Fast Pattern Discovery in Healthcare Data Using Graphics Processors
Abstract
The mobile medical diagnosis and health monitoring system helps in managing the various chronic diseases like asthma, blood pressure and heart diseases etc. in consultation with the remotely available physicians by initiating the emergency call automatically on the physician’s mobile phone and providing the on-line vital medical parameters captured by the body area sensor network of the patient. We observed that a GPU based solution can outperform a CPU based solution by more than 30% in terms of speed up, while giving same accuracy of results, divided among healthy, normal and unhealthy patients. Finally, key parameter to model our health care data likestandard deviations of {1, 0.5, 0.5}, means of {(1, 1), (0, 0), (-1,-1)} are used to study healthy persons and unhealthy patients.
Keywords: Healthcare ; GPU; EEG; PCG; datastructure
DOI
https://doi.org/10.22270/jddt.v9i1-s.2446References
Boyi Xu, et. al., Ubiquitous Data Accessing Method in IoT- Based Information System for Emergency Medical Services, IEEE Transactions on Industrial informatics, 2014, Volume:10 , Issue: 2 ,pp 1578 – 1586.
Verma AK; et. al., Multi-operational home automation system using IOT, An approach, 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference
Khan SF, Health care monitoring system in Internet of Things by using RFID, 2017 6th International Conference on Industrial Technology and Management.
Jimenez F, Torres R; Building an IoT – aware healthcare monitoring system, 2015 34th International Conference of the Chilean Computer Science Society.
Siva S, et.al.; A Smart heart rate sensing system in the internet of Internet of Things, IJCTA, 9(9), 2016, pp. 3659-3663.
Fernandez F, George C. Pallis, Opportunities and challenges of the Internet of Things for healthcare Systems engineering perspective, International Conference on Wireless Mobile Communication and Healthcare (Mobihealth), 2014, pp 263-266.
Rajasekaran S et.al., “ HUMAN HEALTH MONITORING USING WIRELESS SENSORS NETWORK(WSN),” in International Journal of Application or Innovation in Engineering and Management(IJMIEM), December 2013.
Danilo F. S. Santos, et. al., Standard based and Distributed Health Information Sharing for mHealth IoT Systems , IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom), 2014 ,pp 94-98.
Saha HN et. al., Internet of Thing based healthcare monitoring system, 2017 8th IEEE Annual Information Technology, Electronics and Mobile Communication Conference.
Saha HN et. al., Health monitoring using Internet of Things (IoT), 2017 8th Annual Industrial Automation andM Electromechanical Engineering Conference.
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