Biology subjects

Bianco, N. A.

Publications and source records attributed to Bianco, N. A..

8 recordsLinked to original sources

bioRxiv2025

OPTIMIZING AN EXOTENDON AT AN INCREASED RUNNING SPEED

The exotendon is a passive device that reduces the energetic cost of running at 2.7 m/s, but its potential benefits at higher speeds remain unknown. Experimental testing is challenging because of the wide range of conditions that must be tested. Here, we use muscle-driven simulations to overcome this challenge and inform exotendon design. We validated a simulation framework that estimates changes in energy expenditure, body kinematics, and muscle activations when simulated subjects run with and without an exotendon. Simulations of people running at 4 m/s with the exotendon that saved energy at 2.7 m/s predicted a 10% reduction in energy cost compared to natural running. We then performed simulations of 25 designs and found that many of the designs saved energy. A longer, stiffer exotendon yielded slightly greater energy savings (12%). Longer and more compliant exotendons offered little savings. We plan to test a limited set of our simulation predictions in an experiment to evaluate their accuracy and assess how an exotendon impacts running performance at 4 m/s. The purpose of this paper is to present the simulation results and to make predictions about the performance of the runner-exotendon system in experiments. This paper has been posted before the experiments have begun to avoid informing the predictions from the experimental results.

bioengineering↗

bioRxiv2025

How peak knee loads are affected by changing the mass of lower-limb body segments during walking

For individuals with knee osteoarthritis, increased knee loading is linked to disease progression and pain. Some approaches to treating osteoarthritis, such as specialized footwear, braces, and powered exoskeletons, also increase the mass of the lower limbs, which could lead to increases in knee loads. Prior studies have investigated the effect of changes in torso mass and total body mass on peak knee contact forces, but the effects of increased leg mass remain unclear. In this study, we created musculoskeletal simulations informed by experimental data to estimate tibiofemoral knee contact force under different lower-limb segment mass conditions. The mass of the foot, shank, and thigh were varied by adding weights to each segment, separately and concurrently, as healthy young adults (N = 10) walked on a treadmill. Kinematics, kinetics, and muscle activity were recorded. Our simulations used an optimal control framework that enforced experimental kinematics while minimizing a combination of net joint moment errors and mismatch between measured and estimated muscle activity. The simulations revealed that adding mass to the lower-limb segments linearly increased early- and late-stance peaks in knee contact force, but that the slope of this relationship was different for each peak and each mass placement location. For each 1% of body weight (BW) added per limb (2% BW total) at the thigh, shank, and foot, early-stance peak knee contact force increased by 1.5%, 2.1%, and 5.9%, while late-stance peak contact force increased by 1.6%, 0.9% and 3.0%, respectively. Adding mass to the thigh and shank increases peak contact force at or below the rate of increase in body mass, while adding mass to the foot disproportionately increases peak knee contact force. These detrimental effects should be considered when designing interventions for osteoarthritis. Author summaryFor individuals with knee osteoarthritis, increased knee loading is linked to disease progression and pain. Some approaches to treating knee OA, such as specialized footwear, braces, and exoskeletons, increase the mass of the lower limbs, which could lead to increases in knee loads. However, the effects of changing lower limb segment mass on knee loading remain unclear. In this study, we created computer simulations informed by experimental data to estimate knee loads while walking with different amounts of added mass to the lower limb segments. We collected experimental data from 10 healthy participants while they walked on a treadmill with various amounts of mass added to their lower limb segments (thigh, shank, foot). We used these data and a biomechanically accurate model of each participant to construct realistic computer simulations, from which we obtained estimates of internal knee forces that contribute to total knee load. We found that peak knee load increased linearly with amount of added mass, but that this relationship differed by segment. Adding mass to the feet had the greatest effect on knee contact force. Our results can help to inform the design of interventions for knee osteoarthritis.

systems biology↗

bioRxiv2024

Personalizing a computational upper body model improves kinematic tracking in high range-of-motion arm movements

Musculoskeletal models of the shoulder are needed to understand the mechanics of overhead motions. Existing models can be scaled to represent the size of an individual person, but the kinematics are generic. We introduce a method to personalize the shoulder kinematics of a computational model of the upper body that defines the orientations of the clavicle and scapula based on glenohumeral joint angles. During five static calibration poses, we palpate and measure the orientation of the scapula. We explore the importance of representing shoulder elevation by introducing clavicle elevation as a degree of freedom that is independent of the glenohumeral angles. For ten subjects, we record the five calibration poses, ten additional static poses, and dynamic arm raises using optical motion capture. We examine the data using a dynamically-constrained inverse kinematics analysis. Personalization, independent clavicle elevation, and both in combination reduce the average upper body marker tracking error compared to the generic model in the static poses (26 mm to 17-20 mm) and in the dynamic trials (22 mm to 14-17 mm). Only personalization reduces the average scapula marker error (51 mm to 36-38 mm) and scapula axis-angle error (15{degrees} to 10{degrees}) in the static poses, and in the dynamic trials at instances that best match the static poses (53 mm to 37-40 mm, 15{degrees} to 9{degrees}). Our results show that personalizing upper body models improves kinematic tracking. We provide our experimental data, model, and methods to allow researchers to reproduce and build upon our results.

bioengineering↗

bioRxiv2023

AddBiomechanics: Automating model scaling, inverse kinematics, and inverse dynamics from human motion data through sequential optimization

Creating large-scale public datasets of human motion biomechanics could unlock data-driven breakthroughs in our understanding of human motion, neuromuscular diseases, and assistive devices. However, the manual effort currently required to process motion capture data and quantify the kinematics and dynamics of movement is costly and limits the collection and sharing of large-scale biomechanical datasets. We present a method, called AddBiomechanics, to automate and standardize the quantification of human movement dynamics from motion capture data. We use linear methods followed by a non-convex bilevel optimization to scale the body segments of a musculoskeletal model, register the locations of optical markers placed on an experimental subject to the markers on a musculoskeletal model, and compute body segment kinematics given trajectories of experimental markers during a motion. We then apply a linear method followed by another non-convex optimization to find body segment masses and fine tune kinematics to minimize residual forces given corresponding trajectories of ground reaction forces. The optimization approach requires approximately 3-5 minutes to determine a subjects skeleton dimensions and motion kinematics, and less than 30 minutes of computation to also determine dynamically consistent skeleton inertia properties and fine-tuned kinematics and kinetics, compared with about one day of manual work for a human expert. We used AddBiomechanics to automatically reconstruct joint angle and torque trajectories from previously published multi-activity datasets, achieving close correspondence to expert-calculated values, marker root-mean-square errors less than 2 cm, and residual force magnitudes smaller than 2% of peak external force. Finally, we confirmed that AddBiomechanics accurately reproduced joint kinematics and kinetics from synthetic walking data with low marker error and residual loads. We have published the algorithm as an open source cloud service at AddBiomechanics.org, which is available at no cost and asks that users agree to share processed and de-identified data with the community. As of this writing, hundreds of researchers have used the prototype tool to process and share about ten thousand motion files from about one thousand experimental subjects. Reducing the barriers to processing and sharing high-quality human motion biomechanics data will enable more people to use state-of-the-art biomechanical analysis, do so at lower cost, and share larger and more accurate datasets.

bioengineering↗

bioRxiv2022

Simulating the effect of ankle plantarflexion and inversion-eversion exoskeleton torques on center of mass kinematics during walking

Walking balance is central to independent mobility, and falls due to loss of balance are a leading cause of death for people 65 years of age and older. Bipedal gait is typically unstable, but healthy humans use corrective torques to counteract perturbations and stabilize gait. Exoskeleton assistance could benefit people with neuromuscular deficits by providing stabilizing torques at lower-limb joints to replace lost muscle strength and sensorimotor control. However, it is unclear how applied exoskeleton torques translate to changes in walking kinematics. This study used musculoskeletal simulation to investigate how exoskeleton torques applied to the ankle and subtalar joints alter center of mass kinematics during walking. We first created muscle-driven walking simulations using OpenSim Moco by tracking experimental kinematics and ground reaction forces recorded from five healthy adults. We then used forward integration to simulate the effect of exoskeleton torques applied to the ankle and subtalar joints while keeping muscle excitations fixed based on our previous tracking simulation results. Exoskeleton torque lasted for 15% of the gait cycle and was applied between foot-flat and toe-off during the stance phase, and changes in center of mass kinematics were recorded when the torque application ended. We found that changes in center of mass kinematics were dependent on both the type and timing of exoskeleton torques. Plantarflexion torques produced upward and backward changes in velocity of the center of mass in mid-stance and upward and forward velocity changes near toe-off. Eversion and inversion torques primarily produced lateral and medial changes in velocity in mid-stance, respectively. Intrinsic muscle properties reduced kinematic changes from exoskeleton torques. Our results provide mappings between ankle plantarflexion and inversion-eversion torques and changes in center of mass kinematics which can inform designers building exoskeletons aimed at stabilizing balance during walking. Our simulations and software are freely available and allow researchers to explore the effects of applied torques on balance and gait.

bioengineering↗

bioRxiv2021

Simulated hemiparesis increases optimal spatiotemporal gait asymmetry but not metabolic cost

Several neuromuscular impairments, such as weakness (hemiparesis), occur after an individual has a stroke, and these impairments primarily affect one side of the body more than the other. Predictive musculoskeletal modeling presents an opportunity to investigate how a specific impairment affects gait performance post-stroke. Therefore, our aim was to use to predictive simulation to quantify the spatiotemporal asymmetries and changes to metabolic cost that emerge when muscle strength is unilaterally reduced. We also determined how forced spatiotemporal symmetry affects metabolic cost. We modified a 2-D musculoskeletal model by uniformly reducing the peak isometric muscle force in all left-limb muscles. We then solved optimal control simulations of walking across a range of speeds by minimizing the sum of the cubed muscle excitations across all muscles. Lastly, we ran additional optimizations to test if reducing spatiotemporal asymmetry would result in an increase in metabolic cost. Our results showed that the magnitude and direction of effort-optimal spatiotemporal asymmetries depends on both the gait speed and level of weakness. Also, the optimal metabolic cost of transport was 1.25 m/s for the symmetrical and 20% weakness models but slower (1.00 m/s) for the 40% and 60% weakness models, suggesting that hemiparesis can account for a portion of the slower gait speed seen in people post-stroke. Adding spatiotemporal asymmetry to the cost function resulted in small increases (~4%) in metabolic cost. Overall, our results indicate that spatiotemporal asymmetry may be optimal for people post-stroke, who have asymmetrical neuromuscular impairments. Additionally, the effect of speed and level of weakness on spatiotemporal asymmetry may explain the well-known heterogenous distribution of spatiotemporal asymmetries observed in the clinic. Future work could extend our results by testing the effects of other impairments on optimal gait strategies, and therefore build a more comprehensive understanding of the gait patterns in people post-stroke. Author SummaryA stroke causes damage to the brain. This typically results in several changes to the nervous and muscular (neuromuscular) system that change how people post-stroke tend to walk and perform other tasks. Individuals post-stroke tend to walk with an asymmetrical motion and expend more energy while walking than other age-matched individuals. We still do not understand how each specific change to the neuromuscular system is linked with changes in walking patterns, in part because it is difficult to test one individual change at a time in people. Instead, we can use a mathematical model of the musculoskeletal system that represents the individual changes to the muscular system that occur in people post-stroke. In this study, we modeled how a common change in people post-stroke (muscle weakness) can impact walking patterns. We found that the level of weakness and the walking speed affect the asymmetrical walking patterns of our models, but do not change the total energy cost. Overall, our study is one step towards better understanding how neuromuscular changes in people post-stroke affects walking patterns. This knowledge could be applied to identify rehabilitation strategies that are most likely to improve walking in people post-stroke.

bioengineering↗

bioRxiv2021

Coupled exoskeleton assistance simplifies control and maintains metabolic benefits: a simulation study

Assistive exoskeletons can reduce the metabolic cost of walking, and recent advances in exoskeleton device design and control have resulted in large metabolic savings. Most exoskeleton devices provide assistance at either the ankle or hip. Exoskeletons that assist multiple joints have the potential to provide greater metabolic savings, but can require many actuators and complicated controllers, making it difficult to design effective assistance. Coupled assistance, when two or more joints are assisted using one actuator or control signal, could reduce control dimensionality while retaining metabolic benefits. However, it is unknown which combinations of assisted joints are most promising and if there are negative consequences associated with coupled assistance. Since designing assistance with human experiments is expensive and time-consuming, we used musculoskeletal simulation to evaluate metabolic savings from multi-joint assistance and identify promising joint combinations. We generated 2D muscle-driven simulations of walking while simultaneously optimizing control strategies for simulated lower-limb exoskeleton assistive devices to minimize metabolic cost. Each device provided assistance either at a single joint or at multiple joints using massless, ideal actuators. To assess if control could be simplified for multi-joint exoskeletons, we simulated different control strategies in which the torque provided at each joint was either controlled independently or coupled between joints. We compared the predicted optimal torque profiles and changes in muscle and whole-body metabolic power consumption across the single joint and multi-joint assistance strategies. We found multi-joint devices-whether independent or coupled-provided 50% greater metabolic savings than single joint devices. The coupled multi-joint devices were able to achieve most of the metabolic savings produced by independently-controlled multi-joint devices. Our results indicate that device designers could simplify multi-joint exoskeleton designs by reducing the number of torque control parameters through coupling, while still maintaining large reductions in metabolic cost.

bioengineering↗

bioRxiv2019

OpenSim Moco: Musculoskeletal optimal control

Musculoskeletal simulations of movement can provide insights needed to help humans regain mobility after injuries and design robots that interact with humans. Here, we introduce Open-Sim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation but requires extensive technical expertise to implement. Moco frees researchers from implementing direct collocation themselves, allowing them to focus on their scientific questions. The software can handle the wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which are common in musculoskeletal models. To show Mocos abilities, we first solve for muscle activity that produces an observed walking motion while minimizing muscle excitations and knee joint loading. Then, we predict a squat-to-stand motion and optimize the stiffness of a passive assistive knee device. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand human and animal movement.

bioengineering↗