How do Users interact with Mobile Health Apps?: A Markov Chain Analysis
Authors: 
Joris Heyse, 
Gilles Vandewiele, Femke Ongenae, Femke De Backere, Filip De TurckAuthors Info & Claims
Joris Heyse, Gilles Vandewiele, Femke Ongenae, Femke De Backere, Filip De TurckAuthors Info & ClaimsPages 255 - 258
Abstract
Intelligent virtual coaches for healthcare require sufficient insights about the user. Data from interactions with a mobile health app have previously been overlooked as a source of valuable insights. In this paper, traces of interaction with a mobile app are analysed to identify the needs and goals of the user. The mobile app is part of a blended care solution for anxiety therapy. The paper illustrates how Markov Chain analysis proves to be a useful tool in classifying user interaction based on the user's goal.
References
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Index Terms
- How do Users interact with Mobile Health Apps?: A Markov Chain Analysis
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Published In
May 2020
446 pages
ISBN:9781450375320
DOI:10.1145/3421937
- Editors:
- Sean A. Munson,
- Stephen M. Schueller,
- General Chair:
- Rosa Arriaga
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Published: 02 February 2021
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PervasiveHealth '20
PervasiveHealth '20: 14th EAI International Conference on Pervasive Computing Technologies for Healthcare
May 18 - 20, 2020
GA, Atlanta, USA
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PervasiveHealth '20 Paper Acceptance Rate 55 of 116 submissions, 47%;
Overall Acceptance Rate 55 of 116 submissions, 47%
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