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

  • Systems-Level Quality Improvement
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Abstract

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.

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Acknowledgments

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

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering and Architecture, Balikesir University, 10145, Cagis, Balikesir, Turkey

    Mustafa Coşkun & Ayhan Istanbullu

  2. Department of Information Systems Engineering, Faculty of Technology, Mugla Sitki Kocman University, 48000, Kotekli, Mugla, Turkey

    Hüseyin Gürüler

  3. Department of Information Technologies, Samandira Vocational and Technical School, Istanbul, Turkey

    Musa Peker

Authors
  1. Mustafa Coşkun
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  2. Hüseyin Gürüler
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  3. Ayhan Istanbullu
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  4. Musa Peker
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Correspondence to Hüseyin Gürüler.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Coşkun, M., Gürüler, H., Istanbullu, A. et al. Determining the Appropriate Amount of Anesthetic Gas Using DWT and EMD Combined with Neural Network. J Med Syst 39, 173 (2015). https://doi.org/10.1007/s10916-014-0173-3

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  • DOI: https://doi.org/10.1007/s10916-014-0173-3

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