Generative deep learning applied to biomechanics: creating an infinite number of realistic walking data for modelling and data augmentation purposes

Our work using generative deep learning models to generate synthetic human movement data to augment existing datasets was presented at the 9th World Congress of Biomechanics

Estimation of musculotendon parameters for scaled and subject specific musculoskeletal models using an optimization technique.

A challenging aspect of subject specific musculoskeletal modeling is the estimation of muscle parameters, especially optimal fiber length and tendon slack length. In this study, the method for scaling musculotendon parameters published by Winby et al. (2008), J. Biomech. 41, 1682-1688, has been reformulated, generalized and applied to two cases of practical interest: 1) the adjustment of muscle parameters in the entire lower limb following linear scaling of a generic model and 2) their estimation "from scratch" in a subject specific model of the hip joint created from medical images. In the first case, the procedure maintained the muscles׳ operating range between models with mean errors below 2.3% of the reference model normalized fiber length value. In the second case, a subject specific model of the hip joint was created using segmented bone geometries and muscle volumes publicly available for a cadaveric specimen from the Living Human Digital Library (LHDL). Estimated optimal fiber lengths were found to be consistent with those of a previously published dataset for all 27 considered muscle bundles except gracilis. However, computed tendon slack lengths differed from tendon lengths measured in the LHDL cadaver, suggesting that tendon slack length should be determined via optimization in subject-specific applications. Overall, the presented methodology could adjust the parameters of a scaled model and enabled the estimation of muscle parameters in newly created subject specific models. All data used in the analyses are of public domain and a tool implementing the algorithm is available at https://simtk.org/home/opt_muscle_par

Muscle recruitment strategies can reduce joint loading during level walking

Joint inflammation, with consequent cartilage damage and pain, typically reduces functionality and affects activities of daily life in a variety of musculoskeletal diseases. Since mechanical loading is an important determinant of the disease process, a possible conservative treatment is the unloading of joints. In principle, a neuromuscular rehabilitation program aimed to promote alternative muscle recruitments could reduce the loads on the lower-limb joints during walking. The extent of joint load reduction one could expect from this approach remains unknown. Furthermore, assuming significant reductions of the load on the affected joint can be achieved, it is unclear whether, and to what extent, the other joints will be overloaded. Using subject-specific musculoskeletal models of four different participants, we computed the muscle recruitment strategies that minimised the hip, knee and ankle contact force, and predicted the contact forces such strategies induced at the other joints. Significant reductions of the peak force and impulse at the knee and hip were obtained, while only a minimal effect was found at the ankle joint. Adversely, the peak force and the impulse in non-targeted joints increased when aiming to minimize the load in an adjacent joint. These results confirm the potential of alternative muscle recruitment strategies to reduce the loading at the knee and the hip, but not at the ankle. Therefore, neuromuscular rehabilitation can be targeted to reduce the loading at affected joints but must be considered carefully in patients with multiple joints affected due to the potential adverse effects in non-targeted joints

Using musculoskeletal models to estimate in vivo total knee replacement kinematics and loads: effect of differences between models

Total knee replacement (TKR) is one of the most performed orthopedic surgeries to treat knee joint diseases in the elderly population. Although the survivorship of knee implants may extend beyond two decades, the poor outcome rate remains considerable. A recent computational approach used to better understand failure modes and improve TKR outcomes is based on the combination of musculoskeletal (MSK) and finite element models. This combined multiscale modeling approach is a promising strategy in the field of computational biomechanics; however, some critical aspects need to be investigated. In particular, the identification and quantification of the uncertainties related to the boundary conditions used as inputs to the finite element model due to a different definition of the MSK model are crucial. Therefore, the aim of this study is to investigate this problem, which is relevant for the model credibility assessment process. Three different generic MSK models available in the OpenSim platform were used to simulate gait, based on the experimental data from the fifth edition of the “Grand Challenge Competitions to Predict in vivo Knee Loads.” The outputs of the MSK analyses were compared in terms of relative kinematics of the knee implant components and joint reaction (JR) forces and moments acting on the tibial insert. Additionally, the estimated knee JRs were compared with those measured by the instrumented knee implant so that the “global goodness of fit” was quantified for each model. Our results indicated that the different kinematic definitions of the knee joint and the muscle model implemented in the different MSK models influenced both the motion and the load history of the artificial joint. This study demonstrates the importance of examining the influence of the model assumptions on the output results and represents the first step for future studies that will investigate how the uncertainties in the MSK models propagate on disease-specific finite element model results

Biofeedback for gait retraining based on real-time estimation of tibiofemoral joint contact forces

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this study we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed 5 healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only 3 subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this study focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body

Biofeedback for gait retraining based on real-time estimation of tibiofemoral joint contact forces

Biofeedback assisted rehabilitation and intervention technologies have the potential to modify clinically relevant biomechanics. Gait retraining has been used to reduce the knee adduction moment, a surrogate of medial tibiofemoral joint loading often used in knee osteoarthritis research. In this study we present an electromyogram-driven neuromusculoskeletal model of the lower-limb to estimate, in real-time, the tibiofemoral joint loads. The model included 34 musculotendon units spanning the hip, knee, and ankle joints. Full-body inverse kinematics, inverse dynamics, and musculotendon kinematics were solved in real-time from motion capture and force plate data to estimate the knee medial tibiofemoral contact force (MTFF). We analyzed 5 healthy subjects while they were walking on an instrumented treadmill with visual biofeedback of their MTFF. Each subject was asked to modify their gait in order to vary the magnitude of their MTFF. All subjects were able to increase their MTFF, whereas only 3 subjects could decrease it, and only after receiving verbal suggestions about possible gait modification strategies. Results indicate the important role of knee muscle activation patterns in modulating the MTFF. While this study focused on the knee, the technology can be extended to examine the musculoskeletal tissue loads at different sites of the human body

Investigation of the dependence of joint contact forces on musculotendon parameters using a codified workflow for image-based modelling

The generation of subject-specific musculoskeletal models of the lower limb has become a feasible taskthanks to improvements in medical imaging technology and musculoskeletal modelling software.Nevertheless, clinical use of these models in paediatric applications is still limited for what concernsthe estimation of muscle and joint contact forces. Aiming to improve the current state of the art, amethodology to generate highly personalized subject-specific musculoskeletal models of the lower limbbased on magnetic resonance imaging (MRI) scans was codified as a step-by-step procedure and appliedto data from eight juvenile individuals. The generated musculoskeletal models were used to simulate 107gait trials using stereophotogrammetric and force platform data as input. To ensure completeness of themodelling procedure, muscles’ architecture needs to be estimated. Four methods to estimate muscles’maximum isometric force and two methods to estimate musculotendon parameters (optimal fiber lengthand tendon slack length) were assessed and compared, in order to quantify their influence on the models’output. Reported results represent the first comprehensive subject-specific model-based characterizationof juvenile gait biomechanics, including profiles of joint kinematics and kinetics, muscle forces and jointcontact forces. Our findings suggest that, when musculotendon parameters were linearly scaled from areference model and the muscle force-length-velocity relationship was accounted for in the simulations,realistic knee contact forces could be estimated and these forces were not sensitive the method used tocompute muscle maximum isometric force

Diagnostic nerve block in prediction of outcome of botulinum toxin treatment for spastic equinovarus foot after stroke: A retrospective observational study

Objective: To evaluate the role of diagnostic nerve block in predicting the outcome of subsequent botulinum toxin type A treatment for spastic equinovarus foot due to chronic stroke. Design: Retrospective observational study. Patients: Fifty chronic stroke patients with spastic equinovarus foot. Methods: Each patient was given diagnostic tibial nerve block (lidocaine 2% perineural injection) assessment followed by botulinum toxin type A inoculation into the same muscles as had been targeted by the nerve block. All patients were evaluated before diagnostic nerve block, after the nerve block, and 4 weeks after botulinum toxin injection. Outcomes were ankle dorsiflexion passive range of motion of the affected side, and calf muscle spasticity, measured with the modified Ashworth scale and the Tardieu Scale. Results: Significant improvements were measured after diagnostic nerve block and botulinum toxin injection compared with the baseline condition. Diagnostic nerve block led to significantly greater improvements in all outcomes than botulinum toxin injection. Conclusion: This study confirmed diagnostic nerve block as a valuable screening tool in deciding whether to treat spastic equinovarus with botulinum toxin. However, the results support the evidence that diagnostic nerve block results in a greater reduction in muscle overactivity than does botulinum toxin type A in patients with spastic equinovarus due to stroke

Dependency of lower limb joint reaction forces on femoral version

Background Musculoskeletal (MSK) models based on literature data are meant to represent a generic anatomy and are a popular tool employed by biomechanists to estimate the internal loads occurring in the lower limb joints, such as joint reaction forces (JRFs). However, since these models are normally just linearly scaled to an individual’s anthropometry, it is unclear how their estimations would be affected by the personalization of key features of the MSK anatomy, one of which is the femoral version angle. Research Question How are the lower limb JRF magnitudes computed through a generic MSK model affected by changes in the femoral version? Methods We developed a bone-deformation tool in MATLAB (shared at https://simtk.org/projects/bone_deformity) and used it to create a set of seven OpenSim models spanning from 2˚ femoral retroversion to 40˚ anteversion. We used these models to simulate the gait of an elderly individual with an instrumented prosthesis implanted at their knee joint (5th Grand Challenge dataset) and quantified both the changes in JRFs magnitude due to varying the skeletal anatomy and their accuracy against the correspondent in vivo measurements at the knee joint. Results Hip and knee JRF magnitudes were affected by the femoral version with variations from the unmodified generic model up to 17.9 ± 4.5% at the hip and 43.4 ± 27.1% at the knee joint. The ankle joint was unaffected by the femoral geometry. The MSK models providing the most accurate knee JRFs (root mean squared error: 0.370 ± 0.068 body weight, coefficient of determination: 0.757 ± 0.104, peak error range: 0.09−0.42 body weight) were those with femoral anteversion angle closer to that measured on the segmented bone of the individual. Significance Femoral version substantially affects hip and knee JRFs estimated with generic MSK models, suggesting that personalizing key MSK anatomical features might be necessary for accurate estimation of JRFs with these models

Protocol for a Systematic Review on the Effectiveness of Interventions to Reduce Exposure to Occupational Solar UltraViolet Radiation (UVR) Among Outdoor Workers

Background: Solar UltraViolet Radiation (UVR) is considered the most relevant occupational carcinogenic exposure in terms of the number of workers exposed (i.e., outdoor workers) and UVR-induced skin cancers are among the most frequent types of occupational cancers worldwide. This review aims to collect and evaluate all the available preventive interventions conducted on outdoor workers to reduce their solar UVR related risk, with the final purpose of reducing the burden of occupational skin cancers for outdoor workers. Methods: We will search the following databases for peer-reviewed original research published: MEDLINE (through PubMed), Scopus, and EMBASE. We will include only interventional studies, both randomized and non-randomized, with an adequate comparison group, therefore excluding cross-sectional studies, as well as case-reports/series, reviews, and letters/comments. The systematic review will adhere to the “Preferred Reporting Items for Systematic reviews and Meta-Analyses” (PRISMA) guidelines for reporting systematic reviews. After the literature search, studies to be included will be independently reviewed by two Authors, first based on title and abstract, then based on the full text, according to the inclusion criteria. Conflicts will be solved by a third Author. Two authors will independently extract the required data from included studies and perform quality assessment according to the relevant domain for Risk of Bias assessment proposed by the Cochrane collaboration group. In case of sufficient homogeneity of interventions and outcomes evaluated, results from subgroups of studies will be pooled together in a meta-analysis. Discussion: Following the principles for the evaluation of interventions for cancer prevention established by the International Agency for Research on Cancer, this systematic review will investigate the effectiveness of the interventions, and consequently it will provide reliable indications for the actual reduction of skin cancer incidence in outdoor workers