Abstract
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.
Highlights
Polysomnography provides a comprehensive recording of the major physiological changes associated with sleep and is the gold standard for modern sleep analysis, both in research and clinical settings
We developed Sleep, an intuitive and efficient open-source graphical user interface (GUI) dedicated to the visualization of polysomnographic recordings and scoring of sleep stages
We developed Sleep on top of VisPy4 (Campagnola et al, 2015), a Python scientific library based on OpenGL which offloads graphics rendering to the graphics processing unit (GPU) in order to provide fast and high-quality visualization, even under heavy loads as is the case with large dataset
Summary
Polysomnography provides a comprehensive recording of the major physiological changes associated with sleep and is the gold standard for modern sleep analysis, both in research and clinical settings. Automatic sleep scoring has the advantage of being fast, reproducible and with generally good agreement with visual scoring (Berthomier et al, 2007; Lajnef et al, 2015a), yet its usage is far from being widespread and most sleep laboratories still rely on visual scoring, using either commercial softwares or in-house packages. In many cases, these software tools come with their own data and hypnogram file formats, and this heterogeneity can represent a substantial obstacle for sharing of sleep data across laboratories or clinics. Some of the very few existing open sources graphical user interface (GUI) for reading and scoring sleep include Phypno, written in Python, and the MATLAB-based toolboxes sleepSMG2 or SpiSOP3
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