Weighted Hearing Level Metric for Noise-Induced Hearing Loss Detection
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Solution Overview
Problem
Current methods for detecting and preventing noise-induced hearing loss (NIHL) are inadequate due to subjective audiometric interpretations, lack of standardized criteria, and insufficient analytical tools for aggregate data analysis, leading to inconsistent detection and ineffective hearing conservation programs.
Innovation Solution
A method to transform individual audiometric data into a single numerical metric (Weighted Hearing Level, W) and derived metrics (Weighted Threshold Shift, Weighted Correlation Coefficient, and Weighted Left-Right Laterality) to objectively detect and predict early NIHL, enabling post-hoc statistical analysis and predictive capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional audiometric interpretation methods are used, then hearing loss detection is performed, but detection precision and consistency are insufficient due to subjective interpretation
Solution Approach 1:
The patent replaces the manual, subjective mechanical interpretation process with an automated computer-based system that applies standardized algorithms and statistical analysis. The system automatically processes audiometric data, calculates threshold shifts, identifies notches, and generates objective results, eliminating human subjectivity and improving both precision and consistency in hearing loss detection.
Solution Approach 2:
The patent transforms raw audiometric threshold data into derived parameters such as threshold shifts, notch depths, and frequency-specific loss measurements. By changing the form of data representation and applying statistical transformations, the system enhances the precision of hearing loss quantification and enables more reliable detection of early-stage noise-induced hearing loss patterns.
2Loss of information
If comprehensive audiometric data is collected, then more information is available, but data analysis complexity increases without standardized criteria
Solution Approach 1:
The patent segments the comprehensive audiometric data into distinct analytical components: baseline thresholds, threshold shifts by frequency, notch detection at specific frequencies (3kHz, 4kHz, 6kHz), and aggregate metrics. This segmentation allows the system to process and analyze different aspects of hearing loss separately using standardized criteria, reducing overall analysis complexity while preserving all relevant information.
Solution Approach 2:
The patent introduces standardized interpretation criteria and algorithms as intermediaries between raw audiometric data and clinical conclusions. These intermediaries include predefined thresholds for significant changes, standardized notch detection algorithms, and established frequency weighting schemes, which simplify the analysis of comprehensive data by providing consistent rules for interpretation.
3Reliability
If early noise-induced hearing loss is detected, then prevention opportunities increase, but detection sensitivity must be enhanced beyond traditional methods
Solution Approach 1:
The patent applies frequency-specific analysis with enhanced precision at critical frequencies where noise-induced hearing loss first manifests (3kHz, 4kHz, 6kHz). By focusing measurement precision locally at these diagnostically important frequencies rather than uniformly across all frequencies, the system enhances early NIHL detection sensitivity while maintaining efficient data processing.
Data Source
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AI summary
Methods for detecting hearing loss in an individual are disclosed. The methods utilize raw audiometric test data and transform the data into a single numerical metric that summarizes the magnitude of hearing loss specifically toward early noise-induced hearing loss. Also disclosed are systems incorporating the methods of the instant disclosure.