TY - CHAP A1 - Kolditz, Melanie A1 - Albin, Thivaharan A1 - Albracht, Kirsten A1 - Brüggemann, Gert-Peter A1 - Abel, Dirk T1 - Isokinematic leg extension training with an industrial robot T2 - 6th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) June 26-29, 2016. UTown, Singapore Y1 - 2016 U6 - http://dx.doi.org/10.1109/BIOROB.2016.7523750 SP - 950 EP - 955 ER - TY - CHAP A1 - Kolditz, Melanie A1 - Albracht, Kirsten A1 - Fasse, Alessandro A1 - Albin, Thivaharan A1 - Brüggemann, Gert-Peter A1 - Abel, Dirk T1 - Evaluation of an industrial robot as a leg press training device T2 - XV International Symposium on Computer Simulation in Biomechanics July 9th – 11th 2015, Edinburgh, UK Y1 - 2015 SP - 41 EP - 42 ER - TY - CHAP A1 - Kolditz, Melanie A1 - Albin, Thivaharan A1 - Fasse, Alessandro A1 - Brüggemann, Gert-Peter A1 - Abel, Dirk A1 - Albracht, Kirsten T1 - Simulative Analysis of Joint Loading During Leg Press Exercise for Control Applications T2 - IFAC-PapersOnLine Y1 - 2015 U6 - http://dx.doi.org/10.1016/j.ifacol.2015.10.179 N1 - IFAC-PapersOnLine 48-20; Conference Paper Archive VL - 48 IS - 20 SP - 435 EP - 440 ER - TY - CHAP A1 - Ketelhut, Maike A1 - Göll, Fabian A1 - Braunstein, Bjoern A1 - Albracht, Kirsten A1 - Abel, Dirk T1 - Iterative learning control of an industrial robot for neuromuscular training T2 - 2019 IEEE Conference on Control Technology and Applications N2 - Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations. KW - Knee KW - Training KW - Load modeling KW - Force KW - Iterative learning control Y1 - 2019 SN - 978-1-7281-2767-5 (ePub) SN - 978-1-7281-2766-8 (USB) SN - 978-1-7281-2768-2 (PoD) U6 - http://dx.doi.org/10.1109/CCTA.2019.8920659 N1 - 2019 IEEE Conference on Control Technology and Applications (CCTA) Hong Kong, China, August 19-21, 2019 PB - IEEE CY - New York ER -