@misc{Singh, author = {Singh, Max Diamond}, title = {MDR implementation status \& lessons learned}, language = {en} } @misc{Singh, author = {Singh, Max Diamond}, title = {Market Access for Devices under MDD and MDR: Obligations for Manufacturers}, series = {OSMA - Orthopedic Surgical Manufacturers Association, Winter Educational Program - virtual}, journal = {OSMA - Orthopedic Surgical Manufacturers Association, Winter Educational Program - virtual}, language = {en} } @article{OttRosengarthDoenitzetal., author = {Ott, Christian and Rosengarth, Katharina and Doenitz, Christian and Hoehne, Julius and Wendl, Christina and Dodoo-Schittko, Frank and Lang, Elmar Wolfgang and Schmidt, Nils Ole and Goldhacker, Markus}, title = {Preoperative Assessment of Language Dominance through Combined Resting-State and Task-Based Functional Magnetic Resonance Imaging}, series = {Journal of personalized medicine}, volume = {11}, journal = {Journal of personalized medicine}, number = {12}, publisher = {MDPI}, doi = {10.3390/jpm11121342}, abstract = {Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years, the resting-state fMRI (RS-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Twenty patients suffering from brain lesions close to supposed language-relevant cortical areas were included. RS-fMRI and task-based (TB-fMRI) were performed for the purpose of preoperative language assessment. TB-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language-critical and language-supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the TB-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice index. Thereby, the RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. In general, the results suggest that determining language dominance in the human brain is feasible both with TB-fMRI and RS-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.}, language = {en} } @misc{OttRosengarthDoenitzetal., author = {Ott, C. and Rosengarth, K. and Doenitz, Christian and Hoehne, J. and Wendl, C. and Dodoo-Schittko, Frank and Lang, E. and Schmidt, Nils Ole and Goldhacker, Markus}, title = {Preoperative assessment of language dominance through combined resting-state and task-based functional magnetic resonance imaging}, series = {Brain and Spine}, volume = {1}, journal = {Brain and Spine}, number = {Suppl. 2}, publisher = {Elsevier}, doi = {10.1016/j.bas.2021.100523}, abstract = {Background: Brain lesions in language-related cortical areas remain a challenge in the clinical routine. In recent years the resting-state fMRI (rs-fMRI) was shown to be a feasible method for preoperative language assessment. The aim of this study was to examine whether language-related resting-state components, which have been obtained using a data-driven independent-component-based identification algorithm, can be supportive in determining language dominance in the left or right hemisphere. Methods: Twenty patients suffering from brain lesions close to supposed language relevant cortical areas were included. Rs-fMRI and task-based (tb-fMRI) were performed for the purpose of preoperative language assessment. Tb-fMRI included a verb generation task with an appropriate control condition (a syllable switching task) to decompose language critical and language supportive processes. Subsequently, the best fitting ICA component for the resting-state language network (RSLN) referential to general linear models (GLMs) of the tb-fMRI (including models with and without linguistic control conditions) was identified using an algorithm based on the Dice-index. Results: The RSLNs associated with GLMs using a linguistic control condition led to significantly higher laterality indices than GLM baseline contrasts. LIs derived from GLM contrasts with and without control conditions alone did not differ significantly. Conclusion: In general, the results suggest that determining language dominance in the human brain is feasible both with tb-fMRI and rs-fMRI, and in particular, the combination of both approaches yields a higher specificity in preoperative language assessment. Moreover, we can conclude that the choice of the language mapping paradigm is crucial for the mentioned benefits.}, language = {en} } @article{WeinDecoTomeetal., author = {Wein, Simon and Deco, Gustavo and Tom{\´e}, Ana Maria and Goldhacker, Markus and Malloni, Wilhelm M. and Greenlee, Mark W. and Lang, Elmar Wolfgang}, title = {Brain Connectivity Studies on Structure-Function Relationships: A Short Survey with an Emphasis on Machine Learning}, series = {Computational intelligence and neuroscience}, journal = {Computational intelligence and neuroscience}, publisher = {Hindawi}, doi = {10.1155/2021/5573740}, pages = {1 -- 31}, abstract = {This short survey reviews the recent literature on the relationship between the brain structure and its functional dynamics. Imaging techniques such as diffusion tensor imaging (DTI) make it possible to reconstruct axonal fiber tracks and describe the structural connectivity (SC) between brain regions. By measuring fluctuations in neuronal activity, functional magnetic resonance imaging (fMRI) provides insights into the dynamics within this structural network. One key for a better understanding of brain mechanisms is to investigate how these fast dynamics emerge on a relatively stable structural backbone. So far, computational simulations and methods from graph theory have been mainly used for modeling this relationship. Machine learning techniques have already been established in neuroimaging for identifying functionally independent brain networks and classifying pathological brain states. This survey focuses on methods from machine learning, which contribute to our understanding of functional interactions between brain regions and their relation to the underlying anatomical substrate.}, language = {en} } @article{RillBauerKirchbeck, author = {Rill, Georg and Bauer, Florian and Kirchbeck, Mathias}, title = {VTT - a virtual test truck for modern simulation tasks}, series = {Vehicle system dynamics}, volume = {59}, journal = {Vehicle system dynamics}, number = {4}, publisher = {Taylor\&Francis}, doi = {10.1080/00423114.2019.1705356}, pages = {635 -- 656}, abstract = {The development of new technologies like advanced driver assistance systems or automated driving requires a flexible simulation environment of sufficient complexity. In general this flexibility is not provided by commercial software packages. This paper presents a three-dimensional and nonlinear hand-made model for heavy commercial vehicles including tractor and trailer as well as tractor and semitrailer combinations that can be used in different simulation environments, as well as in real-time applications. As typical for trucks, the torsional flexibility of the frame and a suspended driver's cabin are taken into account. The design kinematics makes it possible to handle different and quite complex axle suspensions very efficiently. Appropriate force elements are used to model various couplings between tractor and trailer or tractor and semitrailer, respectively. The virtual test truck environment (VTT) coded in ANSI C is extremely portable and can easily be embedded in commercial simulation packages like MATLAB/Simulink. It includes the TMeasy tyre model and offers flexible interfaces to third-party software tools.}, language = {en} } @article{RillBauerTopcagic, author = {Rill, Georg and Bauer, Florian and Topcagic, Edin}, title = {Performance of leaf spring suspended axles in model approaches of different complexities}, series = {Vehicle System Dynamics}, volume = {60}, journal = {Vehicle System Dynamics}, number = {8}, publisher = {Taylor\&Francis}, doi = {10.1080/00423114.2021.1928249}, pages = {2871 -- 2889}, abstract = {Axles with leaf spring suspension systems are still a popular choice in many commercial vehicles. However, leaf springs are not in perfect conformity to standard multibody vehicle models because they combine guidance and suspension in one single element. Combining standard multibody vehicle models with sophisticated finite element leaf spring models results in rather complex and computing time-consuming solutions. Purely kinematic models, defined by lookup tables or the design kinematics approach, cover only some but not all features of the leaf spring suspension. As shown here, the five-link model, which incorporates a quasi-static solution of the leaf spring compliance, provides a very practical model. It is comparatively lean and provides results of sufficient accuracy in the whole application range.}, language = {en} }