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Related Experiment Video

Updated: Aug 12, 2025

Electrically Evoked Stapedius Reflex Measurements in Cochlear Implantation and Its Application in the Postoperative Fitting Process
07:00

Electrically Evoked Stapedius Reflex Measurements in Cochlear Implantation and Its Application in the Postoperative Fitting Process

Published on: June 21, 2024

853

Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients.

Justine Wathour1, Paul J Govaerts, Emilie Lacroix

  • 1Cliniques universitaires Saint-Luc, Avenue Hippocrate 100, 1200, Brussels, Belgium.

Otology & Neurotology : Official Publication of the American Otological Society, American Neurotology Society [And] European Academy of Otology and Neurotology
|February 2, 2023
PubMed
Summary

Artificial intelligence (AI) software improved hearing outcomes for cochlear implant (CI) patients. The AI-assisted mapping enhanced pure tone audiometry and speech understanding, offering a potential assistive tool for better audiological results.

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Area of Science:

  • Audiology
  • Biomedical Engineering
  • Artificial Intelligence

Background:

  • Cochlear implants (CIs) are crucial for severe to profound hearing loss, but outcomes vary significantly.
  • Variability in CI fitting is a potential cause for differing patient results.

Purpose of the Study:

  • To investigate the impact of an AI software tool (FOX) on programming cochlear implants (CIs).
  • To evaluate the effect of AI-assisted CI mapping on audiological outcomes in experienced CI users.

Main Methods:

  • Forty-seven experienced CI patients participated in the study.
  • A new CI map was generated using AI software and compared to the patient's previous manual map.
  • Auditory outcomes were assessed after 15 days of using the AI-generated map.

Main Results:

  • Significant improvements were observed in pure tone audiometric thresholds at 6,000 Hz (median 10 dB improvement).
  • Phonemic discrimination scores improved by a median of 10%.
  • Speech audiometric scores for soft-intensity and normal-intensity sounds showed median improvements of 10%.

Conclusions:

  • AI-assisted CI mapping shows promise as an assistive tool for experienced CI users.
  • The AI model may enhance audiological outcomes, including high-frequency hearing and speech perception at various levels.