Experienced Adult Cochlear Implant Users Show Improved Speech Recognition When Target Fitting Parameters Are Applied

Area of Science:

• Audiology
• Biomedical Engineering
• Speech Science

Background:

• Cochlear implant (CI) users often experience suboptimal speech recognition.
• Previous research linked electrical dynamic range and aided thresholds to speech perception.
• Prediction models by de Graaff et al. (2020) identified optimal ranges for improved outcomes.

Purpose of the Study:

• To evaluate if de Graaff et al.'s (2020) prediction models can enhance speech recognition in experienced adult postlingual Cochlear CI users.
• To test the hypothesis that refitted sound processor settings improve speech recognition in quiet and noise.
• To assess subjective user preference and perceived loudness with optimized CI settings.

Main Methods:

• A within-participant repeated measures design was employed with 18 adult Cochlear CI users.
• T- and C-levels were adjusted to "optimized settings" based on de Graaff et al.'s (2020) model.
• Measurements included aided thresholds, speech recognition (quiet/noise), and subjective benefit (DOSOS questionnaire) before and after a 4-week acclimatization.

Main Results:

• The mean electrical dynamic range increased from 41.1 to 48.6 CL.
• Speech recognition in quiet significantly improved by 4.9% on average.
• No significant changes were observed in aided thresholds or speech recognition in noise; however, subjective benefit scores improved for speech cues.

Conclusions:

• Optimizing the electrical dynamic range using de Graaff et al.'s (2020) prediction models successfully improved speech recognition in quiet for adult CI users.
• The findings suggest that targeting an electrical dynamic range between 50-60 CL at volume level 10 can enhance quiet listening performance.
• No significant changes in aided thresholds or noise performance were noted, but users preferred the optimized settings, indicating overall benefit.