Hearing Aid System Response Improvement





human auditory system, system identification, hearing aid, human ear model, deterministic artificial intelligence, feedforward, Model Predictive Control (MPC)


This study was conducted to understand the response of hearing aids to different inputs and propose a novel technique to significantly improve performance of hearing aid implants. The motivation behind this study is to represent behavior of hearing aid system with simple input-output relation rather than complicated models. This representation offered a better understanding of the system and inspired an innovation to improve the hearing aid implants. A model of a hearing aid system called cochlear transplants is generated and used to simulate the system response. Using multiple methods, simplified input-output relations are derived. Results from these methods are compared and conclusions are drawn regarding which method is best for this application. One of the methods used resulted in 69.7 % error measure reduction compared to the benchmark method. This method was later used to produce a simplified model, which was then used as the basis for analysis of different configurations. A qualitative comparison of model was made, and significant improvement of cochlear transplants was achieved.


Received: 17 February 2023 | Revised: 29 May 2023 | Accepted: 8 June 2023


Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.


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How to Cite

Parmar, P., & Sands, T. (2023). Hearing Aid System Response Improvement. Journal of Computational and Cognitive Engineering, 2(4), 304–311. https://doi.org/10.47852/bonviewJCCE3202768



Research Articles