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Vandenberg NW, Wheatley BB, Carpenter RD, Christiansen CL, Stoneback JW, Gaffney BMM. Feasibility of predicting changes in gait biomechanics following muscle strength perturbations using optimal control in patients with transfemoral amputation. Comput Methods Biomech Biomed Engin 2024:1-15. [PMID: 39256913 DOI: 10.1080/10255842.2024.2399038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 07/04/2024] [Accepted: 08/20/2024] [Indexed: 09/12/2024]
Abstract
Bone-anchored limbs (BALs) are socket prosthesis alternatives, directly fixing to residual bone via osseointegrated implant. There is a need to quantify multi-level effects of rehabilitation for transfemoral BAL users (i.e. changes in joint loading and movement patterns). Our primary objective was determining feasibility of using optimal control to predict gait biomechanics compared to ground-truth experimental data from transfemoral BAL users. A secondary objective was examining biomechanical effects from estimated changes in hip abductor muscle strength. We developed and validated a workflow for predicting gait biomechanics in four transfemoral BAL users and investigated the biomechanical effects of altered hip abductor strengths.
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Affiliation(s)
- Nicholas W Vandenberg
- Department of Mechanical Engineering, University of Colorado Denver, University to Colorado Bone-Anchored Limb Research Group, Denver, Colorado, USA
| | - Benjamin B Wheatley
- Department of Mechanical Engineering, Bucknell University, Lewisburg, Pennsylvania, USA
| | - R Dana Carpenter
- Department of Mechanical Engineering, University of Colorado Denver, University to Colorado Bone-Anchored Limb Research Group, Denver, Colorado, USA
| | - Cory L Christiansen
- Department of Physical Medicine and Rehabilitation, University of Colorado Anschutz Medical Campus, University to Colorado Bone-Anchored Limb Research Group, Aurora, Colorado, USA
- Department of Veterans Affairs Eastern Colorado Healthcare System, University to Colorado Bone-Anchored Limb Research Group, Aurora, Colorado, USA
| | - Jason W Stoneback
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, University to Colorado Bone-Anchored Limb Research Group, Aurora, Colorado, USA
| | - Brecca M M Gaffney
- Department of Mechanical Engineering, University of Colorado Denver, University to Colorado Bone-Anchored Limb Research Group, Denver, Colorado, USA
- Department of Veterans Affairs Eastern Colorado Healthcare System, University to Colorado Bone-Anchored Limb Research Group, Aurora, Colorado, USA
- Center for Bioengineering, University of Colorado Denver, University to Colorado Bone-Anchored Limb Research Group, Aurora, Colorado, USA
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Lichtwark GA, Schuster RW, Kelly LA, Trost SG, Bialkowski A. Markerless motion capture provides accurate predictions of ground reaction forces across a range of movement tasks. J Biomech 2024; 166:112051. [PMID: 38503062 DOI: 10.1016/j.jbiomech.2024.112051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 02/28/2024] [Accepted: 03/13/2024] [Indexed: 03/21/2024]
Abstract
Measuring or estimating the forces acting on the human body during movement is critical for determining the biomechanical aspects relating to injury, disease and healthy ageing. In this study we examined whether quantifying whole-body motion (segmental accelerations) using a commercial markerless motion capture system could accurately predict three-dimensional ground reaction force during a diverse range of human movements: walking, running, jumping and cutting. We synchronously recorded 3D ground reaction forces (force instrumented treadmill or in-ground plates) with high-resolution video from eight cameras that were spatially calibrated relative to a common coordinate system. We used a commercially available software to reconstruct whole body motion, along with a geometric skeletal model to calculate the acceleration of each segment and hence the whole-body centre of mass and ground reaction force across each movement task. The average root mean square difference (RMSD) across all three dimensions and all tasks was 0.75 N/kg, with the maximum average RMSD being 1.85 N/kg for running vertical force (7.89 % of maximum). There was very strong agreement between peak forces across tasks, with R2 values indicating that the markerless prediction algorithm was able to predict approximately 95-99 % of the variance in peak force across all axes and movements. The results were comparable to previous reports using whole-body marker-based approaches and hence this provides strong proof-of-principle evidence that markerless motion capture can be used to predict ground reaction forces and therefore potentially assess movement kinetics with limited requirements for participant preparation.
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Affiliation(s)
- Glen A Lichtwark
- School of Exercise and Nutrition Sciences, Queensland University of Technology, Kelvin Grove, QLD 4059, Australia; School of Human Movement and Nutrition Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia.
| | - Robert W Schuster
- School of Human Movement and Nutrition Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia
| | - Luke A Kelly
- School of Human Movement and Nutrition Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast 4111, Australia; Griffith Centre of Biomedical and Rehabilitation Engineering, Griffith University, Gold Coast 4111, Australia
| | - Stewart G Trost
- School of Human Movement and Nutrition Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia; Children's Health Queensland Health and Hospital Service, South Brisbane, QLD 4101, Australia
| | - Alina Bialkowski
- School of Electrical Engineering and Computer Science, The University of Queensland, St Lucia, QLD 4072, Australia
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Torvinen P, Ruotsalainen KS, Zhao S, Cronin N, Ohtonen O, Linnamo V. Evaluation of 3D Markerless Motion Capture System Accuracy during Skate Skiing on a Treadmill. Bioengineering (Basel) 2024; 11:136. [PMID: 38391622 PMCID: PMC10886413 DOI: 10.3390/bioengineering11020136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
In this study, we developed a deep learning-based 3D markerless motion capture system for skate skiing on a treadmill and evaluated its accuracy against marker-based motion capture during G1 and G3 skating techniques. Participants performed roller skiing trials on a skiing treadmill. Trials were recorded with two synchronized video cameras (100 Hz). We then trained a custom model using DeepLabCut, and the skiing movements were analyzed using both DeepLabCut-based markerless motion capture and marker-based motion capture systems. We statistically compared joint centers and joint vector angles between the methods. The results demonstrated a high level of agreement for joint vector angles, with mean differences ranging from -2.47° to 3.69°. For joint center positions and toe placements, mean differences ranged from 24.0 to 40.8 mm. This level of accuracy suggests that our markerless approach could be useful as a skiing coaching tool. The method presents interesting opportunities for capturing and extracting value from large amounts of data without the need for markers attached to the skier and expensive cameras.
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Affiliation(s)
- Petra Torvinen
- Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland
| | - Keijo S Ruotsalainen
- Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland
| | - Shuang Zhao
- Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland
| | - Neil Cronin
- Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland
| | - Olli Ohtonen
- Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland
| | - Vesa Linnamo
- Faculty of Sport and Health Sciences, University of Jyväskylä, 88610 Jyväskylä, Finland
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Auer S, Süß F, Dendorfer S. Using markerless motion capture and musculoskeletal models: An evaluation of joint kinematics. Technol Health Care 2024; 32:3433-3442. [PMID: 38905067 DOI: 10.3233/thc-240202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/23/2024]
Abstract
BACKGROUND This study presents a comprehensive comparison between a marker-based motion capture system (MMC) and a video-based motion capture system (VMC) in the context of kinematic analysis using musculoskeletal models. OBJECTIVE Focusing on joint angles, the study aimed to evaluate the accuracy of VMC as a viable alternative for biomechanical research. METHODS Eighteen healthy subjects performed isolated movements with 17 joint degrees of freedom, and their kinematic data were collected using both an MMC and a VMC setup. The kinematic data were entered into the AnyBody Modelling System, which enables the calculation of joint angles. The mean absolute error (MAE) was calculated to quantify the deviations between the two systems. RESULTS The results showed good agreement between VMC and MMC at several joint angles. In particular, the shoulder, hip and knee joints showed small deviations in kinematics with MAE values of 4.8∘, 6.8∘ and 3.5∘, respectively. However, the study revealed problems in tracking hand and elbow movements, resulting in higher MAE values of 13.7∘ and 27.7∘. Deviations were also higher for head and thoracic movements. CONCLUSION Overall, VMC showed promising results for lower body and shoulder kinematics. However, the tracking of the wrist and pelvis still needs to be refined. The research results provide a basis for further investigations that promote the fusion of VMC and musculoskeletal models.
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Affiliation(s)
- Simon Auer
- Laboratory for Biomechanics, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany
| | - Franz Süß
- Laboratory for Biomechanics, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, Ostbayerische Technische Hochschule and University Regensburg, Germany
| | - Sebastian Dendorfer
- Laboratory for Biomechanics, Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany
- Regensburg Center of Biomedical Engineering, Ostbayerische Technische Hochschule and University Regensburg, Germany
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Ripic Z, Nienhuis M, Signorile JF, Best TM, Jacobs KA, Eltoukhy M. A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait. J Biomech 2023; 159:111793. [PMID: 37725886 DOI: 10.1016/j.jbiomech.2023.111793] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 07/20/2023] [Accepted: 09/04/2023] [Indexed: 09/21/2023]
Abstract
Vision-based methods using RGB inputs for human pose estimation have grown in recent years but have undergone limited testing in clinical and biomechanics research areas like gait analysis. The purpose of the present study was to compare lower extremity kinematics during overground gait between a traditional marker-based approach and a commercial multi-view markerless system in a sample of subjects including young adults, older adults, and adults diagnosed with Parkinson's disease. A convenience sample of 35 adults between the age of 18-85 years were included in this study, yielding a total of 114 trials and 228 gait cycles that were compared between systems. A total of 30 time normalized waveforms, including three-dimensional joint centers, segment angles, and joint angles were compared between systems using root mean-squared error (RMSE), range of motion difference (ΔROM), Pearson correlation coefficients (r), and interclass correlation coefficients (ICC). RMSEs for joint center positions were less than 28 mm in all joints with correlations indicating good to excellent agreement. RMSEs for segment and joint angles were in range of previous results, with highest agreement between systems in the sagittal plane. ΔROM differences were within reference values that characterize clinical groups like Parkinson's disease, stroke, or knee osteoarthritis. Further improvements in pelvis tracking, markerless keypoint model definitions, and standardization of comparison study protocols are needed. Nevertheless, markerless solutions seem promising toward unrestricted motion analysis in biomechanics research and clinical settings.
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Affiliation(s)
- Zachary Ripic
- Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Sports Medicine Institute, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Mitch Nienhuis
- Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States
| | - Joseph F Signorile
- Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Center on Aging, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Thomas M Best
- Sports Medicine Institute, University of Miami Miller School of Medicine, Miami, FL, United States; Department of Orthopaedics, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Kevin A Jacobs
- Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States
| | - Moataz Eltoukhy
- Department of Kinesiology and Sport Sciences, University of Miami, Miami, FL, United States; Department of Physical Therapy, University of Miami Miller School of Medicine, Miami, FL, United States; Department of Industrial and Systems Engineering, University of Miami, Miami, FL, United States.
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