The sleep-edf database contains 197 whole-night PolySomnoGraphic sleep recordings, containing EEG, EOG, chin EMG, and event markers. Some records also contain respiration and body temperature. Corresponding hypnograms (sleep patterns) were manually scored by well-trained technicians according to the Rechtschaffen and Kales manual, and are also available.
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MaSS (Multilingual corpus of Sentence-aligned Spoken utterances) is an extension of the CMU Wilderness Multilingual Speech Dataset, a speech dataset based on recorded readings of the New Testament.
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The Montreal Archive of Sleep Studies (MASS) is an open-access and collaborative database of laboratory-based polysomnography (PSG) recordings O’Reilly, C., et al. (2014) J Seep Res, 23(6):628-635. Its goal is to provide a standard and easily accessible source of data for benchmarking the various systems developed to help the automation of sleep analysis. It also provides a readily available source of data for fast validation of experimental results and for exploratory analyses. Finally, it is a shared resource that can be used to foster large-scale collaborations in sleep studies.
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The Sleep Heart Health Study (SHHS) is a multi-center cohort study implemented by the National Heart Lung & Blood Institute to determine the cardiovascular and other consequences of sleep-disordered breathing. It tests whether sleep-related breathing is associated with an increased risk of coronary heart disease, stroke, all cause mortality, and hypertension. In all, 6,441 men and women aged 40 years and older were enrolled between November 1, 1995 and January 31, 1998 to take part in SHHS Visit 1. During exam cycle 3 (January 2001- June 2003), a second polysomnogram (SHHS Visit 2) was obtained in 3,295 of the participants. CVD Outcomes data were monitored and adjudicated by parent cohorts between baseline and 2011. More than 130 manuscripts have been published investigating predictors and outcomes of sleep disorders.
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ISRUC-Sleep is a polysomnographic (PSG) dataset. The data were obtained from human adults, including healthy subjects, and subjects with sleep disorders under the effect of sleep medication. The dataset, which is structured to support different research objectives, comprises three groups of data: (a) data concerning 100 subjects, with one recording session per subject, (b) data gathered from 8 subjects; two recording sessions were performed per subject, which are useful for studies involving changes in the PSG signals over time, (c) data collected from one recording session related to 10 healthy subjects, which are useful for studies involving comparison of healthy subjects with the patients suffering from sleep disorders.
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Data for this challenge were contributed by the Massachusetts General Hospital’s (MGH) Computational Clinical Neurophysiology Laboratory (CCNL), and the Clinical Data Animation Laboratory (CDAC). The dataset includes 1,985 subjects which were monitored at an MGH sleep laboratory for the diagnosis of sleep disorders. The data were partitioned into balanced training (n = 994), and test sets (n = 989).
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