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http://dx.doi.org/10.6109/jkiice.2019.23.12.1485

A Model of Vital Signs Analysis based on Big Data using OCL  

Kim, Tae-Woong (Department of Computer Education, Silla University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.23, no.12, 2019 , pp. 1485-1491 More about this Journal
Abstract
As the type and size of vital signs become extensive at the moment lately, a research is actively progressing to define vital signs as big data and analyze it. We generally use a similar method of processing big data on social network as a way to treat vital signs as big data. Vital Sign Big Data should be extracted as feature data, stored separately, and analyzed with various analytical instruments. In other words, it should ensure interoperability and compatability of data, and the index expression in analytical tools should be concise. For this end, I defined the vital sign as the standard meta-model base of HL7 in this dissertation, and I propose a model for analyzing vital signs using OCL, the OMG's standard mathematical specification language. In addition, the proposed model can be confirmed the applicability by figuring out the consumption of calories using ECG data.
Keywords
vital signs; Big Data; Annotated ECG(Electrocardiogram); meta-model; OCL(Object Constraint language);
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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