Monitoring of global cerebral ischemia using wavelet entropy rate of change

In this paper, the subband wavelet entropy (SWE) and its time difference are proposed as two quantitative measures for analyzing and segmenting the electroencephalographic (EEG) signals. SWE for EEG subbands, namely Delta, Theta, Alpha, Beta, and Gamma, is calculated and segmented using wavelet anal...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2005-12, Vol.52 (12), p.2119-2122
Main Authors: Al-Nashash, H.A., Thakor, N.V.
Format: Article
Language:English
Subjects:
Algorithms
Animals
Brain injuries
Brain Ischemia - diagnosis
Brain Ischemia - physiopathology
Cardiac arrest
Computer Simulation
Diagnosis, Computer-Assisted - methods
Electroencephalography
Electroencephalography - methods
Entropy
Ischemic pain
Models, Neurological
Monitoring
Rats
Rodents
Signal analysis
Signal Processing, Computer-Assisted
Time measurement
Wavelet analysis
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Summary:In this paper, the subband wavelet entropy (SWE) and its time difference are proposed as two quantitative measures for analyzing and segmenting the electroencephalographic (EEG) signals. SWE for EEG subbands, namely Delta, Theta, Alpha, Beta, and Gamma, is calculated and segmented using wavelet analysis. In addition, a time difference entropy measure was calculated because it does not require a baseline and equals to zero in all clinical bands as the initial condition. Visual and quantitative results were obtained from 11 rodents that were subjected to 3, 5, and 7 min of global ischemic brain injury by asphyxic cardiac arrest. We found that the time difference of SWE is capable of amplifying the variations between clinical bands during the various stages of the recovery process and may serve as a novel analytical approach to grade and classify brain rhythms during global ischemic brain injury and recovery.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2005.857634