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Record W2898704496 · doi:10.2196/11470

Rehabilitation for Children With Dystonic Cerebral Palsy Using Haptic Feedback in Virtual Reality: Protocol for a Randomized Controlled Trial

2018· article· en· W2898704496 on OpenAlexvenueno aff
Reika Nicole McNish, Pramod Chembrammel, Nathaniel Christopher Speidel, Julian Lin, Citlali López‐Ortiz

Bibliographic record

VenueJMIR Research Protocols · 2018
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral palsyRandomized controlled trialVirtual realityRehabilitationPhysical medicine and rehabilitationHaptic technologyProtocol (science)Physical therapyPsychologyMedicineComputer scienceHuman–computer interactionSimulationAlternative medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: Cerebral palsy (CP) is the most common developmental motor disorder in children. Individuals with CP demonstrate abnormal muscle tone and motor control. Within the population of children with CP, between 4% and 17% present dystonic symptoms that may manifest as large errors in movement tasks, high variability in movement trajectories, and undesired movements at rest. These symptoms of dystonia typically worsen with physical intervention exercises. OBJECTIVE: The aim of this study is to establish the effect of haptic feedback in a virtual reality (VR) game intervention on movement outcomes of children with dystonic CP. METHODS: The protocol describes a randomized controlled trial that uses a VR game-based intervention incorporating fully automated robotic haptic feedback. The study consists of face-to-face assessments of movement before, after, and 1 month following the completion of the 6-session game-based intervention. Children with dystonic CP, aged between 7 and 17 years, will be recruited for this study through posted fliers and laboratory websites along with a group of typically developing (TD) children in the same age range. We anticipate to recruit a total of 68 participants, 34 each with CP and TD. Both groups of children will be randomly allocated into an intervention or control group using a blocked randomization method. The primary outcome measure will be the smoothness index of the interaction force with the robot and of the accelerometry signals of sensors placed on the upper limb segments. Secondary outcomes include a battery of clinical tests and a quantitative measure of spasticity. Assessors administering clinical measures will be blinded. All sessions will be administered on-site by research personnel. RESULTS: The trial has not started and is pending local institutional review board approval. CONCLUSIONS: Movement outcomes will be examined for changes in muscle activation and clinical measures in children with dystonic CP and TD children. Paired t tests will be conducted on movement outcomes for both groups of children independently. Positive and negative results will be reported and addressed. TRIAL REGISTRATION: ClinicalTrials.gov NCT03744884; https://clinicaltrials.gov/ct2/show/NCT03744884 (Archived by WebCite at http://www.webcitation.org/74RSvmbZP). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/11470.

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)0.026
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.061
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.028
Meta-epidemiology (narrow)0.0070.003
Meta-epidemiology (broad)0.0130.005
Bibliometrics0.0030.003
Science and technology studies0.0030.003
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0610.008

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 head0.125
GPT teacher head0.504
Teacher spread0.378 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations7
Published2018
Admission routes1
Has abstractyes

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