Feature Parameter Optimization for Seizure Detection/Prediction
GEORGIA INST OF TECH ATLANTA
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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.
- Medicine and Medical Research