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Estimation of quality of experience (QoE) in e-Health ecosystems
Estimación de calidad de experiencia (QoE) en ecosistemas de e-Salud
DOI:
https://doi.org/10.15446/ing.investig.v37n2.57664Keywords:
QoE, QoS, complexity science, e-health, fuzzy logic (en)QoE, QoS, ciencia de la complejidad, e-salud, lógica difusa (es)
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.
En este artículo se propone un marco de referencia para diseñar e implementar intervenciones de e-Salud de una manera integral. Recurrimos a la ciencia de la complejidad para estudiar la interacción de los agentes del ecosistema. Para ello, proporcionamos una plataforma para estimar la Calidad de Experiencia (o QoE, por sus siglas en inglés) para evaluar la relación entre la tecnología y los factores humanos que intervienen en los proyectos de e-Salud. Nuestro objetivo es estimar la QoE en los ecosistemas de e-Salud desde la perspectiva de la complejidad mediante la adopción de una metodología que utiliza la lógica difusa para estudiar el comportamiento de los agentes del ecosistema. Aplicamos el marco propuesto a un caso de diagnóstico remoto por medio de una sonda de ultrasonido a través de un enlace por satélite. A pesar de las ambigüedades involucradas en la determinación de calidad de la experiencia, el experimento demuestra la aplicabilidad del marco de referencia propuesto y permite subrayar la importancia de los factores humanos en la implementación de proyectos de e-Salud.
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Copyright (c) 2017 Veronica Alexandra Rojas-Mendizabal, Arturo Serrano-Santoyo, Roberto Conte-Galvan, Salvador Villarreal-Reyes, Raul Rivera-Rodriguez
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