EM Sensor Target Movement Modelling for Respiratory Displacement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
During medical procedures, precise localization of medical devices within the patient's body is challenging due to respiratory and cardiac movements, leading to inaccuracies in targeting and navigation.
Innovation Solution
The method involves using electromagnetic (EM) sensors to model target tissue movement based on catheter and patient chest movement data, allowing for real-time correction of local patient body coordinates and updating of target positions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If electromagnetic navigation is used to guide medical devices to targets, then navigation capability is improved, but positioning accuracy deteriorates due to respiratory and cardiac movements causing target displacement
Solution Approach 1:
The system dynamically updates target position predictions based on real-time breathing phase detection. Instead of using static pre-procedure target coordinates, the system continuously adjusts target positions to account for respiratory and cardiac movements, maintaining positioning accuracy throughout the procedure.
Solution Approach 2:
The system implements feedback by detecting the patient's breathing phase in real-time and using this information to adjust target position predictions. The breathing phase detection provides continuous feedback that allows the system to compensate for tissue movement and maintain accurate positioning.
2Ease of operation
If 3D models are used to visualize target locations, then navigation guidance is improved, but localization accuracy deteriorates due to apparent target movement caused by patient breathing and heartbeat
Solution Approach 1:
The 3D model is dynamically updated to reflect real-time target position predictions based on breathing phase. The system continuously adjusts the displayed target location in the 3D model to match the predicted actual position, preventing the target from appearing to move due to respiratory and cardiac cycles.
Solution Approach 2:
The system performs preliminary prediction of target positions at different breathing phases before the actual navigation step. By pre-calculating where the target will be at the current breathing phase, the system can display the correct position in advance, eliminating localization errors.
3Measurement precision
If target positions are updated in real-time based on breathing phase, then positioning accuracy is improved, but system complexity increases due to additional sensing and modeling requirements
Solution Approach 1:
The system uses breathing phase as an intermediary parameter to link patient physiology with target position prediction. Instead of directly tracking complex tissue movements, the system uses the easily measurable breathing phase as a mediator to infer and compensate for target displacement, simplifying the overall system while maintaining accuracy.
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
This approach enhances the accuracy of medical device localization by compensating for respiratory and cardiac movements, thereby improving the precision and safety of medical procedures.
Implementation Method 1
determining movement of a catheter disposed in a lung during at least one breathing cycle of a patient... determining movement of at least one PST (patient sensor triplet)... receiving a live PST signal from the at least one PST
Data Source
AI summary
Systems and methods for target movement modelling use sequences of position data from a first electromagnetic (EM) sensor disposed at a distal portion of a catheter disposed in a lung and from at least one second EM sensor disposed at the patient's chest in order to update target tissue position. The methods involve generating a breathing model of the lungs as a function of breathing phases based on the position data from the first and second EM sensors. The methods also involve receiving current position data from the at least one second EM sensor and estimating a current breathing phase based on the breathing model and the current position data. The methods also involve predicting displacement of the target based on the breathing model and the current breathing phase, and updating body coordinates near the target based on the displacement of the target.