Table 6.

Comparison of studies for the sleep stage scoring task, including sleep stages, feature extraction method, machine learning algorithm, and overall performance.

Authors	Year	Sleep Stages	Feature Extraction Method	Classification	Performance (%)
Santaji and Desai [59]	2020	S1, S2, REM	Entropy	RF	Accuracy = 97.8
Ebrahimi et al. [279]	2008	Awake, S1 and REM, S2, SWS	WT	MLP	Accuracy = 93
Hassan and Bhuiyan [203]	2016	Awake, S1, S2, S3, S4, REM	EMD	AdaBoost	Accuracy = 92.2
Lajnef et al. [276]	2015	Awake, S1, S2, SWS, REM	Entropy	Dendrogram-SVM	Accuracy = 92
Ravan [202]	2019	Awake, LS and REM, DS	WT	Dendrogram-SVM	Accuracy = 91.4
Kuo and Liang [277]	2011	Awake, S1, S2, SWS, REM	Entropy/AR	LDA	Sensitivity = 89.1
Delimayanti et al. [204]	2020	Awake, S1, S2, S3, S4, REM	FFT	RBF-SVM	Accuracy = 87.8
Zoubek et al. [275]	2007	Awake, NREM1, NREM2, SWS, PS	FFT	MLP	Accuracy = 71.6