EM Sensor Distortion Detection for Surgical Navigation
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Solution Overview
Problem
Electromagnetic (EM) distortion in medical robotic systems can lead to errors in localization and navigation, as existing technologies fail to reliably detect and mitigate such distortions, which are caused by various sources within the operating environment, affecting the accuracy of EM data used for positioning and tracking of surgical instruments.
Innovation Solution
A system comprising EM sensors, a processor, and memory that calculates baseline and updated metrics of EM sensor signals to detect EM distortion by determining differences greater than a threshold value, allowing for real-time detection and adjustment to maintain accurate navigation and localization during medical procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If EM sensors are used for navigation and localization in robotic medical systems, then positioning accuracy is improved, but EM distortion from operating environment sources causes measurement errors
Solution Approach 1:
The patent introduces EM distortion detection as an intermediary monitoring layer that detects distortion sources in the operating environment. By detecting EM distortion through baseline metric comparison, the system identifies interference before it affects navigation accuracy, allowing for corrective actions to maintain positioning precision despite the presence of harmful EM fields from imaging equipment or other devices.
Solution Approach 2:
The system implements feedback by continuously monitoring EM sensor metrics and comparing updated values against baseline values. When distortion is detected through metric differences exceeding thresholds, the system provides feedback signals to alert operators or automatically adjust navigation parameters, creating a closed-loop system that maintains positioning accuracy despite environmental EM interference.
2Reliability
If real-time EM distortion detection is implemented, then navigation reliability is improved, but system complexity increases
Solution Approach 1:
The patent applies preliminary action by establishing baseline EM sensor metrics before the surgical procedure begins. These baseline values represent the expected EM field characteristics under normal conditions. During the procedure, any deviations from these pre-established baselines trigger distortion detection, allowing the system to identify EM interference patterns before they compromise navigation reliability, thus improving reliability through proactive rather than reactive monitoring.
Solution Approach 2:
The system uses partial action by monitoring only specific EM sensor metrics that are most indicative of distortion rather than analyzing all possible sensor data comprehensively. By focusing on key metrics such as signal strength variations or field distribution patterns, the system achieves reliable distortion detection without the computational burden of full spectral analysis or complex multi-sensor fusion, thus managing system complexity while maintaining high reliability.
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
The system effectively detects EM distortion, preventing errors in navigation and localization, ensuring precise positioning of surgical instruments and improving the reliability of EM data for robotic-assisted medical procedures.
Implementation Method 1
a first EM sensor configured to generate a first set of one or more EM sensor signals in response to detection of the EM field
Data Source
AI summary
Systems and methods for electromagnetic field generator alignment are disclosed. In one aspect, the system includes an electromagnetic (EM) sensor configured to generate, when positioned in a working volume of the EM field, one or more EM sensor signals based on detection of the EM field, the EM sensor configured for placement on a patient. The system may also include a processor and a memory storing computer-executable instructions to cause the processor to: determine a position of the EM sensor with respect to the field generator based on the one or more EM sensor signals, encode a representation of the position of the EM sensor with respect to the working volume of the EM field, and provide the encoded representation of the position to a display configured to render encoded data.