MétaCan
Menu
Back to cohort
Record W2783370472 · doi:10.1080/17483107.2018.1425747

Robot-assisted upper extremity rehabilitation for cervical spinal cord injuries: a systematic scoping review

2018· article· en· W2783370472 on OpenAlex
Hardeep Singh, Janelle Unger, José Zariffa, Maureen Pakosh, Susan Jaglal, B. Catharine Craven, Kristin E. Musselman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2018
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoUniversity Health Network
FundersUniversity of TorontoOntario Neurotrauma FoundationCraig H. Neilsen Foundation
KeywordsCINAHLBlindingRehabilitationPhysical medicine and rehabilitationMedicineRandomized controlled trialMEDLINEPsycINFOPhysical therapyPsychological interventionChecklistSystematic reviewPsychologyNursingSurgery

Abstract

fetched live from OpenAlex

Abstact Purpose: To provide an overview of the feasibility and outcomes of robotic-assisted upper extremity training for individuals with cervical spinal cord injury (SCI), and to identify gaps in current research and articulate future research directions. MATERIALS AND METHODS: A systematic search was conducted using Medline, Embase, PsycINFO, CCTR, CDSR, CINAHL and PubMed on June 7, 2017. Search terms included 3 themes: (1) robotics; (2) SCI; (3) upper extremity. Studies using robots for upper extremity rehabilitation among individuals with cervical SCI were included. Identified articles were independently reviewed by two researchers and compared to pre-specified criteria. Disagreements regarding article inclusion were resolved through discussion. The modified Downs and Black checklist was used to assess article quality. Participant characteristics, study and intervention details, training outcomes, robot features, study limitations and recommendations for future studies were abstracted from included articles. RESULTS: Twelve articles (one randomized clinical trial, six case series, five case studies) met the inclusion criteria. Five robots were exoskeletons and three were end-effectors. Sample sizes ranged from 1 to 17 subjects. Articles had variable quality, with quality scores ranging from 8 to 20. Studies had a low internal validity primarily from lack of blinding or a control group. Individuals with mild-moderate impairments showed the greatest improvements on body structure/function and performance-level measures. This review is limited by the small number of articles, low-sample sizes and the diversity of devices and their associated training protocols, and outcome measures. CONCLUSIONS: Preliminary evidence suggests robot-assisted interventions are safe, feasible and can reduce active assistance provided by therapists. Implications for rehabilitation Robot-assisted upper extremity training for individuals with cervical spinal cord injury is safe, feasible and can reduce hands-on assistance provided by therapists. Future research in robotics rehabilitation with individuals with spinal cord injury is needed to determine the optimal device and training protocol as well as effectiveness.

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.

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)0.033
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.005
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 head0.044
GPT teacher head0.423
Teacher spread0.380 · 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