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Entropy 2012, 14(6), 978-992; doi:10.3390/e14060978
Article

Adaptive Computation of Multiscale Entropy and Its Application in EEG Signals for Monitoring Depth of Anesthesia During Surgery

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Received: 29 March 2012; in revised form: 9 May 2012 / Accepted: 21 May 2012 / Published: 25 May 2012
(This article belongs to the Special Issue Concepts of Entropy and Their Applications)
Download PDF [471 KB, uploaded 29 May 2012]
Abstract: Entropy as an estimate of complexity of the electroencephalogram is an effective parameter for monitoring the depth of anesthesia (DOA) during surgery. Multiscale entropy (MSE) is useful to evaluate the complexity of signals over different time scales. However, the limitation of the length of processed signal is a problem due to observing the variation of sample entropy (SE) on different scales. In this study, the adaptive resampling procedure is employed to replace the process of coarse-graining in MSE. According to the analysis of various signals and practical EEG signals, it is feasible to calculate the SE from the adaptive resampled signals, and it has the highly similar results with the original MSE at small scales. The distribution of the MSE of EEG during the whole surgery based on adaptive resampling process is able to show the detailed variation of SE in small scales and complexity of EEG, which could help anesthesiologists evaluate the status of patients.
Keywords: multiscale entropy; electroencephalography; depth of anesthesia; adaptive resampling procedure multiscale entropy; electroencephalography; depth of anesthesia; adaptive resampling procedure
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Liu, Q.; Wei, Q.; Fan, S.-Z.; Lu, C.-W.; Lin, T.-Y.; Abbod, M.F.; Shieh, J.-S. Adaptive Computation of Multiscale Entropy and Its Application in EEG Signals for Monitoring Depth of Anesthesia During Surgery. Entropy 2012, 14, 978-992.

AMA Style

Liu Q, Wei Q, Fan S-Z, Lu C-W, Lin T-Y, Abbod MF, Shieh J-S. Adaptive Computation of Multiscale Entropy and Its Application in EEG Signals for Monitoring Depth of Anesthesia During Surgery. Entropy. 2012; 14(6):978-992.

Chicago/Turabian Style

Liu, Quan; Wei, Qin; Fan, Shou-Zen; Lu, Cheng-Wei; Lin, Tzu-Yu; Abbod, Maysam F.; Shieh, Jiann-Shing. 2012. "Adaptive Computation of Multiscale Entropy and Its Application in EEG Signals for Monitoring Depth of Anesthesia During Surgery." Entropy 14, no. 6: 978-992.


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