Hearing System Autonomous Adaptation via Sensor Feedback
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Solution Overview
Problem
Conventional hearing devices require cumbersome manual adjustments and rely on resource-intensive processing for adapting audio processing parameters to user preferences, often losing settings when the acoustic environment changes.
Innovation Solution
A method and system that use a sensor unit with a classifying unit to derive correction data for audio processing parameters based on user adjustments and similarity factors, employing a time-dependent function to update settings autonomously, reducing the need for large storage and processing power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If fuzzy logic or neural network technology is used to automatically calculate improved audio processing parameter settings, then the adaptation to user preferences is improved, but the processing power requirement and reliability worsen
Solution Approach 1:
The hearing device automatically adapts audio processing parameters by detecting user adjustments and acoustic environments, then self-corrects settings without requiring external intervention or complex processing algorithms. The device serves itself by using simple memory storage to recall and apply corrected parameter sets based on detected conditions.
Solution Approach 2:
The invention replaces complex, resource-intensive algorithms (fuzzy logic/neural networks) with simple, lightweight data structures (parameter sets stored in memory). These simple stored parameter sets act as 'cheap' alternatives to computationally expensive processing, requiring minimal power while achieving the same adaptation goal.
2Adaptability or versatility
If fuzzy logic or neural network technology is used to automatically calculate improved audio processing parameter settings, then the adaptation to user preferences is improved, but the reliability worsens
Solution Approach 1:
The system detects user adjustments as feedback signals and uses this feedback to automatically generate and store corrected parameter sets. When similar acoustic conditions are detected again, the system retrieves and applies the stored corrections, creating a reliable feedback loop that continuously improves adaptation without algorithmic complexity.
Solution Approach 2:
The system pre-calculates and stores corrected parameter sets in memory during initial use. These pre-computed parameter sets are then rapidly retrieved and applied when similar acoustic environments are detected, eliminating the need for real-time complex calculations and ensuring reliable, consistent parameter application.
3Ease of manufacture
If conventional manual adjustment procedures are used, then the fitting session can be completed, but the procedure becomes cumbersome and time-consuming
Solution Approach 1:
The hearing device automatically performs the adaptation function that would otherwise require manual adjustment by a professional. The device detects user preferences through automatic sensing of adjustments and acoustic environments, then self-corrects parameters and stores corrected settings, eliminating the need for time-consuming manual fitting procedures.
Solution Approach 2:
The invention replaces the mechanical interaction of manual parameter adjustment with an automatic electronic sensing and correction system. The device uses sensors to detect user adjustments and automatically processes this information to generate corrected parameter sets, substituting the manual mechanical fitting process with an automated electronic system.
4Adaptability or versatility
If automatic learning of setting values is implemented, then the adaptation to user preferences is improved, but the storage space and processing requirements increase
Solution Approach 1:
The invention extracts only the essential information needed for adaptation - the corrected parameter sets - and stores them in compact form in memory. Rather than storing raw user adjustment data or complex model parameters, the system extracts and stores only the final corrected parameter values that are needed for operation, minimizing storage requirements.
Solution Approach 2:
Instead of storing raw user adjustment data and reconstructing preferences through complex processing, the system inverts the approach by directly storing the corrected parameter sets that represent the desired settings. This inverted storage strategy eliminates the need for large storage capacity to hold raw data, as only the essential correction parameters are retained.
Data Source
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AI summary
The method for operating a hearing system comprising at least one hearing device; at least one signal processing unit; at least one user control by means of which at least one audio processing parameter of said signal processing unit is adjustable; and a sensor unit; comprises the steps of a) obtaining adjustment data (userCorr) representative of adjustments of said at least one parameter carried out by operating said at least one user control; b) obtaining characterizing data (p1;p2) from data outputted from said sensor unit substantially at the time said adjustment data are obtained; c) deriving correction data (learntCorr) from said adjustment data (userCorr); wherein step c) is carried out in dependence of said characterizing data; and d) recognizing an update event; and, upon step d): e) using corrected settings for said at least one audio processing parameter in said signal processing unit, which corrected settings are derived in dependence of said correction data (learntCorr). An improved automatic adaptation of the audio processing properties of the hearing system the hearing system user's preference can be achieved.