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Title: Condition assessment of nonlinear processes

Abstract

There is presented a reliable technique for measuring condition change in nonlinear data such as brain waves. The nonlinear data is filtered and discretized into windowed data sets. The system dynamics within each data set is represented by a sequence of connected phase-space points, and for each data set a distribution function is derived. New metrics are introduced that evaluate the distance between distribution functions. The metrics are properly renormalized to provide robust and sensitive relative measures of condition change. As an example, these measures can be used on EEG data, to provide timely discrimination between normal, preseizure, seizure, and post-seizure states in epileptic patients. Apparatus utilizing hardware or software to perform the method and provide an indicative output is also disclosed.

Inventors:
 [1];  [2];  [3]
  1. Philadelphia, TN
  2. Athens, OH
  3. Knoxville, TN
Issue Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
OSTI Identifier:
874888
Patent Number(s):
6484132
Assignee:
Lockheed Martin Energy Research Corporation (Oak Ridge, TN)
Patent Classifications (CPCs):
A - HUMAN NECESSITIES A61 - MEDICAL OR VETERINARY SCIENCE A61B - DIAGNOSIS
DOE Contract Number:  
AC05-96OR22464
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
condition; assessment; nonlinear; processes; reliable; technique; measuring; change; data; brain; waves; filtered; discretized; windowed; sets; dynamics; set; represented; sequence; connected; phase-space; distribution; function; derived; metrics; introduced; evaluate; distance; functions; properly; renormalized; provide; robust; sensitive; measures; example; eeg; timely; discrimination; normal; preseizure; seizure; post-seizure; epileptic; patients; apparatus; utilizing; hardware; software; perform; method; indicative; output; disclosed; data set; brain wave; /702/600/

Citation Formats

Hively, Lee M, Gailey, Paul C, and Protopopescu, Vladimir A. Condition assessment of nonlinear processes. United States: N. p., 2002. Web.
Hively, Lee M, Gailey, Paul C, & Protopopescu, Vladimir A. Condition assessment of nonlinear processes. United States.
Hively, Lee M, Gailey, Paul C, and Protopopescu, Vladimir A. Tue . "Condition assessment of nonlinear processes". United States. https://www.osti.gov/servlets/purl/874888.
@article{osti_874888,
title = {Condition assessment of nonlinear processes},
author = {Hively, Lee M and Gailey, Paul C and Protopopescu, Vladimir A},
abstractNote = {There is presented a reliable technique for measuring condition change in nonlinear data such as brain waves. The nonlinear data is filtered and discretized into windowed data sets. The system dynamics within each data set is represented by a sequence of connected phase-space points, and for each data set a distribution function is derived. New metrics are introduced that evaluate the distance between distribution functions. The metrics are properly renormalized to provide robust and sensitive relative measures of condition change. As an example, these measures can be used on EEG data, to provide timely discrimination between normal, preseizure, seizure, and post-seizure states in epileptic patients. Apparatus utilizing hardware or software to perform the method and provide an indicative output is also disclosed.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2002},
month = {1}
}