Epileptic seizure focus detection from interictal electroencephalogram: a survey
MR Islam, X Zhao, Y Miao, H Sugano… - Cognitive neurodynamics, 2023 - Springer
Electroencephalogram (EEG) is one of most effective clinical diagnosis modalities for the
localization of epileptic focus. Most current AI solutions use this modality to analyze the EEG …
localization of epileptic focus. Most current AI solutions use this modality to analyze the EEG …
Classification of the epileptic seizure onset zone based on partial annotation
Epilepsy is a chronic disorder caused by excessive electrical discharges. Currently, clinical
experts identify the seizure onset zone (SOZ) channel through visual judgment based on …
experts identify the seizure onset zone (SOZ) channel through visual judgment based on …
Classification of coma/brain-death EEG dataset based on one-dimensional convolutional neural network
B Li, J Cao - Cognitive Neurodynamics, 2023 - Springer
Electroencephalography (EEG) evaluation is an important step in the clinical diagnosis of
brain death during the standard clinical procedure. The processing of the brain-death EEG …
brain death during the standard clinical procedure. The processing of the brain-death EEG …
One‐dimensional atrous conv‐net based architecture for automatic diagnosis of epilepsy using electroencephalography signals and its brain–computer interface …
Precise monitoring and diagnosis of epilepsy by manual analysis of EEG signals are
challenging due to the low doctor‐to‐patient ratio, and shortage of medical resources. To …
challenging due to the low doctor‐to‐patient ratio, and shortage of medical resources. To …
Exploring the potential of pretrained CNNs and time-frequency methods for accurate epileptic EEG classification: a comparative study
Prompt diagnosis of epilepsy relies on accurate classification of automated
electroencephalogram (EEG) signals. Several approaches have been developed to …
electroencephalogram (EEG) signals. Several approaches have been developed to …
Quantitative analysis and machine learning-based interpretation of EEG signals in coma and brain-death diagnosis
B Li, J Liu, T Zhang, Y Cao, J Cao - Cognitive Neurodynamics, 2024 - Springer
Electroencephalography (EEG) reflects brain activity and is crucial for diagnosing states
such as coma and brain-death. However, the clinical interpretation of EEG signals faces …
such as coma and brain-death. However, the clinical interpretation of EEG signals faces …
Automated Classification of Focal and Non-focal Epileptic iEEG Signals using 1D-Convolutional Neural Network
AS Jangde, DS Sisodia - 2023 2nd International Conference …, 2023 - ieeexplore.ieee.org
Epilepsy affects 1% of the population across all age groups, making it the fourth most
dangerous brain disorder diagnosed worldwide. The seizures, limited to a specific area of …
dangerous brain disorder diagnosed worldwide. The seizures, limited to a specific area of …
[PDF][PDF] Classification of the Epileptic Seizure Onset Zone Based on Partial
Epilepsy is a chronic disorder caused by excessive electrical discharges. Currently, clinical
experts identify the seizure onset zone (SOZ) channel through visual judgment based on …
experts identify the seizure onset zone (SOZ) channel through visual judgment based on …
[PDF][PDF] 機械学習に基づいた脳疾患EEG 信号の解析及び高精度BCI システムの構築に関する研究
李博寧 - sit.repo.nii.ac.jp
Electroencephalography (EEG) is a method for recording brain activity as
electrophysiological indices, accurately reflecting the state of brain activity. Proper …
electrophysiological indices, accurately reflecting the state of brain activity. Proper …