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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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    https://www.researchgate.net/profile/Marion-Mundt?ev=hdr_xprf
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  • ORCID iD

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

  • Mundt, M., Pagnon, D., Colyer, S. (2025). The influence of the marker set on inverse kinematics results to inform markerless motion capture annotations. Scientific Reports, 15(1), Article number 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), Article number 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 2024 Conference Proceedings (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 2023 CONFERENCE PROCEEDINGS (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 2023 CONFERENCE PROCEEDINGS (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. 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. 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

  • 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.
  • 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 2021 CONFERENCE PROCEEDINGS (Article number 8). ISBS.

2020

Journal Articles

  • 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., 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., 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

  • 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 2020 CONFERENCE PROCEEDINGS (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 2020 CONFERENCE PROCEEDINGS (Article number 94). ISBS.
  • Eggert, B., Mundt, M., Markert, B. (2020). IMU-based activity recognition of the basketball jump shot. ISBS 2020 CONFERENCE PROCEEDINGS (Article number 88). ISBS.

2019

Journal Articles

  • 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.
  • 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.
  • 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.
  • 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.

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

Current Supervisions

Associate Supervisor

  • Doctor of Philosophy, Deep Learning for 3D Medical Image Segmentation

Completed Supervisions

No data available
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