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Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, January 2018
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Title
Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals
Published in
Journal of NeuroEngineering and Rehabilitation, January 2018
DOI 10.1186/s12984-017-0345-8
Pubmed ID
Authors

Vijaykumar Rajasekaran, Eduardo López-Larraz, Fernando Trincado-Alonso, Joan Aranda, Luis Montesano, Antonio J. del-Ama, Jose L. Pons

Abstract

Gait training for individuals with neurological disorders is challenging in providing the suitable assistance and more adaptive behaviour towards user needs. The user specific adaptation can be defined based on the user interaction with the orthosis and by monitoring the user intentions. In this paper, an adaptive control model, commanded by the user intention, is evaluated using a lower limb exoskeleton with incomplete spinal cord injury individuals (SCI). A user intention based adaptive control model has been developed and evaluated with 4 incomplete SCI individuals across 3 sessions of training per individual. The adaptive control model modifies the joint impedance properties of the exoskeleton as a function of the human-orthosis interaction torques and the joint trajectory evolution along the gait sequence, in real time. The volitional input of the user is identified by monitoring the neural signals, pertaining to the user's motor activity. These volitional inputs are used as a trigger to initiate the gait movement, allowing the user to control the initialization of the exoskeleton movement, independently. A Finite-state machine based control model is used in this set-up which helps in combining the volitional orders with the gait adaptation. The exoskeleton demonstrated an adaptive assistance depending on the patients' performance without guiding them to follow an imposed trajectory. The exoskeleton initiated the trajectory based on the user intention command received from the brain machine interface, demonstrating it as a reliable trigger. The exoskeleton maintained the equilibrium by providing suitable assistance throughout the experiments. A progressive change in the maximum flexion of the knee joint was observed at the end of each session which shows improvement in the patient performance. Results of the adaptive impedance were evaluated by comparing with the application of a constant impedance value. Participants reported that the movement of the exoskeleton was flexible and the walking patterns were similar to their own distinct patterns. This study demonstrates that user specific adaptive control can be applied on a wearable robot based on the human-orthosis interaction torques and modifying the joints' impedance properties. The patients perceived no external or impulsive force and felt comfortable with the assistance provided by the exoskeleton. The main goal of such a user dependent control is to assist the patients' needs and adapt to their characteristics, thus maximizing their engagement in the therapy and avoiding slacking. In addition, the initiation directly controlled by the brain allows synchronizing the user's intention with the afferent stimulus provided by the movement of the exoskeleton, which maximizes the potentiality of the system in neuro-rehabilitative therapies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 165 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 15%
Student > Master 22 13%
Researcher 19 12%
Student > Bachelor 17 10%
Student > Postgraduate 7 4%
Other 23 14%
Unknown 53 32%
Readers by discipline Count As %
Engineering 42 25%
Nursing and Health Professions 15 9%
Medicine and Dentistry 15 9%
Neuroscience 10 6%
Computer Science 6 4%
Other 19 12%
Unknown 58 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 April 2018.
All research outputs
#15,506,823
of 23,045,021 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#848
of 1,292 outputs
Outputs of similar age
#270,149
of 442,588 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#16
of 21 outputs
Altmetric has tracked 23,045,021 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,292 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,588 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.