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Comparison of correlation dimension and fractal dimension in estimating level of consciousness

Comparison of correlation dimension and fractal dimension in estimating level of consciousness
Comparison of correlation dimension and fractal dimension in estimating level of consciousness
This paper compares the correlation dimension (D2) ,Higuchi fractal dimension (HFD),Katz fractal dimension(KFD)and Sevcik fractal dimension(SFD) approaches in estimating Depth of Anesthesia (DOA) based on of electroencephalogram (EEG). The single-channel EEG data was captured in both ICU and operating room and different anesthetic drugs, including propofol and isoflurane were used. For better analysis, application of adaptive segmentation on EEG signal for estimating DOA is evaluated and compared to fixed segmentation. Prediction probability (PK) is used as a measure of correlation between the predictors and BIS index to evaluate the proposed methods. The results show the ability of these algorithms in predicting DOA. Also, evolving fixed and adaptive windowing methods for segmentation of EEG reveals no meaningful difference in estimate DOA.
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a
Zaghari, Bahareh
a0537db6-0dce-49a2-8103-0f4599ab5f6a

Zaghari, Bahareh (2009) Comparison of correlation dimension and fractal dimension in estimating level of consciousness. Conference on Biomedical Engineering, Iran, Islamic Republic of. 01 Oct 2009.

Record type: Conference or Workshop Item (Other)

Abstract

This paper compares the correlation dimension (D2) ,Higuchi fractal dimension (HFD),Katz fractal dimension(KFD)and Sevcik fractal dimension(SFD) approaches in estimating Depth of Anesthesia (DOA) based on of electroencephalogram (EEG). The single-channel EEG data was captured in both ICU and operating room and different anesthetic drugs, including propofol and isoflurane were used. For better analysis, application of adaptive segmentation on EEG signal for estimating DOA is evaluated and compared to fixed segmentation. Prediction probability (PK) is used as a measure of correlation between the predictors and BIS index to evaluate the proposed methods. The results show the ability of these algorithms in predicting DOA. Also, evolving fixed and adaptive windowing methods for segmentation of EEG reveals no meaningful difference in estimate DOA.

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Published date: 8 October 2009
Venue - Dates: Conference on Biomedical Engineering, Iran, Islamic Republic of, 2009-10-01 - 2009-10-01
Organisations: Dynamics Group

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Local EPrints ID: 352997
URI: https://eprints.soton.ac.uk/id/eprint/352997
PURE UUID: ac5a3fba-201a-48d6-b16a-a31533fdf89f

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Date deposited: 28 May 2013 13:27
Last modified: 18 Jul 2017 04:09

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Contributors

Author: Bahareh Zaghari

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