A computer-aided detection of EEG seizures in infants: a singular-spectrum approach and performance comparison
- 7 August 2002
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Biomedical Engineering
- Vol. 49 (5), 455-462
- https://doi.org/10.1109/10.995684
Abstract
Presents a scalp electroencephalogram (EEG) seizure detection scheme based on singular spectrum analysis (SSA) and Rissanen minimum description length (MDL) model-order selection (SSA-MDL). Preprocessing of the signals allows for the drastic reduction of the number of false alarms. Statistical performance comparison with seizure detection schemes of Gotman et al. (1997) and Liu et al. (1992) is performed on both synthetic data and real EEG seizures. Monte Carlo simulations based on synthetic infant EEG seizure data reveals some detection drawbacks on a large variety of seizure waveforms. Detection using both Monte Carlo and four real infant scalp EEG signals shows the superiority of the SSA-MDL method with an average good detection rate of >93% and false detection rate <4%.Keywords
This publication has 26 references indexed in Scilit:
- Nonlinear nonstationary Wiener model of infant EEG seizuresIEEE Transactions on Biomedical Engineering, 2002
- Time-varying statistical dimension analysis with application to newborn scalp EEG seizure signalsMedical Engineering & Physics, 2002
- Observer of autonomic cardiac outflow based on blind source separation of ECG parametersIEEE Transactions on Biomedical Engineering, 2000
- Seizure detection of newborn EEG using a model-based approachIEEE Transactions on Biomedical Engineering, 1998
- Method for single-trial readiness potential identification, based on singular spectrum analysisJournal of Neuroscience Methods, 1996
- Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity lossElectroencephalography and Clinical Neurophysiology, 1995
- Detection of neonatal seizures through computerized EEG analysisElectroencephalography and Clinical Neurophysiology, 1992
- Fractal dimension and local intrinsic dimensionPhysical Review A, 1989
- Singular-value decomposition and embedding dimensionPhysical Review A, 1987
- Detection of signals by information theoretic criteriaIEEE Transactions on Acoustics, Speech, and Signal Processing, 1985