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Technique to Detect the Onset of Epileptic Seizures

標題: Optimization of Spatiio-Temporal Patterns Processing for Seizure Warning and Prediction

詳細技術說明: None

*Abstract

Identifies Pattern Changes in Time Series to Predict Epilepsy, Sleep Disorders, and Even Weather Forecasts

This exciting technology predicts epileptic seizures. Approximately 2.8 million people in the United States suffer from epilepsy, with an estimated 300,000 new cases diagnosed each year. If untreated, an individual with epilepsy is likely to experience repeated seizures, which typically involve loss of consciousness. The ability to detect an epileptic seizure allows doctors to more effectively treat epilepsy patients by providing preventive treatment. Our researchers have developed a technique to identify brain patterns that predict epilepticseizures before they occur.

Applications

Predicting the onset of epileptic seizures
Analyzing data in multidimensional systems such as stock markets, weather forecasts,and manufacturing processes

Advantages

Provides effective seizure warning and prediction not available through traditional signal processing techniques, offering a competitive advantage
Allows doctors to deliver treatment prior to onset to prevent seizures
Non-invasive therapy which does not require the removal of hippocampus or cerebralcortex in the brain significantly increasing potential patient population
Provides broad potential market application since the technology can be used invarious industries, from financial market analysis to geological predictions

Technology

Epileptic seizures can be predicted based on spatiotemporal dynamics in brain patterns of patients with epilepsy. There is a temporal transition before a seizure occurs at certain critical sites in the brain. Our researchers have developed a technique to analyze brain behavior at these critical sites in order to detect an impending epileptic seizure. The technique identifies spatiotemporal patterns in EEG time series that characterize the onset of a seizure. This is the first time that spatiotemporal analysis has been used for epileptic seizure detection. These analysis and prediction techniques can be applied to other systems which are based on dynamic time series.

*IP Issue Date: Dec 2, 2008

*Principal Investigation: Name: Panagote Pardalos
Department:

Name: Deng-Shan Shiau
Department:

Name: James Sackellares
Department:

Name: Leonidas Iasemidis
Department:

Name: Wanpracha Chaovalitwongse
Department:

附加資料: Inventor: Chaovalitwongse, Wanpracha A. | Iasemidis, Leonidas D. | Pardalos, Panos M. | Sackellares, James C. | Shiau, Deng-Shan
Priority Number: US7461045B1
IPC Current: G06F000944 | G06N000702 | G06N000706
US Class: 706052
Assignee Applicant: University of Florida Research Foundation Inc.inesville | Arizona Board of Regents,Scottsdale
Title: Optimization of spatio-temporal pattern processing for seizure warning and prediction
Usefulness: Optimization of spatio-temporal pattern processing for seizure warning and prediction
Summary: Computer-implemented method for predicting an impending seizure caused by epilepsy e.g. temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE), of a patient.
Novelty: Computer-implemented impending seizure predicting method for patient, involves storing identified data components, and predicting impending seizure based on identified data components

主要類別: 生物醫學

細分類別: 復康

申請日期: Aug 18, 2004

申請號碼: 7,461,045

其他

國家/地區: 美國

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