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Items: 1 to 20 of 228

1.

Monitoring the depth of anesthesia using entropy features and an artificial neural network.

Shalbaf R, Behnam H, Sleigh JW, Steyn-Ross A, Voss LJ.

J Neurosci Methods. 2013 Aug 15;218(1):17-24. doi: 10.1016/j.jneumeth.2013.03.008. Epub 2013 Apr 6.

PMID:
23567809
2.

Analysis of depth of anesthesia with Hilbert-Huang spectral entropy.

Li X, Li D, Liang Z, Voss LJ, Sleigh JW.

Clin Neurophysiol. 2008 Nov;119(11):2465-75. doi: 10.1016/j.clinph.2008.08.006. Epub 2008 Sep 21.

PMID:
18812265
3.

Measuring the effects of sevoflurane on electroencephalogram using sample entropy.

Shalbaf R, Behnam H, Sleigh J, Voss L.

Acta Anaesthesiol Scand. 2012 Aug;56(7):880-9. doi: 10.1111/j.1399-6576.2012.02676.x. Epub 2012 Mar 8.

PMID:
22404496
4.

Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia.

Li D, Li X, Liang Z, Voss LJ, Sleigh JW.

J Neural Eng. 2010 Aug;7(4):046010. doi: 10.1088/1741-2560/7/4/046010. Epub 2010 Jun 28.

PMID:
20581428
5.

Multiscale rescaled range analysis of EEG recordings in sevoflurane anesthesia.

Liang Z, Li D, Ouyang G, Wang Y, Voss LJ, Sleigh JW, Li X.

Clin Neurophysiol. 2012 Apr;123(4):681-8. doi: 10.1016/j.clinph.2011.08.027. Epub 2011 Oct 10.

PMID:
21993398
6.

Using permutation entropy to measure the electroencephalographic effects of sevoflurane.

Li X, Cui S, Voss LJ.

Anesthesiology. 2008 Sep;109(3):448-56. doi: 10.1097/ALN.0b013e318182a91b.

PMID:
18719442
7.

Monitoring depth of anesthesia using combination of EEG measure and hemodynamic variables.

Shalbaf R, Behnam H, Jelveh Moghadam H.

Cogn Neurodyn. 2015 Feb;9(1):41-51. doi: 10.1007/s11571-014-9295-z. Epub 2014 May 9.

8.

The EEG signal: a window on the cortical brain activity.

Constant I, Sabourdin N.

Paediatr Anaesth. 2012 Jun;22(6):539-52. doi: 10.1111/j.1460-9592.2012.03883.x. Review.

PMID:
22594406
9.

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

Olofsen E, Sleigh JW, Dahan A.

Br J Anaesth. 2008 Dec;101(6):810-21. doi: 10.1093/bja/aen290. Epub 2008 Oct 12.

PMID:
18852113
10.

Time-frequency balanced spectral entropy as a measure of anesthetic drug effect in central nervous system during sevoflurane, propofol, and thiopental anesthesia.

Vakkuri A, Yli-Hankala A, Talja P, Mustola S, Tolvanen-Laakso H, Sampson T, Viertiö-Oja H.

Acta Anaesthesiol Scand. 2004 Feb;48(2):145-53.

PMID:
14995935
11.

Classification of EEG bursts in deep sevoflurane, desflurane and isoflurane anesthesia using AR-modeling and entropy measures.

Lipping T, Stålnacke J, Olejarczyk E, Marciniak R, Jäntti V.

Conf Proc IEEE Eng Med Biol Soc. 2013;2013:5083-6. doi: 10.1109/EMBC.2013.6610691.

PMID:
24110878
12.

Poincaré analysis of the electroencephalogram during sevoflurane anesthesia.

Hayashi K, Mukai N, Sawa T.

Clin Neurophysiol. 2015 Feb;126(2):404-11. doi: 10.1016/j.clinph.2014.04.019. Epub 2014 Jun 5.

PMID:
24969375
13.

Monitoring the depth of anesthesia using a new adaptive neuro-fuzzy system.

Shalbaf A, Saffar M, Sleigh JW, Shalbaf R.

IEEE J Biomed Health Inform. 2017 May 29. doi: 10.1109/JBHI.2017.2709841. [Epub ahead of print]

PMID:
28574372
14.

Permutation auto-mutual information of electroencephalogram in anesthesia.

Liang Z, Wang Y, Ouyang G, Voss LJ, Sleigh JW, Li X.

J Neural Eng. 2013 Apr;10(2):026004. doi: 10.1088/1741-2560/10/2/026004. Epub 2013 Feb 1.

PMID:
23370095
15.

Neural network-based classification of anesthesia/awareness using Granger causality features.

Nicolaou N, Georgiou J.

Clin EEG Neurosci. 2014 Apr;45(2):77-88. doi: 10.1177/1550059413486271. Epub 2013 Jul 1.

PMID:
23820086
16.

A combination of electroencephalogram and auditory evoked potentials separates different levels of anesthesia in volunteers.

Horn B, Pilge S, Kochs EF, Stockmanns G, Hock A, Schneider G.

Anesth Analg. 2009 May;108(5):1512-21. doi: 10.1213/ane.0b013e3181a04d4c.

PMID:
19372330
17.

Multi-scale sample entropy of electroencephalography during sevoflurane anesthesia.

Wang Y, Liang Z, Voss LJ, Sleigh JW, Li X.

J Clin Monit Comput. 2014 Aug;28(4):409-17. doi: 10.1007/s10877-014-9550-1. Epub 2014 Jan 11.

PMID:
24414381
18.

[Monitoring the depth of anesthesia using a fuzzy neural network based on EEG].

Li M, Ye ZQ.

Zhongguo Yi Liao Qi Xie Za Zhi. 2006 Jul;30(4):253-5. Chinese.

PMID:
17039930
19.

[Comparison of an auditory evoked potentials index and a bispectral index versus clinical signs for determining the depth of anesthesia produced by propofol or sevoflurane].

Litvan H, Jensen EW, Maestre ML, Galán J, Campos JM, Fernández JA, Caminal P, Villar Landeira JM.

Rev Esp Anestesiol Reanim. 2000 Dec;47(10):447-57. Spanish.

PMID:
11171465
20.

EEG signal processing in anaesthesia. Use of a neural network technique for monitoring depth of anaesthesia.

Ortolani O, Conti A, Di Filippo A, Adembri C, Moraldi E, Evangelisti A, Maggini M, Roberts SJ.

Br J Anaesth. 2002 May;88(5):644-8.

PMID:
12067000

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