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Robotic mechanotherapy: the possibility to use an exoskeleton for lower limb rehabilitation in patients with multiple sclerosis and impaired walking function

2020· article· en· W3010756636 on OpenAlexaboutno aff
A. A. Gevorkyan, С. В. Котов, V Yu Lizhdvoy

Bibliographic record

VenueAlmanac of Clinical Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMultiple sclerosisExoskeletonRehabilitationPhysical medicine and rehabilitationExpanded Disability Status ScalePhysical therapyMedicine

Abstract

fetched live from OpenAlex

Background : Robotic mechanotherapy is considered as a promising area of physical rehabilitation of multiple sclerosis patients, while it ensures high training efficacy. Aim : To study the effect of physical training using with the ExoAtlet exoskeleton for lower extremities the functioning of patients with multiple sclerosis. Materials and methods : This was a prospective, open, uncontrolled, single center study. The rehabilitation course with the ExoAtlet exoskeleton included 43 patients (14 male and 29 female, aged from 28 to 59 years, mean age 43,5 ± 9,12 years) with remitting multiple sclerosis in remission (RMS-R) (n = 20) and secondary progressive course (VPRS) (n = 23), with the EDSS scores from 3 to 8. One of the inclusion criteria was the presence of motor paresis of the lower extremities. Training with the ExoAtlet exoskeleton was performed 5 days a week for two weeks. The neurological deficits and functioning were assessed with the Kurtzke expanded disability status scale (EDSS), the multiple sclerosis functional composite (MSFC) test, including the assessment of walking (Timed 25 Footwalk), of upper limb functions (9-Hole PegTest, 9-HPT), and of mental functioning (Symbol Digit Modalities Test, SDMT) before and after the rehabilitation course. Cognitive functions were assessed by the Montreal Cognitive Assessment (MoCA) scale. Results : The rehabilitation course resulted in a significant decrease of neurological deficiency by EDSS (by 0.26 score, 5%, p < 0.001). The MSFC test showed an improvement in all subtests: SDMT by 2 points, or 4.9% (p = 0.018), Timed 25-Footwalk by 3.2 seconds, or 19.6% (p < 0.001), 9-HPT for the dominant hand by 1.6 seconds, or 5% (p = 0.004), and for the non-dominant hand by 2.1 seconds, or 6.2% (p = 0.006). The improvement in the MoCA test after the rehabilitation course was 1.6 points, or 6% (p < 0.001). Conclusion : The study confirmed the positive effect of the exoskeleton in the lower extremities, such as restoration of the walking function in multiple sclerosis patients. There was a positive trend towards restoring of hand motor skills and cognitive functions.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.141
GPT teacher head0.377
Teacher spread0.236 · 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 teacher head, not a consensus.

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

Citations5
Published2020
Admission routes1
Has abstractyes

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