The Effects of Music Salience on the Gait Performance of Young Adults
Bibliographic record
Abstract
BACKGROUND: The presence of a rhythmic beat in the form of a metronome tone or beat-accentuated original music can modulate gait performance; however, it has yet to be determined whether gait modulation can be achieved using commercially available music. OBJECTIVE: The current study investigated the effects of commercially available music on the walking of healthy young adults. Specific aims were (a) to determine whether commercially available music can be used to influence gait (i.e., gait velocity, stride length, cadence, stride time variability), (b) to establish the effect of music salience on gait (i.e., gait velocity, stride length, cadence, stride time variability), and (c) to examine whether music tempi differentially effected gait (i.e., gait velocity, stride length, cadence, stride time variability). METHODS: Twenty-five participants walked the length of an unobstructed walkway while listening to music. Music selections differed with respect to the salience or the tempo of the music. The genre of music and artists were self-selected by participants. RESULTS: Listening to music while walking was an enjoyable activity that influenced gait. Specifically, salient music selections increased measures of cadence, velocity, and stride length; in contrast, gait was unaltered by the presence of non-salient music. Music tempo did not differentially affect gait performance (gait velocity, stride length, cadence, stride time variability) in these participants. CONCLUSIONS: Gait performance was differentially influenced by music salience. These results have implications for clinicians considering the use of commercially available music as an alternative to the traditional rhythmic auditory cues used in rehabilitation programs.
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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 | 0.002 |
| 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) | 0.002 | 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".