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Romanato M, Zhang L, Sawacha Z, Gutierrez-Farewik EM. Influence of different calibration methods on surface electromyography-informed musculoskeletal models with few input signals. Clin Biomech (Bristol, Avon) 2023; 109:106074. [PMID: 37660576 DOI: 10.1016/j.clinbiomech.2023.106074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 06/20/2023] [Accepted: 08/17/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Although model personalization is critical when assessing individuals with morphological or neurological abnormalities, or even non-disabled subjects, its translation into routine clinical settings is hampered by the cumbersomeness of experimental data acquisition and lack of resources, which are linked to high costs and long processing pipelines. Quantifying the impact of neglecting subject-specific information in simulations that aim to estimate muscle forces with surface electromyography informed modeling approaches, can address their potential in relevant clinical questions. The present study investigates how different methods to fine-tune subject-specific neuromuscular parameters, reducing the number of electromyography input data, could affect the estimation of the unmeasured excitations and the musculotendon forces. METHODS Three-dimensional motion analysis was performed on 8 non-disabled adult subjects and 13 electromyographic signals captured. Four neuromusculoskeletal models were created for 8 participants: a reference model driven by a large set of sEMG signals; two models informed by four electromyographic signals but calibrated in different fashions; a model based on static optimization. FINDINGS The electromyography-informed models better predicted experimental excitations, including the unmeasured ones. The model based on static optimization obtained less reliable predictions of the experimental data. When comparing the different reduced models, no major differences were observed, suggesting that the less complex model may suffice for predicting muscle forces with a small set of input in clinical gait analysis tasks. INTERPRETATION Quantitative model performance evaluation in different conditions provides an objective indication of which method yields the most accurate prediction when a small set of electromyographic recordings is available.
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Affiliation(s)
- M Romanato
- Department of Information Engineering, University of Padova, Padova, Italy
| | - L Zhang
- KTH MoveAbility Lab, Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Z Sawacha
- Department of Information Engineering, University of Padova, Padova, Italy; Department of Medicine, University of Padova, Padova, Italy.
| | - E M Gutierrez-Farewik
- KTH MoveAbility Lab, Department of Engineering Mechanics, KTH Royal Institute of Technology, Stockholm, Sweden
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Hambly MJ, De Sousa ACC, Lloyd DG, Pizzolato C. EMG-Informed Neuromusculoskeletal Modelling Estimates Muscle Forces and Joint Moments During Electrical Stimulation. IEEE Int Conf Rehabil Robot 2023; 2023:1-6. [PMID: 37941242 DOI: 10.1109/icorr58425.2023.10304785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
This study implemented an electromyogram (EMG)-informed neuromusculoskeletal (NMS) model evaluating the volitional contributions to muscle forces and joint moments during functional electrical stimulation (FES). The NMS model was calibrated using motion and EMG (biceps brachii and triceps brachii) data recorded from able-bodied participants (n=3) performing weighted elbow flexion and extension cycling movements while equipped with an EMG-controlled closed-loop FES system. Models were executed using three computational approaches (i) EMG-driven, (ii) EMG-hybrid and (iii) EMG-assisted to estimate muscle forces and joint moments. Both EMG-hybrid and EMG-assisted modes were able estimate the elbow moment (root mean squared error and coefficient of determination), but the EMG-hybrid method also enabled quantifying the volitional contributions to muscle forces and elbow moments during FES. The proposed modelling method allows for assessing volitional contributions of patients to muscle force during FES rehabilitation, and could be used as biomarkers of recovery, biofeedback, and for real-time control of combined FES and robotic systems.
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Meszaros-Beller L, Hammer M, Schmitt S, Pivonka P. Effect of neglecting passive spinal structures: a quantitative investigation using the forward-dynamics and inverse-dynamics musculoskeletal approach. Front Physiol 2023; 14:1135531. [PMID: 37324394 PMCID: PMC10264677 DOI: 10.3389/fphys.2023.1135531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 04/28/2023] [Indexed: 06/17/2023] Open
Abstract
Purpose: Inverse-dynamics (ID) analysis is an approach widely used for studying spine biomechanics and the estimation of muscle forces. Despite the increasing structural complexity of spine models, ID analysis results substantially rely on accurate kinematic data that most of the current technologies are not capable to provide. For this reason, the model complexity is drastically reduced by assuming three degrees of freedom spherical joints and generic kinematic coupling constraints. Moreover, the majority of current ID spine models neglect the contribution of passive structures. The aim of this ID analysis study was to determine the impact of modelled passive structures (i.e., ligaments and intervertebral discs) on remaining joint forces and torques that muscles must balance in the functional spinal unit. Methods: For this purpose, an existing generic spine model developed for the use in the demoa software environment was transferred into the musculoskeletal modelling platform OpenSim. The thoracolumbar spine model previously used in forward-dynamics (FD) simulations provided a full kinematic description of a flexion-extension movement. By using the obtained in silico kinematics, ID analysis was performed. The individual contribution of passive elements to the generalised net joint forces and torques was evaluated in a step-wise approach increasing the model complexity by adding individual biological structures of the spine. Results: The implementation of intervertebral discs and ligaments has significantly reduced compressive loading and anterior torque that is attributed to the acting net muscle forces by -200% and -75%, respectively. The ID model kinematics and kinetics were cross-validated against the FD simulation results. Conclusion: This study clearly shows the importance of incorporating passive spinal structures on the accurate computation of remaining joint loads. Furthermore, for the first time, a generic spine model was used and cross-validated in two different musculoskeletal modelling platforms, i.e., demoa and OpenSim, respectively. In future, a comparison of neuromuscular control strategies for spinal movement can be investigated using both approaches.
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Affiliation(s)
- Laura Meszaros-Beller
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Maria Hammer
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
- Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Syn Schmitt
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
- Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Peter Pivonka
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia
- Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD, Australia
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Meszaros-Beller L, Hammer M, Riede JM, Pivonka P, Little JP, Schmitt S. Effects of geometric individualisation of a human spine model on load sharing: neuro-musculoskeletal simulation reveals significant differences in ligament and muscle contribution. Biomech Model Mechanobiol 2023; 22:669-694. [PMID: 36602716 PMCID: PMC10097810 DOI: 10.1007/s10237-022-01673-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 12/08/2022] [Indexed: 01/06/2023]
Abstract
In spine research, two possibilities to generate models exist: generic (population-based) models representing the average human and subject-specific representations of individuals. Despite the increasing interest in subject specificity, individualisation of spine models remains challenging. Neuro-musculoskeletal (NMS) models enable the analysis and prediction of dynamic motions by incorporating active muscles attaching to bones that are connected using articulating joints under the assumption of rigid body dynamics. In this study, we used forward-dynamic simulations to compare a generic NMS multibody model of the thoracolumbar spine including fully articulated vertebrae, detailed musculature, passive ligaments and linear intervertebral disc (IVD) models with an individualised model to assess the contribution of individual biological structures. Individualisation was achieved by integrating skeletal geometry from computed tomography and custom-selected muscle and ligament paths. Both models underwent a gravitational settling process and a forward flexion-to-extension movement. The model-specific load distribution in an equilibrated upright position and local stiffness in the L4/5 functional spinal unit (FSU) is compared. Load sharing between occurring internal forces generated by individual biological structures and their contribution to the FSU stiffness was computed. The main finding of our simulations is an apparent shift in load sharing with individualisation from an equally distributed element contribution of IVD, ligaments and muscles in the generic spine model to a predominant muscle contribution in the individualised model depending on the analysed spine level.
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Affiliation(s)
- Laura Meszaros-Beller
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, Australia.,Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Maria Hammer
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany.,Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Julia M Riede
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Peter Pivonka
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, Australia
| | - J Paige Little
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, Australia
| | - Syn Schmitt
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, Australia. .,Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany. .,Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart, Stuttgart, Germany.
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Meinders E, Pizzolato C, Gonçalves BAM, Lloyd DG, Saxby DJ, Diamond LE. Electromyography measurements of the deep hip muscles do not improve estimates of hip contact force. J Biomech 2022; 141:111220. [PMID: 35841785 DOI: 10.1016/j.jbiomech.2022.111220] [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: 02/24/2022] [Revised: 06/16/2022] [Accepted: 07/06/2022] [Indexed: 11/18/2022]
Abstract
The deep hip muscles are often omitted in studies investigating hip contact forces using neuromusculoskeletal modelling methods. However, recent evidence indicates the deep hip muscles have potential to change the direction of hip contact force and could have relevance for hip contact loading estimates. Further, it is not known whether deep hip muscle excitation patterns can be accurately estimated using neuromusculoskeletal modelling or require measurement (through invasive and time-consuming methods) to inform models used to estimate hip contact forces. We calculated hip contact forces during walking, squatting, and squat-jumping for 17 participants using electromyography (EMG)-informed neuromusculoskeletal modelling with (informed) and without (synthesized) intramuscular EMG for the deep hip muscles (piriformis, obturator internus, quadratus femoris). Hip contact force magnitude and direction, calculated as the angle between hip contact force and vector from femoral head to acetabular center, were compared between configurations using a paired t-test deployed through statistical parametric mapping (P < 0.05). Additionally, root mean square error, correlation coefficients (R2), and timing accuracy between measured and modelled deep hip muscle excitation patterns were computed. No significant between-configuration differences in hip contact force magnitude or direction were found for any task. However, the synthesized method poorly predicted (R2-range 0.02-0.3) deep hip muscle excitation patterns for all tasks. Consequently, intramuscular EMG of the deep hip muscles may be unnecessary when estimating hip contact force magnitude or direction using EMG-informed neuromusculoskeletal modelling, though is likely essential for investigations of deep hip muscle function.
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Affiliation(s)
- Evy Meinders
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland 4222, Australia; Advanced Design and Prototyping Technologies Institute (ADaPT), Griffith University, Gold Coast, Queensland 4222, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Queensland 4222, Australia.
| | - Claudio Pizzolato
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland 4222, Australia; Advanced Design and Prototyping Technologies Institute (ADaPT), Griffith University, Gold Coast, Queensland 4222, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Queensland 4222, Australia
| | - Basílio A M Gonçalves
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland 4222, Australia; Advanced Design and Prototyping Technologies Institute (ADaPT), Griffith University, Gold Coast, Queensland 4222, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Queensland 4222, Australia
| | - David G Lloyd
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland 4222, Australia; Advanced Design and Prototyping Technologies Institute (ADaPT), Griffith University, Gold Coast, Queensland 4222, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Queensland 4222, Australia
| | - David J Saxby
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland 4222, Australia; Advanced Design and Prototyping Technologies Institute (ADaPT), Griffith University, Gold Coast, Queensland 4222, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Queensland 4222, Australia
| | - Laura E Diamond
- Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE), Menzies Health Institute Queensland, Griffith University, Gold Coast, Queensland 4222, Australia; Advanced Design and Prototyping Technologies Institute (ADaPT), Griffith University, Gold Coast, Queensland 4222, Australia; School of Health Sciences and Social Work, Griffith University, Gold Coast, Queensland 4222, Australia; Centre of Clinical Research Excellence in Spinal Pain, Injury and Health, The University of Queensland, Brisbane, Queensland 4072, Australia
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