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Table 2 The average performances of kNN, QDA, and SVM classification methods in sleep stage classification on healthy subjects

From: Sleep stage and obstructive apneaic epoch classification using single-lead ECG

Classification

Sleep Stages

Total

Method

Wake

NREM1

NREM2

NREM3

NREM4

REM

Accuracy

kNN

322/350

105/109

2159/3773

352/390

775/943

655/836

4414/6407

 

= 92%

= 97%

= 58.2%

= 90.3%

= 82.2%

= 78.4%

= 68.9%

 

CKI = 0.95

CKI = 0.98

CKI = 0.55

CKI = 0.95

CKI = 0.90

CKI = 0.91

 

QDA

332/350

106/109

2253/3773

366/390

821/943

695/836

4581/6407

 

= 94.9%

= 97.9%

= 59.7%

= 93.8%

= 87.1%

= 83.2%

= 71.5%

 

CKI = 0.97

CKI = 0.98

CKI = 0.56

CKI = 0.96

CKI = 0.94

CKI = 0.95

 

SVM

334/350

107/109

2328/3773

368/390

824/943

709/836

4684/6407

 

= 95.6%

= 98.5%

= 61.8%

= 94.3%

= 87.4%

= 84.9%

= 73.1%

 

CKI = 0.98

CKI = 0.99

CKI = 0.59

CKI = 0.98

CKI = 0.95

CKI = 0.95

 
  1. The value in each cell shows the number of epochs with accurate estimations divided by the total number of epochs of that specific stage and the corresponding percentage. Cohen's Kappa Index (CKI) is given for each stage and classification method. The last column indicates the total classification accuracy obtained throughout the night for each method.