@inproceedings{BayerHeschelerArtmannetal.2019,
  author    = {Bayer, Robin and Hescheler, J{\"u}rgen and Artmann, Gerhard and Temiz Artmann, Ayseg{\"u}l},
  title     = {Treating arterial hypertension in a cell culture well},
  series = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH AachenW},
  booktitle = {3rd YRA MedTech Symposium 2019 : May 24 / 2019 / FH AachenW},
  editor    = {Staat, Manfred and Erni, Daniel},
  publisher = {Universit{\"a}t Duisburg-Essen},
  address   = {Duisburg},
  organization    = {MedTech Symposium},
  isbn      = {978-3-940402-22-6},
  doi       = {10.17185/duepublico/48750},
  pages     = {5 -- 6},
  year      = {2019},
  abstract  = {Hypertension describes the pathological increase of blood pressure, which is most commonly associated with the increase of vascular wall stiffness [1]. Referring to the "Deutsche Bluthochdruck Liga" this pathology shows a growing trend in our aging society. In order to find novel pharmacological and probably personalized treatments, we want to present a functional approach to study biomechanical properties of a human aortic vascular model. In this method review we will give an overview of recent studies which were carried out with the CellDrum technology [2] and underline the added value to already existing standard procedures known from the field of physiology. Herein described CellDrum technology is a system to measure functional mechanical properties of cell monolayers and thin tissue constructs in-vitro. Additionally, the CellDrum enables to elucidate the mechanical response of cells to pharmacological drugs, toxins and vasoactive agents. Due to its highly flexible polymer support, cells can also be mechanically stimulated by steady and cyclic biaxial stretching.},
  language  = {en}
}
@inproceedings{HingleyDikta2019,
  author    = {Hingley, Peter and Dikta, Gerhard},
  title     = {Finding a well performing box-jenkins forecasting model for annualised patent filings counts},
  series = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019},
  booktitle = {International Symposium on Forecasting, Thessaloniki, Greece, June 2019},
  pages     = {24 Folien},
  year      = {2019},
  language  = {en}
}
@inproceedings{EschlerWozniakRichteretal.2019,
  author    = {Eschler, Eric and Wozniak, Felix and Richter, Christoph and Drechsler, Klaus},
  title     = {Materialanalyse an lokal verst{\"a}rkten Triaxialgeflechten},
  series = {Leichtbau in Forschung und industrieller Anwendung von der Nano- bis zur Makroebene, LLC, Landshuter Leichtbau-Colloquium, 9},
  booktitle = {Leichtbau in Forschung und industrieller Anwendung von der Nano- bis zur Makroebene, LLC, Landshuter Leichtbau-Colloquium, 9},
  publisher = {Leichtbau Cluster},
  address   = {Landshut},
  isbn      = {978-3-9818439-2-7},
  pages     = {120 -- 131},
  year      = {2019},
  language  = {de}
}
@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}
}