Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation
1
Institute of Bioengineering, École Polytechnique Fédérale de Lausanne, 1018 Lausanne, Switzerland
2
Department of Electrical and Computer Engineering, University of Patras, 26504 Patras, Greece
3
Institute for Bio-Economy and Agri-Technology, Center for Research and Technology Hellas, 38333 Volos, Greece
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Academic Editor: Toshiyo Tamura
Sensors 2021, 21(5), 1804; https://doi.org/10.3390/s21051804
Received: 5 February 2021
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Revised: 23 February 2021
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Accepted: 3 March 2021
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Published: 5 March 2021
(This article belongs to the Special Issue Sensors and Musculoskeletal Dynamics to Evaluate Human Movement)
This study aims to explore the possibility of estimating a multitude of kinematic and dynamic quantities using subject-specific musculoskeletal models in real-time. The framework was designed to operate with marker-based and inertial measurement units enabling extensions far beyond dedicated motion capture laboratories. We present the technical details for calculating the kinematics, generalized forces, muscle forces, joint reaction loads, and predicting ground reaction wrenches during walking. Emphasis was given to reduce computational latency while maintaining accuracy as compared to the offline counterpart. Notably, we highlight the influence of adequate filtering and differentiation under noisy conditions and its importance for consequent dynamic calculations. Real-time estimates of the joint moments, muscle forces, and reaction loads closely resemble OpenSim’s offline analyses. Model-based estimation of ground reaction wrenches demonstrates that even a small error can negatively affect other estimated quantities. An application of the developed system is demonstrated in the context of rehabilitation and gait retraining. We expect that such a system will find numerous applications in laboratory settings and outdoor conditions with the advent of predicting or sensing environment interactions. Therefore, we hope that this open-source framework will be a significant milestone for solving this grand challenge.
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Keywords:
real-time; musculoskeletal; kinematics; dynamics; muscle forces; joint reactions; ground reactions; inertial measurement units
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- Supplementary File 1:
ZIP-Document (ZIP, 54974 KiB)
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Externally hosted supplementary file 1
Link: https://simtk.org/projects/real_time
Description: # Overview This folder contains automatically generated plots for the different analyses presented in the publication. Not all coordinates or muscles could be presented in the manuscript. Therefore, we included these as supplementary materials. - `supplementary_filtering.pdf`: presents a comparison of the proposed and spatial filters with respect to OpenSim's kinematics analysis (ground truth) for all model coordinates. - `supplementary_inverse_kinematics.pdf`: a validity check that the inverse kinematics module performs identically to the OpenSim's implementation. - `supplementary_inverse_dynamics.pdf`: presents a comparison of generalized forces of the real-time method using the proposed or the spatial filter and the offline OpenSim inverse dynamics module. - `supplementary_muscle_optimization.pdf`: presents the comparison of muscle forces for the real-time muscle optimization and OpenSim's offline static optimization. - `supplementary_joint_reactions.pdf`: presents the comparison of joint reaction loads between the real-time method (uses muscle forces obtained from the real-time optimization) and the OpenSim's joint reaction analysis. - `real_time_framework_video.webm`: a demo video.
MDPI and ACS Style
Stanev, D.; Filip, K.; Bitzas, D.; Zouras, S.; Giarmatzis, G.; Tsaopoulos, D.; Moustakas, K. Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation. Sensors 2021, 21, 1804. https://doi.org/10.3390/s21051804
AMA Style
Stanev D, Filip K, Bitzas D, Zouras S, Giarmatzis G, Tsaopoulos D, Moustakas K. Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation. Sensors. 2021; 21(5):1804. https://doi.org/10.3390/s21051804
Chicago/Turabian StyleStanev, Dimitar, Konstantinos Filip, Dimitrios Bitzas, Sokratis Zouras, Georgios Giarmatzis, Dimitrios Tsaopoulos, and Konstantinos Moustakas. 2021. "Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation" Sensors 21, no. 5: 1804. https://doi.org/10.3390/s21051804
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