ABR-Based Sound Equalization for Faster Hearing Calibration
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Solution Overview
Problem
Conventional audio devices require users to manually adjust multiple sound equalization parameters, which can be time-consuming and inaccurate, especially when trying to match hearing characteristics or preferences, and existing audiology devices for determining hearing thresholds are cumbersome and do not accurately reflect responses to complex audio samples.
Innovation Solution
A method using auditory brainstem response (ABR) and complex ABR data to determine and adjust sound equalization parameters, analyzing brain activity signals from electrodes while playing audio samples, allowing for dynamic modification of parameters to improve sound output matching user hearing characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users manually adjust multiple sound equalization parameters, then sound output can be customized to match hearing characteristics, but the process becomes time-consuming and complex
Solution Approach 1:
The system automatically determines equalization parameters by analyzing ABR data from the user's brainstem response to test tones, eliminating the need for manual adjustment. The processor compares the ABR data to reference data and autonomously configures the frequency-dependent gain values, allowing the device to serve itself in the calibration process.
Solution Approach 2:
The patent replaces the manual mechanical adjustment process with an automated physiological measurement system. Instead of users physically turning knobs or sliding controls, the system uses electrodes to detect electrical responses from the auditory brainstem and computationally determines the optimal equalization parameters.
2Measurement precision
If conventional audiology devices determine hearing thresholds using tone series, then hearing thresholds can be measured, but the process is cumbersome and does not accurately reflect responses to complex audio samples
Solution Approach 1:
The system uses the same ABR measurement technique for both determining hearing thresholds and optimizing equalization parameters for complex audio samples like music. The processor analyzes the physiological response to configure frequency-dependent gain values that improve perception of complex sounds, making the device versatile for multiple audio processing goals without requiring separate cumbersome procedures.
Solution Approach 2:
The system changes the approach from measuring thresholds in isolation to using the same physiological measurements to optimize multiple audio parameters simultaneously. By analyzing ABR responses across different frequency bands, the processor determines a set of equalization parameters that collectively improve the user's perception of complex audio content, not just isolated tones.
3Manufacturing precision
If users adjust equalization parameters for multiple frequency bands, then sound output can be fine-tuned, but the interdependence of parameters makes the process complex and iterative
Solution Approach 1:
The system automatically determines the interdependent equalization parameters by analyzing the user's physiological response. The processor compares the measured ABR data to reference data and computationally solves for the optimal set of frequency-dependent gain values, eliminating the need for users to manually navigate the complex interrelationships between parameters.
Solution Approach 2:
The system uses real-time feedback from the user's auditory brainstem response to determine equalization parameters. The electrodes detect the physiological response to test tones, and the processor uses this feedback to calculate the optimal gain values for each frequency band, ensuring the parameters are precisely tuned to the individual user's hearing characteristics.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for more accurate determination of sound parameters for multiple frequency bands without requiring users to listen to lengthy tone series, reducing calibration time and effort, and enabling precise adjustment for complex audio samples like music tracks.
Implementation Method 1
acquiring, via one or more electrodes, auditory brainstem response (ABR) data associated with a first audio sample
Data Source
AI summary
A technique for determining one or more equalization parameters includes acquiring, via one or more electrodes, auditory brainstem response (ABR) data associated with a first audio sample and determining, via a processor, one or more equalization parameters based on the ABR data. The technique further includes reproducing a second audio sample based on the one or more equalization parameters, acquiring, via the one or more electrodes, complex auditory brainstem response (cABR) data associated with the second audio sample, and comparing, via the processor, the cABR data to at least one representation of the second audio sample to determine at least one measure of similarity. The technique further includes modifying the one or more equalization parameters based on the at least one measure of similarity.