Estimation of quality of experience (QoE) in e-Health ecosystems
This article proposes a framework to design and implement e- Health interventions in a comprehensive manner. We draw on complexity science to study the interplay of the ecosystem, the behavior and interactions among its agents. We provide a platform to estimate the Quality of Experience (QoE) to ass...
| Authors: | , , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2017 |
| Country: | México |
| Institution: | Centro de Investigación Científica y de Educación Superior de Ensenada |
| Repository: | Redalyc-CICESE |
| OAI Identifier: | oai:redalyc.org:64352303007 |
| Online Access: | https://www.redalyc.org/articulo.oa?id=64352303007 |
| Access Level: | Open access |
| Keyword: | Ingeniería QoE QoS health fuzzy logic complexity science |
| Summary: | This article proposes a framework to design and implement e- Health interventions in a comprehensive manner. We draw on complexity science to study the interplay of the ecosystem, the behavior and interactions among its agents. We provide a platform to estimate the Quality of Experience (QoE) to assess the relationship between technology and human factors involved in e-Health projects. Our aim is to estimate QoE in e-Health ecosystems from the perspective of complexity by adopting a methodology that uses fuzzy logic to study the behavior of the ecosystem’s agents. We apply the proposed framework to a remote diagnosis case by means of an ultrasound probe through a satellite link. Despite the ambiguities for determining QoE, the experiment demonstrates the applicability of the framework and allows to stressing the importance of human factors in the implementation of e-Health projects. |
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