Facilitating movement performance in cerebral palsy: The impact of rhythmic auditory cueing in a goal-directed reaching task
Bibliographic record
Abstract
For individuals with Cerebral Palsy (CP), functional reaching is key to maintaining independence. While previous research indicates benefits for multisensory input in CP, presently it is unknown when during goal-directed movements sensory input is integrated. This study considered the influence of an auditory stimulus during the planning or execution phases of a goal-directed reaching task. Three conditions were presented: No Sound (NS), Sound:Before (SB), and Sound:During (SD), which included a series of three tones presented over a 6s duration. Twenty adult participants (CP=10, TD=10) reached from a home switch to one of two targets, for a total of 60 trials. Infrared emitting diodes (IREDs) were placed on the index finger, second metacarpal, and wrist of the preferred arm to allow an Optotrak 3-D Investigator (250Hz) to record movement trajectories. Dependent variables were analyzed using a 2 Group x 2 Condition (SB-NS; SD-NS) ANOVA. Reaction time analysis demonstrated a significant main effect for condition, with decreased RT in the SB conditions for both groups. Analysis of variable error revealed significant main effects for group and condition, with the CP group executing more consistent movements in both the SB and SD conditions. Analysis of time to peak velocity (PV) divided by movement time revealed a significant group by condition interaction, indicating the CP group was able to achieve PV relatively earlier in the SB condition. Overall, the presence of a sound during movement planning (SB), improved both planning and execution of reaching movements for individuals with CP.Acknowledgments: Many thanks to the participants for their time, to CP Manitoba and The Movement Centre, Inc. for assisting with recruitment, and to the funding organizations (NSERC, CFI, and Research Manitoba) for their support.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".