Big data in mHealth

2018-01-01
Gökalp, Mert Onuralp
Akyol, Mehmet Ali
Eren, Pekin Erhan
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The proliferation of mobile technologies has paved the way for the widespread use of mobile health (mHealth) devices. This in turn generates a large amount of data, which is essentially big data, that can be used for various purposes. In order to obtain the maximum benefit from mHealth data, emerging big data technologies can be employed. In this chapter, the relationship between mHealth and big data is investigated from a sociotechnical perspective. Following an overview of the state-of-the-art, stakeholders and their interests are identified, and the impact of big data on such interests is presented. The opportunities of using big data technologies in the mHealth domain are considered from several viewpoints. Social and economic implications of using big data technologies toward these ends are highlighted. Various challenges exist in the implementation and adoption of mHealth data processing. While there are social challenges including privacy, safety, and a false sense of confidence, there are also technical challenges such as security, standardization, correctness, timely analysis, and domain expertise. Some of these coincide with the challenges of the big data domain, and the others are related to human nature and human capabilities. The use of existing big data platforms requires significant expertise and know-how in data science domain which may hinder the adoption of big data technologies in mHealth. Hence, a solution in the form of a framework that provides higher abstraction level programming models is suggested to facilitate widespread user adoption. Accordingly, user aspects associated with big data in the mHealth domain are discussed.
mHealth, Big data, mHealth use cases, Opportunities and challenges, Visual programming model
https://link.springer.com/book/10.1007/978-3-319-73135-3
https://hdl.handle.net/11511/77557
Graduate School of Informatics, Book / Book chapter

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Citation Formats
M. O. Gökalp, M. A. Akyol, and P. E. Eren, Big data in mHealth. 2018, p. 256.
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