Of late, there has been an increase in hearing impairment cases and to provide the most advantageous solutions to them is an uphill task for audiologists. Significant difficulty faced by the audiologists is in effective programming of hearing aids to provide enhanced satisfaction to the users. The main aim of our study was to develop a software intelligent system (SIS): (i) to perform the required audiological investigations for finding the degree and type of hearing loss, and (ii) to suggest appropriate values of hearing aid parameters for enhancing the speech intelligibility and the satisfaction level among the hearing aid users. In this paper, we present a Neuro-Fuzzy based SIS to automatically predict and suggest the hearing-aid parameters such as gain values, compression ratio and threshold knee point, which are needed to be fixed for different octave frequencies of sound inputs during the hearing-aid trial. The test signals for audiological investigations are generated through the standard hardware present in a personal computer system and with the aid of a software algorithm. The proposed system was validated with 243 subjects’ data collected at the Government General Hospital, Chennai, India. The calculated sensitivity, specificity and accuracy of the proposed audiometer incorporated in the SIS were 98.6%, 96.4 and 98.2%, respectively, by comparing its interpretations with those of the ‘gold standard’ audiometers. Furthermore, 91% (221 of 243) of the hearing impaired subjects attained satisfaction in the first hearing aid trials itself with the gain values as recommended by the improved SIS. The proposed system reduced around 75% of the ‘trial and error’ time spent by audiologists for enhancing satisfactory usage of the hearing aid. Hence, the proposed SIS could be used to find the degree and type of hearing loss and to recommend hearing aid parameters to provide optimal solutions to the hearing aid users.
Journal of Medical Systems – Springer Journals
Published: Jun 2, 2018
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