Project Details
Abstract
This project is to analyze the correction of human ear canal shape and gain by canal resonance
within three years. The model of the ear auditory canal (EAC) of the subjects for this analysis
will be reconstructed based on computed tomography (CT) non-invasively. The geometry of
TM then reconstructed as a 3D mode of the EAC. The geometry of the EAC will include
surface area, volume and 3D curvature obtained by sine law and cosine law. The curvature of
the first bend and second bend were also calculated by the equation of curvature. Further, we
will use water to irrigate and fill the EAC invasively. The ear impression will be also obtained.
Then calculate the curvature and geometry of the EAC. Finally, the subjects will be tested by
pure-tone audiometry, middle ear tympanometry and real ear measurement to measure the
resonance of the EAC. The specific aims include: (1) The 3D model of EAC will be
reconstructed by image processing technique. The geometry, curvature and volume of EAC
will be obtained non-invasively. (2) To irrigate the EAC with water and ear impression
harvested the EAC model. Then we can obtain the real geometry of EAC to develop an
imaging procedure of CT image for the optimal quality of 2D image and 3D mode of patients’
EAC. (3) The auditory function will be evaluated by the hearing tests, such as pure tone
audiometry, speech audiometry and tympanometry. Real ear measure will be used to obtain
the resonance of the EAC of the subjects. Furthermore, the correction of human ear canal
shape and gain by canal resonance can be evaluated in great detail and will be helpful for
developing hearing devices.
Project IDs
Project ID:PB9808-2373
External Project ID:NSC98-2221-E182-010
External Project ID:NSC98-2221-E182-010
Status | Finished |
---|---|
Effective start/end date | 01/08/09 → 31/07/10 |
Keywords
- exteranl auditory canal
- resonance gain
- ear impression
- curvature
- volume
- non-invasively
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.