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Integrating robotic-assisted gait training into an inpatient physiotherapy program for children with subacute acquired brain injury: a feasibility study and characterization of session ingredients

2025· article· en· W7084060135 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2025
Typearticle
Languageen
FieldMaterials Science
TopicRadiation Shielding Materials Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGait trainingGaitAmbulatoryGoal Attainment ScalingGross motor skillAcquired brain injuryIntervention (counseling)

Abstract

fetched live from OpenAlex

While robotic-assisted gait training (RAGT) may permit earlier exposure to ambulation for children with subacute acquired brain injury (ABI), little is known about its associated viability. Our feasibility study focused on RAGT (Lokomat) use in this population. 8-week single-group pre-/post-test study integrated RAGT into an inpatient physiotherapy (PT) program (3 PT sessions/week plus 2 RAGT sessions/week). Twenty-four youth (14 males), mean age 13.7 years (SD = 3.6) participated. Six walked independently (4 devices) at baseline; 18 were pre-ambulatory. Nineteen completed the targeted 10-16 RAGT sessions. One child was withdrawn post-syncopic episode during acclimatization, and two children withdrew after 2-3 sessions due to RAGT-related discomfort with no follow-up assessment. Across four feasibility areas, 58% (Acceptability) to 100% (Safety) of indicators were met. Session characterization showed progression of Lokomat speed and reduced weight-support, and physiotherapists’ use of motor learning strategies. Physiotherapists rated Lokomat ease of use as 7.6/10 and perceived child engagement as 7.2/10. Post-intervention, 15 of the 21 children re-assessed were independently ambulatory (5 devices). Gross Motor Function Measure-88 mean increase was 19.7% points. Canadian Occupational Performance Measure mean gain was 2.5 points/10. PT+RAGT was feasible for 21 of 24 children and associated with large motor gains and goal accomplishment. Treadmill-based robotic-assisted gait training (RAGT) is a viable and safe intervention to use with children during the subacute phase of acquired brain injury.Setting RAGT-specific Goal Attainment Scaling goals provides structure and focus to RAGT treatment sessions.Clinicians should reflect on the child’s engagement, goals, and progress to determine the appropriate time to discontinue RAGT.Clinicians enhance the motor learning strategies content of RAGT treatment sessions beyond the repetitive practice, physical guidance, and augmentative feedback that is inherently part of the RAGT device. Treadmill-based robotic-assisted gait training (RAGT) is a viable and safe intervention to use with children during the subacute phase of acquired brain injury. Setting RAGT-specific Goal Attainment Scaling goals provides structure and focus to RAGT treatment sessions. Clinicians should reflect on the child’s engagement, goals, and progress to determine the appropriate time to discontinue RAGT. Clinicians enhance the motor learning strategies content of RAGT treatment sessions beyond the repetitive practice, physical guidance, and augmentative feedback that is inherently part of the RAGT device.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.036
GPT teacher head0.349
Teacher spread0.313 · 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