Endoluminal Robotic Navigation With Electromagnetic Tracking
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Solution Overview
Problem
Challenges in endoluminal robotic systems include equipment placement, navigation, and visualization within small tubular anatomies, which can be time-consuming and risky for patients due to manual navigation and lack of effective tracking and imaging modalities.
Innovation Solution
The system incorporates automated navigation, enhanced visualization through multiple imaging modalities, and real-time tracking of instruments using electromagnetic fields and machine learning algorithms to improve precision and safety during suturing procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual navigation is used to access and visualize the inside of a patient's lumen, then the physician can perform endoscopic procedures, but the procedure becomes time-consuming and risky due to lack of automated navigation and real-time tracking
Solution Approach 1:
The patent replaces manual mechanical navigation with an automated robotic system that uses electromagnetic field tracking and image fusion to navigate instruments through luminal networks. The robotic system automatically follows pre-planned navigation paths based on 3D reconstructed anatomy, eliminating time-consuming manual navigation while improving patient safety through precise, repeatable positioning.
Solution Approach 2:
The system performs self-navigation by automatically following pre-planned paths through the luminal network. The robotic system autonomously positions instruments based on pre-acquired 3D anatomical data and real-time electromagnetic tracking, reducing dependence on operator skill and experience while maintaining procedural efficiency.
2Measurement precision
If multiple imaging modalities and real-time tracking are implemented, then navigation precision and patient safety improve, but system complexity and equipment requirements increase
Solution Approach 1:
The patent merges multiple imaging modalities (CT, MRI, ultrasound) into a unified 3D reconstructed model of the luminal network. The system combines pre-procedural imaging data with real-time electromagnetic tracking and intra-procedural imaging to create an integrated navigation system that provides comprehensive anatomical visualization without requiring separate independent systems.
Solution Approach 2:
The system introduces an electromagnetic field as an intermediary tracking mechanism that works within the confined luminal space. Electromagnetic sensors attached to instruments track position and orientation through the lumen without requiring direct line-of-sight visual tracking, enabling precise navigation through tortuous anatomical paths where traditional optical tracking would fail.
3Manufacturing precision
If automated navigation with image fusion and real-time tracking is used, then needle placement accuracy and suturing precision improve, but the device complexity and computational requirements increase
Solution Approach 1:
The system performs preliminary 3D reconstruction and navigation path planning before the actual suturing procedure. Pre-acquired CT or MRI data is processed into 3D models, and optimal needle trajectories are calculated in advance. This preliminary preparation enables real-time execution with simplified control, as the robotic system only needs to follow pre-determined paths rather than making complex real-time decisions.
Solution Approach 2:
The system implements real-time feedback through electromagnetic field tracking that continuously monitors instrument position and orientation. The tracked position is fed back to the control system, which compares actual position with the planned navigation path and makes automatic corrections to maintain precise needle placement accuracy throughout the suturing procedure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances procedural efficiency, reduces patient risk, and improves precision in suturing by providing real-time tracking and automated navigation, ensuring accurate needle placement and tissue interaction.
Implementation Method 1
an electromagnetic (EM) field generator configured to generate an EM field and at least one EM sensor coupled to a suture needle. The instructions, when executed by the processor, may cause the processor to track the position of the suture needle based on the EM field sensed by the at least one EM sensor.
Data Source
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AI summary
Endoluminal robotic systems and corresponding methods include subsystems for visualization, navigation, pressure sensing, platform compatibility, and user interfaces. The user interfaces may be implemented by one or more of a console, haptics, image fusion, voice controls, remote support, and multi-system controls.