Dynamic Self-adaptive Remote Health Monitoring System for Diabetics

Myung-kyung Suh; Tannaz Moin; Jonathan Woodbridge; Mars Lan; Hassan Ghasemzadeh; Alex Bui; Sheila Ahmadi; Majid Sarrafzadeh

doi:10.1109/EMBC.2012.6346404

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Dynamic Self-adaptive Remote Health Monitoring System for Diabetics

Journal article

Open access

Dynamic Self-adaptive Remote Health Monitoring System for Diabetics

Myung-kyung Suh, Tannaz Moin, Jonathan Woodbridge, Mars Lan, Hassan Ghasemzadeh, Alex Bui, Sheila Ahmadi and Majid Sarrafzadeh

Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), Vol.2012, pp.2223-2226

2012

DOI: https://doi.org/10.1109/EMBC.2012.6346404

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https://hdl.handle.net/2376/116336

PMCID: PMC5017249

PMID: 23366365

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https://doi.org/10.1109/EMBC.2012.6346404View

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Abstract

Diabetes is the seventh leading cause of death in the United States. In 2010, about 1.9 million new cases of diabetes were diagnosed in people aged 20 years or older. Remote health monitoring systems can help diabetics and their healthcare professionals monitor health-related measurements by providing real-time feedback. However, data-driven methods to dynamically prioritize and generate tasks are not well investigated in the remote health monitoring. This paper presents a task optimization technique used in WANDA (Weight and Activity with Blood Pressure and Other Vital Signs); a wireless health project that leverages sensor technology and wireless communication to monitor the health status of patients with diabetes. WANDA applies data analytics in real-time to improving the quality of care. The developed algorithm minimizes the number of daily tasks required by diabetic patients using association rules that satisfies a minimum support threshold. Each of these tasks maximizes information gain, thereby improving the overall level of care. Experimental results show that the developed algorithm can reduce the number of tasks up to 28.6% with minimum support 0.95, minimum confidence 0.97 and high efficiency.

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Title: Dynamic Self-adaptive Remote Health Monitoring System for Diabetics
Creators: Myung-kyung Suh - Computer Science Department, University of California, Los Angeles, CA, 90095, USA
Tannaz Moin - VA Greater Los Angeles Center of Excellence for the Study of Healthcare Provider Behavior and Department of Medicine, Division of Endocrine, Los Angeles CA. 90073
Jonathan Woodbridge - Computer Science Department, University of California, Los Angeles, CA, 90095, USA
Mars Lan - Computer Science Department, University of California, Los Angeles, CA, 90095, USA
Hassan Ghasemzadeh - Computer Science Department, University of California, Los Angeles, CA, 90095, USA
Alex Bui - Medical Imaging Informatics Group, Department of Radiological Sciences, University of California, Los Angeles, CA, 90024, USA
Sheila Ahmadi - Division of Endocrinology, University of California, Los Angeles, CA, 90024, USA
Majid Sarrafzadeh - Computer Science Department, University of California, Los Angeles, CA, 90095, USA
Publication Details: Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), Vol.2012, pp.2223-2226
Academic Unit: Electrical Engineering and Computer Science, School of
Identifiers: 99900547520301842
Language: English
Resource Type: Journal article