Individualized Signal Processing Strategy to Reduce Hearing Health Care Cost/Disp

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 replaci