Artificial Intelligence-based Signal Processing for Brain Activity Analysis

1. Introduction and Acquisition Methods of Brain Signals 2. AI-EEG: Advanced Integration and Machine Learning Standards for EEG Data Acquisition and Processing 3. Feature Extraction from Brain Signals in Brain-Computer Interface (BCI) Technology 4. PTSD Diagnosis Based on False Memory Tasks and Fuzzy Synchronization Likelihood Index 5. XAI-Enhanced EEG Analysis for Limb Task Identification 6. EEG-based Estimation of Obsessive Compulsive Disorder Severity using Nonlinear Regression via Deep Negative Correlation Learning and Fuzzy Weighting 7. Determination of OCD severity using rule-based representation learner: an EEG study 8. A Deep Transfer Convolutional Neural Network Framework Leveraging VGG16 for Motor Imagery Classification from EEG Signals 9. Classification of Inner Speech EEG signals for BCI Applications 10. Using AttnSleep for Single-channel BCI Processing 11. Comprehensive Analysis of Seizure activity in Critical Care Patients with Harmful Brain Patterns 12. Integration of Multimodal Data for Enhanced Artifacts Detection and Removal in EEG-based BCI Systems 13. Emotion Recognition from EEG Signals Using Machine Learning Algorithms 14. Enhanced U-Net Based on Multi-Scale Fashion for MRI Segmentation 15. Analysis of Alzheimer MRI Image and their Associated Cancer Disease 16. A Review on Feature Extraction Techniques for Diagnosis of Neurological Disorders using Brain Signals