Next-Generation Pressure Injury Prevention and Personalized Care Platform

Publication ID: 24-11857477_0010_PTD

Published: October 28, 2025

Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Pressure Injury Prevention and Personalized Care Platform,” Published Technical Disclosure No. 24-11857477_0010_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857477_0010_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

A comprehensive, AI-driven platform for predicting and preventing pressure injuries in patients, featuring wearable sensors, machine learning algorithms, and personalized preventative care plans.

Background and Problem Solved

The original pressure injury prevention sensor and decision support tool, while effective, has limitations in detecting early signs of pressure injury and providing timely interventions. The new inventive concept addresses these limitations by introducing a wearable sensor array, machine learning-based risk assessment, and personalized care plan generation, enabling proactive and targeted prevention of pressure injuries.

Detailed Description of the Inventive Concept

The next-generation platform comprises a wearable sensor array that detects changes in skin impedance and temperature, providing real-time data for machine learning-based risk assessment. The algorithm analyzes the data and identifies high-risk patients, triggering the generation of personalized preventative care plans. The platform also features a cloud-based database, mobile application, and AI-powered decision support tool for healthcare providers. Additionally, the system can be adapted for remote or underserved populations using low-cost, portable sensor devices and satellite-based communication systems.

Novelty and Inventive Step

The new claims introduce a paradigm shift in pressure injury prevention by leveraging wearable sensors, machine learning, and AI-powered decision support tools. The inventive concept's novelty lies in its ability to provide real-time, personalized risk assessment and prevention plans, making it a significant improvement over the original patent.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include integrating the wearable sensor array with existing hospital systems, developing specialized sensors for specific patient populations, or incorporating natural language processing for personalized risk profiling. Variations of the platform could target different healthcare settings, such as clinics or nursing homes.

Potential Commercial Applications and Market

The next-generation pressure injury prevention platform has significant commercial potential in the healthcare industry, particularly in hospitals, clinics, and nursing homes. The platform's ability to reduce pressure injury incidence and improve patient outcomes could lead to cost savings, improved quality of care, and enhanced patient satisfaction. The target market includes healthcare providers, hospital systems, and medical device manufacturers.

CPC Classifications

Section	Class	Group
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

Section 103 Obviousness Analysis (PHOSITA)

▼

Field of Art

Medical device technology, specifically patient monitoring systems for pressure injury prevention, involving biomedical sensors, machine learning algorithms, and healthcare informatics

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical technology specialist with expertise in sensor design, data analytics, machine learning, and healthcare monitoring systems, holding advanced degrees and practical experience in developing medical diagnostic technologies

Obviousness Rationale

A person having ordinary skill in the art would recognize that the published technical disclosure represents a predictable extension of the source patent's core pressure injury detection methodology by incorporating contemporary machine learning techniques, sensor miniaturization, and personalized healthcare technologies. The fundamental concept of pressure injury prevention remains consistent, with the PTD merely applying standard technological advancements to enhance the original patent's monitoring capabilities. The variations represent incremental improvements using well-established techniques in medical sensor design and predictive analytics.

Obvious Combinations & Variations

Source Patent Element

Pressure measurement sensors configured to detect patient positioning and weight distribution

PTD Variation

Expanded sensor array detecting skin impedance and temperature in addition to pressure measurements

Obviousness Reasoning

Adding complementary physiological sensors represents a predictable enhancement using known biomedical monitoring techniques, providing more comprehensive patient risk assessment

Source Patent Element

Processor-based system for generating patient condition notifications

PTD Variation

Machine learning algorithm for dynamic risk scoring and personalized intervention recommendations

Obviousness Reasoning

Implementing predictive analytics on existing sensor data is a standard approach in medical monitoring technologies, representing an obvious optimization of the original patent's notification system

Source Patent Element

Patient-side alarm and user interface for condition monitoring

PTD Variation

Cloud-based database, mobile application, and telemedicine platform for remote patient monitoring

Obviousness Reasoning

Extending local monitoring to cloud-based systems is a routine technological progression using standard telecommunications and data management infrastructure

Source Patent Element

Frequency-based pressure measurement techniques

PTD Variation

Deep learning models trained on comprehensive patient outcome datasets for risk assessment

Obviousness Reasoning

Applying advanced machine learning to existing sensor data represents a straightforward technological evolution using established data science methodologies

Source Patent Element

System for detecting patient positioning and pressure distribution

PTD Variation

Low-cost portable sensors with satellite communication for remote/underserved populations

Obviousness Reasoning

Adapting medical monitoring technologies for different deployment contexts is a predictable design choice using known telecommunications and sensor miniaturization techniques

35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857477 and the published technical disclosure, a person having ordinary skill in the art would find the claimed variations obvious, as they represent predictable technological extensions employing standard medical monitoring and data analytics techniques. The disclosed innovations constitute prima facie obvious combinations of prior art elements, lacking any inventive leap beyond the existing technological landscape.

Original Patent Information

Patent Number	US 11,857,477
Title	Pressure injury prevention sensor and decision support tool
Assignee(s)	CERNER INNOVATION, INC.