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Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors
BACKGROUND: The impact of medical-grade wearable electrocardiographic (ECG) recording technology is increasing rapidly. A wide range of different portable smartphone-connected ECG and heart rate trackers is available on the market. Smart ECG devices are especially valuable to monitor either supraven...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8890040/ https://www.ncbi.nlm.nih.gov/pubmed/35265927 http://dx.doi.org/10.1016/j.cvdhj.2021.09.006 |
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author | Hilbel, Thomas Alhersh, Taha Stein, Wolfram Doman, Leon Schultz, Jobst-Hendrik |
author_facet | Hilbel, Thomas Alhersh, Taha Stein, Wolfram Doman, Leon Schultz, Jobst-Hendrik |
author_sort | Hilbel, Thomas |
collection | PubMed |
description | BACKGROUND: The impact of medical-grade wearable electrocardiographic (ECG) recording technology is increasing rapidly. A wide range of different portable smartphone-connected ECG and heart rate trackers is available on the market. Smart ECG devices are especially valuable to monitor either supraventricular arrhythmias or prolonged QT intervals to avoid drug-induced life-threatening arrhythmias. However, frequent false alarms or false-positive arrhythmia results from wearable devices are unwanted. Therefore, for clinical evaluation, it should be possible to measure and evaluate the biosignals of the wearables independent of the manufacturer. OBJECTIVE: Unlike radiological devices that do support the universal digital imaging and communications in medicine standard, these medical-grade devices do not yet support a secure standardized exchange pathway between sensors, smartphones/smartwatches, and end services such as cloud storage or universal Web-based application programming interface (API) access. Consequently, postprocessing of recorded ECGs or heart rate interval data requires a whole toolbox of customized software technologies. METHODS/RESULTS: Various methods for measuring and analyzing nonstandardized ECG and heart rate data are proposed, including online measurement of ECG waveforms within a PDF, access to data using manufacturer-specific software development kits, and access to biosignals using modern Web APIs. CONCLUSION: With the appropriate workaround, modern software technologies such as JavaScript and PHP allow health care providers and researchers to easily and instantly access necessary and important signal measurements on demand. |
format | Online Article Text |
id | pubmed-8890040 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-88900402022-03-08 Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors Hilbel, Thomas Alhersh, Taha Stein, Wolfram Doman, Leon Schultz, Jobst-Hendrik Cardiovasc Digit Health J Clinical BACKGROUND: The impact of medical-grade wearable electrocardiographic (ECG) recording technology is increasing rapidly. A wide range of different portable smartphone-connected ECG and heart rate trackers is available on the market. Smart ECG devices are especially valuable to monitor either supraventricular arrhythmias or prolonged QT intervals to avoid drug-induced life-threatening arrhythmias. However, frequent false alarms or false-positive arrhythmia results from wearable devices are unwanted. Therefore, for clinical evaluation, it should be possible to measure and evaluate the biosignals of the wearables independent of the manufacturer. OBJECTIVE: Unlike radiological devices that do support the universal digital imaging and communications in medicine standard, these medical-grade devices do not yet support a secure standardized exchange pathway between sensors, smartphones/smartwatches, and end services such as cloud storage or universal Web-based application programming interface (API) access. Consequently, postprocessing of recorded ECGs or heart rate interval data requires a whole toolbox of customized software technologies. METHODS/RESULTS: Various methods for measuring and analyzing nonstandardized ECG and heart rate data are proposed, including online measurement of ECG waveforms within a PDF, access to data using manufacturer-specific software development kits, and access to biosignals using modern Web APIs. CONCLUSION: With the appropriate workaround, modern software technologies such as JavaScript and PHP allow health care providers and researchers to easily and instantly access necessary and important signal measurements on demand. Elsevier 2021-10-08 /pmc/articles/PMC8890040/ /pubmed/35265927 http://dx.doi.org/10.1016/j.cvdhj.2021.09.006 Text en © 2021 Heart Rhythm Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Clinical Hilbel, Thomas Alhersh, Taha Stein, Wolfram Doman, Leon Schultz, Jobst-Hendrik Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
title | Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
title_full | Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
title_fullStr | Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
title_full_unstemmed | Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
title_short | Analysis and postprocessing of ECG or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
title_sort | analysis and postprocessing of ecg or heart rate data from wearable devices beyond the proprietary cloud and app infrastructure of the vendors |
topic | Clinical |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8890040/ https://www.ncbi.nlm.nih.gov/pubmed/35265927 http://dx.doi.org/10.1016/j.cvdhj.2021.09.006 |
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