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

• Published in: 2009 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 2121 - 2124
• Main Authors: Limpaphayom, K., Newcomb, R.W., Isipradit, P.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2009
• Subjects: Artificial neural networks; Auditory system; Deafness; Delay; Ear; Hopfield neural networks; Humans; Inverse problems; Loss measurement; Mathematical model
• ISBN: 1424438276; 9781424438273
• ISSN: 0271-4302; 2158-1525
• DOI: 10.1109/ISCAS.2009.5118214

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.