DocumentCode :
3756670
Title :
Big Data and mHealth Drive Asthma Self-Management
Author :
Quan Do;Son Tran;Kris Robinson
Author_Institution :
Comput. Sci. Dept., New Mexico State Univ., Las Cruces, NM, USA
fYear :
2015
Firstpage :
806
Lastpage :
809
Abstract :
This paper reports our effort to establish the desirable characteristics for the next generation asthma APP for an underserved population. Proposed asthma mobile APP aims to promote older adults´ positive adjustment to this chronic disease by being an effective tool for patients to track their personal asthma triggers, predict asthma attacks, support asthma self-management and communicate with healthcare provider. Management of asthma is a dynamic process and varies by individual. For that reason, a personalized asthma APP is necessary to control this chronic disease. Environmental indicators, personal triggers, symptoms monitoring, medication use, peak flow, and blood oxygen monitoring data are analyzed to predict an asthma attack or indicate control. Other non-asthma symptom monitoring, such as fatigue, and biometric measures, like blood pressure, may be added as requested by end user.
Keywords :
"Diseases","Monitoring","Medical diagnostic imaging","Blood","Sociology","Statistics"
Publisher :
ieee
Conference_Titel :
Computational Science and Computational Intelligence (CSCI), 2015 International Conference on
Type :
conf
DOI :
10.1109/CSCI.2015.129
Filename :
7424201
Link To Document :
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