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Volume 23 / Issue 6

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Integrating Biomedical Sensor Data into a Simulation Learning Environment for Children Newly Diagnosed with Diabetes

Maria-Blanca Ibáñez (Universidad Carlos III de Madrid, Spain)

Soledad Escolar (Universidad de Castilla La Mancha, Spain)

Ricardo Iskandar (Universidad Carlos III de Madrid, Spain)

Karen Viera (Centro de Salud Ciudad de los Periodistas, Spain)

Carlos Delgado-Kloos (Universidad Carlos III de Madrid, Spain)

Abstract: Deploying Wireless Body Area Networks (WBANs) on/in human bodies has become an increasingly active area of research due to WBANs' capability to monitor human physiological signals, which is useful in a wide range of applications. However, there is a lack of e-learning applications taking advantage of the context-medical data coming from WBANs. This study is aimed at exploring the educational usefulness of integrating data captured by wearable biomedical sensors in a simulation learning environment. To this end, a system has been designed with the aim of introducing 8-12 year old children, newly diagnosed with type 1 diabetes mellitus, to the endocrine regulation of glucose metabolism processes. The system is evaluated in order to determine whether it is technically viable, and its suitability is validated for educational purposes. Technical viability is evaluated through a simulation, whereas educational usefulness is examined by a group of 13 health professionals in terms of fidelity, validity, interactivity and learning content. The results from this experience highlight the potential of the integration of biomedical sensor data in a simulation learning environment to foster the motivation of the target population and reflection about the health consequences of the patients' actual behaviors. The evaluators see potentials on this proposal and even recommended the incorporation of more biomedical sensors, and new functionalities to share the physiological state of the patients with healthcare stakeholders.

Keywords: eHealth, simulation learning environment, wearable computing

Categories: K.3.1, L.3.6, L.5.0