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Investigation of data-driven optical neuromonitoring approach during general anesthesia with sevoflurane
Author(s): Gabriela Hernandez-Meza; Meltem Izzetoglu; Ahmet Sacan; Michael Green; Kurtulus Izzetoglu
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Paper Abstract

Anesthesia monitoring currently needs a reliable method to evaluate the effects of the anesthetics on its primary target, the brain. This study focuses on investigating the clinical usability of a functional near-infrared spectroscopy (fNIRS)-derived machine learning classifier to perform automated and real-time classification of maintenance and emergence states during sevoflurane anesthesia. For 19 surgical procedures, we examine the entire continuum of the maintenance–transition–emergence phases and evaluate the predictive capability of a support vector machine (SVM) classifier during these phases. We demonstrate the robustness of the predictions made by the SVM classifier and compare its performance with that of minimum alveolar concentration (MAC) and bispectral (BIS) index-based predictions. The fNIRS-SVM investigated in this study provides evidence to the usability of the fNIRS signal for anesthesia monitoring. The method presented enables classification of the signal as maintenance or emergence automatically as well as in real-time with high accuracy, sensitivity, and specificity. The features local mean HbTotal, std HbO2, local min Hb and HbO2, and range Hb and HbO2 were found to be robust biomarkers of this binary classification task. Furthermore, fNIRS-SVM was capable of identifying emergence before movement in a larger number of patients than BIS and MAC.

Paper Details

Date Published: 19 August 2017
PDF: 10 pages
Neurophoton. 4(4) 041408 doi: 10.1117/1.NPh.4.4.041408
Published in: Neurophotonics Volume 4, Issue 4
Show Author Affiliations
Gabriela Hernandez-Meza, Drexel Univ. (United States)
Meltem Izzetoglu, Drexel Univ. (United States)
Ahmet Sacan, Drexel Univ. (United States)
Michael Green, Drexel Univ. College of Medicine (United States)
Hahnemann Univ. Hospital (United States)
Kurtulus Izzetoglu, Drexel Univ. (United States)

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