Computer-assisted CI fitting: Is the learning capacity of the intelligent agent FOX beneficial for speech understanding?

OBJECTIVE: The software application FOX ('Fitting to Outcome eXpert') is an intelligent agent to assist in the programing of cochlear implant (CI) processors. The current version utilizes a mixture of deterministic and probabilistic logic which is able to improve over time through a learning effect. This study aimed at assessing whether this learning capacity yields measurable improvements in speech understanding. METHODS: A retrospective study was performed on 25 consecutive CI recipients with a median CI use experience of 10 years who came for their annual CI follow-up fitting session. All subjects were assessed by means of speech audiometry with open set monosyllables at 40, 55, 70, and 85 dB SPL in quiet with their home MAP. Other psychoacoustic tests were executed depending on the audiologist's clinical judgment. The home MAP and the corresponding test results were entered into FOX. If FOX suggested to make MAP changes, they were implemented and another speech audiometry was performed with the new MAP. RESULTS: FOX suggested MAP changes in 21 subjects (84%). The within-subject comparison showed a significant median improvement of 10, 3, 1, and 7% at 40, 55, 70, and 85 dB SPL, respectively. All but two subjects showed an instantaneous improvement in their mean speech audiometric score. DISCUSSION: Persons with long-term CI use, who received a FOX-assisted CI fitting at least 6 months ago, display improved speech understanding after MAP modifications, as recommended by the current version of FOX. This can be explained only by intrinsic improvements in FOX's algorithms, as they have resulted from learning. This learning is an inherent feature of artificial intelligence and it may yield measurable benefit in speech understanding even in long-term CI recipients.