Presenting a novel, neurofuzzy approach for devices that combine neural networks and fuzzy logic to achieve optimal gain requirements - Next-generation hearing prosthetics

Abstract

Neural networks and fuzzy logic are powerful tools for next-generation hearing prosthetics. A neural network, as a function fitter to map the hearing loss to desired gains requirements, provides many benefits over other approaches. The network is able to learn dynamically through experience. It is open and expandable - a physician can easily incorporate new knowledge into the system. Fuzzy logic, on the other hand, is an indispensable tool for the tuning process. It builds a direct and reasonable link between a user's subjective evaluation and the actual required modifications to the gain targets. Again, physicians are free to add new rules to the rule base in reflection of specific needs and patterns. The presented neurofuzzy approach helps hearing prosthetic devices not only in an offline fitting process, but also in online operations. Next-generation hearing prosthetics will be more intelligent than current devices. Hearing aids should be situation-dependent and capable of evolving or adapting. The neurofuzzy approach makes these features possible.