31 results on '"Kober J"'
Search Results
2. OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics
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Passalis, N., Pedrazzi, S., Babuska, R., Burgard, W., Dias, D., Ferro, F., Gabbouj, M., Green, O., Iosifidis, A., Kayacan, E., Kober, J., Michel, O., Nikolaidis, N., Nousi, P., Pieters, R., Tzelepi, M., Valada, A., and Tefas, A.
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Computer Science - Robotics ,Computer Science - Artificial Intelligence - Abstract
Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their relatively steep learning curve and the different methodologies employed by DL compared to traditional approaches, along with the high complexity of DL models, which often leads to the need of employing specialized hardware accelerators, further increase the effort and cost needed to employ DL models in robotics. Also, most of the existing DL methods follow a static inference paradigm, as inherited by the traditional computer vision pipelines, ignoring active perception, which can be employed to actively interact with the environment in order to increase perception accuracy. In this paper, we present the Open Deep Learning Toolkit for Robotics (OpenDR). OpenDR aims at developing an open, non-proprietary, efficient, and modular toolkit that can be easily used by robotics companies and research institutions to efficiently develop and deploy AI and cognition technologies to robotics applications, providing a solid step towards addressing the aforementioned challenges. We also detail the design choices, along with an abstract interface that was created to overcome these challenges. This interface can describe various robotic tasks, spanning beyond traditional DL cognition and inference, as known by existing frameworks, incorporating openness, homogeneity and robotics-oriented perception e.g., through active perception, as its core design principles.
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- 2022
3. Hybrid experimental/computational approach to Time Reversal source localization in thin plates using image source method
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Zeman, R., Kober, J., Scalerandi, M., Krofta, J., and Chlada, M.
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- 2024
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4. Reactive ion beam smoothing of rapidly solidified aluminum (RSA) 501 surfaces for potential visible and ultraviolet light applications
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Hölzel, F., Rolón, D., Bauer, J., Kober, J., Kühne, S., Pietag, F., Oberschmidt, D., and Arnold, T.
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- 2023
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5. Forces and movements during tooth extraction: A scoping review
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Beuling, M.G., Agterbos, P.C.G., van Riet, T.C.T., Ho, J.P.T.F., de Vries, R., Kober, J., and de Lange, J.
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- 2023
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6. Health care effects and medical benefits of a smartphone-based diabetes self-management application: study protocol for a randomized controlled trial
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Ehrmann, D., Eichinger, V., Vesper, I., Kober, J., Kraus, M., Schäfer, V., Hermanns, N., Kulzer, B., and Silbermann, S.
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- 2022
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7. A review on machine learning in flexible surgical and interventional robots: Where we are and where we are going
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Wu, D. (author), Zhang, R. (author), Pore, Ameya (author), Ha, Xuan Thao (author), Li, Z. (author), Herrera, Fernando (author), Kowalczyk, Wojtek (author), De Momi, Elena (author), Dankelman, J. (author), Kober, J. (author), Wu, D. (author), Zhang, R. (author), Pore, Ameya (author), Ha, Xuan Thao (author), Li, Z. (author), Herrera, Fernando (author), Kowalczyk, Wojtek (author), De Momi, Elena (author), Dankelman, J. (author), and Kober, J. (author)
- Abstract
Minimally Invasive Procedures (MIPs) emerged as an alternative to more invasive surgical approaches, offering patient benefits such as smaller incisions, less pain, and shorter hospital stay. In one class of MIPs, where natural body lumens or small incisions are used to access deeper anatomical locations, Flexible Surgical and Interventional Robots (FSIRs) such as catheters and endoscopes are widely used. Due to their flexible and compliant nature, FSIRs can be inserted via natural orifices or small incisions, then moved towards hard-to-reach targets to perform interventional tasks. However, existing FSIRs are confronted with challenges in sensing, control, and navigation. These issues stem from the robot's non-linear behavior and the intricate nature of the lumens, where accurately modeling the complex interactions and disturbances proves to be exceptionally difficult. The rapid advances in Machine Learning (ML) have facilitated the widespread adoption of ML techniques in FSIRs. This article provides an overview of these efforts by first introducing a classification of existing ML algorithms, including traditional ML methods and modern Deep Learning (DL) approaches, commonly used in FSIRs. Next, the use of ML algorithms is surveyed per sub-domain, namely for perception, modeling, control, and navigation. Trends, popularity, strengths, and/or limitations of different ML algorithms are analyzed. The different roles that ML plays among tasks are investigated and described. Finally, discussions are conducted on the limitations and the prospects of ML in MIPs., Medical Instruments & Bio-Inspired Technology, Human-Robot Interaction, Learning & Autonomous Control
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- 2024
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8. Using Models Based on Cognitive Theory to Predict Human Behavior in Traffic: A Case Study
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Schumann, J.F. (author), Srinivasan, Aravinda R. (author), Kober, J. (author), Markkula, Gustav (author), Zgonnikov, A. (author), Schumann, J.F. (author), Srinivasan, Aravinda R. (author), Kober, J. (author), Markkula, Gustav (author), and Zgonnikov, A. (author)
- Abstract
The development of automated vehicles has the potential to revolutionize transportation, but they are currently unable to ensure a safe and time-efficient driving style. Reliable models predicting human behavior are essential for overcoming this issue. While data-driven models are commonly used to this end, they can be vulnerable in safety-critical edge cases. This has led to an interest in models incorporating cognitive theory, but as such models are commonly developed for explanatory purposes, this approach's effectiveness in behavior prediction has remained largely untested so far. In this article, we investigate the usefulness of the Commotions model - a novel cognitively plausible model incorporating the latest theories of human perception, decision-making, and motor control - for predicting human behavior in gap acceptance scenarios, which entail many important traffic interactions such as lane changes and intersections. We show that this model can compete with or even outperform well-established data-driven prediction models across several naturalistic datasets. These results demonstrate the promise of incorporating cognitive theory in behavior prediction models for automated vehicles., Human-Robot Interaction, Learning & Autonomous Control
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- 2023
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9. Stable Motion Primitives via Imitation and Contrastive Learning
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Pérez-Dattari, Rodrigo (author), Kober, J. (author), Pérez-Dattari, Rodrigo (author), and Kober, J. (author)
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Learning from humans allows nonexperts to program robots with ease, lowering the resources required to build complex robotic solutions. Nevertheless, such data-driven approaches often lack the ability to provide guarantees regarding their learned behaviors, which is critical for avoiding failures and/or accidents. In this work, we focus on reaching/point-to-point motions, where robots must always reach their goal, independently of their initial state. This can be achieved by modeling motions as dynamical systems and ensuring that they are globally asymptotically stable. Hence, we introduce a novel Contrastive Learning loss for training deep neural networks (DNN) that, when used together with an Imitation Learning loss, enforces the aforementioned stability in the learned motions. Differently from previous work, our method does not restrict the structure of its function approximator, enabling its use with arbitrary DNNs and allowing it to learn complex motions with high accuracy. We validate it using datasets and a real robot. In the former case, motions are two- and four-dimensional, modeled as first- and second-order dynamical systems. In the latter, motions are three, four, and six-dimensional, of first and second order, and are used to control a 7-DoF robot manipulator in its end effector space and joint space., Learning & Autonomous Control
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- 2023
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10. Probabilistic Risk Assessment for Chance-Constrained Collision Avoidance in Uncertain Dynamic Environments
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Khaled Mustafa, K.A. (author), de Groot, O.M. (author), Wang, X. (author), Kober, J. (author), Alonso-Mora, J. (author), Khaled Mustafa, K.A. (author), de Groot, O.M. (author), Wang, X. (author), Kober, J. (author), and Alonso-Mora, J. (author)
- Abstract
Balancing safety and efficiency when planning in crowded scenarios with uncertain dynamics is challenging where it is imperative to accomplish the robot's mission without incurring any safety violations. Typically, chance constraints are incorporated into the planning problem to provide probabilistic safety guarantees by imposing an upper bound on the collision probability of the planned trajectory. Yet, this results in an overly conservative behavior on the grounds that the gap between the obtained risk and the specified upper limit is not explicitly restricted. To address this issue, we propose a real-time capable approach to quantify the risk associated with planned trajectories obtained from multiple probabilistic planners, running in parallel, with different upper bounds of the acceptable risk level. Based on the evaluated risk, the least conservative plan is selected provided that its associated risk is below a specified threshold. In such a way, the proposed approach provides probabilistic safety guarantees by attaining a closer bound to the specified risk, while being applicable to generic uncertainties of moving obstacles. We demonstrate the efficiency of our proposed approach, by improving the performance of a state-of-the-art probabilistic planner, in simulations and experiments using a mobile robot in an environment shared with humans., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Learning & Autonomous Control
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- 2023
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11. Analysis of movements in tooth removal procedures using robot technology
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van Riet, T.C.T. (author), de Graaf, W.M. (author), de Lange, Jan (author), Kober, J. (author), van Riet, T.C.T. (author), de Graaf, W.M. (author), de Lange, Jan (author), and Kober, J. (author)
- Abstract
Being one of the oldest en most frequently performed invasive procedures; the lack of scientific progress of tooth removal procedures is impressive. This has most likely to do with technical limitations in measuring different aspects of these keyhole procedures. The goal of this study is to accurately capture the full range of motions during tooth removal as well as angular velocities in clinically relevant directions. An ex vivo measuring setup was designed consisting of, amongst others, a compliant robot arm. To match clinical conditions as closely as possible, fresh-frozen cadavers were used as well as regular dental forceps mounted on the robot’s end-effector. Data on 110 successful tooth removal experiments are presented in a descriptive manner. Rotation around the longitudinal axis of the tooth seems to be most dominant both in range of motion as in angular velocity. Buccopalatal and buccolingual movements are more pronounced in the dorsal region of both upper and lower jaw. This study quantifies an order of magnitude regarding ranges of motion and angular velocities in tooth removal procedures. Improved understanding of these complex procedures could aid in the development of evidence-based educational material., Learning & Autonomous Control
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- 2023
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12. Benchmarking Behavior Prediction Models in Gap Acceptance Scenarios
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Schumann, J.F. (author), Kober, J. (author), Zgonnikov, A. (author), Schumann, J.F. (author), Kober, J. (author), and Zgonnikov, A. (author)
- Abstract
Autonomous vehicles currently suffer from a time-inefficient driving style caused by uncertainty about human behavior in traffic interactions. Accurate and reliable prediction models enabling more efficient trajectory planning could make autonomous vehicles more assertive in such interactions. However, the evaluation of such models is commonly oversimplistic, ignoring the asymmetric importance of prediction errors and the heterogeneity of the datasets used for testing. We examine the potential of recasting interactions between vehicles as gap acceptance scenarios and evaluating models in this structured environment. To that end, we develop a framework aiming to facilitate the evaluation of any model, by any metric, and in any scenario. We then apply this framework to state-of-the-art prediction models, which all show themselves to be unreliable in the most safety-critical situations., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Human-Robot Interaction, Learning & Autonomous Control
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- 2023
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13. An Incremental Inverse Reinforcement Learning Approach for Motion Planning with Separated Path and Velocity Preferences
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Avaei, S. (author), van der Spaa, L.F. (author), Peternel, L. (author), Kober, J. (author), Avaei, S. (author), van der Spaa, L.F. (author), Peternel, L. (author), and Kober, J. (author)
- Abstract
Humans often demonstrate diverse behaviors due to their personal preferences, for instance, related to their individual execution style or personal margin for safety. In this paper, we consider the problem of integrating both path and velocity preferences into trajectory planning for robotic manipulators. We first learn reward functions that represent the user path and velocity preferences from kinesthetic demonstration. We then optimize the trajectory in two steps, first the path and then the velocity, to produce trajectories that adhere to both task requirements and user preferences. We design a set of parameterized features that capture the fundamental preferences in a pick-and-place type of object transportation task, both in the shape and timing of the motion. We demonstrate that our method is capable of generalizing such preferences to new scenarios. We implement our algorithm on a Franka Emika 7-DoF robot arm and validate the functionality and flexibility of our approach in a user study. The results show that non-expert users are able to teach the robot their preferences with just a few iterations of feedback., Biomechatronics & Human-Machine Control, Human-Robot Interaction, Learning & Autonomous Control
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- 2023
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14. Knowledge- and ambiguity-aware robot learning from corrective and evaluative feedback
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Celemin, Carlos (author), Kober, J. (author), Celemin, Carlos (author), and Kober, J. (author)
- Abstract
In order to deploy robots that could be adapted by non-expert users, interactive imitation learning (IIL) methods must be flexible regarding the interaction preferences of the teacher and avoid assumptions of perfect teachers (oracles), while considering they make mistakes influenced by diverse human factors. In this work, we propose an IIL method that improves the human–robot interaction for non-expert and imperfect teachers in two directions. First, uncertainty estimation is included to endow the agents with a lack of knowledge awareness (epistemic uncertainty) and demonstration ambiguity awareness (aleatoric uncertainty), such that the robot can request human input when it is deemed more necessary. Second, the proposed method enables the teachers to train with the flexibility of using corrective demonstrations, evaluative reinforcements, and implicit positive feedback. The experimental results show an improvement in learning convergence with respect to other learning methods when the agent learns from highly ambiguous teachers. Additionally, in a user study, it was found that the components of the proposed method improve the teaching experience and the data efficiency of the learning process., Learning & Autonomous Control
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- 2023
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15. Learning from Demonstrations of Critical Driving Behaviours Using Driver's Risk Field
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Du, Yurui (author), Acerbo, Flavia Sofia (author), Kober, J. (author), Son, Tong Duy (author), Du, Yurui (author), Acerbo, Flavia Sofia (author), Kober, J. (author), and Son, Tong Duy (author)
- Abstract
In recent years, imitation learning (IL) has been widely used in industry as the core of autonomous vehicle (AV) planning modules. However, previous IL works show sample inefficiency and low generalisation in safety-critical scenarios, on which they are rarely tested. As a result, IL planners can reach a performance plateau where adding more training data ceases to improve the learnt policy. First, our work presents an IL model using the spline coefficient parameterisation and offline expert queries to enhance safety and training efficiency. Then, we expose the weakness of the learnt IL policy by synthetically generating critical scenarios through optimisation of parameters of the driver's risk field (DRF), a parametric human driving behaviour model implemented in a multi-agent traffic simulator based on the Lyft Prediction Dataset. To continuously improve the learnt policy, we retrain the IL model with augmented data. Thanks to the expressivity and interpretability of the DRF, the desired driving behaviours can be encoded and aggregated to the original training data. Our work constitutes a full development cycle that can efficiently and continuously improve the learnt IL policies in closed-loop. Finally, we show that our IL planner developed with less training resource still has superior performance compared to the previous state-of-the-art., Learning & Autonomous Control
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- 2023
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16. Robotic Packaging Optimization with Reinforcement Learning
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Drijver, Eveline (author), Pérez-Dattari, Rodrigo (author), Kober, J. (author), Della Santina, C. (author), Ajanović, Z. (author), Drijver, Eveline (author), Pérez-Dattari, Rodrigo (author), Kober, J. (author), Della Santina, C. (author), and Ajanović, Z. (author)
- Abstract
Intelligent manufacturing is becoming increasingly important due to the growing demand for maximizing productivity and flexibility while minimizing waste and lead times. This work investigates automated secondary robotic food packaging solutions that transfer food products from the conveyor belt into containers. A major problem in these solutions is varying product supply which can cause drastic productivity drops. Conventional rule-based approaches, used to address this issue, are often inadequate, leading to violation of the industry's requirements. Reinforcement learning, on the other hand, has the potential of solving this problem by learning responsive and predictive policy, based on experience. However, it is challenging to utilize it in highly complex control schemes. In this paper, we propose a reinforcement learning framework, designed to optimize the conveyor belt speed while minimizing interference with the rest of the control system. When tested on real-world data, the framework exceeds the performance requirements (99.8% packed products) and maintains quality (100% filled boxes). Compared to the existing solution, our proposed framework improves productivity, has smoother control, and reduces computation time., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Learning & Autonomous Control
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- 2023
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17. Deep learning methods for the acoustic emission methods to evaluate an onset of plastic straining
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Parma, S., primary, Kovanda, M., additional, Chlada, M., additional, Štefan, J., additional, Kober, J., additional, Feigenbaum, H.P., additional, and Plešek, J., additional
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- 2023
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18. Non-equilibrium strain induces hysteresis and anisotropy in the quasi-static and dynamic elastic behavior of sandstones: Theory and experiments
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Kober, J., primary, Scalerandi, M., additional, and Zeman, R., additional
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- 2023
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19. Robust determination of relaxation times spectra of long-time multirelaxation processes
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Kober, J., primary, Scalerandi, M., additional, and Gabriel, D., additional
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- 2023
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20. OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics
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Passalis, N., primary, Pedrazzi, S., additional, Babuska, R., additional, Burgard, W., additional, Dias, D., additional, Ferro, F., additional, Gabbouj, M., additional, Green, O., additional, Iosifidis, A., additional, Kayacan, E., additional, Kober, J., additional, Michel, O., additional, Nikolaidis, N., additional, Nousi, P., additional, Pieters, R., additional, Tzelepi, M., additional, Valada, A., additional, and Tefas, A., additional
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- 2022
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21. A Multiclass Classification Model for Tooth Removal Procedures
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de Graaf, W.M., primary, van Riet, T.C.T., additional, de Lange, J., additional, and Kober, J., additional
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- 2022
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22. IDF21-0101 Blood Glucose Control using a Mobile Health Application in Asia – A Retrospective Real-World Data Analysis
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Yeoh, E., Eichinger, V., Kober, J., Valdez-faller, T.M., and Tan, W.L.
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- 2022
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23. Simulation of gallium phosphide cutting mechanism in ductile regime using molecular dynamics.
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Tavares, M. R. P. M., Rolon, D. A., Kober, J., Kühne, S., Schroeter, R. B., and Oberschmidt, D.
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- 2023
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24. Simulation of gallium phosphide cutting mechanism in ductile regime using molecular dynamics
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Panchapakesan, Balaji, Attias, André-Jean, Park, Wounjhang, Tavares, M. R. P. M., Rolon, D. A., Kober, J., Kühne, S., Schroeter, R. B., and Oberschmidt, D.
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- 2023
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25. Transitioning from Self-Monitoring of Blood Glucose to Continuous Glucose Monitoring in Combination with a mHealth App Improves Glycemic Control in People with Type 1 and Type 2 Diabetes.
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Zivkovic J, Mitter M, Theodorou D, Kober J, Mueller-Hoffmann W, and Mikulski H
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- Humans, Male, Female, Middle Aged, Adult, Aged, Young Adult, Continuous Glucose Monitoring, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 therapy, Blood Glucose Self-Monitoring methods, Diabetes Mellitus, Type 1 blood, Diabetes Mellitus, Type 1 therapy, Glycemic Control methods, Mobile Applications, Telemedicine, Blood Glucose analysis
- Abstract
Introduction: Integrating mobile health (mHealth) apps into daily diabetes management allows users to monitor and track their health data, creating a comprehensive system for managing daily diabetes activities and generating valuable real-world data. This analysis investigates the impact of transitioning from traditional self-monitoring of blood glucose (SMBG) to real-time continuous glucose monitoring (rtCGM), alongside the use of a mHealth app, on users' glycemic control. Methods: Data were collected from 1271 diabetes type 1 and type 2 users of the mySugr
® app who made a minimum of 50 SMBG logs 1 month before transitioning to rtCGM and then used rtCGM for at least 6 months. The mean and coefficient of variation of glucose, along with the proportions of glycemic measurements in and out of range, were compared between baseline and 1, 2, 3, and 6 months of rtCGM use. A mixed-effects linear regression model was built to quantify the specific effects of transitioning to a rtCGM sensor in different subsamples. A novel validation analysis ensured that the aggregated metrics from SMBG and rtCGM were comparable. Results: Transitioning to a rtCGM sensor significantly improved glycemic control in the entire cohort, particularly among new users of the mySugr app. Additionally, the sustainability of the change in glucose in the entire cohort was confirmed throughout the observation period. People with type 1 and type 2 diabetes exhibited distinct variations, with type 1 experiencing a greater reduction in glycemic variance, while type 2 displayed a relatively larger decrease in monthly averages.- Published
- 2025
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26. An autocrine synergistic desmin-SPARC network promotes cardiomyogenesis in cardiac stem cells.
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Leitner L, Schultheis M, Hofstetter F, Rudolf C, Fuchs C, Kizner V, Fiedler K, Konrad MT, Höbaus J, Genini M, Kober J, Ableitner E, Gmaschitz T, Walder D, and Weitzer G
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The mammalian heart contains cardiac stem cells throughout life, but it has not been possible to harness or stimulate these cells to repair damaged myocardium in vivo. Assuming physiological relevance of these cells, which have evolved and have been maintained throughout mammalian evolution, we hypothesize that cardiac stem cells may contribute to cardiomyogenesis in an unorthodox manner. Since the intermediate filament protein desmin and the matricellular Secreted Protein Acidic and Rich in Cysteine (SPARC) promote cardiomyogenic differentiation during embryogenesis in a cell-autonomous and paracrine manner, respectively, we focus on their genes and employ mouse embryonic and cardiac stem cell lines as in vitro models to ask whether desmin and SPARC cooperatively influence cardiomyogenesis in cardiac stem and progenitor cells. We show that desmin also promotes cardiomyogenesis in a non-cell autonomous manner by increasing the expression and secretion of SPARC in differentiating embryonic stem cells. SPARC is also secreted by cardiac stem cells where it promotes cardiomyogenesis in an autocrine and concentration-dependent manner by upregulating the expression of myocardial transcription factors and its elicitor desmin. Desmin and SPARC interact genetically, forming a positive feedback loop and secreted autocrine and paracrine SPARC negatively affects sparc mRNA expression. Paracrine SPARC rescues cardiomyogenic desmin-haploinsufficiency in cardiac stem cells in a glycosylation-dependent manner, increases desmin expression, the phosphorylation of Smad2 and induces the expression of gata4, nkx2.5 and mef2C. Demonstration that desmin-induced autocrine secretion of SPARC in cardiac stem cells promotes cardiomyogenesis raises the possibility that a physiological function of cardiac stem cells in the adult and aging heart may be the gland-like secretion of factors such as SPARC that modulate age-related and adverse environmental influences and thereby contribute to cardiac homeostasis throughout life., Competing Interests: Declaration of competing interest The authors declare no competing or financial interests., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)
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- 2024
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27. Technical assessment of resolution of handheld ultrasound devices and clinical implications.
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Herzog M, Arsova M, Matthes K, Husman J, Toppe D, Kober J, Trittler T, Swist D, Dorausch EMG, Urbig A, Fettweis GP, Brinkmann F, Martens N, Schmelz R, Kampfrath N, and Hampe J
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- Humans, Liver diagnostic imaging, Pancreas diagnostic imaging, Image Enhancement instrumentation, Female, Sensitivity and Specificity, Intestines diagnostic imaging, Adult, Miniaturization, Male, Ultrasonography instrumentation, Ultrasonography methods, Phantoms, Imaging, Equipment Design
- Abstract
Purpose: Since handheld ultrasound devices are becoming increasingly ubiquitous, objective criteria to determine image quality are needed. We therefore conducted a comparison of objective quality measures and clinical performance., Material and Methods: A comparison of handheld devices (Butterfly IQ+, Clarius HD, Clarius HD3, Philips Lumify, GE VScan Air) and workstations (GE Logiq E10, Toshiba Aplio 500) was performed using a phantom. As a comparison, clinical investigations were performed by two experienced ultrasonographers by measuring the resolution of anatomical structures in the liver, pancreas, and intestine in ten subjects., Results: Axial full width at half maximum resolution (FWHM) of 100µm phantom pins at depths between one and twelve cm ranged from 0.6-1.9mm without correlation to pin depth. Lateral FWHM resolution ranged from 1.3-8.7mm and was positively correlated with depth (r=0.6). Axial and lateral resolution differed between devices (p<0.001) with the lowest median lateral resolution observed in the E10 (5.4mm) and the lowest axial resolution (1.6mm) for the IQ+ device. Although devices showed no significant differences in most clinical applications, ultrasonographers were able to differentiate a median of two additional layers in the wall of the sigmoid colon and one additional structure in segmental portal fields (p<0.05) using cartwheel devices., Conclusion: While handheld devices showed superior or similar performance in the phantom and routine measurements, workstations still provided superior clinical imaging and resolution of anatomical substructures, indicating a lack of objective measurements to evaluate clinical ultrasound devices., Competing Interests: The authors declare that they have no conflict of interest., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)
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- 2024
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28. Efficacy of a Digital Diabetes Logbook for People With Type 1, Type 2, and Gestational Diabetes: Results From a Multicenter, Open-Label, Parallel-Group, Randomized Controlled Trial.
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Ehrmann D, Hermanns N, Finke-Gröne K, Roos T, Kober J, Schäfer V, Krichbaum M, Haak T, Ziegler R, Heinemann L, Rieger C, Bingol E, Kulzer B, and Silbermann S
- Abstract
Background: In a randomized controlled trial, the efficacy of a digital diabetes diary regarding a reduction of diabetes distress was evaluated., Methods: A randomized controlled trial with a 12-week follow-up was conducted in 41 study sites across Germany. Key eligibility criteria were a diagnosis of type 1, type 2, or gestational diabetes and regular self-monitoring of blood glucose. Participants were randomly assigned (2:1 ratio) to either use the digital diabetes logbook (mySugr PRO), or to the control group without app use. The primary outcome was the reduction in diabetes distress at the 12-week follow-up. All analyses were based on the intention-to-treat population with all randomized participants. The trial was registered at the German Register for Clinical Studies (DRKS00022923)., Results: Between February 11, 2021, and June 24, 2022, 424 participants (50% female, 50% male) were included, with 282 being randomized to the intervention group (66.5%) and 142 to the control group (33.5%). A total of 397 participants completed the trial (drop-out rate: 6.4%). The median reduction in diabetes distress was 2.41 (interquartile range [IQR]: -2.50 to 8.11) in the intervention group and 1.25 (IQR: -5.00 to 7.50) in the control group. The model-based adjusted between-group difference was significant (-2.20, IQR: -4.02 to -0.38, P = .0182) favoring the intervention group. There were 27 adverse events, 17 (6.0%) in the intervention group, and 10 (7.0%) in the control group., Conclusions: The efficacy of the digital diabetes logbook was demonstrated regarding improvements in mental health in people with type 1, type 2, and gestational diabetes., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: DE reports Advisory Board member fees from mySugr, Dexcom Germany, and Roche Diabetes Care as well as honoraria for lectures from Berlin-Chemie AG, Sanofi-Aventis, Dexcom Germany, and Roche Diabetes Care. NH reports Advisory Board member fees from Abbott Diabetes Care and Insulet as well as honoraria for lectures from Berlin-Chemie AG, Becton Dickenson, Sanofi Germany, Roche Diabetes Care, and Dexcom Germany. TR reports honoraria for lectures from Berlin-Chemie AG. JK is an employee of mySugr. VS is an employee of Roche Diabetes Care Deutschland. TH reports consulting fees from Eli Lilly, NovoNordisk, Sanofi, Boehringer Ingelheim, and Abbott Diabetes Care as well as honoraria for lectures from Abbott Diabetes Care, Sanofi, and Eli Lilly. RZ reports consulting fees from Roche Diabetes Care and mySugr as well as honoraria for lectures from Roche Diabetes Care, Dexcom, VitalAire, NovoNordisk, and Abbott Diabetes Care. He participated in data safety monitoring boards or advisory boards of Roche Diabetes Care, mySugr, Dexcom, NovoNordisk, and Eli Lilly. LH reports consulting fees from Roche Diabetes Care, Lifecare, Medtronic, Spiden, Embecta, Dexcom, Onetwenty, Perfood, Boydsense, Pharmasense, Unomedical and Sinocare. CR is an employee of Roche Diabetes Care. EB is an employee of mySugr. BK reports Advisory Board member fees from Abbott Diabetes Care, Embecta, Roche Diabetes Care, Novo Nordisk, Berlin-Chemie AG and Dexcom Germany as well as honoraria for lectures from Sanofi Germany, Novo Nordisk, Abbott Diabetes Care, Roche Diabetes Care, Berlin-Chemie AG, Embecta, Dexcom, and Feen. In addition, he reports support for travel and fees for scientific meetings from Sanofi, Roche Diabetes Care and Berlin-Chemie AG as well as unpaid obligations as workshop leader and member of working groups of the German Diabetes Association. SS is an employee of Roche Diabetes Care. The remaining authors have nothing to disclose.
- Published
- 2024
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29. Analysis of movements in tooth removal procedures using robot technology.
- Author
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Riet TV, Graaf W, Lange J, and Kober J
- Subjects
- Movement, Jaw, Mandible, Tooth Extraction, Robotics
- Abstract
Being one of the oldest en most frequently performed invasive procedures; the lack of scientific progress of tooth removal procedures is impressive. This has most likely to do with technical limitations in measuring different aspects of these keyhole procedures. The goal of this study is to accurately capture the full range of motions during tooth removal as well as angular velocities in clinically relevant directions. An ex vivo measuring setup was designed consisting of, amongst others, a compliant robot arm. To match clinical conditions as closely as possible, fresh-frozen cadavers were used as well as regular dental forceps mounted on the robot's end-effector. Data on 110 successful tooth removal experiments are presented in a descriptive manner. Rotation around the longitudinal axis of the tooth seems to be most dominant both in range of motion as in angular velocity. Buccopalatal and buccolingual movements are more pronounced in the dorsal region of both upper and lower jaw. This study quantifies an order of magnitude regarding ranges of motion and angular velocities in tooth removal procedures. Improved understanding of these complex procedures could aid in the development of evidence-based educational material., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Riet et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
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30. Knowledge- and ambiguity-aware robot learning from corrective and evaluative feedback.
- Author
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Celemin C and Kober J
- Abstract
In order to deploy robots that could be adapted by non-expert users, interactive imitation learning (IIL) methods must be flexible regarding the interaction preferences of the teacher and avoid assumptions of perfect teachers (oracles), while considering they make mistakes influenced by diverse human factors. In this work, we propose an IIL method that improves the human-robot interaction for non-expert and imperfect teachers in two directions. First, uncertainty estimation is included to endow the agents with a lack of knowledge awareness (epistemic uncertainty) and demonstration ambiguity awareness (aleatoric uncertainty), such that the robot can request human input when it is deemed more necessary. Second, the proposed method enables the teachers to train with the flexibility of using corrective demonstrations, evaluative reinforcements, and implicit positive feedback. The experimental results show an improvement in learning convergence with respect to other learning methods when the agent learns from highly ambiguous teachers. Additionally, in a user study, it was found that the components of the proposed method improve the teaching experience and the data efficiency of the learning process., Competing Interests: Conflict of interestThe authors declare that they have no conflicts of interest in this work., (© The Author(s) 2023.)
- Published
- 2023
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31. Development and testing of a prototype of a dental extraction trainer with real-time feedback on forces, torques, and angular velocity.
- Author
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Beuling MG, van Riet TCT, van Frankenhuyzen J, Antwerpen RV, de Blocq van Scheltinga B, Dourleijn AHH, Ireiz D, Streefkerk S, van Zanten Jan de Lange JC, Kober J, and Dodou D
- Subjects
- Feedback, Humans, Tooth Extraction, Torque, Emotions, Epoxy Resins
- Abstract
The need for a training modality for tooth extraction procedures is increasing, as dental students do not feel properly trained. In this study, a prototype of a training setup is designed, in which extraction procedures can be performed on jaw models and cadaveric jaws. The prototype was designed in a way that it can give real-time feedback on the applied forces in all three dimensions (buccal/lingual, mesial/distal, and apical/coronal), torques, and angular velocity. To evaluate the prototype, a series of experimental extractions on epoxy models, conserved jaws, and fresh frozen jaws were performed. Extraction duration (s), angular velocity (degrees/s), average force (N), average torque (Nm), linear impulse (Ns), and angular impulse (N ms) were shown in real-time to the user and used to evaluate the prototype. In total, 342 (92.9
% ) successful extractions were performed using the prototype (n= 113 epoxy factory-made, n=187 epoxy re-used, n=17 conserved, n=25 fresh frozen). No significant differences were found between the conserved and the fresh frozen jaws. The fresh frozen extraction duration, linear impulse, and angular impulse differed significantly from the corresponding values obtained for the epoxy models. Extractions were successfully performed, and the applied forces, torques, and angular velocity were recorded and shown as real-time feedback using the prototype of the dental extraction trainer. The feedback of the prototype is considered reliable.- Published
- 2022
- Full Text
- View/download PDF
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