Personalized Audio Tuning Flow for Hearing Profile Setup
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Solution Overview
Problem
Traditional hearing aid fitting methods, based on pure tone audiometry and audiogram prescriptions, often fail to provide a precise solution for improved speech understanding, requiring multiple follow-up appointments and audiologist adjustments, and are inefficient for quick setup in enterprise or academic settings, with security concerns in cloud-based data storage.
Innovation Solution
A system and method for audio perception tuning using a user interface, real-time tuning mechanism, and digital signal processing filter-bank, allowing users to select and refine personalized hearing profiles through iterative adjustments of parameters like equalization, compression thresholds, and gain values, leveraging a database of sample profiles and guided decision trees.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional pure tone audiometry and audiogram prescription methods are used, then hearing aid fitting can be performed with established protocols, but the precision of speech understanding is insufficient and multiple follow-up appointments are required
Solution Approach 1:
The system performs preliminary actions by presenting multiple sample hearing profiles to users before final fitting, allowing them to select and tune their preferred profile in advance. This preliminary selection and tuning process eliminates the need for multiple follow-up appointments, as the profile is optimized before the hearing aid is programmed.
Solution Approach 2:
The system incorporates real-time feedback by allowing users to listen to audio processed by different sample profiles and provide input on their preferences. Users can iteratively tune parameters based on their perceived listening experience, creating a feedback loop that optimizes the hearing profile precisely for their speech understanding needs.
2Ease of operation
If audiologists manually adjust hearing aid settings during follow-up appointments, then personalized tuning can be achieved, but the process is time-consuming and inefficient for quick setup
Solution Approach 1:
The system enables self-service by allowing users to independently select and tune their hearing profiles without requiring audiologist intervention. Users interact with the system themselves, providing input on their listening preferences and adjusting parameters to achieve their desired sound quality, thereby eliminating the need for time-consuming manual adjustments during appointments.
Solution Approach 2:
The system performs preliminary tuning actions by providing users with pre-configured sample profiles that can be quickly evaluated and adjusted. This preliminary setup process enables rapid configuration of hearing aids without requiring extended appointment times for manual fine-tuning by audiologists.
3Adaptability or versatility
If cloud-based data storage is used for hearing profiles, then data can be accessed and updated remotely, but security concerns arise
Solution Approach 1:
The system introduces an intermediary layer by processing and storing hearing profile data locally on the user's device rather than in centralized cloud storage. This local processing approach acts as an intermediary that maintains security by keeping sensitive hearing data on the user's own device while still enabling remote access capabilities through secure local storage and transfer mechanisms.
Data Source
AI summary
A novel system and method for identifying and establishing personalized audio parameter settings for a person with hearing loss and/or certain listening preferences, without requiring a traditional audiogram or hearing test as a starting point. Instead, two new elements are combined: (1) A group of original sample profiles, and (2) An original tuning flow methodology and algorithm. The tuning flow methodology and algorithm includes a decision-tree conditional logic and structured series of questions that leverage a) the group of sample profiles, and b) new approaches to user interface interaction.