Image-Guided Aesthetic Treatment Personalization by Anatomical Sub-Area
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Solution Overview
Problem
Current energy-based aesthetic treatment devices lack customization and personalization, leading to inconsistent treatment settings, safety risks, and ineffective outcomes due to varying tissue properties and user inexperience, without real-time monitoring or feedback.
Innovation Solution
The device uses image acquisition and analysis modules to identify treatment sub-areas based on anatomical characteristics, adjusting settings dynamically and providing real-time feedback to ensure safe, effective treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-programmed treatment settings are used, then device operation is simplified, but treatment customization and effectiveness are reduced
Solution Approach 1:
The system performs preliminary actions by capturing images and analyzing anatomical characteristics before treatment begins. The processor pre-determines treatment sub-areas and their specific parameters based on the patient's unique anatomy, creating a personalized treatment plan in advance that guides the automated treatment process.
Solution Approach 2:
The patent replaces manual operator judgment and mechanical adjustment with an automated image-based recognition system. The processor automatically identifies anatomical landmarks and determines treatment parameters based on image analysis, substituting the mechanical system of manual setting adjustment with an automated digital system.
2Reliability
If operator vigilance is required to maintain treatment quality, then treatment safety can be monitored, but operator burden and complexity increase
Solution Approach 1:
The system implements feedback by continuously monitoring treatment parameters and comparing them against the pre-determined treatment plan. The processor provides real-time feedback to ensure treatment quality, automatically detecting deviations and alerting the operator only when necessary, thereby maintaining safety while reducing constant vigilance requirements.
Solution Approach 2:
The treatment device performs self-service by automatically monitoring and adjusting treatment parameters based on the pre-programmed treatment plan. The system self-corrects for placement deviations and maintains treatment quality without requiring constant operator intervention, reducing the burden of continuous vigilance.
3Adaptability or versatility
If treatment settings are adjusted continuously during treatment, then customization to different anatomical areas is achieved, but treatment time and complexity increase
Solution Approach 1:
The system divides the treatment area into pre-determined sub-areas with specific treatment parameters established before treatment begins. This preliminary segmentation allows the automated system to efficiently transition between areas without requiring continuous manual adjustment, reducing overall treatment time while maintaining customization.
Solution Approach 2:
The treatment system dynamically adapts to different anatomical areas by automatically adjusting parameters based on the pre-determined treatment plan for each sub-area. The system transitions smoothly between different treatment zones, maintaining optimal settings for each area without requiring manual intervention, thereby reducing treatment time while preserving customization.
4Measurement precision
If visual assessment by operator is used to monitor skin reactions, then immediate tissue response can be evaluated, but human error and constant vigilance are required
Solution Approach 1:
The system implements automated feedback monitoring of skin reactions during treatment. The processor continuously evaluates treatment parameters and tissue response, providing objective feedback that reduces reliance on human visual assessment. This automated monitoring eliminates human error while reducing the need for constant operator vigilance.
Data Source
AI summary
A method of customizing an energy-based aesthetic treatment includes obtaining image data identifying a treatment area and a tissue-contacting part of a treatment device. The method further includes selecting an anatomical classification criterion based on a type of energy modality used for said treatment. The method further includes determining, by analyzing the image data using the anatomical classification criterion, a plurality of treatment sub-areas that are differentiated based on a measurable or observable property of an anatomical characteristic which varies across regions of tissue in the treatment area. The method further includes determining, while said treatment is being performed, a current treatment sub-area of the treatment area that is actively being treated or targeted for treatment, and adjusting one or more treatment settings of the treatment device based on the measurable or observable property of the anatomic characteristic of a region of tissue in the current treatment sub-area.