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Record W2991525661 · doi:10.1186/s12984-019-0585-x

Retraining walking over ground in a powered exoskeleton after spinal cord injury: a prospective cohort study to examine functional gains and neuroplasticity

2019· article· en· W2991525661 on OpenAlexaff
Atif S. Khan, Donna Livingstone, Caitlin Hurd, Jennifer Duchcherer, John E. Misiaszek, Monica A. Gorassini, Patricia J. Manns, Jaynie F. Yang

Bibliographic record

VenueJournal of NeuroEngineering and Rehabilitation · 2019
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCraig H. Neilsen Foundation
KeywordsPhysical medicine and rehabilitationSpinal cord injurySpasticityPowered exoskeletonExoskeletonMedicineBalance (ability)RehabilitationPhysical therapySittingPreferred walking speedSpinal cordPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Powered exoskeletons provide a way to stand and walk for people with severe spinal cord injury. Here, we used the ReWalk exoskeleton to determine the training dosage required for walking proficiency, the sensory and motor changes in the nervous system with training, and the functionality of the device in a home-like environment. METHODS: Participants with chronic (> 1 yr) motor complete or incomplete spinal cord injury, who were primarily wheelchair users, were trained to walk in the ReWalk for 12 weeks. Measures were taken before, during, immediately after, and 2-3 months after training. Measures included walking progression, sitting balance, skin sensation, spasticity, and strength of the corticospinal tracts. RESULTS: Twelve participants were enrolled with 10 completing training. Training progression and walking ability: The progression in training indicated about 45 sessions to reach 80% of final performance in training. By the end of training, participants walked at speeds of 0.28-0.60 m/s, and distances of 0.74-1.97 km in 1 h. The effort of walking was about 3.3 times that for manual wheelchair propulsion. One non-walker with an incomplete injury became a walker without the ReWalk after training. Sensory and motor measures: Sitting balance was improved in some, as seen from the limits of stability and sway speed. Neuropathic pain showed no long term changes. Change in spasticity was mixed with suggestion of differences between those with high versus low spasticity prior to training. The strength of motor pathways from the brain to back extensor muscles remained unchanged. Adverse events: Minor adverse events were encountered by the participants and trainer (skin abrasions, non-injurious falls). Field testing: The majority of participants could walk on uneven surfaces outdoors. Some limitations were encountered in home-like environments. CONCLUSION: For individuals with severe SCI, walking proficiency in the ReWalk requires about 45 sessions of training. The training was accompanied by functional improvements in some, especially in people with incomplete injuries. TRIAL REGISTRATION: NCT02322125 Registered 22 December 2014.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.239
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations66
Published2019
Admission routes1
Has abstractyes

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