Published Technical Disclosure Archive

Advanced Pressure Injury Prevention System with Personalized Recommendations

Publication ID: 24-11857477_0001_PTD
Published: October 28, 2025
Category:Direct Improvements & Enhancements

Legal Citation

pr1or.art Inc., “Advanced Pressure Injury Prevention System with Personalized Recommendations,” Published Technical Disclosure No. 24-11857477_0001_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857477_0001_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. 11,857,477.

Summary of the Inventive Concept

An enhanced pressure injury prevention system that utilizes machine learning algorithms to provide personalized recommendations for pressure ulcer prevention, reducing the incidence of pressure ulcers and improving patient care.

Background and Problem Solved

The original patent, 'Pressure injury prevention sensor and decision support tool', addresses the pressing issue of pressure ulcer development in patients. However, it has limitations in terms of providing personalized recommendations and accurate risk assessments. The new inventive concept builds upon the original patent by incorporating machine learning algorithms and expert input to provide a more comprehensive and effective pressure ulcer prevention system.

Detailed Description of the Inventive Concept

The advanced pressure injury prevention system consists of a sensor array that measures pressure distribution, skin conductivity, and other relevant parameters. The system utilizes machine learning algorithms to analyze the data and provide personalized recommendations for pressure ulcer prevention, taking into account the patient's medical history, age, and mobility. The system also includes a patient-specific risk assessment module that generates a tailored prevention plan. Additionally, the system can detect early signs of pressure ulcer development and adjust the patient's position in response to changes in the pressure distribution.

Novelty and Inventive Step

The new inventive concept introduces the use of machine learning algorithms and expert input to provide personalized recommendations for pressure ulcer prevention, which is a novel and non-obvious improvement over the original patent. The incorporation of patient-specific risk assessment and early detection of pressure ulcer development also represent significant advancements.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, such as deep learning or natural language processing, to analyze patient data. Additionally, the system could be integrated with existing electronic health records (EHRs) or hospital information systems to improve data exchange and workflow efficiency.

Potential Commercial Applications and Market

The advanced pressure injury prevention system has significant commercial potential in the healthcare industry, particularly in hospitals and long-term care facilities. The system could be marketed as a standalone solution or integrated into existing patient care systems, providing a competitive advantage for healthcare providers and improving patient outcomes.

CPC Classifications

SectionClassGroup
A A61 A61G7/05769
A A61 A61B5/1116
A A61 A61B5/447
A A61 A61B5/6892
A A61 A61B2562/0247
A A61 A61B2562/046
A A61 A61G2203/44

Field of Art

Medical device technology focused on patient monitoring, pressure injury prevention, and biosensing systems, requiring expertise in biomedical engineering, sensor design, data analysis, and machine learning applications in healthcare

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device researcher with advanced degrees, proficient in sensor technologies, signal processing, machine learning algorithms, and healthcare informatics, with knowledge of patient monitoring systems and risk assessment methodologies

Obviousness Rationale

A PHOSITA would recognize that incorporating machine learning algorithms and personalized risk assessment into an existing pressure injury prevention system represents a predictable technological evolution. The source patent's foundational sensor and monitoring approach provides a clear technical framework that naturally suggests advanced data analysis and personalization techniques. The proposed variations represent incremental improvements using standard machine learning and data processing techniques well-known in medical device engineering.

Obvious Combinations & Variations

Source Patent Element
Measurement device with pressure sensors configured to measure patient weight and pressure distribution
PTD Variation
Adding machine learning algorithms to analyze sensor data and generate personalized recommendations
Obviousness Reasoning
Applying machine learning to sensor data is a known technique for extracting advanced insights, representing an obvious enhancement to existing monitoring systems
Source Patent Element
Notification system for detecting patient condition changes
PTD Variation
Implementing patient-specific risk assessment module incorporating medical history, age, and mobility factors
Obviousness Reasoning
Tailoring risk assessment using patient-specific parameters is a predictable design choice that extends the existing notification framework
Source Patent Element
Sensor-based pressure measurement system
PTD Variation
Integrating skin conductivity measurements and early pressure ulcer detection algorithms
Obviousness Reasoning
Expanding sensor capabilities to detect additional physiological indicators represents a routine engineering optimization with expected technological benefits
Source Patent Element
Basic pressure monitoring system with alarm capabilities
PTD Variation
Implementing automated patient positioning adjustments based on pressure distribution analysis
Obviousness Reasoning
Developing closed-loop feedback mechanisms for patient positioning is an obvious technological progression using standard control system design principles
Source Patent Element
Pressure measurement techniques using frequency analysis
PTD Variation
Incorporating expert input and multiple machine learning algorithms for comprehensive risk profiling
Obviousness Reasoning
Combining multiple analytical approaches is a standard method for improving diagnostic accuracy and represents an expected technological enhancement
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857477, the disclosed pressure injury prevention system variations would be considered obvious to a person having ordinary skill in the art. The proposed technical modifications represent predictable extensions of existing pressure monitoring technologies, utilizing standard machine learning techniques and sensor integration methods that would be readily apparent to a skilled practitioner in medical device engineering.

Original Patent Information

Patent NumberUS 11,857,477
TitlePressure injury prevention sensor and decision support tool
Assignee(s)CERNER INNOVATION, INC.