Getting the Best Out of Advanced Rehabilitation Technology for the Lower Limbs: Minding Motor Learning Principles

Spiess, Martina R.; Steenbrink, Frans; Esquenazi, Alberto

doi:10.1016/j.pmrj.2018.06.007

Cited by 20 publications

(16 citation statements)

References 53 publications

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“…This enables training at the patient's optimal threshold while avoiding frequent and therefore time-consuming falls. The alternative option of adding handheld assistive devices to the training is in contradiction with established locomotor training principles [32,97] as well as with emerging principles of reinforcing functional remapping through arm use [10,11,14].…”

Section: Discussionmentioning

confidence: 99%

“…An elegant solution which does not require reliance on external, arm-based support, would be a stabilizing mode as an integrated feature of the BWS system. Such a feature must be easily scalable to the functional level of the patient to provide a sufficiently large challenge for highly functioning patients, while avoiding overly challenging conditions for less functioning patients [32,33].…”

Section: Introductionmentioning

confidence: 99%

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Mediolateral damping of an overhead body weight support system assists stability during treadmill walking

Bannwart

Bayer

Ignasiak

et al. 2020

J NeuroEngineering Rehabil

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Background: Body weight support systems with three or more degrees of freedom (3-DoF) are permissive and safe environments that provide unloading and allow unrestricted movement in any direction. This enables training of walking and balance control at an early stage in rehabilitation. Transparent systems generate a support force vector that is near vertical at all positions in the workspace to only minimally interfere with natural movement patterns. Patients with impaired balance, however, may benefit from additional mediolateral support that can be adjusted according to their capacity. An elegant solution for providing balance support might be by rendering viscous damping along the mediolateral axis via the software controller. Before use with patients, we evaluated if controlrendered mediolateral damping evokes the desired stability enhancement in able-bodied individuals. Methods: A transparent, cable-driven robotic body weight support system (FLOAT) was used to provide transparent body weight support with and without mediolateral damping to 21 able-bodied volunteers while walking at preferred gait velocity on a treadmill. Stability metrics reflecting resistance to small and large perturbations were derived from walking kinematics and compared between conditions and to free walking. Results: Compared to free walking, the application of body weight support per-se resulted in gait alterations typically associated with body weight support, namely increased step length and swing phase. Frontal plane dynamic stability, measured by kinematic variability and nonlinear dynamics of the center of mass, was increased under body weight support, indicating reduced balance requirements in both damped and undamped support conditions. Adding damping to the body weight support resulted in a greater increase of frontal plane stability. Conclusion: Adding mediolateral damping to 3-DoF body weight support systems is an effective method of increasing frontal plane stability during walking in able-bodied participants. Building on these results, adjustable mediolateral damping could enable therapists to select combinations of unloading and stability specifically for each patient and to adapt this in a task specific manner. This could extend the impact of transparent 3-DoF body weight support systems, enabling training of gait and active balance from an early time point onwards in the rehabilitation process for a wide range of mobility activities of daily life.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mediolateral damping of an overhead body weight support system assists stability during treadmill walking

Bannwart

Bayer

Ignasiak

et al. 2020

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

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“…3 In recent years, robotic devices have been proposed as tools to complement traditional therapy by means of novel rehabilitation programs, based on robot-mediated repeatable, intense, and motivating exercises, integrated with an enriched virtual environment that can feature improvements in movement quality. 11,12 Among all, Robot-Assisted Gait Training (RAGT) approaches have found relatively high success for the treatment of subjects with balance and gait dysfunctions. Two main design and control approaches can be undertaken to implement robot-mediated physical therapy, exoskeletal-or endeffector-based mechanisms.…”

Section: What Is the Impact Of Robotic Rehabilitation On Balance And ...mentioning

confidence: 99%

What is the impact of robotic rehabilitation on balance and gait outcomes in people with multiple sclerosis? A systematic review of randomized control trials

Bowman

Gervasoni

Amico³

et al. 2021

Eur J Phys Rehabil Med

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“…Robot-assisted gait training (RAGT) is a promising technique for rehabilitation after neurological disorders such as stroke or spinal cord injury (SCI). RAGT can be used to provide intensive, repetitive and task-specific training, while it also contributes to reduce physical load for therapists [1]. Reviews of previous studies have shown that RAGT can increase the likelihood that people walk independently after stroke, and that it is most effective in the acute phase after stroke/SCI and in the most impaired patients [2,3].…”

Section: Introductionmentioning

confidence: 99%

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders

Fricke

Bayón

Kooij

et al. 2020

J NeuroEngineering Rehabil

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Background: In clinical practice, therapists choose the amount of assistance for robot-assisted training. This can result in outcomes that are influenced by subjective decisions and tuning of training parameters can be time-consuming. Therefore, various algorithms to automatically tune the assistance have been developed. However, the assistance applied by these algorithms has not been directly compared to manually-tuned assistance yet. In this study, we focused on subtask-based assistance and compared automatically-tuned (AT) robotic assistance with manually-tuned (MT) robotic assistance. Methods: Ten people with neurological disorders (six stroke, four spinal cord injury) walked in the LOPES II gait trainer with AT and MT assistance. In both cases, assistance was adjusted separately for various subtasks of walking (in this study defined as control of: weight shift, lateral foot placement, trailing and leading limb angle, prepositioning, stability during stance, foot clearance). For the MT approach, robotic assistance was tuned by an experienced therapist and for the AT approach an algorithm that adjusted the assistance based on performances for the different subtasks was used. Time needed to tune the assistance, assistance levels and deviations from reference trajectories were compared between both approaches. In addition, participants evaluated safety, comfort, effect and amount of assistance for the AT and MT approach. Results: For the AT algorithm, stable assistance levels were reached quicker than for the MT approach. Considerable differences in the assistance per subtask provided by the two approaches were found. The amount of assistance was more often higher for the MT approach than for the AT approach. Despite this, the largest deviations from the reference trajectories were found for the MT algorithm. Participants did not clearly prefer one approach over the other regarding safety, comfort, effect and amount of assistance. Conclusion: Automatic tuning had the following advantages compared to manual tuning: quicker tuning of the assistance, lower assistance levels, separate tuning of each subtask and good performance for all subtasks. Future clinical trials need to show whether these apparent advantages result in better clinical outcomes.

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Getting the Best Out of Advanced Rehabilitation Technology for the Lower Limbs: Minding Motor Learning Principles

Cited by 20 publications

References 53 publications

Mediolateral damping of an overhead body weight support system assists stability during treadmill walking

Mediolateral damping of an overhead body weight support system assists stability during treadmill walking

What is the impact of robotic rehabilitation on balance and gait outcomes in people with multiple sclerosis? A systematic review of randomized control trials

Automatic versus manual tuning of robot-assisted gait training in people with neurological disorders

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