TY - JOUR
T1 - EPILAB
T2 - A software package for studies on the prediction of epileptic seizures
AU - Teixeira, C. A.
AU - Direito, B.
AU - Feldwisch-Drentrup, H.
AU - Valderrama, M.
AU - Costa, R. P.
AU - Alvarado-Rojas, C.
AU - Nikolopoulos, S.
AU - Le Van Quyen, M.
AU - Timmer, J.
AU - Schelter, B.
AU - Dourado, A.
N1 - Funding Information:
EPILAB is a product of European FP7 EPILEPSIAE Project Grant 211713. The authors express their gratitude to the funding by the European Union. HFD, JT, and BS were also supported by the German Science Foundation (Ti315/4-2) and the Excellence Initiative of the German Federal and State Governments. BS is indebted to the Baden-Wuerttemberg Stiftung for the financial support of this research project by the Eliteprogramme for Postdocs.
PY - 2011/9/15
Y1 - 2011/9/15
N2 - A Matlab ®-based software package, EPILAB, was developed for supporting researchers in performing studies on the prediction of epileptic seizures. It provides an intuitive and convenient graphical user interface. Fundamental concepts that are crucial for epileptic seizure prediction studies were implemented. This includes, for example, the development and statistical validation of prediction methodologies in long-term continuous recordings.Seizure prediction is usually based on electroencephalography (EEG) and electrocardiography (ECG) signals. EPILAB is able to process both EEG and ECG data stored in different formats. More than 35 time and frequency domain measures (features) can be extracted based on univariate and multivariate data analysis. These features can be post-processed and used for prediction purposes. The predictions may be conducted based on optimized thresholds or by applying classifications methods such as artificial neural networks, cellular neuronal networks, and support vector machines.EPILAB proved to be an efficient tool for seizure prediction, and aims to be a way to communicate, evaluate, and compare results and data among the seizure prediction community.
AB - A Matlab ®-based software package, EPILAB, was developed for supporting researchers in performing studies on the prediction of epileptic seizures. It provides an intuitive and convenient graphical user interface. Fundamental concepts that are crucial for epileptic seizure prediction studies were implemented. This includes, for example, the development and statistical validation of prediction methodologies in long-term continuous recordings.Seizure prediction is usually based on electroencephalography (EEG) and electrocardiography (ECG) signals. EPILAB is able to process both EEG and ECG data stored in different formats. More than 35 time and frequency domain measures (features) can be extracted based on univariate and multivariate data analysis. These features can be post-processed and used for prediction purposes. The predictions may be conducted based on optimized thresholds or by applying classifications methods such as artificial neural networks, cellular neuronal networks, and support vector machines.EPILAB proved to be an efficient tool for seizure prediction, and aims to be a way to communicate, evaluate, and compare results and data among the seizure prediction community.
KW - Artificial neural networks
KW - EEG/ECG processing
KW - Epilepsy
KW - Seizure prediction
KW - Seizure prediction characteristic
KW - Support vector machines
UR - https://www.scopus.com/pages/publications/80051595499
U2 - 10.1016/j.jneumeth.2011.07.002
DO - 10.1016/j.jneumeth.2011.07.002
M3 - Article
C2 - 21763347
AN - SCOPUS:80051595499
SN - 0165-0270
VL - 200
SP - 257
EP - 271
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
IS - 2
ER -