Adaptive Transponder Detection in Surgical Environments
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Solution Overview
Problem
Existing transponder detection systems face challenges in accurately detecting inexpensive transponders in noisy surgical environments due to large variations in signal frequency, leading to potential false negatives and increased costs for high-accuracy systems.
Innovation Solution
A method and system that adjust signal detection thresholds based on noise levels, using a higher number of samples for noise detection and response measurements, and employing frequency hopping and adaptive threshold adjustments to improve signal-to-noise ratio, allowing for accurate detection of transponders without requiring expensive, precisely tuned devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If inexpensive transponders are used, then cost is reduced, but frequency variation increases making detection difficult
Solution Approach 1:
The system dynamically adjusts the detection frequency range and threshold parameters based on the actual transponder responses. Instead of using a fixed frequency, the system adapts its detection parameters to accommodate the frequency variations inherent in inexpensive transponders, thereby maintaining detection accuracy without requiring expensive, precisely tuned transponders.
Solution Approach 2:
The system incorporates feedback mechanisms where the detected transponder responses are used to adjust subsequent detection parameters. By continuously monitoring the frequency of returned signals and adjusting the detection threshold accordingly, the system compensates for transponder frequency variations and maintains reliable detection.
2Reliability
If detection threshold is set low to detect all signals, then sensitivity increases, but false positives increase in noisy environments
Solution Approach 1:
Before actual transponder detection, the system performs preliminary noise floor measurement and threshold establishment. By characterizing the background noise environment in advance and setting appropriate detection thresholds based on this preliminary analysis, the system achieves high sensitivity while filtering out false positives from noisy environments.
Solution Approach 2:
The detection threshold is made dynamic rather than fixed, automatically adjusting based on the current noise environment and detected signal characteristics. This dynamic threshold adaptation allows the system to maintain optimal sensitivity while reducing false positives by raising the threshold when noise levels are high.
3Measurement precision
If multiple samples are taken for noise detection, then noise estimation accuracy improves, but detection time increases
Solution Approach 1:
The system takes a predetermined number of noise samples that is sufficient to achieve acceptable noise estimation accuracy without excessive sampling. By optimizing the number of samples to a practical level rather than taking every possible sample, the system balances measurement precision with detection time, achieving adequate noise characterization efficiently.
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 enhances detection accuracy and reduces false positives/negatives, enabling cost-effective and reliable transponder detection in noisy surgical environments, ensuring accurate tracking of surgical objects during procedures.
Implementation Method 1
The interrogation and detection system includes a transmitter that emits pulsed wideband wireless signals (e.g., radio or microwave frequency) and a detector for detecting wireless signals returned by the transponders
Data Source
AI summary
The presence or absence of objects is determined by interrogating or exciting transponders coupled to the objects using pulsed wide band frequency signals. Ambient or background noise is evaluated and a threshold adjusted based on the level of noise. Adjustment may be based on multiple noise measurements or samples. Noise detection may be limited, with emphasis placed on interrogation to increase the signal to noise ratio. Match filtering may be employed. Presence/absence determination may take into account frequency and/or Q value to limit false detections. Appropriate acts may be taken if detected noise is out of defined limits of operation, for example shutting down interrogation and/or providing an appropriate indication.