Reconfigurable Multiband Dynamic Range Compression-based FRM Filter for Hearing Aid

Abstract

In this research, we present an innovative method for enhancing the performance of hearing aids using a Multiband Dynamic Range Compression-based Reconfigurable Frequency Response Masking (FRM) Filterbank. First, a unform16-band reconfigurable filter bank, which is reconfigurable, is designed utilizing the FRM scheme. The strategic arrangement of each sub-band within the proposed filter bank is meticulously prepared to optimize the matching performance. Based on the hearing characteristics of patients, the sub-bands can be distributed in low, medium, and high-frequency regions. Also, the gain can be adjusted per the patient's hearing profile from their audiogram for better auditory compensation.
 Further, the Multiband Dynamic Range Compression (MBDRC) technique is applied to address the specific needs of individuals with different frequency-dependent hearing impairments. It involves using dynamic range compression independently to different frequency sub-bands within a filter bank. In MBDRC, the compression parameters, such as compression threshold and ratio, can be adjusted independently for every subband. It allows for a more tailored approach to address the specific hearing needs of different frequency regions. If an individual has more severe hearing loss in high-frequency regions, higher compression ratios and lower compression thresholds can be applied to those subbands to amplify and improve audibility for high-frequency sounds. Once dynamic range compression is applied to each sub-band, the resultant sub-bands are reassembled to yield the ultimate output signal, which can subsequently be transmitted to the speaker or receiver of the hearing aid. A GUI can be helpful for better visualization and parameter control, including gain adjustment and compression parameters of this entire process. With this aim in mind, a GUI has been developed on MATLAB. Different audio files can be imported, and their frequency response can be generated and observed. Based on a person's audiogram, the control parameters can be set to low, medium, or high. Their sub-band distribution in low, medium, and high-frequency regions can be visualized. Further, the filter bank makes automatic gain adjustments, as seen in the GUI. The gain points for each band can also be manually adjusted according to users' hearing characteristics to minimize the error. Also, the compression parameters can be set separately for each subband as per the hearing requirement of the patient. Further, the processed output can be visualized in the output frequency response tab, and the input and output audio signals can be analyzed.