TY - JOUR
T1 - A rule-based automatic sleep staging method
AU - Liang, Sheng Fu
AU - Kuo, Chin En
AU - Hu, Yu Han
AU - Cheng, Yu Shian
N1 - Funding Information:
This work was supported by the National Science Council of Taiwan under Grant NSC 98-2221-E-006-161-MY3 and 100-2220-E-006-010 .
PY - 2012/3/30
Y1 - 2012/3/30
N2 - In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future.
AB - In this paper, a rule-based automatic sleep staging method was proposed. Twelve features including temporal and spectrum analyses of the EEG, EOG, and EMG signals were utilized. Normalization was applied to each feature to eliminating individual differences. A hierarchical decision tree with fourteen rules was constructed for sleep stage classification. Finally, a smoothing process considering the temporal contextual information was applied for the continuity. The overall agreement and kappa coefficient of the proposed method applied to the all night polysomnography (PSG) of seventeen healthy subjects compared with the manual scorings by R&K rules can reach 86.68% and 0.79, respectively. This method can integrate with portable PSG system for sleep evaluation at-home in the near future.
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U2 - 10.1016/j.jneumeth.2011.12.022
DO - 10.1016/j.jneumeth.2011.12.022
M3 - Article
C2 - 22245090
AN - SCOPUS:84862808334
SN - 0165-0270
VL - 205
SP - 169
EP - 176
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
IS - 1
ER -