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  • Dr Marion Mundt

    Dr Marion Mundt

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    https://scholar.google.com/citations?user=C96na6UAAAAJ&hl=en&oi=ao
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Dr Marion Mundt

Research Fellow

Staff Member Details
Email: m.mundt@ecu.edu.au
Campus: Joondalup  

Marion is a Research Fellow at the Nutrition and Health Innovation Research Institute in the School of Health and Medical Sciences.

Background

07/2020-07/2024 Research Fellow - UWA Tech & Policy Lab, The University of Western Australia, Australia

12/2015-06/2020 Research Associate - Institute of General Mechanics, RWTH Aachen University, Germany

Professional Associations

  • International Society of Biomechanics
  • International Society of Biomechanics in Sport

Awards and Recognition

  • 2022: Hans Gros Emerging Researcher Award, 40th Conference of the International Society of Biomechanics in Sports, Liverpool, UK., On-field motion analysis: repurposing motion capture datasets and training machine learning models to bring the lab to the field
  • 2021: Student Thesis Award, 1st Conference of the South African Society of Biomechanics. (online). Development of intelligent wearables for the estimation of motion kinematics and kinetics
  • 2021: Best thesis award (Nachwuchspreis für herausragende wissenschaftliche Arbeit in der Lebenswissenschaft), German Sport University Cologne. Development of intelligent wearables for the estimation of motion kinematics and kinetics
  • 2019: 2nd Place New Investigator Award, 37th Conference of the International Society of Biomechanics in Sports. Prediction of joint kinetics based on joint kinematics using artificial neural networks
  • 2018: 2nd Place New Investigator Award, 36th Conference of the International Society of Biomechanics in Sports. Joint angle estimation during fast cutting manoeuvres using artificial neural networks

Research Areas and Interests

  • Machine Learning
  • Biomechanics
  • Movement Science
  • Imaging

Qualifications

  • Doctor of Sports Science, Germany, 2020.

Research Outputs

2025

Journal Articles

  • Pagnon, D., Colyer, S., Mundt, M. (2025). The influence of the marker set on inverse kinematics results to inform markerless motion capture annotations. Scientific Reports, 15(1), 14547. https://doi.org/10.1038/s41598-025-97219-5.

2024

Journal Articles

  • Born, Z., Mundt, M., Mian, A., Weber, J., Alderson, J. (2024). Clustering Offensive Strategies in Australian-Rules Football Using Social Network Analysis. Information (Basel), 15(6), article number 364. https://doi.org/10.3390/info15060364.
  • Mundt, M., Colyer, S., Wade, L., Needham, L., Evans, M., Millet, E., Alderson, J. (2024). Automating Video‐Based Two‐Dimensional Motion Analysis in Sport? Implications for Gait Event Detection, Pose Estimation, and Performance Parameter Analysis. Scandinavian Journal of Medicine and Science in Sports, 34(7), e14693. https://doi.org/10.1111/sms.14693.
  • Born, Z., Mundt, M., Mian, A., Weber, J., Alderson, J. (2024). The Eye in the Sky—A Method to Obtain On-Field Locations of Australian Rules Football Athletes. AI (Switzerland), 5(2), 733-745. https://doi.org/10.3390/ai5020038.

Conference Publications

  • Mundt, M., Colyer, S., Anderson, J. (2024). Determination of Gait Events from 2D Video Using Long Short-Term Memory Neural Networks. ISBS Proceedings Archive (Article number 151). ISBS.

2023

Journal Articles

  • Mundt, M. (2023). Bridging the lab-to-field gap using machine learning: a narrative review. Sports Biomechanics, 2023(article in press), TBD. https://doi.org/10.1080/14763141.2023.2200749.
  • Mundt, M., Born, Z., Goldacre, M., Alderson, J. (2023). Estimating Ground Reaction Forces from Two-Dimensional Pose Data: A Biomechanics-Based Comparison of AlphaPose, BlazePose, and OpenPose. Sensors, 23(1), article number 78. https://doi.org/10.3390/s23010078.

Conference Publications

  • Goldacre, M., Born, Z., Mundt, M., Millett, E., Phillips, E., Alderson, J. (2023). Pose estimation or manual digitising: Can automating technologies change the current in-field assessment of high jump?. ISBS Proceedings Archive (Article number 42). ISBS.
  • Born, Z., Goldacre, M., Mundt, M., Millett, E., Phillips, E., Alderson, J. (2023). Simplifying the high-performance biomechanical assessment of high jump technique. ISBS Proceedings Archive (Article number 12). ISBS.

2022

Book Chapters

  • Mundt, M., Koeppe, A., Bamer, F., Markert, B. (2022). Life Science 4.0: Sensor Technology and Machine Learning in Motion Analysis. Handbook Industry 4.0: Law, Technology, Society (879-894). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-64448-5_46.
  • Koeppe, A., Hesser, D., Mundt, M., Bamer, F., Selzer, M., Markert, B. (2022). Mechanics 4.0: Artificial Intelligence for the Analysis of Mechanical Systems. Handbook Industry 4.0: Law, Technology, Society (455-470). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-64448-5_23.

Journal Articles

  • Mundt, M., Oberlack, H., Goldacre, M., Powles, J., Funken, J., Morris, C., Potthast, W., Alderson, J. (2022). Synthesising 2D Video from 3D Motion Data for Machine Learning Applications. Sensors, 22(17), article number 6522. https://doi.org/10.3390/s22176522.

2021

Journal Articles

  • Mundt, M., Johnson, W., Potthast, W., Markert, B., Mian, A., Alderson, J. (2021). A comparison of three neural network approaches for estimating joint angles and moments from inertial measurement units. Sensors, 21(13), article number 4535. https://doi.org/10.3390/s21134535.

Conference Publications

  • Mundt, M., Oberlack, H., Morris, C., Funken, J., Potthast, W., Alderson, J. (2021). No dataset too small! Animating 3D motion data to enlarge 2D video databases. ISBS Proceedings Archive (Article number 8). ISBS.
  • Morris, C., Mundt, M., Goldacre, M., Weber, J., Mian, A., Alderson, J. (2021). Predicting 3D ground reaction force from 2D video via neural networks in sidestepping tasks. ISBS Proceedings Archive (Article number 77). ISBS.

2020

Journal Articles

  • Mundt, M., Thomsen, W., Witter, T., Koeppe, A., David, S., Bamer, F., Potthast, W., Markert, B. (2020). Prediction of lower limb joint angles and moments during gait using artificial neural networks. Medical and Biological Engineering and Computing, 58(1), 211-225. https://doi.org/10.1007/s11517-019-02061-3.
  • Mundt, M., Koeppe, A., David, S., Witter, T., Bamer, F., Potthast, W., Markert, B. (2020). Estimation of Gait Mechanics Based on Simulated and Measured IMU Data Using an Artificial Neural Network. Frontiers in Bioengineering and Biotechnology, 8(2020), article number 41. https://doi.org/10.3389/fbioe.2020.00041.
  • Mundt, M., Koeppe, A., Bamer, F., David, S., Markert, B. (2020). Artificial neural networks in motion analysis—applications of unsupervised and heuristic feature selection techniques. Sensors, 20(16), 1-15. https://doi.org/10.3390/s20164581.
  • Mundt, M., Koeppe, A., David, S., Bamer, F., Potthast, W., Markert, B. (2020). Prediction of ground reaction force and joint moments based on optical motion capture data during gait. Medical Engineering and Physics, 86(44166), 29-34. https://doi.org/10.1016/j.medengphy.2020.10.001.

Conference Publications

  • Eggert, B., Mundt, M., Markert, B. (2020). IMU-based activity recognition of the basketball jump shot. ISBS Proceedings Archive (Article number 88). ISBS.
  • Fohrmann, D., Mundt, M., David, S., Koeppe, A., Markert, B., Potthast, W. (2020). Creating virtual force platforms for cutting maneuvers from kinematic data based on LSTM neural networks. ISBS Proceedings Archive (Article number 109). ISBS.
  • Mundt, M., Koeppe, A., Bamer, F., Potthast, W., Markert, B. (2020). Feature selection for the application of artificial neural networks in motion analysis. ISBS Proceedings Archive (Article number 94). ISBS.

2019

Journal Articles

  • Mundt, M., Thomsen, W., David, S., Dupré, T., Bamer, F., Potthast, W., Markert, B. (2019). Assessment of the measurement accuracy of inertial sensors during different tasks of daily living. Journal of Biomechanics, 84(43510), 81-86. https://doi.org/10.1016/j.jbiomech.2018.12.023.
  • Knobe, M., Bettag, S., Kammerlander, C., Altgassen, S., Maier, K., Nebelung, S., Prescher, A., Horst, K., Pishnamaz, M., Herren, C., Mundt, M., Stoffel, M., Markert, B., Gueorguiev, B. (2019). Is bone-cement augmentation of screw-anchor fixation systems superior in unstable femoral neck fractures? A biomechanical cadaveric study. Injury, 50(2), 292-300. https://doi.org/10.1016/j.injury.2018.10.038.
  • Mundt, M., Batista, J., Markert, B., Bollheimer, C., Laurentius, T. (2019). Walking with rollator: A systematic review of gait parameters in older persons. European Review of Aging and Physical Activity, 16(1), article number 15. https://doi.org/10.1186/s11556-019-0222-5.
  • Mundt, M., David, S., Koeppe, A., Bamer, F., Markert, B., Potthast, W. (2019). Intelligent prediction of kinetic parameters during cutting manoeuvres. Medical and Biological Engineering and Computing, 57(8), 1833-1841. https://doi.org/10.1007/s11517-019-02000-2.

2018

Journal Articles

  • David, S., Mundt, M., Komnik, I., Potthast, W. (2018). Understanding cutting maneuvers – The mechanical consequence of preparatory strategies and foot strike pattern. Human Movement Science, 62(43435), 202-210. https://doi.org/10.1016/j.humov.2018.10.005.
  • Beckmann, A., Herren, C., Mundt, M., Siewe, J., Kobbe, P., Sobottke, R., Pape, H., Stoffel, M., Markert, B. (2018). A new in vitro spine test rig to track multiple vertebral motions under physiological conditions. Biomedizinische Technik, 63(4), 341-347. https://doi.org/10.1515/bmt-2016-0173.

2017

Journal Articles

  • Caldas, R., Mundt, M., Potthast, W., Buarque, dL., Markert, B. (2017). A systematic review of gait analysis methods based on inertial sensors and adaptive algorithms. Gait and Posture, 57(42979), 204-210. https://doi.org/10.1016/j.gaitpost.2017.06.019.
  • Herren, C., Beckmann, A., Meyer, S., Pishnamaz, M., Mundt, M., Sobottke, R., Prescher, A., Stoffel, M., Markert, B., Kobbe, P., Pape, H., Eysel, P., Siewe, J. (2017). Biomechanical testing of a PEEK-based dynamic instrumentation device in a lumbar spine model. Clinical Biomechanics, 44(42856), 67-74. https://doi.org/10.1016/j.clinbiomech.2017.03.009.

Research Student Supervision

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