Evaluating Note Frequency and Velocity During Improvised Active Music Therapy in Clients With Parkinson’s Disease
Bibliographic record
Abstract
The purpose of this article was to report on the findings of the note frequency and velocity measures during Improvised Active Music Therapy (IAMT) sessions with individuals with Parkinson's disease (PD). In this single-subject multiple baseline design across subjects, the article reports the note frequency (note count) and velocity of movement (mean note velocity) played by three right-handed participants while playing uninterrupted improvised music on a simplified electronic drum-set. During baseline, the music therapist played rhythmic accompaniment on guitar using a low-moderate density of syncopation. During treatment, the Music Therapist introduced rhythms with a moderate-high density of syncopation. The music content of the sessions was transformed into digital music using a musical instrument digital interface. Results of this study indicated that all participants exhibited an increase in note count during baseline until reaching a plateau at treatment condition and were found to be significantly positively correlated with the Music Therapist's note count. All participants played more notes with upper extremity (UE) across conditions than with lower extremity. All participants also scored similar total mean velocity across conditions. Two participants demonstrated higher mean note velocity with UE than right foot, whereas the other participant did not demonstrate this difference. Two participants also exhibited greater mean note velocity variability with left foot within and across conditions. More research is required to identify commonalities in note count and mean note velocity measures in individuals with PD during IAMT sessions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".