Published Technical Disclosure Archive

Next-Generation Neuromodulation System for Personalized Treatment Planning and Real-Time Optimization

Publication ID: 24-11857249_0010_PTD
Published: November 07, 2025
Category:Future Evolutions & Paradigm Shifts

Legal Citation

pr1or.art Inc., “Next-Generation Neuromodulation System for Personalized Treatment Planning and Real-Time Optimization,” Published Technical Disclosure No. 24-11857249_0010_PTD, Published November 07, 2025, available at https://archive.pr1or.art/24-11857249_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. 11,857,249.

Summary of the Inventive Concept

A novel neuromodulation system that leverages machine learning, real-time impedance analysis, and patient-specific data to predict optimal energy delivery parameters and enable personalized treatment planning and real-time optimization.

Background and Problem Solved

The original patent addressed the need for monitoring and controlling deployment of a neuromodulation element within a body lumen. However, it had limitations in terms of predicting optimal energy delivery parameters and adjusting to changes in vessel geometry. The new inventive concept addresses these limitations by incorporating machine learning and real-time impedance analysis to enable personalized treatment planning and real-time optimization.

Detailed Description of the Inventive Concept

The new inventive concept consists of a neural interface device configured to monitor and control deployment of a neuromodulation element within a body lumen. The system further comprises a machine learning module to predict optimal energy delivery parameters based on real-time impedance analysis and patient-specific data. The system can analyze impedance data from a treatment site to identify optimal electrode placement and energy delivery parameters, and generate a personalized treatment plan based on the analysis. The system can also adjust energy delivery in real-time based on changes in impedance at the treatment site.

Novelty and Inventive Step

The new inventive concept is novel and non-obvious in its use of machine learning and real-time impedance analysis to predict optimal energy delivery parameters and enable personalized treatment planning and real-time optimization. The original patent did not contemplate the use of machine learning or real-time impedance analysis, and the new claims provide a significant advancement in the field of neuromodulation.

Alternative Embodiments and Variations

Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, different types of sensors to detect changes in vessel geometry, or different cloud-based data analytics platforms to enable real-time monitoring and optimization of treatment outcomes.

Potential Commercial Applications and Market

The new inventive concept has significant commercial potential in the field of neuromodulation, particularly in the treatment of chronic pain, hypertension, and other conditions. The system's ability to enable personalized treatment planning and real-time optimization could lead to improved treatment outcomes and increased adoption in the medical industry.

CPC Classifications

SectionClassGroup
A A61 A61B18/1492
A A61 A61N1/36057
A A61 A61N1/36139
A A61 A61B2018/00267
A A61 A61B2018/00404
A A61 A61B2018/00434
A A61 A61B2018/00511
A A61 A61B2018/00577
A A61 A61B2018/00875
A A61 A61B2018/00898
A A61 A61B2018/144
A A61 A61B2018/1475
A A61 A61N1/0551

Field of Art

Biomedical engineering focusing on neuromodulation technologies, neural interface devices, and minimally invasive medical interventions, with expertise in catheter-based deployment systems, sensor technologies, and real-time physiological monitoring

Person of Ordinary Skill (PHOSITA) Profile

A biomedical engineer or medical device researcher with advanced degrees in bioengineering, electrical engineering, or medical device design, possessing knowledge of neural interface technologies, signal processing, machine learning applications in medical contexts, and experience with catheter-based interventional techniques

Obviousness Rationale

A PHOSITA would recognize that the proposed machine learning and real-time impedance analysis techniques represent a predictable extension of the source patent's core methodology of monitoring neuromodulation element deployment and energy delivery. The fundamental principles of adaptive energy modulation and deployment tracking disclosed in the original patent naturally suggest the incorporation of advanced data analysis techniques to optimize treatment parameters. The proposed variations represent an incremental technological improvement using standard engineering approaches to enhance the precision and personalization of neuromodulation interventions.

Obvious Combinations & Variations

Source Patent Element
Method for detecting stable contact of neuromodulation element with vessel wall and measuring longitudinal shift
PTD Variation
Incorporating machine learning algorithms to predict optimal energy delivery based on longitudinal shift and impedance data
Obviousness Reasoning
A PHOSITA would recognize that applying machine learning to existing deployment tracking methods represents a known technique for improving precision, with predictable results of enhanced treatment optimization
Source Patent Element
Correlating longitudinal shift values to vessel inner diameter
PTD Variation
Implementing real-time impedance analysis to dynamically adjust energy delivery parameters
Obviousness Reasoning
Extending correlation techniques to include impedance-based parameter adjustment is a straightforward application of known signal processing and adaptive control methodologies
Source Patent Element
Energy delivery method linked to physical configuration changes of catheter
PTD Variation
Cloud-based data analytics platform for monitoring and optimizing treatment outcomes across patient populations
Obviousness Reasoning
Aggregating and analyzing treatment data through cloud platforms represents a standard engineering approach to improving medical device performance, utilizing well-established data management techniques
Source Patent Element
Detecting stable contact and measuring physical configuration changes of neuromodulation element
PTD Variation
Micro-sensor array for detecting vessel geometry changes and dynamically adjusting energy delivery
Obviousness Reasoning
Enhancing sensor capabilities to provide more granular physiological monitoring is a predictable evolution of existing deployment tracking technologies
35 U.S.C. § 103 Summary: Based on the teachings of US Patent 11857249 and the disclosed technical variations, a person having ordinary skill in the art would find the proposed neuromodulation system variations obvious and lacking inventive step. The incremental technological improvements, including machine learning-based parameter optimization, real-time impedance analysis, and adaptive energy delivery, represent predictable extensions of existing neuromodulation deployment methodologies that would be readily conceived by a skilled practitioner in the field.

Original Patent Information

Patent NumberUS 11,857,249
TitleDevices, systems, and methods for monitoring and/or controlling deployment of a neuromodulation element within a body lumen and related technology
Assignee(s)Medtronic Ireland Manufacturing Unlimited Company