Modeling and noninvasive correction of auditory disorders with inverse artificial neural network

Author

Limpaphayom, Koranan ; Newcomb, Robert W. ; Isipradit, Permsarp

Author_Institution

Dept. of Electr. & Comput. Eng., Univ. of Maryland, College Park, MD, USA

fYear

2009

fDate

24-27 May 2009

Firstpage

2121

Lastpage

2124

Abstract

A framework for noninvasive correction of hearing impairment is demonstrated with an outlined method of developing into a hearing aid type device. A noninvasive auditory brainstem response (ABR) measured from people with normal hearing and hearing loss is utilized to distinguish among individual hearing functions and characteristics. A model of ABR is developed using the modified nonlinear Hopfield neural network and the model inverse to the modified Hopfield is also derived. The method is presented in system scale as well as in analog behavioral modeling. Simulation results on a model of a patient with sensorineural hearing loss are given as an example.

Keywords

Hopfield neural nets; handicapped aids; hearing; hearing aids; medical computing; analog behavioral modeling; auditory disorders; hearing aid type device; hearing impairment; inverse artificial neural network; modified nonlinear Hopfield neural network; noninvasive auditory brainstem response; noninvasive correction; sensorineural hearing loss; Artificial neural networks; Auditory system; Deafness; Delay; Ear; Hopfield neural networks; Humans; Inverse problems; Loss measurement; Mathematical model;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2009. ISCAS 2009. IEEE International Symposium on

Conference_Location

Taipei

Print_ISBN

978-1-4244-3827-3

Electronic_ISBN

978-1-4244-3828-0

Type

conf

DOI

10.1109/ISCAS.2009.5118214

Filename

5118214