INTEGRATION OF WEARABLE ENVIRONMENTAL SENSORS IN PEDIATRIC ASTHMA MANAGEMENT: ASSESSING EFFICACY AND SOCIOECONOMIC INCLUSIVITY IN URBAN POPULATIONS
DOI:
https://doi.org/10.31435/ijitss.3(51).2026.6493Keywords:
Pediatric Asthma, Wearable Sensors, Digital Health, Health Equity, Predictive Modeling, Remote Patient MonitoringAbstract
Background Pediatric asthma disproportionately impacts marginalized urban demographics, with acute exacerbations frequently driven by localized environmental pollutants. Traditional static air monitors fail to capture individual-level exposures, necessitating continuous remote tracking.
Objectives This review assesses the clinical efficacy of integrating wearable environmental and physiological sensors into pediatric asthma management and evaluates their socioeconomic inclusivity for under-resourced populations.
Methods A comprehensive literature review was conducted to evaluate the technological validity of microenvironmental sensors, their clinical impact through machine learning-driven predictive modeling, and the structural socioeconomic barriers limiting equitable adoption.
Results Wearable environmental platforms demonstrate robust clinical efficacy by quantifying the personal exposome and generating interpretable digital biomarkers. Predictive algorithms utilizing these data streams accurately anticipate subclinical exacerbations, thereby reducing acute healthcare utilization. However, profound socioeconomic barriers, including prohibitive hardware and connectivity costs, digital literacy constraints, and privacy-related medical mistrust, restrict access among vulnerable populations, risking the exacerbation of systemic health disparities.
Conclusions While wearable sensors enable highly effective, proactive pediatric asthma management, achieving equitable implementation requires targeted policy reforms. Healthcare systems must establish digital therapeutics reimbursement pathways, deploy community-based participatory research for culturally adapted designs, and translate exposure data into structural public health interventions.
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Copyright (c) 2026 Antoni Kantor, Kacper Raputa, Aniela Kupiec, Michał Tutaj, Jakub Gościński, Bartosz Kus, Igor Kania, Julia Holzer, Marta Godyń, Mateusz Pietrasz
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