Abstract
An automatic alarm system for detecting epileptic seizure onsets could be of great assistance to patients and medical staff. A novel approach is proposed using the Matching Pursuit algorithm as a feature extractor combined with the Support Vector Machine (SVM) as a classifier for this purpose. The combination of Matching Pursuit and SVM for automatic seizure detection has never been tested before, making this a pilot study. Data from red different patients with 6 to 49 seizures are used to test our model. Three patients are recorded with scalp electroencephalography (sEEG) and three with intracranial electroencephalography (iEEG). A sensitivity of 78-100% and a detection latency of 5-18s has been achieved, while holding the false detection at 0.16-5.31/h. Our results show the potential of Matching Pursuit as a feature extractor for detection of epileptic seizures.
| Original language | English |
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| Journal | I E E E Engineering in Medicine and Biology Society. Conference Proceedings |
| Volume | 2010 |
| Pages (from-to) | 3277-80 |
| Number of pages | 4 |
| ISSN | 2375-7477 |
| DOIs | |
| Publication status | Published - 31 Aug 2010 |
| Event | Annual International Conference of the IEEE 2010: Engineering in Medicine and Biology Society (EMBC) - Buenos Aires, Argentina Duration: 31 Aug 2010 → 4 Sept 2010 |
Conference
| Conference | Annual International Conference of the IEEE 2010 |
|---|---|
| Country/Territory | Argentina |
| City | Buenos Aires |
| Period | 31/08/2010 → 04/09/2010 |
Keywords
- Adult
- Algorithms
- Artificial Intelligence
- Case-Control Studies
- Child
- Diagnosis, Computer-Assisted
- Electroencephalography
- Epilepsy
- Female
- Humans
- Male
- Middle Aged
- Pattern Recognition, Automated
- Reproducibility of Results
- Sensitivity and Specificity
- Young Adult