Adaptive Feedback Cancellation Filter Divergence Prevention
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Solution Overview
Problem
Hearing aids face challenges with feedback mitigation, particularly in open fittings that result in low Maximum Stable Gain, leading to inadequate audio amplification and the occurrence of undesirable sound artifacts like chirps or squeals due to filter divergence during quiet periods.
Innovation Solution
An improved adaptive feedback cancellation (AFBC) system that prevents filter divergence by freezing filter coefficients during quiet periods and gradually adapting them when sound returns, using a noise threshold to maintain stable feedback cancellation performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If open fitting is used to improve natural sound, then natural sound quality is improved, but Maximum Stable Gain decreases leading to insufficient audio amplification
Solution Approach 1:
The patent employs adaptive feedback cancellation (AFBC) technology that continuously monitors and cancels feedback signals in real-time. By using a feedback cancellation filter that adapts to changing acoustic conditions, the system can compensate for the low MSG caused by open fittings, thereby maintaining both natural sound quality and adequate amplification capability
Solution Approach 2:
The system dynamically adjusts filter coefficients based on detected acoustic conditions and noise levels. By changing the parameters of the feedback cancellation filter adaptively, the system optimizes feedback cancellation performance across different operating conditions, enabling stable operation with open fittings while maintaining sufficient gain
2Object-generated harmful factors
If adaptive feedback cancellation is used to reduce feedback, then feedback is reduced, but filter divergence occurs during quiet periods causing sound artifacts
Solution Approach 1:
The patent implements dynamic control of the adaptive filter by detecting quiet periods and adjusting the adaptation state accordingly. During quiet periods when input signal drops below noise floor, the system transitions to a non-adapting state to prevent filter divergence, while resuming adaptation when sound returns, thus maintaining filter stability while continuing to reduce feedback
Solution Approach 2:
The system automatically detects its own operating conditions (quiet periods vs. normal operation) and self-adjusts the filter adaptation state without external intervention. The noise detector monitors input levels and triggers appropriate adaptation modes, enabling the feedback cancellation system to maintain stability across varying acoustic environments
3Speed
If filter adaptation speed is increased to improve feedback cancellation response, then feedback cancellation performance is improved, but filter divergence occurs faster during quiet periods
Solution Approach 1:
The system dynamically adjusts the adaptation speed based on operating conditions. During active sound periods, fast adaptation provides responsive feedback cancellation. During quiet periods below noise floor, the system automatically reduces or suspends adaptation to prevent divergence, thus optimizing both response speed and stability across different operating conditions
Data Source
AI summary
Improved adaptive feedback cancellation may be used to improve performance of audio amplification systems, such as hearing assistance devices, sound reinforcement systems, telephony, and other acoustic amplification and reproduction systems. This adaptive feedback cancellation allows a significant increase in the maximum stable gain of the amplification system, such as by increasing gain while reducing or eliminating feedback. This improves the audibility provided by an audio amplification system. This may provide particular improvements for hearing assistance devices that include open fittings or otherwise have substantial acoustic leakage. This adaptive feedback cancellation provides additional protection from a dynamically changing acoustic leakage by continually updating itself to model the changes, thereby providing increased gain while reducing or eliminating feedback.