Tinnitus Characterization Using Physiological Ear Model
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Solution Overview
Problem
Current tinnitus characterization methods are prone to variability and inaccuracy, particularly for unpracticed listeners, due to difficulties in comparing test tones with perceived tinnitus noise, leading to octave confusion and limited frequency resolution, which complicates the identification of tinnitus frequencies and amplitudes.
Innovation Solution
A method using broadband test signals that assess masking effects to establish a probability correlation, allowing for the reliable identification of tinnitus frequencies and amplitudes by varying signal frequencies and amplitudes based on comparison results, with the aid of a physiological model of the ear to simulate auditory masking effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comparison measurements with test tones are used for tinnitus matching, then tinnitus frequencies can be identified, but the results show high variability and octave confusion occurs particularly for unpracticed listeners
Solution Approach 1:
The patent introduces an intermediary physiological model of the ear (including outer ear, middle ear, inner ear, and cochlea) that acts as a mediator between the test tones and the tinnitus perception. This model transforms the direct comparison task into an indirect assessment through simulated auditory masking effects, reducing the cognitive burden on listeners and eliminating octave confusion by providing a physiological reference framework for frequency identification
Solution Approach 2:
The patent replaces the mechanical comparison process (where listeners directly compare test tones to tinnitus) with a computational approach using physiological models and algorithms. The system automatically processes test tone responses through simulated ear models to determine tinnitus frequencies, substituting the unreliable human comparison mechanism with a more reliable computational system that accounts for physiological masking effects
2Measurement precision
If frequency step size is reduced to improve frequency resolution, then tinnitus frequencies can be identified more precisely, but the measurement process becomes time consuming
Solution Approach 1:
The patent performs preliminary actions by pre-computing and storing transfer functions for different frequency regions and pre-simulating the physiological ear model responses. Before the actual tinnitus matching, the system prepares the computational framework including outer ear, middle ear, and cochlear transfer functions, allowing the measurement process to proceed more efficiently without sacrificing frequency resolution
Solution Approach 2:
The patent implements a dynamic measurement process where the frequency step size and measurement parameters are adaptively adjusted based on preliminary results and physiological model predictions. The system dynamically optimizes the measurement sequence to achieve high frequency resolution while minimizing measurement time by focusing computational resources on critical frequency regions identified through the physiological model
3Ease of operation
If volume adjustment is performed at a frequency different from the tinnitus frequency, then the test can be conducted, but the identified amplitude does not correspond to the actual amplitude at the tinnitus frequency
Solution Approach 1:
The patent implements feedback through the physiological model that continuously monitors and adjusts for the relationship between test tone frequency and tinnitus frequency. When volume adjustment is performed at a frequency different from the tinnitus frequency, the physiological model computes the expected masking effect and provides feedback to correct the amplitude identification, ensuring accurate tinnitus amplitude measurement despite the operational convenience of adjusting at different frequencies
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 simplifies the identification of tinnitus noise, reduces octave confusion, and provides a fast and reliable characterization of tinnitus frequencies and amplitudes, even for unpracticed listeners, by using a probability correlation derived from masking properties of test signals.
Implementation Method 1
a test signal 18 is generated and compared with a tinnitus noise 4 in terms of a masking effect
Data Source
AI summary
A method operates an apparatus for tinnitus characterization, in which, in a first step, a broadband test signal having a number of signal frequencies is generated and compared with a tinnitus noise. The respective test signal is stored with an associated comparison result. A probability correlation for determining the tinnitus noise is established based on the stored test signals and comparison results. In a second step, the amplitudes of the individual signal frequencies of the test signal are varied. The first and second steps are performed repeatedly until the probability correlation reaches or exceeds a first threshold value. In a third step, the amplitudes of the individual signal frequencies of the test signal are varied with reference to the probability correlation.