) Context and usability are important drivers behind the design of the Biomedical REAl-Time Health Evaluation for Pediatric Asthma (BREATHE) platform. First, without context, it becomes difficult to understand the data cap- tured by sensors, diminishing the utility of observations. This observation spurs BREATHE to incorporate as much information about a patient and his/her situation and surroundings in order to fully contextualize interpre- tations and make informed recommendations. Second, usability is an imperative consideration in mobile health (mHealth): if the system is perceived as unusable ? for any reason ? patients will fail to be compliant and the mHealth application will ultimately fail. These two ideas motivate Project 2, which develops the informatics infra- structure to enable context around sensed data, to analyze the data, and to optimize the range of interactions and activities different users will have with BREATHE. Project 2 starts with development of a unified, extensible data model for pediatric asthma, establishing a common foundation for standardizing and organizing information. The data model creates a comprehensive view across different types of sensed information (physiologic, environmental), clinical information, and self-reported infor- mation (e.g., symptoms), all accrued over time. Given this data model, Project 2 establishes an information architecture that enables new data sources (e.g., real-time air quality reports, electronic health records) to be combined with sensor data, providing additional context. Open source projects (UIMA, Taverna) are adapted to provide a flexible framework for specifying data collection protocols and associated data processing workflows on these integrated datasets. As a use case, the linkage of processing workflows to statistical and machine learning methods to aid in predictive risk modeling of asthma exacerbations is considered, along with support for real-time analytics in order to facilitate timely responses by the BREATHE system. Finally, the unified data model also enables the creation of a range of user interfaces (UI) and visualizations: ohmage is leveraged to bootstrap mobile device client and UI development, including the deployment of scheduled surveys, reminders, and data collection; and web-based UIs are proposed to support the review of data collection protocols and patient-specific timeline views that enable clinicians and researchers to ?drill down? into collected information. Usability concerns are reflected in the development of these various UIs through careful requirements analysis, and iterative design and testing. In this regard, Project 2 works closely with Project 1 to develop BREATHE?s mobile device interfaces, and with Project 3 to garner feedback on system design and usability in order to refine the platform over the course of the Center?s efforts.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
1U54EB022002-01
Application #
9077038
Study Section
Special Emphasis Panel (ZRG1-HDM-Z (52))
Project Start
2015-09-30
Project End
2019-09-29
Budget Start
2015-10-01
Budget End
2016-09-30
Support Year
1
Fiscal Year
2015
Total Cost
$2,120,578
Indirect Cost
$765,742
Name
University of California Los Angeles
Department
Type
DUNS #
092530369
City
Los Angeles
State
CA
Country
United States
Zip Code
90095
King, Christine E; Sarrafzadeh, Majid (2018) A SURVEY OF SMARTWATCHES IN REMOTE HEALTH MONITORING. J Healthc Inform Res 2:1-24
Ding, Yichen; Lee, Juhyun; Ma, Jianguo et al. (2017) Light-sheet fluorescence imaging to localize cardiac lineage and protein distribution. Sci Rep 7:42209
Hojaiji, Hannaneh; Kalantarian, Haik; Bui, Alex A T et al. (2017) Temperature and Humidity Calibration of a Low-Cost Wireless Dust Sensor for Real-Time Monitoring. 2017 IEEE Sens Appl Symp (SAS) (2017) 2017:
Ding, Yichen; Abiri, Arash; Abiri, Parinaz et al. (2017) Integrating light-sheet imaging with virtual reality to recapitulate developmental cardiac mechanics. JCI Insight 2:
Li, Rongsong; Yang, Jieping; Saffari, Arian et al. (2017) Ambient Ultrafine Particle Ingestion Alters Gut Microbiota in Association with Increased Atherogenic Lipid Metabolites. Sci Rep 7:42906
Buonocore, Chris M; Rocchio, Rosemary A; Roman, Alfonso et al. (2017) Wireless Sensor-Dependent Ecological Momentary Assessment for Pediatric Asthma mHealth Applications. IEEE Int Conf Connect Health Appl Syst Eng Technol 2017:137-146
Hosseini, Anahita; Buonocore, Chris M; Hashemzadeh, Sepideh et al. (2017) Feasibility of a Secure Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma. Sensors (Basel) 17:
Ma, Jianguo; Luo, Yuan; Sevag Packard, René R et al. (2016) Ultrasonic Transducer-Guided Electrochemical Impedance Spectroscopy to Assess Lipid-Laden Plaques. Sens Actuators B Chem 235:154-161
Hosseini, Anahita; Buonocore, Chris M; Hashemzadeh, Sepideh et al. (2016) HIPAA Compliant Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma. Int Conf Wearable Implant Body Sens Netw 2016:49-54