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

被引：51

作者：

Liu, Quan ^{[2
]}

Wei, Qin ^{[2
]}

Fan, Shou-Zen ^{[3
]}

Lu, Cheng-Wei ^{[1
,4
]}

Lin, Tzu-Yu ^{[1
,4
]}

Abbod, Maysam F. ^{[5
]}

Shieh, Jiann-Shing ^{[1
]}

机构：

[1] Yuan Ze Univ, Dept Mech Engn, Chungli 32003, Taiwan

[2] Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Peoples R China

[3] Natl Taiwan Univ, Dept Anesthesiol, Coll Med, Taipei 100, Taiwan

[4] Far Eastern Mem Hosp, Dept Anesthesiol, Ban Chiao 220, Taiwan

[5] Brunel Univ, Sch Engn & Design, London UB8 3PH, England

来源：

ENTROPY | 2012年 / 14卷 / 06期

基金：

美国国家科学基金会;

关键词：

multiscale entropy; electroencephalography; depth of anesthesia; adaptive resampling procedure; APPROXIMATE ENTROPY; BISPECTRAL INDEX; UNCONSCIOUSNESS; DECOMPOSITION; TRANSITION; AWARENESS;

D O I：

10.3390/e14060978

中图分类号：

O4 [物理学];

学科分类号：

070305 [高分子化学与物理];

摘要：

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 (S-E) 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 S-E 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 S-E in small scales and complexity of EEG, which could help anesthesiologists evaluate the status of patients.

引用

页码：978 / 992

页数：15

共 24 条

[1]

Permutation entropy: A natural complexity measure for time series [J].