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CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring
Mechanical ventilation (MV) provides respiratory support for critically ill patients in the intensive care unit (ICU). Waveform data output by the ventilator provides valuable physiological and diagnostic information. However, existing systems do not provide full access to this information nor allow...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474567/ https://www.ncbi.nlm.nih.gov/pubmed/36117541 http://dx.doi.org/10.1016/j.ohx.2022.e00358 |
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author | Arn Ng, Qing Yew Shuen Ang, Christopher Shiong Chiew, Yeong Wang, Xin Pin Tan, Chee Basri Mat Nor, Mohd Salwa Damanhuri, Nor Geoffrey Chase, J. |
author_facet | Arn Ng, Qing Yew Shuen Ang, Christopher Shiong Chiew, Yeong Wang, Xin Pin Tan, Chee Basri Mat Nor, Mohd Salwa Damanhuri, Nor Geoffrey Chase, J. |
author_sort | Arn Ng, Qing |
collection | PubMed |
description | Mechanical ventilation (MV) provides respiratory support for critically ill patients in the intensive care unit (ICU). Waveform data output by the ventilator provides valuable physiological and diagnostic information. However, existing systems do not provide full access to this information nor allow for real-time, non-invasive data collection. Therefore, large amounts of data are lost and analysis is limited to short samples of breathing cycles. This study presents a data acquisition device for acquiring and monitoring patient ventilation waveform data. Acquired data can be exported to other systems, allowing users to further analyse data and develop further clinically useful parameters. These parameters, together with other ventilatory information, can help personalise and guide MV treatment. The device is designed to be easily replicable, low-cost, and scalable according to the number of patient beds. Validation was carried out by assessing system performance and stability over prolonged periods of 7 days of continuous use. The device provides a platform for future integration of machine-learning or model-based modules, potentially allowing real-time, proactive, patient-specific MV guidance and decision support to improve the quality and productivity of care and outcomes. |
format | Online Article Text |
id | pubmed-9474567 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-94745672022-09-16 CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring Arn Ng, Qing Yew Shuen Ang, Christopher Shiong Chiew, Yeong Wang, Xin Pin Tan, Chee Basri Mat Nor, Mohd Salwa Damanhuri, Nor Geoffrey Chase, J. HardwareX Article Mechanical ventilation (MV) provides respiratory support for critically ill patients in the intensive care unit (ICU). Waveform data output by the ventilator provides valuable physiological and diagnostic information. However, existing systems do not provide full access to this information nor allow for real-time, non-invasive data collection. Therefore, large amounts of data are lost and analysis is limited to short samples of breathing cycles. This study presents a data acquisition device for acquiring and monitoring patient ventilation waveform data. Acquired data can be exported to other systems, allowing users to further analyse data and develop further clinically useful parameters. These parameters, together with other ventilatory information, can help personalise and guide MV treatment. The device is designed to be easily replicable, low-cost, and scalable according to the number of patient beds. Validation was carried out by assessing system performance and stability over prolonged periods of 7 days of continuous use. The device provides a platform for future integration of machine-learning or model-based modules, potentially allowing real-time, proactive, patient-specific MV guidance and decision support to improve the quality and productivity of care and outcomes. Elsevier 2022-09-06 /pmc/articles/PMC9474567/ /pubmed/36117541 http://dx.doi.org/10.1016/j.ohx.2022.e00358 Text en © 2022 Published by Elsevier Ltd. 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 | Article Arn Ng, Qing Yew Shuen Ang, Christopher Shiong Chiew, Yeong Wang, Xin Pin Tan, Chee Basri Mat Nor, Mohd Salwa Damanhuri, Nor Geoffrey Chase, J. CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring |
title | CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring |
title_full | CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring |
title_fullStr | CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring |
title_full_unstemmed | CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring |
title_short | CAREDAQ: Data acquisition device for mechanical ventilation waveform monitoring |
title_sort | caredaq: data acquisition device for mechanical ventilation waveform monitoring |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9474567/ https://www.ncbi.nlm.nih.gov/pubmed/36117541 http://dx.doi.org/10.1016/j.ohx.2022.e00358 |
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