Musculoskeletal Model Personalization Affects Metabolic Cost Estimates for Walking

Assessment of metabolic cost as a metric for human performance has expanded across various fields within the scientific, clinical, and engineering communities. As an alternative to measuring metabolic cost experimentally, musculoskeletal models incorporating metabolic cost models have been developed. However, to utilize these models for practical applications, the accuracy of their metabolic cost predictions requires improvement. Previous studies have reported the benefits of using personalized musculoskeletal models for various applications, yet no study has evaluated how model personalization affects metabolic cost estimation. This study investigated the effect of musculoskeletal model personalization on estimates of metabolic cost of transport (CoT) during post-stroke walking using three commonly used metabolic cost models. We analyzed walking data previously collected from two male stroke survivors with right-sided hemiparesis. The three metabolic cost models were implemented within three musculoskeletal modeling approaches involving different levels of personalization. The first approach used a scaled generic OpenSim model and found muscle activations via static optimization (SOGen). The second approach used a personalized electromyographic (EMG)-driven musculoskeletal model with personalized functional axes but found muscle activations via static optimization (SOCal). The third approach used the same personalized EMG-driven model but calculated muscle activations directly from EMG data (EMGCal). For each approach, the muscle activation estimates were used to calculate each subject’s CoT at different gait speeds using three metabolic cost models (Umberger et al., 2003; Bhargava et al., 2004; Umberger, 2010). The calculated CoT values were compared with published CoT data as a function of walking speed, step length asymmetry, stance time asymmetry, double support time asymmetry, and severity of motor impairment (i.e., Fugl-Meyer score). Overall, only SOCal and EMGCal with the Bhargava metabolic cost model were able to reproduce accurately published experimental trends between CoT and various clinical measures of walking asymmetry post-stroke. Tuning of the parameters in the different metabolic cost models could potentially resolve the observed CoT magnitude differences between model predictions and experimental measurements. Realistic CoT predictions may allow researchers to predict human performance, surgical outcomes, and rehabilitation outcomes reliably using computational simulations.

Download Full-text

Musculoskeletal Model Personalization Affects Metabolic Cost Estimates for Walking

10.1101/2020.08.05.238857 ◽

2020 ◽

Author(s):

Marleny Arones ◽

Mohammad Shourijeh ◽

Carolynn Patten ◽

Benjamin J. Fregly

Keyword(s):

Human Performance ◽

Metabolic Cost ◽

Musculoskeletal Model ◽

Metabolic Energy ◽

Cost Models ◽

Cost Of Transport ◽

Static Optimization ◽

Musculoskeletal Models ◽

Muscle Activations ◽

Model Personalization

AbstractAssessment of metabolic energy cost as a metric for human performance has expanded across various fields within the scientific, clinical, and engineering communities. As an alternative to measuring metabolic cost experimentally, musculoskeletal models incorporating metabolic cost models have been developed. However, to utilize these models for practical applications, the accuracy of their metabolic cost predictions requires improvement. Previous studies have reported the benefits of using personalized musculoskeletal models for various applications, yet no study has evaluated how model personalization affects metabolic cost estimation. This study investigated the effect of musculoskeletal model personalization on estimates of metabolic cost of transport (CoT) during post-stroke walking using three commonly used metabolic cost models. We analyzed data previously collected from two male stroke survivors with right-sided hemiparesis. The three metabolic cost models were implemented within three musculoskeletal modeling approaches involving different levels of personalization. The first approach used a scaled generic OpenSim model and found muscle activations via static optimization (SOGen). The second approach used a personalized EMG-driven musculoskeletal model with personalized functional axes but found muscle activations via static optimization (SOCal). The third approach used the same personalized EMG-driven model but calculated muscle activations directly from EMG data (EMGCal). For each approach, the muscle activation estimates were used to calculate each subject’s cost of transport (CoT) at different gait speeds using three metabolic cost models (Umberger 2003, Umberger 2010, and Bhargava 2004). The calculated CoT values were compared with published CoT trends as a function of stance time, double support time, step positions, walking speed, and severity of motor impairment (i.e., Fugl-Meyer score). Overall, U10-SOCal, U10-EMGCal, U03-SOCal, and U03-EMGCal were able to produce slopes between CoT and the different measures of walking asymmetry that were statistically similar to those found in the literature. Although model personalization seemed to improve CoT estimates, further tuning of parameters associated with the different metabolic cost models in future studies may allow for realistic CoT predictions. An improvement in CoT predictions may allow researchers to predict human performance, surgical, and rehabilitation outcomes reliably using computational simulations.

Download Full-text

Disentangling the energetic costs of step time asymmetry and step length asymmetry in human walking

Journal of Experimental Biology ◽

10.1242/jeb.242258 ◽

2021 ◽

Author(s):

Jan Stenum ◽

Julia T. Choi

Keyword(s):

Energy Cost ◽

Metabolic Cost ◽

Step Length ◽

Human Walking ◽

Metabolic Power ◽

Healthy Human ◽

Time Asymmetry ◽

Double Support ◽

Post Stroke ◽

The Cost

The metabolic cost of walking in healthy individuals increases with spatiotemporal gait asymmetries. Pathological gait, such as post-stroke, often has asymmetry in step lengths and step times which may contribute to an increased energy cost. But paradoxically, enforcing step length symmetry does not reduce metabolic cost of post-stroke walking. The isolated and interacting costs of asymmetry in step times and step lengths remain unclear, because previous studies did not simultaneously enforce spatial and temporal gait asymmetries. Here, we delineate isolated costs of asymmetry in step times and step lengths in healthy human walking. We first show that the cost of step length asymmetry is predicted by the cost of taking two non-preferred step lengths (one short and one long), but that step time asymmetry adds an extra cost beyond the cost of non-preferred step times. The metabolic power of step time asymmetry is about 2.5 times greater than the cost of step length asymmetry. Furthermore, the costs are not additive when walking with asymmetric step times and step lengths: metabolic power of concurrent asymmetry in step lengths and step times is driven by the cost of step time asymmetry alone. The metabolic power of asymmetry is explained by positive mechanical power produced during single support phases to compensate for a net loss of center of mass power incurred during double support phases. These data may explain why metabolic cost remains invariant to step length asymmetry in post-stroke walking and suggests how effects of asymmetry on energy cost can be attenuated.

Download Full-text

Muscle Metabolic Energy Costs While Modifying Propulsive Force Generation During Walking

10.1101/2020.07.31.230698 ◽

2020 ◽

Author(s):

Richard E. Pimentel ◽

Noah L. Pieper ◽

William H. Clark ◽

Jason R. Franz

Keyword(s):

Young Adults ◽

Metabolic Cost ◽

Metabolic Energy ◽

Energy Costs ◽

Joint Power ◽

Lower Limb Muscles ◽

Age Related ◽

Musculoskeletal Models ◽

Metabolic Costs ◽

Related Increase

AbstractWe pose that an age-related increase in the metabolic cost of walking arises in part from a redistribution of joint power where muscles spanning the hip compensate for insufficient ankle push-off and smaller peak propulsive forces (FP). Young adults elicit a similar redistribution when walking with smaller FP via biofeedback. We used targeted FP biofeedback and musculoskeletal models to estimate the metabolic costs of operating lower limb muscles in young adults walking across a range of FP. Our simulations support the theory of distal-to-proximal redistribution of joint power as a determinant of increased metabolic cost in older adults during walking.

Download Full-text

Preliminary Validation of Upper Limb Musculoskeletal Model using Static Optimization

10.1109/embc46164.2021.9629494 ◽

2021 ◽

Author(s):

Yujun Lai ◽

Sheila Sutjipto ◽

Marc G. Carmichael ◽

Gavin Paul

Keyword(s):

Upper Limb ◽

Musculoskeletal Model ◽

Static Optimization ◽

Preliminary Validation

Download Full-text

The Effects of Walking Speed on Tibiofemoral Loading Estimated Via Musculoskeletal Modeling

Journal of Applied Biomechanics ◽

10.1123/jab.2012-0206 ◽

2014 ◽

Vol 30 (2) ◽

pp. 197-205 ◽

Cited By ~ 23

Author(s):

Zachary F. Lerner ◽

Derek J. Haight ◽

Matthew S. DeMers ◽

Wayne J. Board ◽

Raymond C. Browning

Keyword(s):

Walking Speed ◽

Inverse Dynamics ◽

Knee Extension ◽

Musculoskeletal Model ◽

Contact Forces ◽

Muscle Forces ◽

Musculoskeletal Models ◽

Peak Knee ◽

Muscle Moments ◽

Vector Sum

Net muscle moments (NMMs) have been used as proxy measures of joint loading, but musculoskeletal models can estimate contact forces within joints. The purpose of this study was to use a musculoskeletal model to estimate tibiofemoral forces and to examine the relationship between NMMs and tibiofemoral forces across walking speeds. We collected kinematic, kinetic, and electromyographic data as ten adult participants walked on a dual-belt force-measuring treadmill at 0.75, 1.25, and 1.50 m/s. We scaled a musculoskeletal model to each participant and used OpenSim to calculate the NMMs and muscle forces through inverse dynamics and weighted static optimization, respectively. We determined tibiofemoral forces from the vector sum of intersegmental and muscle forces crossing the knee. Estimated tibiofemoral forces increased with walking speed. Peak earlystance compressive tibiofemoral forces increased 52% as walking speed increased from 0.75 to 1.50 m/s, whereas peak knee extension NMMs increased by 168%. During late stance, peak compressive tibiofemoral forces increased by 18% as speed increased. Although compressive loads at the knee did not increase in direct proportion to NMMs, faster walking resulted in greater compressive forces during weight acceptance and increased compressive and anterior/posterior tibiofemoral loading rates in addition to a greater abduction NMM.

Download Full-text

Persons post-stroke improve step length symmetry by walking asymmetrically

10.21203/rs.2.21659/v2 ◽

2020 ◽

Author(s):

Purnima Padmanabhan ◽

Keerthana Sreekanth ◽

Shivam Gulhar ◽

Kendra M. Cherry-Allen ◽

Kristan A. Leech ◽

...

Keyword(s):

Center Of Mass ◽

Metabolic Cost ◽

Step Length ◽

Gait Pattern ◽

Future Research ◽

Cost Of Transport ◽

Post Stroke ◽

Paretic Limb ◽

Gait Parameters ◽

The Many

Abstract Background Restoration of step length symmetry is a common rehabilitation goal after stroke. Persons post-stroke often retain the ability to walk with symmetric step lengths ("symmetric steps") at an elevated metabolic cost relative to healthy adults. Two key questions with direct implications for rehabilitation have emerged: 1) how do persons post-stroke generate symmetric steps, and 2) why do symmetric steps remain so effortful? Here, we aimed to understand how persons post-stroke generate symmetric steps and explored how the resulting gait pattern may relate to the metabolic cost of transport. Methods We recorded kinematic, kinetic, and metabolic data as nine persons post-stroke walked on an instrumented treadmill under two conditions: preferred walking and symmetric stepping (using visual feedback). Results Gait kinematics and kinetics remained markedly asymmetric even when persons post-stroke improved step length symmetry. Impaired paretic propulsion and abnormal movement of the center of mass were evident during both preferred walking and symmetric stepping. These deficits contributed to diminished positive work performed by the paretic limb on the center of mass in both conditions. Within each condition, decreased positive paretic work correlated with increased metabolic cost of transport and decreased walking speed across participants. Conclusions It is critical to consider the mechanics used to restore symmetric steps when designing interventions to improve walking after stroke. Future research should consider the many dimensions of asymmetry in post-stroke gait, and additional within-participant manipulations of gait parameters are needed to improve our understanding of the elevated metabolic cost of walking after stroke.

Download Full-text

Simulated hemiparesis increases optimal spatiotemporal gait asymmetry but not metabolic cost

10.1101/2021.12.20.473515 ◽

2021 ◽

Author(s):

Russell T Johnson ◽

Nicholas August Bianco ◽

James Finley

Keyword(s):

Gait Speed ◽

Metabolic Cost ◽

The Body ◽

Musculoskeletal Modeling ◽

Cost Of Transport ◽

Gait Patterns ◽

Post Stroke ◽

The Cost ◽

Future Work ◽

Isometric Muscle

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 muscles unilaterally. 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.

Download Full-text

Lower Limb Assistive Device Design Optimization Using Musculoskeletal Modeling: A Review

Journal of Medical Devices ◽

10.1115/1.4044739 ◽

2019 ◽

Vol 13 (4) ◽

Cited By ~ 4

Author(s):

Emerson Paul Grabke ◽

Kei Masani ◽

Jan Andrysek

Keyword(s):

Design Optimization ◽

Lower Limb ◽

Musculoskeletal Model ◽

Musculoskeletal Modeling ◽

Model Complexity ◽

Clinical Population ◽

Assistive Device ◽

Patient Specific ◽

Device Design ◽

Musculoskeletal Models

Abstract Many individuals with lower limb amputations or neuromuscular impairments face mobility challenges attributable to suboptimal assistive device design. Forward dynamic modeling and simulation of human walking using conventional biomechanical gait models offer an alternative to intuition-based assistive device design, providing insight into the biomechanics underlying pathological gait. Musculoskeletal models enable better understanding of prosthesis and/or exoskeleton contributions to the human musculoskeletal system, and device and user contributions to both body support and propulsion during gait. This paper reviews current literature that have used forward dynamic simulation of clinical population musculoskeletal models to perform assistive device design optimization using optimal control, optimal tracking, computed muscle control (CMC) and reflex-based control. Musculoskeletal model complexity and assumptions inhibit forward dynamic musculoskeletal modeling in its current state, hindering computational assistive device design optimization. Future recommendations include validating musculoskeletal models and resultant assistive device designs, developing less computationally expensive forward dynamic musculoskeletal modeling methods, and developing more efficient patient-specific musculoskeletal model generation methods to enable personalized assistive device optimization.

Download Full-text

Influence of the Level of Muscular Redundancy on the Validity of a Musculoskeletal Model

Journal of Biomechanical Engineering ◽

10.1115/1.4032127 ◽

2016 ◽

Vol 138 (2) ◽

Cited By ~ 10

Author(s):

Florent Moissenet ◽

Laurence Chèze ◽

Raphaël Dumas

Keyword(s):

Gait Pattern ◽

Musculoskeletal Model ◽

Contact Forces ◽

Generic Model ◽

Grand Challenge ◽

Contact Points ◽

Lateral Contact ◽

Musculoskeletal Models ◽

Joint Contact

While recent literature has clearly demonstrated that an extensive personalization of the musculoskeletal models was necessary to reach high accuracy, several components of the generic models may be further investigated before defining subject-specific parameters. Among others, the choice in muscular geometry and thus the level of muscular redundancy in the model may have a noticeable influence on the predicted musculotendon and joint contact forces. In this context, the aim of this study was to investigate if the level of muscular redundancy can contribute or not to reduce inaccuracies in tibiofemoral contact forces predictions. For that, the dataset disseminated through the Sixth Grand Challenge Competition to Predict In Vivo Knee Loads was applied to a versatile 3D lower limb musculoskeletal model in which two muscular geometries (i.e., two different levels of muscular redundancy) were implemented. This dataset provides tibiofemoral implant measurements for both medial and lateral compartments and thus allows evaluation of the validity of the model predictions. The results suggest that an increase of the level of muscular redundancy corresponds to a better accuracy of total tibiofemoral contact force whatever the gait pattern investigated. However, the medial and lateral contact forces ratio and accuracy were not necessarily improved when increasing the level of muscular redundancy and may thus be attributed to other parameters such as the location of contact points. To conclude, the muscular geometry, among other components of the generic model, has a noticeable impact on joint contact forces predictions and may thus be correctly chosen even before trying to personalize the model.

Download Full-text