Enhanced Skin Analysis System with Advanced Sensors and Machine Learning

Publication ID: 24-11857338_0006_PTD
Published: October 28, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Enhanced Skin Analysis System with Advanced Sensors and Machine Learning,” Published Technical Disclosure No. 24-11857338_0006_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857338_0006_PTD
This technical disclosure describes improvements that would be readily apparent to a Person Having Ordinary Skill In The Art (PHOSITA) when considered in combination with the foundational architecture disclosed in U.S. Patent No. 11,857,338.

Summary of the Inventive Concept

An improved skin analysis system that integrates advanced sensors, machine learning algorithms, and wearable technology to provide more accurate and personalized skin care recommendations, detecting skin conditions earlier and enhancing overall skin health.

Background and Problem Solved

The original patent's skin analysis system had limitations in terms of accuracy, environmental adaptability, and personalized recommendations. The new inventive concept addresses these limitations by incorporating advanced sensors, machine learning algorithms, and wearable technology to provide a more comprehensive and accurate skin analysis, enabling earlier detection of skin conditions and more effective personalized skin care routines.

Detailed Description of the Inventive Concept

The enhanced skin analysis system comprises a contact sensor with a wireless communication module, adapted to provide real-time hydration level measurements with an accuracy of at least 95% using machine learning algorithms to correct for environmental factors. The system also includes an environment sensor integrated with a GPS module, providing location-based environmental data to enhance the accuracy of skin analysis. A wearable device with a built-in contact sensor tracks skin health over time, providing personalized recommendations for skin care routines. The system utilizes machine learning algorithms to identify patterns in skin data, enabling an early warning system for skin conditions such as acne, eczema, or rosacea. A method for personalizing skin care products uses the analysis system to provide customized product recommendations based on the individual's skin type, environmental conditions, and personal preferences.

Novelty and Inventive Step

The new claims introduce the use of machine learning algorithms, wearable technology, and GPS-integrated environment sensors, which are not present in the original patent. These advancements provide a significant improvement in accuracy, adaptability, and personalized recommendations, making the new inventive concept novel and non-obvious compared to the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different types of sensors, such as optical or electrical impedance sensors, or the integration of additional data sources, such as genomic or nutritional information, to further enhance the accuracy and personalization of skin analysis. Variations could also include the development of specialized skin analysis systems for specific skin conditions or demographics.

Potential Commercial Applications and Market

The enhanced skin analysis system has significant commercial potential in the beauty, cosmetology, and dermatology industries, as well as in the personal care and luxury goods markets. The system's ability to provide accurate and personalized skin care recommendations, detect skin conditions earlier, and enhance overall skin health could lead to increased sales and market share for companies adopting this technology. Additionally, the system's potential for early detection and prevention of skin conditions could lead to cost savings for healthcare providers and insurance companies.

Field of Art

Biomedical engineering and dermatological diagnostic technologies, specifically focused on non-invasive skin analysis systems with sensor technologies and data processing methods

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or technical professional with expertise in sensor design, signal processing, machine learning, and medical diagnostic technologies, holding at least a master's degree with 3-5 years of experience in wearable health monitoring systems

Obviousness Rationale

A person of ordinary skill would recognize that integrating machine learning algorithms and GPS-enabled environmental sensors into an existing skin analysis system represents a predictable technological enhancement. The source patent's foundational sensor architecture provides a clear framework for incorporating advanced data processing and contextual environmental tracking. These modifications represent standard engineering approaches to improving diagnostic accuracy and personalization in medical sensing technologies.

Obvious Combinations & Variations

Source Patent Element
Contact sensor configured to measure skin surface dielectric properties and hydration levels
PTD Variation
Adding machine learning algorithms to correct sensor measurements and improve accuracy to 95%
Obviousness Reasoning
Applying machine learning to sensor calibration is a known technique in signal processing, representing a predictable improvement in measurement precision
Source Patent Element
Wireless communication module in contact sensor
PTD Variation
Integrating GPS and location-based environmental data collection
Obviousness Reasoning
Expanding wireless sensor capabilities to include geospatial context is an obvious design choice for enhancing environmental parameter tracking
Source Patent Element
System for analyzing physico-chemical skin properties
PTD Variation
Implementing a wearable device for continuous skin health monitoring
Obviousness Reasoning
Transitioning from point-in-time to continuous monitoring represents a standard technological progression in diagnostic sensing
Source Patent Element
Measurement of skin surface parameters
PTD Variation
Using machine learning to detect early-stage skin conditions
Obviousness Reasoning
Applying pattern recognition algorithms to medical sensor data is a well-established approach for developing predictive diagnostic capabilities
Source Patent Element
Skin surface analysis system
PTD Variation
Generating personalized product recommendations based on individual skin data
Obviousness Reasoning
Developing recommendation systems from collected physiological data is a standard application of data analytics in personalized healthcare technologies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857338, the variations disclosed herein would be considered obvious to a person having ordinary skill in the art of biomedical sensing technologies. The incremental improvements in sensor data processing, environmental context integration, and machine learning-driven personalization represent predictable technological extensions that do not rise to the level of non-obvious innovation, thus rendering potential derivative claims anticipated and obvious under 35 U.S.C. ยง 103.

Original Patent Information

Patent NumberUS 11,857,338
TitleSystem for analysing the physico-chemical properties of a skin surface
Assignee(s)IEVA