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Personalized Alarming System for Asthma Management Based on Lung Functionality: Observational Study
Asthma is a chronic respiratory disease that can be challenging to manage. To improve asthma management, we designed a personalized alarm system that utilizes lung function data to monitor and alert individuals to potentially harmful air quality. Our pilot observation included seven individuals who were exposed to two different air-quality environments, and we observed significant variations in their lung function responses. Based on these observations, we developed customized alarm systems for each participant that continuously monitored air quality and provided notifications when it reached levels that could potentially exacerbate their asthma symptoms. This personalized approach has the potential to enable individuals to proactively protect their respiratory health and avoid asthma attacks by taking timely and appropriate action based on their own specific needs.
Personalized Alarming System for Asthma Management Based on Lung Functionality: Observational Study
Asthma is a chronic respiratory disease that can be challenging to manage. To improve asthma management, we designed a personalized alarm system that utilizes lung function data to monitor and alert individuals to potentially harmful air quality. Our pilot observation included seven individuals who were exposed to two different air-quality environments, and we observed significant variations in their lung function responses. Based on these observations, we developed customized alarm systems for each participant that continuously monitored air quality and provided notifications when it reached levels that could potentially exacerbate their asthma symptoms. This personalized approach has the potential to enable individuals to proactively protect their respiratory health and avoid asthma attacks by taking timely and appropriate action based on their own specific needs.
Personalized Alarming System for Asthma Management Based on Lung Functionality: Observational Study
Alblooshi, Fatima (Autor:in) / Albadi, Reem (Autor:in) / Alblooshi, Khawla (Autor:in) / Ishimirwe, Emma (Autor:in) / Uwisoneye, Yvettte (Autor:in) / Alnajjar, Fady (Autor:in) / Mehiar, Dua'a (Autor:in)
20.02.2023
531619 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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