Hearing Aid Fitting Curves for Self-Service Acoustic Customization
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Solution Overview
Problem
Conventional hearing aid fittings require clinical settings and audiologist intervention for tuning, limiting user satisfaction and convenience, and personal sound amplification products lack advanced customization options.
Innovation Solution
A system and method utilizing a hearing database and computing device to derive initial default fitting curves based on user age, allowing user-adjustable spectral balance through a smartphone interface, incorporating averaging, principal component analysis, and neural networks to optimize hearing aid settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If hearing aid fittings are performed in clinical settings with audiologist intervention, then customization and acoustic performance are improved, but time consumption and cost increase
Solution Approach 1:
The system enables users to perform hearing aid fittings independently through automated algorithms that process audiogram data and generate fitting curves without requiring audiologist intervention. The fitting process is self-service oriented, allowing users to complete adjustments via smartphone applications while the system automatically tunes hearing aid parameters based on the user's hearing profile.
Solution Approach 2:
The patent replaces the mechanical/clinical system of audiologist-based fittings with an automated computational system. Machine learning algorithms and signal processing techniques substitute for manual professional assessment, enabling automated generation of fitting curves from audiogram data without requiring physical presence in clinical settings.
2Manufacturing precision
If hearing aid fittings are performed in clinical settings with audiologist intervention, then acoustic performance customization is improved, but cost increases
Solution Approach 1:
By enabling users to perform their own fittings through automated systems and smartphone applications, the patent eliminates the need for expensive professional services. The self-service model allows users to access fitting capabilities at home, significantly reducing the cost associated with clinical visits and audiologist time.
Solution Approach 2:
The system uses cost-effective computational methods and readily available smartphone technology to replace expensive professional equipment and services. The automated algorithms run on consumer devices, eliminating the need for specialized clinical infrastructure and reducing overall system cost.
3Ease of operation
If personal sound amplification products are distributed directly to consumers, then convenience and accessibility are improved, but customization options are limited
Solution Approach 1:
The patent replaces basic manual adjustment interfaces with automated computational systems that process audiogram data and generate optimized fitting curves. This substitution enables PSAPs to provide clinical-grade customization capabilities through algorithmic processing, matching the adaptability of traditional hearing aids while maintaining direct-to-consumer distribution advantages.
4Manufacturing precision
If traditional audiogram-based tuning is used, then hearing loss matching is improved, but user convenience and accessibility worsen
Solution Approach 1:
The system allows users to perform their own hearing aid fittings by processing their audiogram data through automated algorithms accessible via smartphone applications. Users can complete the fitting process independently at home, eliminating the need to travel to clinical settings while still achieving precise hearing loss matching through computational processing.
Solution Approach 2:
The system performs preliminary processing of audiogram data to generate fitting curves before the user needs them. By pre-processing the hearing threshold data and automatically generating optimized hearing aid parameters, the system eliminates the need for users to wait for professional processing, providing immediate results upon data input.
Data Source
AI summary
Systems for performing hearing aid fittings include a hearing database and a computing device having a processor. The processor is configured to extract a subset of existing most comfortable level (MCL) curves from a set of existing MCL curves stored at a hearing database communicatively coupled to the computing device. The processor is configured to execute a smoothing process on the subset of existing MCL curves to derive a plurality of representative MCL fitting curves. The processor is configured to automatically select a first one of the representative MCL fitting curves as an initial default MCL fitting curve and receive user adjustment feedback to the initial default MCL fitting curve. The processor is configured to automatically select a second one of the representative MCL fitting curves as a selected MCL fitting curve based on the user adjustment feedback and upload the selected MCL fitting curve to a hearing aid.