Deep Learning-Based Ground Reaction Force Estimation for Real-Time Clinical Applications
Aasmann, Alexander Peper, Kim K. Craik, Alexander Haddadin, Sami
Aasmann, Alexander
Peper, Kim K.
Craik, Alexander
Haddadin, Sami
Supervisor
Department
Robotics
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
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Abstract
This study represents a significant step forward in real-time, marker-based gait analysis, offering a cost-effective and efficient method for estimating Ground Reaction Forces (GRF) and Center of Pressure (COP) in clinical settings. Using marker trajectories captured by a motion capture system, we trained a recurrent neural network (RNN) to estimate GRF and COP during treadmill walking. Real-time experiments with five healthy subjects demonstrated high to very high correlations between predictions and ground truth (rCOP =0.81, rGRF = 0.96). These promising results highlight the potential of this approach to transform clinical gait analysis by reducing reliance on expensive and fixed force-plate systems. Future work will focus on validating the method with pathological gait datasets to ensure broader applicability and advancing its integration into diverse clinical environments for real-time feedback and analysis.
Citation
A. Aasmann, K. K. Peper, A. Craik and S. Haddadin, "Deep Learning-Based Ground Reaction Force Estimation for Real-Time Clinical Applications," 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Copenhagen, Denmark, 2025, pp. 1-6, doi: 10.1109/EMBC58623.2025.11253590.
Source
Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Conference
47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Keywords
Humans, Deep Learning, Neural Networks, Computer-Assisted Analysis, Biomechanical Phenomena, Walking, Male, Gait, Algorithms, Gait Analysis, Adult, Plantar Pressure
Subjects
Source
47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Publisher
IEEE