Driving drowsiness detection using spectral signatures of EEG-based neurophysiology

Keyphrases

• Electroencephalography 100%
• Spectral Signature 100%
• Drowsiness Detection 100%
• Driver Drowsiness 100%
• Drowsiness 60%
• Passive Brain-computer Interfaces (pBCI) 60%
• Interface Scheme 40%
• Occipital Cortex 40%
• Driving Task 40%
• Computational Complexity 20%
• Electrodeposition 20%
• Human Brain 20%
• Human Detection 20%
• Selection Strategy 20%
• Feature Extraction 20%
• Classification Results 20%
• Feature Selection Methods 20%
• Temporal Correlation 20%
• Physiological Condition 20%
• Performance Assessment 20%
• Global Features 20%
• Support Vector Machine 20%
• Detection Accuracy 20%
• Execution Time 20%
• Brain Regions 20%
• Decision Tree 20%
• Spectral Bands 20%
• Brain Signals 20%
• Low-cost Hardware 20%
• Kappa Coefficient 20%
• Logistic Regression 20%
• Hardware Requirements 20%
• Area under the Receiver Operating Characteristic Curve 20%
• Multi-channel 20%
• Channel Selection 20%
• Discriminant Analysis 20%
• Assessment Metrics 20%
• Spectral Information 20%
• Score-based 20%
• Interface Modality 20%
• Traditional Machine Learning 20%
• Ensemble Classifier 20%
• Machine Learning Classifiers 20%
• Binary Classification 20%
• Nave Bayes 20%
• Band Power 20%
• Driving Operation 20%
• ReliefF Feature Selection 20%
• Intrusiveness 20%
• Extraction Cost 20%
• Hypothesis Testing Procedure 20%
• F1 Score 20%
• Road Safety 20%
• Aftereffects 20%
• Software Requirements 20%
• Drowsy Driving 20%
• Statistical Hypothesis Testing 20%
• Biosignals 20%
• Road Crashes 20%
• Cohen's kappa 20%
• Low-cost Software 20%
• Confusion Matrix 20%
• Simulated Driving 20%
• Predictor Importance 20%
• Sleep-deprived 20%
• Left Hemisphere 20%
• Feature Ranking 20%
• Normal Driving 20%
• Road Casualties 20%
• Neurological State 20%
• Right Hemisphere 20%
• Classifier Comparison 20%
• Matthews Correlation Coefficient 20%
• Chi-square Feature Selection 20%
• Minimum Redundancy Maximum Relevance (mRMR) 20%
• Inter-channel 20%
• Matrix-based 20%
• K-nearest 20%
• Optimised Ensemble Model 20%

Computer Science

• Drowsiness Detection 100%
• Spectral Signature 100%
• Computer Interface 75%
• Healthy Subject 25%
• Machine Learning 25%
• Feature Extraction 25%
• Feature Selection 25%
• classification result 25%
• Computational Complexity 25%
• Support Vector Machine 25%
• Nearest Neighbors Classifier 25%
• Execution Time 25%
• Decision Trees 25%
• Nave Bayes 25%
• Hardware Requirement 25%
• Temporal Correlation 25%
• Characteristic Curve 25%
• Logistic Regression 25%
• ensemble classifier 25%
• Binary Classification 25%
• Minimum Redundancy 25%
• Global Feature 25%
• Spectral Information 25%
• Left Hemisphere 25%
• Software Requirements 25%
• Discriminant Analysis 25%
• Extraction Cost 25%
• Confusion Matrix 25%

INIS

• detection 100%
• brain 100%
• electroencephalography 100%
• computers 37%
• interfaces 37%
• cost 25%
• humans 25%
• comparative evaluations 25%
• classification 25%
• correlations 25%
• roads 25%
• signals 12%
• performance 12%
• information 12%
• applications 12%
• values 12%
• operation 12%
• accuracy 12%
• simulation 12%
• curves 12%
• testing 12%
• assessments 12%
• computer codes 12%
• precision 12%
• vectors 12%
• extraction 12%
• matrices 12%
• power 12%
• safety 12%
• machine learning 12%
• decision tree analysis 12%
• electrodes 12%
• hypothesis 12%
• specificity 12%
• lethals 12%
• metrics 12%
• sleep 12%
• redundancy 12%