This image shows Syn Schmitt

Syn Schmitt

Prof. Dr.

Director
Institute for Modelling and Simulation of Biomechanical Systems
Professor for Computational Biophysics and Biorobotics

Contact

+49 711 685 60484
 +49 711 685 50484

Nobelstraße 15
70569 Stuttgart
Deutschland
Room: 00.064

Office Hours

  • Tuesday: 10:00 am - 11:00 am

Publications:

  1. 2025

    1. A. Shagan Shomron et al., “A robotic and virtual testing platform highlighting the promise of soft wearable actuators for wrist tremor suppression,” Device, p. 100719, 2025, doi: 10.1016/j.device.2025.100719.
    2. N. Badie, F. Al-Hafez, P. Schumacher, D. F. Haeufle, J. Peters, and S. Schmitt, “Bioinspired morphology and task curricula for learning locomotion in bipedal muscle-actuated systems,” Communications Engineering, vol. 4, Art. no. 1, 2025, doi: 10.1038/s44172-025-00443-0.
    3. Z. Hu, G. Zhang, Z. Yin, D. Haeufle, S. Schmitt, and A. Bulling, “HaHeAE: Learning Generalisable Joint Representations of Human Hand and Head Movements in Extended Reality,” IEEE Transactions on Visualization and Computer Graphics, 2025.
    4. N. S. Badie and S. Schmitt, “Code and Data for: “Bioinspired Morphology and Task Curricula for Learning Locomotion in Bipedal Muscle-Actuated Systems.”” 2025. doi: 10.18419/darus-5030.
    5. P. Schumacher et al., “Emergence of natural and robust bipedal walking by learning from biologically plausible objectives,” iScience, vol. 28, Art. no. 4, 2025, doi: 10.1016/j.isci.2025.112203.

  2. 2024

    1. N. Trube, P. Lerge, L. Nölle, J. Mönnich, T. Lich, and S. Schmitt, “Development and Plausibility Assessment of an Active Human Body Model in Numerical Cyclist to Vehicle Collision Simulations based on Real-life Accident Data,” in Proceedings of the International IRCOBI Conference, Stockholm, Sweden: IRCOBI Council, Sep. 2024, pp. 519–551. [Online]. Available: https://www.ircobi.org/wordpress/downloads/irc24/pdf-files/2479.pdf
    2. L. V. Nölle, I. Wochner, M. Hammer, and S. Schmitt, “Using muscle-tendon load limits to assess unphysiological musculoskeletal model deformation and Hill-type muscle parameter choice,” PloS one, vol. 19, Art. no. 11, 2024, doi: 10.1371/journal.pone.0302949.
    3. Z. Hu, Z. Yin, D. Haeufle, S. Schmitt, and A. Bulling, “HOIMotion: Forecasting Human Motion During Human-Object Interactions Using Egocentric 3D Object Bounding Boxes,” IEEE Transactions on Visualization and Computer Graphics (TVCG), pp. 1–11, 2024, [Online]. Available: https://arxiv.org/abs/2407.02633
    4. N. Badie and S. Schmitt, “Enhancing stance robustness and jump height in bipedal muscle-actuated systems: A bioinspired morphological development approach,” Bioinspiration & Biomimetics, 2024, doi: 10.1088/1748-3190/ad3602.
    5. I. Wochner et al., “ATARO: A Muscle-Driven Biorobotic Arm to Investigate Healthy and Impaired Motor Control,” Sep. 2024, pp. 358–363. doi: 10.1109/BioRob60516.2024.10719710.
    6. T. Nadler, S. Wolfen, D. F. B. Häufle, and S. Schmitt, “Technical specifications and details of the muscle-driven biorobotic arm ATARO,” 2024, doi: 10.18419/DARUS-3813.
    7. H. Yan, Z. Hu, S. Schmitt, and A. Bulling, “GazeMoDiff: Gaze-guided Diffusion Model for Stochastic Human Motion Prediction,” in Proceedings of the 2024 Pacific Conference on Computer Graphics and Applications, 2024.
    8. Z. Hu, J. Xu, S. Schmitt, and A. Bulling, “Pose2Gaze: Eye-body Coordination during Daily Activities for Gaze Prediction from Full-body Poses,” IEEE Transactions on Visualization and Computer Graphics (TVCG), 2024.
    9. S. Gubi-Kelm, L. May, S. Schmitt, C. Bitzigeio, R. Rick, and K. Püschel, “Interdisziplinäre Betrachtung eines Mordes, den es nicht gab - der Fall Manfred G,” Archiv für Kriminologie, vol. 253, pp. 30–75, Feb. 2024, [Online]. Available: https://www.researchgate.net/publication/378100009_Interdisziplinare_Betrachtung_eines_Mordes_den_es_nicht_gab_-_der_Fall_Manfred_G
    10. M. Hammer et al., “A new method to design energy-conserving surrogate models for the coupled, nonlinear responses of intervertebral discs,” Biomechanics and Modeling in Mechanobiology, pp. 1–24, 2024, doi: 10.1007/s10237-023-01804-4.
    11. Z. Hu, S. Schmitt, D. Haeufle, and A. Bulling, “GazeMotion: Gaze-guided Human Motion Forecasting,” in Proceedings of the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024.

  3. 2023

    1. T. Lich, J. Mönnich, M. Voss, P. Lerge, L. V. Nölle, and S. Schmitt, “Applying AI Methods On Video Documented Car-VRU Front Crashes to Determine Generalized Vulnerable Road User Behaviors,” in Proceedings of the 27th International Technical Conference on the Enhanced Safety of Vehicles (ESV), Yokohama, Japan, 2023. [Online]. Available: https://www-esv.nhtsa.dot.gov/Proceedings/27/27ESV-000210.pdf
    2. L. Meszaros-Beller, M. Hammer, J. M. Riede, P. Pivonka, J. P. Little, and S. Schmitt, “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, pp. 1–26, 2023, doi: 10.1007/s10237-022-01673-3.
    3. E. Bunz, D. Haeufle, C. Remy, and S. Schmitt, “Bioinspired preactivation reflex increases robustness of walking on rough terrain,” Scientific Reports, p. 13:13219, 2023, doi: 10.1038/ s41598-023-39364-3.
    4. F. Izzi, A. Mo, S. Schmitt, A. Badri-Spröwitz, and D. F. B. Haeufle, “Muscle prestimulation tunes velocity preflex in simulated perturbed hopping,” Scientific Reports, vol. 13, Art. no. 1, 2023, doi: 10.1038/s41598-023-31179-6.
    5. I. Wochner, P. Schumacher, G. Martius, D. Büchler, S. Schmitt, and D. Haeufle, “Learning with Muscles: Benefits for Data-Efficiency and Robustness in Anthropomorphic Tasks,” in 6th Annual Conference on Robot Learning, 2023. [Online]. Available: https://openreview.net/forum?id=Xo3eOibXCQ8
    6. P. Schumacher et al., “Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models.” arXiv, 2023. doi: 10.48550/arXiv.2309.02976.
    7. L. V. Nölle, E. H. Alfaro, O. V. Martynenko, and S. Schmitt, “An investigation of tendon strains in jersey finger injury load cases using a finite element neuromuscular human body model,” Frontiers in Bioengineering and Biotechnology, vol. 11, p. 1293705, 2023, doi: 10.3389/fbioe.2023.1293705.
    8. L. Meszaros-Beller, M. Hammer, S. Schmitt, and P. Pivonka, “Effect of neglecting passive spinal structures: a quantitative investigation using the forward-dynamics and inverse-dynamics musculoskeletal approach,” Frontiers in Physiology, vol. 14, p. 1135531, 2023, doi: 10.3389/fphys.2023.1135531.
    9. K. B. Christensen, M. Günther, S. Schmitt, and T. Siebert, “Muscle wobbling mass dynamics: eigenfrequency dependencies on activity, impact strength, and ground material,” Scientific Reports, vol. 13, p. 19575 (12pp), 2023, doi: 10.1038/s41598-023-45821-w.
    10. P. F. Chacon, M. Hammer, I. Wochner, J. R. Walter, and S. Schmitt, “A physiologically enhanced muscle spindle model: using a Hill-type model for extrafusal fibers as template for intrafusal fibers,” Computer Methods in Biomechanics and Biomedical Engineering, pp. 1–20, 2023, doi: 10.1080/10255842.2023.2293652.
    11. O. V. Martynenko et al., “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, pp. 1–30, 2023, doi: 10.1007/s10237-023-01748-9.
    12. P. Schumacher, D. F. B. Haeufle, D. Büchler, S. Schmitt, and G. Martius, “DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems,” in Proceedings of the Eleventh InternationalConference on Learning Representations (ICLR), 2023. [Online]. Available: https://iclr.cc/virtual/2023/poster/11618

  4. 2022

    1. I. Wochner, L. V. Nölle, O. V. Martynenko, and S. Schmitt, “‘Falling heads’: investigating reflexive responses to head--neck perturbations,” BioMedical Engineering OnLine, vol. 21, Art. no. 1, 2022, doi: doi: 10.1186/s12938-022-00994-9.
    2. S. Schmitt, “demoa-base: a biophysics simulator for muscle-driven motion,” 2022, doi: 10.18419/darus-2550.
    3. J. R. Walter, I. Wochner, M. Jacob, K. Stollenmaier, P. Lerge, and S. Schmitt, “allmin: A Reduced Human All-Body Model,” 2022, doi: 10.18419/darus-2982.
    4. P. Schumacher, D. Häufle, D. Büchler, S. Schmitt, and G. Martius, “DEP-RL: Embodied Exploration for Reinforcement Learning in Overactuated and Musculoskeletal Systems.” arXiv, 2022. doi: 10.48550/ARXIV.2206.00484.
    5. M. Waldhof, I. Wochner, K. Stollenmaier, N. Parspour, and S. Schmitt, “Design and Scaling of Exoskeleton Power Units Considering Load Cycles of Humans,” Robotics, vol. 11, Art. no. 5, 2022, doi: 10.3390/robotics11050107.
    6. I. Wochner and S. Schmitt, “arm26: A Human Arm Model,” 2022, doi: 10.18419/darus-2871.
    7. M. Hammer, J. M. Riede, L. Meszaros-Beller, and S. Schmitt, “gspine: A Human Spine Model Built Using Literature Data,” 2022, doi: 10.18419/darus-2814.
    8. L. V. Nölle, A. Mishra, O. V. Martynenko, and S. Schmitt, “Evaluation of muscle strain injury severity in active human body models,” Journal of the Mechanical Behavior of Biomedical Materials, p. 105463, 2022, doi: doi.org/10.1016/j.jmbbm.2022.105463.

  5. 2021

    1. K. Ghazi-Zahedi, J. Rieffel, S. Schmitt, and H. Hauser, “Editorial: Recent Trends in Morphological Computation,” Frontiers in Robotics and AI, vol. 8, p. 159, 2021, doi: 10.3389/frobt.2021.708206.
    2. J. Walter, P. Lerge, and S. Schmitt, “Human-centred design: a comparison of ingress motion for two car concepts using a musculoskeletal, digital human body model.” 2021. doi: 10.18419/opus-11478.
    3. J. Walter, M. Günther, D. Haeufle, and S. Schmitt, “Correction to: A geometry- and muscle-based control architecture for synthesising biological movement,” Biological Cybernetics, Art. no. 115, 2021, doi: 10.1007/s00422-021-00869-7.
    4. L. Gizzi et al., “Variations in Muscle Activity and Exerted Torque During Temporary Blood Flow Restriction in Healthy Individuals,” Frontiers in Bioengineering and Biotechnology, vol. 9, p. 100, 2021, doi: 10.3389/fbioe.2021.557761.
    5. B. Haasdonk, T. Wenzel, G. Santin, and S. Schmitt, “Biomechanical Surrogate Modelling Using Stabilized Vectorial Greedy Kernel Methods,” in Numerical Mathematics and Advanced Applications ENUMATH 2019, F. J. Vermolen and C. Vuik, Eds., Cham: Springer International Publishing, 2021, pp. 499–508. doi: 10.1007/978-3-030-55874-1_49.
    6. O. V. Martynenko et al., “Comparison of the Head-Neck Kinematics of Different Active Human Body Models with Experimental Data,” in Proceedings of IRCOBI Conference, 2021, pp. 105–121. [Online]. Available: http://www.ircobi.org/wordpress/downloads/irc21/pdf-files/2121.pdf
    7. T. Banik, L. V. Nölle, S. Schmitt, and O. V. Martynenko, “Representation of the Elderly Population with Active Human Body Models,” in Proceedings of IRCOBI Conference, 2021, pp. 534–536. [Online]. Available: http://www.ircobi.org/wordpress/downloads/irc21/pdf-files/2158.pdf
    8. K. B. Christensen, M. Günther, S. Schmitt, and T. Siebert, “Cross-bridge mechanics estimated from skeletal muscles’ work-loop responses to impacts in legged locomotion,” Scientific Reports, vol. 11, p. 23638 (12pp), 2021, doi: 10.1038/s41598-021-02819-6.
    9. J. Walter, M. Günther, D. F. B. Haeufle, and S. Schmitt, “A geometry- and muscle-based control architecture for synthesising biological movement,” Biological Cybernetics, vol. 115, Art. no. 1, 2021, doi: 10.1007/s00422-020-00856-4.
    10. M. Günther, R. Rockenfeller, T. Weihmann, D. F. B. Haeufle, T. Götz, and S. Schmitt, “Rules of nature’s Formula Run: Muscle mechanics during late stance is the key to explaining maximum running speed,” Journal of Theoretical Biology, vol. 523, p. 110714, 2021, doi: 10.1016/j.jtbi.2021.110714.
    11. R. Rockenfeller, M. Hammer, J. M. Riede, S. Schmitt, and K. Lawonn, “Intuitive assessment of modeled lumbar spinal motion by clustering and visualization of finite helical axes,” Computers in Biology and Medicine, vol. 135, p. 104528, 2021, doi: 10.1016/j.compbiomed.2021.104528.
    12. J. M. Riede, C. Holm, S. Schmitt, and D. F. B. Haeufle, “The control effort to steer self-propelled microswimmers depends on their morphology: comparing symmetric spherical versus asymmetric <i>L</i>-shaped particles,” Royal Society Open Science, vol. 8, Art. no. 9, 2021, doi: 10.1098/rsos.201839.

  6. 2020

    1. L. V. Nölle, S. Schmitt, and O. V. Martynenko, “Defining Injury Criteria for the Muscle-Tendon-Unit,” in Proceedings of the International IRCOBI Conference, Munich, Germany: IRCOBI Council, 2020, pp. 811–813. [Online]. Available: http://www.ircobi.org/wordpress/downloads/irc20/pdf-files/89.pdf
    2. O. V. Martynenko, L. V. Nölle, and S. Schmitt, “Integration of the Open-Source Extended Hill-type Muscle Material into THUMSv5,” in Proceedings of the International IRCOBI Conference, Munich, Germany: IRCOBI Council, 2020, pp. 205–206. [Online]. Available: http://www.ircobi.org/wordpress/downloads/irc20/pdf-files/25.pdf
    3. D. F. B. Haeufle et al., “Energy Expenditure of Dynamic Submaximal Human Plantarflexion Movements: Model Prediction and Validation by in-vivo Magnetic Resonance Spectroscopy,” Frontiers in Bioengineering and Biotechnology, vol. 8, Jun. 2020, doi: 10.3389/fbioe.2020.00622.
    4. D. F. B. Haeufle, K. Stollenmaier, I. Heinrich, S. Schmitt, and K. Ghazi-Zahedi, “Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy,” Frontiers in Robotics and AI, vol. 7, 2020, doi: 10.3389/frobt.2020.511265.
    5. R. Rockenfeller et al., “Exhaustion of skeletal muscle fibers within seconds: incorporating phosphate kinetics into a Hill-type model,” Frontiers in Physiology, vol. 11, p. 306 (25pp), 2020, doi: 10.3389/fphys.2020.00306.
    6. F. Mörl, M. Günther, J. M. Riede, M. Hammer, and S. Schmitt, “Loads distributed in vivo among vertebrae, muscles, spinal ligaments, and intervertebral discs in a passively flexed lumbar spine,” Biomechanics and Modeling in Mechanobiology, vol. 19, Art. no. 6, Dec. 2020, doi: 10.1007/s10237-020-01322-7.
    7. D. F. Haeufle, I. Wochner, D. Holzmüller, D. Driess, M. Günther, and S. Schmitt, “Muscles reduce neuronal information load: quantification of control effort in biological vs robotic pointing and walking,” Frontiers in Robotics and AI, vol. 7, p. 77 (13pp), 2020, doi: https://doi.org/10.3389/frobt.2020.00077.
    8. S. Brändle, S. Schmitt, and M. A. Müller, “A systems-theoretic analysis of low-level human motor control: application to a single-joint arm model.,” J Math Biol, vol. 80, Art. no. 4, 2020, doi: 10.1007/s00285-019-01455-z.
    9. M. Günther, D. F. B. Haeufle, and S. Schmitt, “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, vol. 488, p. 110143, Mar. 2020, doi: 10.1016/j.jtbi.2019.110143.
    10. P. Lerge, S. Schmitt, and O. V. Martynenko, “Simulation of Pedestrian Kinematics before Impact with a Vehicle using an Active Pedestrian Human Body Model,” in Proceedings of the International IRCOBI Conference, Munich, Germany: IRCOBI Council, Sep. 2020, pp. 210–212. [Online]. Available: http://www.ircobi.org/wordpress/downloads/irc20/pdf-files/27.pdf
    11. I. Wochner, D. Driess, H. Zimmermann, D. F. Haeufle, M. Toussaint, and S. Schmitt, “Optimality principles in human point-to-manifold reaching accounting for muscle dynamics,” Frontiers in Computational Neuroscience, vol. 14, p. 38, 2020, doi: https://doi.org/10.3389/fncom.2020.00038.

  7. 2019

    1. S. Schmitt, M. Günther, and D. F. B. Haeufle, “The dynamics of the skeletal muscle: a systems biophysics perspective on muscle modeling with the focus on Hill-type muscle models,” GAMM--Mitteilungen, vol. 58, p. e201900013, 2019, doi: 10.1002/gamm.201900013.
    2. D. Driess, S. Schmitt, and M. Toussaint, “Active Inverse Model Learning with Error and Reachable Set Estimates,” in Proc. of the IEEE Int. Conf. on Intelligent Robotsand Systems (IROS), 2019. doi: 10.1109/IROS40897.2019.8967858.
    3. M. Hammer, M. Günther, D. F. B. Haeufle, and S. Schmitt, “Tailoring anatomical muscle paths: a sheath-like solution for muscle routing in musculo-skeletal computer models,” Mathematical Biosciences, vol. 311, pp. 68–81, 2019, doi: 10.1016/j.mbs.2019.02.004.

  8. 2018

    1. D. F. Haeufle, B. Schmortte, H. Geyer, R. Müller, and S. Schmitt, “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, vol. 12, p. 80, 2018, [Online]. Available: https://www.frontiersin.org/articles/10.3389/fncom.2018.00080/full
    2. S. Wolfen, J. Walter, M. Günther, D. F. B. Haeufle, and S. Schmitt, “Bioinspired pneumatic muscle spring units mimicking the human motion apparatus: benefits for passive motion range and joint stiffness variation in antagonistic setups,” in 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP), Stuttgart, 2018, p. 6pp. doi: 10.1109/M2VIP.2018.8600913.
    3. D. Suissa, M. Günther, A. Shapiro, I. Melzer, and S. Schmitt, “On laterally perturbed human stance: experiment, model, and control,” Applied Bionics and Biomechanics, p. 4767624 (20pp), 2018, doi: 10.1155/2018/4767624.
    4. M. Günther, D. F. B. Haeufle, and S. Schmitt, “The basic mechanical structure of the skeletal muscle machinery: One model for linking microscopic and macroscopic scales,” Journal of Theoretical Biology, vol. 456, pp. 137–167, 2018, doi: 10.1016/j.jtbi.2018.07.023.
    5. D. Driess et al., “Learning to Control Redundant Musculoskeletal Systems with Neural Networks and SQP: Exploiting Muscle Properties,” in Proc. of the International Conference on Robotics and Automation, 2018. doi: 10.1109/ICRA.2018.8463160.

  9. 2017

    1. U. Lindemann, M. Schwenk, S. Schmitt, M. Weyrich, W. Schlicht, and C. Becker, “Effect of uphill and downhill walking on walking performance in geriatric patients using a wheeled walker,” Zeitschrift für Gerontologie und Geriatrie, vol. 50, Art. no. 6, 2017, doi: 10.1007/s00391-016-1156-4.
    2. O. Röhrle, M. Sprenger, and S. Schmitt, “A two-muscle, continuum-mechanical forward simulation of the upper limb,” Biomechanics and Modeling in Mechanobiology, vol. 16, Art. no. 3, Jun. 2017, doi: 10.1007/s10237-016-0850-x.
    3. A. Bayer, S. Schmitt, M. Günther, and D. F. B. Haeufle, “The influence of biophysical muscle properties on simulating fast human arm movements,” Computer Methods in Biomechanics and Biomedical Engineering, vol. 20, Art. no. 8, 2017, doi: 10.1080/10255842.2017.1293663.
    4. K. B. Christensen, M. Günther, S. Schmitt, and T. Siebert, “Strain in shock-loaded skeletal muscle and the time scale of muscular wobbling mass dynamics,” Scientific Reports, vol. 7, p. 13266 (11pp), 2017, doi: 10.1038/s41598-017-13630-7.
    5. N. Brown et al., “Weekly Time Course of Neuro-Muscular Adaptation to Intensive Strength Training,” Frontiers in Physiology, vol. 8, p. 329, 2017, doi: 10.3389/fphys.2017.00329.
    6. C. Kleinbach, O. Martynenko, J. Promies, D. F. Haeufle, J. Fehr, and S. Schmitt, “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, vol. 16, Art. no. 1, 2017, doi: 10.1186/s12938-017-0399-7.
    7. O. Martynenko, C. Kleinbach, M. Hammer, D. F. B. Haeufle, C. Mayer, and S. Schmitt, “Advanced Hill-type Muscle model as User Defined Material in LS-DYNA with Routing Capability for Application in Active Human Body Models,” in Proceedings of the International IRCOBI Conference, Antwerp, Belgium: IRCOBI Council, Sep. 2017, pp. 679–680. [Online]. Available: http://www.ircobi.org/wordpress/downloads/irc17/pdf-files/91.pdf
    8. R. Rockenfeller, M. Günther, S. Schmitt, and T. Götz, “Corrigendum to ``Comparative Sensitivity Analysis of Muscle Activation Dynamics″,” Computational and Mathematical Methods in Medicine, vol. 2017, p. 2, 2017, doi: 10.1155/2017/6752731.

  10. 2016

    1. K. Ghazi-Zahedi, D. F. Haeufle, G. Montúfar, S. Schmitt, and N. Ay, “Evaluating morphological computation in muscle and dc-motor driven models of hopping movements,” Frontiers in Robotics and AI, vol. 3, p. 42, 2016, doi: 10.3389/frobt.2016.00042/full.
    2. S. Hochstein et al., “Assessment of physical activity of the human body considering the thermodynamic system,” Computer Methods in Biomechanics and Biomedical Engineering, vol. 19, Art. no. 9, 2016, doi: 10.1080/10255842.2015.1076804.
    3. D. F. Haeufle, T. Bäuerle, J. Steiner, L. Bremicker, S. Schmitt, and C. Bechinger, “External control strategies for self-propelled particles: Optimizing navigational efficiency in the presence of limited resources,” Physical Review E, vol. 94, Art. no. 1, 2016, doi: 10.1103/PhysRevE.94.012617.

  11. 2015

    1. S. Schmitt, A. Lechler, and O. Röhrle, “Modellierung und Simulation als Werkzeug für das Design von Mensch-Maschine-Systemen,” Berlin: Springer Vieweg, 2015, pp. 178–184.
    2. T. K. Rupp, W. Ehlers, N. Karajan, M. Günther, and S. Schmitt, “A forward dynamics simulation of human lumbar spine flexion predicting the load sharing of intervertebral discs, ligaments, and muscles,” Biomechanics and Modeling in Mechanobiology, vol. 14, Art. no. 5, 2015, doi: 10.1007/s10237-015-0656-2.
    3. R. Rockenfeller, M. Günther, S. Schmitt, and T. Götz, “Comparative sensitivity analysis of muscle activation dynamics,” Computational and Mathematical Methods in Medicine, p. 585409 (16pp), 2015, doi: 10.1155/2015/585409.
    4. S. Schmitt and D. Haeufle, “Mechanics and thermodynamics of biological muscle--a simple model approach,” in Soft Robotics, Springer, 2015, pp. 134–144. doi: 10.1007/978-3-662-44506-8_12.

  12. 2014

    1. S. David, S. Schmitt, J. Utz, A. Hub, and W. Schlicht, “Navigation within buildings: Novel movement detection algorithms supporting people with visual impairments,” Research in Developmental Disabilities, vol. 35, Art. no. 9, 2014, doi: https://doi.org/10.1016/j.ridd.2014.04.032.
    2. D. F. B. Haeufle, M. Günther, G. Wunner, and S. Schmitt, “Quantifying control effort of biological and technical movements: An information-entropy-based approach,” Physical Review E, vol. 89, p. 12716, 2014, doi: 10.1103/PhysRevE.89.012716.
    3. D. F. B. Haeufle, M. Günther, A. Bayer, and S. Schmitt, “Hill-type muscle model with serial damping and eccentric force-velocity relation,” Journal of Biomechanics, vol. 47, Art. no. 6, 2014, doi: 10.1016/j.jbiomech.2014.02.009.

  13. 2013

    1. N. Karajan, O. Röhrle, W. Ehlers, and S. Schmitt, “Linking continuous and discrete intervertebral disc models through homogenisation,” Biomechanics and modeling in mechanobiology, vol. 12, Art. no. 3, 2013.
    2. S. Schmitt, M. Günther, T. K. Rupp, A. Bayer, and D. F. B. Haeufle, “Theoretical Hill-type muscle and stability: numerical model and application,” Computational and Mathematical Methods in Medicine, p. 570878 (7pp), 2013, doi: 10.1155/2013/570878.

  14. 2012

    1. D. F. B. Haeufle, M. Günther, R. Blickhan, and S. Schmitt, “Proof of concept: model based bionic muscle with hyperbolic force-velocity relation,” Applied Bionics and Biomechanics, vol. 9, Art. no. 3, 2012, doi: 10.3233/ABB-2011-0052.
    2. F. Mörl, T. Siebert, S. Schmitt, R. Blickhan, and M. Günther, “Electro-mechanical delay in Hill-type muscle models,” Journal of Mechanics in Medicine and Biology, vol. 12, Art. no. 5, 2012, doi: 10.1142/S0219519412500856.
    3. M. Günther, D. F. B. Haeufle, O. Röhrle, and S. Schmitt, “Spreading out muscle mass within a Hill-type model: A computer simulation study,” Computational and Mathematical Methods in Medicine, p. 848630 (13pp), 2012, doi: 10.1155/2012/848630.
    4. D. F. B. Haeufle, M. Günther, R. Blickhan, and S. Schmitt, “Can quick release experiments reveal the muscle structure? A bionic approach,” Journal of Bionic Engineering, vol. 9, Art. no. 2, 2012, doi: 10.1016/S1672-6529(11)60115-7.
    5. S. Schmitt, D. F. B. Haeufle, R. Blickhan, and M. Günther, “Nature as an engineer: one simple concept of bio-inspired functional artificial muscle,” Bioinspiration & Biomimetics, vol. 7, Art. no. 3, 2012, doi: 10.1088/1748-3182/7/3/036022.
    6. D. F. B. Haeufle, M. D. Taylor, S. Schmitt, and H. Geyer, “A clutched parallel elastic actuator concept: Towards energy efficient powered legs in prosthetics and robotics,” in 2012 4th IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Jun. 2012, pp. 1614–1619. doi: 10.1109/BioRob.2012.6290722.

  15. 2011

    1. T. Rupp and S. Schmitt, “Inverse dynamics of the lower extremities: novel approach considering upper and lower ankle joint axis,” Journal of Mechanics in Medicine and Biology, p. 13 pages, 2011.
    2. S. Schmitt and M. Günther, “Human leg impact: energy dissipation of wobbling masses,” Archive of Applied Mechanics, vol. 81, Art. no. 7, 2011, doi: 10.1007/s00419-010-0458-z.
    3. D. F. B. Haeufle, M. Günther, R. Blickhan, and S. Schmitt, “Proof of concept of an artificial muscle: theoretical model, numerical model and hardware experiment.” pp. 1–6, 2011. doi: 10.1109/ICORR.2011.5975336.

  16. 2010

    1. D. F. B. Häufle, M. Günther, R. Blickhan, and S. Schmitt, “Proof of concept: model based bionic muscle with hyperbolic force-velocity relation,” in Proceedings of the first International Conference of Applied Biomechanics and Bionics, 2010, p. 7 pages.
    2. R. Blickhan, M. Günther, and S. Schmitt, “Vorrichtung zur Nachbildung des Bewegungsverhaltens eines natürlichen Muskels,” Europäisches Patentamt, PCT/DE 2010/000160, 2010.
    3. S. Schmitt, M. Melnyk, W. Alt, and A. Gollhofer, “Novel approach for a precise determination of short-time intervals in ankle sprain experiments.,” Journal of Biomechanics, vol. 42, pp. 2823–2825, 2010, doi: 10.1016/j.jbiomech.2009.08.015.
    4. M. Günther and S. Schmitt, “A macroscopic ansatz to deduce the Hill relation,” Journal of Theoretical Biology, vol. 263, Art. no. 4, 2010, doi: 10.1016/j.jtbi.2009.12.027.

 

Since 06/19 Adjunct Professor of the School of Chemistry Physics and Mechanical Engineering at Queensland University of Technology Brisbane, Australia
Since 04/19 Founding Director (jointly with Prof. O. Röhrle) of the Institute for Modelling and Simulation of Biomechanical Systems, Faculty 2: Civil and Environmental Engineering, University of Stuttgart, Germany.
Since 09/18 Faculty Member of the International Max Planck Research School for Intelligent Systems (IMPRS-IS), Stuttgart and Tübingen
Since 09/18 W3-Professor for Computational Biophysics and Biorobotics in Faculty 2: Civil and Environmental Engineering and Stuttgart Center for Simulation Science (SimTech) at the University of Stuttgart, Germany.
Since 02/16 Fellow of the Stuttgart Center for Simulation Science (SC SimTech), Stuttgart, Germany.
09/12-09/18 Assistant Professor (Juniorprofessor) for "Modelling and Simulation in Human Movement" at the Institute of Sports and Movement Sciences (inspo) of the University of Stuttgart, Germany.
07/07-09/12 Research Scientist at the Institute of Sports and Movement Science (inspo) of the University of Stuttgart, Germany
12/06
PhD in Theoretical Physics (Biophysics), University of Tübingen, Germany
(Prof. H. Ruder)
01/04-06/07
 Doctoral research scientist in the Biomechanics Group at the Department of Theoretical Astrophysics of University of Tübingen, Department of Sports and Rehabilitation Medicine of the University Clinic Freiburg and Institute for Sports and Sports Science of the University of Freiburg, Germany.
 
12/03
 State examination (1. Staatsexamen) in Physics and Sports Education at the University of Stuttgart
07/03
 Master of Science in Physics (Diplomphysiker) at the University of Stuttgart

The bathtub murder - that wasn't one!

Talk on Morpholgical Intelligence at MPI Intelligent Systems Summer Colloquium 2020

SimTech und die Simulation des menschlichen Körpers (YouTube Video)

SimTech and the Simulation of the Human Body (YouTube Video)

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