Virtual muscles and reflex control generates human-like ankle torques during gait perturbations.

A biologically-inspired actuation system, including muscles, spinal reflexes, and vestibular feedback, may be capable of achieving more natural gait mechanics in powered prostheses or exoskeletons. In this study, we developed a Virtual Muscle Reflex (VMR) system to control ankle torque and tuned it using data from human responses to anteroposterior mechanical perturbations at three walking speeds. The system consists of three Hill-Type muscles, simulated in real time, and uses feedback from ground reaction force and from stretch sensors on the virtual muscle fibers.

A comprehensive dataset on biomechanics and motor control during human walking with discrete mechanical perturbations.

Background: Humans have a remarkable capability to maintain balance while walking. There is, however, a lack of publicly available research data on reactive responses to destabilizing perturbations during gait.

Methods: Here, we share a comprehensive dataset collected from 10 participants who experienced random perturbations while walking on an instrumented treadmill.

Model-based estimation of muscle and ACL forces during turning maneuvers in alpine skiing.

In alpine skiing, estimation of the muscle forces and joint loads such as the forces in the ACL of the knee are essential to quantify the loading pattern of the skier during turning maneuvers. Since direct measurement of these forces is generally not feasible, non-invasive methods based on musculoskeletal modeling should be considered. In alpine skiing, however, muscle forces and ACL forces have not been analyzed during turning maneuvers due to the lack of three dimensional musculoskeletal models.

Data-Driven Dynamic Motion Planning for Practical FES-Controlled Reaching Motions in Spinal Cord Injury.

Functional electrical stimulation (FES) is a promising technology for restoring reaching motions to individuals with upper-limb paralysis caused by a spinal cord injury (SCI). However, the limited muscle capabilities of an individual with SCI have made achieving FES-driven reaching difficult. We developed a novel trajectory optimization method that used experimentally measured muscle capability data to find feasible reaching trajectories.

Estimation of Joint Moments During Turning Maneuvers in Alpine Skiing Using a Three Dimensional Musculoskeletal Skier Model and a Forward Dynamics Optimization Framework.

In alpine skiing, estimation of the joint moments acting onto the skier is essential to quantify the loading of the skier during turning maneuvers. In the present study, a novel forward dynamics optimization framework is presented to estimate the joint moments acting onto the skier incorporating a three dimensional musculoskeletal model (53 kinematic degrees of freedom, 94 muscles). Kinematic data of a professional skier performing a turning maneuver were captured and used as input data to the optimization framework.

Antagonistic co-contraction can minimize muscular effort in systems with uncertainty.

Muscular co-contraction of antagonistic muscle pairs is often observed in human movement, but it is considered inefficient and it can currently not be predicted in simulations where muscular effort or metabolic energy are minimized. Here, we investigated the relationship between minimizing effort and muscular co-contraction in systems with random uncertainty to see if muscular co-contraction can minimize effort in such system. We also investigated the effect of time delay in the muscle, by varying the time delay in the neural control as well as the activation time constant.

Predicting neuromuscular control patterns that minimize ACL forces during injury-prone jump-landing manoeuvres in downhill skiing using a musculoskeletal simulation model.

Competitive skiers encounter a high risk of sustaining an ACL injury during jump-landing in downhill ski racing. Facing an injury-prone landing manoeuvre, there is a lack of knowledge regarding optimum control strategies. So, the purpose of the present study was to investigate possible neuromuscular control patterns to avoid injury during injury-prone jump-landing manoeuvres.

Early evaluation of a powered transfemoral prosthesis with force-modulated impedance control and energy regeneration.

Individuals with an above-knee (AK) amputation typically use passive prostheses, whether reactive (microprocessor) or purely mechanical. Though sufficient for walking, these solutions lack the positive power generation observed in able-bodied individuals. Active (powered) prostheses can provide positive power but suffer complex control and limited energy storage capacities.

A progressive-individualized midstance gait perturbation protocol for reactive balance assessment in stroke survivors.

Restoration of balance control is a primary focus of rehabilitation after a stroke. The study developed a gait perturbation, treadmill-based, balance assessment protocol and demonstrated that it can be used to quantify improvements in reactive balance responses among individuals post-stroke. The protocol consists of a sequence of fifteen 90-second treadmill walking trials, with a single perturbation applied during the middle third of each trial.

An Anthropometrically Parameterized Assistive Lower Limb Exoskeleton.

This paper presents an innovative design methodology for development of lower limb exoskeletons with the fabrication and experimental evaluation of prototype hardware. The proposed design approach is specifically conceived to be suitable for the pediatric population and uses additive manufacturing and a model parameterized in terms of subject anthropometrics to give a person-specific custom fit. The methodology is applied to create computer-aided design models using average anthropometrics of children 6-11 years old and using anthropometrics of an individual measured by the researchers.

Review of musculoskeletal modelling in a clinical setting: Current use in rehabilitation design, surgical decision making and healthcare interventions.

Background: Musculoskeletal modelling is a common means by which to non-invasively analyse movement. Such models have largely been used to observe function in both healthy and patient populations. However, utility in a clinical environment is largely unknown.

Identification of Postural Controllers in Human Standing Balance.

Standing balance is a simple motion task for healthy humans but the actions of the central nervous system (CNS) have not been described by generalized and sufficiently sophisticated control laws. While system identification approaches have been used to extracted models of the CNS, they either focus on short balance motions, leading to task-specific control laws, or assume that the standing balance system is linear. To obtain comprehensive control laws for human standing balance, complex balance motions, long duration tests, and nonlinear controller models are all needed.

A model-based approach to predict neuromuscular control patterns that minimize ACL forces during jump landing.

Jump landing is a common situation leading to knee injuries involving the anterior cruciate ligament (ACL) in sports. Although neuromuscular control is considered as a key injury risk factor, there is a lack of knowledge regarding optimum control strategies that reduce ACL forces during jump landing. In the present study, a musculoskeletal model-based computational approach is presented that allows identifying neuromuscular control patterns that minimize ACL forces during jump landing.

Efficient trajectory optimization for curved running using a 3D musculoskeletal model with implicit dynamics.

Trajectory optimization with musculoskeletal models can be used to reconstruct measured movements and to predict changes in movements in response to environmental changes. It enables an exhaustive analysis of joint angles, joint moments, ground reaction forces, and muscle forces, among others. However, its application is still limited to simplified problems in two dimensional space or straight motions.

CNN-Based Estimation of Sagittal Plane Walking and Running Biomechanics From Measured and Simulated Inertial Sensor Data.

Machine learning is a promising approach to evaluate human movement based on wearable sensor data. A representative dataset for training data-driven models is crucial to ensure that the model generalizes well to unseen data. However, the acquisition of sufficient data is time-consuming and often infeasible.

A solution method for predictive simulations in a stochastic environment.

Predictive gait simulations currently do not account for environmental or internal noise. We describe a method to solve predictive simulations of human movements in a stochastic environment using a collocation method. The optimization is performed over multiple noisy episodes of the trajectory, instead of a single episode in a deterministic environment.

Model-Based Control of Individual Finger Movements for Prosthetic Hand Function.

Prosthetic devices for hand difference have advanced considerably in recent years, to the point where the mechanical dexterity of a state-of-the-art prosthetic hand approaches that of the natural hand. Control options for users, however, have not kept pace, meaning that the new devices are not used to their full potential. Promising developments in control technology reported in the literature have met with limited commercial and clinical success.

Identification of the human postural control system through stochastic trajectory optimization.

Background: System identification can be used to obtain a model of the human postural control system from experimental data in which subjects are mechanically perturbed while standing. However, unstable controllers were sometimes found, which obviously do not explain human balance and cannot be applied in control of humanoid robots. Eigenvalue constraints can be used to avoid unstable controllers.

ISB recommendations on the reporting of intersegmental forces and moments during human motion analysis.

The International Society of Biomechanics (ISB) has charged this committee with development of a standard similar in scope to the kinematic standard proposed in Wu et al. (2002) and Wu et al. (2005).

Metabolic cost calculations of gait using musculoskeletal energy models, a comparison study.

This paper compares predictions of metabolic energy expenditure in gait using seven metabolic energy expenditure models to assess their correlation with experimental data. Ground reaction forces, marker data, and pulmonary gas exchange data were recorded for six walking trials at combinations of two speeds, 0.8 m/s and 1.

Estimation of gait kinematics and kinetics from inertial sensor data using optimal control of musculoskeletal models.

Inertial sensing enables field studies of human movement and ambulant assessment of patients. However, the challenge is to obtain a comprehensive analysis from low-quality data and sparse measurements. In this paper, we present a method to estimate gait kinematics and kinetics directly from raw inertial sensor data performing a single dynamic optimization.

Optimal control simulation predicts effects of midsole materials on energy cost of running.

Testing sports equipment with athletes is costly, time-consuming, hazardous and sometimes impracticable. We propose a method for virtual testing of running shoes and predict how midsoles made of BOOST affect energy cost of running. We contribute a visco-elastic contact model and identified model parameters based on load-displacement measurements.

A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait.

Whether humans minimize metabolic energy in gait is unknown. Gradient-based optimization could be used to predict gait without using walking data but requires a twice differentiable metabolic energy model. Therefore, the metabolic energy model of Umberger et al.

Peak ACL force during jump landing in downhill skiing is less sensitive to landing height than landing position.

Background: Competitive skiers face a high risk of sustaining an ACL injury during jump landing in downhill skiing. There is a lack of knowledge on how landing height affects this risk.

Objectives: To evaluate the effect of varied landing height on peak ACL force during jump landing and to compare the effect of the landing height with the effect of the landing position varied by the trunk lean of the skier.

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.