Accession Number:

ADA409937

Title:

Feature Parameter Optimization for Seizure Detection/Prediction

Descriptive Note:

Conference paper

Corporate Author:

GEORGIA INST OF TECH ATLANTA

Report Date:

2001-10-25

Pagination or Media Count:

6.0

Abstract:

When dealing with seizure detectionprediction problems, there are three main performance metrics that must be optimized false positive rate, false negative rate, detection delay or, if the problem is seizure prediction, it is desirable to obtain the greatest prediction time achievable. Tuning specific extracted features to individual patients can lead to improved results. The processing window length is also an important parameter whose optimization may significantly affect performance. In this study we propose an approach for selecting the window length for the particular detectionprediction problem. This approach is applicable to other feature parameters suitable for tuning or optimization.

Subject Categories:

  • Medicine and Medical Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE