8/7/2023 0 Comments Python sleepBy contrast, 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. Apart from being time-consuming, visual sleep scoring is subject to both inter and intra-rater variability and is thus far from being optimal. It results in a hypnogram which represents the succession of sleep stages across time. Sleep staging is generally done visually by inspecting consecutive polysomnographic segments of 30 s. In humans, a normal night of sleep consists of a repetition of four or five cycles in which sleep stages tend to follow each other in a particular order. This nomenclature was updated in 2007 by the American Academy of Sleep Medicine ( Iber et al., 2007) and sleep stage 3 and 4 have been merged into stage N3. A first set of rules were published by Rechtschaffen and Kales (1968) and proposed to divide sleep into 5 stages with distinct electrophysiological properties, named rapid-eye movement (REM) and non-REM (NREM) stages 1, 2, 3, 4. At its simplest, it consists of monitoring at least 2 electroencephalogram (EEG), an electro-oculogram (EOG), and a submental electromyogram (EMG), providing sufficient information to identify sleep stages (sleep scoring) according to standard international established guidelines. Polysomnography provides a comprehensive recording of the major physiological changes associated with sleep and is hence the gold standard for modern sleep analysis, both in research and clinical settings. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module. Sleep is freely available ( ) and comes with sample datasets and an extensive documentation. As a result, it is capable of efficiently handling and displaying large sleep datasets. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. 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. 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. We introduce Sleep, a new Python open-source graphical user interface (GUI) dedicated to visualization, scoring and analyses of sleep data. 6Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, Montreal, QC, Canada.5Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.4Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.3Lyon Neuroscience Research Center, Brain Dynamics and Cognition team, INSERM UMRS 1028, CNRS UMR 5292, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France.2Inter-University Laboratory of Human Movement Biology, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France.1Département de Psychologie, Université de Montréal, Montreal, QC, Canada.Etienne Combrisson 1,2 * †, Raphael Vallat 3 * †, Jean-Baptiste Eichenlaub 4, Christian O'Reilly 5, Tarek Lajnef 1,6, Aymeric Guillot 2, Perrine M.
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