@inproceedings{KetelhutGoellBraunsteinetal.2019,
  author    = {Ketelhut, Maike and G{\"o}ll, Fabian and Braunstein, Bjoern and Albracht, Kirsten and Abel, Dirk},
  title     = {Iterative learning control of an industrial robot for neuromuscular training},
  series = {2019 IEEE Conference on Control Technology and Applications},
  booktitle = {2019 IEEE Conference on Control Technology and Applications},
  publisher = {IEEE},
  address   = {New York},
  isbn      = {978-1-7281-2767-5 (ePub)},
  doi       = {10.1109/CCTA.2019.8920659},
  pages     = {7 Seiten},
  year      = {2019},
  abstract  = {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.},
  language  = {en}
}
@inproceedings{SchmitzApandiSpillneretal.2024,
  author    = {Schmitz, Annika and Apandi, Shah Eiman Amzar Shah and Spillner, Jan and Hima, Flutura and Behbahani, Mehdi},
  title     = {Effect of different cannula positions in the pulmonary artery on blood flow and gas exchange using computational fluid dynamics analysis},
  series = {YRA MedTech Symposium (2024)},
  booktitle = {YRA MedTech Symposium (2024)},
  editor    = {Digel, Ilya and Staat, Manfred and Trzewik, J{\"u}rgen and Sielemann, Stefanie and Erni, Daniel and Zylka, Waldemar},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-65-3},
  doi       = {10.17185/duepublico/81475},
  pages     = {29 -- 30},
  year      = {2024},
  abstract  = {Pulmonary arterial cannulation is a common and effective method for percutaneous mechanical circulatory support for concurrent right heart and respiratory failure [1]. However, limited data exists to what effect the positioning of the cannula has on the oxygen perfusion throughout the pulmonary artery (PA). This study aims to evaluate, using computational fluid dynamics (CFD), the effect of different cannula positions in the PA with respect to the oxygenation of the different branching vessels in order for an optimal cannula position to be determined. The four chosen different positions (see Fig. 1) of the cannulas are, in the lower part of the main pulmonary artery (MPA), in the MPA at the junction between the right pulmonary artery (RPA) and the left pulmonary artery (LPA), in the RPA at the first branch of the RPA and in the LPA at the first branch of the LPA.},
  language  = {en}
}