Hearing Aid Feedback Canceller Tuning Using Artifact Logging

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Solution Overview

Problem

Hearing aids experience artifacts such as chirping, howling, or whistling due to acoustic feedback, which are challenging to address with existing methods that rely on universal learning rates and require professional tuning, often being time-consuming and ineffective for individual user scenarios.

Innovation Solution

An automated system for detecting and logging artifacts in hearing devices, computing individual artifact statistics, and adjusting feedback canceller parameters based on comparisons with user data from similar devices to optimize performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If universal learning rates are used for feedback canceller tuning, then device complexity is reduced, but artifact suppression performance deteriorates

Engineering Contradiction:

Improvefeedback canceller tuning complexityVSAvoidartifact suppression performance

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The feedback canceller automatically detects artifacts and adjusts its own parameters without requiring professional tuning. The system monitors for artifacts like chirping and howling, computes artifact statistics from detected data, and autonomously optimizes parameters based on comparisons with population data, enabling self-tuning and eliminating the need for universal learning rates

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system dynamically changes feedback canceller parameters based on computed artifact statistics and population comparisons. Instead of using fixed universal learning rates, the parameters are adjusted according to individual user artifact patterns and population-derived optimal settings, improving artifact suppression while maintaining automated operation

Inventive Principle:

Principle #35Parameter changes

2Reliability

If professional tuning is performed manually, then feedback canceller performance can be optimized, but time consumption increases

Engineering Contradiction:

Improvefeedback canceller performanceVSAvoidtuning time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs automatic artifact detection and parameter optimization without requiring professional intervention. The feedback canceller independently monitors artifacts, computes statistics, compares with population data, and adjusts parameters autonomously, eliminating time-consuming manual tuning while maintaining optimized performance

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-computes artifact statistics from detected artifacts and compares them with population data before final parameter adjustment. This preliminary analysis enables the system to proactively optimize parameters based on predicted performance needs rather than waiting for manual assessment

Inventive Principle:

Principle #10Preliminary action

3Adaptability or versatility

If individual user data is collected and analyzed, then feedback canceller customization improves, but device complexity increases

Engineering Contradiction:

Improvefeedback canceller customizationVSAvoiddata collection and processing complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system uses population artifact data to establish universal patterns that apply across multiple users. By comparing individual artifact statistics with aggregated population data, the system leverages universal characteristics to simplify customization while maintaining individual adaptability, reducing the complexity of processing individual user data

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Measurement precision

If artifact detection and logging is implemented, then feedback canceller tuning accuracy improves, but processing requirements increase

Engineering Contradiction:

Improveartifact detection accuracyVSAvoidprocessing energy consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The system extracts only the essential artifact characteristics and statistics needed for parameter tuning, rather than processing complete raw audio data. By logging and analyzing only relevant artifact parameters and comparing them with population statistics, the system maintains high detection accuracy while minimizing processing energy requirements

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS20260019757A1Artifact detection and logging for tuning of feedback canceller

Publication Date: 2026.01.15 STARKEY LABORATORIES INC

AI summary

Disclosed herein, among other things, are systems and methods for artifact detection and tuning of a feedback canceller. A method includes detecting an artifact of a feedback canceller during operation of a hearing device. Artifact data associated with the detected artifact is stored in a memory of the hearing device, the artifact data including information related to the detected artifact and information related to the hearing device during occurrence of the detected artifact. Artifact statistics are computed based on the stored artifact data, and the artifact data and the artifact statistics are transmitted to an external device. Comparison data is received from the external device, including results of a comparison of artifact data or artifact statistics of the hearing device to artifact data or artifact statistics of other devices. Parameters of the hearing device are automatically adjusted based on the comparison data to improve performance of the feedback canceller.