Implanted Wireless Sensor False Lock Prevention
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Solution Overview
Problem
Current systems for monitoring pressure in abdominal aortic aneurysms using implanted wireless sensors face challenges such as inefficiency in energy use, sensitivity issues in detecting leaks, and false locking problems due to environmental variations and signal characteristics.
Innovation Solution
A system that communicates with an implanted wireless sensor using a low duty cycle, gated burst of RF energy to determine the resonant frequency, employing phase locked loops to adjust the energizing signal and detect false locks by identifying unwanted beat frequencies and pulsatile characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple frequency transmission signal is used to determine resonant frequency, then measurement accuracy is improved, but energy consumption increases
Solution Approach 1:
The system uses periodic frequency sweeping through multiple frequency bands to locate the resonant frequency. Instead of continuously transmitting at multiple frequencies, the system periodically sweeps through frequency bands, identifying the resonant frequency only when needed, thereby reducing overall energy consumption while maintaining measurement accuracy.
Solution Approach 2:
The system dynamically adjusts transmission frequency parameters to match the detected resonant frequency. By changing the operating frequency parameter to align with the sensor's resonant frequency, the system achieves maximum energy transfer efficiency and optimal signal strength, reducing the power needed for transmission while maintaining measurement precision.
2Reliability
If continuous monitoring is performed to detect false locks, then reliability is improved, but energy consumption increases
Solution Approach 1:
The system performs false lock detection periodically rather than continuously. By sampling the received signal at regular intervals and analyzing frequency content, the system can detect false locks reliably while consuming significantly less power compared to continuous monitoring approaches.
Solution Approach 2:
The system uses feedback from signal strength and frequency analysis to determine when false lock detection is necessary. When signal conditions suggest potential false locking (e.g., unexpected frequency shifts or signal strength anomalies), the system activates detection routines, otherwise it operates in low-power mode, optimizing the balance between reliability and energy consumption.
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 enables efficient energy use, improved sensitivity in detecting leaks, and accurate pressure monitoring by preventing false locks, thus enhancing the reliability of aneurysm treatment and surveillance.
Implementation Method 1
A pair of phase locked loops (“PLLs”) is used to adjust the phase and the frequency of the energizing signal until its frequency locks to the resonant frequency of the sensor.
Implementation Method 2
The resonant frequency of the circuit varies with the pressure of the environment in which the sensor is located and thus, the resonant frequency of the circuit varies as the pressure varies.
Implementation Method 3
The system identifies false locks by detecting an unwanted beat frequency
Data Source
AI summary
The present invention determines the resonant frequency of a wireless sensor by adjusting the phase and frequency of an energizing signal until the frequency of the energizing signal matches the resonant frequency of the sensor. The system energizes the sensor with a low duty cycle, gated burst of RF energy having a predetermined frequency. The system receives the ring down response of the sensor and determines the resonant frequency of the sensor, which is used to calculate a physical parameter. The system uses a pair of phase locked loops to adjust the phase and the frequency of the energizing signal. The system identifies false locks by detecting an unwanted beat frequency in the coupled signal, as well as determining whether the coupled signal exhibits pulsatile characteristics that correspond to a periodic physiological characteristic, such as blood pressure.