The ability to observe the internals of an execution of a computer-based system is a fundamental requirement for ultimately ensuring correctness and safe behaviour. Within COEMS (Continuous Observation of Embedded Multicore Systems) a novel observer platform with supporting verification methods for software systems is created. COEMS tackles the issues of detection and identification of non-deterministic software failures caused by race conditions and access to inconsistent data. It gives insight to the system’s actual behaviour without affecting it allowing new verification methods. An efficient real-time access and analysis as a critical element for operating safe systems will be developed and validated by COEMS. Moreover, a cross-layer programming approach supporting failure detection will be proposed. COEMS aims at shortening the development cycle by considerably increased test efficiency and effectivity, by increased debug efficiency (especially for non-deterministically occurring failures) and by supporting performance optimization. COEMS improves the reliability of delivered systems, enabling software developers to identify, understand, and remove software defects before release, as well as improving efficiency of software for multi/many-core computing systems in terms of performance, real-time behaviour, and energy consumption. The two Global Players Thales Group and Airbus Group, both active in safety-critical domains, will validate the COEMS approach by suitable demonstrators, i.e. testing and debugging of real-world multicore applications. In addition to these two domains, we will address the domains of safety-critical medical applications, automation and automotive industry, as well as the Internet of Things. Technologically, COEMS will provide the world-wide first comprehensive online observation approach that is non-intrusive allowing improved testing and debugging. Altogether, COEMS will define a new state-of-the-art for software systems development.

Ventricular tachycardia (VT) is an unpredictable and potentially deadly condition and should be promptly treated with catheter ablation and medication, before irreversible and potentially fatal organ damage follows. Unfortunately, this combination of treatments does not prevent VT reoccurrence in 30-50% of VT patients and while they can undergo multiple invasive ablations, technical difficulties or refusal of the patient can lead to a lack of effective treatment options. A promising novel, non-invasive treatment option for VT is stereotactic arrhythmia radioablation (STAR). Besides being non-invasive, STAR can also be used to reach locations that are inaccessible for catheter ablation, which may potentially improve effectiveness of overall VT treatment. Small scale first in men/early phase trials have been performed for STAR, providing proof-of-concept for clinical safety and efficacy. However, patients with recurrent VT are not a homogenous group and each center deals with different inclusion criteria, imaging and/or target definition. Many questions remain and the available studies lack the power to clinically validate the approach and prepare for late stage phase III trials. The STOPSTORM consortium sets out to consolidate all current and future European efforts to clinically validate STAR treatment by merging all data in a validation cohort study, standardising pre-treatment and follow-up, in order to collect the data sets and statistical power needed to unanimously establish clinical safety, efficacy and benefit for STAR. The STOPSTORM consortium also sets out to refine protocols and guidelines, determine volumes of interest, define and model the optimal target region and target dose, also in relation to surrounding healthy tissues (i.e. organs at risk) and determine which patient population and underlying cardiopathies respond best to STAR. By doing so the STOPSTORM consortium paves the way to consensus and future late stage clinical trials for STAR.

Clinical diagnosis is seldom definitive. Clinical data are noisy and sparse, and often support multiple diagnoses and potential therapies. To decide how best to treat a patient requires identifying the many possible outcomes for an individual and their corresponding probabilities. In this project we will apply the mathematics of uncertainty quantification, developed for automotive, geological and meteorological predictions, combined with biophysical models of individual patient physiology and pathophysiology to predict patient outcomes and their corresponding probabilities. This will demonstrate how patient specific computational models can be used to make prospective predictions to guide procedures and inform uncertain clinical decisions. The use of uncertainty quantification and predictive patient specific models will be applied to patients with atrial fibrillation. Atrial fibrillation (AF) is the most common cardiac arrhythmia in the UK. In patients who do not respond to drug treatment, the pathological regions of the atria are removed or isolated through catheter ablation. However, up to 40% of patients with advanced (persistent) AF require further ablations to treat atrial tachycardia (pathological but regular activation) that develops after they have had an initial ablation to treat their AF. To reduce the number of additional procedures, this project will predict the probability that a patient will develop atrial tachycardia and the path that the atrial tachycardia will take, based on measurements recorded at the time of the initial persistent AF ablation procedure. If successful this approach would guide preventative ablations during the initial procedure to reduce the need for repeat procedures.