Rapid Evidence-based Development of Mobile Medical IoT Apps

被引：0
|
作者：
Bagade, Priyanka [1 ]
Banerjee, Ayan [2 ]
Gupta, Sandeep K. S. [2 ]
机构：
[1] Intel Corp, Portland, OR 97209 USA
[2] Arizona State Univ, IMPACT Lab, CIDSE, Tempe, AZ USA
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATION WORKSHOPS (PERCOM WORKSHOPS) | 2016年
关键词：
SAFE;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Mobile medical apps (MMAs) work in close loop with human physiology through sensing and control. As such it is essential for them to achieve intended functionality, without having harmful effects on human physiology, affecting the availability of the service and compromising the privacy of health data. However for a mobile app manufacturer, generating evidences regarding safety, sustainability and security (S3) of MMAs can be time consuming. To accelerate the development of S3 assured MMAs, we propose Health-Dev beta tool that takes high level description of MMAs and automatically generates validated code and evidences of safety, security, and sustainability. Using the mobile artificial pancreas medical control application we show that Health-Dev beta tool can generate code that satisfies requirements and reduce development time by a factor of 1.8.
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页数：6
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