Automated Allergy Office System Using AR and Machine Learning
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Solution Overview
Problem
Current allergy testing systems are burdensome, complex, and prone to errors, leading to false positives and negatives, and they do not effectively minimize patient discomfort or reduce costs.
Innovation Solution
The automated allergy office system combines augmented reality, a multiple allergen testing system, and machine learning to guide medical professionals through the testing process, minimize errors, and improve patient experience, while allowing for remote initiation and updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional allergy testing systems are used, then the testing process can be performed, but the system becomes burdensome and complex with increased errors
Solution Approach 1:
The patent replaces manual mechanical testing procedures with an automated imaging system that uses optical fields to detect and measure skin reactions. The system captures images of wheals and flares and uses image processing algorithms to automatically measure their dimensions, eliminating the need for manual measurement tools and procedures while improving consistency and reducing human error.
Solution Approach 2:
The patent creates a digital copy of the skin test area through imaging, allowing the reaction to be measured and analyzed from the image rather than requiring direct physical measurement. This digital replica enables automated analysis, reduces handling of the actual test site, and allows for precise measurement of wheal and flare dimensions without disturbing the test area.
2Reliability
If manual measurement methods are used, then the testing process is simple, but false positives and negatives increase
Solution Approach 1:
The patent replaces manual visual estimation and physical measurement with automated image processing and digital measurement algorithms. The system automatically identifies wheal and flare boundaries in captured images and calculates their dimensions using computational methods, eliminating subjective human judgment while maintaining operational simplicity through automated processing.
Solution Approach 2:
The system provides automated feedback by comparing measured wheal and flare dimensions against established criteria to automatically determine positive or negative test results. This feedback mechanism reduces human error in interpretation while maintaining ease of operation, as the system guides the user through the process and provides objective result determination.
3Productivity
If multiple allergens are tested simultaneously, then testing efficiency increases, but patient discomfort and errors increase
Solution Approach 1:
The patent segments the testing process by applying allergens to discrete, separated test sites on the patient's skin rather than mixing multiple allergens in one location. Each allergen is applied to a distinct area, allowing the imaging system to capture and analyze each reaction separately. This segmentation reduces patient discomfort by distributing the test burden across multiple small, localized sites rather than one large affected area.
Solution Approach 2:
The system uses minimal amounts of each allergen applied to small, localized test sites, rather than using large quantities or extensive test areas. The automated imaging capability allows for precise measurement of small reactions, enabling efficient multi-allergen testing while minimizing patient discomfort through reduced allergen exposure and smaller test site sizes.
Data Source
AI summary
The augmented-reality automated allergy office method comprises initially delivering a trace amount of a first allergen to a first test site via a multiple test applicator as the multiple test applicator delivers a trace amount of a second allergen to a second test site during allergen deposition. The multiple test applicator is cooperatively engageable with a fluid tray during allergen loading and with the patient's skin during allergen deposition. Then, capturing a first image of the first and second test site using a smart phone or tablet computer. Subsequently, capturing a second image of the first and second test site within 15 to 20 minutes after allergen deposition. And finally, developing a computer-generated treatment plan using machine learning for the patient with an allergy condition that is a step-by-step procedure, the computer-generated treatment plan being stored in a medical database for treating patients with the allergy condition.