EM Sensor Selection for Medical Tracking Distortion Correction
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Solution Overview
Problem
Existing tracking systems for medical procedures face inaccuracies due to magnetic field distortions caused by field-distorting objects, which are not fully compensated for, leading to errors in device positioning and orientation, especially at greater transmitter-to-receiver distances.
Innovation Solution
A method and system that select an optimum electromagnetic (EM) sensor based on quality metrics such as transmitter-to-receiver distance and EM field integrity to correct for magnetic field distortions, using multiple EM sensors to ensure accurate device positioning and orientation projection onto diagnostic images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If distortion maps are used to compensate for field distorting objects, then some distortion compensation is achieved, but residual distortion remains uncorrected
Solution Approach 1:
The system changes the parameter of sensor selection by evaluating quality metrics (signal strength, noise level, distortion characteristics) and dynamically selecting which sensor's data to use based on current field conditions, thereby adapting to varying distortion levels without requiring perfect compensation for all objects
Solution Approach 2:
The patent replaces the mechanical/distortion-map-based compensation approach with an electromagnetic field-based selection approach, using quality metrics derived from the EM field itself to determine which sensor provides reliable data, substituting physical distortion compensation with intelligent sensor selection
2Area of stationary object
If the transmitter-to-receiver distance increases, then the coverage area increases, but the signal-to-noise ratio deteriorates
Solution Approach 1:
The system dynamically changes the parameter of sensor selection based on signal quality metrics, allowing the effective coverage area to be optimized by selecting sensors that maintain acceptable signal-to-noise ratios even at varying distances from the transmitter
Solution Approach 2:
The patent introduces dynamic sensor selection where the system continuously evaluates quality metrics and adapts which sensor is used for position determination, allowing the tracking system to maintain precision across a larger coverage area by switching to sensors with better signal characteristics as conditions change
3Reliability
If multiple EM sensors are used to improve reliability, then the system can select the most reliable sensor, but the device complexity increases
Solution Approach 1:
The system implements self-service through automatic quality metric evaluation and sensor selection, where the multiple sensors and selection algorithm autonomously determine which sensor provides the most reliable data without requiring external intervention or complex manual configuration
Solution Approach 2:
The patent employs feedback mechanisms by continuously monitoring quality metrics from each sensor and using this information to select the most reliable sensor for position determination, creating a closed-loop system that adapts to changing field conditions and maintains 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
This approach improves the accuracy of device positioning and orientation by selecting the most reliable EM sensor, reducing errors caused by field distortions and maintaining a robust signal-to-noise ratio, even at increased distances, thereby enhancing the precision of medical procedures.
Implementation Method 1
The EM transmitter generates an electromagnetic field that is detected by the EM receivers
Implementation Method 2
the presence of field distorting objects (e.g., a C-arm, X-ray detector, or surgical table) may result in distortions in the magnetic field emitted from the EM transmitter and thereby change the magnitude and direction of this field
Data Source
AI summary
In one aspect of the present technique, a method for selecting between a plurality of electromagnetic sensors to correct for one or more field distortions includes, in the presence of an electromagnetic field, acquiring signals representative of the location of a plurality of electromagnetic sensors. The method further includes selecting between the signals from the plurality of electromagnetic sensors based on one or more quality metrics. In another aspect of the present technique, a system for selecting an optimum EM sensor to correct for one or more field distortions includes a plurality of EM sensors and an additional EM sensor for transmitting or receiving signals representative of the location of each of the plurality of EM sensors. The system further includes a controller configured to acquire signals representative of the location of the plurality of EM sensors, and select between the signals from the plurality of EM sensors based on one or more quality metrics.