A novel empirical wavelet SODP and spectral entropy based index for assessing the depth of anaesthesia

Schmierer, Thomas and Li, Tianning ORCID: https://orcid.org/0000-0001-5142-8654 and Li, Yan ORCID: https://orcid.org/0000-0002-4694-4926 (2022) A novel empirical wavelet SODP and spectral entropy based index for assessing the depth of anaesthesia. Health Information Science and Systems, 10 (1):10. pp. 1-14.

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Abstract

The requirement for anaesthesia during modern surgical procedures is unquestionable to ensure a safe experience for patients with successful recovery. Assessment of the depth of anaesthesia (DoA) is an important and ongoing field of research to ensure patient stability during and post-surgery. This research addresses the limitations of current DoA indexes by developing a new index based on electroencephalography (EEG) signal analysis. Empirical wavelet transformation (EWT) methods are employed to extract wavelet coefficients before statistical analysis. The features Spectral Entropy and Second Order Difference Plot are extracted from the wavelet coefficients. These features are used to train a new index, SSEDoA, utilising a Support Vector Machine (SVM) with a linear kernel function. The new index accurately assesses the DoA to illustrate the transition between different anaesthetic stages. Testing was undertaken with nine patients and an additional four patients with low signal quality. Across the nine patients we tested, an average correlation of 0.834 was observed with the Bispectral (BIS) index. The analysis of the DoA stage transition exhibited a Choen's Kappa of 0.809, indicative of a high agreement.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Mathematics, Physics and Computing (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Mathematics, Physics and Computing (1 Jan 2022 -)
Date Deposited: 11 Jul 2022 05:20
Last Modified: 17 Oct 2022 01:08
Uncontrolled Keywords: Depth of anaesthesia; Statistical model; Empirical wavelet transform; Second order difference plot
Fields of Research (2020): 42 HEALTH SCIENCES > 4203 Health services and systems > 420311 Health systems
Identification Number or DOI: https://doi.org/10.1007/s13755-022-00178-8
URI: http://eprints.usq.edu.au/id/eprint/49450

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