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Record W4311674924 · doi:10.2340/jrm.v54.4544

Feasibility and Safety of a Powered Exoskeleton for Balance Training for People Living with Multiple Sclerosis: A Single-Group Preliminary Study (Rapper III)

2022· article· en· W4311674924 on OpenAlexaff
Mohamed Sakel, Karen Saunders, Philip Hodgson, David Stephensen, Chetan P. Phadke, Paul Bassett, David T. Wilkinson

Bibliographic record

VenueJournal of Rehabilitation Medicine · 2022
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsWest Park Healthcare Centre
FundersUniversity of KentNational Institute for Health and Care Research
KeywordsExoskeletonBalance (ability)Physical medicine and rehabilitationMultiple sclerosisPhysical therapyRehabilitationMedicine

Abstract

fetched live from OpenAlex

Objective: To evaluate the feasibility, usability, safety, and potential health benefits of using an exoskeleton device for rehabilitation of people living with multiple sclerosis.Design: Single-group preliminary study.Subjects: Eleven adults living with multiple sclerosis, with Expanded Disability Status Scores that ranged from 6 to 7.5 (mean age (standard deviation; SD) 54.2 (11.8) years), were recruited.Methods: Individual participants undertook a balance rehabilitation exercise programme using the Rex Rehab robotic exoskeleton device. Each participant undertook 4 × 45–60 min supervised, balance exercise sessions. Primary outcomes were: (i) the number of participants who completed the trial protocol safely, and (ii) the number and nature of adverse events reported. Secondary outcomes were: mobility; balance; spasticity; sleep; functional independence; quality of life; and device satisfaction.Results: Ten out of 11 participants completed the trial protocol safely. Four adverse events were recorded (1 serious), all of which were deemed unrelated to the trial. Secondary outcomes showed allied improvements in balance, joint mobility, spasticity and quality of life. All participants found the device acceptable to use.Conclusion: These results suggest that it is feasible and safe to use the Rex Rehab exoskeleton device to assist with balance rehabilitation for people living with multiple sclerosis. LAY ABSTRACTMultiple sclerosis (MS) is a chronic neurological disease that can lead to symptoms, including muscle weakness and balance issues. The incidence of falls in people living with MS (PwMS) is 3 times higher than that in older people. To try to reduce this vulnerability to falls, this study aimed to evaluate the feasibility, safety, and potential health benefits of using an exoskeleton device for a balance exercise programme. Eleven PwMS undertook 4×45–60 min supervised, balance exercise sessions using the exoskeleton device. Feasibility and safety were assessed by identifying the number of participants who completed the trial safely; consideration of any issues experienced during the trial and how these were resolved. Ten participants completed the trial (1 withdrew due to their MS) and only 4 issues were reported, all of which were unrelated to the trial. Some participants also experienced improvements in balance, mobility, and quality of life.

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)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.029
GPT teacher head0.250
Teacher spread0.222 · 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 designNon-randomized trial
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

Citations4
Published2022
Admission routes1
Has abstractyes

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