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Real-time seizure prediction from local field potentials using an adaptive Wiener algorithm.

P Rajdev1, M P Ward, J Rickus

  • 1Department of Biomedical Engineering, Purdue University, West Lafayette, IN, USA. poojarajdev@yahoo.com

Computers in Biology and Medicine
|December 22, 2009
PubMed
Summary
This summary is machine-generated.

A new adaptive Wiener prediction algorithm for epilepsy seizure detection shows promise for responsive neurostimulation. This real-time system offers improved sensitivity and a low false positive rate for predicting seizures before they occur.

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Epilepsy affects millions, with 30% experiencing refractory seizures unresponsive to medication.
  • Current treatments for refractory epilepsy have limitations in efficacy.
  • Responsive neurostimulation offers a potential alternative for seizure control.

Purpose of the Study:

  • To present a real-time adaptive Wiener prediction algorithm for seizure detection using local field potential (LFP) recordings.
  • To implement this algorithm on a digital signal processor for a portable, hand-held device.
  • To evaluate the algorithm's performance against statistical prediction methods.

Main Methods:

  • Developed a real-time adaptive Wiener prediction algorithm utilizing local field potential (LFP) data.
  • Implemented the algorithm on a Texas Instruments C6713 digital signal processor for real-time application.
  • Compared the Wiener algorithm's predictive accuracy against two naive statistical prediction algorithms using ROC curves and other metrics.

Main Results:

  • Offline analysis in rats predicted seizures 27 seconds before onset with 94% sensitivity and a 0.009 min(-1) false positive rate.
  • Real-time implementation predicted seizures 6.7 seconds before onset with 92% sensitivity and a 0.08 min(-1) false positive rate.
  • The Wiener algorithm demonstrated favorable sensitivity and false positive rates compared to similar studies.

Conclusions:

  • The real-time adaptive Wiener prediction algorithm is effective for early seizure detection.
  • Hardware implementation enables a miniaturized, portable system for responsive neurostimulation.
  • This technology holds potential for improving seizure management in patients with refractory epilepsy.