A dynamic foot model for predictive simulations of human gait reveals causal relations between foot structure and whole-body mechanics.

The unique structure of the human foot is seen as a crucial adaptation for bipedalism. The foot's arched shape enables stiffening the foot to withstand high loads when pushing off, without compromising foot flexibility. Experimental studies demonstrated that manipulating foot stiffness has considerable effects on gait. In clinical practice, altered foot structure is associated with pathological gait. Yet, experimentally manipulating individual foot properties (e.g. arch height or tendon and ligament stiffness) is hard and therefore our understanding of how foot structure influences gait mechanics is still limited. Predictive simulations are a powerful tool to explore causal relationships between musculoskeletal properties and whole-body gait. However, musculoskeletal models used in three-dimensional predictive simulations assume a rigid foot arch, limiting their use for studying how foot structure influences three-dimensional gait mechanics. Here, we developed a four-segment foot model with a longitudinal arch for use in predictive simulations. We identified three properties of the ankle-foot complex that are important to capture ankle and knee kinematics, soleus activation, and ankle power of healthy adults: (1) compliant Achilles tendon, (2) stiff heel pad, (3) the ability to stiffen the foot. The latter requires sufficient arch height and contributions of plantar fascia, and intrinsic and extrinsic foot muscles. A reduced ability to stiffen the foot results in walking patterns with reduced push-off power. Simulations based on our model also captured the effects of walking with anaesthetised intrinsic foot muscles or an insole limiting arch compression. The ability to reproduce these different experiments indicates that our foot model captures the main mechanical properties of the foot. The presented four-segment foot model is a potentially powerful tool to study the relationship between foot properties and gait mechanics and energetics in health and disease.

Combined translational and rotational perturbations of standing balance reveal contributions of reduced reciprocal inhibition to balance impairments in children with cerebral palsy.

Balance impairments are common in cerebral palsy. When balance is perturbed by backward support surface translations, children with cerebral palsy have increased co-activation of the plantar flexors and tibialis anterior muscle as compared to typically developing children. However, it is unclear whether increased muscle co-activation is a compensation strategy to improve balance control or is a consequence of reduced reciprocal inhibition. During translational perturbations, increased joint stiffness due to co-activation might aid balance control by resisting movement of the body with respect to the feet. In contrast, during rotational perturbations, increased joint stiffness will hinder balance control as it couples body to platform rotation. Therefore, we expect increased muscle co-activation in response to rotational perturbations if co-activation is caused by reduced reciprocal inhibition but not if it is merely a compensation strategy. We perturbed standing balance by combined backward translational and toe-up rotational perturbations in 20 children with cerebral palsy and 20 typically developing children. Perturbations induced forward followed by backward movement of the center of mass. We evaluated reactive muscle activity and the relation between center of mass movement and reactive muscle activity using a linear feedback model based on center of mass kinematics. In typically developing children, perturbations induced plantar flexor balance correcting muscle activity followed by tibialis anterior balance correcting muscle activity, which was driven by center of mass movement. In children with cerebral palsy, the switch from plantar flexor to tibialis anterior activity was less pronounced than in typically developing children due to increased muscle co-activation of the plantar flexors and tibialis anterior throughout the response. Our results thus suggest that a reduction in reciprocal inhibition causes muscle co-activation in reactive standing balance in children with cerebral palsy.

Muscle fibre typology affects whole-body metabolic rate during isolated muscle contractions and human locomotion.

The wide variation in muscle fibre type distribution across individuals, along with the very different energy consumption rates in slow versus fast muscle fibres, suggests that muscle fibre typology contributes to inter-individual differences in metabolic rate during exercise. However, this has been hard to demonstrate due to the gap between a single muscle fibre and full-body exercises. We investigated the isolated effect of triceps surae muscle contraction velocity on whole-body metabolic rate during cyclic contractions in individuals a priori selected for their predominantly slow (n = 11) or fast (n = 10) muscle fibre typology by means of proton magnetic resonance spectroscopy (1H-MRS). Subsequently, we examined their whole-body metabolic rate during walking and running at 2 m/s, exercises with comparable metabolic rates but distinct triceps surae muscle force and velocity demands (walking: low force, high velocity; running: high force, low velocity). Increasing triceps surae contraction velocity during cyclic contractions elevated net whole-body metabolic rate for both typology groups. However, the slow group consumed substantially less net metabolic energy at the slowest contraction velocity, but the metabolic difference between groups diminished at faster velocities. Consistent with the more economic force production during slow contractions, the slow group exhibited lower metabolic rates than the fast group while running, whereas metabolic rates were similar during walking. These findings provide important insights into the influence of muscle fibre typology on whole-body metabolic rate and emphasize the importance of considering muscle mechanical demands to understand muscle fibre typology related differences in whole-body metabolic rates. KEY POINTS: Muscle fibre typology is often suggested to affect whole-body metabolic rate, yet convincing in vivo evidence is lacking. Using isolated plantar flexor muscle contractions in individuals a priori selected for their predominantly slow or fast muscle fibre typology, we demonstrated that having predominantly slow muscle fibres provides a metabolic advantage during slow muscle contractions, but this benefit disappeared at faster contractions. We extended these results to full-body exercises, where we demonstrated that higher proportions of slow fibres associated with better economy during running but not when walking. These findings provide important insights into the influence of muscle fibre typology on whole-body metabolic rate and emphasize the importance of considering muscle mechanical demands to understand muscle fibre typology related differences in whole-body metabolic rate.

An approximate stochastic optimal control framework to simulate nonlinear neuro-musculoskeletal models in the presence of noise.

Optimal control simulations have shown that both musculoskeletal dynamics and physiological noise are important determinants of movement. However, due to the limited efficiency of available computational tools, deterministic simulations of movement focus on accurately modelling the musculoskeletal system while neglecting physiological noise, and stochastic simulations account for noise while simplifying the dynamics. We took advantage of recent approaches where stochastic optimal control problems are approximated using deterministic optimal control problems, which can be solved efficiently using direct collocation. We were thus able to extend predictions of stochastic optimal control as a theory of motor coordination to include muscle coordination and movement patterns emerging from non-linear musculoskeletal dynamics. In stochastic optimal control simulations of human standing balance, we demonstrated that the inclusion of muscle dynamics can predict muscle co-contraction as minimal effort strategy that complements sensorimotor feedback control in the presence of sensory noise. In simulations of reaching, we demonstrated that nonlinear multi-segment musculoskeletal dynamics enables complex perturbed and unperturbed reach trajectories under a variety of task conditions to be predicted. In both behaviors, we demonstrated how interactions between task constraint, sensory noise, and the intrinsic properties of muscle influence optimal muscle coordination patterns, including muscle co-contraction, and the resulting movement trajectories. Our approach enables a true minimum effort solution to be identified as task constraints, such as movement accuracy, can be explicitly imposed, rather than being approximated using penalty terms in the cost function. Our approximate stochastic optimal control framework predicts complex features, not captured by previous simulation approaches, providing a generalizable and valuable tool to study how musculoskeletal dynamics and physiological noise may alter neural control of movement in both healthy and pathological movements.

In Silico Biomarkers of Motor Function to Inform Musculoskeletal Rehabilitation and Orthopedic Treatment.

In this review, we elaborate on how musculoskeletal (MSK) modeling combined with dynamic movement simulation is gradually evolving from a research tool to a promising in silico tool to assist medical doctors and physical therapists in decision making by providing parameters relating to dynamic MSK function and loading. This review primarily focuses on our own and related work to illustrate the framework and the interpretation of MSK model-based parameters in patients with 3 different conditions, that is, degenerative joint disease, cerebral palsy, and adult spinal deformities. By selecting these 3 clinical applications, we also aim to demonstrate the differing levels of clinical readiness of the different simulation frameworks introducing in silico model-based biomarkers of motor function to inform MSK rehabilitation and treatment, with the application for adult spinal deformities being the most recent of the 3. Based on these applications, barriers to clinical integration and positioning of these in silico technologies within standard clinical practice are discussed in the light of specific challenges related to model assumptions, required level of complexity and personalization, and clinical implementation.

Similar sensorimotor transformations control balance during standing and walking.

Standing and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback similar to standing balance control. We found that delayed linear feedback of center of mass position and velocity, but not delayed linear feedback from ankle angles and angular velocities, can explain reactive ankle muscle activity and joint moments in response to perturbations of walking across protocols (discrete and continuous platform translations and discrete pelvis pushes). Feedback gains were modulated during the gait cycle and decreased with walking speed. Our results thus suggest that similar task-level variables, i.e. center of mass position and velocity, are controlled across standing and walking but that feedback gains are modulated during gait to accommodate changes in body configuration during the gait cycle and in stability with walking speed. These findings have important implications for modelling the neuromechanics of human balance control and for biomimetic control of wearable robotic devices. The feedback mechanisms we identified can be used to extend the current neuromechanical models that lack balance control mechanisms for the ankle joint. When using these models in the control of wearable robotic devices, we believe that this will facilitate shared control of balance between the user and the robotic device.

Computational modelling of muscle fibre operating ranges in the hindlimb of a small ground bird (Eudromia elegans), with implications for modelling locomotion in extinct species.

The arrangement and physiology of muscle fibres can strongly influence musculoskeletal function and whole-organismal performance. However, experimental investigation of muscle function during in vivo activity is typically limited to relatively few muscles in a given system. Computational models and simulations of the musculoskeletal system can partly overcome these limitations, by exploring the dynamics of muscles, tendons and other tissues in a robust and quantitative fashion. Here, a high-fidelity, 26-degree-of-freedom musculoskeletal model was developed of the hindlimb of a small ground bird, the elegant-crested tinamou (Eudromia elegans, ~550 g), including all the major muscles of the limb (36 actuators per leg). The model was integrated with biplanar fluoroscopy (XROMM) and forceplate data for walking and running, where dynamic optimization was used to estimate muscle excitations and fibre length changes throughout both gaits. Following this, a series of static simulations over the total range of physiological limb postures were performed, to circumscribe the bounds of possible variation in fibre length. During gait, fibre lengths for all muscles remained between 0.5 to 1.21 times optimal fibre length, but operated mostly on the ascending limb and plateau of the active force-length curve, a result that parallels previous experimental findings for birds, humans and other species. However, the ranges of fibre length varied considerably among individual muscles, especially when considered across the total possible range of joint excursion. Net length change of muscle-tendon units was mostly less than optimal fibre length, sometimes markedly so, suggesting that approaches that use muscle-tendon length change to estimate optimal fibre length in extinct species are likely underestimating this important parameter for many muscles. The results of this study clarify and broaden understanding of muscle function in extant animals, and can help refine approaches used to study extinct species.

Triceps surae muscle force potential and force demand shift with altering stride frequency in running.

While it is well recognized that the preferred stride frequency (PSF) in running closely corresponds to the metabolically optimal frequency, the underlying mechanisms are still unclear. Changes in joint kinematics when altering stride frequency will affect the muscle-tendon unit lengths and potentially the efficiency of muscles crossing these joints. Here, we investigated how fascicle kinematics and forces of the triceps surae muscle, a highly energy consuming muscle, are affected when running at different stride frequencies. Twelve runners ran on a force measuring treadmill, adopting five different frequencies (PSF; PSF ± 8%; PSF ± 15%), while we measured joint kinematics, whole-body energy expenditure, triceps surae muscle activity, and soleus (SOL; N = 10) and gastrocnemius medialis (GM; N = 12) fascicle kinematics. In addition, we used dynamic optimization to estimate SOL and GM muscle forces. We found that SOL and GM mean muscle fascicle length during stance followed an inverted U-relationship with the longest fascicle lengths occurring at PSF. Fascicle lengths were shortest at frequencies lower than PSF. In addition, average SOL force was greater at PSF-15% compared with PSF. Overall, our results suggest that reduced SOL and GM muscle fascicle lengths, associated with reduced muscle force potential, together with greater SOL force demand, contribute to the increased whole-body energy expenditure when running at lower than PSF. At higher stride frequencies, triceps surae muscle kinematics and force production were less affected suggesting that increased energy expenditure is rather related to higher cost of leg swing and greater cost of force production.

Interactions between initial posture and task-level goal explain experimental variability in postural responses to perturbations of standing balance.

Postural responses to similar perturbations of standing balance vary widely within and across subjects. Here, we identified two sources of variability and their interactions by combining experimental observations with computational modeling: differences in posture at perturbation onset across trials and differences in task-level goals across subjects. We first collected postural responses to unpredictable backward support-surface translations during standing in 10 young adults. We found that maximal trunk lean in postural responses to backward translations were highly variable both within subjects (mean of ranges = 28.3°) and across subjects (range of means = 39.9°). Initial center of mass (COM) position was correlated with maximal trunk lean during the response, but this relation was subject specific (R2 = 0.29-0.82). We then used predictive simulations to assess causal relations and interactions with task-level goal. Our simulations showed that initial posture explains the experimentally observed intrasubject variability with a more anterior initial COM position increasing the use of the hip strategy. Differences in task-level goal explain observed intersubject variability with prioritizing effort minimization leading to ankle strategies and prioritizing stability leading to hip strategies. Interactions between initial posture and task-level goal explain observed differences in intrasubject variability across subjects. Our findings suggest that variability in initial posture due to increased sway as observed in older adults might increase the occurrence of less stable postural responses to perturbations. Insight in factors causing movement variability will advance our ability to study the origin of differences between groups and conditions.NEW & NOTEWORTHY Responses to perturbations of standing balance vary both within and between individuals. By combining experimental observations with computational modeling, we identified causes of observed kinematic variability in healthy young adults. First, we found that trial-by-trial differences in posture at perturbation onset explain most of the kinematic variability observed within subjects. Second, we found that differences in prioritizing effort versus stability explained differences in the postural response as well as differences in trial-by-trial variability across subjects.

Perspective on musculoskeletal modelling and predictive simulations of human movement to assess the neuromechanics of gait.

Locomotion results from complex interactions between the central nervous system and the musculoskeletal system with its many degrees of freedom and muscles. Gaining insight into how the properties of each subsystem shape human gait is challenging as experimental methods to manipulate and assess isolated subsystems are limited. Simulations that predict movement patterns based on a mathematical model of the neuro-musculoskeletal system without relying on experimental data can reveal principles of locomotion by elucidating cause-effect relationships. New computational approaches have enabled the use of such predictive simulations with complex neuro-musculoskeletal models. Here, we review recent advances in predictive simulations of human movement and how those simulations have been used to deepen our knowledge about the neuromechanics of gait. In addition, we give a perspective on challenges towards using predictive simulations to gain new fundamental insight into motor control of gait, and to help design personalized treatments in patients with neurological disorders and assistive devices that improve gait performance. Such applications will require more detailed neuro-musculoskeletal models and simulation approaches that take uncertainty into account, tools to efficiently personalize those models, and validation studies to demonstrate the ability of simulations to predict gait in novel circumstances.

Distal-to-proximal joint mechanics redistribution is a main contributor to reduced walking economy in older adults.

Age-related neural and musculoskeletal declines affect mobility and the quality of life of older adults. To date, the mechanisms underlying reduced walking economy in older adults still remain elusive. In this study, we wanted to investigate which biomechanical factors were associated with the higher energy cost of walking in older compared with young adults. Fourteen younger (24 ± 2 years) and fourteen older (74 ± 4 years) adults were tested. Plantarflexor strength and Achilles tendon stiffness were evaluated during a dynamometer test. Medial gastrocnemius fascicle length, ground reaction forces, joint kinematics, and oxygen consumption were measured during walking treadmill at 0.83 and 1.39 m.s-1 . Energy cost of walking, lower-limb joint mechanics, muscle-tendon unit, and tendinous tissues length were calculated. The energy cost of walking was higher at 0.83 m.s-1 (+16%; P = .005) and plantarflexor strength lower (-31%; P = .007) in older adults. Achilles tendon stiffness and medial gastrocnemius fascicle length changes did not differ between older and young adults. The reduction in ankle mechanics was compensated by increases in hip mechanics in older adults during walking. The hip extensor moment was the only significant predictor of the energy cost of walking (adjusted R2 : 0.35-0.38). The higher energy cost in older adults is mainly associated with their distal-to-proximal redistribution of joint mechanics during walking possibly due to plantarflexor weakness. In our study, medial gastrocnemius fascicle and tendinous tissue behavior did not explain the higher energy cost of walking in older compared to young adults.

Habitual foot strike pattern does not affect simulated triceps surae muscle metabolic energy consumption during running.

Foot strike pattern affects ankle joint work and triceps surae muscle-tendon dynamics during running. Whether these changes in muscle-tendon dynamics also affect triceps surae muscle energy consumption is still unknown. In addition, as the triceps surae muscle accounts for a substantial amount of the whole-body metabolic energy consumption, changes in triceps surae energy consumption may affect whole-body metabolic energy consumption. However, direct measurements of muscle metabolic energy consumption during dynamic movements is difficult. Model-based approaches can be used to estimate individual muscle and whole-body metabolic energy consumption based on Hill type muscle models. In this study, we use an integrated experimental and dynamic optimization approach to compute muscle states (muscle forces, lengths, velocities, excitations and activations) of 10 habitual midfoot/forefoot striking and nine habitual rearfoot striking runners while running at 10 and 14 km h-1 The Achilles tendon stiffness of the musculoskeletal model was adapted to fit experimental ultrasound data of the gastrocnemius medialis muscle during ground contact. Next, we calculated triceps surae muscle and whole-body metabolic energy consumption using four different metabolic energy models provided in the literature. Neither triceps surae metabolic energy consumption (P>0.35) nor whole-body metabolic energy consumption (P>0.14) was different between foot strike patterns, regardless of the energy model used or running speed tested. Our results provide new evidence that midfoot/forefoot and rearfoot strike patterns are metabolically equivalent.

Model-based control for exoskeletons with series elastic actuators evaluated on sit-to-stand movements.

BACKGROUND: Currently, control of exoskeletons in rehabilitation focuses on imposing desired trajectories to promote relearning of motions. Furthermore, assistance is often provided by imposing these desired trajectories using impedance controllers. However, lower-limb exoskeletons are also a promising solution for mobility problems of individuals in daily life. To develop an assistive exoskeleton which allows the user to be autonomous, i.e. in control of his motions, remains a challenge. This paper presents a model-based control method to tackle this challenge. METHODS: The model-based control method utilizes a dynamic model of the exoskeleton to compensate for its own dynamics. After this compensation of the exoskeleton dynamics, the exoskeleton can provide a desired assistance to the user. While dynamic models of exoskeletons used in the literature focus on gravity compensation only, the need for modelling and monitoring of the ground contact impedes their widespread use. The control strategy proposed here relies on modelling of the full exoskeleton dynamics and of the contacts with the environment. A modelling strategy and general control scheme are introduced. RESULTS: Validation of the control method on 15 non-disabled adults performing sit-to-stand motions shows that muscle effort and joint torques are similar in the conditions with dynamically compensated exoskeleton and without exoskeleton. The condition with exoskeleton in which the compensating controller was not active showed a significant increase in human joint torques and muscle effort at the knee and hip. Motor saturation occurred during the assisted condition, which limited the assistance the exoskeleton could deliver. CONCLUSIONS: This work presents the modelling steps and controller design to compensate the exoskeleton dynamics. The validation seems to indicate that the presented model-based controller is able to compensate the exoskeleton.

OpenSim Versus Human Body Model: A Comparison Study for the Lower Limbs During Gait.

Musculoskeletal modeling and simulations have become popular tools for analyzing human movements. However, end users are often not aware of underlying modeling and computational assumptions. This study investigates how these assumptions affect biomechanical gait analysis outcomes performed with Human Body Model and the OpenSim gait2392 model. The authors compared joint kinematics, kinetics, and muscle forces resulting from processing data from 7 healthy adults with both models. Although outcome variables had similar patterns, there were statistically significant differences in joint kinematics (maximal difference: 9.8° [1.5°] in sagittal plane hip rotation), kinetics (maximal difference: 0.36 [0.10] N·m/kg in sagittal plane hip moment), and muscle forces (maximal difference: 8.51 [1.80] N/kg for psoas). These differences might be explained by differences in hip and knee joint center locations up to 2.4 (0.5) and 1.9 (0.2) cm in the posteroanterior and inferosuperior directions, respectively, and by the offset in pelvic reference frames of about 10° around the mediolateral axis. The choice of model may not influence the conclusions in clinical settings, where the focus is on interpreting deviations from the reference data, but it will affect the conclusions of mechanical analyses in which the goal is to obtain accurate estimates of kinematics and loading.

Mechanical effort predicts the selection of ankle over hip strategies in nonstepping postural responses.

Experimental studies have shown that a continuum of ankle and hip strategies is used to restore posture following an external perturbation. Postural responses can be modeled by feedback control with feedback gains that optimize a specific objective. On the one hand, feedback gains that minimize effort have been used to predict muscle activity during perturbed standing. On the other hand, hip and ankle strategies have been predicted by minimizing postural instability and deviation from upright posture. It remains unclear, however, whether and how effort minimization influences the selection of a specific postural response. We hypothesize that the relative importance of minimizing mechanical work vs. postural instability influences the strategy used to restore upright posture. This hypothesis was investigated based on experiments and predictive simulations of the postural response following a backward support surface translation. Peak hip flexion angle was significantly correlated with three experimentally determined measures of effort, i.e., mechanical work, mean muscle activity and metabolic energy. Furthermore, a continuum of ankle and hip strategies was predicted in simulation when changing the relative importance of minimizing mechanical work and postural instability, with increased weighting of mechanical work resulting in an ankle strategy. In conclusion, the combination of experimental measurements and predictive simulations of the postural response to a backward support surface translation showed that the trade-off between effort and postural instability minimization can explain the selection of a specific postural response in the continuum of potential ankle and hip strategies.

The effect of muscle weakness on the capability gap during gross motor function: a simulation study supporting design criteria for exoskeletons of the lower limb.

BACKGROUND: Enabling persons with functional weaknesses to perform activities of daily living (ADL) is one of the main challenges for the aging society. Powered orthoses, or exoskeletons, have the potential to support ADL while promoting active participation of the user. For this purpose, assistive devices should be designed and controlled to deliver assistance as needed (AAN). This means that the level of assistance should bridge the capability gap, i.e. the gap between the capabilities of the subjects and the task requirements. However, currently the actuators of exoskeletons are mainly designed using inverse dynamics (ID) based calculations of joint moments. The goal of the present study is to calculate the capability gap for the lower limb during ADL when muscle weakness is present, which is needed for appropriate selection of actuators to be integrated in exoskeletons. METHODS: A musculoskeletal model (MM) is used to calculate the joint kinematics, joint kinetics and muscle forces of eight healthy subjects during ADL (gait, sit-to-stand, stand-to-sit, stair ascent, stair descent). Muscle weakness was imposed to the MM by a stepwise decrease in maximal isometric force imposed to all muscles. Muscle forces were calculated using static optimization. In order to compensate for muscle weakness, ideal moment actuators that represent the motors of an exoskeleton in the simulation were added to deliver AAN required to perform the task. RESULTS: The ID approach overestimates the required assistance since it relies solely on the demands of the task, whereas the AAN approach incorporates the capabilities of the subject. Furthermore, the ID approach delivers continuous support whereas the AAN approach targets the period where a capability gap occurs. The level of muscle weakness for which the external demands imposed by ADL can no longer be met by active muscle force production, is respectively 40%, 70%, 80% and 30%. CONCLUSIONS: The present workflow allows estimating the AAN during ADL for different levels of muscle weakness, which can be used in the mechatronic design and control of powered exoskeletons. The AAN approach is a more physiological approach than the ID approach, since the MM accounts for the subject-specific capabilities of the user.

Altering length and velocity feedback during a neuro-musculoskeletal simulation of normal gait contributes to hemiparetic gait characteristics.

BACKGROUND: Spasticity is an important complication after stroke, especially in the anti-gravity muscles, i.e. lower limb extensors. However the contribution of hyperexcitable muscle spindle reflex loops to gait impairments after stroke is often disputed. In this study a neuro-musculoskeletal model was developed to investigate the contribution of an increased length and velocity feedback and altered reflex modulation patterns to hemiparetic gait deficits. METHODS: A musculoskeletal model was extended with a muscle spindle model providing real-time length and velocity feedback of gastrocnemius, soleus, vasti and rectus femoris during a forward dynamic simulation (neural control model). By using a healthy subject's base muscle excitations, in combination with increased feedback gains and altered reflex modulation patterns, the effect on kinematics was simulated. A foot-ground contact model was added to account for the interaction effect between the changed kinematics and the ground. The qualitative effect i.e. the directional effect and the specific gait phases where the effect is present, on the joint kinematics was then compared with hemiparetic gait deviations reported in the literature. RESULTS: Our results show that increased feedback in combination with altered reflex modulation patterns of soleus, vasti and rectus femoris muscle can contribute to excessive ankle plantarflexion/inadequate dorsiflexion, knee hyperextension/inadequate flexion and increased hip extension/inadequate flexion during dedicated gait cycle phases. Increased feedback of gastrocnemius can also contribute to excessive plantarflexion/inadequate dorsiflexion, however in combination with excessive knee and hip flexion. Increased length/velocity feedback can therefore contribute to two types of gait deviations, which are both in accordance with previously reported gait deviations in hemiparetic patients. Furthermore altered modulation patterns, in particular the reduced suppression of the muscle spindle feedback during swing, can contribute largely to an increased plantarflexion and knee extension during the swing phase and consequently to hampered toe clearance. CONCLUSIONS: Our results support the idea that hyperexcitability of length and velocity feedback pathways, especially in combination with altered reflex modulation patterns, can contribute to deviations in hemiparetic gait. Surprisingly, our results showed only subtle temporal differences between length and velocity feedback. Therefore, we cannot attribute the effects seen in kinematics to one specific type of feedback.

Identification of Neural and Non-Neural Origins of Joint Hyper-Resistance Based on a Novel Neuromechanical Model.

Joint hyper-resistance is a common symptom in neurological disorders. It has both neural and non-neural origins, but it has been challenging to distinguish different origins based on clinical tests alone. Combining instrumented tests with parameter identification based on a neuromechanical model may allow us to dissociate the different origins of joint hyper-resistance in individual patients. However, this requires that the model captures the underlying mechanisms. Here, we propose a neuromechanical model that, in contrast to previously proposed models, accounts for muscle short-range stiffness (SRS) and its interaction with muscle tone and reflex activity. We collected knee angle trajectories during the pendulum test in 15 children with cerebral palsy (CP) and 5 typically developing children. We did the test in two conditions - hold and pre-movement - that have been shown to alter knee movement. We modeled the lower leg as an inverted pendulum actuated by two antagonistic Hill-type muscles extended with SRS. Reflex activity was modeled as delayed, linear feedback from muscle force. We estimated neural and non-neural parameters by optimizing the fit between simulated and measured knee angle trajectories during the hold condition. The model could fit a wide range of knee angle trajectories in the hold condition. The model with personalized parameters predicted the effect of pre-movement demonstrating that the model captured the underlying mechanism and subject-specific deficits. Our model may help with the identification of neural and non-neural origins of joint hyper-resistance and thereby opens perspectives for improved diagnosis and treatment selection in children with spastic CP, but such applications require further studies to establish the method's reliability.

Gait classification for growing children with Duchenne muscular dystrophy.

Classifying gait patterns into homogeneous groups could enhance communication among healthcare providers, clinical decision making and clinical trial designs in boys with Duchenne muscular dystrophy (DMD). Sutherland's classification has been developed 40 years ago. Ever since, the state-of-the-art medical care has improved and boys with DMD are now longer ambulatory. Therefore, the gait classification requires an update. The overall aim was to develop an up-to-date, valid DMD gait classification. A total of 137 three-dimensional gait analysis sessions were collected in 30 boys with DMD, aged 4.6-17 years. Three classes were distinguished, which only partly aligned with increasing severity of gait deviations. Apart from the mildly affected pattern, two more severely affected gait patterns were found, namely the tiptoeing pattern and the flexion pattern with distinct anterior pelvic tilt and posterior trunk leaning, which showed most severe deviations at the ankle or at the proximal segments/joints, respectively. The agreement between Sutherland's and the current classification was low, suggesting that gait pathology with the current state-of-the-art medical care has changed. However, overlap between classes, especially between the two more affected classes, highlights the complexity of the continuous gait changes. Therefore, caution is required when classifying individual boys with DMD into classes.

Faster triceps surae muscle cyclic contractions alter muscle activity and whole body metabolic rate.

Hundred years ago, Fenn demonstrated that when a muscle shortens faster, its energy liberation increases. Fenn's results were the first of many that led to the general understanding that isometric muscle contractions are energetically cheaper than concentric contractions. However, this evidence is still primarily based on single fiber or isolated (ex vivo) muscle studies and it remains unknown whether this translates to whole body metabolic rate. In this study, we specifically changed the contraction velocity of the ankle plantar flexors and quantified the effects on triceps surae muscle activity and whole body metabolic rate during cyclic plantar flexion (PF) contractions. Fifteen participants performed submaximal ankle plantar flexions (∼1/3 s activation and ∼2/3 s relaxation) on a dynamometer at three different ankle angular velocities: isometric (10° PF), isokinetic at 30°/s (5-15° PF), and isokinetic at 60°/s (0-20° PF) while target torque (25% MVC) and cycle frequency were kept constant. In addition, to directly determine the effect of ankle angular velocity on muscle kinematics we collected gastrocnemius medialis muscle fascicle ultrasound data. As expected, increasing ankle angular velocity increased gastrocnemius medialis muscle fascicle contraction velocity and positive mechanical work (P < 0.01), increased mean and peak triceps surae muscle activity (P < 0.01), and considerably increased net whole body metabolic rate (P < 0.01). Interestingly, the increase in triceps surae muscle activity with fast ankle angular velocities was most pronounced in the gastrocnemius lateralis (P < 0.05). Overall, our results support the original findings from Fenn in 1923 and we demonstrated that greater triceps surae muscle contraction velocities translate to increased whole body metabolic rate.NEW & NOTEWORTHY Single muscle fiber studies or research on isolated (ex vivo) muscles demonstrated that faster concentric muscle contractions yield increased energy consumption. Here we translated this knowledge to muscle activation and whole body metabolic rate. Increasing ankle angular velocity increased triceps surae contraction velocity and mechanical work, increasing triceps surae muscle activity and substantially elevating whole body metabolic rate. Additionally, we demonstrated that triceps surae muscle activation strategy depends on the mechanical demands of the task.