False Alarm Reduction in Self-Care by Personalized Automatic Detection of ECG Electrode Cable Interchanges.

Introduction: False alarm reduction is an important challenge in self-care, whereas one of the most important false alarm causes in the cardiology domain is electrodes misplacements in ECG recordings, the main investigations to perform for early and pervasive detection of cardiovascular diseases. In this context, we present and assess a new method for electrode reversals identification for Mason-Likar based 3D ECG recording systems which are especially convenient to use in self-care and allow to achieve, as previously reported, high computerized ischemia detection accuracy.

Methods: We mathematically simulate the effect of the six pairwise reversals of the LA, RA, LL, and C2 electrodes on the three ECG leads I, II, and V2.

Personalized Message Routing Policy in Pervasive eHealth Applications Based on HL7 RIM.

The design of relevant message routing strategies that provide reliable communications between different healthcare actors is deemed among one of the most challenging requirements to enhance QoS in eHealth applications. In this paper, we propose a data and context-driven model that aims to support the design of personalized, intelligent and adaptive eHealth message routing policies. Our model is suitably complying with HL7 v3, an international standard for healthcare information exchange.

Wearable sensor systems: the challenges.

Given the soaring costs associated with the treatment of ever more prevalent chronic disease, it is widely agreed that a revolution is required in health care provision. It is often thought that the necessary technology already exists for the home-based monitoring of such patients and that it is other factors which are holding back the more widespread clinical uptake of these new tools. The authors suggest that the necessary sensor-related technologies are often not as advanced as may first appear; certainly they are generally not adequate for the robust, long-term monitoring of patients under real-life conditions.

Data privacy preservation in telemedicine: the PAIRSE project.

The preservation of medical data privacy and confidentiality is a major challenge in eHealth systems and applications. A technological solution based on advanced information and communication systems architectures is needed in order to retrieve and exchange the patient's data in a secure and reliable manner. In this paper, we introduce the project PAIRSE, Preserving Privacy in Peer to Peer (P2P) environments, which proposes an original web service oriented framework preserving the privacy and confidentiality of shared or exchanged medical data.

A classification tree approach for cardiac ischemia detection using spatiotemporal information from three standard ECG leads.

The accurate noninvasive diagnosis of cardiac ischemia remains a great challenge. To this end, the ECG is the main source of information, and personal health systems may now embed intelligence for enabling any citizen to self-record an ECG anywhere at any time. Our objective is to find a decision-support approach that makes best use of these resources.