Table 10.

Comparison of our proposed method with existing techniques for the categorization of wake vs. S1-sleep vs. S2-sleep vs. S3-sleep vs. REM sleep stages using multi-channel and single-channel EEG signals.

Feature Extraction Methods	Classifier Used	Overall Accuracy (%)
Spectral Features evaluated from different rhythms of multi-channel EEG signals [14]	MSVM	68.24
Different non-linear features extracted from multi-channel EEG signals [9]	Unsupervised learning (J-means clustering)	57.40
Time domain and spectral features extracted from multi-channel EEG [23]	DSVM	74.80
Learnable features evaluated from multi-channel EEG signal in convolution layer stages [24]	Transfer learning using CNN	67.70
Renyi entropy features computed from the time-frequency representation of single-channel EEG signals [21]	Random forest	73.21
Multi-scale DE and BE features extracted from Multi-channel EEG signal (proposed work)	hybrid learning	73.88