TY - THES A1 - Albracht, Kirsten T1 - Influence of mechanical properties of the leg extensor muscletendon units on running economy Y1 - 2010 N1 - Cologne, German Sport Univ., Diss., 2010 PB - Deutsche Sporthochschule Köln CY - Köln 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 - https://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 - JOUR A1 - Horbach, Andreas A1 - Staat, Manfred T1 - Optical strain measurement for the modeling of surgical meshes and their porosity JF - Current Directions in Biomedical Engineering N2 - 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. Y1 - 2018 U6 - https://doi.org/10.1515/cdbme-2018-0045 SN - 2364-5504 VL - Band 4 IS - 1 SP - 181 EP - 184 PB - De Gruyter CY - Berlin ER - TY - JOUR A1 - Bhattarai, Aroj A1 - Staat, Manfred T1 - Computational comparison of different textile implants to correct apical prolapse in females JF - Current Directions in Biomedical Engineering N2 - 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. Y1 - 2018 U6 - https://doi.org/10.1515/cdbme-2018-0159 VL - 4 IS - 1 SP - 661 EP - 664 PB - De Gruyter CY - Berlin ER - TY - CHAP A1 - Bialonski, Stephan A1 - Lehnertz, Klaus T1 - From time series to complex networks: an overview T2 - Recent Advances in Predicting and Preventing Epileptic Seizures: Proceedings of the 5th International Workshop on Seizure Prediction N2 - 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. Y1 - 2013 SN - 978-981-4525-36-7 U6 - https://doi.org/10.1142/9789814525350_0010 SP - 132 EP - 147 ER - TY - BOOK A1 - Bialonski, Stephan T1 - Inferring complex networks from time series of dynamical systems: Pitfalls, misinterpretations, and possible solutions Y1 - 2012 N1 - Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn, Diss., 2012 PB - Universitäts- und Landesbibliothek Bonn CY - Bonn ER - TY - JOUR A1 - Bialonski, Stephan A1 - Wendler, Martin A1 - Lehnertz, Klaus T1 - Unraveling spurious properties of interaction networks with tailored random networks JF - Plos one N2 - 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 Erdös-Rényi 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. Y1 - 2011 U6 - https://doi.org/10.1371/journal.pone.0022826 VL - 6 IS - 8 PB - Plos CY - San Francisco ER - TY - CHAP A1 - Bialonski, Stephan T1 - Are interaction clusters in epileptic networks predictive of seizures? T2 - Epilepsy: The Intersection of Neurosciences, Biology, Mathematics, Engineering, and Physics Y1 - 2016 SN - 978-143983886-0 SP - 349 EP - 355 PB - CRC Press ER - TY - JOUR A1 - Bialonski, Stephan A1 - Horstmann, Marie-Therese A1 - Lehnertz, Klaus T1 - From brain to earth and climate systems: Small-world interaction networks or not? JF - Chaos: An Interdisciplinary Journal of Nonlinear Science N2 - 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. Y1 - 2010 U6 - https://doi.org/10.1063/1.3360561 SN - 1089-7682 VL - 20 IS - 1 PB - AIP Publishing CY - Melville, NY ER -