Combrisson Etienne, Vallat Raphael, Eichenlaub Jean-Baptiste, O'Reilly Christian, Lajnef Tarek, Guillot Aymeric, Ruby Perrine M, Jerbi Karim
Département de Psychologie, Université de MontréalMontreal, QC, Canada.
Inter-University Laboratory of Human Movement Biology, Université Claude Bernard Lyon 1, Université de LyonLyon, France.
Front Neuroinform. 2017 Sep 21;11:60. doi: 10.3389/fninf.2017.00060. eCollection 2017.
We introduce Sleep, a new Python open-source graphical user interface (GUI) dedicated to visualization, scoring and analyses of sleep data. Among its most prominent features are: (1) Dynamic display of polysomnographic data, spectrogram, hypnogram and topographic maps with several customizable parameters, (2) Implementation of several automatic detection of sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM), (3) Implementation of practical signal processing tools such as re-referencing or filtering, and (4) Display of main descriptive statistics including publication-ready tables and figures. The software package supports loading and reading raw EEG data from standard file formats such as European Data Format, in addition to a range of commercial data formats. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. As a result, it is capable of efficiently handling and displaying large sleep datasets. Sleep is freely available (http://visbrain.org/sleep) and comes with sample datasets and an extensive documentation. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module.
我们推出了Sleep,这是一个全新的Python开源图形用户界面(GUI),专门用于睡眠数据的可视化、评分和分析。其最显著的特点包括:(1)动态显示多导睡眠图数据、频谱图、睡眠图和地形图,并带有多个可定制参数;(2)实现了多种睡眠特征的自动检测,如纺锤波、K复合波、慢波和快速眼动(REM);(3)实现了实用的信号处理工具,如重新参考或滤波;(4)显示主要描述性统计信息,包括可供发表的表格和图表。该软件包除了支持一系列商业数据格式外,还支持从标准文件格式(如欧洲数据格式)加载和读取原始脑电图数据。最重要的是,Sleep基于VisPy库构建,该库提供基于GPU的快速和高级可视化。因此,它能够高效地处理和显示大型睡眠数据集。Sleep可免费获取(http://visbrain.org/sleep),并附带示例数据集和详细文档。新功能将不断添加,预计开放科学社区的努力将增强该模块的功能。