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Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm
In response to anticipated shortages of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features foun...
Formato: | Online Artículo Texto |
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Lenguaje: | English |
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IEEE
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545031/ https://www.ncbi.nlm.nih.gov/pubmed/32870799 http://dx.doi.org/10.1109/TBCAS.2020.3020702 |
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collection | PubMed |
description | In response to anticipated shortages of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features found on commercial ventilators. This work reports a low-cost, easy-to-produce electronic sensor and alarm system for pressure-cycled ventilators that estimates clinically useful metrics such as pressure and respiratory rate and sounds an alarm when the ventilator malfunctions. A low-complexity signal processing algorithm uses a pair of nonlinear recursive envelope trackers to monitor the signal from an electronic pressure sensor connected to the patient airway. The algorithm, inspired by those used in hearing aids, requires little memory and performs only a few calculations on each sample so that it can run on nearly any microcontroller. |
format | Online Article Text |
id | pubmed-8545031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | IEEE |
record_format | MEDLINE/PubMed |
spelling | pubmed-85450312021-11-12 Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm IEEE Trans Biomed Circuits Syst Article In response to anticipated shortages of ventilators caused by the COVID-19 pandemic, many organizations have designed low-cost emergency ventilators. Many of these devices are pressure-cycled pneumatic ventilators, which are easy to produce but often do not include the sensing or alarm features found on commercial ventilators. This work reports a low-cost, easy-to-produce electronic sensor and alarm system for pressure-cycled ventilators that estimates clinically useful metrics such as pressure and respiratory rate and sounds an alarm when the ventilator malfunctions. A low-complexity signal processing algorithm uses a pair of nonlinear recursive envelope trackers to monitor the signal from an electronic pressure sensor connected to the patient airway. The algorithm, inspired by those used in hearing aids, requires little memory and performs only a few calculations on each sample so that it can run on nearly any microcontroller. IEEE 2020-09-01 /pmc/articles/PMC8545031/ /pubmed/32870799 http://dx.doi.org/10.1109/TBCAS.2020.3020702 Text en This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm |
title | Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm |
title_full | Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm |
title_fullStr | Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm |
title_full_unstemmed | Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm |
title_short | Low-Complexity System and Algorithm for an Emergency Ventilator Sensor and Alarm |
title_sort | low-complexity system and algorithm for an emergency ventilator sensor and alarm |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8545031/ https://www.ncbi.nlm.nih.gov/pubmed/32870799 http://dx.doi.org/10.1109/TBCAS.2020.3020702 |
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