Temperature Distribution Map Error Detection for Medical Probes
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Solution Overview
Problem
Existing medical mapping technologies do not effectively incorporate sensor malfunctions into temperature distribution maps during invasive procedures, failing to visually indicate malfunctioning thermal sensors and thus potentially misleading practitioners.
Innovation Solution
A method and apparatus that acquire temperature signals from multiple thermal sensors, interpolate to create a temperature distribution map, identify malfunctioning sensors, assign arbitrary temperatures, and generate an error distribution map to highlight suspect areas by superimposing it on the temperature distribution map.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If thermal sensors are used to measure temperature in biological tissue during invasive procedures, then temperature distribution maps can be generated to guide surgical procedures, but malfunctioning sensors may produce erroneous readings that compromise the reliability of the temperature map
Solution Approach 1:
The system performs preliminary detection of sensor malfunction by monitoring sensor readings against expected physiological temperature ranges before the malfunction affects the entire temperature map. When a sensor is detected as malfunctioning, the system proactively identifies and isolates the erroneous data point, preventing it from compromising the overall temperature distribution map.
Solution Approach 2:
The system introduces an intermediary error detection and visualization layer between the raw sensor readings and the final temperature distribution map. This intermediary layer detects sensor malfunctions, assigns arbitrary temperatures to isolate erroneous data, and visually marks suspect regions on the temperature map, thereby mediating between unreliable sensor data and the need for accurate surgical guidance.
2Area of stationary object
If multiple thermal sensors are mounted on a probe to create a comprehensive temperature distribution map, then spatial temperature coverage is improved, but the complexity of detecting and managing sensor malfunctions increases
Solution Approach 1:
The system segments the temperature distribution map into individual sensor contribution zones, allowing independent analysis of each sensor's readings. By dividing the overall temperature map into discrete regions corresponding to each thermal sensor's measurement area, the system can easily identify which specific sensor is malfunctioning and isolate its erroneous readings without affecting the rest of the temperature distribution map.
Solution Approach 2:
The system implements continuous feedback monitoring where sensor readings are constantly compared against expected physiological temperature ranges and spatial temperature gradients. When a sensor's reading deviates from expected values, the system provides immediate feedback by flagging the sensor as malfunctioning and visualizing the resulting error region on the temperature map, enabling real-time detection and management of sensor failures.
3Ease of operation
If sensor malfunctions are not visually indicated on the temperature distribution map, then the map remains clean and simple, but practitioners may be misled by erroneous temperature readings
Solution Approach 1:
The system uses color changes to visually indicate malfunctioning sensors and suspect regions on the temperature distribution map. Malfunctioning sensors are highlighted with distinct color markers or color-coded regions, allowing practitioners to immediately identify and ignore erroneous readings while maintaining the overall integrity and simplicity of the temperature map interpretation.
Solution Approach 2:
The system creates a visual copy or overlay on the temperature distribution map that replicates the spatial location and characteristics of malfunctioning sensors. This visual copy appears as distinct markers or shaded regions superimposed on the temperature map, providing practitioners with a clear visual representation of which areas should be interpreted with caution without requiring complex data annotations.
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 allows for real-time visualization of potential errors in temperature readings, enhancing procedural accuracy by clearly indicating malfunctioning sensors within the temperature distribution maps, thereby improving the reliability of invasive procedures.
Implementation Method 1
acquiring signals, indicative of temperatures at respective locations in a biological tissue, from a plurality of thermal sensors mounted on a probe in contact with the tissue
Implementation Method 2
interpolating between the temperatures so as to produce a temperature distribution map
Data Source
AI summary
A method, consisting of acquiring signals, indicative of temperatures at respective locations in a biological tissue, from a plurality of thermal sensors mounted on a probe in contact with the tissue, interpolating between the temperatures so as to produce a temperature distribution map, and displaying the temperature distribution map on a screen. The method also includes determining that at least one of the thermal sensors is a malfunctioning thermal sensor, and that remaining thermal sensors of the plurality are correctly operating. The at least one malfunctioning thermal sensor is assigned a first arbitrary temperature and the correctly operating thermal sensors are assigned second arbitrary temperatures. The method further includes interpolating between the first and second arbitrary temperatures so as to produce an error distribution map indicative of a suspect portion of the temperature distribution map, and superimposing graphically the error distribution map on the displayed temperature distribution map.