Depth of anaesthesia assessment using interval second-order difference plot and permutation entropy techniques

Li, Tianning and Wen, Peng (2017) Depth of anaesthesia assessment using interval second-order difference plot and permutation entropy techniques. IET Signal Processing, 11 (2). pp. 221-227. ISSN 1751-9675

Abstract

This study presents a new method to apply the interval second-order difference plot (ISODP) and interval permutation entropy (IPE) techniques to assess the depth of anaesthesia (DoA). First, the denoised electroencephalograph signals are decomposed into 13 different frequency bands. The second-order difference plot (SODP) and permutation entropy (PE) values of each frequency band are calculated. The SODP and PE values of high-frequency bands (21.5-47 Hz) show the highest linear relationship with the anaesthesia states, therefore they are selected to form the parameter set. Then the SODP and PE parameters are fine tuned using the interval feature technique. Finally, a new index is designed using the ISODP and IPE. The new index is evaluated and compared with measured bispectral (BIS). The results show that there is a very close correlation
between the proposed index and the BIS during different anaesthetic states. The new index also shows an earlier time response (3.1–59.7 s) than BIS during the change of anaesthetic states. In addition, the proposed index is able to continuously assess the DoA of patients when the quality of signal is poor and the BIS does not have any valid outputs.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Date Deposited: 13 Feb 2017 05:26
Last Modified: 19 Dec 2017 05:17
Uncontrolled Keywords: depth of anesthesia (DoA), second order different plot (SODP), Permutation entropy, Interval feature method
Fields of Research : 08 Information and Computing Sciences > 0899 Other Information and Computing Sciences > 089999 Information and Computing Sciences not elsewhere classified
09 Engineering > 0903 Biomedical Engineering > 090399 Biomedical Engineering not elsewhere classified
09 Engineering > 0903 Biomedical Engineering > 090303 Biomedical Instrumentation
Identification Number or DOI: 10.1049/iet-spr.2015.0114
URI: http://eprints.usq.edu.au/id/eprint/30048

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