How AI reduced fitting time and improved hearing device accuracy

Challenge: Delivering comfort and accuracy at scale

Our client, a global healthcare company, faced difficulties with the fitting and fine-tuning of hearing devices worn daily by patients around the world. While these devices are essential for enabling patients with hearing impairments to live as normal a life as possible, the existing calibration process was slow and inefficient. It required numerous manual interactions, involved highly complex parameters, and often resulted in ill-calibrated devices. This led to long fitting times, increased clinician workload, and a suboptimal patient experience

How we helped

We implemented sophisticated ML models that predicted user adjustment patterns during live fine-tuning sessions and also optimized the hearing device parameters for individual users. This personalized approach allowed the devices to learn from each interaction, ensuring a more accurate fit and improved user experience with fewer manual adjustments required.

The impact: Faster fitting, happier patients

• The new ML-driven system significantly reduced the time and complexity involved in fitting hearing devices, providing users with a better-fitted product.
• By accurately predicting and automating parameter adjustments, the system improved overall satisfaction with the device's performance.
• Seamless integration with existing systems, boosting AI adoption.

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