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. We then assess the similarity between the synthesized ECGs and the original ECGs at the quantitative level in comparison with generic and patient-specific multiple-regression-based methods. The ANN achieved accurate reconstruction of the 12-lead ECGs of the study population using both generic and patient-specific ANN transforms, showing significant improvements over generic (p -value < or = 0.05) and patient-specific ( p-value < or = 0.01) multiple-linear-regression-based models. Consequently, our neural-network-based approach has proven to be sufficiently accurate to be deployed in home care as well as in ambulatory situations to synthesize a standard 12-lead ECG from a reduced lead-set ECG recording.

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 multicentric evaluation performed in Europe with a series of device prototypes and the performance assessment of the original methods of signal synthesis that were designed to guarantee a high interoperability level of the recorded data within the clinical practice, as well as of the decision-support methodologies that were developed for an early detection of life-threatening myocardial ischemia and arrhythmia, at home or anywhere, demonstrate the pertinence of going toward a personal health society in cardiology, which still yields the highest mortality rate in industrialized countries.

New medical devices and services enabling citizenpsilas health care anywhere and anytime are expected in the near future. However, to become a reality these devices must be supported by personalized services which satisfy user needs. In this paper we propose a general approach to manage the complexity of ambiguously related information for providing enhanced, user-specific services in the self-care domain. The global architecture is driven by a compositional model between a domain-specific and a context-awareness model, which aggregates the citizenpsilas and the devices profiles, the citizenpsilas healthcare characteristics and available signal processing methods. The final objective is to support automatic composition of services helping any citizen to select an optimal and personalized sensor system and to improve decision-making.

In 2002, DARPA put together a challenging proposition to the research community: demonstrate using an existing information system and available DARPA developed and other COTS technologies that a very high level of survivability against unconstrained attack by a nation state-level red team is achievable. This report describes the monitoring, intrusion detection, and reporting infrastructure of the resulting system, highlighting the design principles and lessons learned that are generally applicable to survivable information systems

There is an increasing demand for new eHealth solutions improving patients safety and reducing the overall cardiac mortality and morbidity by allowing the monitoring of the patient and of the citizen health status, wherever they could be, at home, at work, on travel. Decision support systems, cardiac event recorders and digital signal transmission systems were thus intensively investigated over the last decade. The EPI-MEDICS project has designed an intelligent, portable personal ECG monitor (PEM) that is able to record and to analyse a 3-lead SCP-ECG compliant electrocardiogram (ECG), and to synthesize the missing standard ECG leads by means of advanced neural network-based methods. In addition, the PEM device embeds decision-making methods taking into account the ECG analysis results, the patient risk factors and clinical data, and have the capability of generating different levels of alarms that are transmitted to the relevant health care providers by means of a standard Bluetooth-enabled, GSM/GPRS-compatible mobile phone. In this paper, we present strategies for the implementation and the deployment of patient/citizen specific neural network-based methods used for the synthesis and interpretation of the patients ECGs by means of an ad hoc infrastructure that allows neural learning on a large scale, thanks to Web services and grid computing technologies. The proposed solution is open, generic and adaptable to any standard SCP-ECG compliant portable electrocardiograph or PEM device from the EPI-MEDICS project. The aim is to facilitate the remote initialisation and adaptive update of the medical record and of the patient-specific configuration parameters of the intelligence embedded in the ECG device.

We have created a sensor-sharing protocol that uses cognition to increase performance by choosing protocol parameters based on the current environment and the past relationships between environment and performance. We have constructed a prototype of the protocol, and experimented with it in a four-node outdoor testbed. Our testbed is part of a larger effort, ADROIT, which seeks to create cognitive teams of software-defined radios [l].

Abstract Applications that are part of a mission‐critical information system need to maintain a usable level of key services through ongoing cyber‐attacks. In addition to the well‐publicized denial of service (DoS) attacks, these networked and distributed applications are increasingly threatened by sophisticated attacks that attempt to corrupt system components and violate service integrity. While various approaches have been explored to deal with DoS attacks, corruption‐inducing attacks remain largely unaddressed. We have developed a collection of mechanisms based on redundancy, Byzantine fault tolerance, and adaptive middleware that help distributed, object‐based applications tolerate corruption‐inducing attacks. In this paper, we present the ITUA architecture, which integrates these mechanisms in a framework for auto‐adaptive intrusion‐tolerant systems, and we describe our experience in using the technology to defend a critical application that is part of a larger avionics system as an example. We also motivate the adaptive responses that are key to intrusion tolerance, and explain the use of the ITUA architecture to support them in an architectural framework. Copyright © 2006 John Wiley & Sons, Ltd.

Many techniques and mechanisms exist today, some COTS, others less mature research products that can be used to deflect, detect, or even recover from specific types of cyber attacks. None of them individually is sufficient to provide an all around defense for a mission critical distributed system. A mission critical system must operate despite sustained attacks throughout the mission cycle, which in the case of military systems, can range from hours to days. A comprehensive survivability architecture, where individual security tools and defense mechanisms are used as building blocks, is required to achieve this level of survivability. We have recently designed a survivability architecture, which combined elements of protection, detection, and adaptive reaction; and applied it to a DoD information system. The resulting defense-enabled system was first evaluated internally, and then deployed for external Red Team exercise. In this paper we describe the survivability architecture of the system, and explain the rationale that motivated the design

Coordinating multiple overlapping defense mechanisms, at differing levels of abstraction, is fraught with the potential for misconfiguration, so there is strong motivation to generate policies for those mechanisms from a single specification in order to avoid that risk. This paper presents our experience and the lessons learned as we developed, validated and coordinated network communication security policies for a defense-in-depth enabled system that withstood sustained red team attack. Network communication was mediated by host-based firewalls, process domain mechanisms and application-level security policies enforced by the Java virtual machine. We coordinated the policies across the layers using a variety of tools, but we discovered that, at least for defense-in-depth enabled systems, constructing a single specification from which to derive all policies is probably neither practical nor even desirable

The same network infrastructure that is essential for the operation of today’s high valued distributed systems can also be misused by malicious attackers. Experience shows that implementing absolute security or preventing cyber attacks completely is infeasible when systems must be highly interconnected and comprise of COTS components with unknown security characteristics. Therefore, focus is shifting towards making high valued distributed systems survivable, enabling them to operate through attacks. This paper focuses on the networking aspects of the DPASA1 survivability architecture, which was used recently to defense-enable a DoD information system.

Physiological signals are usually patient specific, and they are difficult to predict, especially for the cardiovascular system. New methods capable to be adapted to each case and to learn the singular behavior of heart functions should be developed to support physicians in their decisionmaking. One of the most widely studied relations is the QT-RR one, between the total duration of the ventricle activation and inactivation, and the heart rate. In the past, different studies were made to approach this relation in the steady state. In this paper, a new method for modeling and predicting the transient dynamic behavior of QT interval in relation to changing RR intervals is presented using parametric models and multilayer perceptrons (MLP).

Building dependable distributed systems from commercial off-the-shelf components is of growing practical importance. For both cost and production reasons, there is interest in approaches and architectures that facilitate building such systems. The AQuA architecture is one such approach; its goal is to provide adaptive fault tolerance to CORBA applications by replicating objects. The AQuA architecture allows application programmers to request desired levels of dependability during applications' runtimes. It provides fault tolerance mechanisms to ensure that a CORBA client can always obtain reliable services, even if the CORBA server object that provides the desired services suffers from crash failures and value faults. AQuA includes a replicated dependability manager that provides dependability management by configuring the system in response to applications' requests and changes in system resources due to faults. It uses Maestro/Ensemble to provide group communication services. It contains a gateway to intercept standard CORBA IIOP messages to allow any standard CORBA application to use AQuA. It provides different types of replication schemes to forward messages reliably to the remote replicated objects. All of the replication schemes ensure strong, data consistency among replicas. This paper describes the AQuA architecture and presents, in detail, the active replication pass-first scheme. In addition, the interface to the dependability manager and the design of the dependability manager replication are also described. Finally, we describe performance measurements that were conducted for the active replication pass-first scheme, and we present results from our study of fault detection, recovery, and blocking times.

Building large-scale distributed object-oriented systems that provide multidimensional quality of service (QoS) in terms of fault tolerance, scalability, and performance is challenging. In order to meet this challenge, we need an architecture that can ensure that applications' requirements can be met while providing reusable technologies and software solutions. This paper describes techniques, based on the AQuA architecture, that enhance the applications' dependability and scalability by introducing two types of group members and a novel passive replication scheme. In addition, we describe how to make the management structure itself dependable by using the passive replication scheme. Finally, we provide performance measurements for the passive replication scheme.