• 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