Hearing Aid Probabilistic Compensation for Frequency-Dependent Loss
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Solution Overview
Problem
Current hearing aids for sensorineural hearing loss lack a mathematical description of hearing loss, making it difficult to evaluate and compare compensation methods objectively, relying heavily on subjective testing and empirical rules.
Innovation Solution
A probabilistic hearing loss compensation method using a predetermined hearing loss model, such as the Zurek Model, to process audio signals and restore hearing to normal levels through a probabilistic compensator, which can include Bayesian inference algorithms like Kalman filters, ensuring objective evaluation and frequency-dependent processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic range compressors are configured with multiple frequency bands to account for frequency-dependent hearing loss, then hearing loss compensation performance is improved, but device complexity increases
Solution Approach 1:
The patent divides the audio signal into multiple frequency bands (typically 2-8 bands) and applies separate compression parameters to each band. This segmentation allows the system to account for frequency-dependent hearing loss characteristics while maintaining manageable complexity through modular processing of each band independently.
Solution Approach 2:
The patent implements dynamic adjustment of compression parameters (compression ratio, knee points, attack/release time constants) for each frequency band based on real-time signal characteristics and fitted hearing loss data. This dynamic adaptation optimizes compensation performance across varying listening conditions without requiring manual reconfiguration.
2Ease of operation
If empirical fitting rules are used to adjust compressor parameters, then ease of operation is improved, but manufacturing precision of hearing loss compensation deteriorates
Solution Approach 1:
The patent incorporates feedback loops that continuously monitor the effectiveness of compression parameter adjustments and automatically refine them based on measured outcomes against the fitted hearing loss model. This closed-loop approach ensures high precision compensation while minimizing manual intervention requirements.
Solution Approach 2:
The patent systematically varies compression parameters (compression ratio, knee point positions, attack/release time constants) across different frequency bands based on mathematically fitted hearing loss characteristics. This parameter optimization process transforms empirical fitting into a precision-driven configuration approach.
3Ease of operation
If subjective testing is used to evaluate dynamic range compressor algorithms, then ease of operation is maintained, but measurement precision of hearing loss compensation deteriorates
Solution Approach 1:
The patent replaces subjective human evaluation with objective computational metrics based on fitted hearing loss models. The system uses mathematical calculations to predict and measure compensation effectiveness, substituting subjective listening tests with precise algorithmic assessment that can be automatically computed and compared.
Solution Approach 2:
The patent introduces fitted hearing loss models as an intermediary between the compressor algorithms and evaluation process. These models serve as mathematical mediators that translate subjective hearing loss characteristics into objective, measurable parameters that can be systematically evaluated and compared across different algorithms.
Data Source
AI summary
A hearing aid includes: an input transducer for provision of an audio signal in response to sound; a hearing loss model for calculation of a hearing loss as a function of a signal level of the audio signal; and a probabilistic hearing loss compensator that is configured to process the audio signal into a hearing loss compensated audio signal in such a way that the hearing loss is restored to normal hearing in accordance with the hearing loss model.