Technology Update SessionSession 2B Accurate first-fit gain settings are essential for successful hearing aid fittings. However, modern hearing aid fitting systems use predictive acoustic models to determine the gain settings that align with prescriptive targets. Because these models rely on population-averaged ear acoustics, they do not account for individual variations in actual ear canal geometry and acoustic coupling. This limitation can result in mismatches between predicted and actual real-ear aided responses (REARs), requiring time-consuming fine-tuning during probe-microphone verification. Starkey’s Acoustic Model Optimization (AMO) feature, available in the Omega AI product family, addresses this challenge by leveraging in-situ electroacoustic measurements during Feedback Canceller (FBC) initialization to construct individualized acoustic models in real-time, improving the accuracy of the initial fit. In a clinical study involving 100 participants, two versions of the AMO feature were evaluated by comparing in-situ audiometry thresholds to gold-standard insert earphone thresholds. Omega AI hearing aids with the updated AMO 2.0 feature demonstrated substantially lower deviations and correlation exceeding 0.9 across most frequencies, confirming improved accuracy in estimating true hearing thresholds when using in-situ audiometry. Additionally, probe-microphone data from 62 Omega AI users showed that AMO 2.0 achieved median REAR deviations within 3 dB of prescriptive targets across most frequencies, with over 66% of fittings falling within a ±5 dB margin, without any manual gain adjustments to the initial fit. Laboratory evaluations using a Head and Torso Simulator (HATS) further demonstrated that AMO 2.0 substantially reduces deviations between measured REARs and prescriptive targets across different coupling styles and prescriptive formulas. Under mismatched acoustic coupling conditions, AMO 2.0 achieved up to an 89% reduction in RMS error for occluded and power dome fittings. These findings validate the algorithm’s ability to detect and correct for real-ear acoustic mismatches, even when fitting software settings do not match the physical coupling. Simulated fine-tuning scenarios showed a marked reduction in the number of gain adjustments required to match targets, translating to faster, more efficient fittings. For clinicians, AMO 2.0 provides significant benefits by improving first-fit accuracy, reducing the need for manual adjustments, and improving the reliability of in-situ audiometry. These advancements support more efficient, personalized fittings and better patient outcomes, reinforcing AMO 2.0 as a valuable tool in modern audiological practice.
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