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Record W4416925719 · doi:10.1080/14992027.2025.2595212

Remote microphone performance in exercise environments: an effectiveness–implementation study

2025· article· en· W4416925719 on OpenAlexaff
Mohamed Rahme, Vahid Ashkanichenarlogh, Paula Folkeard, Matthew Holden, Kristin Nugent, J Wang, Vijay Parsa, Susan Scollie

Bibliographic record

VenueInternational Journal of Audiology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsWestern University
Fundersnot available
KeywordsMicrophoneHearing lossHearing aidSound (geography)Audiometry

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to evaluate the effectiveness and feasibility of implementing remote microphones in group exercise environments. DESIGN: This study used a modified effectiveness-implementation hybrid design, with an electroacoustic assessment of hearing aid remote microphones using manikins as simulated talkers and listeners. Test conditions were at varying distances, azimuths, and reverberation levels in exercise environments. The listener manikins were programmed to simulate mild-to-moderate sloping audiograms and were fitted with three brands of premium receiver-in-the-canal style hearing aids, including their proprietary remote microphones (both low- and high-technology levels). Recordings of these conditions were compared to the reference recordings using the Hearing Aid Speech Perception Index. STUDY SAMPLE: This was a manikin-based research study, therefore, human subjects were not recruited. RESULTS: Remote microphones produced higher speech perception scores than hearing aids alone regardless of reverberation levels, hearing loss, or the distances and azimuths relative to the simulated talker. Remote microphones were shown to be feasible to implement in exercise environments. CONCLUSIONS: Remote microphone technology may be beneficial to exercisers with hearing loss in exercise environments, however, this area remains highly understudied. Future behavioural assessments of remote microphones in environments with individuals with hearing loss are discussed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.018
GPT teacher head0.356
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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