Abstract: Today’s hearing aid patients are less stigmatized about the use of hearing aids, but have higher expectations regarding sound quality, performance in noise, and connectivity than with previous generations. To date, modern hearing aids have used machine learning and deep neural networks (DNN) to monitor and reduce background noise, but Starkey’s Omega AI is the first product to simultaneously monitor and adapt noise management settings, spatial awareness AND directional microphones. This session will provide an overview of the benefits, including data from clinical research studies and patient testimonials.
Assumptions: Attendees should have a working knowledge of contemporary hearing aid technology, including basic noise management, directional microphones, and connectivity features. Familiarity with foundational concepts in signal processing and clinical fitting practices will support application of advanced AI and DNN-driven hearing aid strategies.
Summary: This session addresses the evolving expectations of today’s hearing aid patients, who seek superior sound quality, performance in noise, and advanced connectivity. Participants will explore how artificial intelligence, machine learning, and deep neural networks, as demonstrated through Starkey Omega AI, enable hearing aids to simultaneously monitor spatial awareness, adapt directional microphone behavior, and optimize noise management. Drawing on clinical research data, participants will gain insight into how integrated AI-driven processing improves real-world listening outcomes. Attendees will leave with concrete clinical takeaways related to patient selection, counseling, and fitting strategies that support evidence-based decisions and enhanced performance in complex listening environments.
Clinical Takeaways: The clinical takeaway for this session is that many current hearing aid signal processing models may be prioritizing directionality over spatial awareness for many patients. The clinical takeaway for this session is that most effective patient-driven hearing aid strategies combine the benefits of speech understanding in noise AND all-day battery life from rechargeable RIC and custom devices.
Learning Objectives:
Upon completion, participants will be able to describe the magnitude of patient benefits of combining adaption of noise reduction, spatial awareness, and directional microphones in laboratory and “real world” use.
Upon completion, participants will be able to explain key differences between machine-learning and deep neural network (DNN) based models of artificial intelligence in “patient friendly” terminology.
Upon completion, participants will be able to list the top four drivers of hearing aid performance, according to HIA’s MarkeTrak surveys.
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