The Use of Artificial Intelligence to Program Cochlear Implants

OBJECTIVE Cochlear implant (CI) technology and techniques have advanced over the years. There has not been the same degree of change in programming and there remains a lack of standardization techniques. The purpose of this study is to compare performance in cochlear implant subjects using experienced clinician (EC) standard programming methods versus an Artificial Intelligence, FOX based algorithm for programming. STUDY DESIGN Prospective, nonrandomized, multicenter study using within-subject experimental design SETTING:: Tertiary referral centers. PATIENTS Fifty-five adult patients with ≥ 3 months experience with a Nucleus 5, 6, Kanso, or 7 series sound processor. INTERVENTION Therapeutic Main Outcome Measures: CNC words and AzBio sentences in noise (+10 dB SNR) tests were administered in a soundproof booth followed by a direct connect psychoacoustic battery using the EC program. Tests were repeated 1 month later using the optimized FOX program. Subjective measures of patient satisfaction were also measured. RESULTS Performance for the EC program was compared to the FOX program for both measures. Group mean results revealed equivalent performance (Kruskal-Wallis ANOVA p = 0.934) with both programming methods. While some patients had better performance with the FOX method and some performed more poorly, the majority had equivalent performance and preferred the FOX system. CONCLUSION The study demonstrated that on average, FOX outcomes are equivalent to those using traditional programming techniques. In addition, the FOX programming method can effect standardization across centers and increase access for many individuals who could benefit.