Document Detail


Detection of epileptic seizures in scalp electroencephalogram: an automated real-time wavelet-based approach.
MedLine Citation:
PMID:  22353980     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
SUMMARY: This study evaluates a new automated patient-specific method for epileptic seizure detection using scalp electroencephalogram (EEG). The method relies on a normalized wavelet-based index, named the combined seizure index (CSI), and requires a seizure example and a nonseizure EEG interval as reference. The CSI is derived for every epoch in each EEG channel and is sensitive to both the rhythmicity and relative energy of that epoch and the consistency of EEG patterns among different channels. Increasing significantly as seizures occur, the CSI is monitored using a one-sided cumulative sum test to generate appropriate alarms in each channel. A seizure alarm is finally generated according to channel-based information. The proposed method was evaluated using the scalp EEG test data of approximately 236 hours from 26 patients with a total of 79 focal seizures, achieving a high sensitivity of approximately 91% with a false detection rate of 0.33 per hour and a median detection latency of 7 seconds. In addition, statistical analysis revealed that the average CSI around the onset on the side of the focus in patients with temporal lobe epilepsy (TLE) is significantly greater than that of the opposite side (P < 0.001), indicating the capability of this index in lateralizing the seizure focus in this type of epilepsy.
Authors:
Ali Shahidi Zandi; Guy A Dumont; Manouchehr Javidan; Reza Tafreshi
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society     Volume:  29     ISSN:  1537-1603     ISO Abbreviation:  J Clin Neurophysiol     Publication Date:  2012 Feb 
Date Detail:
Created Date:  2012-02-22     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8506708     Medline TA:  J Clin Neurophysiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1-16     Citation Subset:  IM    
Affiliation:
*Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada †Neurophysiology Laboratory, Vancouver General Hospital and Division of Neurology, Department of Medicine, The University of British Columbia, Vancouver, BC, Canada ‡Mechanical Engineering Program, Texas A&M University at Qatar, Doha, Qatar.
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