@phdthesis{Albracht2010,
  author    = {Albracht, Kirsten},
  title     = {Influence of mechanical properties of the leg extensor muscletendon units on running economy},
  publisher = {Deutsche Sporthochschule K{\"o}ln},
  address   = {K{\"o}ln},
  pages     = {X, 1221 Bl. : graph. Darst.},
  year      = {2010},
  language  = {en}
}
@inproceedings{KolditzAlbrachtFasseetal.2015,
  author    = {Kolditz, Melanie and Albracht, Kirsten and Fasse, Alessandro and Albin, Thivaharan and Br{\"u}ggemann, Gert-Peter and Abel, Dirk},
  title     = {Evaluation of an industrial robot as a leg press training device},
  series = {XV International Symposium on Computer Simulation in Biomechanics July 9th - 11th 2015, Edinburgh, UK},
  booktitle = {XV International Symposium on Computer Simulation in Biomechanics July 9th - 11th 2015, Edinburgh, UK},
  pages     = {41 -- 42},
  year      = {2015},
  language  = {en}
}
@inproceedings{KolditzAlbinFasseetal.2015,
  author    = {Kolditz, Melanie and Albin, Thivaharan and Fasse, Alessandro and Br{\"u}ggemann, Gert-Peter and Abel, Dirk and Albracht, Kirsten},
  title     = {Simulative Analysis of Joint Loading During Leg Press Exercise for Control Applications},
  series = {IFAC-PapersOnLine},
  volume    = {48},
  booktitle = {IFAC-PapersOnLine},
  number    = {20},
  doi       = {10.1016/j.ifacol.2015.10.179},
  pages     = {435 -- 440},
  year      = {2015},
  language  = {en}
}
@article{HorbachStaat2018,
  author    = {Horbach, Andreas and Staat, Manfred},
  title     = {Optical strain measurement for the modeling of surgical meshes and their porosity},
  series = {Current Directions in Biomedical Engineering},
  volume    = {Band 4},
  journal   = {Current Directions in Biomedical Engineering},
  number    = {1},
  publisher = {De Gruyter},
  address   = {Berlin},
  issn      = {2364-5504},
  doi       = {10.1515/cdbme-2018-0045},
  pages     = {181 -- 184},
  year      = {2018},
  abstract  = {The porosity of surgical meshes makes them flexible for large elastic deformation and establishes the healing conditions of good tissue in growth. The biomechanic modeling of orthotropic and compressible materials requires new materials models and simulstaneoaus fit of deformation in the load direction as well as trannsversely to to load. This nonlinear modeling can be achieved by an optical deformation measurement. At the same time the full field deformation measurement allows the dermination of the change of porosity with deformation. Also the socalled effective porosity, which has been defined to asses the tisssue interatcion with the mesh implants, can be determined from the global deformation of the surgical meshes.},
  language  = {en}
}
@article{BhattaraiStaat2018,
  author    = {Bhattarai, Aroj and Staat, Manfred},
  title     = {Computational comparison of different textile implants to correct apical prolapse in females},
  series = {Current Directions in Biomedical Engineering},
  volume    = {4},
  journal   = {Current Directions in Biomedical Engineering},
  number    = {1},
  publisher = {De Gruyter},
  address   = {Berlin},
  doi       = {10.1515/cdbme-2018-0159},
  pages     = {661 -- 664},
  year      = {2018},
  abstract  = {Prosthetic textile implants of different shapes, sizes and polymers are used to correct the apical prolapse after hysterectomy (removal of the uterus). The selection of the implant before or during minimally invasive surgery depends on the patient's anatomical defect, intended function after reconstruction and most importantly the surgeon's preference. Weakness or damage of the supporting tissues during childbirth, menopause or previous pelvic surgeries may put females in higher risk of prolapse. Numerical simulations of reconstructed pelvic floor with weakened tissues and organ supported by textile product models: DynaMesh®-PRS soft, DynaMesh®-PRP soft and DynaMesh®-CESA from FEG Textiletechnik mbH, Germany are compared.},
  language  = {en}
}
@incollection{BialonskiLehnertz2013,
  author    = {Bialonski, Stephan and Lehnertz, Klaus},
  title     = {From time series to complex networks: an overview},
  series = {Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction},
  booktitle = {Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction},
  isbn      = {978-981-4525-36-7},
  doi       = {10.1142/9789814525350_0010},
  pages     = {132 -- 147},
  year      = {2013},
  abstract  = {The network approach towards the analysis of the dynamics of complex systems has been successfully applied in a multitude of studies in the neurosciences and has yielded fascinating insights. With this approach, a complex system is considered to be composed of different constituents which interact with each other. Interaction structures can be compactly represented in interaction networks. In this contribution, we present a brief overview about how interaction networks are derived from multivariate time series, about basic network characteristics, and about challenges associated with this analysis approach.},
  language  = {en}
}
@book{Bialonski2012,
  author    = {Bialonski, Stephan},
  title     = {Inferring complex networks from time series of dynamical systems: Pitfalls, misinterpretations, and possible solutions},
  publisher = {Universit{\"a}ts- und Landesbibliothek Bonn},
  address   = {Bonn},
  pages     = {Online-Ausgabe (III, 135 S. : Ill., graph. Darst.)},
  year      = {2012},
  language  = {en}
}
@article{BialonskiWendlerLehnertz2011,
  author    = {Bialonski, Stephan and Wendler, Martin and Lehnertz, Klaus},
  title     = {Unraveling spurious properties of interaction networks with tailored random networks},
  series = {Plos one},
  volume    = {6},
  journal   = {Plos one},
  number    = {8},
  publisher = {Plos},
  address   = {San Francisco},
  doi       = {10.1371/journal.pone.0022826},
  pages     = {e22826},
  year      = {2011},
  abstract  = {We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erd{\"o}s-R{\´e}nyi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures - known for their complex spatial and temporal dynamics - we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.},
  language  = {en}
}
@incollection{Bialonski2016,
  author    = {Bialonski, Stephan},
  title     = {Are interaction clusters in epileptic networks predictive of seizures?},
  series = {Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics},
  booktitle = {Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics},
  publisher = {CRC Press},
  isbn      = {978-143983886-0},
  pages     = {349 -- 355},
  year      = {2016},
  language  = {en}
}
@article{BialonskiHorstmannLehnertz2010,
  author    = {Bialonski, Stephan and Horstmann, Marie-Therese and Lehnertz, Klaus},
  title     = {From brain to earth and climate systems: Small-world interaction networks or not?},
  series = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  volume    = {20},
  journal   = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  number    = {1},
  publisher = {AIP Publishing},
  address   = {Melville, NY},
  issn      = {1089-7682},
  doi       = {10.1063/1.3360561},
  pages     = {013134},
  year      = {2010},
  abstract  = {We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.},
  language  = {en}
}