Power Autonomy Estimation of Low-Power Sensor for Long-Term ECG Monitoring.

The paper analyses the autonomy of a wireless body sensor that continuously measures the potential difference between two proximal electrodes on the skin, primarily used for measuring an electrocardiogram (ECG) when worn on the torso. The sensor is powered by a small rechargeable battery and is designed for extremely low power use. However, the autonomy of the sensor, regarding its power consumption, depends significantly on the measurement quality selection, which directly influences the amount of data transferred. Therefore, we perform an in-depth analysis of the power consumption sources, particularly those connected with the Bluetooth Low Energy (BLE) communication protocol, in order to model and then tune the autonomy of the wireless low-power body sensor for long-term ECG monitoring. Based on the findings, we propose two analytical models for power consumption: one for power consumption estimation in idle mode and the other one for power estimation in active mode. The proposed models are validated with the measured power consumption of the ECG sensor at different ECG sensor settings, such as sampling rate and transmit power. The proposed models show a good fit to the measured power consumption at different ECG sensor sampling rates. This allows for power consumption analysis and sensor autonomy predictions for different sensor settings. Moreover, the results show that the transmit power has a negligible effect on the sensor autonomy in the case of streaming data with high sampling rates. The most energy can be saved by lowering the sampling rate with suitable connection interval and by packing as much data as possible in a single BLE packet.

Medical-Grade ECG Sensor for Long-Term Monitoring.

The recent trend in electrocardiogram (ECG) device development is towards wireless body sensors applied for patient monitoring. The ultimate goal is to develop a multi-functional body sensor that will provide synchronized vital bio-signs of the monitored user. In this paper, we present an ECG sensor for long-term monitoring, which measures the surface potential difference between proximal electrodes near the heart, called differential ECG lead or differential lead, in short. The sensor has been certified as a class IIa medical device and is available on the market under the trademark Savvy ECG. An improvement from the user's perspective-immediate access to the measured data-is also implemented into the design. With appropriate placement of the device on the chest, a very clear distinction of all electrocardiographic waves can be achieved, allowing for ECG recording of high quality, sufficient for medical analysis. Experimental results that elucidate the measurements from a differential lead regarding sensors' position, the impact of artifacts, and potential diagnostic value, are shown. We demonstrate the sensors' potential by presenting results from its various areas of application: medicine, sports, veterinary, and some new fields of investigation, like hearth rate variability biofeedback assessment and biometric authentication.

On the Convergence of Stresses in Fretting Fatigue.

Fretting is a phenomenon that occurs at the contacts of surfaces that are subjected to oscillatory relative movement of small amplitudes. Depending on service conditions, fretting may significantly reduce the service life of a component due to fretting fatigue. In this regard, the analysis of stresses at contact is of great importance for predicting the lifetime of components. However, due to the complexity of the fretting phenomenon, analytical solutions are available for very selective situations and finite element (FE) analysis has become an attractive tool to evaluate stresses and to study fretting problems. Recent laboratory studies in fretting fatigue suggested the presence of stress singularities in the stick-slip zone. In this paper, we constructed finite element models, with different element sizes, in order to verify the existence of stress singularity under fretting conditions. Based on our results, we did not find any singularity for the considered loading conditions and coefficients of friction. Since no singularity was found, the present paper also provides some comments regarding the convergence rate. Our analyses showed that the convergence rate in stress components depends on coefficient of friction, implying that this rate also depends on the loading condition. It was also observed that errors can be relatively high for cases with a high coefficient of friction, suggesting the importance of mesh refinement in these situations. Although the accuracy of the FE analysis is very important for satisfactory predictions, most of the studies in the literature rarely provide information regarding the level of error in simulations. Thus, some recommendations of mesh sizes for those who wish to perform FE analysis of fretting problems are provided for different levels of accuracy.

Plant defence model revisions through iterative minimisation of constraint violations.

Biologists have been investigating plant defence response to virus infections; however, a comprehensive mathematical model of this complex process has not been developed. One obstacle in developing a dynamic model, useful for simulation, is the lack of kinetic data from which the model parameters could be determined. We address this problem by proposing a methodology for iterative improvement of the model parameters until the simulation results come close to the expectation of biology experts. These expectations are formalised in the form of constraints to be satisfied by the model simulations. In three iterative steps the model converged to satisfy the biology experts. There are two results of our approach: individual simulations and optimised model parameters, which provide a deeper insight into the biological system. Our constraint-driven optimisation approach allows for an efficient exploration of the dynamic behaviour of biological models and, at the same time, increases their reliability.

Exact parallel maximum clique algorithm for general and protein graphs.

A new exact parallel maximum clique algorithm MaxCliquePara, which finds the maximum clique (the fully connected subgraph) in undirected general and protein graphs, is presented. First, a new branch and bound algorithm for finding a maximum clique on a single computer core, which builds on ideas presented in two published state of the art sequential algorithms is implemented. The new sequential MaxCliqueSeq algorithm is faster than the reference algorithms on both DIMACS benchmark graphs as well as on protein-derived product graphs used for protein structural comparisons. Next, the MaxCliqueSeq algorithm is parallelized by splitting the branch-and-bound search tree to multiple cores, resulting in MaxCliquePara algorithm. The ability to exploit all cores efficiently makes the new parallel MaxCliquePara algorithm markedly superior to other tested algorithms. On a 12-core computer, the parallelization provides up to 2 orders of magnitude faster execution on the large DIMACS benchmark graphs and up to an order of magnitude faster execution on protein product graphs. The algorithms are freely accessible on http://commsys.ijs.si/~matjaz/maxclique.

Asynchronous master-slave parallelization of differential evolution for multi-objective optimization.

In this paper, we present AMS-DEMO, an asynchronous master-slave implementation of DEMO, an evolutionary algorithm for multi-objective optimization. AMS-DEMO was designed for solving time-intensive problems efficiently on both homogeneous and heterogeneous parallel computer architectures. The algorithm is used as a test case for the asynchronous master-slave parallelization of multi-objective optimization that has not yet been thoroughly investigated. Selection lag is identified as the key property of the parallelization method, which explains how its behavior depends on the type of computer architecture and the number of processors. It is arrived at analytically and from the empirical results. AMS-DEMO is tested on a benchmark problem and a time-intensive industrial optimization problem, on homogeneous and heterogeneous parallel setups, providing performance results for the algorithm and an insight into the parallelization method. A comparison is also performed between AMS-DEMO and generational master-slave DEMO to demonstrate how the asynchronous parallelization method enhances the algorithm and what benefits it brings compared to the synchronous method.

Parallel-ProBiS: fast parallel algorithm for local structural comparison of protein structures and binding sites.

The ProBiS algorithm performs a local structural comparison of the query protein surface against the nonredundant database of protein structures. It finds proteins that have binding sites in common with the query protein. Here, we present a new parallelized algorithm, Parallel-ProBiS, for detecting similar binding sites on clusters of computers. The obtained speedups of the parallel ProBiS scale almost ideally with the number of computing cores up to about 64 computing cores. Scaling is better for larger than for smaller query proteins. For a protein with almost 600 amino acids, the maximum speedup of 180 was achieved on two interconnected clusters with 248 computing cores. Source code of Parallel-ProBiS is available for download free for academic users at http://probis.cmm.ki.si/download.

Simulated temperature distribution of the proximal forearm.

Temperature changes in the resting proximal human forearm have been studied non-invasively, using computer simulation. A procedure for spatial model generation, based on digitized slice data, has been applied. A mathematical model and a 3-D computer simulation program have been implemented. Heat transfer in the non-homogenous tissue was modeled with a well known bio-heat equation. The heat production by tissue metabolism was modeled using the Q10 rule, while the heat exchange between the blood and tissue was modeled as a function of local temperature and regional blood flow. The stability and accuracy of the method was confirmed by varying the simulation parameters, the initial and boundary values, and the model dimensions, with subsequent analysis of the results. We have explained, by computer simulation, the variations in the Pennes' well-known in vivo measurements of the steady-state temperatures along the transverse axis of the proximal forearm. Suspecting that the anatomical positioning of his measuring probes varied, we have reconstructed their possible positions by searching for the simulated positions that result in the best agreement between simulated and measured temperature fields. Our simulations indicate that the fluctuations of the measured steady-state temperatures should not be smoothed out because they are the natural consequence of a complex interplay between the position of the measuring probes, anatomical position of the main arteries, dimensions of the forearm, blood flow, inhomogeneity of tissues, and environmental temperature.

Computer-simulated alternative modes of U-wave genesis.

OBJECTIVE: Several hypotheses for the origin of the U wave in electrocardiograms have been proposed. We have set out to explore and test alternative modes for U-wave genesis via computer simulations. METHODS AND RESULTS: A spatial model of a left ventricle has been constructed from 12 layers composed of cubic cells. Each cell is assigned its own time-dependent action potential with its own contribution to the electrical potential at arbitrary points where ECGs are measured. Simulated ECGs show that U waves can be generated using various combinations of action potentials (APs) across the different layers of the ventricular wall. We demonstrate a new mode of U-wave genesis, even with small differences in the repolarization. CONCLUSION: The U wave can be generated in the presence of strong intercellular coupling. Myocardial layers with prolonged action potentials, like M cells, are not necessarily needed for U-wave genesis.