Ambient Intelligence and Pervasive Architecture Designed within the EPI-MEDICS Personal ECG Monitor

Ambient Intelligence and Pervasive Architecture Designed within the EPI-MEDICS Personal ECG Monitor

Hussein Atoui (Université de Lyon and INSERM, France), David Télisson (Université de Lyon and INSERM, France), Jocelyne Fyan (Université de Lyon and INSERM, France) and Paul Rubel (Université de Lyon and INSERM, France)
DOI: 10.4018/jhisi.2008100105
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Abstract

Recent years have witnessed a growing interest in developing personalized and nonhospital based care systems to improve the management of cardiac care. The EPI-MEDICS project has designed an intelligent, portable Personal ECG Monitor (PEM) embedding an advanced decision making system. We present two of the ambient intelligence models embedded in the PEM: the neural-network based ischemia detection module and the Bayesian-network risk stratification module. Ischemia detection was expanded to take into account the patient ECG, clinical data, and medical history. The neural-network ECG interpretation module and the Bayesian-network risk factors module collaborate through a fuzzy-logic-based layer. We also present two telemedicine solutions that we have designed and in which the PEM is integrated. The first telemedical architecture was created to allow the collection of medical data and their transmission between healthcare providers to get an expert opinion. The second one is intended for improving healthcare in old people’s homes.

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