The Mechanical Impedance of the Human Skull via Direct Bone Conduction Implants
Bibliographic record
Abstract
Bo Håkansson,1 Fausto Woelflin,1,2 Anders Tjellström,3 William Hodgetts2 1Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden; 2Department of Communication Sciences and Disorders, University of Alberta, Edmonton, Canada; 3Department of Otolaryngology, Head and Neck Surgery, Sahlgrenska Academy, Gothenburg, SwedenCorrespondence: Bo HåkanssonDepartment of Electrical Engineering, Chalmers University of Technology, Hörsalsvägen 9, Gothenburg 41296, SwedenTel +46 317721807Email boh@chalmers.sePurpose: The mechanical skull impedance is used in the design of direct bone drive hearing systems. This impedance is also important for the design of skull simulators used in manufacturing, service, and fitting procedures of such devices.Patients and Methods: The skull impedance was measured in 45 patients (25 female and 20 male) who were using percutaneous bone conduction implants (Ponto system or Baha system). Patients were recruited as a consecutive prospective case series and having an average age of 55.4 years (range 18– 80 years). Seven patients were treated in Gothenburg, Sweden, and 38 patients in Edmonton, Canada. An impedance head (B&K 8001), driven by an excitation transducer with emphasized low-frequency response, was used to measure the mechanical point impedance with a swept sine from 100 to 10k Hz.Results and Discussion: The skull impedance was found to have an anti-resonance of approximately 150 Hz, with a median maximum magnitude of 4500 mechanical ohms. Below this anti-resonance, the mechanical impedance was mainly mass-controlled corresponding to an effective skull mass of 2.5 kg at 100 Hz with substantial damping from neck and shoulder. Above the anti-resonance and up to 4 kHz, the impedance was stiffness-controlled, with a total compliance of approximately 450n m/N with a small amount of damping. At frequencies above 4 kHz, the skull impedance becomes gradually mass-controlled originating from the mass of the osseointegrated implant and adjacent bone. No significant differences related to gender or skull abnormalities were seen, just a slight dependence on age and major ear surgeries. The variability of the mechanical impedance among patients was not found to have any clinical importance.Conclusion: The mechanical skull impedance of percutaneous implants was found to confirm previous studies and can be used for optimizing the design and test procedures of direct bone drive hearing implants.Keywords: bone conduction, mechanical impedance, percutaneous hearing implants, bone anchored hearing aid
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 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 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".