scholarly journals Calculation of transfer function of acoustic feedback path for in-the-ear hearing aids with a correction for specific acoustic impedance of a tubule

2006 ◽  
Vol 27 (4) ◽  
pp. 242-244 ◽  
Author(s):  
Katsuya Nakao ◽  
Ryouichi Nishimura ◽  
Yôiti Suzuki
Keyword(s):  
Transfer Function ◽  
Hearing Aids ◽  
Acoustic Impedance ◽  
Acoustic Feedback ◽  
Feedback Path

scholarly journals Acoustic feedback path modeling for hearing aids: Comparison of physical position based and position independent models

2020 ◽  
Vol 147 (1) ◽  
pp. 85-100
Author(s):  
Tobias Sankowsky-Rothe ◽  
Henning Schepker ◽  
Simon Doclo ◽  
Matthias Blau
Keyword(s):  
Hearing Aids ◽  
Path Modeling ◽  
Acoustic Feedback ◽  
Feedback Path ◽  
Physical Position

Simulating the open‐loop transfer function as a means for understanding acoustic feedback in hearing aids

1989 ◽  
Vol 85 (1) ◽  
pp. 454-467 ◽  
Author(s):  
David P. Egolf ◽  
Brett T. Haley ◽  
Henry C. Howell ◽  
Stanislaw Legowski ◽  
Vernon D. Larson
Keyword(s):  
Transfer Function ◽  
Hearing Aids ◽  
Open Loop ◽  
Acoustic Feedback ◽  
Loop Transfer Function

Evaluation of an Articulation-Index Based Model for Predicting the Effects of Adaptive Frequency Response Hearing Aids

1990 ◽  
Vol 33 (4) ◽  
pp. 676-689 ◽  
Author(s):  
David A. Fabry ◽  
Dianne J. Van Tasell
Keyword(s):  
Transfer Function ◽  
Frequency Response ◽  
Hearing Aids ◽  
Background Noise ◽  
Speech Intelligibility ◽  
Hearing Aid ◽  
Hearing Impaired ◽  
Articulation Index ◽  
Intelligibility Ratings ◽  
High Pass

The Articulation Index (AI) was used to evaluate an “adaptive frequency response” (AFR) hearing aid with amplification characteristics that automatically change to become more high-pass with increasing levels of background noise. Speech intelligibility ratings of connected discourse by normal-hearing subjects were predicted well by an empirically derived AI transfer function. That transfer function was used to predict aided speech intelligibility ratings by 12 hearing-impaired subjects wearing a master hearing aid with the Argosy Manhattan Circuit enabled (AFR-on) or disabled (AFR-off). For all subjects, the AI predicted no improvements in speech intelligibility for the AFR-on versus AFR-off condition, and no significant improvements in rated intelligibility were observed. The ability of the AI to predict aided speech intelligibility varied across subjects. However, ratings from every hearing-impaired subject were related monotonically to AI. Therefore, AI calculations may be used to predict relative—but not absolute—levels of speech intelligibility produced under different amplification conditions.

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