Next-Generation Optical Shape Sensing for Autonomous Navigation
Legal Citation
Summary of the Inventive Concept
A real-time optical shape sensing system that integrates machine learning and dynamic FBG reconfiguration to enable autonomous navigation of medical devices through complex passages.
Background and Problem Solved
The original patent's optical shape sensing device has limitations in its ability to navigate complex passages and provide real-time feedback. This new inventive concept addresses these limitations by introducing autonomous navigation capabilities and advanced force sensing.
Detailed Description of the Inventive Concept
The next-generation optical shape sensing system comprises a multicore optical fiber with dynamically reconfigured FBGs, a machine learning module, and a control module. The FBGs are integrated along the entire length of the fiber, enabling real-time shape sensing and force detection. The machine learning module analyzes shape data to predict optimal navigation paths, and the control module adjusts the device's trajectory accordingly. The system provides real-time feedback to the user and can be calibrated using historical shape data.
Novelty and Inventive Step
The new claims introduce a paradigm shift in optical shape sensing by integrating machine learning and dynamic FBG reconfiguration, enabling autonomous navigation and real-time feedback. This is a significant departure from the original patent's limitations, providing a more ambitious and forward-thinking solution.
Alternative Embodiments and Variations
Alternative embodiments include using different types of sensors or machine learning algorithms, or integrating the system with other medical devices. Variations could include adapting the system for use in non-medical applications, such as robotics or industrial inspection.
Potential Commercial Applications and Market
The next-generation optical shape sensing system has significant commercial potential in the medical device industry, particularly in the areas of minimally invasive surgery and diagnostics. The system's autonomous navigation capabilities and real-time feedback could improve patient outcomes and reduce procedure times.
CPC Classifications
| Section | Class | Group |
|---|---|---|
| A | A61 | A61B34/20 |
| G | G01 | G01B11/24 |
| G | G01 | G01L1/246 |
| A | A61 | A61B2034/2061 |
| A | A61 | A61B2090/064 |
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Medical device engineering, optical sensing technologies, specifically focused on shape-sensing systems for minimally invasive medical procedures and robotic navigation
Person of Ordinary Skill (PHOSITA) Profile
A biomedical engineer with expertise in optical fiber technologies, machine learning applications in medical devices, and sensor integration, holding advanced degrees in bioengineering or electrical engineering with 3-5 years of specialized experience in medical sensing systems
Obviousness Rationale
A PHOSITA would recognize that integrating machine learning and dynamic FBG reconfiguration into the existing optical shape sensing framework represents a predictable extension of known techniques in sensor optimization and medical device navigation. The core technological principles of shape sensing and force detection remain consistent with the source patent, with the PTD introducing incremental improvements in data processing and adaptive sensing. The machine learning approach provides a natural progression in sensor intelligence that would be obvious to a skilled practitioner seeking to enhance the performance of optical shape sensing devices.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,268 |
|---|---|
| Title | Optical shape sensing device with integrated force sensing region and tip integration |
| Assignee(s) | Koninklijke Philips N.V. |