Simulator Verification Is Potentially Beneficial for the Fitting of Softband Bone Conduction Hearing Devices in Young Children
Bibliographic record
Abstract
HYPOTHESIS: The current study employed a skull-simulator verification method to assess whether the output of softband bone conduction hearing devices (BCHDs) at the manufacturer's default settings deviated widely from the target determined by the fitting formula. BACKGROUND: Real ear analysis is utilized for the verification of the fitting of air conduction hearing devices (ACHDs) in a variety of institutions. This procedure, however, has not been used in the fitting of BCHDs, largely due to the difficulty of testing the output of these devices to temporal bones. Despite the availability of skull simulators, they have not been utilized clinically to measure BCHD output. MATERIALS AND METHODS: This prospective, single-center study enrolled 42 subjects, aged 3 months to 10 years, with microtia-atresia-associated mild-to-severe bilateral conductive hearing loss. Hearing sensitivity was evaluated behaviorally by pure tone audiometry (PTA) in 22 subjects 4 years or older (the PTA group), and by auditory brainstem response (ABR) in 20 subjects younger than 4 years (the ABR group). Following 6 months of subjects wearing the prescribed softband BCHDs, their dial level (DL) thresholds were reassessed while using their own BCHDs, configured with zero gain across all frequencies, functioning solely as a bone vibrator. These DL thresholds were inputted into the fitting formula, desired sensation level-bone conduction devices (DSL-BCD) for children, to obtain the target values of BCHD output. The simulator output of the BCHD programmed at the manufacturer's default setting was measured in response to speech presented at 55, 65, and 80 dB SPL, followed by gain adjustment based on the differences between the simulator output and the target. Aided speech intelligibility index (SII) was measured before and after the gain adjustment. RESULTS: The softband BCHDs at the manufacturer's settings generally had lower output than the prescribed target values. This difference was larger at low frequencies and low levels. Across the 12 points tested (four frequencies from 500 to 4000 Hz multiplied by three levels), 22 (52.3%) and 42 (100%) BCHDs had deviations of +7 and +5 dB, respectively, at one point or more. The gain adjustments reduced the deviation and improved the SII values at the two lower levels of speech presented. CONCLUSION: The simulator output of softband bone conduction hearing devices (BCHDs) with the manufacturer's settings may exhibit significant deviations from the formula. Objective output verification should be considered a beneficial step in BCHD fitting and is recommended when applicable.
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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 | 0.002 | 0.011 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".