Game-Based Augmented Visual Feedback for Enlarging Speech Movements in Parkinson's Disease
Bibliographic record
Abstract
Purpose: The purpose of this pilot study was to demonstrate the effect of augmented visual feedback on acquisition and short-term retention of a relatively simple instruction to increase movement amplitude during speaking tasks in patients with dysarthria due to Parkinson's disease (PD). Method: Nine patients diagnosed with PD, hypokinetic dysarthria, and impaired speech intelligibility participated in a training program aimed at increasing the size of their articulatory (tongue) movements during sentences. Two sessions were conducted: a baseline and training session, followed by a retention session 48 hr later. At baseline, sentences were produced at normal, loud, and clear speaking conditions. Game-based visual feedback regarding the size of the articulatory working space (AWS) was presented during training. Results: Eight of nine participants benefited from training, increasing their sentence AWS to a greater degree following feedback as compared with the baseline loud and clear conditions. The majority of participants were able to demonstrate the learned skill at the retention session. Conclusions: This study demonstrated the feasibility of augmented visual feedback via articulatory kinematics for training movement enlargement in patients with hypokinesia due to PD. Supplemental Materials: https://doi.org/10.23641/asha.5116840.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".