904 resultados para motion-based driving simulator
Resumo:
Patients with an implantable cardioverter defibrillator (ICD) have an ongoing risk of sudden incapacitation that might cause harm to others while driving a car. Driving restrictions vary across different countries in Europe. The most recent recommendations for driving of ICD patients in Europe were published in 1997 and focused mainly on patients implanted for secondary prevention. In recent years there has been a vast increase in the number of patients with an ICD and in the percentage of patients implanted for primary prevention. The EHRA task force on ICD and driving was formed to reassess the risk of driving for ICD patients based on the literature available. The recommendations are summarized in the following table and are further explained in the document. [table: see text] Driving restrictions are perceived as difficult for patients and their families, and have an immediate consequence for their lifestyle. To increase the adherence to the driving restrictions, adequate discharge of education and follow-up of patients and family are pivotal. The task force members hope this document may serve as an instrument for European and national regulatory authorities to formulate uniform driving regulations.
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Methods for optical motion capture often require timeconsuming manual processing before the data can be used for subsequent tasks such as retargeting or character animation. These processing steps restrict the applicability of motion capturing especially for dynamic VR-environments with real time requirements. To solve these problems, we present two additional, fast and automatic processing stages based on our motion capture pipeline presented in [HSK05]. A normalization step aligns the recorded coordinate systems with the skeleton structure to yield a common and intuitive data basis across different recording sessions. A second step computes a parameterization based on automatically extracted main movement axes to generate a compact motion description. Our method does not restrict the placement of marker bodies nor the recording setup, and only requires a short calibration phase.
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In this paper, we investigate how a multilinear model can be used to represent human motion data. Based on technical modes (referring to degrees of freedom and number of frames) and natural modes that typically appear in the context of a motion capture session (referring to actor, style, and repetition), the motion data is encoded in form of a high-order tensor. This tensor is then reduced by using N-mode singular value decomposition. Our experiments show that the reduced model approximates the original motion better then previously introduced PCA-based approaches. Furthermore, we discuss how the tensor representation may be used as a valuable tool for the synthesis of new motions.
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In this paper we present a hybrid method to track human motions in real-time. With simplified marker sets and monocular video input, the strength of both marker-based and marker-free motion capturing are utilized: A cumbersome marker calibration is avoided while the robustness of the marker-free tracking is enhanced by referencing the tracked marker positions. An improved inverse kinematics solver is employed for real-time pose estimation. A computer-visionbased approach is applied to refine the pose estimation and reduce the ambiguity of the inverse kinematics solutions. We use this hybrid method to capture typical table tennis upper body movements in a real-time virtual reality application.
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Let us consider a large set of candidate parameter fields, such as hydraulic conductivity maps, on which we can run an accurate forward flow and transport simulation. We address the issue of rapidly identifying a subset of candidates whose response best match a reference response curve. In order to keep the number of calls to the accurate flow simulator computationally tractable, a recent distance-based approach relying on fast proxy simulations is revisited, and turned into a non-stationary kriging method where the covariance kernel is obtained by combining a classical kernel with the proxy. Once the accurate simulator has been run for an initial subset of parameter fields and a kriging metamodel has been inferred, the predictive distributions of misfits for the remaining parameter fields can be used as a guide to select candidate parameter fields in a sequential way. The proposed algorithm, Proxy-based Kriging for Sequential Inversion (ProKSI), relies on a variant of the Expected Improvement, a popular criterion for kriging-based global optimization. A statistical benchmark of ProKSI’s performances illustrates the efficiency and the robustness of the approach when using different kinds of proxies.
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Purpose Femoral fracture is a common medical problem in osteoporotic individuals. Bone mineral density (BMD) is the gold standard measure to evaluate fracture risk in vivo. Quantitative computed tomography (QCT)-based homogenized voxel finite element (hvFE) models have been proved to be more accurate predictors of femoral strength than BMD by adding geometrical and material properties. The aim of this study was to evaluate the ability of hvFE models in predicting femoral stiffness, strength and failure location for a large number of pairs of human femora tested in two different loading scenarios. Methods Thirty-six pairs of femora were scanned with QCT and total proximal BMD and BMC were evaluated. For each pair, one femur was positioned in one-legged stance configuration (STANCE) and the other in a sideways configuration (SIDE). Nonlinear hvFE models were generated from QCT images by reproducing the same loading configurations imposed in the experiments. For experiments and models, the structural properties (stiffness and ultimate load), the failure location and the motion of the femoral head were computed and compared. Results In both configurations, hvFE models predicted both stiffness (R2=0.82 for STANCE and R2=0.74 for SIDE) and femoral ultimate load (R2=0.80 for STANCE and R2=0.85 for SIDE) better than BMD and BMC. Moreover, the models predicted qualitatively well the failure location (66% of cases) and the motion of the femoral head. Conclusions The subject specific QCT-based nonlinear hvFE model cannot only predict femoral apparent mechanical properties better than densitometric measures, but can additionally provide useful qualitative information about failure location.
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In this paper we present a solution to the problem of action and gesture recognition using sparse representations. The dictionary is modelled as a simple concatenation of features computed for each action or gesture class from the training data, and test data is classified by finding sparse representation of the test video features over this dictionary. Our method does not impose any explicit training procedure on the dictionary. We experiment our model with two kinds of features, by projecting (i) Gait Energy Images (GEIs) and (ii) Motion-descriptors, to a lower dimension using Random projection. Experiments have shown 100% recognition rate on standard datasets and are compared to the results obtained with widely used SVM classifier.
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During the last decade, medical education in the German-speaking world has been striving to become more practice-oriented. This is currently being achieved in many schools through the implementation of simulation-based instruction in Skills Labs. Simulators are thus an essential part of this type of medical training, and their acquisition and operation by a Skills Lab require a large outlay of resources. Therefore, the Practical Skills Committee of the Medical Education Society (GMA) introduced a new project, which aims to improve the flow of information between the Skills Labs and enable a transparent assessment of the simulators via an online database (the Simulator Network).
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Recently developed technologies allow aortic valve implantation off-pump in a beating heart. In this procedure, the native, stenotic aortic valve is not removed, but simply crushed by a pressure balloon mounted on a percutaneous catheter. Removal of the native aortic cusps before valve replacement may reduce the incidence of annular or cuspal calcium embolization and late perivalvular leaks and increase implantable valve size. However, a temporary valve system in the ascending aorta may be necessary to maintain hemodynamic stability by reducing acute aortic regurgitation and left ventricular volume overload. This study evaluates the hemodynamic effects of a wire-mounted, monoleaflet, temporary valve apparatus in a mechanical cardiovascular simulator. Aortic flow, systemic pressure and left ventricular pressure were continuously monitored. An intraluminal camera obtained real-time proximal and distal images of the valve in operation. Insertion of the parachute valve in the simulator increased diastolic pressure from 7 to 38 mm Hg. Cardiac output increased from 2.08 to 4.66 L/min and regurgitant volume decreased from 65 to 23 mL. In conclusion, placement of a temporary valve in the ascending aorta may help maintain hemodynamic stability and improve off-pump aortic valve replacement.
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Previous analyses of aortic displacement and distension using computed tomography angiography (CTA) were performed on double-oblique multi-planar reformations and did not consider through-plane motion. The aim of this study was to overcome this limitation by using a novel computational approach for the assessment of thoracic aortic displacement and distension in their true four-dimensional extent. Vessel segmentation with landmark tracking was executed on CTA of 24 patients without evidence of aortic disease. Distension magnitudes and maximum displacement vectors (MDV) including their direction were analyzed at 5 aortic locations: left coronary artery (COR), mid-ascending aorta (ASC), brachiocephalic trunk (BCT), left subclavian artery (LSA), descending aorta (DES). Distension was highest for COR (2.3 ± 1.2 mm) and BCT (1.7 ± 1.1 mm) compared with ASC, LSA, and DES (p < 0.005). MDV decreased from COR to LSA (p < 0.005) and was highest for COR (6.2 ± 2.0 mm) and ASC (3.8 ± 1.9 mm). Displacement was directed towards left and anterior at COR and ASC. Craniocaudal displacement at COR and ASC was 1.3 ± 0.8 and 0.3 ± 0.3 mm. At BCT, LSA, and DES no predominant displacement direction was observable. Vessel displacement and wall distension are highest in the ascending aorta, and ascending aortic displacement is primarily directed towards left and anterior. Craniocaudal displacement remains low even close to the left cardiac ventricle.
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BACKGROUND: The observation of conspecifics influences our bodily perceptions and actions: Contagious yawning, contagious itching, or empathy for pain, are all examples of mechanisms based on resonance between our own body and others. While there is evidence for the involvement of the mirror neuron system in the processing of motor, auditory and tactile information, it has not yet been associated with the perception of self-motion. METHODOLOGY/PRINCIPAL FINDINGS: We investigated whether viewing our own body, the body of another, and an object in motion influences self-motion perception. We found a visual-vestibular congruency effect for self-motion perception when observing self and object motion, and a reduction in this effect when observing someone else's body motion. The congruency effect was correlated with empathy scores, revealing the importance of empathy in mirroring mechanisms. CONCLUSIONS/SIGNIFICANCE: The data show that vestibular perception is modulated by agent-specific mirroring mechanisms. The observation of conspecifics in motion is an essential component of social life, and self-motion perception is crucial for the distinction between the self and the other. Finally, our results hint at the presence of a "vestibular mirror neuron system".
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OBJECTIVE This study aimed to develop a pathway to bring together current UK legislation, good clinical practice and appropriate management strategies that could be applied across a range of healthcare settings. METHODS The pathway was constructed by a multidisciplinary clinical team based in a busy Memory Assessment Service. A process of successive iteration was used to develop the pathway, with input and refinement provided via survey and small group meetings with individuals from a wide range of regional clinical networks and diverse clinical backgrounds as well as discussion with mobility centres and Forum of Mobility Centres, UK. RESULTS We present a succinct clinical pathway for patients with dementia, which provides a decision-making framework for how health professionals across a range of disciplines deal with patients with dementia who drive. CONCLUSIONS By integrating the latest guidance from diverse roles within older people's health services and key experts in the field, the resulting pathway reflects up-to-date policy and encompasses differing perspectives and good practice. It is potentially a generalisable pathway that can be easily adaptable for use internationally, by replacing UK legislation for local regulations. A limitation of this pathway is that it does not address the concern of mild cognitive impairment and how this condition relates to driving safety. © 2014 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons, Ltd.
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Fitness to drive in elderly drivers is most commonly discussed with a focus on cognitive impairment. Therefore, this article is focussing on mental illness and the use of psychotropic drugs in elderly drivers, which can both interfere with fitness to drive. Based on a detailed literature review and on clinical judgement, we propose signposts and "red flags" to judge the individual risks. Health professionals dealing with elderly patients should in particular be aware of the dangers related to cumulative risks and need to inform the patients appropriately. For medico-legal reasons the information provided to patients must be written down in the medical record. Individual counselling is important as fitness to drive is a complex topic.
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Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.
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Attractive business cases in various application fields contribute to the sustained long-term interest in indoor localization and tracking by the research community. Location tracking is generally treated as a dynamic state estimation problem, consisting of two steps: (i) location estimation through measurement, and (ii) location prediction. For the estimation step, one of the most efficient and low-cost solutions is Received Signal Strength (RSS)-based ranging. However, various challenges - unrealistic propagation model, non-line of sight (NLOS), and multipath propagation - are yet to be addressed. Particle filters are a popular choice for dealing with the inherent non-linearities in both location measurements and motion dynamics. While such filters have been successfully applied to accurate, time-based ranging measurements, dealing with the more error-prone RSS based ranging is still challenging. In this work, we address the above issues with a novel, weighted likelihood, bootstrap particle filter for tracking via RSS-based ranging. Our filter weights the individual likelihoods from different anchor nodes exponentially, according to the ranging estimation. We also employ an improved propagation model for more accurate RSS-based ranging, which we suggested in recent work. We implemented and tested our algorithm in a passive localization system with IEEE 802.15.4 signals, showing that our proposed solution largely outperforms a traditional bootstrap particle filter.