TY - GEN
T1 - Automatic detection of high frequency epileptiform oscillations from intracranial EEG recordings of patients with neocortical epilepsy
AU - Smart, O. L.
AU - Worrell, G. A.
AU - Vachtsevanos, G. J.
AU - Litt, B.
PY - 2005
Y1 - 2005
N2 - High frequency epileptiform oscillations (HFEOs) have been observed before neocortical seizures on intracranial EEG recordings. There is suggestion that HFEOs may localize epileptic brain regions important to seizure generation in humans, a finding that would be valuable for understanding, diagnosing, and treating epilepsy. In this paper, an automated approach for detecting HFEOs is described. Fuzzy clustering and histograms are used to characterize HFEO events. Compared to neurologist markings, the algorithm detected 87 % of the HFEOs while achieving 68% precision and 90% specificity, without training. Applied to thirty-five minute seizure records obtained from six patients, spatial and temporal localization of HFEOs were observed in 77% and 61% of the segments respectively. Results highlight the potential of the method to identify brain regions vital to seizure generation by tracking the spatio-temporal evolution of high frequency seizure precursors in the epileptic network.
AB - High frequency epileptiform oscillations (HFEOs) have been observed before neocortical seizures on intracranial EEG recordings. There is suggestion that HFEOs may localize epileptic brain regions important to seizure generation in humans, a finding that would be valuable for understanding, diagnosing, and treating epilepsy. In this paper, an automated approach for detecting HFEOs is described. Fuzzy clustering and histograms are used to characterize HFEO events. Compared to neurologist markings, the algorithm detected 87 % of the HFEOs while achieving 68% precision and 90% specificity, without training. Applied to thirty-five minute seizure records obtained from six patients, spatial and temporal localization of HFEOs were observed in 77% and 61% of the segments respectively. Results highlight the potential of the method to identify brain regions vital to seizure generation by tracking the spatio-temporal evolution of high frequency seizure precursors in the epileptic network.
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M3 - Conference contribution
AN - SCOPUS:33847761078
SN - 0780388984
SN - 9780780388987
T3 - 2005 IEEE Region 5 and IEEE Denver Section Technical, Professional and Student Development Workshop
SP - 53
EP - 58
BT - 2005 IEEE Region 5 and IEEE Denver Section Technical, Professional and Student Development Workshop
T2 - 2005 IEEE Region 5 and IEEE Denver Section Technical, Professional and Student Development Workshop
Y2 - 7 April 2005 through 8 April 2005
ER -