ExoOpt - A framework for patient centered design optimization of lower limb exoskeletons

Koch, Henning; Mombaur, Katja

doi:10.1109/icorr.2015.7281185

Cited by 15 publications

(8 citation statements)

References 14 publications

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“…To the best of our knowledge such approaches are not yet widely used with few comparable studies (see e.g. [19], [20], [36], [37]). We note the following important points about our present work:…”

Section: Discussionmentioning

confidence: 99%

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Motion Optimization and Parameter Identification for a Human and Lower Back Exoskeleton Model

Manns

Sreenivasa

Millard

et al. 2017

IEEE Robot. Autom. Lett.

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Designing an exoskeleton to reduce the risk of lowback injury during lifting is challenging. Computational models of the human-robot system coupled with predictive movement simulations can help to simplify this design process. Here, we present a study that models the interaction between a human model actuated by muscles and a lower-back exoskeleton. We provide a computational framework for identifying the spring parameters of the exoskeleton using an optimal control approach and forward-dynamics simulations. This is applied to generate dynamically consistent bending and lifting movements in the sagittal plane. Our computations are able to predict motions and forces of the human and exoskeleton that are within the torque limits of a subject. The identified exoskeleton could also yield a considerable reduction of the peak lower-back torques as well as the cumulative lower-back load during the movements. This work is relevant to the research communities working on human-robot interaction, and can be used as a basis for a better human-centered design process.

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Section: Discussionmentioning

confidence: 99%

“…They have been used successfully for robot and human motion generation in the past (e.g. [16]- [18]), and to a limited extent for the design of lower limb exoskeletons [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Motion Optimization and Parameter Identification for a Human and Lower Back Exoskeleton Model

Manns

Sreenivasa

Millard

et al. 2017

IEEE Robot. Autom. Lett.

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“…Our framework is not restricted to passive walkers. On a wider scale, it can evaluate some paradigms in the design and the control of new humanoid robots [40], [41] and exoskeletons [42]. In the near future, we will exploit this framework to evaluate and design a bipedal robot inspired from passive walkers.…”

Section: Discussion and Future Workmentioning

confidence: 99%

A simulation framework for simultaneous design and control of passivity based walkers

Saurel

Carpentier

Mansard

et al. 2016

2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR)

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In this paper, we propose a simulation framework which simultaneously computes both the design and the control of bipedal walkers. The problem of computing a design and a control is formulated as a single large-scale parametric optimal control problem on hybrid dynamics with path constraints (e.g. non sliding and non slipping contact constraints). Our framework relies on state-of-the-art numerical optimal control techniques and efficient computation of the multi-body rigid dynamics. It allows to compute both the parametrized model and the control of passive walkers on different scenarios, in only few seconds on a standard computer. The framework is illustrated by several examples which highlight the interest of the approach.

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“…In general, an OCP defines a minimization problem where an objective function is minimized while abiding the dynamics describing a physical system (in our case the human body + orthosis dynamics). Such methods have been used successfully for robot and human motion generation in the past (Bobrow et al, 1985 ; von Stryk and Schlemmer, 1994 ; Schultz and Mombaur, 2010 ), and to a limited extent for the design of human-assistive devices (Koch and Mombaur, 2015 ; Mombaur, 2016 ). In the current work, we strike a balance between model complexity and computational efficiency by modeling the muscles as lumped torque generators rather than anatomically equivalent line-type actuators.…”

Section: Introductionmentioning

confidence: 99%

Optimal Control Based Stiffness Identification of an Ankle-Foot Orthosis Using a Predictive Walking Model

Sreenivasa

Millard

Felis

et al. 2017

Front. Comput. Neurosci.

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Predicting the movements, ground reaction forces and neuromuscular activity during gait can be a valuable asset to the clinical rehabilitation community, both to understand pathology, as well as to plan effective intervention. In this work we use an optimal control method to generate predictive simulations of pathological gait in the sagittal plane. We construct a patient-specific model corresponding to a 7-year old child with gait abnormalities and identify the optimal spring characteristics of an ankle-foot orthosis that minimizes muscle effort. Our simulations include the computation of foot-ground reaction forces, as well as the neuromuscular dynamics using computationally efficient muscle torque generators and excitation-activation equations. The optimal control problem (OCP) is solved with a direct multiple shooting method. The solution of this problem is physically consistent synthetic neural excitation commands, muscle activations and whole body motion. Our simulations produced similar changes to the gait characteristics as those recorded on the patient. The orthosis-equipped model was able to walk faster with more extended knees. Notably, our approach can be easily tuned to simulate weakened muscles, produces physiologically realistic ground reaction forces and smooth muscle activations and torques, and can be implemented on a standard workstation to produce results within a few hours. These results are an important contribution toward bridging the gap between research methods in computational neuromechanics and day-to-day clinical rehabilitation.

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ExoOpt - A framework for patient centered design optimization of lower limb exoskeletons

Cited by 15 publications

References 14 publications

Motion Optimization and Parameter Identification for a Human and Lower Back Exoskeleton Model

Motion Optimization and Parameter Identification for a Human and Lower Back Exoskeleton Model

A simulation framework for simultaneous design and control of passivity based walkers

Optimal Control Based Stiffness Identification of an Ankle-Foot Orthosis Using a Predictive Walking Model

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