This project describes a novel approach to automate and individualize the signal processing strategy for hearing aids (HA) that can result in improved speech intelligibility in background noise, greater user satisfaction and acceptance for HAs, and reduce barriers to affordable hearing health care. The proposed Individualized Signal Processing Strategy (ISPS) is based on 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 can result 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 HA service delivery models yet can be implemented within existing business models and in concert with current practitioners. The ISPS method effectively replaces target-based HA fitting (e.g. NAL-NL2) with individualized speech-based parameter adjustment. The proposed work follows successful completion of our pilot project and builds upon the research team?s prior research on novel fitting methods for cochlear implant (CI) devices recently acquired by Cochlear, Ltd. Following the successful implementation of ISPS and integration with commercial HA software in the pilot study, we demonstrated feasibility including a field study in which performance outcomes for the ISPS method were as good as a conventional HA fitting method and only took a fraction of the time, despite ISPS having no prior knowledge of patient characteristics and no audiogram. Successful maturation and commercialization of the ISPS technology in Phase II will address several barriers identified in the previous RFA-DC-12-004 including physical, infrastructure, and knowledge barriers (by allowing remote or self-fitting HAs), economic barriers (by reducing overall costs), and cultural barriers (by providing easy access to HA fitting for patients who tend to avoid professional help). This Phase II project will develop an operational ISPS method by (1) integrating ISPS with hardware/software systems of our industry partners, (2) refine and enhance the ISPS method to improve efficiency and effectiveness of fitting hearing instruments, (3) build support for the use of ISPS in multiple marketplaces, and (4) evaluate the technology through field trials in different service delivery environments by 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 III project will focus on the transition of the technology to support remote and self-fitting of hearing instruments.
This project seeks to develop, implement and test a novel automated method for fitting hearing aids based on real-time speech perception performance. This automated approach can improve hearing aid success while significant reducing costs of hearing health care. The automation of the fitting procedure can dramatically increase accessibility of hearing health care.
