Hearing Aid Adjustment Using Reference User Profiles
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Solution Overview
Problem
The process of adjusting hearing aids is time-consuming due to variations in individual hearing perceptions and requires repeated hearing tests and evaluations, even with the use of interactive genetic algorithms, which can necessitate dozens or hundreds of iterations to find suitable processing parameters.
Innovation Solution
A hearing aid adjustment device and method that compares user evaluations to reference user evaluations stored in a database, setting hearing aid processing parameters based on similarities to reduce the need for repeated testing and evaluations by identifying suitable parameters from reference users with similar hearing profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If interactive genetic algorithms are used to automatically adjust hearing aid parameters, then the automation of adjustment is improved, but the adjustment time increases significantly due to repeated testing and evaluation
Solution Approach 1:
The system pre-collects and stores evaluation data from multiple reference users for various hearing aid processing parameters in a database before actual adjustment. This preliminary data collection enables the system to predict suitable parameters for new users without requiring extensive real-time testing, thus reducing adjustment time while maintaining automation.
Solution Approach 2:
The system creates virtual models of user hearing characteristics based on reference user data stored in the database. These copied profiles allow the system to simulate and predict user responses to different processing parameters, eliminating the need for repeated physical testing and evaluation while preserving the automated adjustment capability.
2Manufacturing precision
If multiple hearing tests and evaluations are conducted to account for individual hearing perceptions, then the accuracy of parameter setting is improved, but the adjustment process becomes time-consuming
Solution Approach 1:
The system uses pre-collected evaluation data from reference users to create virtual models that copy and represent individual hearing perceptions. These copied profiles enable accurate parameter prediction without requiring multiple actual hearing tests, thus maintaining precision while reducing time consumption.
Solution Approach 2:
The system replaces the mechanical process of conducting multiple physical hearing tests with an information processing approach using stored evaluation data and algorithms. This substitution eliminates the need for repeated physical testing while maintaining the accuracy of parameter setting through data-driven predictions.
3Adaptability or versatility
If hearing aid processing parameters are adjusted to reflect individual user preferences, then the suitability of the hearing aid is improved, but repeated testing and evaluation are required which increases adjustment time
Solution Approach 1:
The system creates virtual models of individual user preferences by copying and analyzing evaluation data from reference users with similar hearing characteristics. These copied preference profiles enable the system to predict suitable processing parameters that reflect individual user preferences without requiring repeated actual testing, thus maintaining adaptability while reducing adjustment time.
Solution Approach 2:
The system introduces a database of pre-collected evaluation data as an intermediary between the user's individual preferences and the hearing aid parameter adjustment. This intermediary enables the system to infer and adapt to individual preferences without requiring direct repeated testing, thus maintaining suitability while reducing time consumption.
Data Source
AI summary
A hearing aid adjustment device (1) has a comparator (22a) and a setting section (22b). The comparator (22a) compares a user evaluation given by a user (T) of a hearing aid (5) in response to sound obtained by hearing aid processing based on fitting theories and hearing level data for the user (T), with a reference evaluation that has been acquired ahead of time and corresponds to each of customers (A to C) and is given by the customers (A to C) in response to sound obtained by hearing aid processing based on fitting theories and hearing level data for the customers (A to C). The setting section (22b) sets the value of a user parameter designating hearing aid processing to be given to a user (T), to a value that is the same as the value of a reference parameter that has been acquired ahead of time and that designates hearing aid processing suited to a customer (A) who gave a reference evaluation similar to the user evaluation, out of the customers (A to C).


