Automatic seizure detection in SEEG using high frequency activities in wavelet domain.
L Ayoubian1, H Lacoma, J Gotman
1Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada. leilayou_54@yahoo.com
Medical Engineering & Physics
|June 1, 2012
Summary
This study introduces a novel seizure detection system using high-frequency electroencephalography (EEG) activity. The system shows potential for clinical use by detecting epileptic seizures with significant high-frequency contributions.
Area of Science:
- Neurology
- Biomedical Engineering
- Signal Processing
Background:
- Current automatic seizure detection methods have limitations in specificity and speed.
- High-frequency (80-500 Hz) activity in intracranial EEG is prominent in epilepsy but underutilized for detection.
Purpose of the Study:
- To evaluate the contribution of high-frequency EEG activity to epileptic seizure detection.
- To develop and assess a novel seizure detection system incorporating these frequencies.
Main Methods:
- Utilized 30 hours of intracranial EEG data from 15 patients with 15 seizures for training.
- Employed wavelet decomposition, feature extraction, adaptive thresholding, and artifact removal.
- Developed an EMG removal algorithm based on frequency band correlation and energy spread.
Main Results:
- Tested on 36 hours of intracranial EEG data with 18 seizures.
- Achieved 72% sensitivity, 0.7 false detections per hour, and a median delay of 5.7 seconds.
- Missed seizures were associated with subtle high frequencies or EMG removal; false detections stemmed from EMG or interictal activity.
Conclusions:
- The developed system demonstrates sufficient performance for potential clinical application.
- High-frequency EEG activity can significantly enhance the detection of epileptic seizures.
- The system's performance is promising despite using frequencies typically outside routine clinical interpretation.
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