Bioinspired Technologies to Connect Musculoskeletal Mechanobiology to the Person for Training and Rehabilitation

The future of in-field sports biomechanics: wearables plus modelling compute real-time in vivo tissue loading to prevent and repair musculoskeletal injuries

This paper explores the use of biomechanics in identifying the mechanistic causes of musculoskeletal tissue injury and degeneration. It appraises how biomechanics has been used to develop training programmes aiming to maintain or recover tissue health. Tissue health depends on the functional mechanical environment experienced by tissues during daily and rehabilitation activities. These environments are the result of the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing musculoskeletal tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and deformation), which may be enabled by appropriate real-time biofeedback. Recent research shows that biofeedback technologies may increase their quality and effectiveness by integrating a personalised neuromusculoskeletal modelling driven by real-time motion capture and medical imaging. Model personalisation is crucial in obtaining physically and physiologically valid predictions of tissue biomechanics. Model real-time execution is crucial and achieved by code optimisation and artificial intelligence methods. Furthermore, recent work has also shown that laboratory-based motion capture biomechanical measurements and modelling can be performed outside the laboratory with wearable sensors and artificial intelligence. The next stage is to combine these technologies into well-designed easy to use products to guide training to maintain or recover tissue health in the real-world.

Real-Time Calibration-Free Musculotendon Kinematics for Neuromusculoskeletal Models

Neuromusculoskeletal (NMS) models enable non-invasive estimation of clinically important internal biomechanics. A critical part of NMS modelling is the estimation of musculotendon kinematics, which comprise musculotendon unit lengths, moment arms, and lines of action. Musculotendon kinematics, which are partially dependent on joint angles, define the non-linear mapping of muscle forces to joint moments and contact forces. Currently, real-time computation of musculotendon kinematics requires creation of a per-individual surrogate model. The computational speed and accuracy of these surrogates degrade with increasing number of coordinates. We developed a feed-forward neural network that completely encodes musculotendon kinematics of a target model across a wide anthropometric range, enabling accurate real-time estimates of musculotendon kinematics without need for a priori creation of a per-individual surrogate model. Compared to reference, the neural network had median normalized errors ~0.1% for musculotendon lengths, <0.4% for moment arms, and <0.10° for line of action orientations. The neural network was employed within an electromyogram-informed NMS model to calculate hip contact forces, demonstrating little difference (normalized root mean square error 1.23±0.15 %) compared to using reference musculotendon kinematics. Finally, execution time was <0.04 ms per frame and constant for increasing number of model coordinates. Our approach to musculoskeletal kinematics may facilitate deployment of complex real-time NMS modelling in computer vision or wearable sensors applications to realize biomechanics monitoring, rehabilitation, and disease management outside the research laboratory.

Prediction of Achilles Tendon Force During Common Motor Tasks From Markerless Video

Remodeling of the Achilles tendon (AT) is partly driven by its mechanical environment. AT force can be estimated with neuromusculoskeletal (NMSK) modeling; however, the complex experimental setup required to perform the analyses confines use to the laboratory. We developed task-specific long short-term memory (LSTM) neural networks that employ markerless video data to predict the AT force during walking, running, countermovement jump, single-leg landing, and single-leg heel rise. The task-specific LSTM models were trained on pose estimation keypoints and corresponding AT force data from 16 subjects, calculated via an established NMSK modeling pipeline, and cross-validated using a leave-one-subject-out approach. As proof-of-concept, new motion data of one participant was collected with two smartphones and used to predict AT forces. The task-specific LSTM models predicted the time-series AT force using synthesized pose estimation data with root mean square error (RMSE) ≤ 526 N, normalized RMSE (nRMSE) ≤ 0.21 , R 2 ≥ 0.81 . Walking task resulted the most accurate with RMSE = 189±62 N; nRMSE = 0.11±0.03 , R 2 = 0.92±0.04 . AT force predicted with smartphones video data was physiologically plausible, agreeing in timing and magnitude with established force profiles. This study demonstrated the feasibility of using low-cost solutions to deploy complex biomechanical analyses outside the laboratory.

Hip contact forces can be predicted with a neural network using only synthesised key points and electromyography in people with hip osteoarthritis

OBJECTIVE

To develop and validate a neural network to estimate hip contact forces (HCF), and lower body kinematics and kinetics during walking in individuals with hip osteoarthritis (OA) using synthesised anatomical key points and electromyography. To assess the capability of the neural network to detect directional changes in HCF resulting from prescribed gait modifications.

DESIGN

A calibrated electromyography-informed neuromusculoskeletal model was used to compute lower body joint angles, moments, and HCF for 17 participants with mild-to-moderate hip OA. Anatomical key points (e.g., joint centres) were synthesised from marker trajectories and augmented with bias and noise expected from computer vision-based pose estimation systems. Temporal convolutional and long short-term memory neural networks (NN) were trained using leave-one-subject-out validation to predict neuromusculoskeletal modelling outputs from the synthesised key points and measured electromyography data from 5 hip-spanning muscles.

RESULTS

HCF was predicted with an average error of 13.4 ± 7.1% of peak force. Joint angles and moments were predicted with an average root-mean-square-error of 5.3 degrees and 0.10 Nm/kg, respectively. The NN could detect changes in peak HCF that occur due to gait modifications with good agreement with neuromusculoskeletal modelling (r2 = 0.72) and a minimum detectable change of 9.5%.

CONCLUSION

The developed neural network predicted HCF and lower body joint angles and moments in individuals with hip OA using noisy synthesised key point locations with acceptable errors. Changes in HCF magnitude due to gait modifications were predicted with high accuracy. These findings have important implications for implementation of load-modification based gait retraining interventions for people with hip OA in a natural environment (i.e., home, clinic).

Joint contact forces during semi-recumbent seated cycling

Semi-recumbent cycling performed from a wheelchair is a popular rehabilitation exercise following spinal cord injury (SCI) and is often paired with functional electrical stimulation. However, biomechanical assessment of this cycling modality is lacking, even in unimpaired populations, hindering the development of personalised and safe rehabilitation programs for those with SCI. This study developed a computational pipeline to determine lower limb kinematics, kinetics, and joint contact forces (JCF) in 11 unimpaired participants during voluntary semi-recumbent cycling using a rehabilitation ergometer. Two cadences (40 and 60 revolutions per minute) and three crank powers (15 W, 30 W, and 45 W) were assessed. A rigid body model of a rehabilitation ergometer was combined with a calibrated electromyogram-informed neuromusculoskeletal model to determine JCF at the hip, knee, and ankle. Joint excursions remained consistent across all cadence and powers, but joint moments and JCF differed between 40 and 60 revolutions per minute, with peak JCF force significantly greater at 40 compared to 60 revolutions per minute for all crank powers. Poor correlations were found between mean crank power and peak JCF across all joints. This study provides foundation data and computational methods to enable further evaluation and optimisation of semi-recumbent cycling for application in rehabilitation after SCI and other neurological disorders.

Continuous Motion Intention Prediction Using sEMG for Upper-Limb Rehabilitation: A Systematic Review of Model-Based and Model-Free Approaches

Upper limb functional impairments persisting after stroke significantly affect patients' quality of life. Precise adjustment of robotic assistance levels based on patients' motion intentions using sEMG signals is crucial for active rehabilitation. This paper systematically reviews studies on continuous prediction of upper limb single joints and multi-joint combinations motion intention using Model-Based (MB) and Model-Free (MF) approaches over the past decade, based on 186 relevant studies screened from six major electronic databases. The findings indicate ongoing challenges in terms of subject composition, algorithm robustness and generalization, and algorithm feasibility for practical applications. Moreover, it suggests integrating the strengths of both MB and MF approaches to improve existing algorithms. Therefore, future research should further explore personalized MB-MF combination methods incorporating deep learning, attention mechanisms, muscle synergy features, motor unit features, and closed-loop feedback to achieve precise, real-time, and long-duration prediction of multi-joint complex movements, while further refining the transfer learning strategy for rapid algorithm deployment across days and subjects. Overall, this review summarizes the current research status, significant findings, and challenges, aiming to inspire future research on predicting upper limb motion intentions based on sEMG.

Osteoarthritis year in review 2023: Biomechanics

Biomechanics plays a significant yet complex role in osteoarthritis (OA) onset and progression. Identifying alterations in biomechanical factors and their complex interactions is critical for gaining new insights into OA pathophysiology and identification of clearly defined and modifiable mechanical treatment targets. This review synthesized biomechanics studies from March 2022 to April 2023, from which three themes relating to human gait emerged: (1) new insights into the pathogenesis of OA using computational modeling and machine learning, (2) technology-enhanced biomechanical interventions for OA, and (3) out-of-lab biomechanical assessments of OA. We further highlighted future-focused areas which may continue to advance the field of biomechanics in OA, with a particular emphasis on exploiting technology to understand and treat biomechanical mechanisms of OA outside the laboratory. The breadth of studies included in this review highlights the complex role of biomechanics in OA and showcase numerous innovative and outstanding contributions to the field. Exciting cross-disciplinary efforts integrating computational modeling, mobile sensors, and machine learning methods show great promise for streamlining in vivo multi-scale biomechanics workflows and are expected to underpin future breakthroughs in the understanding and treatment of biomechanics in OA.

Triceps surae muscle forces during dynamic exercises in patients with Achilles tendinopathy: A cross-sectional study

PURPOSE

The aim of this study was to investigate the individual triceps surae muscle forces during the execution of six different functional movements and rehabilitation exercises in patients with Achilles tendinopathy compared to a control group.

METHODS

Triceps surae muscle forces of 15 participants with Achilles tendinopathy (AT) and 15 healthy controls were estimated through a combination of experimental data and musculo-skeletal modeling. Three-dimensional motion capture and force plates were used to collect the ankle and knee joint angles and moments during three functional movements (walking, heel walking, and toe walking) and three rehabilitation exercises (bilateral heel drop, unilateral heel drop with extended knee and with flexed knee). A dynamic optimization method was used to obtain the modeled triceps surae muscle forces. Force-sharing strategies were calculated at the peak triceps surae muscle force and compared between groups.

RESULTS

Lower peak triceps surae forces were obtained for the AT group during dynamic exercises. Across all exercises, the average contribution of the soleus (SOL) to the total triceps surae muscle force was the largest (60.83 ± 13.89% [AT] > 56.90 ± 16.18% [healthy]), followed by the gastrocnemius medialis (29.87 ± 10.67% [AT] < 32.19 ± 12.90% [healthy]) and the gastrocnemius lateralis (9.30 ± 4.31% [AT] < 10.91 ± 4.66% [healthy]). The triceps surae force-sharing strategy was different for the toe walking, heel walking, and the bilateral and unilateral heel drop with extended knee.

CONCLUSION

This study provides evidence for altered triceps surae muscle force-sharing strategies during dynamic tasks in patients with AT. The influence of altered muscle force-sharing on the subtendon nonuniformity and/or the tendon loading should be explored in future work.

Electromyography-informed musculoskeletal modeling provides new insight into hand tendon forces during tennis forehand

Lateral epicondylitis, also known as tennis elbow, is a major health issue among tennis players. This musculo-skeletal disorder affects hand extensor tendons, results in substantial pain and impairments for sporting and everyday activities and requires several weeks of recovery. Unfortunately, prevention remains limited by the lack of data regarding biomechanical risk factors, especially because in vivo evaluation of hand tendon forces remains challenging. Electromyography-informed musculo-skeletal modeling is a noninvasive approach to provide physiological estimation of tendon forces based on motion capture and electromyography but was never applied to study hand tendon loading during tennis playing. The objective of this study was to develop such electromyography-informed musculo-skeletal model to provide new insight into hand tendon loading in tennis players. The model was tested with three-dimensional kinematics and electromyography data of two players performing forehand drives at two-shot speeds and with three rackets. Muscle forces increased with shot speed but were moderately affected by racket properties. Wrist prime extensors withstood the highest forces, but their relative implication compared to flexors depended on the player-specific grip force and racket motion strategy. When normalizing wrist extensor forces by shot speed and grip strength, up to threefold differences were observed between players, suggesting that gesture technique, for example, grip position or joint motion coordination, could play a role in the overloading of wrist extensor tendons. This study provided a new methodology for in situ analysis of hand biomechanical loadings during tennis gesture and shed a new light on lateral epicondylitis risk factors.

A Digital Twin Framework for Precision Neuromusculoskeletal Health Care: Extension Upon Industrial Standards

There is a powerful global trend toward deeper integration of digital twins into modern life driven by Industry 4.0 and 5.0. Defense, agriculture, engineering, manufacturing, and urban planning sectors have thoroughly incorporated digital twins to great benefit across their respective product lifecycles. Despite clear benefits, a digital twin framework for health and medical sectors is yet to emerge. This paper proposes a digital twin framework for precision neuromusculoskeletal health care. We build upon the International Standards Organization framework for digital twins for manufacturing by presenting best available computational models within a digital twin framework for clinical application. We map a use case for modeling Achilles tendon mechanobiology, highlighting how current modeling practices align with our proposed digital twin framework. Similarly, we map a use case for advanced neurorehabilitation technology, highlighting the role of a digital twin in control of systems where human and machine are interfaced. Future work must now focus on creating an informatic representation to govern how digital data are passed to, from, and within the digital twin, as well as specific standards to declare which measurement systems and modeling methods are acceptable to move toward widespread use of the digital twin framework for precision neuromusculoskeletal health care.

Depth camera-based model for studying the effects of muscle loading on distal radius fracture healing

BACKGROUND

Distal radius fractures (DRFs) treated with volar locking plates (VLPs) allows early rehabilitation exercises favourable to fracture recovery. However, the role of rehabilitation exercises induced muscle forces on the biomechanical microenvironment at the fracture site remains to be fully explored. The purpose of this study is to investigate the effects of muscle forces on DRF healing by developing a depth camera-based fracture healing model.

METHOD

First, the rehabilitation-related hand motions were captured by a depth camera system. A macro-musculoskeletal model is then developed to analyse the data captured by the system for estimating hand muscle and joint reaction forces which are used as inputs for our previously developed DRF model to predict the tissue differentiation patterns at the fracture site. Finally, the effect of different wrist motions (e.g., from 60° of extension to 60° of flexion) on the DRF healing outcomes will be studied.

RESULTS

Muscle and joint reaction forces in hands which are highly dependent on hand motions could significantly affect DRF healing through imposed compressive and bending forces at the fracture site. There is an optimal range of wrist motion (i.e., between 40° of extension and 40° of flexion) which could promote mechanical stimuli governed healing while mitigating the risk of bony non-union due to excessive movement at the fracture site.

CONCLUSION

The developed depth camera-based fracture healing model can accurately predict the influence of muscle loading induced by rehabilitation exercises in distal radius fracture healing outcomes. The outcomes from this study could potentially assist osteopathic surgeons in designing effective post-operative rehabilitation strategies for DRF patients.

EMG-Informed Neuromusculoskeletal Modelling Estimates Muscle Forces and Joint Moments During Electrical Stimulation

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.

Maintaining soldier musculoskeletal health using personalised digital humans, wearables and/or computer vision

OBJECTIVES

The physical demands of military service place soldiers at risk of musculoskeletal injuries and are major concerns for military capability. This paper outlines the development new training technologies to prevent and manage these injuries.

DESIGN

Narrative review.

METHODS

Technologies suitable for integration into next-generation training devices were examined. We considered the capability of technologies to target tissue level mechanics, provide appropriate real-time feedback, and their useability in-the-field.

RESULTS

Musculoskeletal tissues' health depends on their functional mechanical environment experienced in military activities, training and rehabilitation. These environments result from the interactions between tissue motion, loading, biology, and morphology. Maintaining health of and/or repairing joint tissues requires targeting the "ideal" in vivo tissue mechanics (i.e., loading and strain), which may be enabled by real-time biofeedback. Recent research has shown that these biofeedback technologies are possible by integrating a patient's personalised digital twin and wireless wearable devices. Personalised digital twins are personalised neuromusculoskeletal rigid body and finite element models that work in real-time by code optimisation and artificial intelligence. Model personalisation is crucial in obtaining physically and physiologically valid predictions.

CONCLUSIONS

Recent work has shown that laboratory-quality biomechanical measurements and modelling can be performed outside the laboratory with a small number of wearable sensors or computer vision methods. The next stage is to combine these technologies into well-designed easy to use products.

Can genetics guide exercise prescriptions in osteoarthritis?

Osteoarthritis (OA) is the most common form of arthritis and has a multifactorial etiology. Current management for OA focuses on minimizing pain and functional loss, typically involving pharmacological, physical, psychosocial, and mind-body interventions. However, there remain challenges in determining which patients will benefit most from which interventions. Although exercise-based interventions are recommended as first-line treatments and are known to be beneficial for managing both the disease and illness of OA, the optimal exercise “prescription” is unknown, due in part to our limited understanding of the precise mechanisms underlying its action. Here we present our perspective on the potential role of genetics in guiding exercise prescription for persons with OA. We describe key publications in the areas of exercise and OA, genetics and OA, and exercise and genetics, and point to a paucity of knowledge at the intersection of exercise, genetics, and OA. We suggest there is emerging evidence to support the use of genetics and epigenetics to explain the beneficial effects of exercise for OA. We identify missing links in the existing research relating to exercise, genetics, and OA, and highlight epigenetics as a promising mechanism through which environmental exposures such as exercise may impact OA outcomes. We anticipate future studies will improve our understanding of how genetic and epigenetic factors mediate exercise-based interventions to support implementation and ultimately improve OA patient care.

Implantable biosensors for musculoskeletal health

PURPOSE

A healthy musculoskeletal system requires complex functional integration of bone, muscle, cartilage, and connective tissues responsible for bodily support, motion, and the protection of vital organs. Conditions or injuries to musculoskeeltal tissues can devastate an individual's quality of life. Some conditions that are particularly disabling include severe bone and muscle injuries to the extremities and amputations resulting from unmanageable musculoskeletal conditions or injuries. Monitoring and managing musculoskeletal health is intricate because of the complex mechanobiology of these interconnected tissues.

METHODS

For this article, we reviewed literature on implantable biosensors related to clinical data of the musculoskeletal system, therapeutics for complex bone injuries, and osseointegrated prosthetics as example applications.

RESULTS

As a result, a brief summary of biosensors technologies is provided along with review of noteworthy biosensors and future developments needed to fully realize the translational benefit of biosensors for musculoskeletal health.

CONCLUSIONS

Novel implantable biosensors capable of tracking biophysical parameters in vivo are highly relevant to musculoskeletal health because of their ability to collect clinical data relevant to medical decisions, complex trauma treatment, and the performance of osseointegrated prostheses.

A muscle synergy-based method to estimate muscle activation patterns of children with cerebral palsy using data collected from typically developing children

Preparing children with cerebral palsy prior to gait analysis may be a challenging and time-intensive task, especially when large number of sensors are involved. Collecting minimum number of electromyograms (EMG) and yet providing adequate information for clinical assessment might improve clinical workflow. The main goal of this study was to develop a method to estimate activation patterns of lower limb muscles from EMG measured from a small set of muscles in children with cerebral palsy. We developed and implemented a muscle synergy extrapolation method able to estimate the full set of lower limbs muscle activation patterns from only three experimentally measured EMG. Specifically, we extracted a set of hybrid muscle synergies from muscle activation patterns of children with cerebral palsy and their healthy counterparts. Next, those muscle synergies were used to estimate activation patterns of muscles, which were not initially measured in children with cerebral palsy. Two best combinations with three (medial gastrocnemius, semi membranous, and vastus lateralis) and four (lateral gastrocnemius, semi membranous, sartorius, and vastus medialis) experimental EMG were able to estimate the full set of 10 muscle activation patterns with mean (± standard deviation) variance accounted for of 79.93 (± 9.64)% and 79.15 (± 6.40)%, respectively, using only three muscle synergies. In conclusion, muscle activation patterns of unmeasured muscles in children with cerebral palsy can be estimated from EMG measured from three to four muscles using our muscle synergy extrapolation method. In the future, the proposed muscle synergy-based method could be employed in gait clinics to minimise the required preparation time.

Free Achilles tendon strain during selected rehabilitation, locomotor, jumping, and landing tasks

A better understanding of the strains experienced by the Achilles tendon during commonly prescribed exercises and locomotor tasks is needed to improve efficacy of Achilles tendon training and rehabilitation programs. The aim of this study was to estimate in vivo free Achilles tendon strain during selected rehabilitation, locomotor, jumping, and landing tasks. Sixteen trained runners with no symptoms of Achilles tendinopathy participated in this study. Personalised free Achilles tendon moment arm and force-strain curve were obtained from imaging data and used in conjunction with motion capture and surface electromyography to estimate free Achilles tendon strain using electromyogram-informed neuromusculoskeletal modelling. There was a strong correspondence between Achilles tendon force estimates from the present study and experimental data reported in the literature (R² > 0.85). The average tendon strain was highest for maximal hop landing (8.8±1.6%), lowest for walking at 1.4 m/s (3.1±0.8%) and increased with locomotor speed during running (run 3.0 m/s: 6.5±1.6%; run 5.0 m/s: 7.9±1.7%) and during heel rise exercise with added mass (BW: 5.8±1.3%; 1.2 BW: 6.9±1.7%). The peak tendon strain was highest during running (5 m/s: 13.7±2.5%) and lowest during walking (1.4 m/s: 7±1.8%). Overall findings provide a preliminary evidence base for exercise selection to maximise anabolic tendon remodelling during training and rehabilitation of the Achilles tendon.

Biofeedback: e-health prediction based on evolving fuzzy neural network and wearable technologies

Recent advances in wearable microelectronics and new neural networks paradigms, capable to evolve and learn online such as the Evolving Fuzzy Neural Network (EFuNN), enable the deploy of biofeedback-based applications. The missed physiologic response could be recovered by measuring uninvasively the vital signs such as the heart rate, the bio impedance, the body temperature, the motion activity, the blood pressure, the blood oxygenation and the respiration rate. Then, the prediction could be performed applying the evolving ANN paradigms. The simulation of a wearable biofeedback system has been executed applying the Evolving Fuzzy Neural Network (EFuNN) paradigm for prediction. An highly integrated wearable microelectronic device for uninvasively vital signs measurement has been deployed. Simulation results demonstrate that biofeedback control model could be an effective reference design that enables short and long-term e-health prediction. The biofeedback framework was been then defined.

Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation

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.

STRESS-STRAIN DISTRIBUTION IN THE MODEL OF RETROCALCANEAL BURSITIS BY USING HEEL-ELEVATION INSOLES

The aim of this study is the analysis of the equivalent stress on the rear foot structures in retrocalcaneal bursitis, when using heel-elevation insoles of different heights (10 mm and 20 mm). Methods – mathematical calculations of the Achilles force required in the heel-off of the gait stance phase in the conditions of lifting the heel by 10 mm and 20 mm. A 3D-simulation foot model with an enlarged retrocalcaneal bursa was created. The analysis was carried out by the finite element method to calculate and study the stress and strain in the rear foot structures. Results. When using a 10.0 mm height heel-elevation insole, the calf muscle strength, which must be applied to the heel-off of the gait stance phase, was 19.0 % less than without support and 26.8 % less in 20.0 mm insole. Accordingly, analyzing the simulation results in terms of von-Mises stress, the maximum stress observed on the Achilles tendon decreases by 20.0 % and by 30.0 %. The total deformations maximum in the model when using heel-elevation insoles decreased up to 18.1 % and they were localized not in the tendon, but in the bone structures of subtalar joint. The maximum values of the total deformation of the model in the case of 10.0 mm and 20.0 mm heel-elevation insoles were 91.67 mm (–20.2 %) and 80.04 mm (–30.3 %), respectively, compared 114.92 mm in the absence of insoles. When using insole with a height of 10.0 mm, the stress in the retrocalcaneal bursa decreased by 20.0 % and was equal to 14.92 MPa compared to 18.66 MPa, and when using a 20.0 mm insoles - by 30.0 %. Conclusions. It was found that when using 10.0–20.0 mm heel-elevation insoles, the stress distribution in the rear foot structures was significantly reduced by an average of 20.0-30.0 % and correlated with the height of the insoles.

Changes in the Plantar Flexion Torque of the Ankle and in the Morphological Characteristics and Mechanical Properties of the Achilles Tendon after 12-Week Gait Retraining

Purpose: Although the Achilles tendon (AT) is the largest and strongest tendon, it remains one of the most vulnerable tendons among elite and recreational runners. The present study aims to explore the effects of 12-week gait retraining (GR) on the plantar flexion torque of the ankle and the morphological and mechanical properties of the AT. Methods: Thirty-four healthy male recreational runners (habitual rearfoot strikers) who never tried to run in minimal shoes were recruited, and the intervention was completed (20 in the GR group vs. 14 in the control (CON) group). The participants in the GR group were asked to run in minimal shoes (INOV-8 BARE-XF 210) provided by the investigators with forefoot strike patterns during the progressive 12-week GR. Meanwhile, the participants in the CON group were instructed to run in their own running shoes, which they were familiar with, with original foot strike patterns and intensities. The morphological properties of the AT, namely, length and cross-sectional area (CSA), were obtained by using an ultrasound device. A dynamometer was utilized simultaneously to measure and calculate the plantar flexion torque of the ankle, the rate of torque development, the peak force of the AT, and the stress and strain of the AT. Results: After 12-week GR, the following results were obtained: (1) A significant time effect in the peak ankle plantarflexion torque was observed (p = 0.005), showing a 27.5% increase in the GR group; (2) A significant group effect in the CSA was observed (p = 0.027), specifically, the increase in CSA was significantly larger in the GR group than the CON group; (3) A significant time effect in the peak AT force was observed (p = 0.005), showing a 27.5% increase in the GR group. Conclusion: The effect of 12 weeks of GR is an increase in AT CSA, plantar flexor muscle strength of the ankle, and peak AT force during a maximal voluntary isometric contraction test. These changes in AT morphology and function could be positive for tendon health and could prevent future AT injury.

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

Musculoskeletal tissues, including tendons, are sensitive to their mechanical environment, with both excessive and insufficient loading resulting in reduced tissue strength. Tendons appear to be particularly sensitive to mechanical strain magnitude, and there appears to be an optimal range of tendon strain that results in the greatest positive tendon adaptation. At present, there are no tools that allow localized tendon strain to be measured or estimated in training or a clinical environment. In this paper, we first review the current literature regarding Achilles tendon adaptation, providing an overview of the individual technologies that so far have been used in isolation to understand in vivo Achilles tendon mechanics, including 3D tendon imaging, motion capture, personalized neuromusculoskeletal rigid body models, and finite element models. We then describe how these technologies can be integrated in a novel framework to provide real-time feedback of localized Achilles tendon strain during dynamic motor tasks. In a proof of concept application, Achilles tendon localized strains were calculated in real-time for a single subject during walking, single leg hopping, and eccentric heel drop. Data was processed at 250 Hz and streamed on a smartphone for visualization. Achilles tendon peak localized strains ranged from ∼3 to ∼11% for walking, ∼5 to ∼15% during single leg hop, and ∼2 to ∼9% during single eccentric leg heel drop, overall showing large strain variation within the tendon. Our integrated framework connects, across size scales, knowledge from isolated tendons and whole-body biomechanics, and offers a new approach to Achilles tendon rehabilitation and training. A key feature is personalization of model components, such as tendon geometry, material properties, muscle geometry, muscle-tendon paths, moment arms, muscle activation, and movement patterns, all of which have the potential to affect tendon strain estimates. Model personalization is important because tendon strain can differ substantially between individuals performing the same exercise due to inter-individual differences in these model components.

Individuals with mild-to-moderate hip osteoarthritis walk with lower hip joint contact forces despite higher levels of muscle co-contraction compared to healthy individuals

OBJECTIVE

To compare hip joint contact forces (HJCF), hip muscle forces, and hip muscle co-contraction levels between individuals with mild-to-moderate hip osteoarthritis (OA) and healthy controls during walking.

DESIGN

Eighteen participants with mild-to-moderate hip OA and 23 healthy controls walked at a self-selected speed while motion capture and electromyographic data were synchronously collected. HJCF were computed using a calibrated electromyography-informed neuromusculoskeletal model. Hip joint contact forces, muscle forces, and co-contraction indices for flexor/extensor and adductor/abductor muscle groups were compared between groups using independent sample t-tests (P < 0.05).

RESULTS

There was no between-group difference in self-selected walking speed. On average, participants with hip OA walked with 11% lower first peak (mean difference 235 [95% confidence interval (CI) 57-413] N) and 22% lower second peak (mean difference 574 [95%CI 304-844] N) HJCF compared to controls. Hip muscle forces were also significantly lower in the hip OA compared to control group at first (mean difference 224 [95%CI 66-382] N) and second (mean difference 782 [95%CI 399-1164] N) peak HJCF. Participants with hip OA exhibited higher levels of hip muscle co-contraction in both flexor/extensor and adductor/abductor muscle groups. Consistent with existing literature, hip joint angles (extension, adduction) and external moments (flexion, extension, adduction) were lower in hip OA compared to controls.

CONCLUSION

Lower HJCF were detected in mild-to-moderate hip OA, primarily due to lower hip muscle force production, and despite higher levels of hip muscle co-contraction. Findings suggest that lower loading of the hip joint during walking is a feature of mild-to-moderate hip OA, which could have implications for the pathogenesis of hip OA and/or disease progression.

Modelling Human Locomotion to Inform Exercise Prescription for Osteoporosis

PURPOSE OF REVIEW

We review the literature on hip fracture mechanics and models of hip strain during exercise to postulate the exercise regimen for best promoting hip strength.

RECENT FINDINGS

The superior neck is a common location for hip fracture and a relevant exercise target for osteoporosis. Current modelling studies showed that fast walking and stair ambulation, but not necessarily running, optimally load the femoral neck and therefore theoretically would mitigate the natural age-related bone decline, being easily integrated into routine daily activity. High intensity jumps and hopping have been shown to promote anabolic response by inducing high strain in the superior anterior neck. Multidirectional exercises may cause beneficial non-habitual strain patterns across the entire femoral neck. Resistance knee flexion and hip extension exercises can induce high strain in the superior neck when performed using maximal resistance loadings in the average population. Exercise can stimulate an anabolic response of the femoral neck either by causing higher than normal bone strain over the entire hip region or by causing bending of the neck and localized strain in the superior cortex. Digital technologies have enabled studying interdependences between anatomy, bone distribution, exercise, strain and metabolism and may soon enable personalized prescription of exercise for optimal hip strength.

Use of Wearables: Tracking and Retraining in Endurance Runners

Wearable devices are ubiquitous among runners, coaches, and clinicians with an ever-increasing number of devices coming on the market. In place of gold standard measures in the laboratory, these devices attempt to provide a surrogate means to track running biomechanics outdoors. This review provides an update on recent literature in the field of wearable devices in runners, with an emphasis on criterion validity and usefulness in the coaching and rehabilitation of runners. Our review suggests that while enthusiasm should be tempered, there is still much for runners to gain with wearables. Overall, our review finds evidence supporting the use of wearables to improve running performance, track global training loads applied to the runner, and provide real-time feedback on running speed and run cadence. Case studies illustrate the use of wearables for the purposes of performance and rehabilitation.

Neuromusculoskeletal Modeling-Based Prostheses for Recovery After Spinal Cord Injury

Concurrent stimulation and reinforcement of motor and sensory pathways has been proposed as an effective approach to restoring function after developmental or acquired neurotrauma. This can be achieved by applying multimodal rehabilitation regimens, such as thought-controlled exoskeletons or epidural electrical stimulation to recover motor pattern generation in individuals with spinal cord injury (SCI). However, the human neuromusculoskeletal (NMS) system has often been oversimplified in designing rehabilitative and assistive devices. As a result, the neuromechanics of the muscles is seldom considered when modeling the relationship between electrical stimulation, mechanical assistance from exoskeletons, and final joint movement. A powerful way to enhance current neurorehabilitation is to develop the next generation prostheses incorporating personalized NMS models of patients. This strategy will enable an individual voluntary interfacing with multiple electromechanical rehabilitation devices targeting key afferent and efferent systems for functional improvement. This narrative review discusses how real-time NMS models can be integrated with finite element (FE) of musculoskeletal tissues and interface multiple assistive and robotic devices with individuals with SCI to promote neural restoration. In particular, the utility of NMS models for optimizing muscle stimulation patterns, tracking functional improvement, monitoring safety, and providing augmented feedback during exercise-based rehabilitation are discussed.

Magnetic Resonance Imaging and Freehand 3-D Ultrasound Provide Similar Estimates of Free Achilles Tendon Shape and 3-D Geometry

The purpose of this study was to assess the similarity of free Achilles tendon shape and 3-D geometry between magnetic resonance imaging (MRI) and freehand 3-D ultrasound (3-DUS) imaging methods. Fourteen elite/sub-elite middle-distance runners participated in the study. MRI and 3-DUS scans of the Achilles tendon were acquired on two separate imaging sessions, and all 3-D reconstructions were performed using identical methods. Shape similarity of free Achilles tendon reconstructed from MRI and 3-DUS data was assessed using Jaccard index, Hausdorff distance and root mean square error (RMSE). The Jaccard index, Hausdorff distance and RMSE values were 0.76 ± 0.05, 2.70 ± 0.70 and 0.61 ± 0.10 mm, respectively. The level of agreement between MRI and 3-DUS for free Achilles tendon volume, length and average cross-sectional area (CSA) was assessed using Bland-Altman analysis. Compared to MRI, freehand 3-DUS overestimated volume, length and average CSA by 30.6 ± 15.8 mm³ (1.1% ± 0.6%), 0.3 ± 0.7 mm (0.6% ± 1.9%) and 0.3 ± 1.42 mm² (0.4% ± 2.0%), respectively. The upper and lower limits of agreement between MRI and 3-DUS for volume, length and average CSA were -0.4 to 61.7 mm³ (-0.2% to 2.3%), -1.0 to 1.5 mm (-3.2% to 4.5%) and -2.5 to 3.1 mm² (-3.5% to 4.3%), respectively. There were no significant differences between imaging methods in CSA along the length of the tendon. In conclusion, MRI and freehand 3-DUS may be considered equivalent methods for estimating shape and 3-D geometry of the free Achilles tendon. These findings, together with the practical benefits of being able to assess 3-D Achilles tendon shape and geometry in a laboratory environment and under isometric loading, make 3-DUS an attractive alternative to MRI for assessing 3-D free Achilles tendon macro-structure in future studies.

Gait Mechanics in Women of the ACL-SPORTS Randomized Control Trial: Interlimb Symmetry Improves Over Time Regardless of Treatment Group

Women after anterior cruciate ligament (ACL) injury and ACL reconstruction (ACLR) are more likely than men to exhibit asymmetric movement patterns, which are associated with post-traumatic osteoarthritis. We developed the ACL specialized post-operative return-to-sports (ACL-SPORTS) randomized control trial to test the effect of strength, agility, plyometric, and secondary prevention (SAPP) training with and without perturbation training (SAPP + PERT) on gait mechanics in women after ACLR. We hypothesized that movement symmetry would improve over time across both groups but more so among the SAPP + PERT group. Thirty-nine female athletes 3-9 months after primary ACLR were randomized to SAPP or SAPP + PERT training. Biomechanical testing during overground walking occurred before (Pre-training) and after (Post-training) training and one and 2 years post-operatively. Hip and knee kinematic and kinetic variables were compared using repeated measures analysis of variance with Bonferroni corrections for post hoc comparisons (α = 0.05). There was a time by limb interaction effect (p = 0.028) for peak knee flexion angle (PKFA), the primary outcome which powered the study, characterized by smaller PKFA in the involved compared to uninvolved limbs across treatment groups at Pre-training, Post-training, and 1 year, but not 2 years. Similar findings occurred across sagittal plane knee excursions and kinetics and hip extension excursion at midstance. There were no meaningful interactions involving group. Neither SAPP nor SAPP + PERT training improved walking mechanics, which persisted 1 but not 2 years after ACLR. Statement of clinical significance: Asymmetrical movement patterns persisted long after participants achieved symmetrical strength and functional performance, suggesting more time is needed to recover fully after ACLR. © 2019 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 37:1743-1753, 2019.

A 12-month prospective exploratory study of muscle and fat characteristics in individuals with mild-to-moderate hip osteoarthritis

Background

Reductions in lower extremity muscle strength, size and quality and increased fat content have been reported in advanced hip osteoarthritis (OA). Whether these differences are also evident at earlier stages of the disease and the extent to which they might develop over time is unclear. The main purpose of this 12-month exploratory prospective study was to compare changes in muscle and fat characteristics in individuals with mild-to-moderate hip OA and healthy controls.

Methods

Fourteen individuals with mild-to-moderate symptomatic and radiographic hip OA (n = 9 unilateral; n = 5 bilateral), and 15 healthy controls similar in age and sex without symptoms or radiographic hip OA were assessed at baseline and at 12-month follow-up. Maximal voluntary isometric strength of the hip and knee muscle groups was assessed using an isokinetic dynamometer. Lower extremity lean and fat mass were assessed using dual-energy x-ray absorptiometry, and thigh muscle and fat areas and thigh muscle density were assessed using peripheral quantitative computed tomography.

Results

Knee extension (p = 0.01), hip extension (p < 0.01), hip flexion (p = 0.03), and hip abduction (p < 0.01) strength, lower extremity lean mass (p < 0.01), thigh muscle area (p = 0.03), and thigh muscle density (p < 0.01) were significantly lower in hip OA compared to controls. Hip extension (p < 0.05), hip flexion (p = 0.03), and hip abduction (p = 0.03) strength significantly declined over the follow-up period in the hip OA group.

Conclusions

Pre-existing deficits in hip muscle strength in individuals with mild-to-moderate hip OA were accentuated over 12-months, though no changes in symptoms or joint structure were observed. A longer follow-up period is required to establish whether strength deficits drive clinical and structural decline in these patients. Interventions to prevent or slow declines in strength may be relevant in the management of mild-to-moderate hip OA.

Electronic supplementary material

The online version of this article (10.1186/s12891-019-2668-z) contains supplementary material, which is available to authorized users.

Gait mechanics and tibiofemoral loading in men of the ACL-SPORTS randomized control trial

The risk for post-traumatic osteoarthritis is elevated after anterior cruciate ligament reconstruction (ACLR), and may be especially high among individuals with aberrant walking mechanics, such as medial tibiofemoral joint underloading 6 months postoperatively. Rehabilitation training programs have been proposed as one strategy to address aberrant gait mechanics. We developed the anterior cruciate ligament specialized post-operative return-to-sports (ACL-SPORTS) randomized control trial to test the effect of 10 post-operative training sessions consisting of strength, agility, plyometric, and secondary prevention exercises (SAPP) or SAPP plus perturbation (SAPP + PERT) training on gait mechanics after ACLR. A total of 40 male athletes (age 23 ± 7 years) after primary ACLR were randomized to SAPP or SAPP + PERT training and tested at three distinct, post-operative time points: 1) after impairment resolution (Pre-training); 2) following 10 training sessions (Post-training); and 3) 2 years after ACLR. Knee kinematic and kinetic variables as well as muscle and joint contact forces were calculated via inverse dynamics and a validated electromyography-informed musculoskeletal model. There were no significant improvements from Pre-training to Post-training in either intervention group. Smaller peak knee flexion angles, extension moments, extensor muscle forces, medial compartment contact forces, and tibiofemoral contact forces were present across group and time, however the magnitude of interlimb differences were generally smaller and likely not meaningful 2 years postoperatively. Neither SAPP nor SAPP + PERT training appears effective at altering gait mechanics in men in the short-term; however, meaningful gait asymmetries mostly resolved between post-training and 2 years after ACLR regardless of intervention group. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:2364-2372, 2018.

Application of quality by design for 3D printed bone prostheses and scaffolds

3D printing is an emergent manufacturing technology recently being applied in the medical field for the development of custom bone prostheses and scaffolds. However, successful industry transformation to this new design and manufacturing approach requires technology integration, concurrent multi-disciplinary collaboration, and a robust quality management framework. This latter change enabler is the focus of this study. While a number of comprehensive quality frameworks have been developed in recent decades to ensure that the manufacturing of medical devices produces reliable products, they are centred on the traditional context of standardised manufacturing techniques. The advent of 3D printing technologies and the prospects for mass customisation provides significant market opportunities, but also presents a serious challenge to regulatory bodies tasked with managing and assuring product quality and safety. Before 3D printing bone prostheses and scaffolds can gain traction, industry stakeholders, such as regulators, clients, medical practitioners, insurers, lawyers, and manufacturers, would all require a high degree of confidence that customised manufacturing can achieve the same quality outcomes as standardised manufacturing. A Quality by Design (QbD) approach to custom 3D printed prostheses can help to ensure that products are designed and manufactured correctly from the beginning without errors. This paper reports on the adaptation of the QbD approach for the development process of 3D printed custom bone prosthesis and scaffolds. This was achieved through the identification of the Critical Quality Attributes of such products, and an extensive review of different design and fabrication methods for 3D printed bone prostheses. Research outcomes include the development of a comprehensive design and fabrication process flow diagram, and categorised risks associated with the design and fabrication processes of such products. An extensive systematic literature review and post-hoc evaluation survey with experts was completed to evaluate the likely effectiveness of the herein suggested QbD framework.