: A Feasibility Study.Bioengineering (Basel, Switzerland) · 2023Article
- Deep learning-based EEG emotion recognition: Current trends and future perspectives.Frontiers in psychology · 2023Review
- An end-to-end seizure prediction approach using long short-term memory network.Frontiers in human neuroscience · 2023Article
- Epilepsy seizure prediction with few-shot learning method.Brain informatics · 2022Article
- Epilepsy Seizures Prediction Based on Nonlinear Features of EEG Signal and Gradient Boosting Decision Tree.International journal of environmental research and public health · 2022Article
- Effective Evaluation of Medical Images Using Artificial Intelligence Techniques.Computational intelligence and neuroscience · 2022Article
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a patient-specific epileptic seizure predication method relying on the common spatial pattern- (CSP-) based feature extraction of scalp electroencephalogram (sEEG) signals. Multichannel EEG signals are traced and segmented into overlapping segments for both preictal and interictal intervals. The features extracted using CSP are used for training a linear discriminant analysis classifier, which is then employed in the testing phase. A leave-one-out cross-validation strategy is adopted in the experiments. The experimental results for seizure prediction obtained from the records of 24 patients from the CHB-MIT database reveal that the proposed predictor can achieve an average sensitivity of 0.89, an average false prediction rate of 0.39, and an average prediction time of 68.71 minutes using a 120-minute prediction horizon.
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