Towards co-design of rehabilitation technologies: a collaborative approach to prioritize usability issues.

Introduction: Early stakeholder engagement is critical to the successful development and translation of rehabilitation technologies, a pivotal step of which is usability testing with intended end-users. To this end, several methods employ end-user feedback to identify usability and implementation issues. However, the process of prioritizing identified issues seldom leverages the knowledge and expertise of the range of stakeholders who will ultimately affect the demand and supply of a device. This paper describes a novel method to prioritize end-user feedback using transdisciplinary stakeholder consultation and address it in subsequent product development. The proposed approach was demonstrated using a case study relating to the development of a novel technology for neural recovery after spinal cord injury. Method: Feedback from five individuals with chronic spinal cord injury was collected during two-hour usability evaluation sessions with a fully functional high-fidelity system prototype. A think-aloud and semi-structured interview protocol was used with each participant to identify usability and acceptability issues relating to the system in a 3-phase approach. Phase 1 involved extracting usability issues from think-aloud and semi-structured interview data. Phase 2 involved rating the usability issues based on their significance, technical feasibility, and implementation priority by relevant internal and external stakeholders. Finally, Phase 3 involved aggregating the usability issues according to design and implementation elements to facilitate solution generation, and these solutions were then raised as action tasks for future design iterations. Results: Sixty usability issues representing nine facets of usability were rated. Eighty percent of issues were rated to be of moderate to high significance, 83% were rated as being feasible to address, and 75% were rated as addressable using existing project resources. Fifty percent of the issues were rated to be a high priority for implementation. Evaluation of the grouped issues identified 21 tasks which were mapped to the product roadmap for integration into future design iterations. Discussion: This paper presents a method for meaningful transdisciplinary stakeholder engagement in rehabilitation technology development that can extended to other projects. Alongside a worked example, we offer practical considerations for others seeking to co-develop rehabilitation technologies.

Evaluating cost function criteria in predicting healthy gait.

Accurate predictive simulations of human gait rely on optimisation criteria to solve the system's redundancy. Defining such criteria is challenging, as the objectives driving the optimization of human gait are unclear. This study evaluated how minimising various physiologically-based criteria (i.e., cost of transport, muscle activity, head stability, foot-ground impact, and knee ligament use) affects the predicted gait, and developed and evaluated a combined, weighted cost function tuned to predict healthy gait. A generic planar musculoskeletal model with 18 Hill-type muscles was actuated using a reflex-based, parameterized controller. First, the criteria were applied into the base simulation framework separately. The gait pattern predicted by minimising each criterion was compared to experimental data of healthy gait using coefficients of determination (R2) and root mean square errors (RMSE) averaged over all biomechanical variables. Second, the optimal weighted combined cost function was created through stepwise addition of the criteria. Third, performance of the resulting combined cost function was evaluated by comparing the predicted gait to a simulation that was optimised solely to track experimental data. Optimising for each of the criteria separately showed their individual contribution to distinct aspects of gait (overall R2: 0.37-0.56; RMSE: 3.47-4.63 SD). An optimally weighted combined cost function provided improved overall agreement with experimental data (overall R2: 0.72; RMSE: 2.10 SD), and its performance was close to what is maximally achievable for the underlying simulation framework. This study showed how various optimisation criteria contribute to synthesising gait and that careful weighting of them is essential in predicting healthy gait.

12 Degrees of Freedom Muscle Force Driven Fibril-Reinforced Poroviscoelastic Finite Element Model of the Knee Joint.

Accurate knowledge of the joint kinematics, kinetics, and soft tissue mechanical responses is essential in the evaluation of musculoskeletal (MS) disorders. Since in vivo measurement of these quantities requires invasive methods, musculoskeletal finite element (MSFE) models are widely used for simulations. There are, however, limitations in the current approaches. Sequentially linked MSFE models benefit from complex MS and FE models; however, MS model's outputs are independent of the FE model calculations. On the other hand, due to the computational burden, embedded (concurrent) MSFE models are limited to simple material models and cannot estimate detailed responses of the soft tissue. Thus, first we developed a MSFE model of the knee with a subject-specific MS model utilizing an embedded 12 degrees of freedom (DoFs) knee joint with elastic cartilages in which included both secondary kinematic and soft tissue deformations in the muscle force estimation (inverse dynamics). Then, a muscle-force-driven FE model with fibril-reinforced poroviscoelastic cartilages and fibril-reinforced poroelastic menisci was used in series to calculate detailed tissue mechanical responses (forward dynamics). Second, to demonstrate that our workflow improves the simulation results, outputs were compared to results from the same FE models which were driven by conventional MS models with a 1 DoF knee, with and without electromyography (EMG) assistance. The FE model driven by both the embedded and the EMG-assisted MS models estimated similar results and consistent with experiments from literature, compared to the results estimated by the FE model driven by the MS model with 1 DoF knee without EMG assistance.

Automated creation and tuning of personalised muscle paths for OpenSim musculoskeletal models of the knee joint.

Computational modelling is an invaluable tool for investigating features of human locomotion and motor control which cannot be measured except through invasive techniques. Recent research has focussed on creating personalised musculoskeletal models using population-based morphing or directly from medical imaging. Although progress has been made, robust definition of two critical model parameters remains challenging: (1) complete tibiofemoral (TF) and patellofemoral (PF) joint motions, and (2) muscle tendon unit (MTU) pathways and kinematics (i.e. lengths and moment arms). The aim of this study was to develop an automated framework, using population-based morphing approaches to create personalised musculoskeletal models, consisting of personalised bone geometries, TF and PF joint mechanisms, and MTU pathways and kinematics. Informed from medical imaging, personalised rigid body TF and PF joint mechanisms were created. Using atlas- and optimisation-based methods, personalised MTU pathways and kinematics were created with the aim of preventing MTU penetration into bones and achieving smooth MTU kinematics that follow patterns from existing literature. This framework was integrated into the Musculoskeletal Atlas Project Client software package to create and optimise models for 6 participants with incrementally increasing levels of personalisation with the aim of improving MTU kinematics and pathways. Three comparisons were made: (1) non-optimised (Model 1) and optimised models (Model 3) with generic joint mechanisms; (2) non-optimised (Model 2) and optimised models (Model 4) with personalised joint mechanisms; and (3) both optimised models (Model 3 and 4). Following optimisation, improvements were consistently shown in pattern similarity to cadaveric data in comparison (1) and (2). For comparison (3), a number of comparisons showed no significant difference between the two compared models. Importantly, optimisation did not produce statistically significantly worse results in any case.

Machine learning methods to support personalized neuromusculoskeletal modelling.

Many biomedical, orthopaedic, and industrial applications are emerging that will benefit from personalized neuromusculoskeletal models. Applications include refined diagnostics, prediction of treatment trajectories for neuromusculoskeletal diseases, in silico design, development, and testing of medical implants, and human-machine interfaces to support assistive technologies. This review proposes how physics-based simulation, combined with machine learning approaches from big data, can be used to develop high-fidelity personalized representations of the human neuromusculoskeletal system. The core neuromusculoskeletal model features requiring personalization are identified, and big data/machine learning approaches for implementation are presented together with recommendations for further research.

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.

Individual muscle contributions to tibiofemoral compressive articular loading during walking, running and sidestepping.

The tibiofemoral joint (TFJ) experiences large compressive articular contact loads during activities of daily living, caused by inertial, ligamentous, capsular, and most significantly musculotendon loads. Comparisons of relative contributions of individual muscles to TFJ contact loading between walking and sporting movements have not been previously examined. The purpose of this study was to determine relative contributions of individual lower-limb muscles to compressive articular loading of the medial and lateral TFJ during walking, running, and sidestepping. The medial and lateral compartments of the TFJ were loaded by a combination of medial and lateral muscles. During all gait tasks, the primary muscles loading the medial and lateral TFJ were the vastus medialis (VM) and vastus lateralis (VL) respectively during weight acceptance, while typically the medial gastrocnemii (MG) and lateral gastrocnemii (LG) dominated medial and lateral TFJ loading respectively during midstance and push off. Generally, the contribution of the quadriceps muscles were higher in running compared to walking, whereas gastrocnemii contributions were higher in walking compared to running. When comparing running and sidestepping, contributions to medial TFJ contact loading were generally higher during sidestepping while contributions to lateral TFJ contact loading were generally lower. These results suggests that after orthopaedic procedures, the VM, VL, MG and LG should be of particular rehabilitation focus to restore TFJ stability during dynamic gait tasks.

The influence of speed and size on avian terrestrial locomotor biomechanics: Predicting locomotion in extinct theropod dinosaurs.

How extinct, non-avian theropod dinosaurs moved is a subject of considerable interest and controversy. A better understanding of non-avian theropod locomotion can be achieved by better understanding terrestrial locomotor biomechanics in their modern descendants, birds. Despite much research on the subject, avian terrestrial locomotion remains little explored in regards to how kinematic and kinetic factors vary together with speed and body size. Here, terrestrial locomotion was investigated in twelve species of ground-dwelling bird, spanning a 1,780-fold range in body mass, across almost their entire speed range. Particular attention was devoted to the ground reaction force (GRF), the force that the feet exert upon the ground. Comparable data for the only other extant obligate, striding biped, humans, were also collected and studied. In birds, all kinematic and kinetic parameters examined changed continuously with increasing speed, while in humans all but one of those same parameters changed abruptly at the walk-run transition. This result supports previous studies that show birds to have a highly continuous locomotor repertoire compared to humans, where discrete 'walking' and 'running' gaits are not easily distinguished based on kinematic patterns alone. The influences of speed and body size on kinematic and kinetic factors in birds are developed into a set of predictive relationships that may be applied to extinct, non-avian theropods. The resulting predictive model is able to explain 79-93% of the observed variation in kinematics and 69-83% of the observed variation in GRFs, and also performs well in extrapolation tests. However, this study also found that the location of the whole-body centre of mass may exert an important influence on the nature of the GRF, and hence some caution is warranted, in lieu of further investigation.

Using step width to compare locomotor biomechanics between extinct, non-avian theropod dinosaurs and modern obligate bipeds.

How extinct, non-avian theropod dinosaurs locomoted is a subject of considerable interest, as is the manner in which it evolved on the line leading to birds. Fossil footprints provide the most direct evidence for answering these questions. In this study, step width-the mediolateral (transverse) distance between successive footfalls-was investigated with respect to speed (stride length) in non-avian theropod trackways of Late Triassic age. Comparable kinematic data were also collected for humans and 11 species of ground-dwelling birds. Permutation tests of the slope on a plot of step width against stride length showed that step width decreased continuously with increasing speed in the extinct theropods (p < 0.001), as well as the five tallest bird species studied (p < 0.01). Humans, by contrast, showed an abrupt decrease in step width at the walk-run transition. In the modern bipeds, these patterns reflect the use of either a discontinuous locomotor repertoire, characterized by distinct gaits (humans), or a continuous locomotor repertoire, where walking smoothly transitions into running (birds). The non-avian theropods are consequently inferred to have had a continuous locomotor repertoire, possibly including grounded running. Thus, features that characterize avian terrestrial locomotion had begun to evolve early in theropod history.

Osteoarthritis year in review 2016: mechanics.

Inappropriate biomechanics, namely wear-and-tear, has been long believed to be a main cause of osteoarthritis (OA). However, this view is now being re-evaluated, especially when examined alongside mechanobiology and new biomechanical studies. These are multiscale experimental and computational studies focussing on cell- and tissue-level mechanobiology through to organ- and whole-body-level biomechanics, which focuses on the biomechanical and biochemical environment of the joint tissues. This review examined papers from April 2015 to April 2016, with a focus on multiscale experimental and computational biomechanical studies of OA. Assessing the onset or progression of OA at organ- and whole-body-levels, gait analysis, medical imaging and neuromusculoskeletal modelling revealed the extent to which tissue damage changes the view of inappropriate biomechanics. Traditional gait analyses studies reported that conservative treatments can alter joint biomechanics, thereby improving pain and function experienced by those with OA. Results of animal models of OA were consistent with these human studies, showing interactions among bone, cartilage and meniscus biomechanics and the onset and/or progression OA. Going down size scales, experimental and computational studies probed the nanosize biomechanics of molecules, cells and extracellular matrix, and demonstrated how the interactions between biomechanics and morphology affect cartilage dynamic poroelastic behaviour and pathways to OA. Finally, integration of multiscale experimental data and computational models were proposed to predict cartilage extracellular matrix remodelling and the development of OA. Summarising, experimental and computational methods provided a nuanced biomechanical understanding of the sub-cellular, cellular, tissue, organ and whole-body mechanisms involved in OA.

Different visual stimuli affect body reorientation strategies during sidestepping.

Sidestepping in response to unplanned stimuli is a high-risk maneuver for anterior cruciate ligament (ACL) injuries. Yet, differences in body reorientation strategies between high- and low-level soccer players prior to sidestepping in response to quasi-game-realistic vs non-game-realistic stimuli, remain unknown. Fifteen high-level (semi-professional) and 15 low-level (amateur) soccer players responded to a quasi-game-realistic one-defender scenario (1DS) and two-defender scenario (2DS), and non-game-realistic arrow-planned condition (AP) and arrow-unplanned condition (AUNP). The AP, 1DS, 2DS to AUNP represented increasing time constraints to sidestep. Selected biomechanics from the penultimate step to foot-off were assessed using a mixed-model (stimuli × skill) ANOVA (P < 0.05). Step length decreased in the defender scenarios compared with the arrow conditions. Support foot placement increased laterally, away from mid-pelvis, with increasing temporal constraints. Greater trunk lateral flexion in the 1DS, 2DS, and AUNP has been associated with ACL injury onsets. Higher level players pushed off closer to their pelvic midline at initial foot contact in the 2DS especially. Higher level perception of game-realistic visual information could have contributed to this safer neuromuscular strategy that, when understood better, could potentially be trained in lower level players to reduce ACL injury risk associated with dangerous sidestepping postures.

Toward modeling locomotion using electromyography-informed 3D models: application to cerebral palsy.

This position paper proposes a modeling pipeline to develop clinically relevant neuromusculoskeletal models to understand and treat complex neurological disorders. Although applicable to a variety of neurological conditions, we provide direct pipeline applicative examples in the context of cerebral palsy (CP). This paper highlights technologies in: (1) patient-specific segmental rigid body models developed from magnetic resonance imaging for use in inverse kinematics and inverse dynamics pipelines; (2) efficient population-based approaches to derive skeletal models and muscle origins/insertions that are useful for population statistics and consistent creation of continuum models; (3) continuum muscle descriptions to account for complex muscle architecture including spatially varying material properties with muscle wrapping; (4) muscle and tendon properties specific to CP; and (5) neural-based electromyography-informed methods for muscle force prediction. This represents a novel modeling pipeline that couples for the first time electromyography extracted features of disrupted neuromuscular behavior with advanced numerical methods for modeling CP-specific musculoskeletal morphology and function. The translation of such pipeline to the clinical level will provide a new class of biomarkers that objectively describe the neuromusculoskeletal determinants of pathological locomotion and complement current clinical assessment techniques, which often rely on subjective judgment. WIREs Syst Biol Med 2017, 9:e1368. doi: 10.1002/wsbm.1368 For further resources related to this article, please visit the WIREs website.

Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim.

Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.

Joint kinematic calculation based on clinical direct kinematic versus inverse kinematic gait models.

Most clinical gait laboratories use the conventional gait analysis model. This model uses a computational method called Direct Kinematics (DK) to calculate joint kinematics. In contrast, musculoskeletal modelling approaches use Inverse Kinematics (IK) to obtain joint angles. IK allows additional analysis (e.g. muscle-tendon length estimates), which may provide valuable information for clinical decision-making in people with movement disorders. The twofold aims of the current study were: (1) to compare joint kinematics obtained by a clinical DK model (Vicon Plug-in-Gait) with those produced by a widely used IK model (available with the OpenSim distribution), and (2) to evaluate the difference in joint kinematics that can be solely attributed to the different computational methods (DK versus IK), anatomical models and marker sets by using MRI based models. Eight children with cerebral palsy were recruited and presented for gait and MRI data collection sessions. Differences in joint kinematics up to 13° were found between the Plug-in-Gait and the gait 2392 OpenSim model. The majority of these differences (94.4%) were attributed to differences in the anatomical models, which included different anatomical segment frames and joint constraints. Different computational methods (DK versus IK) were responsible for only 2.7% of the differences. We recommend using the same anatomical model for kinematic and musculoskeletal analysis to ensure consistency between the obtained joint angles and musculoskeletal estimates.

Changes in muscle activation following balance and technique training and a season of Australian football.

OBJECTIVES: Determine if balance and technique training implemented adjunct to 1001 male Australian football players' training influenced the activation/strength of the muscles crossing the knee during pre-planned and unplanned sidestepping. DESIGN: Randomized Control Trial. METHODS: Each Australian football player participated in either 28 weeks of balance and technique training or 'sham' training. Twenty-eight Australian football players (balance and technique training, n=12; 'sham' training, n=16) completed biomechanical testing pre-to-post training. Peak knee moments and directed co-contraction ratios in three degrees of freedom, as well as total muscle activation were calculated during pre-planned and unplanned sidestepping. RESULTS: No significant differences in muscle activation/strength were observed between the 'sham' training and balance and technique training groups. Following a season of Australian football, knee extensor (p=0.023) and semimembranosus (p=0.006) muscle activation increased during both pre-planned sidestepping and unplanned sidestepping. Following a season of Australian football, total muscle activation was 30% lower and peak valgus knee moments 80% greater (p=0.022) during unplanned sidestepping when compared with pre-planned sidestepping. CONCLUSIONS: When implemented in a community level training environment, balance and technique training was not effective in changing the activation of the muscles crossing the knee during sidestepping. Following a season of Australian football, players are better able to support both frontal and sagittal plane knee moments. When compared to pre-planned sidestepping, Australian football players may be at increased risk of anterior cruciate ligament injury during unplanned sidestepping in the latter half of an Australian football season.

Correlation between EMG-based co-activation measures and medial and lateral compartment loads of the knee during gait.

BACKGROUND: Inappropriate tibiofemoral joint contact loading during gait is thought to contribute to the development of osteoarthritis. Increased co-activation of agonist/antagonist pair of muscles during gait has commonly been observed in pathological populations and it is thought that this results in increased articular loading and subsequent risk of disease development. However, these hypotheses assume that there is a close relationship between muscle electromyography and force production, which is not necessarily the case. METHODS: This study investigated the relationship between different electromyography-based co-activation measures and articular loading during gait using an electromyography-driven model to estimate joint contact loads. FINDINGS: The results indicated that significant correlations do exist between selected electromyography-based activity measures and articular loading, but these are inconsistent and relatively low. However despite this, it was found that it may still be possible to use carefully selected measures of muscle activation in conjunction with external adduction moment measures to account for up to 50% of the variance in medial and lateral compartment loads. INTERPRETATION: The inconsistency in correlations between many electromyography-based co-activation measures and articular loading still highlights the danger of inferring joint contact loads during gait using these measures. These results suggest that some form of electromyography-driven modelling is required to estimate joint contact loads in the tibiofemoral joint.

An anterior cruciate ligament injury prevention framework: incorporating the recent evidence.

Anterior cruciate ligament (ACL) injury rates have increased by ∼50% over the last 10 years. These figures suggest that ACL focused research has not been effective in reducing injury rates among community level athletes. Training protocols designed to reduce ACL injury rates have been both effective (n = 3) and ineffective (n = 7). Although a rationale for the use of exercise to reduce ACL injuries is established, the mechanisms by which they act are relatively unknown. This article provides an injury prevention framework specific to noncontact ACL injuries and the design of prophylactic training protocols. It is also apparent that feedback within this framework is needed to determine how biomechanically relevant risk factors like peak joint loading and muscular support are influenced following training. It is by identifying these links that more effective ACL injury prevention training programs can be developed, and, in turn, lead to reduced ACL injury rates in the future.

Optimizing whole-body kinematics to minimize valgus knee loading during sidestepping: implications for ACL injury risk.

The kinematic mechanisms associated with elevated externally applied valgus knee moments during non-contact sidestepping and subsequent anterior cruciate ligament (ACL) injury risk are not well understood. To address this issue, the residual reduction algorithm (RRA) in OpenSim was used to create nine subject-specific, full-body (37 degrees of freedom) torque-driven simulations of athletic males performing unplanned sidestep (UnSS) sport tasks. The RRA was used again to produce an optimized kinematic solution with reduced peak valgus knee torques during the weight acceptance phase of stance. Pre-to-post kinematic optimization, mean peak valgus knee moments were significantly reduced by 44.2 Nm (p=0.045). Nine of a possible 37 upper and lower body kinematic changes in all three planes of motion were consistently used during the RRA to decrease peak valgus knee moments. The generalized kinematic strategy used by all nine simulations to reduce peak valgus knee moments and subsequent ACL injury risk during UnSS was to redirect the whole-body center of mass medially, towards the desired direction of travel.

Rational targeting of peroxisome proliferating activated receptor subtypes.

Peroxisome-Proliferating Activating Receptors (PPARs) have long been established as validated targets for therapeutic intervention in several important disease states, including type II diabetes and dyslipidemia. More recently, evidence has implicated novel regulatory roles for PPARs in cancer, inflammation and neurodegeneration. Although current PPAR targeting treatments exist, most are associated with undesirable and potentially life-threatening side effects. Consequent from these observations is a significant research effort into PPAR modulator drug discovery and design. In this review, the progress of PPAR modulator design over the past several years will be highlighted. Particular focus on how detailed structural information and virtual screening techniques can aid in the rational design and development of tailored next generation PPAR drug therapeutics will be discussed.