Model-Driven Approach for Body Area Network Application Development.

This paper introduces the sensor-networked IoT model as a prototype to support the design of Body Area Network (BAN) applications for healthcare. Using the model, we analyze the synergistic effect of the functional requirements (data collection from the human body and transferring it to the top level) and non-functional requirements (trade-offs between energy-security-environmental factors, treated as Quality-of-Service (QoS)). We use feature models to represent the requirements at the earliest stage for the analysis and describe a model-driven methodology to design the possible BAN applications. Firstly, we specify the requirements as the problem domain (PD) variability model for the BAN applications. Next, we introduce the generative technology (meta-programming as the solution domain (SD)) and the mapping procedure to map the PD feature-based variability model onto the SD feature model. Finally, we create an executable meta-specification that represents the BAN functionality to describe the variability of the problem domain though transformations. The meta-specification (along with the meta-language processor) is a software generator for multiple BAN-oriented applications. We validate the methodology with experiments and a case study to generate a family of programs for the BAN sensor controllers. This enables to obtain the adequate measure of QoS efficiently through the interactive adjustment of the meta-parameter values and re-generation process for the concrete BAN application.

Identification of predictors of inhospital postreperfusion mode of death in patients with acute ST-elevation myocardial infarction.

OBJECTIVES. The aim of this study was to identify the predictors of the postreperfusion mode of death using the distinctions in clinical characteristics of patients who died and survived after reperfusion therapy, treated due to ST-elevation myocardial infarction (STEMI). MATERIAL AND METHODS. This consecutive study has involved 36 patients: 18 patients who died from progressive heart failure (PHF) (group 1, n=13) or from cardiac rupture (CR) (group 2, n=5) after primary coronary intervention. The control group consisted of 18 randomly selected patients who survived in-hospital period (group 3). The initial and postreperfusion heart rate (HR), systolic and diastolic arterial pressures (SAP and DAP), maximal ST elevation (max ST upward arrow) and depression (max ST downward arrow), ST score, TIMI flow grade, coronary score (CS), and their perireperfusion changes were assessed for each patient. The complex prognostic predictors--TIMI Risk Score and TIMI Risk Index--were also assessed. The data analysis was performed by standard statistical and machine learning approach methods. RESULTS. The comparison of three patients' groups according to simple ECG or circulatory characteristics showed that more significant differences were seen in postreperfusion characteristics or their perireperfusion changes. Herewith, the major part of significantly different characteristics (baseline SAP, DAP, and HR, postreperfusion SAP, DAP, ST score, and TIMI flow grade, resolution of ST score) was observed comparing both the groups of dead patients with survivors (control group). The differences in the complex predictors (TIMI Risk Score and TIMI Risk Index) were similar. However, the smallest number of significantly different characteristics was seen comparing both the groups of dead patients. The baseline DAP (P=0.045), postreperfusion SAP (P=0.04) and DAP (P=0.03), and ST score (P=0.0025) were higher in the patients who died from CR. The postreperfusion ST score and SAP were also identified as necessary components in the assessment of informative prognostic sets according to feature selection methods used in data mining field. CONCLUSION. The postreperfusion ST score, SAP, and DAP could be useful for the prediction of in-hospital postreperfusion mode of death in patients with STEMI; evidently more clinical predictors could be useful for the prediction of general occurrence of postreperfusion deaths.