Neurology

Seizures

Latest AI and machine learning research in seizures for healthcare professionals.

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MRI based early Temporal Lobe Epilepsy detection using DGWO based optimized HAETN and Fuzzy-AAL Segmentation Framework (FASF).

This work aims to promote early and accurate diagnosis of Temporal Lobe Epilepsy (TLE) by developing...

EEG based real time classification of consecutive two eye blinks for brain computer interface applications.

Human eye blinks are considered a significant contaminant or artifact in electroencephalogram (EEG),...

Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex.

The human thalamus projects nerve fibers to all cortical regions and propagates epileptic activity. ...

EmoTrans attention based emotion recognition using EEG signals and facial analysis with expert validation.

Emotion recognition via EEG signals and facial analysis becomes one of the key aspects of human-comp...

Improving EEG based brain computer interface emotion detection with EKO ALSTM model.

Decoding signals from the CNS brain activity is done by a computer-based communication device called...

Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection.

Schizophrenia is a mental disorder characterized by hallucinations, delusions, disorganized thinking...

Towards decoding motor imagery from EEG signal using optimized back propagation neural network with honey badger algorithm.

The importance of using Brain-Computer Interface (BCI) systems based on electro encephalography (EEG...

Schizophrenia detection from electroencephalogram signals using image encoding and wrapper-based deep feature selection approach.

Schizophrenia is a persistent and serious mental illness that leads to distortions in cognition, per...

STIED: a deep learning model for the spatiotemporal detection of focal interictal epileptiform discharges with MEG.

Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges...

Automated posture adjustment system for immobilized patients using EEG signals.

This paper presents a Brain Computing Interface (BCI) system utilizing Electroencephalography (EEG) ...

Identification of plasma proteins associated with seizures in epilepsy: A consensus machine learning approach.

Blood-based biomarkers in epilepsy could constitute important research tools advancing neurobiologic...

The impact of EEG preprocessing parameters on ultra-low-power seizure detection.

OBJECTIVE: Closed-loop neurostimulation is a promising treatment for drug-resistant focal epilepsy. ...

Microstate Analysis of Resting-State EEG Signals for Classifying Tinnitus from Healthy Subjects.

Electroencephalography (EEG) is a noninvasive technique for studying brain electrophysiology with h...

Revisiting Euclidean alignment for transfer learning in EEG-based brain-computer interfaces.

Due to large intra-subject and inter-subject variabilities of electroencephalogram (EEG) signals, EE...

γ neuromodulations: unraveling biomarkers for neurological and psychiatric disorders.

γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric di...

The class imbalance problem in automatic localization of the epileptogenic zone for epilepsy surgery: a systematic review.

Accurate localization of the epileptogenic zone (EZ) is crucial for epilepsy surgery, but the class ...

A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection.

Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain act...

Cerebral lateralization assessment: an explainable deep learning approach with channel attention mechanism.

In recent years, cross-frequency coupling (CFC) has emerged as a valuable tool in the study of a wid...

Epilepsy Prediction via Time-Frequency Features and Multi-Scale Hybrid Neural Networks.

The prediction of epileptic seizures heavily depends on the precise embedding and classification of ...

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