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Gamification of Breath Training for Wind Players

2024· article· en· W4400527264 on OpenAlexaff
L Jones, Matthew McConnell, Hua Shen, Jeremy Brown, Jeffrey E. Boyd

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsTraining (meteorology)Computer scienceAeronauticsEngineeringMeteorologyPhysics

Abstract

fetched live from OpenAlex

This paper presents the gamification of the Abdominal- Thoracic-Expansion-Measurement prototype wear-able device (ATEMP) and the subsequent study. The ATEMP is a newly developed wearable device for musicians that measures breathing-induced abdominal and ribcage expansion and contraction in real-time. Flute Hero video game was developed as a side-scroller game that uses the ATEMP as player input, and provides real-time biofeedback. The Flute Hero video game study (pretest, post-test, control group study design), gathered metrics from 41 flutists and analyzed whether playing Flute Hero improves breathing technique more so than not playing Flute Hero. All participants performed the pretest and post-test, but only the treatment group played Flute Hero for three weeks between the pretest and post-test. Response to the gaming was positive, participants were keen to play the game and remained engaged throughout the duration of the study. Participants commented that they felt playing Flute Hero positively impacted their breathing technique and sound production. The metrics showed significant improvement in the breath period of the treatment group, but did not show significant improvement in abdominal or thoracic expansion. Further research with changes to the experimental methodology, including longer treatment run time, might garner better results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.286
GPT teacher head0.569
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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