Nonlinear dynamical seizure prediction and detection

Information

  • Research Project
  • 6442117
  • ApplicationId
    6442117
  • Core Project Number
    R43NS043100
  • Full Project Number
    1R43NS043100-01
  • Serial Number
    43100
  • FOA Number
    PA-00-18
  • Sub Project Id
  • Project Start Date
    4/1/2002 - 22 years ago
  • Project End Date
    9/30/2003 - 21 years ago
  • Program Officer Name
    SWAIN, AMY L
  • Budget Start Date
    4/1/2002 - 22 years ago
  • Budget End Date
    9/30/2003 - 21 years ago
  • Fiscal Year
    2002
  • Support Year
    1
  • Suffix
  • Award Notice Date
    3/27/2002 - 22 years ago

Nonlinear dynamical seizure prediction and detection

DESCRIPTION (provided by applicant): Techniques from nonlinear dynamics are potentially valuable for prediction of epileptic seizures based on preliminary results with reported prediction times of up to several minutes before electrographic onset. These results must be validated using a database containing more subjects and longer time series with more than one seizure per series in order to establish their predictive sensitivity and specificity. Moreover, criteria for prospective inference must be developed at the same time as computational efficiency is improved, in order to be usable in real time. FHS, with proven expertise in epileptic signal analysis and a database containing over 2000 hours of ECoG recordings from 20 subjects with over 100 seizures, is ideally suited for this task. The end product of this proposed research will be a user-friendly software package for the detection, prediction, and quantification of epileptic seizures for use in a portable device or in diagnostic equipment. The introduction of this software will advance the field scientifically, clinically, and commercially. In Phase I, we will demonstrate proof of principle for this concept, assessing the value of the measures for the task of seizure prediction and detection, and quantifying their sensitivity to amplitude and frequency changes. PROPOSED COMMERCIAL APPLICATION: NOT AVAILABLE

IC Name
NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
  • Activity
    R43
  • Administering IC
    NS
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    97668
  • Sub Project Total Cost
  • ARRA Funded
  • CFDA Code
    853
  • Ed Inst. Type
  • Funding ICs
    NINDS:97668\
  • Funding Mechanism
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    FLINT HILLS SCIENTIFIC, LLC
  • Organization Department
  • Organization DUNS
  • Organization City
    LAWRENCE
  • Organization State
    KS
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    66049
  • Organization District
    UNITED STATES