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RIPPLELAB: A Comprehensive Application for the Detection Analysis and Classification of High Frequency Oscillations in Electroencephalographic Signals

机译：RIPPLELAB：脑电信号高频振荡的检测分析和分类的综合应用

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High Frequency Oscillations (HFOs) in the brain have been associated with different physiological and pathological processes. In epilepsy, HFOs might reflect a mechanism of epileptic phenomena, serving as a biomarker of epileptogenesis and epileptogenicity. Despite the valuable information provided by HFOs, their correct identification is a challenging task. A comprehensive application, RIPPLELAB, was developed to facilitate the analysis of HFOs. RIPPLELAB provides a wide range of tools for HFOs manual and automatic detection and visual validation; all of them are accessible from an intuitive graphical user interface. Four methods for automated detection—as well as several options for visualization and validation of detected events—were implemented and integrated in the application. Analysis of multiple files and channels is possible, and new options can be added by users. All features and capabilities implemented in RIPPLELAB for automatic detection were tested through the analysis of simulated signals and intracranial EEG recordings from epileptic patients (n = 16; 3,471 analyzed hours). Visual validation was also tested, and detected events were classified into different categories. Unlike other available software packages for EEG analysis, RIPPLELAB uniquely provides the appropriate graphical and algorithmic environment for HFOs detection (visual and automatic) and validation, in such a way that the power of elaborated detection methods are available to a wide range of users (experts and non-experts) through the use of this application. We believe that this open-source tool will facilitate and promote the collaboration between clinical and research centers working on the HFOs field. The tool is available under public license and is accessible through a dedicated web site.
机译：大脑中的高频振荡（HFO）与不同的生理和病理过程有关。在癫痫中，HFOs可能反映了癫痫现象的机制，可作为癫痫发生和致痫性的生物标记。尽管HFO提供了宝贵的信息，但正确识别它们是一项艰巨的任务。开发了一个综合应用程序RIPPLELAB，以方便对HFO进行分析。 RIPPLELAB为HFO手动和自动检测以及视觉验证提供了广泛的工具。所有这些都可以通过直观的图形用户界面访问。在应用程序中实现并集成了四种自动检测方法以及用于可视化和验证检测到的事件的几种选项。可以分析多个文件和通道，并且用户可以添加新选项。通过分析来自癫痫患者的模拟信号和颅内EEG记录，对RIPPLELAB中实现的用于自动检测的所有功能进行了测试（n = 16；分析的小时数为3,471）。还测试了视觉验证，并将检测到的事件分为不同类别。与其他可用的用于EEG分析的软件包不同，RIPPLELAB独特地为HFO检测（可视和自动）和验证提供了合适的图形和算法环境，从而使详尽的检测方法的强大功能可用于广泛的用户（专家）。和非专家）使用此应用程序。我们相信，这种开源工具将促进和促进在HFO领域工作的临床和研究中心之间的合作。该工具可在公共许可下获得，并可通过专用网站进行访问。

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