Development of a Novel Bone Conduction Verification Tool Using a Surface Microphone: Validation With Percutaneous Bone Conduction Users
Bibliographic record
Abstract
OBJECTIVES: To determine if a newly-designed, forehead-mounted surface microphone would yield equivalent estimates of audibility when compared to audibility measured with a skull simulator for adult bone conduction users. DESIGN: Data was analyzed using a within subjects, repeated measures design. There were two different sensors (skull simulator and surface microphone) measuring the same hearing aid programmed to the same settings for all subjects. We were looking for equivalent results. PATIENTS: Twenty-one adult percutaneous bone conduction users (12 females and 9 males) were recruited for this study. Mean age was 54.32 years with a standard deviation of 14.51 years. Nineteen of the subjects had conductive/mixed hearing loss and two had single-sided deafness. METHODS: To define audibility, we needed to establish two things: (1) in situ-level thresholds at each audiometric frequency in force (skull simulator) and in sound pressure level (SPL; surface microphone). Next, we measured the responses of the preprogrammed test device in force on the skull simulator and in SPL on the surface mic in response to pink noise at three input levels: 55, 65, and 75 dB SPL. The skull simulator responses were converted to real head force responses by means of an individual real head to coupler difference transform. Subtracting the real head force level thresholds from the real head force output of the test aid yielded the audibility for each audiometric frequency for the skull simulator. Subtracting the SPL thresholds from the surface microphone from the SPL output of the test aid yielded the audibility for each audiometric frequency for the surface microphone. The surface microphone was removed and retested to establish the test-retest reliability of the tool. RESULTS: We ran a 2 (sensor) × 3 (input level) × 10 (frequency) mixed analysis of variance to determine if there were any significant main effects and interactions. There was a significant three-way interaction, so we proceeded to explore our planned comparisons. There were 90 planned comparisons of interest, three at each frequency (3 × 10) for the three input levels (30 × 3). Therefore, to minimize a type 1 error associated with multiple comparisons, we adjusted alpha using the Holm-Bonferroni method. There were five comparisons that yielded significant differences between the skull simulator and surface microphone (test and retest) in the estimation of audibility. However, the mean difference in these effects was small at 3.3 dB. Both sensors yielded equivalent results for the majority of comparisons. CONCLUSIONS: Models of bone conduction devices that have intact skin cannot be measured with the skull simulator. This study is the first to present and evaluate a new tool for bone conduction verification. The surface microphone is capable of yielding equivalent audibility measurements as the skull simulator for percutaneous bone conduction users at multiple input levels. This device holds potential for measuring other bone conduction devices (Sentio, BoneBridge, Attract, Soft headband devices) that do not have a percutaneous implant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".