@article{KetelhutBrueggeGoelletal.2020, author = {Ketelhut, Maike and Br{\"u}gge, G. M. and G{\"o}ll, Fabian and Braunstein, Bjoern and Albracht, Kirsten and Abel, Dirk}, title = {Adaptive iterative learning control of an industrial robot during neuromuscular training}, series = {IFAC PapersOnLine}, volume = {53}, journal = {IFAC PapersOnLine}, number = {2}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2405-8963}, doi = {10.1016/j.ifacol.2020.12.741}, pages = {16468 -- 16475}, year = {2020}, abstract = {To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.}, language = {en} } @article{JayaramanMummidisettyLoeschetal.2019, author = {Jayaraman, Chandrasekaran and Mummidisetty, Chaitanya Krishna and Loesch, Alexandra and Kaur, Sandi and Hoppe-Ludwig, Shenan and Staat, Manfred and Jayaraman, Arun}, title = {Postural and metabolic benefits of using a forearm support walker in older adults with impairments}, series = {Archives of Physical Medicine and Rehabilitation}, volume = {Volume 100}, journal = {Archives of Physical Medicine and Rehabilitation}, number = {Issue 4}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0003-9993}, doi = {10.1016/j.apmr.2018.10.001}, pages = {638 -- 647}, year = {2019}, language = {en} } @article{LeschingerBirgelHackletal.2019, author = {Leschinger, Tim and Birgel, Stefan and Hackl, Michael and Staat, Manfred and M{\"u}ller, Lars Peter and Wegmann, Kilian}, title = {A musculoskeletal shoulder simulation of moment arms and joint reaction forces after medialization of the supraspinatus footprint in rotator cuff repair}, series = {Computer Methods in Biomechanics and Biomedical Engineering}, journal = {Computer Methods in Biomechanics and Biomedical Engineering}, number = {Early view}, publisher = {Taylor \& Francis}, address = {London}, doi = {10.1080/10255842.2019.1572749}, year = {2019}, language = {en} } @article{JungStaat2019, author = {Jung, Alexander and Staat, Manfred}, title = {Modeling and simulation of human induced pluripotent stem cell-derived cardiac tissue}, series = {GAMM - Mitteilungen der Gesellschaft f{\"u}r Angewandte Mathematik und Mechanik}, volume = {42}, journal = {GAMM - Mitteilungen der Gesellschaft f{\"u}r Angewandte Mathematik und Mechanik}, number = {4}, publisher = {Wiley}, address = {Weinheim}, issn = {1522-2608}, doi = {10.1002/gamm.201900002}, pages = {11 Seiten}, year = {2019}, language = {en} } @incollection{DachwaldOhndorf2019, author = {Dachwald, Bernd and Ohndorf, Andreas}, title = {Global optimization of continuous-thrust trajectories using evolutionary neurocontrol}, series = {Modeling and Optimization in Space Engineering}, booktitle = {Modeling and Optimization in Space Engineering}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-10501-3}, doi = {10.1007/978-3-030-10501-3_2}, pages = {33 -- 57}, year = {2019}, abstract = {Searching optimal continuous-thrust trajectories is usually a difficult and time-consuming task. The solution quality of traditional optimal-control methods depends strongly on an adequate initial guess because the solution is typically close to the initial guess, which may be far from the (unknown) global optimum. Evolutionary neurocontrol attacks continuous-thrust optimization problems from the perspective of artificial intelligence and machine learning, combining artificial neural networks and evolutionary algorithms. This chapter describes the method and shows some example results for single- and multi-phase continuous-thrust trajectory optimization problems to assess its performance. Evolutionary neurocontrol can explore the trajectory search space more exhaustively than a human expert can do with traditional optimal-control methods. Especially for difficult problems, it usually finds solutions that are closer to the global optimum. Another fundamental advantage is that continuous-thrust trajectories can be optimized without an initial guess and without expert supervision.}, language = {en} } @article{LyonsMikuckiGermanetal.2019, author = {Lyons, W. Berry and Mikucki, Jill A. and German, Laura A. and Welch, Kathleen A. and Welch, Susan A. and Gardener, Christopher B. and Tulaczyk, Slawek M. and Pettit, Erin C. and Kowalski, Julia and Dachwald, Bernd}, title = {The Geochemistry of Englacial Brine from Taylor Glacier, Antarctica}, series = {Journal of Geophysical Research: Biogeosciences}, journal = {Journal of Geophysical Research: Biogeosciences}, publisher = {Wiley}, address = {Hoboken}, issn = {2169-8961}, doi = {10.1029/2018JG004411}, year = {2019}, language = {en} } @article{CampenKowalskiLyonsetal.2019, author = {Campen, R. and Kowalski, Julia and Lyons, W.B. and Tulaczyk, S. and Dachwald, Bernd and Pettit, E. and Welch, K. A. and Mikucki, J.A.}, title = {Microbial diversity of an Antarctic subglacial community and high-resolution replicate sampling inform hydrological connectivity in a polar desert}, series = {Environmental Microbiology}, journal = {Environmental Microbiology}, number = {accepted article}, publisher = {Wiley}, address = {Weinheim}, issn = {1462-2920}, doi = {10.1111/1462-2920.14607}, year = {2019}, language = {en} } @article{AlbannaLuekeSchubertetal.2019, author = {Albanna, Walid and L{\"u}ke, Jan Niklas and Schubert, Gerrit Alexander and Dibu{\´e}-Adjei, Maxine and Kotliar, Konstantin and Hescheler, J{\"u}rgen and Clusmann, Hans and Steiger, Hans-Jakob and H{\"a}nggi, Daniel and Kamp, Marcel A. and Schneider, Toni and Neumaier, Felix}, title = {Modulation of Ca v 2.3 channels by unconjugated bilirubin (UCB) - Candidate mechanism for UCB-induced neuromodulation and neurotoxicity}, series = {Molecular and Cellular Neuroscience}, volume = {96}, journal = {Molecular and Cellular Neuroscience}, number = {4}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1044-7431}, doi = {10.1016/j.mcn.2019.03.003}, pages = {35 -- 46}, year = {2019}, language = {en} } @article{MeyerGaalenLeschingeretal.2019, author = {Meyer, Carolin and Gaalen, Kerstin van and Leschinger, Tim and Scheyerer, Max J. and Neiss, Wolfram F. and Staat, Manfred and M{\"u}ller, Lars P. and Wegmann, Kilian}, title = {Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement}, series = {BioMed Research International}, journal = {BioMed Research International}, doi = {10.1155/2019/9232813}, pages = {Article ID 9232813}, year = {2019}, language = {en} } @book{StaatErni2019, author = {Staat, Manfred and Erni, Daniel}, title = {Symposium Proceedings; 3rd YRA MedTech Symposium 2019: May 24 / 2019 / FH Aachen}, publisher = {Universit{\"a}t Duisburg-Essen}, address = {Duisburg}, organization = {MedTech Symposium}, isbn = {978-3-940402-22-6}, doi = {10.17185/duepublico/48750}, pages = {49 Seiten}, year = {2019}, language = {en} }