Development of a stochastic finite element model for use in the diagnosis of middle-ear pathologies
- The calibrated model accurately reproduces the mean and variance of middle-ear measurements like impedance, reflectance, stapes and umbo transfer function. Ligament and joint material parameters have a significant effect on the variance of these measurements, while variations in center of mass positions, for example, have less effect. The neural network trained on the simulated data shows promise for diagnostics, achieving 86-100% sensitivity and 85-93% specificity for detecting otosclerosis and disarticulation, which is similar to the performance of classifiers trained on measured immittance data.
| Author of HS Reutlingen | Lauxmann, Michael; Sackmann, Benjamin; Winkler, Simon |
|---|---|
| URN: | urn:nbn:de:bsz:rt2-opus4-54020 |
| DOI: | https://doi.org/10.1515/bmt-2024-1002 |
| ISSN: | 1862-278X |
| Erschienen in: | Biomedical Engineering / Biomedizinische Technik : Abstracts of the 58th Annual Meeting of the German Society of Biomedical Engineering, 18 - 20 September 2024, Stuttgart |
| Publisher: | De Gruyter |
| Place of publication: | Berlin |
| Document Type: | Conference proceeding |
| Language: | German |
| Publication year: | 2024 |
| Volume: | 69 |
| Issue: | S2 |
| Page Number: | 1 |
| First Page: | 66 |
| DDC classes: | 610 Medizin, Gesundheit |
| Open access?: | Ja |
| Licence (German): |  Open Access |
