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.

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.

A novel neural-network model for deriving standard 12-lead ECGs from serial three-lead ECGs: application to self-care.

Synthesis of the 12-lead ECG has been investigated in the past decade as a method to improve patient monitoring in situations where the acquisition of the 12-lead ECG is cumbersome and time consuming. This paper presents and assesses a novel approach for deriving 12-lead ECGs from a pseudoorthogonal three-lead subset via generic and patient-specific nonlinear reconstruction methods based on the use of artificial neural-networks (ANNs) committees. We train and test the ANN on a set of serial ECGs from 120 cardiac inpatients from the intensive care unit of the Cardiology Hospital of Lyon.

Toward a personal health society in cardiology.

In this paper, we present a new generation of health services that has emerged due to the development of advanced information and communication technology (ICT) solutions, like the Enhanced Personal, Intelligent, and Mobile system for Early Detection and Interpretation of Cardiac Syndromes (EPI-MEDICS). It is a personal self-care system that allows any citizen to self-record high-quality ECGs on demand with a smart portable device, which is endowed with powerful ICT capabilities: self-adaptive embedded intelligence, mobile health record management support on SmartMedia card, embedded Web server, and wireless communication. The EPI-MEDICS solution design also provides ambient, intelligent, and pervasive computing services offering any citizen a ubiquitous, reliable, and efficient management of his/her own cardiac status.

A knowledge model driven solution for web-based telemedicine applications.

Building knowledge-based telemedicine systems to deliver high quality services is still a challenge. The availability and capability of different human, communication and material resources play an important role in the telemedical task management process especially in emergency scenarios. In this paper we propose a knowledge model enabling intelligent, ubiquitous telemedicine tasks management.

An ontology-based telemedicine tasks management system architecture.

The recent developments in ambient intelligence and ubiquitous computing offer new opportunities for the design of advanced Telemedicine systems providing high quality services, anywhere, anytime. In this paper we present an approach for building an ontology-based task-driven telemedicine system. The architecture is composed of a task management server, a communication server and a knowledge base for enabling decision makings taking account of different telemedical concepts such as actors, resources, services and the Electronic Health Record.

A generic task-driven multi-agent telemedicine system.

Pervasive Telemedicine is an emerging research discipline, which focuses on the development and the application of ubiquitous computing technology for healthcare purposes. However, the current telemedicine systems lack to be self adaptable to handle different types of data such as vital biosignals, images, video and textual data. In addition, they do not use the full capabilities of the computing devices on which they run.

Spatiotemporal electrocardiographic characterization of ventricular depolarization and repolarization abnormalities in long QT syndrome.

Background And Purpose: If only a standard electrocardiogram (ECG) is available, at least 25% of patients with long QT syndrome (LQTS) may be missed. Our goal is to quantify abnormal electrical activity and to develop an ECG decision rule for the patients with LQTS.

Methods: One hundred forty-one subjects were included in this study (71 patients with LQTS and 70 healthy subjects).

Improvement of the detection of myocardial ischemia thanks to information technologies.

Background: The standard 12-lead ECG remains one of the basic investigations for the early detection and assessment of acute coronary syndromes. It is easy to perform, anywhere and anytime, and can be digitally transmitted within minutes to an emergency medical service for remote advice and triage. But the conventional ST-segment deviation criteria are of limited diagnostic accuracy.

Toward personal eHealth in cardiology. Results from the EPI-MEDICS telemedicine project.

Despite many attempts to improve the management of acute myocardial infarction, only small trends to shorter time intervals before treatment have been reported. The self-care solution developed by the European EPI-MEDICS project (2001-2004) is a novel, very affordable, easy-to-use, portable, and intelligent Personal ECG Monitor (PEM) for the early detection of cardiac ischemia and arrhythmia that is able to record a professional-quality, 3-lead electrocardiogram (ECG) based on leads I, II, and V2; derive the missing leads of the standard 12-lead ECG (thanks to either a generic or a patient-specific transform), compare each ECG with a reference ECG by means of advanced neural network-based decision-making methods taking into account the serial ECG measurements and the patient risk factors and clinical data; and generate different levels of alarms and forward the alarm messages with the recorded ECGs and the patient's Personal electronic Health Record (PHR) to the relevant health care providers by means of a standard Bluetooth-enabled, GSM/GPRS-compatible mobile phone. The ECG records are SCP-ECG encoded and stored with the PHR on a secure personal SD Card embedded in the PEM device.

New paradigms in telemedicine: ambient intelligence, wearable, pervasive and personalized.

After decades of development of information systems dedicated to health professionals, there is an increasing demand for personalized and non-hospital based care. An especially critical domain is cardiology: almost two third of cardiac deaths occur out of hospital, and victims do not survive long enough to benefit from in-hospital treatments. We need to reduce the time before treatment.

Pervasive self-care solutions in telecardiology. Typical use cases from the EPI-MEDICS project.

In western countries, heart disease is the main cause of premature death. Most of cardiac deaths occur out of hospital. Because of a continuously growing elderly population, the number of heart attacks is steadily increasing.

Adaptive user interface customization through browsing knowledge capitalization.

Hypermedia data browsing is a mean for improving information access. However, the overload and the heterogeneity of medical information, as well as the multitude of possible navigational paths, turn the consultation of data into a difficult task. We present in this paper a solution for the development of adaptive user interfaces in a hypermedia data browsing environment.