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UnoViS: the MedIT public unobtrusive vital signs database

While PhysioNet is a large database for standard clinical vital signs measurements, such a database does not exist for unobtrusively measured signals. This inhibits progress in the vital area of signal processing for unobtrusive medical monitoring as not everybody owns the specific measurement syste...

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Autores principales: Wartzek, Tobias, Czaplik, Michael, Antink, Christoph Hoog, Eilebrecht, Benjamin, Walocha, Rafael, Leonhardt, Steffen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4450479/
https://www.ncbi.nlm.nih.gov/pubmed/26038690
http://dx.doi.org/10.1186/s13755-015-0010-1
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author Wartzek, Tobias
Czaplik, Michael
Antink, Christoph Hoog
Eilebrecht, Benjamin
Walocha, Rafael
Leonhardt, Steffen
author_facet Wartzek, Tobias
Czaplik, Michael
Antink, Christoph Hoog
Eilebrecht, Benjamin
Walocha, Rafael
Leonhardt, Steffen
author_sort Wartzek, Tobias
collection PubMed
description While PhysioNet is a large database for standard clinical vital signs measurements, such a database does not exist for unobtrusively measured signals. This inhibits progress in the vital area of signal processing for unobtrusive medical monitoring as not everybody owns the specific measurement systems to acquire signals. Furthermore, if no common database exists, a comparison between different signal processing approaches is not possible. This gap will be closed by our UnoViS database. It contains different recordings in various scenarios ranging from a clinical study to measurements obtained while driving a car. Currently, 145 records with a total of 16.2 h of measurement data is available, which are provided as MATLAB files or in the PhysioNet WFDB file format. In its initial state, only (multichannel) capacitive ECG and unobtrusive PPG signals are, together with a reference ECG, included. All ECG signals contain annotations by a peak detector and by a medical expert. A dataset from a clinical study contains further clinical annotations. Additionally, supplementary functions are provided, which simplify the usage of the database and thus the development and evaluation of new algorithms. The development of urgently needed methods for very robust parameter extraction or robust signal fusion in view of frequent severe motion artifacts in unobtrusive monitoring is now possible with the database.
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spelling pubmed-44504792015-06-03 UnoViS: the MedIT public unobtrusive vital signs database Wartzek, Tobias Czaplik, Michael Antink, Christoph Hoog Eilebrecht, Benjamin Walocha, Rafael Leonhardt, Steffen Health Inf Sci Syst Database While PhysioNet is a large database for standard clinical vital signs measurements, such a database does not exist for unobtrusively measured signals. This inhibits progress in the vital area of signal processing for unobtrusive medical monitoring as not everybody owns the specific measurement systems to acquire signals. Furthermore, if no common database exists, a comparison between different signal processing approaches is not possible. This gap will be closed by our UnoViS database. It contains different recordings in various scenarios ranging from a clinical study to measurements obtained while driving a car. Currently, 145 records with a total of 16.2 h of measurement data is available, which are provided as MATLAB files or in the PhysioNet WFDB file format. In its initial state, only (multichannel) capacitive ECG and unobtrusive PPG signals are, together with a reference ECG, included. All ECG signals contain annotations by a peak detector and by a medical expert. A dataset from a clinical study contains further clinical annotations. Additionally, supplementary functions are provided, which simplify the usage of the database and thus the development and evaluation of new algorithms. The development of urgently needed methods for very robust parameter extraction or robust signal fusion in view of frequent severe motion artifacts in unobtrusive monitoring is now possible with the database. BioMed Central 2015-06-02 /pmc/articles/PMC4450479/ /pubmed/26038690 http://dx.doi.org/10.1186/s13755-015-0010-1 Text en © Wartzek et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Database
Wartzek, Tobias
Czaplik, Michael
Antink, Christoph Hoog
Eilebrecht, Benjamin
Walocha, Rafael
Leonhardt, Steffen
UnoViS: the MedIT public unobtrusive vital signs database
title UnoViS: the MedIT public unobtrusive vital signs database
title_full UnoViS: the MedIT public unobtrusive vital signs database
title_fullStr UnoViS: the MedIT public unobtrusive vital signs database
title_full_unstemmed UnoViS: the MedIT public unobtrusive vital signs database
title_short UnoViS: the MedIT public unobtrusive vital signs database
title_sort unovis: the medit public unobtrusive vital signs database
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4450479/
https://www.ncbi.nlm.nih.gov/pubmed/26038690
http://dx.doi.org/10.1186/s13755-015-0010-1
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