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Record W4381997154 · doi:10.2196/45816

Cognitive Training With Head-Mounted Display Virtual Reality in Neurorehabilitation: Pilot Randomized Controlled Trial

2023· article· en· W4381997154 on OpenAlexvenueno aff
Julian Specht, Barbara Stegmann, Hanna Gross, Karsten Krakow

Bibliographic record

VenueJMIR Serious Games · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsNeurorehabilitationRehabilitationVirtual realityCognitive trainingCognitive rehabilitation therapyPhysical medicine and rehabilitationCognitionRandomized controlled trialPsychologyPhysical therapyStroke (engine)MedicineHuman–computer interactionComputer sciencePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Neurological rehabilitation is technologically evolving rapidly, resulting in new treatments for patients. Stroke, one of the most prevalent conditions in neurorehabilitation, has been a particular focus in recent years. However, patients often need help with physical and cognitive constraints, whereby the cognitive domain in neurorehabilitation does not technologically exploit existing potential. Usually, cognitive rehabilitation is performed with pen and paper or on a computer, which leads to limitations in preparation for activities of daily living. Technologies such as virtual reality (VR) can bridge this gap. OBJECTIVE: This pilot study investigated the use of immersive VR in cognitive rehabilitation for patients undergoing inpatient neurorehabilitation. The goal was to determine the difference in rehabilitation effectiveness between a VR serious game that combines everyday activities with cognitive paradigms and conventional computerized cognitive training. We hypothesized the superiority of the VR serious game regarding cognitive abilities and patient-reported outcomes as well as transfer to daily life. METHODS: We recruited 42 patients with acute brain affection from a German neurorehabilitation clinic in inpatient care with a Mini Mental Status Test score >20 to participate in this randomized controlled trial. Participants were randomly assigned to 2 groups, with 1 receiving the experimental VR treatment (n=21). VR training consisted of daily life scenarios, for example, in a kitchen, focusing on treating executive functions such as planning and problem-solving. The control group (n=21) received conventional computerized cognitive training. Each participant received a minimum of 18 treatment sessions in their respective group. Patients were tested for cognitive status, subjective health, and quality of life before and after the intervention (Alters-Konzentrations-Test, Wechsler Memory Scale-Revised, Trail Making Test A and B, Tower of London-German version, Short Form 36, European Quality of Life 5 Dimensions visual analog scale, and Fragebogen zur Erfassung der Performance in VR). RESULTS: was detected (all P>.05). Furthermore, a nonsignificant trend was observed in visual speed in the VR group (P=.09, Bonferroni P=.02). CONCLUSIONS: The results of this pilot randomized controlled trial showed that immersive VR training in cognitive rehabilitation had greater effectiveness than the standard of care in treating patients experiencing stroke in some cognitive domains . These findings support the further use and study of VR training incorporating activities of daily living in other neurological disorders involving cognitive dysfunction. TRIAL REGISTRATION: Federal Registry of Clinical Trials of Germany (DRKS) DRKS00023605; https://drks.de/search/de/trial/DRKS00023605.

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 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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.027
GPT teacher head0.352
Teacher spread0.326 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized 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

Citations23
Published2023
Admission routes1
Has abstractyes

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