Validation of forward simulations to predict the effects of bilateral plantarflexor weakness on gait

Waterval, Niels F.J.; Veerkamp, K.; Geijtenbeek, Thomas; Harlaar, Jaap; Nollet, Frans; Brehm, Merel-Anne; Krogt, Marjolein M. van der

doi:10.1016/j.gaitpost.2021.04.020

Cited by 36 publications

(71 citation statements)

References 34 publications

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“…In order to improve the AFO stiffness provision, research should focus on creating comprehensive recommendations including all relevant factors to select the individual optimal AFO stiffness. Besides body weight and type of impairment, previous work indicated that higher walking speeds [ 10 ] and severity of (calf muscle) weakness [ 4 , 23 ] influence gait biomechanics and the optimal stiffness. To determine the precise influence of these factors and their interactions on the optimal stiffness, simulations should be used as these, unlike human experiments, allow for independent and systematic manipulations of multiple subject-characteristics.…”

Section: Discussionmentioning

confidence: 99%

Individual stiffness optimization of dorsal leaf spring ankle–foot orthoses in people with calf muscle weakness is superior to standard bodyweight-based recommendations

Waterval

Brehm

Harlaar

et al. 2021

J NeuroEngineering Rehabil

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Background In people with calf muscle weakness, the stiffness of dorsal leaf spring ankle–foot orthoses (DLS-AFO) needs to be individualized to maximize its effect on walking. Orthotic suppliers may recommend a certain stiffness based on body weight and activity level. However, it is unknown whether these recommendations are sufficient to yield the optimal stiffness for the individual. Therefore, we assessed whether the stiffness following the supplier’s recommendation of the Carbon Ankle7 (CA7) dorsal leaf matched the experimentally optimized AFO stiffness. Methods Thirty-four persons with calf muscle weakness were included and provided a new DLS-AFO of which the stiffness could be varied by changing the CA7® (Ottobock, Duderstadt, Germany) dorsal leaf. For five different stiffness levels, including the supplier recommended stiffness, gait biomechanics, walking energy cost and speed were assessed. Based on these measures, the individual experimentally optimal AFO stiffness was selected. Results In only 8 of 34 (23%) participants, the supplier recommended stiffness matched the experimentally optimized AFO stiffness, the latter being on average 1.2 ± 1.3 Nm/degree more flexible. The DLS-AFO with an experimentally optimized stiffness resulted in a significantly lower walking energy cost (− 0.21 ± 0.26 J/kg/m, p < 0.001) and a higher speed (+ 0.02 m/s, p = 0.003). Additionally, a larger ankle range of motion (+ 1.3 ± 0.3 degrees, p < 0.001) and higher ankle power (+ 0.16 ± 0.04 W/kg, p < 0.001) were found with the experimentally optimized stiffness compared to the supplier recommended stiffness. Conclusions In people with calf muscle weakness, current supplier’s recommendations for the CA7 stiffness level result in the provision of DLS-AFOs that are too stiff and only achieve 80% of the reduction in energy cost achieved with an individual optimized stiffness. It is recommended to experimentally optimize the CA7 stiffness in people with calf muscle weakness in order to maximize treatment outcomes. Trial registration Nederlands Trial Register 5170. Registration date: May 7th 2015. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5170.

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Section: Discussionmentioning

confidence: 99%

Individual stiffness optimization of dorsal leaf spring ankle–foot orthoses in people with calf muscle weakness is superior to standard bodyweight-based recommendations

Waterval

Brehm

Harlaar

et al. 2021

J NeuroEngineering Rehabil

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“…Waterval et al. (2021) also reproduced most gait changes due to bilateral plantar flexor weakness based on Geyer and Herr's model. Similarly, Ong et al.…”

Section: Introductionmentioning

confidence: 95%

“…Song and Geyer (2018) simulated the major contribution of loss of muscle strength and contraction speed in walking speed and efficiency decline with ageing based on Song and Geyer (2015). Waterval et al (2021) also reproduced most gait changes due to bilateral plantar flexor weakness based on Geyer and Herr's model. Similarly, Ong et al (2019) modelled SOL and GAS weakness and contracture with respectively reduced maximal isometric force and reduced muscle fibre optimal length.…”

Section: Introductionmentioning

confidence: 97%

Investigation of neural and biomechanical impairments leading to pathological toe and heel gaits using neuromusculoskeletal modelling

Bruel

Ghorbel

Russo

et al. 2022

The Journal of Physiology

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“…The anatomical simulation model consisting of bones, musculotendons, and their contraction dynamics achieves better accuracy, flexibility, and applicability in gait simulation. The combination of muscle actuation models and nonlinear optimization has successfully demonstrated the simulation of healthy and pathological human gaits [50,47,40,44,35,51]. Since control optimization is notoriously timeconsuming, early studies used simplified musculoskeletal models with only one or two dozens of musculotendon units.…”

Section: Related Workmentioning

confidence: 99%

“…Ideally, we wish that appropriate gait emerges from biological principles for any given body condition. This approach often requires dynamical models much simpler than human anatomy [18,50] or results in aberrant gaits that do not look human-like [14,51]. Alternatively, many gait simulation algorithms leverage motion capture data as reference to formulate the problem as trajectory tracking [29,37,12].…”

Section: Introductionmentioning

confidence: 99%

Generative GaitNet

Park¹,

Min²,

Chang³

et al. 2022

Preprint

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Understanding the relation between anatomy and gait is key to successful predictive gait simulation. In this paper, we present Generative GaitNet, which is a novel network architecture based on deep reinforcement learning for controlling a comprehensive, fullbody, musculoskeletal model with 304 Hill-type musculotendons. The Generative Gait is a pre-trained, integrated system of artificial neural networks learned in a 618-dimensional continuous domain of anatomy conditions (e.g., mass distribution, body proportion, bone deformity, and muscle deficits) and gait conditions (e.g., stride and cadence). The pre-trained Gait-Net takes anatomy and gait conditions as input and generates a series of gait cycles appropriate to the conditions through physics-based simulation. We will demonstrate the efficacy and expressive power of Generative GaitNet to generate a variety of healthy and pathologic human gaits in real-time physics-based simulation.

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Validation of forward simulations to predict the effects of bilateral plantarflexor weakness on gait

Cited by 36 publications

References 34 publications

Individual stiffness optimization of dorsal leaf spring ankle–foot orthoses in people with calf muscle weakness is superior to standard bodyweight-based recommendations

Individual stiffness optimization of dorsal leaf spring ankle–foot orthoses in people with calf muscle weakness is superior to standard bodyweight-based recommendations

Investigation of neural and biomechanical impairments leading to pathological toe and heel gaits using neuromusculoskeletal modelling

Generative GaitNet

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