Effect of mahjong, a Chinese tiled-based game, combined with upper limb robot training on upper limb function and rehabilitation participation in Chinese stroke patients: a clinical trial protocol
Bibliographic record
Abstract
INTRODUCTION: Stroke is the second leading cause of death and disability creating a huge economic burden annually. Robot-assisted training (RT) is a promising therapy in stroke rehabilitation, but for the elderly, traditional 'reaching objects'" tasks do not seem to create sufficient motivation, an important factor in rehabilitation, which reduces the effect of rehabilitation. Combining RT with some popular card games like mahjong, a popular tiled-based game in the Chinese elderly, is a strategy to motivate stroke survivors. Combining functional near-infrared imaging spectroscopy technique (fNIRS), the aim of this trial is to explore the effects of mahjong-based RT on stroke survivors compared with traditional RT. METHODS AND ANALYSIS: The three-arm, assessor-blinded, randomised controlled trial will allocate 18 participants in each group, traditional robot-assisted training (TRT) group, mahjong game-based upper limb robot-assisted training (MULR) group and conventional rehabilitation group. Participants in these three groups will receive 30-min physical therapy and 30-min occupational therapy 5 days per week for 3 weeks. Participants in the TRT group will receive an extra 30-min TRT, while participants in the MULR group will receive an extra 30-min MULR 5 days per week for 3 weeks. The primary outcome will be the neuromuscular function of upper limb assessed by Fugl-Meyer Assessment of Upper Extremity assessed at baseline and after the last treatment has been completed. Other outcomes will include cognitive function assessed by Montreal Cognitive Assessment, rehabilitation motivation assessed by Pittsburgh Rehabilitation Participation Scale, activities of daily living assessed by Modified Barthel Index, emotion assessed by self-rating anxiety scale and self-rating depression scale) and brain neural activity assessed by fNIRS. Two-way analysis of variance, Welch's ANOVA, post hoc comparison and simple effects analyses will be used for the analysis of scale data; while generalisation linear model analysis and seed-based correlation will be used for the analysis of fNIRS data. ETHICS AND DISSEMINATION: This trial was approved by the ethics committee of the West China Hospital of Sichuan University, China (reference number: 2024298). The results of this trial will be published in peer-reviewed scientific journals. TRIAL REGISTRATION NUMBER: This trial has been registered on the Chinese Clinical Trial Registry, https://www.chictr.org.cn. The reference number is ChiCTR2400084049. The registered name is 'Effect of mahjong game-based upper limb robot training on upper limb function in stroke patients: a functional near-infrared clinical study protocol'.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".