A sliding-window based algorithm to determine the presence of chest compressions from acceleration data
This publication presents in detail five exemplary cases and the algorithm used in the article (Orlob et al. 2022). Defibrillator records for the five exemplary cases were obtained from the German Resuscitation Registry. They consist of accelerometry, electrocardiogram and capnography time series as...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-04-01
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| Series: | Data in Brief |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340922001846 |
| _version_ | 1818357197932855296 |
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| author | Wolfgang J. Kern Simon Orlob Birgitt Alpers Michael Schörghuber Andreas Bohn Martin Holler Jan-Thorsten Gräsner Jan Wnent |
| author_facet | Wolfgang J. Kern Simon Orlob Birgitt Alpers Michael Schörghuber Andreas Bohn Martin Holler Jan-Thorsten Gräsner Jan Wnent |
| author_sort | Wolfgang J. Kern |
| collection | DOAJ |
| description | This publication presents in detail five exemplary cases and the algorithm used in the article (Orlob et al. 2022). Defibrillator records for the five exemplary cases were obtained from the German Resuscitation Registry. They consist of accelerometry, electrocardiogram and capnography time series as well as defibrillation times, energies and impedance when recorded. For these cases, experienced physicians annotated time points of cardiac arrest and return of spontaneous circulation or termination of resuscitation attempts, as well as the beginning and ending of every single chest compression period in consensus, as described in Orlob et al. (2022). Furthermore, an algorithm was developed which reliably detects chest compression periods automatically without the time-consuming process of manual annotation. This algorithm allows for an usage in automatic resuscitation quality assessment, machine learning approaches, and handling of big amounts of data (Orlob et al. 2022). |
| first_indexed | 2024-12-13T20:09:17Z |
| format | Article |
| id | doaj.art-b652774c27eb44f583f91c94c3138e45 |
| institution | Directory Open Access Journal |
| issn | 2352-3409 |
| language | English |
| last_indexed | 2024-12-13T20:09:17Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Data in Brief |
| spelling | doaj.art-b652774c27eb44f583f91c94c3138e452022-12-21T23:32:57ZengElsevierData in Brief2352-34092022-04-0141107973A sliding-window based algorithm to determine the presence of chest compressions from acceleration dataWolfgang J. Kern0Simon Orlob1Birgitt Alpers2Michael Schörghuber3Andreas Bohn4Martin Holler5Jan-Thorsten Gräsner6Jan Wnent7Corresponding author.; University of Graz, Institute of Mathematics and Scientific Computing, Heinrichstr. 36, Graz, Austria; BioTechMed-Graz, Graz, AustriaBioTechMed-Graz, Graz, Austria; University Hospital Schleswig-Holstein, Institute for Emergency Medicine, Kiel, Germany; Department of Anesthesiology and Intensive Care Medicine, Division of Anesthesiology for Cardiovascular and Thoracic Surgery and Intensive Care Medicine, Medical University of Graz, Graz, AustriaUniversity Hospital Schleswig-Holstein, Institute for Emergency Medicine, Kiel, GermanyDepartment of Anesthesiology and Intensive Care Medicine, Division of Anesthesiology for Cardiovascular and Thoracic Surgery and Intensive Care Medicine, Medical University of Graz, Graz, AustriaDepartment of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Münster, Germany; City of Münster Fire Department, Münster, GermanyUniversity of Graz, Institute of Mathematics and Scientific Computing, Heinrichstr. 36, Graz, Austria; BioTechMed-Graz, Graz, AustriaUniversity Hospital Schleswig-Holstein, Institute for Emergency Medicine, Kiel, Germany; Department of Anaesthesiology and Intensive Care Medicine, University Hospital Schleswig-Holstein, Kiel, GermanyUniversity Hospital Schleswig-Holstein, Institute for Emergency Medicine, Kiel, Germany; Department of Anaesthesiology and Intensive Care Medicine, University Hospital Schleswig-Holstein, Kiel, Germany; School of Medicine, University of Namibia, Windhoek, NamibiaThis publication presents in detail five exemplary cases and the algorithm used in the article (Orlob et al. 2022). Defibrillator records for the five exemplary cases were obtained from the German Resuscitation Registry. They consist of accelerometry, electrocardiogram and capnography time series as well as defibrillation times, energies and impedance when recorded. For these cases, experienced physicians annotated time points of cardiac arrest and return of spontaneous circulation or termination of resuscitation attempts, as well as the beginning and ending of every single chest compression period in consensus, as described in Orlob et al. (2022). Furthermore, an algorithm was developed which reliably detects chest compression periods automatically without the time-consuming process of manual annotation. This algorithm allows for an usage in automatic resuscitation quality assessment, machine learning approaches, and handling of big amounts of data (Orlob et al. 2022).http://www.sciencedirect.com/science/article/pii/S2352340922001846Cardiac arrestCardiopulmonary resuscitationChest compressionsChest compression fractionAccelerometry |
| spellingShingle | Wolfgang J. Kern Simon Orlob Birgitt Alpers Michael Schörghuber Andreas Bohn Martin Holler Jan-Thorsten Gräsner Jan Wnent A sliding-window based algorithm to determine the presence of chest compressions from acceleration data Data in Brief Cardiac arrest Cardiopulmonary resuscitation Chest compressions Chest compression fraction Accelerometry |
| title | A sliding-window based algorithm to determine the presence of chest compressions from acceleration data |
| title_full | A sliding-window based algorithm to determine the presence of chest compressions from acceleration data |
| title_fullStr | A sliding-window based algorithm to determine the presence of chest compressions from acceleration data |
| title_full_unstemmed | A sliding-window based algorithm to determine the presence of chest compressions from acceleration data |
| title_short | A sliding-window based algorithm to determine the presence of chest compressions from acceleration data |
| title_sort | sliding window based algorithm to determine the presence of chest compressions from acceleration data |
| topic | Cardiac arrest Cardiopulmonary resuscitation Chest compressions Chest compression fraction Accelerometry |
| url | http://www.sciencedirect.com/science/article/pii/S2352340922001846 |
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