DocumentCode
803129
Title
Analog seizure detection and performance evaluation
Author
Bhavaraju, Naresh C. ; Frei, Mark G. ; Osorio, Ivan
Author_Institution
Flint Hills Sci., Lawrence, KS, USA
Volume
53
Issue
2
fYear
2006
Firstpage
238
Lastpage
245
Abstract
Epilepsy is the most prevalent neurological disorder affecting both adults and children. Over two-and-one-half million individuals in the United States have epilepsy and 25% of them do not respond to drugs. A significant focus of current research efforts is the development of a fully implantable device for real-time seizure detection and automated warning and blockage of seizures. The purpose of this paper is to describe and demonstrate the feasibility of incorporating a novel tool, the percentile tracking filter into a successful, validated seizure detection algorithm to create an analog seizure detection device. We demonstrate, in a small-scale study, that the performance of this analog implementation is statistically similar to a digital implementation of a previously described and successfully validated seizure digital algorithm. This analog implementation can be realized into an application specific integrated circuit that is suitable for a fully implantable device for seizure monitoring, warning and treatment, which is likely to consume very little power, a feature of practical value.
Keywords
bioelectric phenomena; diseases; medical signal detection; medical signal processing; neurophysiology; tracking filters; analog seizure detection; automated seizure warning; epilepsy; fully implantable device; neurological disorder; percentile tracking filter; seizure blockage; Application specific integrated circuits; Computerized monitoring; Costs; Detection algorithms; Drugs; Electrical stimulation; Epilepsy; Filters; Medical treatment; Patient monitoring; ASIC; Analog; detection; low-power, median-filter; seizure; Algorithms; Analog-Digital Conversion; Diagnosis, Computer-Assisted; Electroencephalography; Epilepsy; Equipment Design; Equipment Failure Analysis; Feasibility Studies; Humans; Pattern Recognition, Automated; Reproducibility of Results; Retrospective Studies; Seizures; Sensitivity and Specificity;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2005.862532
Filename
1580829
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