Dataset: GR-OXMSTR-N10N11 Oximetry/heartrate and brain strokes Greece, Nov.2010 - Nov.2011 Release Notes Copyright (c) 2016 by Harris V. Georgiou ======================================================== Release: Jul 30, 2016 - Version: 1.1a - Format: .xls/.txt/.mat ======================================================== This file contains important information about the current version of the dataset package. Downloading and using this material hints that you accept the EULA/Terms-of-Use (please read carefully). We welcome your comments and suggestions. _______________________________________________ WHAT'S IN THIS PACKAGE? - Overview - Available file formats - Files and Datasets - License Agreement _______________________________________________ OVERVIEW Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a common disorder, in which upper airway resistance is increased during sleep due to upper airway dilator muscle relaxation and airway narrowing. It is a common disorder and a recognized public health problem, affecting roughly 2-4% of adult male and 1-2% adult female population. It is still under-diagnosed and believed to be linked with severe cardiovascular diseases, including hypertension, chronic fatigue, metabolic disorders, daytime sleepiness, etc. Additionally, recent studies in neurophysiology link brain strokes with some abnormal variances and change of patterns in oxygene saturation (SpO2) in the blood, due to (possible) damage in the brain, especially in the stem. This package contains two sets of data including real heart rate and SpO2 measurements throughout multiple timezones (awake or asleep) for a total of 118+55 unique patients of normal, stroke, and stem stroke classes. The data are of complete-signal registration in full resolution, so that it can be used for thorough signal processing (e.g. spectral analysis), feature extraction and classification for computer-aided diagnosis (CAD). The sources of the datasets were created in collaboration with the people of Acute Stroke Unit, Dept of Neurology, Eginition, School of Medicine, National Kapodistrian University of Athens (NKUA/UoA), Greece. These datasets have already been used in various publications describing OSAHS characterization. Detailed description and related conclusions can be found at: * Harris V. Georgiou, "Adaptive detection and severity level characterization algorithm for Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) via oximetry signal analysis" (28-Aug-2013) -- https://arxiv.org/abs/1308.6203 _______________________________________________ AVAILABLE FILE FORMATS The datasets are available in the following formats (included): *.xls : MS-Excel/LibreOffice native spreadsheets *.asc : space-separated plaintext spreadsheets *.mat : Matlab/Octave native data file (workspace) These data formats are equivalent, i.e., they contain the exact same sets of data. Normally, at least one of them should be compatible with any major programming platform (e.g. Matlab, Octave, R) or any native programming language for arbitrary handling (e.g. C, Java).

For details see: * Harris V. Georgiou, "Adaptive detection and severity level characterization algorithm for Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) via oximetry signal analysis" (28-Aug-2013) -- https://arxiv.org/abs/1308.6203