ArticleFrontiers in digital health2025
AirPredict: an eHealth platform for asthma management leveraging wearable sensors, digital diaries, and air quality monitoring to optimize patient outcomes.
Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Evaluating a digital health ecosystem for asthma and air quality: an early feasibility study based on clinicians and patient-reported measures.Frontiers in digital health · 2026Article
- Modernisation of chronic respiratory disease management: The integration of wearable technology.Chronic respiratory diseaseReview
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Asthma management is complex, and while it is known that many environmental factors play a critical role in exacerbations, there is increasing interest on the role of air pollution. Yet, the precise relations by which these factors affect exacerbation risk are not fully understood. There is a need for innovative solutions to monitor and assess personal exposure to air pollutants in both outdoor and indoor environments to better understand their impact on respiratory outcomes, particularly asthma exacerbations. This paper introduces AirPredict, an innovative eHealth platform designed to enhance asthma management through the integration of wearable sensors, digital diaries, and ambient air quality monitoring. Methods: AirPredict comprises a mobile application for patients, a web interface for clinicians, and a robust cloud-based infrastructure. The platform utilizes devices such as the Fitbit Charge 6 for heart rate monitoring, the Atmotube PRO for air quality assessment, and the MIR SmartOne for spirometry, providing precise, real-time data on individual exposures and health outcomes. A feasibility study involving 16 participants, including asthma patients and specialized clinicians in Padova, Italy, was conducted to evaluate the usability of platform's components. Results: The results indicated high usability and user satisfaction, with average Single Ease Question (SEQ) scores ranging from of 6.8 to 5.5 out of 7 for patients and from 6.8 to 6.6 for clinicians, reflecting ease of use and functionality. Discussion: The findings support the platform's broader adoption and further development, highlighting its role in advancing eHealth solutions for chronic disease management.
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