CISUC-Centro de Informática e Sistemas da Universidade de Coimbra, Faculty of Sciences and Technology, University of Coimbra, 3030-290 Coimbra, Portugal.
J Neurosci Methods. 2011 Sep 15;200(2):257-71. doi: 10.1016/j.jneumeth.2011.07.002. Epub 2011 Jul 7.
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.
一个基于 Matlab®的软件包 EPILAB 被开发出来，用于支持研究人员进行癫痫发作预测的研究。它提供了一个直观和方便的图形用户界面。实现了癫痫发作预测研究中至关重要的基本概念。例如，在长期连续记录中开发和统计验证预测方法。癫痫发作预测通常基于脑电图 (EEG) 和心电图 (ECG) 信号。EPILAB 能够处理以不同格式存储的 EEG 和 ECG 数据。可以基于单变量和多变量数据分析提取超过 35 个时频域测量值（特征）。这些特征可以进行后处理，并用于预测目的。预测可以基于优化的阈值进行，也可以应用分类方法，如人工神经网络、细胞神经网络和支持向量机。EPILAB 被证明是一种有效的癫痫发作预测工具，旨在成为一种在癫痫发作预测社区中进行交流、评估和比较结果和数据的方式。
