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Detection of the QRS complex is a long-standing topic in the context of electrocardiography and many algorithms build upon the knowledge of the QRS positions. Although the first solutions to this problem were proposed in the 1970s and 1980s, there is still potential for improvements. Advancements in neural network technology made in recent years also lead to the emergence of enhanced QRS detectors based on artificial neural networks. In this work, we propose a method for assessing the certainty that is in each of the detected QRS complexes, i.e. how confident the QRS detector is that there is, in fact, a QRS complex in the position where it was detected. We further show how this metric can be utilised to distinguish correctly detected QRS complexes from false detections.
Background Heart failure (HF) is a complex, chronic condition that is associated with debilitating symptoms, all of which necessitate close follow-up by health care providers. Lack of disease monitoring may result in increased mortality and more frequent hospital readmissions for decompensated HF. Remote patient management (RPM) in this patient population may help to detect early signs and symptoms of cardiac decompensation, thus enabling a prompt initiation of the appropriate treatment and care before a manifestation of HF decompensation. Objective The objective of the present article is to describe the design of a new trial investigating the impact of RPM on unplanned cardiovascular hospitalisations and mortality in HF patients. Methods The TIM-HF2 trial is designed as a prospective, randomised, controlled, parallel group, open (with randomisation concealment), multicentre trial with pragmatic elements introduced for data collection. Eligible patients with HF are randomised (1:1) to either RPM + usual care or to usual care only and are followed for 12 months. The primary outcome is the percentage of days lost due to unplanned cardiovascular hospitalisations or all-cause death. The main secondary outcomes are all-cause and cardiovascular mortality. Conclusion The TIM-HF2 trial will provide important prospective data on the potential beneficial effect of telemedical monitoring and RPM on unplanned cardiovascular hospitalisations and mortality in HF patients.
Many of today's distributed computing systems in the field do not Support the migration of execution entities among computing nodes (luring runtime. The relatively static association between units of processing and computing nodes makes it difficult to implement fault-tolerant behavior or load-balancing schemes. The concept of code migration may provide a solution to the above-mentioned problems. it can be defined as the movement of processes, objects, or components from one computing node to another during system runtime in a distributed environment. With the advent of the virtual machine-based NET framework, many of the cross-language heterogeneity issues have been resolved. With the commercial implementation, the shared source "Rotor", and the open-source "Mono" implementation on hand, we have focused on cross-operating system heterogeneity issues and present interoperability and migration schemes for applications distributed over different operating systems (namely Linux and Windows 2000) as well as various NET implementations. Within this paper, we describe the integration of a migration facility with the hell) of Aspect- Oriented Programming (AOP) into the NET framework. AOP is interesting as it addresses non-functional system properties on the middleware level, without the need to manipulate lower system layers like the operating system itself. Most features required to implement object or process migration (such as reflection mechanisms or a machine-independent executable format) are already present in the NET frameworks, so the integration of such a concept is a natural extension of the system capabilities. We have implemented several proof-of-concept applications for different use case scenarios. The paper contains an experimental evaluation of the performance impact of object migration in context of those applications.
With the growth of virtualization and cloud computing, more and more forensic investigations rely on being able to perform live forensics on a virtual machine using virtual machine introspection (VMI). Inspecting a virtual machine through its hypervisor enables investigation without risking contamination of the evidence, crashing the computer, etc. To further access to these techniques for the investigator/researcher we have developed a new VMI monitoring language. This language is based on a review of the most commonly used VMI-techniques to date, and it enables the user to monitor the virtual machine's memory, events and data streams. A prototype implementation of our monitoring system was implemented in KVM, though implementation on any hypervisor that uses the common x86 virtualization hardware assistance support should be straightforward. Our prototype outperforms the proprietary VMWare VProbes in many cases, with a maximum performance loss of 18% for a realistic test case, which we consider acceptable. Our implementation is freely available under a liberal software distribution license. (C) 2014 Digital Forensics Research Workshop. Published by Elsevier Ltd. All rights reserved.