HIPAA compliant wireless sensing smartwatch application for the self-management of pediatric asthma

Asthma is the most prevalent chronic disease among pediatrics, as it is the leading cause of student absenteeism and hospitalization for those under the age of 15. To address the significant need to manage this disease in children, the authors present a mobile health (mHealth) system that determines...

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Bibliographic Details
Published in:2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN) 2016-06, Vol.2016, p.49-54
Main Authors: Hosseini, Anahita, Buonocore, Chris M., Hashemzadeh, Sepideh, Hojaiji, Hannaneh, Kalantarian, Haik, Sideris, Costas, Bui, Alex A. T., King, Christine E., Sarrafzadeh, Majid
Format: Article
Language:English
Subjects:
Asthma
Children
Encryption
Health
Networks
Pediatrics
Real-time systems
Risk
Sensors
Watches
Wearable
Wireless communication
Wireless sensor networks
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Summary:Asthma is the most prevalent chronic disease among pediatrics, as it is the leading cause of student absenteeism and hospitalization for those under the age of 15. To address the significant need to manage this disease in children, the authors present a mobile health (mHealth) system that determines the risk of an asthma attack through physiological and environmental wireless sensors and representational state transfer application program interfaces (RESTful APIs). The data is sent from wireless sensors to a smartwatch application (app) via a Health Insurance Portability and Accountability Act (HIPAA) compliant cryptography framework, which then sends data to a cloud for real-time analytics. The asthma risk is then sent to the smartwatch and provided to the user via simple graphics for easy interpretation by children. After testing the safety and feasibility of the system in an adult with moderate asthma prior to testing in children, it was found that the analytics model is able to determine the overall asthma risk (high, medium, or low risk) with an accuracy of 80.10±14.13%. Furthermore, the features most important for assessing the risk of an asthma attack were multifaceted, highlighting the importance of continuously monitoring different wireless sensors and RESTful APIs. Future testing this asthma attack risk prediction system in pediatric asthma individuals may lead to an effective self-management asthma program.
ISSN:2376-8886
2376-8894
DOI:10.1109/BSN.2016.7516231