A Physiologically Explainable Machine Learning Framework for Hearing Aid Development
In this work, we propose a machine learning framework for hearing aid development based on a physiological model of the inner ear (CARFAC) and neural network.
Translating the Panoramic ECAP Method to Clinic
The Panoramic ECAP Method is being made accessible online to allow researchers and clinicians alike to collect the relevant Electrically Evoked Compound Action Potentials and subsequently extract patient-specific estimates of current spread and neural responsiveness for cochlear implant users.
Investigating the Efficacy of the Automatic Classifier AutoSense Sky OS for Children with Cochlear Implants in a Virtual Reality Classroom and other Complex Acoustic Environments
A new listening test in a virtual reality classroom measured speech intelligibility from the front and sound detection from other directions to evaluate the efficacy of automatically switching to directional microphone mode by AutoSense Sky OS in children with cochlear implants.