Audio Equalization Using ABR Feedback for Hearing Calibration
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Solution Overview
Problem
Conventional audio devices rely on user input for adjusting sound equalization parameters, which can be time-consuming and ineffective, as users often struggle to properly configure settings to match their hearing characteristics or preferences, and existing methods for determining hearing thresholds are cumbersome and do not accurately reflect responses to complex audio samples.
Innovation Solution
A method and system that use auditory brainstem response (ABR) and complex ABR data to determine equalization parameters by analyzing brain activity signals from electrodes while playing audio samples, allowing for dynamic adjustment of sound parameters to improve sound perception for multiple frequency bands, including complex audio samples like music tracks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually adjust multiple sound equalization parameters to configure output to suit hearing characteristics, then sound customization accuracy is improved, but user effort and time consumption increase significantly
Solution Approach 1:
The system automatically determines equalization parameters by analyzing the user's brain activity signals (ABR and cABR) without requiring manual adjustment. The processor autonomously processes the neural responses to audio stimuli and configures the sound output parameters, allowing the system to serve itself rather than requiring continuous user intervention for calibration.
Solution Approach 2:
The patent replaces the manual mechanical adjustment process with an automated neurophysiological measurement system. Instead of users physically turning knobs or sliding controls to adjust equalization parameters, the system uses electrodes to detect brainstem responses and automatically computes the optimal parameters based on the measured neural activity patterns.
2Measurement precision
If conventional tone tests are used to determine hearing thresholds, then hearing characteristics are measured, but the tests are cumbersome and do not accurately reflect responses to complex audio samples
Solution Approach 1:
The system changes the type of audio stimulus from simple pure tones to complex audio samples (such as music tracks or environmental sounds) that better represent real-world listening conditions. By using complex stimuli with multiple frequencies and temporal structures, the system measures hearing thresholds in a more ecologically valid context while maintaining measurement accuracy through analysis of the brain's response to the complex signal.
Solution Approach 2:
The system uses electrodes to directly copy and measure the neural response (ABR and cABR signals) to audio stimuli, bypassing the need for subjective user reporting. This objective measurement approach captures the actual neural processing of complex audio samples without requiring the user to actively participate in the testing process, making it both accurate and easy to administer.
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 accurate determination of sound parameters without requiring lengthy tone tests, reducing user effort and time in calibrating audio devices, enabling better sound customization tailored to individual hearing characteristics.
Implementation Method 1
acquiring, via one or more electrodes, auditory brainstem response (ABR) data associated to the first audio sample
Implementation Method 2
determining, via a processor, one or more equalization parameters based on the ABR data
Data Source
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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.