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Record W2469916564 · doi:10.1097/aud.0000000000000199

Evaluation of Speech-Evoked Envelope Following Responses as an Objective Aided Outcome Measure

2015· article· en· W2469916564 on OpenAlexaffabout
Vijayalakshmi Easwar, David W. Purcell, Steven J. Aiken, Vijay Parsa, Susan Scollie

Bibliographic record

VenueEar and Hearing · 2015
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsDalhousie UniversityWestern University
Fundersnot available
KeywordsAudiologyStimulus (psychology)Sensorineural hearing lossHearing aidHearing lossFormantVowelPsychologyMedicineSpeech recognitionComputer science

Abstract

fetched live from OpenAlex

OBJECTIVES: The present study evaluated a novel test paradigm based on speech-evoked envelope following responses (EFRs) as an objective aided outcome measure for individuals fitted with hearing aids. Although intended for use in infants with hearing loss, this study evaluated the paradigm in adults with hearing loss, as a precursor to further evaluation in infants. The test stimulus was a naturally male-spoken token /susa∫i/, modified to enable recording of eight individual EFRs, two from each vowel for different formants and one from each fricative. In experiment I, sensitivity of the paradigm to changes in audibility due to varying stimulus level and use of hearing aids was tested. In experiment II, sensitivity of the paradigm to changes in aided audible bandwidth was evaluated. As well, experiment II aimed to test convergent validity of the EFR paradigm by comparing the effect of bandwidth on EFRs and behavioral outcome measures of hearing aid fitting. DESIGN: Twenty-one adult hearing aid users with mild to moderately severe sensorineural hearing loss participated in the study. To evaluate the effects of level and amplification in experiment I, the stimulus was presented at 50 and 65 dB SPL through an ER-2 insert earphone in unaided conditions and through individually verified hearing aids in aided conditions. Behavioral thresholds of EFR carriers were obtained using an ER-2 insert earphone to estimate sensation level of EFR carriers. To evaluate the effect of aided audible bandwidth in experiment II, EFRs were elicited by /susa∫i/ low-pass filtered at 1, 2, and 4 kHz and presented through the programmed hearing aid. EFRs recorded in the 65 dB SPL aided condition in experiment I represented the full bandwidth condition. EEG was recorded from the vertex to the nape of the neck over 300 sweeps. Speech discrimination using the University of Western Ontario Distinctive Feature Differences test and sound quality rating using the Multiple-Stimulus Hidden Reference and Anchor paradigm were measured in the same bandwidth conditions. RESULTS: In experiment I, an increase in stimulus level above threshold and the use of amplification resulted in a significant increase in the number of EFRs detected per condition. At positive sensation levels, an increase in level demonstrated a significant increase in response amplitude in unaided and aided conditions. At 50 and 65 dB SPL, the use of amplification led to a significant increase in response amplitude for the majority of carriers. In experiment II, the number of EFR detections and the combined response amplitude of all eight EFRs improved with an increase in bandwidth up to 4 kHz. In contrast, behavioral measures continued to improve at wider bandwidths. Further change in EFR parameters was possibly limited by the hearing aid bandwidth. Significant positive correlations were found between EFR parameters and behavioral test scores in experiment II. CONCLUSIONS: The EFR paradigm demonstrates sensitivity to changes in audibility due to a change in stimulus level, bandwidth, and use of amplification in clinically feasible test times. The paradigm may thus have potential applications as an objective aided outcome measure. Further investigations exploring stimulus-response relationships in aided conditions and validation studies in children are warranted.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.742
Threshold uncertainty score0.745

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
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 head0.219
GPT teacher head0.400
Teacher spread0.181 · 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

Citations54
Published2015
Admission routes2
Has abstractyes

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