Publications

Publications of Members of the Institute for Modelling and Simulation of Biomechanical Systems

International, peer-reviewed Publications

  1. submitted 2023

    1. Meszaros-Beller, L., Hammer, M., Schmitt, S., & Pivonka, P. (n.d.). Effect of neglecting passive spinal structures on estimated joint loads: a quantitative investigation using the forward-dynamics and inverse-dynamics musculoskeletal approach. Frontiers in Physiology.

  2. 2023

    1. Bunz, E., Haeufle, D., Remy, C., & Schmitt, S. (2023). Bioinspired preactivation reflex increases robustness of walking on rough terrain. Scientific Reports, 13:13219. https://doi.org/10.1038/ s41598-023-39364-3
    2. Haggie, L., Schmid, L., Röhrle, O., Besier, T., McMorland, A., & Saini, H. (2023). Linking cortex and contraction—Integrating models along the corticomuscular pathway. Frontiers in Physiology, 14. https://doi.org/10.3389/fphys.2023.1095260
    3. Izzi, F., Mo, A., Schmitt, S., Badri-Spröwitz, A., & Haeufle, D. F. B. (2023). Muscle prestimulation tunes velocity preflex in simulated perturbed hopping. Scientific Reports, 13(1), Article 1. https://doi.org/10.1038/s41598-023-31179-6
    4. Klotz, T., Lehmann, L., Negro, F., & Röhrle, O. (2023). High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study. Journal of Neural Engineering. https://doi.org/10.1088/1741-2552/ace7f7
    5. Kneifl, J., Rosin, D., Röhrle, O., & Fehr, J. C. (2023). Low-dimensional data-based surrogate model of a continuum-mechanical musculoskeletal system based on non-intrusive model order reduction. Archive of Applied Mechanics, 1–27. https://doi.org/10.1007/s00419-023-02458-5
    6. Lich, T., Mönnich, J., Voss, M., Lerge, P., Nölle, L. V., & Schmitt, S. (2023). Applying AI Methods On Video Documented Car-VRU Front Crashes to Determine Generalized Vulnerable Road User Behaviors. Proceedings of the 27th International Technical Conference on the Enhanced Safety of Vehicles (ESV), Yokohama, Japan. https://www-esv.nhtsa.dot.gov/Proceedings/27/27ESV-000210.pdf
    7. Martynenko, O. V., Kempter, F., Kleinbach, C., Nölle, L. V., Lerge, P., Schmitt, S., & Fehr, J. (2023). Development and verification of a physiologically motivated internal controller for the open-source extended Hill-type muscle model in LS-DYNA. Biomechanics and Modeling in Mechanobiology, 1--30. https://doi.org/10.1007/s10237-023-01748-9
    8. Meszaros-Beller, L., Hammer, M., Riede, J. M., Pivonka, P., Little, J. P., & Schmitt, S. (2023). Effects of geometric individualisation of a human spine model on load sharing: neuro-musculoskeletal simulation reveals significant differences in ligament and muscle contribution. Biomechanics and Modeling in Mechanobiology, 1--26. https://doi.org/10.1007/s10237-022-01673-3
    9. Meszaros-Beller, L., Hammer, M., Schmitt, S., & Pivonka, P. (2023). Effect of neglecting passive spinal structures: a quantitative investigation using the forward-dynamics and inverse-dynamics musculoskeletal approach. Frontiers in Physiology, 14, 1135531. https://doi.org/10.3389/fphys.2023.1135531
    10. Rockenfeller, R., Günther, M., & Hooper, S. L. (2023). Sarcomere mechanics in the double-actin-overlap                    zone. Biophysical Journal, 122(17), Article 17. https://doi.org/10.1016/j.bpj.2023.08.002
    11. Rockenfeller, R., Günther, M., & Mörl, F. (2023). Reports of deaths are an exaggeration: all-cause                    and NAA-test-conditional mortality in Germany during                    the SARS-CoV-2 era. Royal Society Open Science, 10(8), Article 8. https://doi.org/10.1098/rsos.221551
    12. Schumacher, P., Geijtenbeek, T., Caggiano, V., Kumar, V., Schmitt, S., Martius, G., & Haeufle, D. (2023). Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models. arXiv. https://doi.org/10.48550/arXiv.2309.02976
    13. Trivedi, Z., Gehweiler, D., Wychowaniec, J. K., Ricken, T., Gueorguiev, B., Wagner, A., & Röhrle, O. (2023). A continuum mechanical porous media model for vertebroplasty: Numerical simulations and experimental validation. Biomechanics and Modeling in Mechanobiology. https://doi.org/10.1007/s10237-023-01715-4
    14. Trube, N., Matt, P., Jenerowicz, M., Ballal, N., Soot, T., Fressmann, D., Lazarov, N., Moennich, J., Lich, T., Lerge, P., & others. (2023). Plausibility Assessment of Numerical Cyclist to Vehicle Collision Simulations based on Accident Data. Proceedings of the IRCOBI Conference, 113--135. http://www.ircobi.org/wordpress/downloads/irc23/pdf-files/2323.pdf
    15. Zhang, C., Zhang, J., Widmann, M., Benke, M., Kübler, M., Dasari, D., Klotz, T., Gizzi, L., Röhrle, O., Brenner, P., & Wrachtrup, J. (2023). Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications. Frontiers in Neuroscience, 16. https://doi.org/10.3389/fnins.2022.1034391

  3. 2022

    1. Ali, H., Umander, J., Rohlén, R., Röhrle, O., & Grönlund, C. (2022). Modelling intra-muscular contraction dynamics using in silico to in vivo domain translation. Biomedical Engineering Online, 21(1), Article 1. https://doi.org/10.1186/s12938-022-01016-4
    2. Bleiler, C., & Röhrle, O. (2022). Strain Measures and Energies for Crimped Fibres and Novel Analytical Expressions for Fibre Populations: Ingredients for Structural Fibre Network Models. Journal of Elasticity, 150, 401–448. https://doi.org/10.1007/s10659-022-09920-5
    3. Günther, M., Mörl, F., & Rockenfeller, R. (2022). Where have the dead gone? Frontiers in Medicine, 9, 837287 (3pp). https://doi.org/10.3389/fmed.2022.837287
    4. Hammer, M., Riede, J. M., Meszaros-Beller, L., & Schmitt, S. (2022). gspine: A Human Spine Model Built Using Literature Data. https://doi.org/10.18419/darus-2814
    5. Hessenthaler, A., Falgout, R. D., Schroder, J. B., de Vecchi, A., Nordsletten, D., & Röhrle, O. (2022). Time-periodic steady-state solution of fluid-structure interaction and cardiac flow problems through multigrid-reduction-in-time. Computer Methods in Applied Mechanics and Engineering, 389, 114368. https://doi.org/10.1016/j.cma.2021.114368
    6. Klotz, T., Gizzi, L., & Röhrle, O. (2022). Investigating the spatial resolution of EMG and MMG based on a systemic  multi-scale model. Biomechanics and Modeling in Mechanobiology, 21, 983–997. https://doi.org/10.1007/s10237-022-01572-7
    7. Kässinger, J., Rosin, D., Dürr, F., Hornischer, N., Rothermel, K., & Röhrle, O. (2022). Persival: Simulating Complex 3D Meshes on Resource-Constrained Mobile AR Devices Using Interpolation. Proceedings of the 2022 IEEE International Conference on Distributed Computing Systems (ICDCS), 961--971. https://doi.org/10.1109/ICDCS54860.2022.00097
    8. Mörl, F., Günther, M., & Rockenfeller, R. (2022). Is the harm-to-benefit ratio a key criterion in vaccine approval? Frontiers in Medicine, 9, 879120 (4pp). https://doi.org/10.3389/fmed.2022.879120
    9. Nölle, L. V., Mishra, A., Martynenko, O. V., & Schmitt, S. (2022). Evaluation of muscle strain injury severity in active human body models. Journal of the Mechanical Behavior of Biomedical Materials, 105463. https://doi.org/doi.org/10.1016/j.jmbbm.2022.105463
    10. Ramakrishnan, A. N., Roehrle, O., Ludtka, C., Varghese, R., Koehler, J., Kiesow, A., & Schwan, S. (2022). FINITE ELEMENT EVALUATION OF THE EFFECT OF ADHESIVE CREAMS ON THE STRESS STATE OF DENTURES AND ABUTMENT TEETH. Journal of Mechanics in Medicine and Biology, 22(05), Article 05. https://doi.org/10.1142/S0219519422500270
    11. Ramakrishnan, A. N., Röhrle, O., Ludtka, C., Köhler, J., Kiesow, A., & Schwan, S. (2022). The Role of Denture Adhesives on the Oral Health of Partial Denture Wearers: A Numerical Study. Macromolecular Symposia, 403(1), Article 1. https://doi.org/10.1002/masy.202100422
    12. Ramakrishnan, A. N., Röhrle, O., Ludtka, C., Varghese, R., Koehler, J., Kiesow, A., & Schwan, S. (2022). Numerical study of the stress state on the oral mucosa and abutment tooth upon insertion of partial dentures in the mandible. International Journal for Numerical Methods in Biomedical Engineering, e3604. https://doi.org/10.1002/cnm.3604
    13. Renjewski, D., Lipfert, S. W., & Günther, M. (2022). Foot function enabled by human walking dynamics. Physical Review E, 106(6), Article 6. https://doi.org/10.1103/PhysRevE.106.064405
    14. Rockenfeller, R., Günther, M., & Hooper, S. L. (2022). Muscle active force-length curve explained by an electrophysical model of interfilament spacing. Biophysical Journal, 121(10), Article 10. https://doi.org/10.1016/j.bpj.2022.04.019
    15. Sahrmann, A. S., Gizzi, L., Zanker, A., Handsfield, G. G., & Röhrle, O. (2022). Dynamic 3D Ultrasound Imaging of the Tibialis Anterior Muscle. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 3899–3902. https://doi.org/10.1109/EMBC48229.2022.9871352
    16. Saini, H., Klotz, T., & Röhrle, O. (2022). Modelling motor units in 3D: Influence on muscle contraction and joint force via a proof of concept simulation. Biomechanics and Modeling in Mechanobiology, 1--18. https://doi.org/10.1007/s10237-022-01666-2
    17. Saini, H., & Röhrle, O. (2022). A Biophysically Guided Constitutive Law of the Musculotendon-Complex: Modelling and Numerical Implementation in Abaqus. Available at SSRN 4102677, 226, 107152. https://doi.org/10.1016/j.cmpb.2022.107152
    18. Schmid, L., Klotz, T., Yavuz, U. Ş., Maltenfort, M., & Röhrle, O. (2022). Spindle Model Responsive to Mixed Fusimotor Inputs: an updated version of the Maltenfort and Burke (2003) model. Physiome. https://doi.org/10.36903/physiome.19070171.v2
    19. Schmitt, S. (2022). demoa-base: a biophysics simulator for muscle-driven motion. https://doi.org/10.18419/darus-2550
    20. Schumacher, P., Häufle, D., Büchler, D., Schmitt, S., & Martius, G. (2022). DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems. arXiv. https://doi.org/10.48550/ARXIV.2206.00484
    21. Villota-Narvaez, Y., Garzón-Alvarado, D. A., Röhrle, O., & Ramírez-Martínez, A. M. (2022). Multi-scale mechanobiological model for skeletal muscle hypertrophy. Frontiers in Physiology, 1924. https://doi.org/10.3389/fphys.2022.899784
    22. Waldhof, M., Wochner, I., Stollenmaier, K., Parspour, N., & Schmitt, S. (2022). Design and Scaling of Exoskeleton Power Units Considering Load Cycles of Humans. Robotics, 11(5), Article 5. https://doi.org/10.3390/robotics11050107
    23. Walter, J. R., Wochner, I., Jacob, M., Stollenmaier, K., Lerge, P., & Schmitt, S. (2022). allmin: A Reduced Human All-Body Model. https://doi.org/10.18419/darus-2982
    24. Wochner, I., Nölle, L. V., Martynenko, O. V., & Schmitt, S. (2022). ‘Falling heads’: investigating reflexive responses to head--neck perturbations. BioMedical Engineering OnLine, 21(1), Article 1. https://doi.org/doi: 10.1186/s12938-022-00994-9
    25. Wochner, I., & Schmitt, S. (2022). arm26: A Human Arm Model. https://doi.org/10.18419/darus-2871
    26. Wochner, I., Schumacher, P., Martius, G., Büchler, D., Schmitt, S., & Haeufle, D. (2022). Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks. 6th Annual Conference on Robot Learning. https://openreview.net/forum?id=Xo3eOibXCQ8

  4. 2021

    1. Banik, T., Nölle, L. V., Schmitt, S., & Martynenko, O. V. (2021). Representation of the Elderly Population with Active Human Body Models. Proceedings of IRCOBI Conference, 2021, 534--536. http://www.ircobi.org/wordpress/downloads/irc21/pdf-files/2158.pdf
    2. Bleiler, C., Ponte Castañeda, P., & Röhrle, O. (2021). Tangent second-order homogenisation estimates for incompressible hyperelastic composites with fibrous microstructures and anisotropic phases. Journal of the Mechanics and Physics of Solids, 147, 104251. https://doi.org/10.1016/j.jmps.2020.104251
    3. Christensen, K. B., Günther, M., Schmitt, S., & Siebert, T. (2021). Cross-bridge mechanics estimated from skeletal muscles’ work-loop responses to impacts in legged locomotion. Scientific Reports, 11, 23638 (12pp). https://doi.org/10.1038/s41598-021-02819-6
    4. Ghazi-Zahedi, K., Rieffel, J., Schmitt, S., & Hauser, H. (2021). Editorial: Recent Trends in Morphological Computation. Frontiers in Robotics and AI, 8, 159. https://doi.org/10.3389/frobt.2021.708206
    5. Gizzi, L., Vujaklija, I., Sartori, M., Röhrle, O., & Severini, G. (2021). Editorial: Somatosensory Integration in Human Movement: Perspectives for Neuromechanics, Modelling and Rehabilitation. 9. https://doi.org/10.3389/fbioe.2021.725603
    6. Gizzi, L., Yavuz, U. S., Hillerkuss, D., Geri, T., Gneiting, E., Domeier, F., Schmitt, S., & Röhrle, O. (2021). Variations in Muscle Activity and Exerted Torque During  Temporary Blood Flow Restriction in Healthy Individuals. Frontiers in Bioengineering and Biotechnology, 9, 100. https://doi.org/10.3389/fbioe.2021.557761
    7. Günther, M., & Mörl, F. (2021). Giraffes and hominins: reductionist model predictions of compressive loads at the spine base for erect exponents of the animal kingdom. Biology Open, 10(1), Article 1. https://doi.org/10.1242/bio.057224
    8. Günther, M., Rockenfeller, R., Weihmann, T., Haeufle, D. F. B., Götz, T., & Schmitt, S. (2021). Rules of nature’s Formula Run: Muscle mechanics during late stance is the key to explaining maximum running speed. Journal of Theoretical Biology, 523, 110714. https://doi.org/10.1016/j.jtbi.2021.110714
    9. Haasdonk, B., Wenzel, T., Santin, G., & Schmitt, S. (2021). Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods. In F. J. Vermolen & C. Vuik (Eds.), Numerical Mathematics and Advanced Applications ENUMATH 2019 (pp. 499--508). Springer International Publishing. https://doi.org/10.1007/978-3-030-55874-1_49
    10. Klotz, T., Bleiler, C., & Röhrle, O. (2021). A Physiology-Guided Classification of Active-Stress and Active-Strain Approaches for Continuum-Mechanical Modeling of Skeletal Muscle Tissue. Frontiers in Physiology, 12, 1–13. https://doi.org/10.3389/fphys.2021.685531
    11. Lara, J., Cheng, L. K., Roehrle, O., & Paskaranandavadivel, N. (2021). Muscle-Specific High-Density Electromyography Arrays for Hand Gesture Classification. IEEE Transactions on Biomedical Engineering. https://doi.org/10.1109/TBME.2021.3131297
    12. Martynenko, O. V., Wochner, I., Nölle, L. V., Alfaro, E. H., Schmitt, S., Mayer, C., Mishra, A., Ghosh, P., Chitteti, R. K., Weber, J., & others. (2021). Comparison of the Head-Neck Kinematics of Different Active Human Body Models with Experimental Data. Proceedings of IRCOBI Conference, 105--121. http://www.ircobi.org/wordpress/downloads/irc21/pdf-files/2121.pdf
    13. Ramakrishnan, A. N., Röhrle, O., Ludtka, C., Varghese, R., Koehler, J., Kiesow, A., & Schwan, S. (2021). Finite Element Evaluation of the Effect of Adhesive Creams on the Stress State of Dentures and Oral Mucosa. Journal of Mechanics in Medicine and Biology, 22(5), Article 5. https://doi.org/10.1142/S0219519422500270
    14. Riede, J. M., Holm, C., Schmitt, S., & Haeufle, D. F. B. (2021). The control effort to steer self-propelled microswimmers depends on their morphology: comparing symmetric spherical versus asymmetric L-shaped particles. Royal Society Open Science, 8(9), Article 9. https://doi.org/10.1098/rsos.201839
    15. Rockenfeller, R., Hammer, M., Riede, J. M., Schmitt, S., & Lawonn, K. (2021). Intuitive assessment of modeled lumbar spinal motion by  clustering and visualization of finite helical axes. Computers in Biology and Medicine, 135, 104528. https://doi.org/10.1016/j.compbiomed.2021.104528
    16. Shuva, S., Buchfink, P., Röhrle, O., & Haasdonk, B. (2021). Reduced Basis Methods for Efficient Simulation of a Rigid Robot Hand Interacting with Soft Tissue. International Conference on Large-Scale Scientific Computing, 402--409. https://doi.org/10.1007/978-3-030-97549-4_46
    17. Walter, J., Günther, M., Haeufle, D. F. B., & Schmitt, S. (2021). A geometry- and muscle-based control architecture for synthesising biological movement. Biological Cybernetics, 115(1), Article 1. https://doi.org/10.1007/s00422-020-00856-4
    18. Walter, J., Günther, M., Haeufle, D., & Schmitt, S. (2021). Correction to:  A geometry- and muscle-based control architecture for synthesising biological movement. Biological Cybernetics, 115, Article 115. https://doi.org/10.1007/s00422-021-00869-7
    19. Walter, J., Lerge, P., & Schmitt, S. (2021). Human-centred design: a comparison of ingress motion for two car concepts using a musculoskeletal, digital human body model. https://doi.org/10.18419/opus-11478
    20. Woodford, S. C., Robinson, D. L., Edelmann, C., Mehl, A., Röhrle, O., Lee, P. V. S., & Ackland, D. C. (2021). Low-Profile Electromagnetic Field Sensors in the Measurement and Modelling of Three-Dimensional Jaw Kinematics and Occlusal Loading. Annals of Biomedical Engineering, 49(6), Article 6. https://doi.org/10.1007/s10439-020-02688-6
    21. Zhang, C., Shagieva, F., Widmann, M., Kübler, M., Vorobyov, V., Kapitanova, P., Nenasheva, E., Corkill, R., Röhrle, O., Nakamura, K., Sumiya, H., Onoda, S., Isoya, J., & Wrachtrup, J. (2021). Diamond Magnetometry and Gradiometry Towards Subpicotesla dc Field Measurement. Phys. Rev. Applied, 15(6), Article 6. https://doi.org/10.1103/PhysRevApplied.15.064075

  5. 2020

    1. Altan, E., Seide, S., Bayram, I., Gizzi, L., Ertan, H., & Röhrle, O. (2020). A systematic review and meta-analysis on the longitudinal effects of unilateral knee extension exercise on muscle strength. Frontiers in Sports and Active Living, 2. https://dx.doi.org/10.3389%2Ffspor.2020.518148
    2. Asgharzadeh, P., Birkhold, A. I., Trivedi, Z., Özdemir, B., Reski, R., & Röhrle, O. (2020). A NanoFE Simulation-based Surrogate Machine Learning Model to Predict Mechanical Functionality of Protein Networks from Live Confocal Imaging. Computational and Structural Biotechnology Journal, 18, 2774–2788. https://doi.org/10.1016/j.csbj.2020.09.024
    3. Asgharzadeh, P., Röhrle, O., Willie, B. M., & Birkhold, A. I. (2020). Decoding Rejuvenating Effects of Mechanical Loading on Skeletal Aging using in Vivo microCT Imaging and Deep Learning. Acta Biomaterialia. https://doi.org/10.1016/j.actbio.2020.02.007
    4. Brändle, S., Schmitt, S., & Müller, M. A. (2020). A systems-theoretic analysis of low-level human motor control: application to a single-joint arm model. J Math Biol, 80(4), Article 4. https://doi.org/10.1007/s00285-019-01455-z
    5. Emamy, N., Litty, P., Klotz, T., Mehl, M., & Röhrle, O. (2020). POD-DEIM Model Order Reduction for the Monodomain Reaction-Diffusion Sub-Model of the Neuro-Muscular System. IUTAM Symposium on Model Order Reduction of Coupled Systems, Stuttgart, Germany, May 22--25, 2018, 177--190. https://doi.org/10.1007/978-3-030-21013-7_13
    6. Günther, M., Haeufle, D. F. B., & Schmitt, S. (2020). Corrigendum to “The basic mechanical structure of the skeletal muscle machinery: One model for linking microscopic and macroscopic scales” Journal of Theoretical Biology 456 (2018) 137–167. Journal of Theoretical Biology, 488, 110143. https://doi.org/10.1016/j.jtbi.2019.110143
    7. Haeufle, D. F. B., Wochner, I., Holzmüller, D., Driess, D., Günther, M., & Schmitt, S. (2020). Muscles reduce neuronal information load: quantification of control effort in biological vs robotic pointing and walking. Frontiers in Robotics and AI -- Soft Robotics, 7, 77 (13pp). https://doi.org/10.3389/frobt.2020.00077
    8. Haeufle, D. F. B., Siegel, J., Hochstein, S., Gussew, A., Schmitt, S., Siebert, T., Rzanny, R., Reichenbach, J. R., & Stutzig, N. (2020). Energy Expenditure of Dynamic Submaximal Human Plantarflexion Movements: Model Prediction and Validation by in-vivo Magnetic Resonance Spectroscopy. Frontiers in Bioengineering and Biotechnology, 8. https://doi.org/10.3389/fbioe.2020.00622
    9. Haeufle, D. F. B., Stollenmaier, K., Heinrich, I., Schmitt, S., & Ghazi-Zahedi, K. (2020). Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy. Frontiers in Robotics and AI, 7. https://doi.org/10.3389/frobt.2020.511265
    10. Hessenthaler, A., Balmus, M., Röhrle, O., & Nordsletten, D. (2020). A class of analytic solutions for verification and convergence analysis of linear and nonlinear fluid-structure interaction algorithms. Computer Methods in Applied Mechanics and Engineering, 362, 112841. https://doi.org/10.1016/j.cma.2020.112841
    11. Hessenthaler, A., Southworth, B. S., Nordsletten, D., Röhrle, O., Falgout, R. D., & Schroder, J. B. (2020). Multilevel convergence analysis of multigrid-reduction-in-time. SIAM Journal on Scientific Computing, 42(2), Article 2. https://doi.org/10.1137/19M1238812
    12. Klotz, T., Gizzi, L., Yavuz, U., & Röhrle, O. (2020). Modelling the electrical activity of skeletal muscle tissue using a multi-domain approach. Biomechanics and Modelling in Mechanobiology, 19, 335–349. https://doi.org/10.1007/s10237-019-01214-5
    13. Lerge, P., Schmitt, S., & Martynenko, O. V. (2020). Simulation of Pedestrian Kinematics before Impact with a Vehicle using an Active Pedestrian Human Body Model. Proceedings of the International IRCOBI Conference, 210--212. http://www.ircobi.org/wordpress/downloads/irc20/pdf-files/27.pdf
    14. Martynenko, O. V., Nölle, L. V., & Schmitt, S. (2020). Integration of the Open-Source Extended Hill-type Muscle Material into THUMSv5. Proceedings of the International IRCOBI Conference, 205--206. http://www.ircobi.org/wordpress/downloads/irc20/pdf-files/25.pdf
    15. Mörl, F., Günther, M., Riede, J. M., Hammer, M., & Schmitt, S. (2020). Loads distributed in vivo among vertebrae, muscles, spinal ligaments, and intervertebral discs in a passively flexed lumbar spine. Biomechanics and Modeling in Mechanobiology, 19(6), Article 6. https://doi.org/10.1007/s10237-020-01322-7
    16. Nölle, L. V., Schmitt, S., & Martynenko, O. V. (2020). Defining Injury Criteria for the Muscle-Tendon-Unit. Proceedings of the International IRCOBI Conference, 811--813. http://www.ircobi.org/wordpress/downloads/irc20/pdf-files/89.pdf
    17. Rockenfeller, R., Günther, M., Stutzig, N., Haeufle, D. F. B., Siebert, T., Schmitt, S., Leichsenring, K., Böl, M., & Götz, T. (2020). Exhaustion of skeletal muscle fibers within seconds: incorporating phosphate kinetics into a Hill-type model. Frontiers in Physiology, 11, 306 (25pp). https://doi.org/10.3389/fphys.2020.00306
    18. Saini, H., Ackland, D. C., Gong, L., Cheng, L. K., & Röhrle, O. (2020). Occlusal load modelling significantly impacts the predicted tooth stress response during biting: a simulation study. Computer Methods in Biomechanics and Biomedical Engineering, 1--10. https://doi.org/10.1080/10255842.2020.1711886
    19. Walter, J. R., Saini, H., Maier, B., Mostashiri, N., Aguayo, J. L., Zarshenas, H., Hinze, C., Shuva, S., Köhler, J., Sahrmann, A. S., Chang, C., Csiszar, A., Galliani, S., Cheng, L. K., & Röhrle, O. (2020). Comparative Study of a Biomechanical Model-based and Black-box Approach for Subject-Specific Movement Prediction. 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 4775--4778. https://doi.org/10.1109/EMBC44109.2020.9176600
    20. Wochner, I., Driess, D., Zimmermann, H., Haeufle, D. F., Toussaint, M., & Schmitt, S. (2020). Optimality principles in human point-to-manifold reaching accounting for muscle dynamics. Frontiers in Computational Neuroscience, 14, 38. https://doi.org/10.3389/fncom.2020.00038

  6. 2019

    1. Bleiler, C., Ponte Castañeda, P., & Röhrle, O. (2019). A microstructurally-based, multi-scale, continuum-mechanical model for the passive behaviour of skeletal muscle tissue. Journal of the Mechanical Behavior of Biomedical Materials, 97, 171--186. https://doi.org/10.1016/j.jmbbm.2019.05.012
    2. Driess, D., Schmitt, S., & Toussaint, M. (2019). Active Inverse Model Learning with Error and Reachable Set Estimates. Proc. of the IEEE Int. Conf. on Intelligent Robotsand Systems (IROS). https://doi.org/10.1109/IROS40897.2019.8967858
    3. Gizzi, L., Röhrle, O., Petzke, F., & Falla, D. (2019). People with low back pain show reduced movement complexity during their most active daily tasks. European Journal of Pain, 23(2), Article 2. https://doi.org/10.1002/ejp.1318
    4. Gommeringer, A., Nölle, L. V., Kern, F., & Gadow, R. (2019). Yttria Ceria Co-Stabilized Zirconia Reinforced with Alumina and Strontium Hexaaluminate. Applied Sciences, 9(4), Article 4. https://doi.org/10.3390/app9040729
    5. Hammer, M., Günther, M., Haeufle, D. F. B., & Schmitt, S. (2019). Tailoring anatomical muscle paths: a sheath-like solution for muscle routing in musculo-skeletal computer models. Mathematical Biosciences, 311, 68–81. https://doi.org/10.1016/j.mbs.2019.02.004
    6. Röhrle, O., Yavuz, U. S., Klotz, T., Negro, F., & Heidlauf, T. (2019). Multiscale modeling of the neuromuscular system: Coupling neurophysiology and skeletal muscle mechanics. Wiley Interdisciplinary Reviews: Systems Biology and Medicine, e1457. https://doi.org/10.1002/wsbm.1457
    7. Schmid, L., Klotz, T., Siebert, T., & Röhrle, O. (2019). Characterization of electromechanical delay based on a biophysical multi-scale skeletal muscle model. Frontiers in Physiology, 10, 1270. https://doi.org/10.3389/fphys.2019.01270
    8. Schmitt, S., Günther, M., & Haeufle, D. F. B. (2019). The dynamics of the skeletal muscle: a systems biophysics perspective on muscle modeling with the focus on Hill-type muscle models. GAMM--Mitteilungen, 58, e201900013. https://doi.org/10.1002/gamm.201900013
    9. Tomalka, A., Röhrle, O., Han, J.-C., Pham, T., Taberner, A. J., & Siebert, T. (2019). Extensive eccentric contractions in intact cardiac trabeculae: revealing compelling differences in contractile behaviour compared to skeletal muscles. Proceedings of the Royal Society B, 286(1903), Article 1903. https://doi.org/10.1098/rspb.2019.0719

  7. 2018

    1. Asgharzadeh, P., Özdemir, B., Reski, R., Röhrle, O., & Birkhold, A. I. (2018). Computational 3D imaging to quantify structural components and assembly of protein networks. Acta Biomaterialia, 69, 206--217. https://doi.org/10.1016/j.actbio.2018.01.020
    2. Bradley, C. P., Emamy, N., Ertl, T., Göddeke, D., Hessenthaler, A., Klotz, T., Krämer, A., Krone, M., Maier, B., Mehl, M., Rau, T., & Röhrle, O. (2018). Enabling Detailed, Biophysics-Based Skeletal Muscle Models on HPC Systems. Frontiers in Physiology, 9. https://doi.org/10.3389/fphys.2018.00816
    3. Driess, D., Zimmermann, H., Wolfen, S., Suissa, D., Haeufle, D., Hennes, D., Toussaint, M., & Schmitt, S. (2018). Learning to Control Redundant Musculoskeletal Systems with Neural Networks and SQP: Exploiting Muscle Properties. Proc. of the International Conference on Robotics and Automation. https://doi.org/10.1109/ICRA.2018.8463160
    4. Eggs, B., Birkhold, A. I., Röhrle, O., & Betz, O. (2018). Structure and function of the musculoskeletal ovipositor system of an ichneumonid wasp. BMC Zoology, 3(1), Article 1. https://doi.org/10.1186/s40850-018-0037-2
    5. Günther, M., Haeufle, D. F. B., & Schmitt, S. (2018). The basic mechanical structure of the skeletal muscle machinery: One model for linking microscopic and macroscopic scales. Journal of Theoretical Biology, 456, 137–167. https://doi.org/10.1016/j.jtbi.2018.07.023
    6. Haeufle, D. F., Schmortte, B., Geyer, H., Müller, R., & Schmitt, S. (2018). The benefit of combining neuronal feedback and feed-forward control for robustness in step down perturbations of simulated human walking depends on the muscle function. Frontiers in Computational Neuroscience, 12, 80. https://www.frontiersin.org/articles/10.3389/fncom.2018.00080/full
    7. Hessenthaler, A., Nordsletten, D., Röhrle, O., Schroder, J. B., & Falgout, R. D. (2018). Convergence of the multigrid reduction in time algorithm for the linear elasticity equations. Numerical Linear Algebra with Applications, 25(3), Article 3. https://doi.org/10.1002/nla.2155
    8. Hoekstra, A. G., van de Vosse, F., & Röhrle, O. (2018). The virtual physiological human conference 2016. Journal of Computational Science, 24, 65--67. https://doi.org/10.1016/j.jocs.2017.11.014
    9. Ramasamy, E., Avci, O., Dorow, B., Chong, S.-Y., Gizzi, L., Steidle, G., Schick, F., & Röhrle, O. (2018). An efficient modelling-simulation-analysis workflow to investigate stump-socket interaction using patient-specific, three-dimensional, continuum-mechanical, finite element residual limb models. Frontiers in Bioengineering and Biotechnology, 6. https://dx.doi.org/10.3389%2Ffbioe.2018.00126
    10. Rockenfeller, R., & Günther, M. (2018). Inter-filament spacing mediates calcium binding to troponin: A simple geometric-mechanistic model explains the shift of force-length maxima with muscle activation. Journal of Theoretical Biology, 454, 240–252. https://doi.org/10.1016/j.jtbi.2018.06.009
    11. Roehrle, O., Saini, H., & Ackland, D. C. (2018). Occlusal loading during biting from an experimental and simulation point of view. Dental Materials, 34(1), Article 1. https://doi.org/10.1016/j.dental.2017.09.005
    12. Röhrle, O., Saini, H., Lee, P. V., & Ackland, D. C. (2018). A novel computational method to determine subject-specific bite force and occlusal loading during mastication. Computer Methods in Biomechanics and Biomedical Engineering, 21(6), Article 6. https://doi.org/10.1080/10255842.2018.1479744
    13. Schneider, M., Buschbaum, J., Joeris, A., Röhrle, O., Dwyer, J., Hunter, J. B., Reynolds, R. A., Slongo, T. F., Gueorguiev, B., & Varga, P. (2018). Biomechanical investigation of two long bone growth modulation techniques by finite element simulations. Journal of Orthopaedic Research®, 36(5), Article 5. https://doi.org/10.1002/jor.23762
    14. Suissa, D., Günther, M., Shapiro, A., Melzer, I., & Schmitt, S. (2018). On laterally perturbed human stance: experiment, model, and control. Applied Bionics and Biomechanics, 4767624 (20pp). https://doi.org/10.1155/2018/4767624
    15. Valentin, J., Sprenger, M., Pflüger, D., & Röhrle, O. (2018). Gradient-based optimization with B-splines on sparse grids for solving forward-dynamics simulations of three-dimensional, continuum-mechanical musculoskeletal system models. International Journal for Numerical Methods in Biomedical Engineering, 34(5), Article 5. https://doi.org/10.1002/cnm.2965
    16. Wolfen, S., Walter, J., Günther, M., Haeufle, D. F. B., & Schmitt, S. (2018). Bioinspired pneumatic muscle spring units mimicking the human motion apparatus: benefits for passive motion range and joint stiffness variation in antagonistic setups. 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), (6pp). https://doi.org/10.1109/M2VIP.2018.8600913
    17. Özdemir, B., Asgharzadeh, P., Birkhold, A. I., Mueller, S. J., Röhrle, O., & Reski, R. (2018). Cytological analysis and structural quantification of FtsZ1-2 and FtsZ2-1 network characteristics in Physcomitrella patens. Scientific Reports, 8(1), Article 1. https://doi.org/10.1038/s41598-018-29284-y

  8. 2017

    1. Bayer, A., Schmitt, S., Günther, M., & Haeufle, D. F. B. (2017). The influence of biophysical muscle properties on simulating fast human arm movements. Computer Methods in Biomechanics and Biomedical Engineering, 20(8), Article 8. https://doi.org/10.1080/10255842.2017.1293663
    2. Brown, N., Bubeck, D., Haeufle, D. F. B., Weickenmeier, J., Kuhl, E., Alt, W., & Schmitt, S. (2017). Weekly Time Course of Neuro-Muscular Adaptation to Intensive Strength Training. Frontiers in Physiology, 8, 329. https://doi.org/10.3389/fphys.2017.00329
    3. Christensen, K. B., Günther, M., Schmitt, S., & Siebert, T. (2017). Strain in shock-loaded skeletal muscle and the time scale of muscular wobbling mass dynamics. Scientific Reports, 7, 13266 (11pp). https://doi.org/10.1038/s41598-017-13630-7
    4. Heidlauf, T., Klotz, T., Rode, C., Siebert, T., & Röhrle, O. (2017). A continuum-mechanical skeletal muscle model including actin-titin interaction predicts stable contractions on the descending limb of the force-length relation. PLoS Computational Biology, 13(10), Article 10. https://doi.org/10.1371/journal.pcbi.1005773
    5. Hessenthaler, A., Gaddum, N., Holub, O., Sinkus, R., Röhrle, O., & Nordsletten, D. (2017). Experiment for validation of fluid-structure interaction models and algorithms. International Journal for Numerical Methods in Biomedical Engineering, 33(9), Article 9. https://dx.doi.org/10.1002%2Fcnm.2848
    6. Hessenthaler, A., Röhrle, O., & Nordsletten, D. (2017). Validation of a non-conforming monolithic fluid-structure interaction method using phase-contrast MRI. International Journal for Numerical Methods in Biomedical Engineering, 33(8), Article 8. https://doi.org/10.1002/cnm.2845
    7. Kleinbach, C., Martynenko, O., Promies, J., Haeufle, D. F., Fehr, J., & Schmitt, S. (2017). Implementation and validation of the extended Hill-type muscle model with robust routing capabilities in LS-DYNA for active human body models. Biomedical Engineering Online, 16(1), Article 1. https://doi.org/10.1186/s12938-017-0399-7
    8. Krohn, B., Sathar, S., Röhrle, O., Vanderwinden, J.-M., O’Grady, G., & Cheng, L. K. (2017). A framework for simulating gastric electrical propagation in confocal microscopy derived geometries. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 4215--4218. https://doi.org/10.1109/EMBC.2017.8037786
    9. Lindemann, U., Schwenk, M., Schmitt, S., Weyrich, M., Schlicht, W., & Becker, C. (2017). Effect of uphill and downhill walking on walking performance in geriatric patients using a wheeled walker. Zeitschrift Für Gerontologie Und Geriatrie, 50(6), Article 6. https://doi.org/10.1007/s00391-016-1156-4
    10. Martynenko, O., Kleinbach, C., Hammer, M., Haeufle, D. F. B., Mayer, C., & Schmitt, S. (2017). Advanced Hill-type Muscle model as User Defined Material in LS-DYNA with Routing Capability for Application in Active Human Body Models. Proceedings of the International IRCOBI Conference, 679--680. http://www.ircobi.org/wordpress/downloads/irc17/pdf-files/91.pdf
    11. Mordhorst, M., Strecker, T., Wirtz, D., Heidlauf, T., & Röhrle, O. (2017). POD-DEIM reduction of computational EMG models. Journal of Computational Science, 19, 86--96. https://doi.org/10.1016/j.jocs.2017.01.009
    12. Rockenfeller, R., & Günther, M. (2017). Hill equation and Hatze’s muscle activation dynamics complement each other: enhanced pharmacological and physiological interpretability of modelled activity-pCa curves. Journal of Theoretical Biology, 431, 11–24. https://doi.org/10.1016/j.jtbi.2017.07.023
    13. Rockenfeller, R., & Günther, M. (2017). How to model a muscle’s active force-length relation: A comparative study. Computer Methods in Applied Mechanics and Engineering, 313, 321–336. https://doi.org/10.1016/j.cma.2016.10.003
    14. Rockenfeller, R., Günther, M., Schmitt, S., & Götz, T. (2017). Corrigendum to ``Comparative Sensitivity Analysis of Muscle Activation Dynamics’’. Computational and Mathematical Methods in Medicine, 2017, 2. https://doi.org/10.1155/2017/6752731
    15. Röhrle, O., Sprenger, M., & Schmitt, S. (2017). A two-muscle, continuum-mechanical forward simulation of the upper limb. Biomechanics and Modeling in Mechanobiology, 16(3), Article 3. https://doi.org/10.1007/s10237-016-0850-x
    16. Zderic, I., Steinmetz, P., Benneker, L. M., Sprecher, C., Röhrle, O., Windolf, M., Boger, A., & Gueorguiev, B. (2017). Bone cement allocation analysis in artificial cancellous bone structures. Journal of Orthopaedic Translation, 8, 40--48. https://doi.org/10.1016/j.jot.2016.09.002

  9. 2016

    1. Asgharzadeh, P., Özdemir, B., Müller, S. J., Reski, R., & Röhrle, O. (2016). Analysis of confocal microscopy image data of Physcomitrella chloroplasts to reveal adaptation principles leading to structural stability at the nanoscale. PAMM, 16(1), Article 1.
    2. Chong, S.-Y., & Röhrle, O. (2016). Exploring the Use of Non-Image-Based Ultrasound to Detect the Position of the Residual Femur within a Stump. PloS One, 11(10), Article 10. https://dx.doi.org/10.1371%2Fjournal.pone.0164583
    3. Ghazi-Zahedi, K., Haeufle, D. F., Montúfar, G., Schmitt, S., & Ay, N. (2016). Evaluating morphological computation in muscle and dc-motor driven models of hopping movements. Frontiers in Robotics and AI, 3, 42. https://doi.org/10.3389/frobt.2016.00042/full
    4. Günther, M., & Wagner, H. (2016). Dynamics of quiet human stance: computer simulations of a triple inverted pendulum model. Computer Methods in Biomechanics and Biomedical Engineering, 19(8), Article 8. https://doi.org/10.1080/10255842.2015.1067306
    5. Haeufle, D. F., Bäuerle, T., Steiner, J., Bremicker, L., Schmitt, S., & Bechinger, C. (2016). External control strategies for self-propelled particles: Optimizing navigational efficiency in the presence of limited resources. Physical Review E, 94(1), Article 1. https://doi.org/10.1103/PhysRevE.94.012617
    6. Heidlauf, T., Klotz, T., Rode, C., Altan, E., Bleiler, C., Siebert, T., & Röhrle, O. (2016). A multi-scale continuum model of skeletal muscle mechanics predicting force enhancement based on actin--titin interaction. Biomechanics and Modeling in Mechanobiology, 15(6), Article 6. https://doi.org/10.1007/s10237-016-0772-7
    7. Hochstein, S., Rauschenberger, P., Weigand, B., Siebert, T., Schmitt, S., Schlicht, W., Převorovská, S., & Maršík, F. (2016). Assessment of physical activity of the human body considering the thermodynamic system. Computer Methods in Biomechanics and Biomedical Engineering, 19(9), Article 9. https://doi.org/10.1080/10255842.2015.1076804
    8. Rockenfeller, R., & Günther, M. (2016). Extracting low-velocity concentric and eccentric dynamic muscle properties from isometric contraction                  experiments. Mathematical Biosciences, 278, 77–93. https://doi.org/10.1016/j.mbs.2016.06.005
    9. Röhrle, O., Neumann, V., & Heidlauf, T. (2016). The role of parvalbumin, sarcoplasmatic reticulum calcium pump rate, rates of cross-bridge dynamics, and ryanodine receptor calcium current on peripheral muscle fatigue: a simulation study. Computational and Mathematical Methods in Medicine, 2016. https://doi.org/10.1155/2016/3180205
    10. Steinmetz, P., Benneker, L. M., Röhrle, O., Windolf, M., Boger, A., & Gueorguiev, B. (2016). Bone cement allocation analysis in artificial cancellous bone structures. Journal of Orthopaedic Translation, 20, 1e9.

  10. 2015

    1. Bleiler, C., Wagner, A., Stadelmann, V. A., Windolf, M., Köstler, H., Boger, A., Gueorguiev-Rüegg, B., Ehlers, W., & Röhrle, O. (2015). Multiphasic modelling of bone-cement injection into vertebral cancellous bone. International Journal for Numerical Methods in Biomedical Engineering, 31(1), Article 1.
    2. Chong, S.-Y., Dorow, B., Ramasamy, E., Dennerlein, F., & Röhrle, O. (2015). The use of collision detection to infer multi-camera calibration quality. Frontiers in Bioengineering and Biotechnology, 3, 65.
    3. Kupczik, K., Stark, H., Mundry, R., Neininger, F. T., Heidlauf, T., & Röhrle, O. (2015). Reconstruction of muscle fascicle architecture from iodine-enhanced microCT images: a combined texture mapping and streamline approach. Journal of Theoretical Biology, 382, 34--43.
    4. Mordhorst, M., Heidlauf, T., & Röhrle, O. (2015). Predicting electromyographic signals under realistic conditions using a multiscale chemo--electro--mechanical finite element model. Interface Focus, 5(2), Article 2.
    5. Rockenfeller, R., Günther, M., Schmitt, S., & Götz, T. (2015). Comparative sensitivity analysis of muscle activation dynamics. Computational and Mathematical Methods in Medicine, 585409 (16pp). https://doi.org/10.1155/2015/585409
    6. Rupp, T. K., Ehlers, W., Karajan, N., Günther, M., & Schmitt, S. (2015). A forward dynamics simulation of human lumbar spine flexion predicting the load sharing of intervertebral discs, ligaments, and muscles. Biomechanics and Modeling in Mechanobiology, 14(5), Article 5. https://doi.org/10.1007/s10237-015-0656-2
    7. Weihmann, T., Goetzke, H. H., & Günther, M. (2015). Requirements and limits of anatomy-based predictions of locomotion in terrestrial arthropods with emphasis on arachnids. Journal of Paleontology, 89(6), Article 6. https://doi.org/10.1017/jpa.2016.33

  11. 2014

    1. David, S., Schmitt, S., Utz, J., Hub, A., & Schlicht, W. (2014). Navigation within buildings: Novel movement detection algorithms supporting people with visual impairments. Research in Developmental Disabilities, 35(9), Article 9. https://doi.org/10.1016/j.ridd.2014.04.032
    2. Gaitzsch, J., Appelhans, D., Janke, A., Strempel, M., Schwille, P., & Voit, B. (2014). Cross-linked and pH sensitive supported polymer bilayers from polymersomes--studies concerning thickness, rigidity and fluidity. Soft Matter, 10(1), Article 1.
    3. Haeufle, D. F. B., Günther, M., Bayer, A., & Schmitt, S. (2014). Hill-type muscle model with serial damping and eccentric force-velocity relation. Journal of Biomechanics, 47(6), Article 6. https://doi.org/10.1016/j.jbiomech.2014.02.009
    4. Haeufle, D. F. B., Günther, M., Wunner, G., & Schmitt, S. (2014). Quantifying control effort of biological and technical movements: An information-entropy-based approach. Physical Review E, 89, 012716. https://doi.org/10.1103/PhysRevE.89.012716
    5. Heidlauf, T., & Röhrle, O. (2014). A multiscale chemo-electro-mechanical skeletal muscle model to analyze muscle contraction and force generation for different muscle fiber arrangements. Frontiers in Physiology, 5, 498.
    6. Kieser, J., Farland, M., Jack, H., Farella, M., Wang, Y., & Rohrle, O. (2014). The role of oral soft tissues in swallowing function: what can tongue pressure tell us? Australian Dental Journal, 59, 155--161.
    7. Lipfert, S. W., Günther, M., Renjewski, D., & Seyfarth, A. (2014). Impulsive ankle push-off powers leg swing in human walking. The Journal of Experimental Biology, 217(Pt 8), Article Pt 8. https://doi.org/10.1242/​jeb.097345
    8. Ramasamy, E., Dorow, B., Schneider, U., & Roehrle, O. (2014). Simulation-assisted prosthetic design. BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 59, S1021--S1021.
    9. Rosenfeld, E. V., & Günther, M. (2014). An enhanced model of cross-bridge operation with internal elasticity. European Biophysics Journal, 43(4–5), Article 4–5. https://doi.org/10.1007/s00249-014-0947-z
    10. Siebert, T., Till, O., Stutzig, N., Günther, M., & Blickhan, R. (2014). Muscle force depends on the amount of transversal muscle loading. Journal of Biomechanics, 47(8), Article 8. https://doi.org/10.1016/j.jbiomech.2014.03.029

  12. 2013

    1. Fürthauer, S., Strempel, M., Grill, S. W., & Jülicher, F. (2013). Active chiral processes in thin films. Physical Review Letters, 110(4), Article 4.
    2. Heidlauf, T., Negro, F., Farina, D., & Röhrle, O. (2013). An integrated model of the neuromuscular system. 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 227--230.
    3. Heidlauf, T., & Röhrle, O. (2013). Modeling the chemoelectromechanical behavior of skeletal muscle using the parallel open-source software library OpenCMISS. Computational and Mathematical Methods in Medicine, 2013.
    4. Karajan, N., Röhrle, O., Ehlers, W., & Schmitt, S. (2013). Linking continuous and discrete intervertebral disc models through homogenisation. Biomechanics and Modeling in Mechanobiology, 12(3), Article 3.
    5. Schmitt, S., Günther, M., Rupp, T. K., Bayer, A., & Haeufle, D. F. B. (2013). Theoretical Hill-type muscle and stability: numerical model and application. Computational and Mathematical Methods in Medicine, 570878 (7pp). https://doi.org/10.1155/2013/570878
    6. Wang, Y. K., Nash, M. P., Pullan, A. J., Kieser, J. A., & Röhrle, O. (2013). Model-based identification of motion sensor placement for tracking retraction and elongation of the tongue. Biomechanics and Modeling in Mechanobiology, 12(2), Article 2.

  13. 2012

    1. Fürthauer, S., Strempel, M., Grill, S. W., & Jülicher, F. (2012). Active chiral fluids. The European Physical Journal E, 35(9), Article 9.
    2. Günther, M., Haeufle, D. F. B., Röhrle, O., & Schmitt, S. (2012). Spreading out muscle mass within a Hill-type model: A computer simulation study. Computational and Mathematical Methods in Medicine, 848630 (13pp). https://doi.org/10.1155/2012/848630
    3. Günther, M., Müller, O., & Blickhan, R. (2012). What does head movement tell about the minimum number of mechanical degrees of freedom in quiet human stance? Archive of Applied Mechanics, 82(3), Article 3. https://doi.org/10.1007/s00419-011-0559-3
    4. Günther, M., & Weihmann, T. (2012). Climbing in hexapods: A plain model for heavy slopes. Journal of Theoretical Biology, 293, 82–86. https://doi.org/10.1016/j.jtbi.2011.10.011
    5. Haeufle, D. F. B., Günther, M., Blickhan, R., & Schmitt, S. (2012). Proof of concept: model based bionic muscle with hyperbolic force-velocity relation. Applied Bionics and Biomechanics, 9(3), Article 3. https://doi.org/10.3233/ABB-2011-0052
    6. Haeufle, D. F. B., Günther, M., Blickhan, R., & Schmitt, S. (2012). Can quick release experiments reveal the muscle structure? A bionic approach. Journal of Bionic Engineering, 9(2), Article 2. https://doi.org/10.1016/S1672-6529(11)60115-7
    7. Haeufle, D. F. B., Taylor, M. D., Schmitt, S., & Geyer, H. (2012). A clutched parallel elastic actuator concept: Towards energy efficient powered legs in prosthetics and robotics. 2012 4th IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), 1614–1619. https://doi.org/10.1109/BioRob.2012.6290722
    8. Lipfert, S. W., Günther, M., Renjewski, D., Grimmer, S., & Seyfarth, A. (2012). A model-experiment comparison of system dynamics for human walking and running. Journal of Theoretical Biology, 292, 11–17. https://doi.org/10.1016/j.jtbi.2011.09.021
    9. Mörl, F., Siebert, T., Schmitt, S., Blickhan, R., & Günther, M. (2012). Electro-mechanical delay in Hill-type muscle models. Journal of Mechanics in Medicine and Biology, 12(5), Article 5. https://doi.org/10.1142/S0219519412500856
    10. Röhrle, O., Davidson, J. B., & Pullan, A. J. (2012). A physiologically based, multi-scale model of skeletal muscle structure and function. Frontiers in Physiology, 3, 358.
    11. Schmitt, S., Haeufle, D. F. B., Blickhan, R., & Günther, M. (2012). Nature as an engineer: one simple concept of bio-inspired functional artificial muscle. Bioinspiration & Biomimetics, 7(3), Article 3. https://doi.org/10.1088/1748-3182/7/3/036022
    12. Siebert, T., Günther, M., & Blickhan, R. (2012). A 3D-geometric model for the deformation of a transversally loaded muscle. Journal of Theoretical Biology, 298, 116–121. https://doi.org/10.1016/j.jtbi.2012.01.009
    13. Weihmann, T., Günther, M., & Blickhan, R. (2012). Hydraulic leg-extension is not necessarily the main drive in large spiders. The Journal of Experimental Biology, 215(Pt 4), Article Pt 4. https://doi.org/10.1242/jeb.054585

  14. 2011

    1. Bradley, C., Bowery, A., Britten, R., Budelmann, V., Camara, O., Christie, R., Cookson, A., Frangi, A. F., Gamage, T. B., Heidlauf, T., & others. (2011). OpenCMISS: a multi-physics & multi-scale computational infrastructure for the VPH/Physiome project. Progress in Biophysics and Molecular Biology, 107(1), Article 1.
    2. Günther, M. (2011). Biomechanik: Eine Naturwissenschaft. In T. Ertelt (Ed.), Beiträge zur Bewegungswissenschaft (Vol. 2, pp. 1–8). Verlag Dr. Kovac.
    3. Günther, M., Müller, O., & Blickhan, R. (2011). Watching quiet human stance to shake off its straitjacket. Archive of Applied Mechanics, 81(3), Article 3. https://doi.org/10.1007/s00419-010-0414-y
    4. Günther, M., Putsche, P., Leistritz, L., & Grimmer, S. (2011). Phase synchronisation of the three leg joints in quiet human stance. Gait & Posture, 33(3), Article 3. https://doi.org/10.1016/j.gaitpost.2010.12.014
    5. Günther, M., & Weihmann, T. (2011). The load distribution among three legs on the wall: model predictions for cockroaches. Archive of Applied Mechanics, 81(9), Article 9. https://doi.org/10.1007/s00419-010-0485-9
    6. Haeufle, D. F. B., Günther, M., Blickhan, R., & Schmitt, S. (2011). Proof of concept of an artificial muscle: theoretical model, numerical model and hardware experiment (pp. 1–6). https://doi.org/10.1109/ICORR.2011.5975336
    7. Rupp, T., & Schmitt, S. (2011). Inverse dynamics of the lower extremities: novel approach considering upper and lower ankle joint axis. Journal of Mechanics in Medicine and Biology, 13 pages.
    8. Schmitt, S., & Günther, M. (2011). Human leg impact: energy dissipation of wobbling masses. Archive of Applied Mechanics, 81(7), Article 7. https://doi.org/10.1007/s00419-010-0458-z

  15. 2010

    1. Günther, M., & Schmitt, S. (2010). A macroscopic ansatz to deduce the Hill relation. Journal of Theoretical Biology, 263(4), Article 4. https://doi.org/10.1016/j.jtbi.2009.12.027
    2. Günther, M., & Weihmann, T. (2010). Wie Küchenschaben den Absturz verhindern können, wenn es heftig steil wird: eine Modellbetrachtung. In T. Ertelt (Ed.), Beiträge zur Bewegungswissenschaft (Vol. 1, pp. 87–95). Verlag Dr. Kovac.
    3. Häufle, D. F. B., Günther, M., Blickhan, R., & Schmitt, S. (2010). Proof of concept: model based bionic muscle with hyperbolic force-velocity relation. Proceedings of the First International Conference of Applied Biomechanics and Bionics, 7 pages.
    4. Roth, R., Wank, V., Müller, O., Hochwald, H., & Günther, M. (2010). A simple new device to examine human stance: the totter-slab. Biomedizinische Technik, 55(1), Article 1. https://doi.org/10.1515/BMT.2010.004
    5. Röhrle, O. (2010). Simulating the electro-mechanical behavior of skeletal muscles. Computing in Science & Engineering, 12(6), Article 6.
    6. Schmid, H., Watton, P., Maurer, M., Wimmer, J., Winkler, P., Wang, Y., Röhrle, O., & Itskov, M. (2010). Impact of transmural heterogeneities on arterial adaptation. Biomechanics and Modeling in Mechanobiology, 9(3), Article 3.
    7. Siebert, T., Günther, M., & Mörl, F. (2010). Vorhersage des elektromechanischen Delays (EMD) unter Verwendung einfacher Hill-Typ Muskelmodelle. In T. Ertelt (Ed.), Beiträge zur Bewegungswissenschaft (Vol. 1, pp. 5–18). Verlag Dr. Kovac.

  16. 2009

    1. Günther, M., Grimmer, S., Siebert, T., & Blickhan, R. (2009). All leg joints contribute to quiet human stance: a mechanical analysis. Journal of Biomechanics, 42(16), Article 16. https://doi.org/10.1016/j.jbiomech.2009.08.014
    2. Lipfert, S. W., Günther, M., & Seyfarth, A. (2009). Diverging times in movement analysis. Journal of Biomechanics, 42(6), Article 6. https://doi.org/10.1016/j.jbiomech.2008.12.020
    3. Melnyk, M., Schloz, C., Schmitt, S., & Gollhofer, A. (2009). Neuromuscular ankle joint stabilisation after 4-weeks WBV training. International Journal of Sports Medicine, 30(6), Article 6. https://doi.org/10.1055/s-0028-1112141
    4. Röhrle, O., Waddell, J. N., Foster, K. D., Saini, H., & Pullan, A. J. (2009). Using a motion-capture system to record dynamic articulation for application in CAD/CAM software. Journal of Prosthodontics: Implant, Esthetic and Reconstructive Dentistry, 18(8), Article 8.
    5. Saini, H., Wadell, J., Pullan, A., & Röhrle, O. (2009). Automatically generating subject-specific functional tooth surfaces using virtual mastication. Annals of Biomedical Engineering, 37(8), Article 8.
    6. Schmitt, S., Melnyk, M., Alt, W., & Gollhofer, A. (2009). Novel approach for a precise determination of short-time intervals in ankle sprain experiments. Journal of Biomechanics, 42, 2823–2825. https://doi.org/10.1016/j.jbiomech.2009.08.015

  17. 2008

    1. Grimmer, S., Ernst, M., Günther, M., & Blickhan, R. (2008). Running on uneven ground: leg adjustment to vertical steps and self-stability. The Journal of Experimental Biology, 211(Pt 18), Article Pt 18. https://doi.org/10.1242/jeb.014357
    2. Günther, M., Otto, D., Müller, O., & Blickhan, R. (2008). Transverse pelvic rotation during quiet human stance. Gait & Posture, 27(3), Article 3. https://doi.org/10.1016/j.gaitpost.2007.05.014
    3. Röhrle, O., Davidson, J. B., & Pullan, A. J. (2008). Bridging scales: a three-dimensional electromechanical finite element model of skeletal muscle. SIAM Journal on Scientific Computing, 30(6), Article 6.
    4. Xu, W., Bronlund, J., Potgieter, J., Foster, K., Röhrle, O., Pullan, A., & Kieser, J. (2008). Review of the human masticatory system and masticatory robotics. Mechanism and Machine Theory, 43(11), Article 11.

  18. 2007

    1. Blickhan, R., Seyfarth, A., Geyer, H., Grimmer, S., Wagner, H., & Günther, M. (2007). Intelligence by mechanics. Philosophical Transactions of the Royal Society A, 365(1850), Article 1850. https://doi.org/10.1098/rsta.2006.1911
    2. Günther, M., Schmitt, S., & Wank, V. (2007). High-frequency oscillations as a consequence of neglected serial damping in Hill-type muscle models. Biological Cybernetics, 97(1), Article 1. https://doi.org/10.1007/s00422-007-0160-6
    3. Kim, J. H., Davidson, J. B., Röhrle, O., Soboleva, T. K., & Pullan, A. J. (2007). Anatomically based lower limb nerve model for electrical stimulation. Biomedical Engineering Online, 6(1), Article 1.
    4. Röhrle, O., & Pullan, A. J. (2007). Three-dimensional finite element modelling of muscle forces during mastication. Journal of Biomechanics, 40(15), Article 15.
    5. Schmid, H., Nash, M., Young, A., Röhrle, O., & Hunter, P. (2007). A computationally efficient optimization kernel for material parameter estimation procedures. Journal of Biomechanical Engineering, 129(2), Article 2.
    6. Schmitt, S., Kettler, A., Mutschler, H., Schmidt, H., Ruder, H., & Wilke, H.-J. (2007). Simulation von Störungen auf die Lumbalwirbelsäule - eine Projektskizze. In VDI Berichte Nr. 2002 (Ed.), Humanschwingungen (pp. 277–291). Düsseldorf, VDI.

  19. 2006

    1. Blickhan, R., Seyfarth, A., Wagner, H., Friedrichs, A., Günther, M., & Maier, K. D. (2006). Robust behaviour of the human leg. In H. Kimura, K. Tsuchiya, A. Ishiguro, & H. Witte (Eds.), Adaptive Motion of Animals and Machines (pp. 5–16). Springer. https://doi.org/10.1007/4-431-31381-8_2
    2. Kim, S. D., Lee, C.-O., Manteuffel, T. A., McCormick, S. F., & Röhrle, O. (2006). First-order system least squares for the Oseen equations. Numerical Linear Algebra with Applications, 13(7), Article 7.
    3. Manteuffel, T. A., McCormick, S. F., & Röhrle, O. (2006). Projection multilevel methods for quasilinear elliptic partial differential equations: Theoretical results. SIAM Journal on Numerical Analysis, 44(1), Article 1.
    4. Manteuffel, T. A., McCormick, S. F., Röhrle, O., & Ruge, J. (2006). Projection multilevel methods for quasilinear elliptic partial differential equations: numerical results. SIAM Journal on Numerical Analysis, 44(1), Article 1.

  20. 2005

    1. Blickhan, R., Wank, V., & Günther, M. (2005). Energieabsorption, Energiespeicherung und Arbeit bei schneller Lokomotion über unebenes Terrain. In F. Pfeiffer & H. Cruse (Eds.), Autonomes Laufen (pp. 71–96). Springer. https://doi.org/10.1007/3-540-26453-1_5
    2. Günther, M., Witte, H., & Blickhan, R. (2005). Joint energy balances: the commitment to the synchronization of measuring systems. Journal of Mechanics in Medicine and Biology, 5(1), Article 1. https://doi.org/10.1142/s0219519405001345

  21. 2004

    1. Blickhan, R., Günther, M., Maier, K. D., Seyfarth, A., & Wagner, H. (2004). Robustes Laufen: Biomechanische Grundlagenforschung für Biologie, Robotik und Sport. In H. Riehle (Ed.), Biomechanik als Anwendungsforschung -- Transfer zwischen Theorie und Praxis (Vol. 132, pp. 24–34). Czwalina.
    2. Günther, M., Keppler, V., Seyfarth, A., & Blickhan, R. (2004). Human leg design: optimal axial alignment under constraints. Journal of Mathematical Biology, 48(6), Article 6. https://doi.org/10.1007/s00285-004-0269-3
    3. Müller, O., Günther, M., Krauß, I., & Horstmann, T. (2004). Physikalische Charakterisierung des Therapiegerätes Posturomed als Messgerät -- Vorstellung eines Verfahrens zur Quantifizierung des Balancevermögens. Biomedizinische Technik, 49(3), Article 3. https://doi.org/10.1515/BMT.2004.011
    4. Seyfarth, A., Günther, M., & Blickhan, R. (2004). Beinsteifigkeit als Schlüssel zur Charakterisierung der Gelenkfunktion bei repulsiver Beinbeanspruchung. In H. Riehle (Ed.), Biomechanik als Anwendungsforschung - Transfer                  zwischen Theorie und Praxis (Vol. 132, pp. 151–155). Czwalina.

  22. 2003

    1. Günther, M., & Ruder, H. (2003). Synthesis of two-dimensional human walking: a test of the $łambda$-model. Biological Cybernetics, 89(2), Article 2. https://doi.org/10.1007/s00422-003-0414-x
    2. Günther, M., Sholukha, V. A., Keßler, D., Wank, V., & Blickhan, R. (2003). Dealing with skin motion and wobbling masses in inverse dynamics. Journal of Mechanics in Medicine and Biology, 3(3/4), Article 3/4. https://doi.org/10.1142/S0219519403000831

  23. 2002

    1. Günther, M., & Blickhan, R. (2002). Joint stiffness of the ankle and the knee in running. Journal of Biomechanics, 35(11), Article 11. https://doi.org/10.1016/S0021-9290(02)00183-5
    2. Seyfarth, A., Geyer, H., Günther, M., & Blickhan, R. (2002). A movement criterion for running. Journal of Biomechanics, 35(5), Article 5. https://doi.org/10.1016/S0021-9290(01)00245-7

  24. 2001

    1. Seyfarth, A., Geyer, H., Günther, M., & Blickhan, R. (2001). Stability of running with elastic legs. In R. Blickhan (Ed.), Motion Systems (pp. 92–95). Shaker Verlag.
    2. Seyfarth, A., Günther, M., & Blickhan, R. (2001). Stable operation of an elastic three-segment leg. Biological Cybernetics, 84(5), Article 5. https://doi.org/10.1007/PL00007982

  25. 1994

    1. Ruder, H., Ertl, T., Gruber, K., Günther, M., Hospach, F., Ruder, M., Subke, J., & Widmayer, K. (1994). Kinematics and dynamics for computer animation. In S. Coquillart, W. Straßer, & P. Stucki (Eds.), From Object Modelling to Advanced Visual    Communication (pp. 76–117). Springer. https://doi.org/10.1007/978-3-642-78291-6_2

  26. 1993

    1. Ertl, T., Ruder, H., Allrutz, R., Gruber, K., Günther, M., Hospach, F., Ruder, M., Subke, J., & Widmayer, K. (1993). Interactive control of biomechanical animation. The Visual Computer, 9, 459–465. https://doi.org/10.1007/BF01888720

        

Book Chapter or Edited Books

  1. Saini H, Röhrle O. Simulation Study to Investigate the Accuracy of in Vivo Motor-Unit Twitch Force Measurements. In: Tavares JMRS, Bourauel C, Geris L, Vander Slote J, editors. International Symposium on Computer Methods in Biomechanics and Biomedical Engineering. Cham: Springer International Publishing; 2023. p. 234--243. (Tavares JMRS, Bourauel C, Geris L, Vander Slote J, editors. International Symposium on Computer Methods in Biomechanics and Biomedical Engineering).
  2. Bleiler C, Röhrle O. Classification of Biomechanical Models: The Wrong Battle Between Phenomenological and Structural Approaches, the Partly Underestimated Strength of Phenomenology and Challenges for Future (Clinical) Applications. In: Solid (Bio) mechanics: Challenges of the Next Decade. Springer; 2022. p. 335--352. (Solid (Bio) mechanics: Challenges of the Next Decade).
  3. Reski R, Özdemir B, Asgharzadeh P, Birkhold A, Röhrle O. The plastid skeleton: a source of ideas in the nano range. In: Biomimetics for Architecture Learning from Nature. Birkhäuser; 2019. p. 163–6. (Biomimetics for Architecture. Learning from Nature).
  4. Röhrle O. Skeletal Muscle Modelling. Encyclopaedia for Continuum Mechanics Section Biomechanics. 2018;
  5. Asgharzadeh P, Özdemir B, Müller SJ, Röhrle O, Reski R. Analysis of Physcomitrella chloroplasts to reveal adaptation principles leading to structural stability at the nano-scale. In: Biomimetic Research for Architecture and Building Construction. Springer, Cham; 2016. p. 261--275. (Biomimetic Research for Architecture and Building Construction).
  6. Betz O, Birkhold A, Caliaro M, Eggs B, Mader A, Knippers J, et al. Adaptive stiffness and joint-free kinematics: actively actuated rod-shaped structures in plants and animals and their biomimetic potential in architecture and engineering. In: Biomimetic Research for Architecture and Building Construction. Springer, Cham; 2016. p. 135--167. (Biomimetic Research for Architecture and Building Construction).
  7. Schmitt S, Lechler A, Röhrle O. Modellierung und Simulation als Werkzeug für das Design von Mensch-Maschine-Systemen. In Berlin: Springer Vieweg; 2015. p. 178–84.
  8. Schmitt S, Haeufle D. Mechanics and thermodynamics of biological muscle--a simple model approach. In: Soft Robotics [Internet]. Springer; 2015. p. 134--144. (Soft Robotics). Available from: https://link.springer.com/chapter/10.1007/978-3-662-44506-8_12
  9. Wang Y, Gamage TPB, Nielsen PM, Röhrle O, Nash MP. Identification of tongue muscle fibre group contraction from MR images. In: Computational Biomechanics for Medicine. Springer, New York, NY; 2013. p. 185--196. (Computational Biomechanics for Medicine).
  10. Röhrle O, Sprenger M, Ramasamy E, Heidlauf T. Multiscale skeletal muscle modeling: from cellular level to a multi-segment skeletal muscle model of the upper limb. In: Computer models in biomechanics. Springer, Dordrecht; 2013. p. 103--116. (Computer models in biomechanics).
  11. Röhrle O, Köstler H, Loch M. Segmentation of skeletal muscle fibres for applications in computational skeletal muscle mechanics. In: Computational Biomechanics for Medicine. Springer, New York, NY; 2011. p. 107--117. (Computational Biomechanics for Medicine).
  12. Ehlers W, Markert B, Röhrle O, editors. Biomechanics. GAMM-Mitteilungen; 2009.
  13. Wangerin M, Schmitt S, Stapelfeldt B, Gollhofer A. Inverse Dynamics in Cycling Performance. In: Buzug T, editor. Advances in Medical Engineering [Internet]. Springer; 2007. p. 329--334. (Buzug T, editor. Advances in Medical Engineering). Available from: https://link.springer.com/chapter/10.1007/978-3-540-68764-1_55

Patents

  1. Kleiner B, Röhrle O, Hülsmann A, Röhrle A. Mobile radar-basierte Umgebungsvermessung unter Anwendung von Sensorfusion mittels Intrarotkamera und Inertialsensorik. 2015.
  2. Röhrle O. Verfahren zur Bestimmung einer Beißkraft. 2014.
  3. Smith NP, Budgett DM, Hunter PJ, Malcolm DTK, Cheng LKW, Nash MP, et al. Biophysical virtual model database and applications. 2010.
  4. Blickhan R, Günther M, Schmitt S. Vorrichtung zur Nachbildung des Bewegungsverhaltens eines natürlichen Muskels. Europäisches Patentamt; 2010. Report No.: PCT/DE 2010/000160.
  5. Blickhan R, Günther M, Schmitt S. Vorrichtung zur Nachbildung des Bewegungsverhaltens eines natürlichen Muskels. Deutsches Patent- und Markenamt; 2008. Report No.: DE 10 2008 058 604.8.

Completed PhD Thesis

  1. Altan, Ekin (2022): Data-driven modelling of neuromechanical adaptation in skeletal muscles in response to isometric exercise, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-07-6, DOI: 10.18419/opus-12097]
  2. Bleiler, Christian (2021): Continuum-mechanical modelling across scales : homogenisation methods and their application to microstructurally-based skeletal muscle modelling, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-06-9, DOI: 10.18419/opus-11959]
  3. Saini, Harnoor (2021): Modelling the functional heterogeneity of skeletal muscles : enriching continuum-mechanical models on a motor-unit level, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-06-9, DOI: 10.18419/opus-11602]
  4. Asgharzadeh, Pouyan (2020): Image-based analysis of biological network structures using machine learning and continuum mechanics, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-05-2, DOI: 10.18419/opus-11154]
  5. Mordhorst, Mylena (2020): Towards a fast and stable dynamic skeletal muscle model, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-04-5, DOI: 10.18419/opus-11159]
  6. Hessenthaler, Andreas (2020): Multilevel convergence analysis: parallel-in-time integration for fluid-structure interaction problems with applications in cardiac flow modeling, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-03-8, DOI: 10.18419/opus-11260] 
  7. Ramasamy, Ellankavi (2019): A modelling-simulation-analysis workflow for investigating socket-stump interaction, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-02-1, DOI: 10.18419/opus-10559]
  8. Sprenger, Michael (2015): A 3D continuum-mechanical model for forward-dynamics simulations of the upper limb, Dissertation, University of Stuttgart [Download PDF, ISBN 978-3-946412-01-4, DOI: 10.18419/opus-8777]
  9. Heidlauf, Thomas (2015): Chemo-electro-mechanical modelling of the neuromuscular system, Dissertation, University of Stuttgart [Download PDF,  ISBN 978-3-946412-00-7, DOI: 10.18419/opus-658]
  10. Wang, Yikun (2014): Modelling Tongue Mechanics, Dissertation, University of Auckland, New Zealand [Download PDF]
  11. Davidson, John (2009): Biophysical Modelling of Skeletal Muscle, Dissertation, University of Auckland, New Zealand [Download PDF]
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