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The number of impaired persons rises -- as a result of both regular degradation with age and psychological problems like burnout. Sheltered work organizations aim to reintegrate impaired persons into work environments and prepare them for the re-entry in the regular job market.
Both for elderly and for impaired persons it is crucial to quickly assess the abilities, to identify limits and potentials and thus find work processes suitable for their skill profile.
This work focuses on the analysis and comparison of software-tools that assess the abilities of persons with impairments. We describe two established generic tools (CANTAB, Cogstate), analyze a yet unknown specialized tool (Hamet) and present a new gamified tool (GATRAS).
Finally, we present a study with 20 participants with impairments, comparing the tools against a ground truth baseline generated by a real-world assembly task.
This work documents the rising acceptance of social robots for healthcare as well as their growing economic potential from 2017 to 2021. The comparison is based on two studies in the active assisted living (AAL) community. We first provide a brief overview of social robotics and a discussion of the economic potential of social health robots. We found that, despite the huge potential for robotic support in healthcare and domestic routines, social robots still lack the functionality to access that potential. At the same time, the study exemplifies a rise in acceptance: all health-related activities are more accepted in 2021 when in 2017, most of them with high statistical significance. When investigating the economic perspective, we found that persons are aware of the influence of cultural, spiritual, or religious beliefs. Most experts (57%), having a European background, expect the state or the government to be the key driver for establishing social robots in health and significantly prefer leasing or renting a social health robot to buying one. Nevertheless, we speculate that it might be a global financial elite which is first to adopt social robots.
A smart energy concept was designed and implemented for a cluster of 5 existing multi-family houses, which combines heat pumps, photovoltaic (PV) modules and combined heat and power units (CHP) to achieve energy- and cost-efficient operation. Measurement results of the first year of operation show that the local power generation by PV modules and CHP unit has a positive effect on the electrical self-sufficiency by reducing electricity import from the grid. In winter, when the CHP unit operates continuously for long periods, the entire electricity for the heat pump and 91 % of the total electricity demand of the neighborhood are supplied locally. In summer, only 53 % is generated within the neighborhood. The use of a specifically developed energy management system EMS is intended to further increase this share. CO2 emissions for heating and electricity of the neighborhood are evaluated and amount to 18.4 kg/(m2a). Compared to the previous energy system consisting of gas boilers (29.1 kg/(m2a)), savings of 37 % are achieved with electricity consumption from the grid being reduced by 65 %. In the second construction stage, an additional heat pump, CHP unit and PV modules will be added. The measurement results indicate that the final district energy system is likely to achieve the ambitious CO2 reduction goal of -50% and further increase the self-sufficiency of the district.
Background: The electrical field (E-field) of the biventricular (BV) stimulation is essential for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex. 3D modeling allows the simulation of CRT and high frequency (HF) ablation.
Purpose: The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
Methods: The modeling and simulation was carried out using the electromagnetic simulation software. Five multipolar left ventricular (LV) electrodes, one epicardial LV electrode, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modeled. Different models of electrodes were integrated into a heart rhythm model for the electrical field simulation (fig.1). The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
Results: The RV and LV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode, each with a pulse width of 0.5 ms. The far-field potentials generated by the BV stimulations were perceived by the RA electrode. The far-field potential at the RA electrode tip was 32.86 mV. A far-field potential of 185.97 mV resulted at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal 8 mm ablation electrode. The temperature at the catheter tip was 103.87 ° C after 5 s ablation time, 44.17 ° C from the catheter tip in the myocardium and 37.61 ° C at a distance of 2 mm. After 10 s, the temperature at the three measuring points described above was 107.33 ° C, 50.87 ° C, 40.05 ° C and after 15 seconds 118.42 ° C, 55.75 ° C and 42.13 ° C.
Conclusions: Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF. The 3D simulation of the electrical field and temperature profile may be used to optimize the CRT and AF ablation.
The electrical field (E-field) of the biventricular (BV) stimulation is important for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex.
The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
The modeling and simulation was carried out using the electromagnetic simulation software CST. Five multipolar left ventricular (LV) electrodes, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modelled. A selection were integrated into the heart rhythm model (Schalk, Offenburg) for the electrical field simulation. The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
The BV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode with a pulse width of 0.5 ms each. The far-field potential at the RA electrode tip was 32.86 mV and 185.97 mV at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal ablation electrode. The temperature at the catheter tip was 103.87 °C after 5 s ablation time and 37.61 °C at a distance of 2 mm inside the myocardium. After 15 s, the temperature was 118.42 °C and 42.13 °C.
Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF and could be used to optimize the CRT and AF ablation.
Modelling detailed chemistry in lithium-ion batteries: Insight into performance, ageing and safety
(2018)
Muli-scale thermos-electrochemical modelling of aging mechanisms in an LFP/graphite lithium-ion cell
(2017)
ECG simulators, available on the market, imitate the electric activity of the heart in a simplified manner. Thus, they are suitable for education purposes but not really for testing algorithms to recognize complex arrhythmias needed for pacemakers and implantable defibrillators. Especially certain discrimination between various morphologies of atrial and ventricular fibrillation needs simulators providing native electrograms of different patients’ heart rhythm events. This explains the necessity to develop an ECG simulator providing high-resolution native intracardiac and surface electrograms of in-vivo rhythm events. In this paper we demonstrate an approach for an ECG simulator based on a consumer multichannel soundcard and a corresponding software application for a laptop computer. This Live-ECG Simulator is able to handle invasive electrogram recordings from electrophysiological studies and send the data to a modified external soundcard for subsequent digital to analog conversion. The hardware is completed with an electronic circuit providing level adjustment to adapt the output amplitude to the input conditions of several cardiac implants.
Active safety systems for advanced driver assistance systems act within a complex, dynamic traffic environment featuring various sensor systems which detect the vehicles’ surroundings and interior. This paper describes the recent progress towards a performance evaluation of car-to-car communication (C2C) for active safety systems - in particular for crash constellation prediction. The methodology introduced in this work is designed to evaluate the impact of different sensors on the accuracy of a crash constellation prediction algorithm. The benefit of C2C communication (viewed as a virtual sensor) within a sensor data fusion architecture for pre-crash collision prediction is explored. Therefore, a simulation environment for accident scenarios analysis reproducing real-world sensor behaviour, is designed and implemented. Performance evaluation results show that C2C increases confidence in the estimated position of the oncoming vehicle. With C2C enhancement the given accuracy in time-to-collision (TTC) estimation is achievable about 110 ms earlier for moderate velocities at TTC range of [0.5s..0.2s]. The uncertainty in the vehicle position prediction at the time of collision can be reduced about half by integrating C2C communication into the sensor data fusion.
New frontiers of supraventricular tachycardia and atrial flutter evaluation and catheter ablation
(2012)
Radiofrequency catheter ablation (RFCA) has revolutionized treatment for tachyarrhythmias and has become first-line therapy for some tachycardias. Although developed in the 1980s and widely applied in the 1990s, the technique is still in development. Transesophageal atrial pacing (TAP) can used for initiation and termination of supraventricular tachycardia (SVT).
Methods: The paroxysmal SVT include a wide spectrum of disorders including, in descending order of frequency, atrial flutter, atrioventricular (AV) nodal reentry, Wolff-Parkinson-White syndrome, and atrial tachycardia. While not life-threatening in most cases, they may cause important symptoms, such as palpitations, chest discomfort, breathlessness, anxiety, and syncope, which significantly impair quality of life. Medical therapy has variable efficacy, and most patients are not rendered free of symptoms. Research over the past several decades has revealed fundamental mechanisms involved in the initiation and maintenance of all of these arrhythmias. Knowledge of mechanisms has in turn led to highly effective surgical and catheter-based treatments. The supraventricular arrhythmias and their treatment are described in this report. SVT initiation was analysed with programmed TAP in 49 patients with palpitations (age 47 ± 17 years, 24 females, 25 males).
Results: In comparison to antiarrhythmic drug therapy the radiofrequency catheter ablation in patients suffering from atrial flutter, atrioventricular nodal reentry, atrioventricular reentry and atrial tachycardia is the better choice in most cases. TAP SVT initiation was possible in 23 patients before RFCA. Atrial cycle length of SVT was 320 ± 59 ms. We initiated AV nodal reentrant tachycardia (AVNRT, n=15), atrial tachycardia (AT, n=6) and AV reentrant tachycardia with Kent pathway conduction (AVRT, n=2) before RFCA.
Conclusions: Radiofrequency catheter ablation is a successful and safe method to cure most patients with paroxysmal supraventricular tachycardias. TAP allowed initiation and termination of SVT especially in outpatients.
In this paper, we describe a first publicly available fine-grained product recognition dataset based on leaflet images. Using advertisement leaflets, collected over several years from different European retailers, we provide a total of 41.6k manually annotated product images in 832 classes. Further, we investigate three different approaches for this fine-grained product classification task, Classification by Image, by Text, as well as by Image and Text. The approach "Classification by Text" uses the text extracted directly from the leaflet product images. We show, that the combination of image and text as input improves the classification of visual difficult to distinguish products. The final model leads to an accuracy of 96.4% with a Top-3 score of 99.2%. We release our code at https://github.com/ladwigd/Leaflet-Product-Classification.
In medical applications wireless technologies are not widely spread. Today they are mainly used in non latency-critical applications where reliability can be guaranteed through retransmission protocols and error correction mechanisms. By using retransmission protocols within the disturbed shared wireless channel latency will increase. Therefore retransmission protocols are not sufficient for removing latency-critical wired connections within operating rooms such as foot switches. Todays research aims to improve reliability through the physical characteristics of the wireless channel by using diversity methods and more robust modulation. In this paper an Architecture for building up a reliable network is presented. The Architecture offers the possibility for devices with different reliability, latency and energy consumption requirements to participate. Furthermore reliability, latency and energy consumption are scalable for every single participant.
During the day-to-day exploitation of localization systems in mines, the technical staff tends to incorrectly rearrange radio equipment: positions of devices may not be accurately marked on a map or their positions may not correspond to the truth. This situation may lead to positioning inaccuracies and errors in the operation of the localization system.This paper presents two Bayesian algorithms for the automatic corrections of positions of the equipment on the map using trajectories restored by the inertial measurement units mounted to mobile objects, like pedestrians and vehicles. As a basis, a predefined map of the mine represented as undirected weighted graph was used as input. The algorithms were implemented using the Simultaneous Localization and Mapping (SLAM) approach.The results prove that both methods are capable to detect misplacement of access points and to provide corresponding corrections. The discrete Bayesian filter outperforms the unscented Kalman filter, which, however, requires more computational power.
This paper presents an extended version of a previously published Bayesian algorithm for the automatic correction of the positions of the equipment on the map with simultaneous mobile object trajectory localization (SLAM) in underground mine environment represented by undirected graph. The proposed extended SLAM algorithm requires much less preliminary data on possible equipment positions and uses an additional resample move algorithm to significantly improve the overall performance.
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset where, a subspace is the subset of dimensions of the data. But exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, thus, parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage, firstly, the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation has shown linear speedup. Secondly, we are developing an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.