Treatment of Hypophonia in Parkinson's Disease Through Biofeedback in Daily Life Administered with A Portable Voice Accumulator
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to assess the outcome following continuous tactile biofeedback of voice sound level administered, with a portable voice accumulator to individuals with Parkinson's disease (PD). METHOD: Nine out of 16 participants with PD completed a 4-week intervention program where biofeedback of voice sound level was administered with the portable voice accumulator VoxLog during speech in daily life. The feedback, a tactile vibration signal from the device, was activated when the wearer used a voice sound level below an individually predetermined threshold level, reminding the wearer to increase voice sound level during speech. Voice use was registered in daily life with the VoxLog during the intervention period as well as during one baseline week, one follow-up week post intervention and 1 week 3 months post intervention. Self-to-other ratio (SOR), which is the difference between voice sound level and environmental noise, was studied in multiple noise ranges. RESULTS: A significant increase in SOR across all noise ranges of 2.28 dB (SD: 0.55) was seen for participants with scores above the cut-off for normal function (>26 points) on the cognitive screening test Montreal Cognitive Assessment (MoCA) (n = 5). No significant increase was seen for the group of participants with MoCA scores below 26 (n = 4). Forty-four percent ended their participation early, all which scored below 26 on MoCA (n = 7). CONCLUSIONS: Biofeedback administered in daily life regarding voice level may help individuals with PD to increase their voice sound level in relation to environmental noise in daily life, but only for a limited subset. Only participants with normal cognitive function as screened by MoCA improved their voice sound level in relation to environmental noise.
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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 | 0.000 |
| 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".