Targeted Achilles Tendon Training and Rehabilitation Using Personalized and Real-Time Multiscale Models of the Neuromusculoskeletal System

Pizzolato, Claudio; Shim, Vickie; Lloyd, David G.; Devaprakash, Daniel; Obst, Steven; Newsham-West, Richard; Graham, David F.; Besier, Thor F.; Zheng, Minghao; Barrett, Rod

doi:10.3389/fbioe.2020.00878

Cited by 36 publications

(25 citation statements)

References 84 publications

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“…This information could be used to inform clinical interventions in the future. For example, movement therapies assisted by real-time biofeedback based on musculoskeletal simulation (similar to Pizzolato et al, 2020) could be used to alter key biomechanical parameters (i.e. hip JCF orientation) to normalize growth trends.…”

Section: Discussionmentioning

confidence: 99%

ESB Clinical Biomechanics Award 2020: Pelvis and hip movement strategies discriminate typical and pathological femoral growth – Insights gained from a multi-scale mechanobiological modelling framework

Kainz

Killen

Campenhout

et al. 2021

Clinical Biomechanics

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Background: Many children with cerebral palsy (CP) develop skeletal deformities during childhood. So far, it is unknown why some children with CP develop bony deformities whereas others do not. The aims of this study were to (i) investigate what loading characteristics lead to typical and pathological femoral growth, and (ii) evaluate why some children with CP develop femoral deformities whereas other do not. Methods: A multi-scale mechanobiological modelling workflow was used to simulate femoral growth based on three-dimensional motion capture data of six typically developing children and 16 children with CP. Based on the growth results, the participants with CP were divided into two groups: typical growth group and pathological growth group. Gait kinematics and femoral loading were compared between simulations resulting in typical growth and those resulting in pathologic growth. Findings: Hip joint contact forces were less posteriorly-oriented in the pathological growth simulations compared to the typical ones. Compared to the typically developing participants, the CP group with pathological femoral growth presented increased knee flexion and no hip extension. The CP group with simulated typical growth presented similar sagittal plane joint kinematics but differed in the frontal plane pelvic and hip movement strategy, which normalized the hip joint contact force and therefore contributed to typical femoral growth trends. Interpretation: Our simulation results identified specific gait features, which may contribute to pathological femoral growth. Furthermore, the hip joint contact force orientation in the sagittal plane seems to be the dominant factor for determining femoral growth simulations.

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Section: Discussionmentioning

confidence: 99%

ESB Clinical Biomechanics Award 2020: Pelvis and hip movement strategies discriminate typical and pathological femoral growth – Insights gained from a multi-scale mechanobiological modelling framework

Kainz

Killen

Campenhout

et al. 2021

Clinical Biomechanics

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“…This substantial variation amongst elite athletes indicates that the relative time courses of adaptation in muscle and tendon might reveal differences at an individual level and that imbalances between muscle and tendon could often remain undetected when only group mean values are considered. Therefore we argue that individualized approaches (Arampatzis et al, 2020) and rapid subject-specific tendon strain estimates (Pizzolato et al, 2020) are needed to provide valuable information for coaches and athletes as well as their medical teams about the adaptive processes in muscles and tendons during the various phases of athletic training. This would enable detection of temporal disruption of the fine-tuned interaction within the MTU during the course of training and could allow adjustment of individual athlete training loads through tailored intervention.…”

Section: Discussionmentioning

confidence: 99%

Monitoring Muscle-Tendon Adaptation Over Several Years of Athletic Training and Competition in Elite Track and Field Jumpers

Karamanidis

Epro

2020

Front. Physiol.

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Differences in muscle and tendon responsiveness to mechanical stimuli and time courses of adaptive changes may disrupt the interaction of the musculotendinous unit (MTU), increasing the risk for overuse injuries. We monitored training-induced alterations in muscle and tendon biomechanical properties in elite jumpers over 4 years of athletic training to detect potential non-synchronized adaptations within the triceps surae MTU. A combined cross-sectional and longitudinal investigation over 4 years was conducted by analyzing triceps surae MTU mechanical properties in both legs via dynamometry and ultrasonography in 67 elite track and field jumpers and 24 age-matched controls. Fluctuations in muscle and tendon adaptive changes over time were quantified by calculating individual residuals. The cosine similarity of the relative changes of muscle strength and tendon stiffness between sessions served as a measure of uniformity of adaptive changes. Our cross-sectional study was unable to detect clear non-concurrent differences in muscle strength and tendon stiffness in elite jumpers. However, when considering the longitudinal data over several years of training most of the jumpers demonstrated greater fluctuations in muscle strength and tendon stiffness and hence tendon strain compared to controls, irrespective of training period (preparation vs. competition). Moreover, two monitored athletes with chronic Achilles tendinopathy showed in their affected limb lower uniformity in MTU adaptation as well as higher fluctuations in tendon strain over time. Habitual mechanical loading can affect the MTU uniformity in elite jumpers, leading to increased mechanical demand on the tendon over an athletic season and potentially increased risk for overuse injuries.

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“…This time margin of about 80 ms will be crucial when carrying the method out in an experimental context as it leaves time for other computing tasks while remaining in real-time (e.g., EMG and markers processing, visualization, warm-starting with an extended Kalman filter, etc.). All these side computations are commonly carried out in real-time (Zohar and van den Bogert, 2008 ; Menegaldo, 2017 ; Pizzolato et al, 2017b , 2020 ) and could be run in parallel, opening up the possibility of working with more complex models. For instance, in Pizzolato et al ( 2017b ), data processing in Vicon Nexus, time delays caused by the filtering phase shift and refresh time of the monitor used to provide the visual biofeedback accounted for 50% of the total processing time, i.e., 58 ms.…”

Section: Discussionmentioning

confidence: 99%

Real-Time and Dynamically Consistent Estimation of Muscle Forces Using a Moving Horizon EMG-Marker Tracking Algorithm—Application to Upper Limb Biomechanics

Bailly

Ceglia

Michaud

et al. 2021

Front. Bioeng. Biotechnol.

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Real-time biofeedback of muscle forces should help clinicians adapt their movement recommendations. Because these forces cannot directly be measured, researchers have developed numerical models and methods informed by electromyography (EMG) and body kinematics to estimate them. Among these methods, static optimization is the most computationally efficient and widely used. However, it suffers from limitation, namely: unrealistic joint torques computation, non-physiological muscle forces estimates and inconsistent for motions inducing co-contraction. Forward approaches, relying on numerical optimal control, address some of these issues, providing dynamically consistent estimates of muscle forces. However, they result in a high computational cost increase, apparently disqualifying them for real-time applications. However, this computational cost can be reduced by combining the implementation of a moving horizon estimation (MHE) and advanced optimization tools. Our objective was to assess the feasibility and accuracy of muscle forces estimation in real-time, using a MHE. To this end, a 4-DoFs arm actuated by 19 Hill-type muscle lines of action was modeled for simulating a set of reference motions, with corresponding EMG signals and markers positions. Excitation- and activation-driven models were tested to assess the effects of model complexity. Four levels of co-contraction, EMG noise and marker noise were simulated, to run the estimator under 64 different conditions, 30 times each. The MHE problem was implemented with three cost functions: EMG-markers tracking (high and low weight on markers) and marker-tracking with least-squared muscle excitations. For the excitation-driven model, a 7-frame MHE was selected as it allowed the estimator to run at 24 Hz (faster than biofeedback standard) while ensuring the lowest RMSE on estimates in noiseless conditions. This corresponds to a 3,500-fold speed improvement in comparison to state-of-the-art equivalent approaches. When adding experimental-like noise to the reference data, estimation error on muscle forces ranged from 1 to 30 N when tracking EMG signals and from 8 to 50 N (highly impacted by the co-contraction level) when muscle excitations were minimized. Statistical analysis was conducted to report significant effects of the problem conditions on the estimates. To conclude, the presented MHE implementation proved to be promising for real-time muscle forces estimation in experimental-like noise conditions, such as in biofeedback applications.

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Targeted Achilles Tendon Training and Rehabilitation Using Personalized and Real-Time Multiscale Models of the Neuromusculoskeletal System

Cited by 36 publications

References 84 publications

ESB Clinical Biomechanics Award 2020: Pelvis and hip movement strategies discriminate typical and pathological femoral growth – Insights gained from a multi-scale mechanobiological modelling framework

ESB Clinical Biomechanics Award 2020: Pelvis and hip movement strategies discriminate typical and pathological femoral growth – Insights gained from a multi-scale mechanobiological modelling framework

Monitoring Muscle-Tendon Adaptation Over Several Years of Athletic Training and Competition in Elite Track and Field Jumpers

Real-Time and Dynamically Consistent Estimation of Muscle Forces Using a Moving Horizon EMG-Marker Tracking Algorithm—Application to Upper Limb Biomechanics

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