Improving the hearing aid system using optimized variable bandwidth filter based on wolf optimization

Hearing loss sufferers might struggle in noisy environments. A new hearing aid system with noise-reducing filters can improve communication even in a noisy environment. However, current filters drain battery life, have matching errors, and are computationally expensive. Additionally, traditional filter banks have limitations. This paper proposes a novel Wolf-based Fractional Delay Variable Bandwidth Filter (W-FDVBF) to address these issues. The W-FDVBF aims to suppress background noise while optimizing factors like power consumption and computational complexity for a better user experience. Wolf optimization function helps to adjust filter parameters for robust noise reduction, leading to lower power usage, reduced matching errors, and less computational burden. The performance of the designed filter bank is tested in MATLAB and Xilinx software with the Field Programmable Gate Array (FPGA) accelerator. Finally, the obtained results are compared with other existing approaches and have gained better outcomes by attaining less power and matching error. The model achieved a 1.76 matching error and 1.4W power consumption, which is lower than other methods.