Heart disease and stroke are becoming the leading causes of death worldwide. Electrocardiography monitoring devices (ECG) are the only tool that help physicians diagnose cardiac abnormalities. Although the design of ECGs has followed closely the electronics miniaturization evolution over the years, existing wearable ECGs have limited accuracy and rely on external resources to analyse the signals and evaluate heart activity. In this paper, we work towards empowering the wearable device with processing capabilities to locally analyse the signal and identify abnormal behaviour. The ability to differentiate between normal and abnormal heart activity significantly reduces (a) the need to store the signals, (b) the data transmitted to the cloud, (c) the overall power consumption and (d) the confidentiality of private data. Based on this concept, the HEART system presented in this work, combines wearable embedded devices, mobile edge devices, and cloud services to provide on-the-spot, reliable, accurate, and instant heart monitoring. The wearable device is remotely trained by a physician to learn to accurately identify critical events related to each particular patient. Following this training session, the wearable device becomes capable of interpreting a large number of heart abnormalities without relying on cloud services and edge resources, when the medical doctor is not present. The Fog computing approach extends the cloud computing paradigm by migrating data-processing closer to production site, thus accelerating the system's responsiveness to events. The HEART system's performance concerning the accuracy of detecting abnormal events and the power consumption of the wearable device is evaluated. Results indicate that a very high success rate can be achieved in terms of event detection ratio and the battery is able to sustain operation up to a full week without the need for recharge.

The paper describes research that has been carried out in "extrovert-Gadgets", a research project funded in the context of EU IST/FET proactive initiative "Disappearing Computer". It presents a set of architectures for the composition of ubiquitous computing applications. The proposed architectures are part of GAS (Gadgetware Architectural Style), a generic architectural style, which can be used to describe everyday environments populated with computational artifacts. The overall innovation of the GAS approach lies in viewing the process where people configure and use complex collections of interacting eGadgets, as having much in common with the process where system builders design software systems out of components. This approach regards the everyday environment as being populated with tens even hundreds of artifacts, which people (who are always in control) associate in ad-hoc and dynamic ways.

In the new paradigm of computer use, the computer ceases to exist as an integrated multi-task device, but disintegrates into a task-oriented collection of networked devices. These devices do not resemble computers yet they have computational abilities. None of these concepts will be realised without appropriate support from communication technologies-P2P networking being the primary candidate. This paper describes part of the research being conducted in the Extrovert Gadgets project geared towards applying P2P computing solutions to the context of networked everyday objects.