DocumentCode :
139724
Title :
Superiority of high frequency hypoxic ischemic EEG signals of fetal sheep for sharp wave detection using Wavelet-Type 2 Fuzzy classifiers
Author :
Abbasi, Hasan ; Unsworth, Charles P. ; Gunn, Alistair J. ; Bennet, Laura
Author_Institution :
Dept. of Eng. Sci., Univ. of Auckland, Auckland, New Zealand
fYear :
2014
fDate :
26-30 Aug. 2014
Firstpage :
1893
Lastpage :
1896
Abstract :
There is approximately a 6-8 hour window that exists from when a hypoxic-ischemic insult occurs, in utero, before significant irreversible brain injury occurs in new born infants. The focus of our work is to determine through the electroencephalogram (EEG) if such a hypoxic-ischemic insult has occurred such that neuro-protective treatment can be sought within this period. At present, there are no defined biomarkers in the EEG that are currently being used to help classify if a hypoxic ischemia insult has occurred. However, micro-scale transients in the form of spikes, sharps and slow waves exists that could provide precursory information whether a hypoxic-ischemic insult has occurred or not. In our previous studies we have successfully automatically identified spikes with high sensitivity and selectivity in the conventional 64Hz sampled EEG. This paper details the significant advantage that can be obtained in using high frequency 1024Hz sampled EEG for sharp wave detection over the typically employed 64Hz sampled EEG. This advantage is amplified when a combination of wavelet Type-2 Fuzzy Logic System (WT-Type-2-FLS) classifiers are used to identify the sharp wave transients. By applying WT-Type-2-FLS to the 1024Hz EEG record and to the same down-sampled 64Hz EEG record we demonstrate, how the sharp wave transients detection increases significantly for high resolution 1024Hz EEG over 64Hz EEG. The WT-Type-2-FLS algorithm performance was assessed over 3 standardised time periods within the first 8 hours, post occlusion of a fetal sheep, in utero. 1024Hz EEG results demonstrate the algorithm detected sharps with overall performance rates of 85%, 92%, and 87% in the Early/Mid and Late-latent phases of injury, respectively as compared to 25%, 55% and 31% in the 64Hz EEG. These results demonstrate the power of Wavelet Type-2 Fuzzy Logic System at detecting sharp waves in 1024Hz EEG and suggest that there should be a movement toward recording high frequency EEG for analys- s of hypoxic ischemic micro-scale transients that does not occur at present.
Keywords :
electroencephalography; fuzzy logic; medical signal processing; paediatrics; signal classification; FLS algorithm; brain injury; electroencephalogram; fetal sheep; frequency 1024 Hz; frequency 64 Hz; fuzzy logic system; high frequency hypoxic ischemic EEG signals; hypoxic ischemia insult; hypoxic-ischemic insult; neuro-protective treatment; sharp wave detection; wavelet Type-2 fuzzy classifiers; Electroencephalography; Feature extraction; Fuzzy logic; Sensitivity; Transient analysis; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2014.6943980
Filename :
6943980
Link To Document :
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