Proetex is a European Integrated Project dedicated to micro- and nano-technology-based wearable equipment for emergency operators. During the first year of work, a careful analysis of several emergency scenarios has been carried out and has resulted in the design of a complete “smart” uniform for fire-fighters and emergency rescuers. These garments aim at monitoring both physiological parameters, position and posture of the operators and the presence of external potential sources of danger and to send these data to a remote coordinating unit. In the following, the main issues of the design flow will be described and discussed

The development of new high-performance Focal Plane Arrays (FPAs) for imaging systems is driven by advances in photodetector material growth and processing, readout integrated circuits and IR detector chip hybridisation/packaging. The hybridisation of the IR detector chip and the readout integrated circuit (ROIC) through flip-chip bonding is a key packaging challenge for pixel arrays with very small indium bumps and 10-30 m pitch sizes. This paper details the development and use of finite element models that can be used to assess and optimise the compression bonding process, and can enable insights into the impact of chip misalignment on the resulting flip-chip quality and the bonding equipment placement accuracy requirements for a given FPA specification. In addition, the fatigue performance of the indium interconnects of different fine pitch FPAs is evaluated and compared. The modelling results point that high quality interconnects and robust, defects-free assembly require micrometre placement accuracy. It is also possible that indium joints of higher resolution, larger size FPAs accumulate less damage under cryogenic temperature cycling compared to less dense, smaller in size, focal plane arrays.

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Abstract:Novel sensor-based continuous biomedical monitoring technologies have a major role in chronic disease management for early detection and prevention of known adverse trends. In the future, a diversity of physiological, biochemical and mechanical sensing principles will be available through sensor device 'ecosystems'. In anticipation of these sensor-based ecosystems, we have developed Healthcare@Home (HH) -a research-phase generic intervention-outcome monitoring framework. HH incorporates a closedloop intervention effect analysis engine to evaluate the relevance of measured (sensor) input variables to system-defined outcomes. HH offers real-world sensor type validation by evaluating the degree to which sensor-derived variables are relevant to the predicted outcome. This 'index of relevance' is essential where clinical decision support applications depend on sensor inputs. HH can help determine system-integrated cost-utility ratios of bespoke sensor families within defined applications -taking into account critical factors like device robustness / reliability / reproducibility, mobility / interoperability, authentication / security and scalability / usability. Through examples of hardware / software technologies incorporated in the HH end-to-end monitoring system, this paper discusses aspects of novel sensor technology integration for outcome-based risk analysis in diabetes.

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