Browse > Article
http://dx.doi.org/10.4313/TEEM.2013.14.6.299

Analysis on the Depth of Anesthesia by Using EEG and ECG Signals  

Ye, Soo-Young (Department of Radiological Science, Catholic University of Pusan)
Choi, Seok-Yoon (Department of Radiological Science, Catholic University of Pusan)
Kim, Dong-Hyun (Department of Radiological Science, Catholic University of Pusan)
Song, Seong-Hwan (Division of Energy and Bio-engineering, Dongseo University)
Publication Information
Transactions on Electrical and Electronic Materials / v.14, no.6, 2013 , pp. 299-303 More about this Journal
Abstract
Anesthesia, which started being used to remove pain during surgery, has become itself one of the major concerns to be considered during surgery. While actual anesthesia is being performed, patients tend to have unpleasant experiences, due to wakening that accompanies pain, or wakening that does not accompany pain. Since this awakening during anesthesia is a most unpleasant experience in a patient's life, evaluating the depth of anesthesia during surgery is essential for patients to avoid this experience. Although there has been much effort on the understanding and measurement of the depth of anesthesia, while various researches were performed on the need of anesthesia, the development of an indicator that could objectively evaluate the depth of anesthesia, other than by using the patient's vital signs, is still inadequate. Therefore, this study was to develop an objective indicator by using EEG and ECG, which are essentially measured during the surgery, to evaluate the depth of anesthesia. The experiment was performed by taking patients who require a relatively short operation time, and general inhalation anesthetics among surgical patients in obstetrics and gynecology as the subjects of experiment, to measure the EEG and ECG signals of patients under anesthetics. The result showed that SEF using EEG and LF, HF using ECG signal and correlation dimension analysis parameter were valuable parameters that could measure the depth of anesthesia, by the stage of anesthesia.
Keywords
Depth of anesthesia; EEG; ECG; PSD; LF; HF;
Citations & Related Records
연도 인용수 순위
  • Reference
1 John ER, "A field theory of consciousness", Conscious congnition, Vol. 10, No. 2, pp. 184-213, 2001 [DOI: http://dx.doi. org/10.1006/ccog.2001.0508].   DOI   ScienceOn
2 Recart A, White PF, Wang A, Gasanova I, Byerly S, Jones SB., "Effect of auditory evoked potential index monitoring on anesthetic drug requirements and recovery profile after laparoscopic surgery: a clinical utility study", Anesthesilolgy, Vol. 99, No. 4, pp. 813-818, 2003 [DOI: http://dx.doi.org/10.1213/ane.0b013e3181adc21a].   DOI   ScienceOn
3 McKeever S, Johnston L, Davidson AJ.," An observational study exploring amplitude-integrated electroencephalogram and spectral edge frequency during paediatric anaesthesia." Anaesth Intensive Care, Vol. 40, No. 2, pp. 275-284, 2012 [DOI: http://dx.doi.org/10.1093/bja/aes312].   DOI   ScienceOn
4 Janda M, Schubert A, Bajorat J, Hofmockel R, Noldge-Schomburg GF, Lampe BP, Simanski O., "Design and implementation of a control system reflecting the level of analgesia during general anesthesia", Biomed Tech(Berl), Vol. 58, No. 1, pp. 1-11, 2013 [DOI: http://dx.doi.org/10.1515/bmt-2012-0090].   DOI   ScienceOn
5 L. Gugino, R. Chabot, L. Prichep, E. John, V. Formanek, and L. Aglio, "Quantitative EEG changes associated with loss and return of consciousness in healthy adult volunteers anaesthetized with propofol or sevoflurane," Br. J. Anaesth., Vol. 87, pp. 421-428, Sep. 2001 [DOI: http://dx.doi.org/10.1093/bja/87.3.421].   DOI   ScienceOn
6 A. Miller, J.W.Sleigh, J.Barnard, and D.A.Steyn-Ross, "Does bispectral analysis and anything but complexity? BIS sub-components may be superior to BIS for detection of awareness ", Br. J Anaesth., Vol. 93, No. 4, pp. 596-597, 2004 [DOI: http://dx.doi. org/10.1093/bja/aeh612].   DOI   ScienceOn
7 Curtis BM, O'Keefe JH," Autonomic Tone as a Cardiovascular RiskFactor", The Dangers of Chronic Fight and Flight Mayo Clinic Proceedings, Vol. 77, No. 1, pp. 45-54, 2002 [DOI: http:// dx.doi.org/10.1016/S0025-6196(11)62137-X].
8 A. T. Mazzeo, E. La Monaca, R. Di Leo, G. Vita and L. B. Santamaria, "Heart rate variability: a diagnostic and prognostic tool in anesthesia and intensive care " Acta Anesthesiol Scand, Vol. 55, pp. 79-811, 2011 [DOI: http://dx.doi.org/10.1111/j.1399-6576.2011.02466.x].   DOI   ScienceOn
9 C. K Karmakar, A. H Khandoker, A. Voss and M. Palaniswami, "Sensitivity of temporal heart rate variability in Poincare plot to changes in parasympathetic nervous system activity", BioMedical Engineering, Vol. 10:17, 2011 [DOI: http://dx.doi. org/10.1186/1475-925X-10-17].   DOI   ScienceOn
10 U. Kraus, A. Schneider, S. Breitner, R. Hampe, R. Rucker, M. Pitz, U. Geruschkat, P. Belcredi, K. Radon, A. Peters," Individual Daytime Noise Exposure during Routine Activities and Heart Rate Variability in Adults: A Repeated Measures Study", Environment Health perspectives, Vol. 121, pp. 607-612, 2013 [DOI: http://dx.doi.org/10.1289/ehp.1205606].   DOI   ScienceOn
11 Suzuki N, Sugawara J, Kimura Y, Nagase S, Okamura K, Yaegashi N.," Assessment of maternal heart-rate variability during labor using wavelet-based power spectral analysis", Gynecol Obstet Invest., Vol. 74, No. 1, pp. 35-40, 2012 [DOI: http://dx.doi. org/10.1159/000336064].   DOI   ScienceOn
12 Freeman WJ, Zhai J.," Simulated power spectral density (PSD) of background electrocorticogram (ECoG).", Cogn Neurodyn., Vol. 3, No. 1, 2009 [DOI: http://dx.doi.org/10.1007/s11571-008-9064-y].   DOI
13 Liao F, Jan YK., "Using recurrence network approach to quantify nonlinear dynamics of skin blood flow in response to loading pressure.", Conf Proc IEEE Eng Med Biol Soc., Vol. 2012, pp. 4196-9, 2012 [DOI: http://dx.doi.org/10.1109/EMBC.2012.6346892].   DOI   ScienceOn
14 Benitez R, Alvarez-Lacalle E, Echebarria B, Gomis P, Vallverdu M, Caminal P.," Characterization of the nonlinear content of the heart rate dynamics during myocardial ischemia",Med Eng Phys. Vol. 31, No. 6, pp. 660-7, 2009 [DOI: http://dx.doi.org/10.1016/j.medengphy].   DOI
15 Isgum I, Prokop M, Niemeijer M, Viergever MA, van Ginneken B., "Automatic coronary calcium scoring in low-dose chest computed tomography."IEEE Trans Med Imaging. Vol. 31, No.12, pp. 2322-2334, 2012 [DOI: http://dx.doi.org/10.1109/TMI.2012.2216889].   DOI   ScienceOn
16 Lewis MJ, McNarry MA.,"Influence of age and aerobic fitness on the multifractal characteristics of electrocardiographic RR time-series.", Front Physiol., Vol. 4, No. 100, pp. 1-13, 2013 [DOI: http://dx.doi.org/10.3389/fphys].
17 Xiuqing Zheng, Zhiwu Liao, Shaoxiang Hu, Ming Li, Jiliu Zhou, "Improving Spatial Adaptivity of Nonlocal Means in Low-Dosed CT Imaging Using Pointwise Fractal Dimension", Comput Math Methods Med., Vol. 2013, No. 902143, 2013 [DOI: http://dx.doi. org/10.1155/2013/902143].   DOI
18 Peter Grassberger, Itamar Procaccia. "Measuring the Strangeness of Strange Attractors". Physica D: Nonlinear Phenomena, Vol. 9 No. 1-2, pp. 189-208, 1983 [DOI: http://dx.doi. org/10.1016/0167-2789(83)90298-1]   DOI   ScienceOn