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Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor

With the acceleration of people's life rhythm, obstructive sleep apnea syndrome appears more and more frequently. This research mainly discusses the treatment of obstructive sleep apnea syndrome with a positive pressure ventilator based on artificial intelligence processor. The information stor...

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Detalles Bibliográficos
Autores principales: Chen, Zhuxiang, Zhao, Zhang, Zhang, Zhimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486548/
https://www.ncbi.nlm.nih.gov/pubmed/34603650
http://dx.doi.org/10.1155/2021/5683433
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author Chen, Zhuxiang
Zhao, Zhang
Zhang, Zhimin
author_facet Chen, Zhuxiang
Zhao, Zhang
Zhang, Zhimin
author_sort Chen, Zhuxiang
collection PubMed
description With the acceleration of people's life rhythm, obstructive sleep apnea syndrome appears more and more frequently. This research mainly discusses the treatment of obstructive sleep apnea syndrome with a positive pressure ventilator based on artificial intelligence processor. The information storage function of the smart positive pressure ventilator is included in the local medical terminal, presented after logging in with the user authority. It is mainly composed of data collection, data processing, and medical interface design, which embeds data request, data transmission, data analysis, and detailed tasks such as data compression and storage, and functions such as data display, image drawing, and alarm notification are realized by the medical interface. When the CPAP ventilator transmits respiratory data to the local medical terminal, it sends real-time respiratory information data packets. The data packet is collected and sent in real time in a fixed period and then received and analyzed by the local medical terminal. In the CPAP ventilator telemedicine system, the function of alarm message processing is mainly used to detect the patient's breathing status in real time, extract the alarm-related information, and generate an alarm. This function specifically includes several tasks such as alarm detection, alarm prompt, alarm storage, and remote transmission of alarm messages. The confirmed OSAS patients were pressure-titrated with a smart CPAP ventilator and then treated for 5 hours a day, followed by echocardiography after 5 months of continuous treatment. During the study, the average BMI was (28.9 ± 7.2) kg/m(2) and the average AHI index was (53.1 ± 37.8) times/h. This study may help improve the quality of life of patients with obstructive sleep apnea syndrome.
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spelling pubmed-84865482021-10-02 Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor Chen, Zhuxiang Zhao, Zhang Zhang, Zhimin J Healthc Eng Research Article With the acceleration of people's life rhythm, obstructive sleep apnea syndrome appears more and more frequently. This research mainly discusses the treatment of obstructive sleep apnea syndrome with a positive pressure ventilator based on artificial intelligence processor. The information storage function of the smart positive pressure ventilator is included in the local medical terminal, presented after logging in with the user authority. It is mainly composed of data collection, data processing, and medical interface design, which embeds data request, data transmission, data analysis, and detailed tasks such as data compression and storage, and functions such as data display, image drawing, and alarm notification are realized by the medical interface. When the CPAP ventilator transmits respiratory data to the local medical terminal, it sends real-time respiratory information data packets. The data packet is collected and sent in real time in a fixed period and then received and analyzed by the local medical terminal. In the CPAP ventilator telemedicine system, the function of alarm message processing is mainly used to detect the patient's breathing status in real time, extract the alarm-related information, and generate an alarm. This function specifically includes several tasks such as alarm detection, alarm prompt, alarm storage, and remote transmission of alarm messages. The confirmed OSAS patients were pressure-titrated with a smart CPAP ventilator and then treated for 5 hours a day, followed by echocardiography after 5 months of continuous treatment. During the study, the average BMI was (28.9 ± 7.2) kg/m(2) and the average AHI index was (53.1 ± 37.8) times/h. This study may help improve the quality of life of patients with obstructive sleep apnea syndrome. Hindawi 2021-09-23 /pmc/articles/PMC8486548/ /pubmed/34603650 http://dx.doi.org/10.1155/2021/5683433 Text en Copyright © 2021 Zhuxiang Chen et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Zhuxiang
Zhao, Zhang
Zhang, Zhimin
Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor
title Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor
title_full Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor
title_fullStr Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor
title_full_unstemmed Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor
title_short Obstructive Sleep Apnea Syndrome Treated Using a Positive Pressure Ventilator Based on Artificial Intelligence Processor
title_sort obstructive sleep apnea syndrome treated using a positive pressure ventilator based on artificial intelligence processor
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486548/
https://www.ncbi.nlm.nih.gov/pubmed/34603650
http://dx.doi.org/10.1155/2021/5683433
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