Cochlear implant telemedicine: Remote fitting based on psychoacoustic self-tests and artificial intelligence

Area of Science:

• Audiology
• Biomedical Engineering
• Artificial Intelligence in Healthcare

Background:

• Cochlear implants (CI) require precise fitting for optimal hearing outcomes.
• Current CI fitting processes are typically clinic-based and require audiologist intervention.
• Exploring autonomous and remote fitting methods can improve accessibility and patient convenience.

Purpose of the Study:

• To evaluate the feasibility of self-guided cochlear implant (CI) fitting using psychoacoustic self-tests and artificial intelligence (AI).
• To assess adult CI recipients' acceptance and comfort with autonomous fitting procedures.
• To identify challenges and requirements for implementing remote CI fitting.

Main Methods:

• A feasibility study involving six adult CI recipients using Nucleus devices.
• Participants conducted self-administered pure tone audiometry and spectral discrimination tests.
• An AI application (FOX) analyzed self-test results to recommend new CI maps.

Main Results:

• Four out of six participants successfully completed self-tests independently.
• Four participants received AI-generated fitting maps without manual audiologist input.
• All participants found the self-testing and automated fitting concept acceptable, while emphasizing the need for audiologist supervision.

Conclusions:

• Audiological self-assessment combined with AI-driven remote CI fitting is feasible for certain CI recipients.
• Technical and regulatory hurdles must be overcome for widespread adoption of autonomous CI fitting.
• This approach shows promise for enhancing CI care delivery under appropriate supervision.