From manual to artificial intelligence fitting: Two cochlear implant case studies

Abstract

Objective: To assess whether CI programming by means of a software application using artificial intelligence (AI), FOX®, may improve cochlear implant (CI) performance.

Patients: Two adult CI recipients who had mixed auditory results with their manual fitting were selected for an AI-assisted fitting. Even after 17 months CI experience and 19 manual fitting sessions, the first subject hadn’t developed open set word recognition. The second subject, after 9 months of manual fitting, had developed good open set word recognition, but his scores remained poor at soft and loud presentation levels.

Main outcome measure(s): Cochlear implant fitting parameters, pure tone thresholds, bisyllabic word recognition, phonemic discrimination scores and loudness scaling curves.

Results: For subject 1, a first approach trying to optimize the home maps by means of AI-proposed adaptations was not successful whereas a second approach based on the use of Automaps (an AI approach based on universal, i.e. population based group statistics) during 3 months allowed the development of open set word recognition. For subject 2, the word recognition scores improved at soft and loud intensities with the AI suggestions. The AI-suggested modifications seem to be atypical.

Conclusions: The two case studies illustrate that adults implanted with manual CI fitting may experience an improvement in their auditory results with AI-assisted fitting.

Keywords:

• Cochlear implant
• Artificial intelligence
• T & C levels
• Auditory outcomes