Journal of Medical Systems

, 39:173 | Cite as

Determining the Appropriate Amount of Anesthetic Gas Using DWT and EMD Combined with Neural Network

  • Mustafa Coşkun
  • Hüseyin Gürüler
  • Ayhan Istanbullu
  • Musa Peker
Systems-Level Quality Improvement
Part of the following topical collections:
  1. Systems-Level Quality Improvement


The spectrum of EEG has been studied to predict the depth of anesthesia using variety of signal processing methods up to date. Those standard models have used the full spectrum of EEG signals together with the systolic-diastolic pressure and pulse values. As it is generally agreed today that the brain is in stable state and the delta-theta bands of the EEG spectrum remain active during anesthesia. Considering this background, two questions that motivates this paper. First, determining the amount of gas to be administered is whether feasable from the spectrum of EEG during the maintenance stage of surgical operations. Second, more specifically, the delta-theta bands of the EEG spectrum are whether sufficient alone for this aim. This research aims to answer these two questions together. Discrete wavelet transformation (DWT) and empirical mode decomposition (EMD) were applied to the EEG signals to extract delta-theta bands. The power density spectrum (PSD) values of target bands were presented as inputs to multi-layer perceptron (MLP) neural network (NN), which predicted the gas level. The present study has practical implications in terms of using less data, in an effective way and also saves time as well.


Anesthesia Estimating anesthetic gas level Artificial intelligence Discrete wavelet transform Empirical mode decomposition 



We would like to thank Dr. Mustafa Tosun for supplying the patient data.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Mustafa Coşkun
    • 1
  • Hüseyin Gürüler
    • 2
  • Ayhan Istanbullu
    • 1
  • Musa Peker
    • 3
  1. 1.Department of Computer Engineering, Faculty of Engineering and ArchitectureBalikesir UniversityCagisTurkey
  2. 2.Department of Information Systems Engineering, Faculty of TechnologyMugla Sitki Kocman UniversityKotekliTurkey
  3. 3.Department of Information TechnologiesSamandira Vocational and Technical SchoolIstanbulTurkey

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