Measuring and reflecting depth of anesthesia using wavelet and power spectral density

Nguyen-Ky, Tai and Wen, Peng (Paul) and Li, Yan and Gray, Robert (2011) Measuring and reflecting depth of anesthesia using wavelet and power spectral density. IEEE Transactions on Information Technology in Biomedicine, 15 (4). pp. 630-639. ISSN 1089-7771

Abstract

This paper evaluates depth of anesthesia (DoA)monitoring using a new index. The proposed method preconditions raw EEG data using an adaptive threshold technique to remove spikes and low-frequency noise. We also propose an adaptive window length technique to adjust the length of the sliding window. The information pertinent to DoA is then extracted to develop a feature function using discrete wavelet transform and power spectral density. The evaluation demonstrates that the new index reflects the patient’s transition fromconsciousness to unconsciousness with the induction of anesthesia in real time.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version due to publisher copyright policy.
Depositing User: Dr Tai Nguyen-Ky
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Electrical, Electronic and Computer Engineering
Date Deposited: 07 Sep 2011 00:15
Last Modified: 11 Jul 2014 06:52
Uncontrolled Keywords: depth of anesthesia; EEG; eigenvector methods; wavelet transform
Fields of Research (FOR2008): 09 Engineering > 0903 Biomedical Engineering > 090304 Medical Devices
01 Mathematical Sciences > 0102 Applied Mathematics > 010202 Biological Mathematics
11 Medical and Health Sciences > 1103 Clinical Sciences > 110301 Anaesthesiology
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: doi: 10.1109/TITB.2011.2155081
URI: http://eprints.usq.edu.au/id/eprint/19594

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