Decoding Human Somatosensory Sensitivity Through Resting EEG and Behavioral Analysis: A Multimodal Fusion Approach

Keyphrases

• Fusion Approach 100%
• Behavior Analysis 100%
• Resting-state EEG 100%
• Electroencephalography Analysis 100%
• Multimodal Fusion 100%
• Frequency-based Approach 83%
• Thermally Sensitive 66%
• Non-sensitive 66%
• Power Spectral Density 50%
• Sensitive Groups 50%
• Support Vector Machine 33%
• K-nearest 33%
• Brain Networks 33%
• Gaussian Classifier 33%
• Random Forest Classifier 33%
• Quantitative Sensory Testing 33%
• Clinical Practice 16%
• K-means 16%
• Feature Selection 16%
• Selected Frequency 16%
• Density-based 16%
• Healthy Individuals 16%
• Classification Task 16%
• Group by 16%
• Perceptual Evaluation 16%
• Pain Management 16%
• Power Types 16%
• Spectral Frequency 16%
• Acceptable Accuracy 16%
• Precision Medicine 16%
• Classifier Model 16%
• Supervised Classification 16%
• Leave-one-subject-out 16%
• Multi-parameter 16%
• Healthy Participants 16%
• Inter-electrode 16%
• Pain Perception 16%
• Connectivity-based 16%
• Multimodal Data 16%
• Brain Activation Pattern 16%
• Pressure Stimulus 16%
• Punctate 16%
• Clinical Pain 16%
• Phenotype Frequencies 16%
• Brain Signature 16%
• Minimum Redundancy Maximum Relevance (mRMR) 16%
• Quantitative Objectives 16%

Neuroscience

• Support Vector Machine 100%
• Brain Network 100%
• Brain Activation 50%
• Nociception 50%
• Neurophysiology 50%
• Quantitative Sensory Testing 50%