Intelligent Catheter Systems for Real-time Occlusion Prevention and Optimization

Publication ID: 24-11857734_0005_PTD
Published: October 28, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Intelligent Catheter Systems for Real-time Occlusion Prevention and Optimization,” Published Technical Disclosure No. 24-11857734_0005_PTD, Published October 28, 2025, available at https://archive.pr1or.art/24-11857734_0005_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. 11,857,734.

Summary of the Inventive Concept

A next-generation catheter system that leverages AI, machine learning, and real-time sensor data to predict and prevent occlusion, ensuring optimal patient outcomes and reducing healthcare costs.

Background and Problem Solved

The original patent addressed the need for a catheter system clamp to prevent occlusion, but it relied on manual intervention and did not utilize advanced technologies to predict and prevent occlusion. This new inventive concept addresses the limitations of the original patent by integrating AI, machine learning, and real-time sensor data to create a proactive, intelligent catheter system that can predict and prevent occlusion, reducing the risk of complications and improving patient care.

Detailed Description of the Inventive Concept

The new inventive concept comprises a catheter system with integrated AI-powered sensors that detect changes in blood flow and pressure, and automatically adjust catheter flushing protocols to prevent occlusion and ensure optimal patient outcomes. The system utilizes machine learning algorithms trained on a dataset of catheter usage patterns to generate a predictive model for detecting occlusion risk based on real-time sensor data. Additionally, the system features a modular design with interchangeable, AI-enabled components that can be easily swapped or upgraded as needed, allowing for customization and optimization of catheter performance.

Novelty and Inventive Step

The new claims introduce a paradigm shift in catheter technology by leveraging AI, machine learning, and real-time sensor data to predict and prevent occlusion. The integration of these advanced technologies with the catheter system's components and operation is new and non-obvious compared to the original patent, which relied on manual intervention and did not utilize predictive analytics.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different AI algorithms, sensor types, or communication protocols. Variations could also include the integration of the catheter system with other medical devices, such as ECG monitors or infusion pumps, to create a more comprehensive patient care platform.

Potential Commercial Applications and Market

The intelligent catheter system has significant commercial potential in the healthcare industry, particularly in hospitals, clinics, and home healthcare settings. The system's ability to predict and prevent occlusion can reduce healthcare costs associated with complications, improve patient outcomes, and enhance the overall quality of care. The market for this technology is substantial, with an estimated global value of over $10 billion by 2025.

CPC Classifications

SectionClassGroup
A A61 A61M25/00
A A61 A61M5/14
A A61 A61M39/28
G G16 G16H10/60
A A61 A61M2005/1403
A A61 A61M2025/0019
A A61 A61M2205/18
A A61 A61M2205/3327
A A61 A61M2205/3334
A A61 A61M2205/3584
A A61 A61M2205/581
A A61 A61M2205/582
A A61 A61M2205/583
A A61 A61M2205/587

Field of Art

Medical Device Technology, specifically Catheter Systems and Infusion Management, with expertise in sensor integration, medical monitoring systems, and computational healthcare technologies

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device designer with advanced knowledge of sensor technologies, computational systems, machine learning applications in medical contexts, and catheter performance optimization techniques

Obviousness Rationale

A PHOSITA would recognize that the source patent's foundational catheter monitoring system naturally extends to more sophisticated predictive and adaptive technologies. The integration of machine learning and real-time sensor analytics represents a logical progression of the existing clamp monitoring and alert system disclosed in the original patent. The technical challenges of catheter occlusion prevention are well-understood, making AI-driven solutions a predictable evolutionary step for those skilled in medical device design.

Obvious Combinations & Variations

Source Patent Element
Clamp with onboard computing system and sensor for detecting clamp state
PTD Variation
AI-powered sensor system that dynamically adjusts catheter flushing protocols based on real-time flow and pressure data
Obviousness Reasoning
Extending sensor-based monitoring to predictive analytics is a known technique in medical device design, representing an incremental improvement using standard machine learning approaches
Source Patent Element
Alert generation for catheter management
PTD Variation
Cloud-based analytics platform providing personalized clinician alerts with occlusion risk predictions
Obviousness Reasoning
Transforming manual alert systems into networked, intelligent notification platforms is a predictable technological evolution using standard communication and data processing techniques
Source Patent Element
Electronic health record integration for catheter state tracking
PTD Variation
Modular catheter system with interchangeable AI-enabled components for performance optimization
Obviousness Reasoning
Modular design and component-level intelligence represent a natural design progression for medical devices, utilizing known system architecture principles
Source Patent Element
Fluid tube management and occlusion prevention method
PTD Variation
Machine learning algorithm trained on catheter usage patterns to generate predictive occlusion risk models
Obviousness Reasoning
Applying statistical learning techniques to medical device performance monitoring is a standard approach for improving diagnostic and preventative capabilities
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857734 and the disclosed technical variations, a person of ordinary skill in the art would find the claimed AI-enhanced catheter monitoring and management systems obvious and non-patentable. The incremental technological advancements represent predictable applications of known machine learning and sensor integration techniques to existing catheter monitoring methodologies.

Original Patent Information

Patent NumberUS 11,857,734
TitleCatheter system clamp, systems, and methods
Assignee(s)Becton, Dickinson and Company