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Jocelyne Fayn

Publications and source records attributed to Jocelyne Fayn.

6 recordsLinked to original sources
PubMed2006

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. The purpose of this study is to investigate how much the use of computerized ECG techniques based on the measurement of the serial spatiotemporal ECG changes could improve the detection accuracy of transmural myocardial ischemia. METHODS: We considered the serial changes of continuous 12-lead ECGs of 90 patients undergoing elective percutaneous coronary angioplasty (PTCA) recorded during balloon inflation as an experimental model of ECG changes induced by coronary artery occlusion. The spatiotemporal ECG changes were measured according to the CAVIAR method and assessed by multivariate discriminant analysis in reference to serial changes of control recordings and standard ECG criteria. RESULTS: The diagnostic accuracy of the CAVIAR criteria for ischemia detection was 97%, with sensitivity of 98% and specificity of 96%, whereas the diagnostic accuracy of the conventional ST-segment criteria was 74%, with sensitivity of 60% and specificity of 88%. The increase of overall performance was obtained for all the occlusion locations. CONCLUSIONS: Computer-assisted quantitative serial ECG analysis, taking into account the spatiotemporal changes of the QRS and T waves, would provide the physician with additional information for significantly improving the detection of transmural myocardial ischemia.

Diagnosis, Computer-Assisted↗
PubMed2005

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. The alarm messages and the PHR are XML encoded. Major alarm messages are automatically transmitted to the nearest emergency call center. Medium or minor alarms are sent on demand to a central PEM Alarm Web Server. Health professionals are informed by a Short Message Service. The PEM embeds itself a Web server to facilitate the reviewing and/or update of the PHR during a routine visit at the office of the general physician or cardiologist. Eighty PEM prototypes have been finalized and tested for several weeks on 697 citizens/patients in different clinical and self-care situations involving end users (188 patients), general physicians (10), and cardiologists (9). The clinical evaluation indicates that the EPI-MEDICS concept may save lives and is very valuable for prehospitalization triage.

Allied Health Personnel↗
PubMed2004

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. But symptoms are often interpreted wrongly. The only immediate diagnostic tool to assess the possibility of a cardiac event is the electrocardiogram (ECG). Event and transtelephonic ECG recorders are used to improve decision making but require setting up new infrastructures. The European EPI-MEDICS project has developed an intelligent Personal ECG Monitor (PEM) for the early detection of cardiac events. The PEM embeds advanced decision making techniques, generates different alarm levels and forwards alarm messages to the relevant care providers by means of new generation wireless communication. It is cost saving, involving care provider only if necessary and requiring no specific infrastructure. This solution is a typical example of pervasive computing and ambient intelligence that demonstrates how personalized, wearable, ubiquitous devices could improve healthcare.

Artificial Intelligence↗
PubMed2003

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. Symptoms are often interpreted incorrectly. Victims do not survive long enough to benefit from inhospital treatments. To reduce the time before treatment, the only useful diagnostic tool to assess the presence of a cardiac event is the electrocardiogram (ECG). Event and transtelephonic ECG recorders are used to improve decision-making but require setting up new infrastructures. The pervasive solution proposed by the European EPI-MEDICS project is an intelligent Personal ECG Monitor for the early detection of cardiac events. It includes part of the patient electronic health record (EHR), embeds a web server and decision-making techniques, generates different alarm levels and forwards alarm messages to the relevant care providers by means of new generation wireless communication. It is cost saving, involving care providers only if necessary, without requiring to set-up specific infrastructures. Healthcare becomes personalized, wearable and ubiquitous.

Arrhythmias, Cardiac↗
PubMed2002

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. It is based on the capitalization of the users knowledge in the decision-making process, expressed in terms of navigational paths and of data presentation modes that are customized to the user's preferences and practice. This capitalization offers the user a way to automatically store and reuse the experience accumulated in browsing through patient records. We illustrate our approach with the implementation of HEMA, a clinical workstation prototype that we have specialized for the cardiology domain.

Artificial Intelligence↗