Biology subjects

Afschrift, M.

Publications and source records attributed to Afschrift, M..

14 recordsLinked to original sources

bioRxiv2026

Simulations predict that alterations in balance control contribute to the higher cost of walking with a prosthesis

The high metabolic cost of walking in individuals with a transtibial amputation is often attributed to reduced ankle propulsion. However, the cost of stabilizing walking may also increase after amputation, potentially explaining why restoring ankle propulsion does not always normalize metabolic cost. Because the contributions of propulsion and stabilization are difficult to dissociate experimentally, we used simulations to probe the effects of transtibial amputation and different prostheses on walking cost. We simulated gait using a conceptual planar torque-driven model. Leg joint torques were controlled by feedforward and linear, time-varying full state feedback. We computed feedforward torques associated with propulsion and feedback gains for stabilizing walking that minimized expected effort (sum of torques squared) in the presence of sensorimotor noise while imposing stability. We simulated walking for an intact model and three walkers with a prosthesis: a passive, a feedforward-controlled active, and a feedforward and local feedback-controlled active prosthesis. We solved a deterministic approximation of the resultant stochastic optimal control problems for different levels of sensorimotor noise. Feedforward and expected feedback torques were higher for the passive prosthesis walker than for the intact walker. An active prosthesis restored total biological effort (i.e., effort of all but the prosthesis joint) to the level of the intact walker, but this effort was generated by fewer biological joints. Biological feedback effort was higher in prosthesis walkers than in the intact walker. Adding local feedback to an active prosthesis reduced biological feedback effort, but only at low noise levels. Our results suggest that walking with a passive prosthesis increases effort related to both propulsion and stabilization. While active prostheses can support propulsion, local feedback control only marginally reduced stabilization-related effort, suggesting that controllers require sensory information from the rest of the body to fully restore the metabolic cost of walking.

systems biology↗

bioRxiv2026

Stochastic optimal control simulations of walking: potential and perspective

Human walking is intrinsically variable. For example, there is considerable stride to stride variability even when walking speed is constant. This variability is due to uncertainty in the sensorimotor system and the environment, and is shaped by both musculoskeletal dynamics (e.g. joint stiffness and damping originating from muscles) and the control strategy used to mitigate the effects of uncertainty. Yet, insight into how sensorimotor noise shapes walking variability is limited due to a lack of experimental methods to assess sensorimotor noise and control strategies during walking. Simulations that account for uncertainty can elucidate how sensorimotor noise affects movement variability but due to numerical challenges, accounting for sensorimotor noise is not common in simulations of walking. Existing simulations have hugely simplified musculoskeletal dynamics (e.g. no muscles), the control policy (e.g. pre-defined feedback loops), or sensorimotor noise sources (e.g. only motor noise). Here, we performed stochastic optimal control simulations of walking based on a model with 9 degrees of freedom and 18 muscles to study how the level of sensory and motor noise influences walking. We solved for feedforward muscle excitations and full-state time-varying feedback gains that minimised expected effort while generating periodic, and hence stable, gait patterns. To enable these simulations, we approximated the state distribution with a Gaussian and used an unscented transform to propagate the state covariance. Resulting optimisation problems were solved with direct collocation. Sensorimotor noise level had a small effect on the mean kinematics but shaped kinematic and muscle activity variability as well as expected effort. Although simulations underestimated the magnitude of experimental positional variability, they captured its structure. In agreement with experimental results, the control policy prioritised limiting variability of centre of mass kinematics and minimal swing foot clearance over limiting joint angle variability. Hence, our simulations suggest that effort minimisation underlies these observations. Author summaryWhen performing a movement multiple times, each repetition will be slightly different due to random disturbances in the neural signals used to control movement, i.e. sensorimotor noise. Because it is difficult to measure inside the nervous system of a moving person, computer simulations are used to study movement control. They found that both sensorimotor noise and musculoskeletal mechanics determine how people control arm movements and standing. However, there are no simulations of walking that systematically evaluated how sensorimotor noise level influences walking kinematics because they pose computational challenges. Here, we proposed and used an approach for minimal effort simulations of walking in the presence of uncertainty. We imposed forward speed and stability but not kinematics. We found that the level of sensorimotor noise had little effect on the mean movement but a strong effect on the variability and the expected effort. The control strategy prioritised reducing the variability of the centre of mass position and swing foot clearance over reducing the variability of individual joint angles, which is also observed in experiments. Interestingly, strict control of centre of mass position and foot clearance in our simulations emerged from minimising effort.

systems biology↗

bioRxiv2025

Foot placement is not controlled based on angular momentum

This study examined how mediolateral foot placement is controlled following mechanical perturbations that affected either whole-body linear or angular momentum. Predictive foot placement models based on center of mass state alone were compared with models that additionally included whole-body angular momentum to determine whether whole-body angular momentum contributes to foot placement control beyond linear momentum. Ten healthy adults walked on a treadmill at 2 km/h and 5 km/h while being exposed to two perturbation types: (1) a pull to the pelvis that primarily altered linear momentum (translation perturbation) and (2) simultaneous pulls to the pelvis and shoulder in opposite directions that primarily altered angular momentum (rotation perturbation). Perturbations were applied at heel strike, with a magnitude of [~]120 N and a duration of 300 ms. Whole-body kinematics were recorded using 3D motion capture and processed in OpenSim to compute linear and angular momentum. Translation perturbations caused large deviations in whole-body linear momentum with minimal changes in whole-body angular momentum, whereas rotation perturbations induced strong whole-body angular momentum deviations with smaller changes in linear momentum. Including whole-body angular momentum minimally improved foot placement predictions during early swing after rotation perturbations. These findings indicate that mediolateral foot placement is primarily governed by linear momentum dynamics.

biophysics↗

bioRxiv2025

Speeding up, not slowing down, decreases the energy needed to control walking balance

There is a metabolic cost associated with controlling walking balance but it remains unclear to what extent sagittal plane balance control contributes to this cost. Furthermore, sagittal plane balance control strategies vary with speed but it is unclear whether this also leads to a speed-dependent balance-related metabolic cost. Here, we explored the metabolic cost of stabilizing walking in the sagittal plane across speeds and its relationship with balance control strategies. To this aim, we applied continuous treadmill belt speed perturbations (standard deviation of 0.13 ms-1) to 22 healthy individuals walking at 0.8, 1.2, and 1.6 m/s. We evaluated changes in metabolic energy consumption and balance control strategies between perturbed and unperturbed walking and explored relationships between both. Perturbations induced larger increases in metabolic rate and changes in balance control strategies at slower than faster walking speeds, suggesting that walking is more robust against perturbations at faster speeds. Perturbations increased the metabolic rate by 16.7% at the slowest versus 4.6% at the fastest walking speed. When perturbed, subjects took shorter, wider, and more variable steps, and variability in ankle muscle activation increased but most changes were larger at slower speeds. Metabolic rate increased more due to perturbations in individuals who reduced step length more, i.e. relied more on anticipatory adjustments of the walking pattern. Our findings are especially relevant for explaining the increased metabolic cost of individuals with mobility impairments, who often walk slower and have altered balance control.

physiology↗

bioRxiv2024

Benchmarking the predictive capability of human gait simulations.

Physics-based simulation generate movement patterns based on a neuro-musculoskeletal model without relying on experimental movement data, offering a powerful approach to study how neuro-musculoskeletal properties shape locomotion. Yet, simulated gait patterns and metabolic powers do not always agree with experiments, pointing to modeling errors reflecting gaps in our understanding. Here, we systematically evaluated the predictive capability of simulations based on a 3D musculoskeletal model to predict gait mechanics, muscle activity and metabolic power across gait conditions. We simulated the effect of adding mass to body segments, variations in walking speed, incline walking, crouched walking. We chose tasks that are straightforward to model, ensuring that prediction errors stem from shortcomings in the neuro-musculoskeletal model. The simulations predicted stride frequency and walking kinematic with reasonable accuracy but underestimated variation in metabolic power across conditions. In particular, they underestimated changes in metabolic power with respect to level walking in tasks requiring substantial positive mechanical work, such as incline walking (27% underestimation). We identified two possible errors in simulated metabolic power. First, the Hill-type muscle model and phenomenological metabolic power model produced high maximal mechanical efficiency (average 0.58) during concentric contractions, compared to the observed 0.2-0.3 in laboratory experiments. Second, when we multiplied the mechanical work with more realistic estimates of mechanical efficiency (i.e. 0.25), simulations overestimated the metabolic power by 84%. This suggests that positive work by muscle fibers was overestimated in the simulations. This overestimation may be caused by several assumptions and errors in the musculoskeletal model including its interacting with the environment and/or its many parameters. This study highlights the need for more accurate models of muscle mechanics, energetics, and passive elastic structures to improve the realism of human movement simulations. Validating simulations across a broad range of conditions is important to pinpoint shortcomings in neuro-musculoskeletal modeling. Author summary: (non-technical summary of the work)Our research focuses on understanding how humans walk by using computer simulations. These simulations are based on detailed models, i.e. mathematical descriptions, of skeleton, muscles, joints, and control system. By comparing our simulations to actual experiments where people walked under different conditions--such as carrying extra weight, walking faster or slower, or moving uphill or downhill--we evaluated how well the simulations could predict real-life movement and energy use. We found that while the simulations performed well in predicting the walking pattern, they underestimated metabolic energy used by the body, especially in tasks like walking uphill. Errors in simulated metabolic power likely stem from two issues. First, the metabolic power model resulted in unrealistically high mechanical efficiency compared to experiment. Second, positive work (and as a result also net negative work) by muscle fibers was overestimated in the simulations. These findings highlight the need to improve the models so they can more accurately reflect the complexity of human movement and energy use. Ultimately, better models will help us design devices like exoskeletons and prosthetics and improve treatments for people with movement difficulties.

biophysics↗

bioRxiv2024

Springs vs. motors: Ideal assistance in the lower limbs during walking at different speeds

Recent years have witnessed breakthroughs in assistive exoskeletons; both passive and active devices have reduced metabolic costs near preferred walking speed by assisting muscle actions. Metabolic reductions at multiple speeds should thus also be attainable. Musculoskeletal simulation can potentially predict the interaction between assistive moments, muscle-tendon mechanics, and walking energetics. In this study, we simulated devices optimal assistive moments based on minimal muscle activations during walking with prescribed kinematics and dynamics. We used a generic musculoskeletal model with calibrated muscle-tendon parameters and computed metabolic rates from muscle actions. We then simulated walking across multiple speeds and with two ideal actuation modes - motor-based and spring-based - to assist ankle plantarflexion, knee extension, hip flexion, and hip abduction and compared computed metabolic rates. We found that both actuation modes considerably reduced physiological joint moments but did not always reduce metabolic rates. Compared to unassisted conditions, motor-based ankle plantarflexion and hip flexion assistance reduced metabolic rates, and this effect was more pronounced as walking speed increased. Spring-based hip flexion and abduction assistance increased metabolic rates at some walking speeds despite a moderate decrease in some muscle activations. Both modes of knee extension assistance reduced metabolic rates to a small extent, even though the actuation contributed with practically the entire net knee extension moment during stance. Motor-based hip abduction assistance reduced metabolic rates more than spring-based assistance, though this reduction was relatively small. Future work should experimentally validate the effects of assistive moments and refine modeling assumptions accordingly. Our computational workflow is freely available online. Author SummaryWe used simulation to identify ideal assistance at major lower limb joints that can potentially be produced by motor-based or spring-based assistive devices in slow, normal, and fast walking. We found that assistance from both actuation modes decreased muscle activations and net muscle moments to varying extents, depending on joint and walking speed, but they did not always reduce metabolic energy of muscles. Motor-based assistance was overall more effective than spring-based assistance, and spring-based assistance at times increased the metabolic energy. The largest metabolic energy reductions occurred with motor-based plantarflexion assistance, followed by motor-based hip flexion assistance, both more notably at higher speeds. Motor-based hip abduction assistance also reduced metabolic energy, somewhat inversely with walking speed. Spring-based assistance was overall less effective than motor-based assistance but did reduce metabolic energy with plantarflexion assistance in slow walking and with hip flexion assistance in fast walking. Knee extension assistance, regardless of actuation mode or walking speed, had little to no influence on metabolic energy. Our simulation findings do not support knee extension assistance at all, nor spring-based hip flexion assistance in slow walking or hip abduction assistance at any speed if a device goal is to reduce muscle activations.

bioengineering↗

bioRxiv2023

ASSESSMENT OF STABILIZING FEEDBACK CONTROL OF WALKING, A TUTORIAL

Walking without falling requires stabilization of the trajectory of the body center of mass relative to the base of support. Model studies suggest that this requires active, feedback control, i.e., the nervous system must process sensory information on the state of the body to generate descending motor commands to the muscles to stabilize walking, especially in the mediolateral direction. Stabilization of bipedal gait is challenging and can be impaired in older and diseased individuals. In this tutorial, we illustrate how gait analysis can be used to assess the stabilizing feedback control of gait. We present methods ranging from those that require limited input data (e.g. position data of markers placed on the feet and pelvis only) to those that require full-body kinematics and electromyography. Analyses range from simple kinematics analyses to inverse dynamics. These methods assess stabilizing feedback control of human walking at three levels: 1) the level of center of mass movement and horizontal ground reaction forces, 2) the level of center of mass movement and foot placement and 3) the level of center of mass movement and the joint moments or muscle activity. We show how these can be calculated and provide a GitHub repository (https://github.com/VU-HMS/Tutorial-stabilizing-walking) which contains open access Matlab and Python code to calculate these. Finally, we discuss what information on feedback control can be learned from each of these.

neuroscience↗

bioRxiv2023

A dynamic foot model for predictive simulations of 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. Its arched shape makes it possible to stiffen the foot to withstand high loads when pushing off, without compromising the range of motion. Experimental studies demonstrated that manipulating foot stiffness had considerable effects on gait. In clinical practise, altered foot structure is associated with pathological gait. Yet our understanding of how foot structure influences gait mechanics is still poor. Here we used predictive simulations to explore causal relations between foot properties and whole-body gait. Our dynamic three-segment foot model with longitudinal arch improved gait predictions compared to one- and two-segment foot models and can explain measured ankle-foot kinematics and energetics. We identified three properties of the ankle-foot complex that are crucial for healthy walking: (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, intrinsic and extrinsic foot muscles. Insufficient foot stiffness results in walking patterns with reduced push-off power. During terminal stance plantar fascia and intrinsic foot muscles transfer energy from the metatarsophalangeal to midtarsal joint, which further increases push-off power.

bioengineering↗

bioRxiv2022

Accuracy-speed-stability trade-offs in a targeted stepping task are similar in young and older adults

BackgroundStepping accuracy, speed, and stability are lower in older compared to young adults. Lower stepping performance in older adults may be due to larger accuracy-speed-stability trade-offs because of reduced ability to simultaneously fulfill these task-level goals. Our goal was to evaluate whether trade-offs are larger in older compared to young adults in a targeted stepping task. Since sensorimotor function declines with age, our secondary goal was to evaluate whether poorer sensorimotor function was associated with larger trade-offs. Methods25 young (median 22 years old) and 25 older (median 70 years old) adults stepped into projected targets in conditions with various levels of accuracy, speed, and stability requirements. We determined trade-offs as the change in performance, i.e. foot placement error, step duration, and mediolateral center of pressure path length, between each of these conditions and a control condition. To assess age-related differences in the magnitude of trade-offs, we compared the change in performance between age groups. Associations between trade-offs and measures of sensorimotor function were tested using correlations. ResultsWe found an accuracy-speed and an accuracy-stability trade-off in both young and older adults, but trade-offs were not different between young and older adults. Inter-subject differences in sensorimotor function could not explain inter-subject differences in trade-offs. ConclusionAge-related differences in the ability to combine task-level goals do not explain why older adults stepped less accurate and less stable than young adults. However, lower stability combined with an age-independent accuracy-stability trade-off could explain lower accuracy in older adults.

neuroscience↗

bioRxiv2022

Assisting walking balance using a bio-inspired exoskeleton controller

Balance control is important for mobility, yet exoskeleton research has mainly focused on improving metabolic energy efficiency. Here we present a biomimetic exoskeleton controller that supports walking balance and reduces muscle activity. Humans restore balance after a perturbation by adjusting activity of the muscles actuating the ankle in proportion to deviations from steady-state center of mass kinematics. We designed a controller that mimics the neural control of steady-state walking and the balance recovery responses to perturbations. This controller uses both feedback from ankle kinematics in accordance with an existing model and feedback from the center of mass velocity. Control parameters were estimated by fitting the experimental relation between kinematics and ankle moments observed in humans that were walking while being perturbed by push and pull perturbations. This identified model was implemented on a bilateral ankle exoskeleton. The exoskeleton provided 30% of the estimated ankle moment during steady-state and perturbed walking. Across twelve subjects, exoskeleton support reduced calf muscle activity in steady-state walking by 19 % with respect to a minimal impedance controller. Proportional feedback of the center of mass velocity improved balance support after perturbation. Muscle activity is reduced in response to push and pull perturbations by 10 and 16 % and center of mass deviations by 9 and 18% with respect to the same controller without center of mass feedback. Our control approach implemented on bilateral ankle exoskeletons can thus effectively support steady-state walking and balance control and therefore has the potential to improve mobility in balance-impaired individuals.

biophysics↗

bioRxiv2022

Turning the head while biking makes older people lose cycling direction and balance

Older adults are more often involved in bike accidents than other age groups, especially in single-sided accidents (crashes without another road user). This suggests that older adults have more difficulty maintaining balance while cycling, likely due to age-related sensorimotor decline. A particularly challenging maneuver in traffic is the shoulder check (turning the upper body to look behind while maintaining balance and direction). This study investigates how age-related sensorimotor deficits impact this skill. 40 young (22.86 {+/-} 1.53 years) and 41 older participants (62.73 {+/-} 1.57 years) cycled in a straight lane while performing a shoulder check to identify the color of an object behind them. We recorded the task-errors (interrupted cycling, incorrect color identification, cycling outside the lane) and computed the steering angle, rotation of the frame, pelvis and torso, and task duration from inertial measurement unit data. Older adults made more task-errors than young participants; one-third failed the task due to mistakes such as misidentifying the color, losing balance, or leaving the lane. In the successful trials, older adults showed greater steering variability, increased pelvic rotation relative to the frame, and took longer to complete the task than the young participants. These findings suggest that age-related difficulties in maintaining balance while head-turning may contribute to the higher rate of single-sided bike accidents among older cyclists. Infrastructure adaptations (e.g., wider bike lanes) and individual-level interventions (e.g., mirrors) that alleviate the difficulties older adults experience when performing a shoulder check could improve safety for people from this age group.

neuroscience↗

bioRxiv2021

Modeling toes contributes to realistic stance knee mechanics in three-dimensional predictive simulations of walking

Physics-based predictive simulations have been shown to capture many salient features of human walking. Yet they often fail to produce realistic stance knee mechanics and terminal stance ankle plantarflexion. While the influence of the performance criterion on the predicted walking pattern has been previously studied, the influence of the mechanics has been less explored. Here, we investigated the influence of two mechanical assumptions on the predicted walking pattern: the complexity of the foot segment and the stiffness of the Achilles tendon. We found, through three-dimensional muscle-driven predictive simulations of walking, that modeling the toes and metatarsophalangeal joints, and thus using two-segment instead of single-segment foot models, contributed to robustly eliciting physiological stance knee flexion angles, knee extension torques, and knee extensor activity. Yet modeling toe joints did not improve ankle kinematics, nor did decreasing the Achilles tendon stiffness. The lack of predicted terminal stance ankle plantarflexion thereby remains an open question. Overall, this simulation study shows that not only the performance criterion but also mechanical assumptions affect predictive simulations of walking. Improving the realism of predictive simulations is required for their application in clinical contexts. Here, we suggest that using complex models is needed to yield such realism.

bioengineering↗

bioRxiv2020

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 feedback of center of mass position and velocity, but not local feedback of joint positions and 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.

neuroscience↗

bioRxiv2019

Ultrasound-based optimal parameter estimation improves assessment of calf muscle-tendon interaction during walking

We present and evaluate a new approach to estimate calf muscle-tendon parameters and calculate calf muscle-tendon function during walking. We used motion analysis, ultrasound, and EMG data of the calf muscles collected in six young and six older adults during treadmill walking as inputs to a new optimal estimation algorithm. We used estimated parameters or scaled generic parameters in an existing approach to calculate muscle fiber lengths and activations. We calculated the fit with experimental data in terms of root mean squared differences (RMSD) and coefficients of determination (R2). We also calculated the calf muscle metabolic energy cost. RMSD between measured and calculated fiber lengths and activations decreased and R2 increased when estimating parameters compared to using scaled generic parameters. Moreover, R2 between measured and calculated gastrocnemius medialis fiber length and soleus activations increased by 19 % and 70 %, and calf muscle metabolic energy decreased by 25% when using estimated parameters compared to using scaled generic parameters at speeds not used for estimation. This new approach estimates calf muscle-tendon parameters in good accordance with values reported in literature. The approach improves calculations of calf muscle-tendon interaction during walking and highlights the importance of individualizing calf muscle-tendon parameters.

bioengineering↗