Patterns of asymmetry and energy cost generated from predictive simulations of hemiparetic gait

Perturbation-based estimation of within-stride cycle metabolic cost

Metabolic cost greatly impacts trade-offs within a variety of human movements. Standard respiratory measurements only obtain the mean cost of a movement cycle, preventing understanding of the contributions of different phases in, for example, walking. We present a method that estimates the within-stride cost of walking by leveraging measurements under different force perturbations. The method reproduces time series with greater consistency (r = 0.55 and 0.80 in two datasets) than previous model-based estimations (r = 0.29). This perturbation-based method reveals how the cost of push-off (10%) is much smaller than would be expected from positive mechanical work (~ 70%). This work elucidates the costliest phases during walking, offering new targets for assistive devices and rehabilitation strategies.

NSF DARE-transforming modeling in neurorehabilitation: a patient-in-the-loop framework

In 2023, the National Science Foundation (NSF) and the National Institute of Health (NIH) brought together engineers, scientists, and clinicians by sponsoring a conference on computational modelling in neurorehabiilitation. To facilitate multidisciplinary collaborations and improve patient care, in this perspective piece we identify where and how computational modelling can support neurorehabilitation. To address the where, we developed a patient-in-the-loop framework that uses multiple and/or continual measurements to update diagnostic and treatment model parameters, treatment type, and treatment prescription, with the goal of maximizing clinically-relevant functional outcomes. This patient-in-the-loop framework has several key features: (i) it includes diagnostic and treatment models, (ii) it is clinically-grounded with the International Classification of Functioning, Disability and Health (ICF) and patient involvement, (iii) it uses multiple or continual data measurements over time, and (iv) it is applicable to a range of neurological and neurodevelopmental conditions. To address the how, we identify state-of-the-art and highlight promising avenues of future research across the realms of sensorimotor adaptation, neuroplasticity, musculoskeletal, and sensory & pain computational modelling. We also discuss both the importance of and how to perform model validation, as well as challenges to overcome when implementing computational models within a clinical setting. The patient-in-the-loop approach offers a unifying framework to guide multidisciplinary collaboration between computational and clinical stakeholders in the field of neurorehabilitation.

Design and characterization of a variable-stiffness ankle-foot orthosis

BACKGROUND

Ankle-foot orthoses (AFOs) are a type of assistive device that can improve the walking ability of individuals with neurological disorders. Adjusting stiffness is a common way to customize settings according to individuals' impairment.

OBJECTIVE

This study aims to design a variable-stiffness AFO by stiffness module and characterize the AFO stiffness range to provide subject-specific settings for the users.

METHODS

We modeled AFO using bending beams with varying fulcrum positions to adjust the stiffness. To characterize the stiffness range and profile, we used the superposition method to generate the theoretical model to analyze the AFO numerically. The intrinsic deformation of the bending beam in the AFO is considered a combination of 2 bending deformations to replicate actual bending conditions. The corresponding experiments in different fulcrum positions were performed to compare with and optimize the theoretical model. The curve fitting method was applied to tune the theoretical model by adding a fulcrum position-related coefficient.

RESULTS

The AFO stiffness increased as the fulcrum moved to the proximal position. The maximum stiffness obtained was 1.77 Nm/° at a 6-cm fulcrum position, and the minimum stiffness was 0.82 Nm/° at a 0.5-cm fulcrum position with a 0.43-cm thick fiberglass beam. The corresponding theoretical model had maximum and minimum stiffness of 1.71 and 0.80 Nm/°, respectively. The theoretical model had a 4.08% difference compared with experimental values.

CONCLUSIONS

The stiffness module can provide adjustable stiffness with the fulcrum position and different kinds of fiberglass bars, especially the thickness and material of the beam. The theoretical model with different fulcrum positions can be used to profile the real-time stiffness of the AFO in a dynamic motion and to determine the appropriate dimensions of the bending beam.

Higher coactivations of lower limb muscles increase stability during walking on slippery ground in forward dynamics musculoskeletal simulation

The energy efficiency theory of human bipedal locomotion has been widely accepted as a neuro-musculoskeletal control method. However, coactivation of agonist and antagonist muscles in the lower limb has been observed during various limb movements, including walking. The emergence of this coactivation cannot be explained solely by the energy efficiency theory and remains a subject of debate. To shed light on this, we investigated the role of muscle coactivations in walking stability using a forward dynamics musculoskeletal simulation combined with neural-network-based gait controllers. Our study revealed that a gait controller with minimal muscle activations had a high probability of falls under challenging gait conditions such as slippery ground and uneven terrain. Lower limb muscle coactivations emerged in the process of gait controller training on slippery ground. Controllers with physiological coactivation levels demonstrated a significantly reduced probability of falls. Our results suggest that achieving stable walking requires muscle coactivations beyond the minimal level of muscle energy. This study implies that coactivations likely emerge to maintain gait stability under challenging conditions, and both coactivation and energy optimization of lower limb muscles should be considered when exploring the foundational control mechanisms of human walking.

Muscle-driven simulations and experimental data of cycling

Muscle-driven simulations have provided valuable insights in studies of walking and running, but a set of freely available simulations and corresponding experimental data for cycling do not exist. The aim of this work was to develop a set of muscle-driven simulations of cycling and to validate them by comparison with experimental data. We used direct collocation to generate simulations of 16 participants cycling over a range of powers (40-216 W) and cadences (75-99 RPM) using two optimization objectives: a baseline objective that minimized muscle effort and a second objective that additionally minimized tibiofemoral joint forces. We tested the accuracy of the simulations by comparing the timing of active muscle forces in our baseline simulation to timing in experimental electromyography data. Adding a term in the objective function to minimize tibiofemoral forces preserved cycling power and kinematics, improved similarity between active muscle force timing and experimental electromyography, and decreased tibiofemoral joint reaction forces, which better matched previously reported in vivo measurements. The musculoskeletal models, muscle-driven simulations, simulation software, and experimental data are freely shared at https://simtk.org/projects/cycling_sim for others to reproduce these results and build upon this research.

Effects of soft robotic exosuit on ambulation ability in stroke patients: a systematic review

BACKGROUND

Robot-assisted gait training is incorporated into guidelines for stroke rehabilitation. It is a promising tool combined with conventional therapy for low ambulatory patients. The heavy weight and bulky appearance of a robotic exoskeleton limits its practicality. On the other hand, soft robotic exosuit (SRE) based on its light weight and inconspicuous property, is better tolerated by patients in daily life. The aim of this study is to review the efficacy of the SRE with regard to walking ability and biomechanical properties in stroke patients.

METHODS

Electronic searches were carried out in PubMed, Embase, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database. Clinical trials that investigated the effectiveness of SREs on ambulation ability in patients with post-stroke hemiparesis were eligible. Qualitative data synthesis was subsequently performed.

RESULTS

Nine studies were identified as relevant, involving a total of 83 patients. For the assessment of SRE efficacy, outcome measures were walking ability and biomechanical properties. In terms of both immediate effect and training effect, SREs improved the walking speed, walking distance, peak ankle dorsiflexion angle during swing phase, peak paretic propulsion, stride length and compensated gait in stroke patients.

CONCLUSIONS

SRE improved the ambulation ability of stroke patients in terms of walking ability and biomechanical properties. The small number of studies limits the generalizability of interpretation. More controlled studies with better quality are required to reach a more solid conclusion on this issue.

Minimum effort simulations of split-belt treadmill walking exploit asymmetry to reduce metabolic energy expenditure

Walking on a split-belt treadmill elicits an adaptation response that changes baseline step length asymmetry. The underlying causes of this adaptation, however, are difficult to determine. It has been proposed that effort minimization may drive this adaptation, based on the idea that adopting longer steps on the fast belt, or positive step length asymmetry (SLA), can cause the treadmill to exert net-positive mechanical work on a bipedal walker. However, humans walking on split-belt treadmills have not been observed to reproduce this behavior when allowed to freely adapt. To determine if an effort-minimization motor control strategy would result in experimentally observed adaptation patterns, we conducted simulations of walking on different combinations of belt speeds with a human musculoskeletal model that minimized muscle excitations and metabolic rate. The model adopted increasing amounts of positive SLA and decreased its net metabolic rate with increasing belt speed difference, reaching +42.4% SLA and -5.7% metabolic rate relative to tied-belt walking at our maximum belt speed ratio of 3:1. These gains were primarily enabled by an increase in braking work and a reduction in propulsion work on the fast belt. The results suggest that a purely effort minimization driven split-belt walking strategy would involve substantial positive SLA, and that the lack of this characteristic in human behavior points to additional factors influencing the motor control strategy, such as aversion to excessive joint loads, asymmetry, or instability.NEW & NOTEWORTHY Behavioral observations of split-belt treadmill adaptation have been inconclusive toward its underlying causes. To estimate gait patterns when driven exclusively by one of these possible underlying causes, we simulated split-belt treadmill walking with a musculoskeletal model that minimized its summed muscle excitations. Our model took significantly longer steps on the fast belt and reduced its metabolic rate below tied-belt walking, unlike experimental observations. This suggests that asymmetry is energetically optimal, but human adaptation involves additional factors.

Age-related changes in gait biomechanics and their impact on the metabolic cost of walking: Report from a National Institute on Aging workshop

Changes in old age that contribute to the complex issue of an increased metabolic cost of walking (mass-specific energy cost per unit distance traveled) in older adults appear to center at least in part on changes in gait biomechanics. However, age-related changes in energy metabolism, neuromuscular function and connective tissue properties also likely contribute to this problem, of which the consequences are poor mobility and increased risk of inactivity-related disease and disability. The U.S. National Institute on Aging convened a workshop in September 2021 with an interdisciplinary group of scientists to address the gaps in research related to the mechanisms and consequences of changes in mobility in old age. The goal of the workshop was to identify promising ways to move the field forward toward improving gait performance, decreasing energy cost, and enhancing mobility for older adults. This report summarizes the workshop and brings multidisciplinary insight into the known and potential causes and consequences of age-related changes in gait biomechanics. We highlight how gait mechanics and energy cost change with aging, the potential neuromuscular mechanisms and role of connective tissue in these changes, and cutting-edge interventions and technologies that may be used to measure and improve gait and mobility in older adults. Key gaps in the literature that warrant targeted research in the future are identified and discussed.