TY - GEN
T1 - Automatic stage scoring of single-channel sleep EEG based on multiscale permutation entropy
AU - Kuo, Chih En
AU - Liang, Sheng Fu
PY - 2011
Y1 - 2011
N2 - Multiscale entropy is a recently developed method to estimate complexity associated with the long-range temporal correlation of a time series. Since sleep EEG patterns also change regularly from light to deep sleep states, we firstly applied multiscale permutation entropy (MPE) to analysis sleep EEG to investigate the relations between changes of sleep stages and the MPE values. It was observed that correlation coefficient between the averaged MPE values of sleep EEG and the manual scoring of sleep stages can reach over 0.7. Then a MPE-based sleep scoring method for single channel EEG was developed. After training based on the data from 10 subjects, the overall sensitivity of the proposed automatic sleep scoring method combining MPE, autoregressive models, and linear discriminant analysis can reach 89.1% evaluated by the data of the other 10 subjects. Due to high accuracy and requiring only single-channel EEG, the proposed method has good applicability for sleep monitoring and home cares.
AB - Multiscale entropy is a recently developed method to estimate complexity associated with the long-range temporal correlation of a time series. Since sleep EEG patterns also change regularly from light to deep sleep states, we firstly applied multiscale permutation entropy (MPE) to analysis sleep EEG to investigate the relations between changes of sleep stages and the MPE values. It was observed that correlation coefficient between the averaged MPE values of sleep EEG and the manual scoring of sleep stages can reach over 0.7. Then a MPE-based sleep scoring method for single channel EEG was developed. After training based on the data from 10 subjects, the overall sensitivity of the proposed automatic sleep scoring method combining MPE, autoregressive models, and linear discriminant analysis can reach 89.1% evaluated by the data of the other 10 subjects. Due to high accuracy and requiring only single-channel EEG, the proposed method has good applicability for sleep monitoring and home cares.
UR - http://www.scopus.com/inward/record.url?scp=84855647116&partnerID=8YFLogxK
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U2 - 10.1109/BioCAS.2011.6107824
DO - 10.1109/BioCAS.2011.6107824
M3 - Conference contribution
AN - SCOPUS:84855647116
SN - 9781457714696
T3 - 2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011
SP - 448
EP - 451
BT - 2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011
T2 - 2011 IEEE Biomedical Circuits and Systems Conference, BioCAS 2011
Y2 - 10 November 2011 through 12 November 2011
ER -