Permutation entropy of the electroencephalogram: a measure of anaesthetic drug effect

Olofsen, Erik; Sleigh, James W.; Dahan, Albert

doi:10.1093/bja/aen290

Cited by 318 publications

(284 citation statements)

References 25 publications

(11 reference statements)

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“…Thereby, the SampEn and ApEn of denoised EEG have been compared to the commercial indexes firstly, and then the statistical analysis and comparison with diagnosis results of anesthetists will be the next step in our study. Moreover, other complexity measures of EEG signals would also be used in further analysis and improvement, like the permutation entropy [23], Hilbert-Huang spectral entropy [24], and so on.…”

Section: Discussionmentioning

confidence: 99%

Analysis of EEG via Multivariate Empirical Mode Decomposition for Depth of Anesthesia Based on Sample Entropy

Wei

Liu

Fan

et al. 2013

Entropy

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Abstract:In monitoring the depth of anesthesia (DOA), the electroencephalography (EEG) signals of patients have been utilized during surgeries to diagnose their level of consciousness. Different entropy methods were applied to analyze the EEG signal and measure its complexity, such as spectral entropy, approximate entropy (ApEn) and sample entropy (SampEn). However, as a weak physiological signal, EEG is easily subject to interference from external sources such as the electric power, electric knives and other electrophysiological signal sources, which lead to a reduction in the accuracy of DOA determination. In this study, we adopt the multivariate empirical mode decomposition (MEMD) to decompose and reconstruct the EEG recorded from clinical surgeries according OPEN ACCESSEntropy 2013, 15 3459 to its best performance among the empirical mode decomposition (EMD), the ensemble EMD (EEMD), and the complementary EEMD (CEEMD) and the MEMD. Moreover, according to the comparison between SampEn and ApEn in measuring DOA, the SampEn is a practical and efficient method to monitor the DOA during surgeries at real time.

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Section: Discussionmentioning

confidence: 99%

Analysis of EEG via Multivariate Empirical Mode Decomposition for Depth of Anesthesia Based on Sample Entropy

Wei

Liu

Fan

et al. 2013

Entropy

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“…3 shows the variations of the signal's entropy for four different methods. The performance of PE and WPE is compared to two other methods from the literature, namely approximate entropy or ApEn [1,13] and the composite PE index or CPEI [14]. In the following, we give a brief description of each.…”

Section: A Synthetic Datamentioning

confidence: 99%

Weighted-permutation entropy: A complexity measure for time series incorporating amplitude information

et al. 2013

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Permutation entropy (PE) has been recently suggested as a novel measure to characterize the complexity of nonlinear time series. In this paper, we propose a simple method to address some of PE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif, and the sensitivity of patterns close to the noise floor. The method relies on the fact that patterns may be too disparate in amplitudes and variances and proceeds by assigning weights for each extracted vector when computing the relative frequencies associated with every motif. Simulations were conducted over synthetic and real data for a weighting scheme inspired by the variance of each pattern. Results show better robustness and stability in the presence of higher levels of noise, in addition to a distinctive ability to extract complexity information from data with spiky features or having abrupt changes in magnitude.

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“…It is worth noting that a non-proprietary EEG can be used inexpensively. Information from the EEG and from non-proprietary processed EEG indices might yield comparable information to commercially available devices [25][26][27][28].…”

Section: Editorialmentioning

confidence: 99%

The incidence of intra‐operative awareness in the UK: under the rate or under the radar?

Avidan

Mashour

2013

Anaesthesia

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Permutation entropy of the electroencephalogram: a measure of anaesthetic drug effect

Abstract: PE of the EEG shows promise as a simple measure of GABAergic anaesthetic drug effect.

Cited by 318 publications

References 25 publications

Analysis of EEG via Multivariate Empirical Mode Decomposition for Depth of Anesthesia Based on Sample Entropy

Analysis of EEG via Multivariate Empirical Mode Decomposition for Depth of Anesthesia Based on Sample Entropy

Weighted-permutation entropy: A complexity measure for time series incorporating amplitude information

The incidence of intra‐operative awareness in the UK: under the rate or under the radar?

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