Cross-Phaseogram Analysis for Complex Auditory Brainstem Response Diagnosis
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Solution Overview
Problem
Current technologies for analyzing auditory brainstem responses are limited in their ability to accurately diagnose learning disabilities due to subjective and time-consuming methods, particularly when dealing with complex sounds, which are not optimally addressed by existing commercial systems.
Innovation Solution
The development of a system and method using cross-phaseogram analysis to objectively quantify brainstem timing and phase information from complex auditory brainstem responses (cABRs), enabling more precise and automated diagnosis of central auditory processing disorders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ABR testing is used, then physiological indication is provided, but no connection has been established between results and learning disabilities
Solution Approach 1:
The patent transforms conventional ABR testing by changing the stimulus parameters from simple clicks to complex auditory stimuli (speech sounds, music, environmental sounds). This parameter change enables the system to capture brainstem responses that are specifically relevant to learning disabilities, establishing a meaningful connection between the test results and diagnostic criteria while maintaining physiological measurement reliability
Solution Approach 2:
The patent introduces cross-phaseogram analysis as an intermediary processing method that bridges the gap between raw ABR data and learning disability diagnosis. This intermediary analysis technique extracts phase information from the brainstem responses to complex stimuli, creating a measurable connection that links physiological data to diagnostic outcomes
2Reliability
If subjective perceptual tests are used for CAP evaluation, then diagnostic information is obtained, but the process is time-consuming and lacks objectivity
Solution Approach 1:
The patent replaces the manual, subjective evaluation process with an automated computer-based system. The system automatically presents complex auditory stimuli, records brainstem responses, performs cross-phaseogram analysis, and provides diagnostic feedback without requiring manual interpretation of perceptual tests, thereby eliminating time-consuming subjective evaluation while maintaining diagnostic reliability
Solution Approach 2:
The system performs self-service through automated analysis of the recorded brainstem responses. The cross-phaseogram analysis automatically extracts phase information, compares it against diagnostic criteria, and generates diagnostic conclusions without requiring clinician intervention in the measurement and analysis process, significantly reducing evaluation time
3Loss of information
If complex auditory stimuli are used, then more information about brainstem processing is obtained, but existing commercial systems are not optimally designed for this
Solution Approach 1:
The patent segments the complex analysis process into distinct functional modules: stimulus presentation, response recording, cross-phaseogram analysis, and diagnostic evaluation. This segmentation allows each component to be optimized independently while working together to handle complex auditory stimuli, making the overall system more manageable and effective for capturing detailed brainstem processing information
Data Source
AI summary
Certain examples provide a method of collecting and analyzing complex auditory brainstem response. The example method includes presenting at least one complex auditory stimulus to a subject and acquiring the subject's complex auditory brainstem response. The example method includes averaging complex auditory brainstem responses from the subject in at least one of a time domain and a frequency domain to form a collected response. The example method includes analyzing the collected response using a signal processor to process the collected response to provide a processed output and to adapt the response for comparison to the at least one complex auditory stimulus. The example method includes performing statistical computations on the processed output to generate visual and data feedback for a user.