Hearing Aid Processing Changes Tone Burst Onset: Effect on Cortical Auditory Evoked Potentials in Individuals With Normal Audiometric Thresholds
Bibliographic record
Abstract
PURPOSE: The validity of using the cortical auditory evoked potential (CAEP) as an objective measure of hearing aid outcome has been questioned in the literature due to stimulus modifications caused by hearing aid processing. This study aimed to investigate the effects of hearing aid processing on the CAEP elicited with tone bursts that may have altered onsets. METHOD: CAEPs to unprocessed and hearing aid-processed tone bursts were obtained from 16 individuals with normal audiometric thresholds when the onset time, level, and signal-to-noise ratio (SNR) were matched between the 2 conditions. Tone bursts processed by the hearing aid were recorded in an anechoic box and were presented through insert receivers. Unprocessed tone bursts were superimposed with hearing aid noise floor to match the SNR of the hearing aid-processed tone bursts. RESULTS: Shortening of rise time and overshoot at the onset of the tone burst were evident in the hearing aid-processed stimuli. Statistical analysis of data showed no significant effects of hearing aid processing on the latency or amplitude of CAEP peaks (p > .05). CONCLUSION: The changes in rise time occurring in the tone bursts due to hearing aid processing may not confound CAEP measures that are used to validate hearing aid fitting.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".