This project describes a novel approach to automate and individualize the signal processing strategy for hearing aids that can result in improved speech intelligibility in background noise, greater user satisfaction and acceptance for hearing aids, and reduce barriers to affordable hearing health care. The proposed Individualized Signal Processing Strategy (ISPS) is based upon individual performance on categorical perception tasks for speech stimuli. This differs from traditional methods based on sophisticated gain models built upon average perception, performance, and preference data. The ability to determine one's ISPS automatically, rapidly and remotely results in dramatic cost-savings and greater accessibility to hearing health care for patients who cannot afford it or for those who lack easy access to the necessary expertise. These technical achievements have the potential to radically change the hearing aid sales and delivery models yet can also be implemented within existing business models by replacing contemporary hearing aid fitting methods (e.g. adjusting to gain-frequency targets followed by subjective fine tuning) with individualized speech-based parameter adjustment. Successful implementation of the ISPS technology will impact several barriers identified in RFA-DC-12-004 including physical, infrastructure and knowledge barriers (by allowing remote or self-fitting hearing aids and minimizing the need for highly skilled expertise), economic barriers (by reducing overall costs) and cultural barriers (by providing easy access to hearing aid fitting for patients who tend to avoid seeking professional help). This Phase I project will demonstrate the feasibility for the ISPS approach by (1) implementing the ISPS on a standard personal computer, (2) integrating the ISPS with a commercially available hearing aid, and (3) completing a pilot clinical study comparing outcomes with ISPS fitting to those achieved with traditional prescriptive gain fitting within the same subjects. Following successful demonstration of these objectives, a Phase II project will be proposed to enable extension of the technology to a wide range of hearing aids, patient characteristics and listening environments, including innovations supporting the use for remote and self-fitting applications.
This project seeks to develop, implement and test a novel approach for fitting hearing aids using an individual's speech perception abilities. This automated approach can improved listener performance while significant reducing costs of hearing health care. The automation of the fitting procedure can dramatically increase accessibility of hearing health care.
