Ear Tip Fitment Tool Using Image Analysis and Machine Learning
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Solution Overview
Problem
Existing earbuds often fail to provide an optimal fit for users due to inadequate ergonomic considerations, leading to discomfort and poor sound quality, as they rely heavily on forming a good seal with the ear canal.
Innovation Solution
A computer-implemented tool that captures images of the user's ear, processes them using machine learning algorithms, and provides recommendations for earbud fit improvement by assessing criteria such as stability, comfort, pressure, and acoustics, offering a percent probability value for the fit quality and suggesting adjustments to achieve a better fit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If earbuds are designed with standard ergonomic considerations, then general usability is improved, but optimal fit for individual users cannot be achieved
Solution Approach 1:
The patent applies local quality by capturing and analyzing the specific geometric characteristics of each user's ear canal to determine optimal ear tip fitment. Instead of using a universal ergonomic design, the system customizes the fit assessment based on local anatomical variations of the user's ear, thereby achieving both general usability and individual optimization.
2Adaptability or versatility
If multiple ear tip sizes are provided, then adaptability is improved, but users still cannot determine the optimal fit without trial and error
Solution Approach 1:
The patent applies preliminary action by performing image capture and machine learning-based analysis before the user makes an ear tip selection. The system pre-determines the optimal ear tip size based on the user's ear anatomy, eliminating the need for trial and error. This preliminary assessment guides the user to select the correct ear tip size on first attempt.
Solution Approach 2:
The patent introduces an intermediary tool - a mobile device with image capture and machine learning algorithms - that mediates between the user's ear anatomy and the ear tip selection. This intermediary system analyzes ear canal geometry and provides data-driven recommendations, replacing the traditional trial-and-error approach with an automated assessment process.
3Device complexity
If ear tip fitment is not optimized, then device simplicity is maintained, but sound quality and comfort deteriorate
Solution Approach 1:
The patent replaces the mechanical trial-and-error fitting process with an automated image-based assessment system using machine learning algorithms. Instead of relying on physical trial fitting, the system captures images of the user's ear and uses computational analysis to determine optimal fitment, thereby maintaining device simplicity while improving sound quality and comfort through data-driven recommendations.
Data Source
AI summary
A computer implemented tool and method for assisting users of earphones with selecting an earbud that will provide the best fit for the user. The tool collects image data of the user's ear, along with fit data associated with the user's experience (for example, comfort and/or stability data). The tool further includes a database of ear data and associated objective/subjective data that is utilized to calculate a fit value representative of the quality of fit based on the image data and the fit criteria data generated by the user. The tool will output at least one of an indication of fit level of the earphone in the user's ear based on the fit value, and a recommendation to the user for altering the selected earphone to improve fit of the earphone within the user's ear based on the fit value.