Publications

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

International, peer-reviewed Publications

  1. 2021

    1. 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
    2. 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
    3. 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
    4. 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
    5. 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
    6. 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.
    7. Klotz, T., Gizzi, L., & Röhrle, O. (2021). Investigating the spatial resolution of EMG and MMG based on a systemic  multi-scale model. http://arxiv.org/abs/2108.05046
    8. 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
    9. 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. Applied Bionics and Biomechanics, 2021. https://doi.org/10.1155/2021/5533770
    10. 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), 201839. https://doi.org/10.1098/rsos.201839
    11. 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
    12. Walter, J. R., Günther, M., Haeufle, D. F. B., & Schmitt, S. (2021). A geometry- and muscle-based control architecture for  synthesising biological movement. Biological Cybernetics. https://doi.org/10.1007/s00422-020-00856-4
    13. 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), 1561--1571. https://doi.org/10.1007/s10439-020-02688-6
    14. 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), 064075. https://doi.org/10.1103/PhysRevApplied.15.064075

  2. 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), 1139--1158. 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., 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
    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., 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, 7, 77. https://doi.org/10.3389/frobt.2020.00077
    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), A771--A796. 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. 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), 2015--2047. https://doi.org/10.1007/s10237-020-01322-7
    14. 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. https://doi.org/10.3389/fphys.2020.00306
    15. 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
    16. 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
    17. 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

  3. 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), 410--418. https://doi.org/10.1002/ejp.1318
    4. Hammer, M., Günther, M., Haeufle, D. F. B., & Schmitt, S. (2019). Tailoring anatomical muscle paths: a sheath-like solution for muscle routing in musculoskeletal computer models. Mathematical Biosciences, 311, 68–81. https://doi.org/10.1016/j.mbs.2019.02.004
    5. 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
    6. 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
    7. Schmitt, S., Günther, M., & Häufle, D. F. (2019). The dynamics of the skeletal muscle: A systems biophysics perspective on muscle modeling with the focus on Hill-type muscle models. GAMM-Mitteilungen, e201900013. https://doi.org/10.1002/gamm.201900013
    8. 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), 20190719. https://doi.org/10.1098/rspb.2019.0719

  4. 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), 12. https://doi.org/10.1186/s40850-018-0037-2
    5. Günther, M., Häufle, D., & Schmitt, S. (2018). The basic mechanical structure of the skeletal muscle machinery: One model for linking microscopic and macroscopic scales.
    6. Günther, M., Haeufle, D. F., & 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.
    7. 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.
    8. 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), e2155. https://doi.org/10.1002/nla.2155
    9. Hoekstra, A. G., van de Vosse, F., & Röhrle, O. (2018). The virtual physiological human conference 2016. Journal of Computational Science, 24, 65--67.
    10. 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.
    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), 58--68.
    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), 453--460.
    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), 1398--1405.
    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, 2018, 20. 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), e2965.
    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. 2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), 1--6. 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), 11165.

  5. 2017

    1. Bayer, A., Schmitt, S., Günther, M., & Haeufle, D. (2017). The influence of biophysical muscle properties on simulating fast human arm movements. Computer Methods in Biomechanics and Biomedical Engineering, 20(8), 803--821.
    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(1), 13266. 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), e1005773.
    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), e2848.
    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), e2845.
    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), 109.
    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.
    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), 483--487.
    10. 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.
    11. 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
    12. 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), 743--762. https://doi.org/10.1007/s10237-016-0850-x
    13. 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.

  6. 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), 69--70.
    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), e0164583.
    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.
    4. 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), 012617.
    5. 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), 1423--1437.
    6. 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), 923–933. https://doi.org/10.1080/10255842.2015.1076804
    7. 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.
    8. 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.

  7. 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), 20140076.
    5. Rockenfeller, R., Günther, M., Schmitt, S., & Götz, T. (2015). Comparative sensitivity analysis of muscle activation dynamics. Computational and Mathematical Methods in Medicine, 2015.
    6. Rupp, T., 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), 1081--1105.

  8. 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), 2026–2034. https://doi.org/10.1016/j.ridd.2014.04.032
    2. Haeufle, D., Günther, M., Bayer, A., & Schmitt, S. (2014). Hill-type muscle model with serial damping and eccentric force--velocity relation. Journal of Biomechanics, 47(6), 1531--1536.
    3. Haeufle, D., Günther, M., Wunner, G., & Schmitt, S. (2014). Quantifying control effort of biological and technical movements: an information-entropy-based approach. Physical Review E, 89(1), 012716.
    4. 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.
    5. 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.
    6. Ramasamy, E., Dorow, B., Schneider, U., & Roehrle, O. (2014). Simulation-assisted prosthetic design. BIOMEDICAL ENGINEERING-BIOMEDIZINISCHE TECHNIK, 59, S1021--S1021.

  9. 2013

    1. 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.
    2. 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.
    3. 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), 453--466.
    4. Schmitt, S., Günther, M., Rupp, T., Bayer, A., & Häufle, D. (2013). Theoretical Hill-type muscle and stability: numerical model and application. Computational and Mathematical Methods in Medicine, 2013, 570878.
    5. 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), 383--399.

  10. 2012

    1. Günther, M., Röhrle, O., Haeufle, D. F., & Schmitt, S. (2012). Spreading out muscle mass within a Hill-type model: a computer simulation study. Computational and Mathematical Methods in Medicine, 2012.
    2. 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
    3. Haeufle, D., Günther, M., Blickhan, R., & Schmitt, S. (2012). Can quick release experiments reveal the muscle structure? A bionic approach. Journal of Bionic Engineering, 9(2), 211--223.
    4. Häufle, 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), 276–274.
    5. Mörl, F., Siebert, T., Schmitt, S., Blickhan, R., & Guenther, M. (2012). Electro-mechanical delay in Hill-type muscle models. Journal of Mechanics in Medicine and Biology, 12(05), 1250085.
    6. 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.
    7. Schmitt, S., Haeufle, D., Blickhan, R., & Günther, M. (2012). Nature as an engineer: one simple concept of a bio-inspired functional artificial muscle. Bioinspiration & Biomimetics, 7(3), 036022.

  11. 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), 32--47.
    2. Häufle, D. F. B., Günther, M., Blickhan, R., & Schmitt, S. (2011). Proof of concept of an artificial muscle: theoretical model, numerical model and hardware experiment. Proceedings of the 12th IEEE International Conference on Rehabilitation Robotics, 8 pages.
    3. 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.
    4. Schmitt, S., & Günther, M. (2011). Human leg impact: energy dissipation of wobbling masses. Archive of Applied Mechanics, 81(7), 887--897. https://doi.org/10.1007/s00419-010-0458-z

  12. 2010

    1. Günther, M., & Schmitt, S. (2010). A macroscopic ansatz to deduce the Hill relation. Journal of Theoretical Biology, 263(4), 407--418.
    2. 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.
    3. Röhrle, O. (2010). Simulating the electro-mechanical behavior of skeletal muscles. Computing in Science & Engineering, 12(6), 48--58.
    4. 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), 295--315.

  13. 2009

    1. 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), 461--466. https://doi.org/10.1055/s-0028-1112141
    2. 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), 703--710.
    3. 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), 1646--1653.
    4. 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

  14. 2008

    1. 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), 2882--2904.
    2. 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), 1353--1375.

  15. 2007

    1. 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), 48.
    2. Röhrle, O., & Pullan, A. J. (2007). Three-dimensional finite element modelling of muscle forces during mastication. Journal of Biomechanics, 40(15), 3363--3372.
    3. 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), 279--283.
    4. 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.

  16. 2006

    1. 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), 523--542.
    2. 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), 139--152.
    3. 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), 120--138.

        

Book Chapter or Edited Books

  1. 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).
  2. Röhrle O. Skeletal Muscle Modelling. Encyclopaedia for Continuum Mechanics Section Biomechanics. 2018;
  3. 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).
  4. 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).
  5. Schmitt S, Lechler A, Röhrle O. Modellierung und Simulation als Werkzeug für das Design von Mensch-Maschine-Systemen: Modellierung und Simulation als Werkzeug für das Design von Mensch-Maschine-Systemen. In Berlin: Springer Vieweg; 2015. p. 178–84.
  6. Schmitt S, Haeufle D. Mechanics and thermodynamics of biological muscle--a simple model approach. In: Soft Robotics. Springer; 2015. p. 134--144. (Soft Robotics).
  7. 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).
  8. 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).
  9. 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).
  10. Ehlers W, Markert B, Röhrle O, editors. Biomechanics. GAMM-Mitteilungen; 2009.
  11. Wangerin M, Schmitt S, Stapelfeldt B, Gollhofer A. Inverse Dynamics in Cycling Performance. In: Buzug T, editor. Advances in Medical Engineering. Springer; 2007. p. 329--334. (Buzug T, editor. Advances in Medical Engineering).

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 LK-W, 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. 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]
  2. 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]
  3. 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] 
  4. 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]
  5. 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]
  6. 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]
  7. Wang, Yikun (2014): Modelling Tongue Mechanics, Dissertation, University of Auckland, New Zealand [Download PDF]
  8. Davidson, John (2009): Biophysical Modelling of Skeletal Muscle, Dissertation, University of Auckland, New Zealand [Download PDF]
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