Index of content:
Volume 126, Issue 1, July 2009
- PHYSIOLOGICAL ACOUSTICS 
126(2009); http://dx.doi.org/10.1121/1.3129129View Description Hide Description
A three-dimensional finite element(FE)model of human ear with structures of the external ear canal, middle ear, and cochlea has been developed recently. In this paper, the FEmodel was used to predict the effect of tympanic membrane (TM) perforations on sound transmission through the middle ear. Two perforations were made in the posterior-inferior quadrant and inferior site of the TM in the model with areas of 1.33 and , respectively. These perforations were also created in human temporal bones with the same size and location. The vibrations of the TM (umbo) and stapes footplate were calculated from the model and measured from the temporal bones using laser Doppler vibrometers. The sound pressure in the middle ear cavity was derived from the model and measured from the bones. The results demonstrate that the TM perforations can be simulated in the FEmodel with geometrical visualization. The FEmodel provides reasonable predictions on effects of perforation size and location on middle ear transfer function. The middle ear structure-function relationship can be revealed with multi-field coupled FE analysis.
Optimal electrode selection for multi-channel electroencephalogram based detection of auditory steady-state responses126(2009); http://dx.doi.org/10.1121/1.3133872View Description Hide Description
Auditory steady-state responses (ASSRs) are used for hearing threshold estimation at audiometric frequencies. Hearing impaired newborns, in particular, benefit from this technique as it allows for a more precise diagnosis than traditional techniques, and a hearing aid can be better fitted at an early age. However, measurement duration of current single-channel techniques is still too long for clinical widespread use. This paper evaluates the practical performance of a multi-channel electroencephalogram (EEG) processing strategy based on a detection theory approach. A minimum electrode set is determined for ASSRs with frequencies between 80 and using eight-channel EEGmeasurements of ten normal-hearing adults. This set provides a near-optimal hearing threshold estimate for all subjects and improves response detection significantly for EEG data with numerous artifacts. Multi-channel processing does not significantly improve response detection for EEG data with few artifacts. In this case, best response detection is obtained when noise-weighted averaging is applied on single-channel data. The same test setup (eight channels, ten normal-hearing subjects) is also used to determine a minimum electrode setup for ASSRs. This configuration allows to record near-optimal signal-to-noise ratios for 80% of subjects.