BackgroundResting conventional 12-lead ECG has low sensitivity for detection of coronary artery disease (CAD) and left ventricular hypertrophy (LVH) and low positive predictive value (PPV) for prediction of left ventricular systolic dysfunction (LVSD). We hypothesized that a ~5-min resting 12-lead advanced ECG test ("A-ECG") that combined results from both the advanced and conventional ECG could more accurately screen for these conditions than strictly conventional ECG.MethodsResults from nearly every conventional and advanced resting ECG parameter known from the literature to have diagnostic or predictive value were first retrospectively evaluated in 418 healthy controls and 290 patients with imaging-proven CAD, LVH and/or LVSD. Each ECG parameter was examined for potential inclusion within multi-parameter A-ECG scores derived from multivariate regression models that were designed to optimally screen for disease in general or LVSD in particular. The performance of the best retrospectively-validated A-ECG scores was then compared against that of optimized pooled criteria from the strictly conventional ECG in a test set of 315 additional individuals.ResultsCompared to optimized pooled criteria from the strictly conventional ECG, a 7-parameter A-ECG score validated in the training set increased the sensitivity of resting ECG for identifying disease in the test set from 78% (72-84%) to 92% (88-96%) (P < 0.0001) while also increasing specificity from 85% (77-91%) to 94% (88-98%) (P < 0.05). In diseased patients, another 5-parameter A-ECG score increased the PPV of ECG for LVSD from 53% (41-65%) to 92% (78-98%) (P < 0.0001) without compromising related negative predictive value.ConclusionResting 12-lead A-ECG scoring is more accurate than strictly conventional ECG in screening for CAD, LVH and LVSD.

Several studies have shown that diminution of the high-frequency (HF; 150-250 Hz) components present within the central portion of the QRS complex of an electrocardiogram (ECG) is a more sensitive indicator for the presence of myocardial ischemia than are changes in the ST segments of the conventional low-frequency ECG. However, until now, no device has been capable of displaying, in real time on a beat-to-beat basis, changes in these HF QRS ECG components in a continuously monitored patient. Although several software programs have been designed to acquire the HF components over the entire QRS interval, such programs have involved laborious off-line calculations and postprocessing, limiting their clinical utility. We describe a personal computer-based ECG software program developed recently at the National Aeronautics and Space Administration (NASA) that acquires, analyzes, and displays HF QRS components in each of the 12 conventional ECG leads in real time. The system also updates these signals and their related derived parameters in real time on a beat-to-beat basis for any chosen monitoring period and simultaneously displays the diagnostic information from the conventional (low-frequency) 12-lead ECG. The real-time NASA HF QRS ECG software is being evaluated currently in multiple clinical settings in North America. We describe its potential usefulness in the diagnosis of myocardial ischemia and coronary artery disease.

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The ionic polymer–metal composite (IPMC) is a new practical engineering material that, it has a wide range of capabilities in both dry and liquid environments. IPMC is a new candidate for diaphragms in micropump devices, micro and Nano robotic applications. IPMCs are regarded as a capable actuator for transportable applications, however, the unique combination of electrochemical and mechanical properties that they possess, such as back-relaxation, restraint their use in real-life applications. There have a lot of attempts to understand and model the IPMCs properties and build a whole prototype that can be used, with certainty, in different robotic, control, and medical applications, yet, till now, it seems that the dehydration and back-relaxation are still not modeled properly. The Nernst-Plank-Poisson was chosen to be the base model for the IPMC behavior, we were able to create a new model that truly represent the back-relaxation effects that occur in IPMCs, we’ve called the new model as modified NPP model. The modification used captured data from our experimental work Our modified analytical NPP (Nernst-Plank-Poisson) model was the verified using MATLAB & Simulink, which showed that the model, and the controller design for it was able to first compensate the loss of position of the IPMC due to back-relaxation, and then track the desired position input signals with great accuracy. The model and designed controller can be utilized in verity of robotic applications.