Subproject C03

Subproject C03

Investigation of Postural Control Using Sensomotorically Extended Musculoskeletal Human Models

Novel postural control models of standing and walking are explored to characterize the components of dynamic balance control. For this purpose, clinically annotated standing and walking movements are used as input data, and muscle-actuated multi-body models are extended by a sensorimotor level. Neuromotor and control model parameters of (patho-)physiological movement are identified with the help of machine learning methods. Technical and clinical validation of the models will be performed. New EmpkinS measurement techniques will be transferred to the developed models as soon as possible.

 

From: https://doi.org/10.1186/s12984-023-01235-3

 

Contacts

Prof. Dr. Björn Eskofier

Principal Investigator

Dr.-Ing. Jörg Miehling

Principal Investigator

Prof. Dr.-Ing. Sandro Wartzack

Principal Investigator

Prof. Dr. med. Jürgen Winkler

Principal Investigator

Sophie Fleischmann, M. Sc.

Doctoral Candidate

Julian Shanbhag, M.Sc

Doctoral Candidate

Jonas Müller, M. Sc.

Associate Doctoral Candidate

 

 

PD Dr. Heiko Gaßner

Associated Member

Prof. Dr. Jochen Klucken

Associated Member

 

Additional Information

  • Fleischmann S., Dietz S., Shanbhag J., Wünsch A., Nitschke M., Miehling J., Wartzack S., Leyendecker S., Eskofier B., Koelewijn A.:
    Exploring Dataset Bias and Scaling Techniques in Multi-Source Gait Biomechanics: An Explainable Machine Learning Approach.
    In: ACM Transactions on Intelligent Systems and Technology 20 (2024), Art.Nr.: 20. ISSN: 2157-6904. DOI: 10.1145/3702646
  • Fleischmann S., Holzwarth Correa V., Coppers B., Sadeghi M., Richer R., Kleyer A., Simon D., Bräunig J., Vossiek M., Schönau V., Schett G., Koelewijn A., Leyendecker S., Eskofier B., Liphardt AM.:
    Classification of rheumatoid arthritis from hand motion capture data using machine learning.
    13. Kongress der Deutschen Gesellschaft für Biomechanik (DGfB) (Heidelberg, 24 April 2024 – 26 April 2024)
  • Shanbhag J., Fleischmann S., Gaßner H., Winkler J., Eskofier B., Koelewijn A., Wartzack S., Miehling J.:
    Modelling postural control of upright standing during translational perturbations
    29th Congress of the European Society of Biomechanics (Edinburgh, Scotland, 30 Juni 2024 – 3 Juli 2024)
  • Shanbhag J., Fleischmann S., Wechsler I., Gaßner H., Winkler J., Eskofier B., Koelewijn A., Wartzack S., Miehling J.:
    A sensorimotor enhanced neuromusculoskeletal model for simulating postural control of upright standing
    In: Frontiers in Neuroscience 18 (2024). ISSN: 1662-4548. DOI: 10.3389/fnins.2024.1393749
  • Wechsler I., Wolf A., Shanbhag J., Leyendecker S., Eskofier B., Koelewijn A., Wartzack S., Miehling J.:
    Bridging the sim2real gap. Investigating deviations between experimental motion measurements and musculoskeletal simulation results—a systematic review
    In: Frontiers in Bioengineering and Biotechnology 12 (2024). ISSN: 2296-4185. DOI: 10.3389/fbioe.2024.1386874
  • Brückner S., Weber J., Michler F., Shanin N., Schober R., Hagelauer A., Weigel R., Gaßner H., Winkler J., Eskofier B., Vossiek M.:
    A Wireless Joint Communication and Localization EMG-Sensing Concept for Movement Disorder Assessment
    IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology (2023)
  • Fleischmann S., Shanbhag J., Miehling J., Wartzack S., Leyendecker S., Koelewijn A., Eskofier B.:
    Time vs. Space: Comparing gait cycle normalization methods and their effect on foot placement control
    28th Congress of the European Society of Biomechanics (Maastricht, 9 Juli 2023 – 12 Juli 2023)
  • Shanbhag J., Fleischmann S., Eskofier B., Koelewijn A., Wartzack S., Miehling J.:
    Towards postural control simulation using a sensorimotor enhanced musculoskeletal human model
    ISPGR World Congress 2023 (Brisbane, 9 Juli 2023 – 13 Juli 2023)
  • Shanbhag J., Wolf A., Wechsler I., Fleischmann S., Winkler J., Leyendecker S., Eskofier B., Koelewijn A., Wartzack S., Miehling J.:
    Methods for integrating postural control into biomechanical human simulations: A systematic review
    Journal of NeuroEngineering and Rehabilitation (2023)
  • Wechsler I., Wolf A., Fleischmann S., Waibel J., Molz C., Scherb D., Shanbhag J., Franz M., Wartzack S., Miehling J.:
    Method for Using IMU-Based Experimental Motion Data in BVH Format for Musculoskeletal Simulations via OpenSim
    Sensors (2023)
  • Fleischmann S., Nitschke M., Marzilger R., Koelewijn A.:
    Can we combine data sets? Feature extraction and clustering motion capture data
    17th International Symposium of 3-D Analysis of Human Movement (3D-AHM) (Tokyo, Japan, 16 Juli 2022 – 19 Juli 2022)
  • Gaßner H., Friedrich J., Masuch A., Jukic J., Stallforth S., Regensburger M., Marxreiter F., Winkler J., Klucken J.:
    The Effects of an Individualized Smartphone-Based Exercise Program on Self-defined Motor Tasks in Parkinson Disease: Pilot Interventional Study
    JMIR Rehabilitation and Assistive Technologies (2022)
  • Gaßner H., Trutt E., Seifferth S., Friedrich J., Zucker D., Salhani Z., Adler W., Winkler J., Jost WH.:
    Treadmill training and physiotherapy similarly improve dual task gait performance: a randomized-controlled trial in Parkinson’s disease
    Journal of Neural Transmission (2022)
  • Ullrich M., Roth N., Küderle A., Richer R., Gladow T., Gaßner H., Marxreiter F., Klucken J., Eskofier B., Kluge F.:
    Fall Risk Prediction in Parkinson’s Disease Using Real-World Inertial Sensor Gait Data
    IEEE T NEUR SYS REH (2022)
  • Jakob V., Küderle A., Klucken J., Eskofier B., Winkler J., Winterholler M., Gaßner H., Kluge F.:
    Validation of a sensor-based gait analysis system with a gold-standard motion capture system in patients with parkinson’s disease
    Sensors (2021)