TinySleepNet: An Efficient Deep Learning Model for Sleep Stage Scoring based on Raw Single-Channel EEG

Keyphrases

• Deep Learning Model 100%
• Sleep Scoring 100%
• Single-channel EEG 100%
• Efficient Deep Learning 100%
• Sleep Data 66%
• Training Data 33%
• State-of-the-art Techniques 33%
• Data Augmentation 33%
• Popular 33%
• Novel Technique 33%
• Deep Learning 33%
• Different Datasets 33%
• Different Characteristics 33%
• Hyperparameters 33%
• Computational Resources 33%
• Training Techniques 33%
• Amount of Training 33%
• Overfitting 33%
• Training Parameters 33%
• Processing pipeline 33%
• Scoring Criteria 33%
• Model Driven Architecture 33%
• Sleep Stages 33%
• Class-imbalanced Data 33%
• Time Axis 33%
• Spectrogram 33%
• Raw Signal 33%

Computer Science

• Deep Learning Model 100%
• Training Data 50%
• Large Data Set 50%
• Deep Learning Method 50%
• Imbalanced Data 50%
• Data Augmentation 50%
• Leaning Parameter 50%
• Computational Resource 50%
• Model Architecture 50%