RESONANT CIRCUIT-BASED VASCULAR MONITOR AND ASSOCIATED SYSTEMS AND METHODS - Patent application

Abstract

A system and method for control and signal processing in a variable inductance, resonant circuit vascular monitoring device is disclosed, including using the magnitude of the sensor signal to determine and interpret a sensed parameter.

Description

[Technical field]

[0001]

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 344,409, filed May 20, 2022, and entitled "RESONANT CIRCUIT-BASED MONITOR AND RELATED SYSTEMS AND METHODS," which is incorporated herein by reference.

[0002]

[0002] The present disclosure relates to improvements in wireless vascular monitors, particularly resonant circuit-based vascular monitors, and related systems and methods. [Background technology]

[0003]

[0003] A resonant circuit (RC) based sensor is a sensor that transmits a change in resonant frequency as a result of a change in a physical parameter in the surrounding environment, which causes a change in the resonant frequency generated by a circuit in the device. The change in resonant frequency, detected as a "ringback" signal when the circuit is energized, indicates the sensed parameter or its change. As is well known, a basic resonant circuit includes an inductance and a capacitance. In most available RC sensing devices, the change in resonant frequency is caused by a change in the capacitance of the circuit. A well-known example of such a device is a capacitor whose plates move together or apart in response to changes in pressure to provide a pressure sensor. Less commonly, the change in resonant frequency is based on a change in the inductance of the circuit.

[0004]

[0004] The applicant has filed numerous patent applications disclosing novel RC monitoring devices that use variable inductance to monitor intravascular dimensions and, based thereon, determine physiological parameters such as a patient's fluid status. See, for example, PCT / US2017 / 063749 (Publication No. WO2018 / 102435), entitled "Wireless Resonant Circuit and Variable Inductance Vascular Implant for Monitoring a Patient's Vascular and Fluid Status, and Systems and Methods for Using the Same," filed on November 29, 2017, and PCT / US2019 / 034657 (Publication No. WO2019 / 232213), entitled "Wireless Resonant Circuit and Variable Inductance Vascular Monitoring Implant and Anchor Structure Therefor," filed on May 30, 2019. Each of these is incorporated herein by reference and discloses various embodiments and techniques related to such devices. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2018 / 102435 [Patent Document 2] International Publication No. 2019 / 232213 Summary of the Invention [Problem to be solved by the invention]

[0006]

[0005] Despite the technological advances represented by these prior art, improvements in the control and signal processing of such devices are still possible. Thus, the present disclosure provides solutions to some of the inherent problems described herein that were only encountered after the introduction and testing of the aforementioned new RC monitoring devices. [Means for solving the problem]

[0007]

[0006] In one embodiment, the disclosure relates to a method for controlling a wireless resonant circuit sensor, the sensor including a variable inductance coil that changes resonant frequency in response to changes in a monitored physical parameter and generates a ringback signal when energized, the ringback signal having a signal amplitude that correlates with the physical parameter. The method includes outputting an excitation signal selected to generate the ringback signal from the sensor, receiving the ringback signal from the sensor with a receive amplifier, comparing the magnitude of the sensor ringback signal to a dynamic range of the receive amplifier, and reducing the receive amplifier gain if the compared magnitude is equal to or exceeds the magnitude dynamic range of the receive amplifier. If the amplitude is at the limit of the dynamic range, the receiver gain can be reduced to bring the system back into a linear range.

[0008] In another embodiment, the disclosure relates to a method for characterizing a resonant circuit sensor and correlating the sensor output to a measured physical parameter, the sensor comprising a variable inductance coil that, when excited, changes its resonant frequency in response to changes in the physical parameter by generating a ringback signal having a signal amplitude correlable to the physical parameter. The method includes determining physical parameter value versus signal amplitude data for at least one sensor over a range of parameter values ​​and signal amplitudes prior to placement on a patient, and creating a signal amplitude characteristic curve for the at least one sensor by plotting a curve with the signal amplitude data using curve fitting or interpolation techniques.

[0009] In yet another embodiment, the disclosure is directed to a method for controlling a wireless resonant circuit sensor, the sensor including a variable inductor that changes resonant frequency in response to changes in a monitored physical parameter and that, when energized, generates a ringback signal at a frequency or magnitude that correlates with the physical parameter. The method includes: outputting a sensor energization signal at an initial transmit frequency; receiving a ringback signal at a ringback frequency from the sensor in response to the sensor energization signal; determining a difference between the transmit frequency and the ringback frequency; periodically repeating the outputting, receiving, and determining while the difference between the transmit frequency and the ringback frequency is below a predetermined threshold; changing the transmit frequency of the sensor energization signal to a new transmit frequency that matches the ringback frequency of the last received ringback signal if the difference meets or exceeds the predetermined threshold; and periodically repeating the outputting at the new transmit frequency and then the receiving and determining. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a schematic system overview of an embodiment of a wireless vascular monitoring system employing a resonant circuit-based sensor implant. [Diagram 2] FIG. 2 is a block diagram of an embodiment of a control system of the wireless vascular monitoring system disclosed herein. [Diagram 3] 3A, 3B, and 3C show signals obtained in in vivo preclinical experiments using the prototype RC-WVM system disclosed herein. [Figure 4] 4A and 4B show example ringback signals received in benchtop testing through a control system receive amplifier module with and without transmit-to-receive excitation signal leakage in accordance with embodiments disclosed herein. [Diagram 5] FIG. 5 is an example of a sensor characteristic curve. [Figure 6] FIG. 6 is an example of a size vs. area characteristic curve. [Figure 7]FIG. 7 is an example of an empirically derived transmission efficiency curve. [Figure 8] FIG. 8 is an example of a plot of a frequency time curve for a fixed transmit frequency system, with the average transmit frequency shown as a dashed line and the average resonant frequency shown as a solid line. [Figure 9] FIG. 9 is an example of a plot of a dynamically adjusted frequency system frequency versus time curve, with the average transmit frequency shown as a dashed line and the average resonant frequency shown as a solid line. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] For the purpose of illustrating the invention, the drawings show aspects of one or more embodiments of the invention, it being understood, however, that the invention is not limited to the precise arrangements and instrumentalities shown in the drawings.

[0012]

[0010] The unique physiology of the inferior vena cava (IVC) presents some unique challenges when attempting to detect and interpret changes in its dimensions due to changes in a patient's fluid status. For example, the IVC walls in a typical monitoring region (i.e., between the hepatic and renal veins) are relatively flexible compared to other blood vessels, meaning that changes in vessel volume may result in different changes in the relative distance between the anterior and posterior walls compared to the lateral and medial walls. Thus, it is quite common for changes in fluid volume to lead to paradoxical changes in vessel shape and motion. That is, when blood volume decreases, the IVC tends to become smaller and collapse with respiration, and when blood volume increases, the IVC tends to become larger and collapse with respiration decreases. Applicant has developed a novel wireless sensor implant and associated systems and methods to address these challenges and provide a clinically effective wireless vascular monitor ("WVM"). In one such embodiment, the WVM includes a resonant circuit ("RC-WVM") configured as a coil implantable in the patient's vasculature. Detailed examples of embodiments of the RC-WVM system and method are disclosed, inter alia, in Applicant's U.S. Patent No. 1,1206,992 (U.S. Patent Application No. 17 / 018,194, filed September 11, 2020), entitled "Wireless Resonant Circuit and Variable Inductance Vascular Monitoring Implant and Its Anchor Structure," which was granted on December 28, 2021, and is incorporated by reference in its entirety into this specification.

[0013] In the course of working on embodiments of the RC-WVM as described in the above-referenced applications, applicant has developed a number of new embodiments that further improve the accuracy and ease of use of the aforementioned RC-WVM implants, systems, and methods as disclosed herein, which are described below after providing a basic overview of one example of the RC-WVM system and its operation.

[0014]

[0012] Figure 1 shows an overview of an RC-WVM system 10 to which the embodiments disclosed herein are applicable. As shown in the figure, such a system may generally include an RC-WVM implant 12 configured for placement in a patient's inferior vena cava (IVC), a control system 14, an antenna module 16, and one or more remote systems 18, such as a processing system, user interface / display, data storage, etc., that communicate with the control and communication module via one or more data links 26. The data links 26 may be wired or remote / wireless data links. In many implementations, the remote system 18 may include a computing device and user interface, such as a laptop, tablet, or smartphone, that serves as an external interface device.

[0015]

[0013] The RC-WVM implant 12 generally comprises a resonant LC circuit formed as a variable inductance, constant capacitance, collapsible and expandable coil structure that, when placed in a monitoring position within a patient's IVC, moves with the IVC wall as it expands and contracts due to changes in bodily fluid volume. The variable inductance is provided by the implant's coil structure, which changes inductance as the dimensions of the coil (e.g., the area enclosed by the coil or "sensor area") change with the movement of the IVC wall. The capacitive element of the circuit may be provided by a separate capacitor or a specially designed intrinsic capacitance of the implant structure itself. When an excitation signal is directed to the RC-WVM implant, the resonant circuit generates a "ringback" signal at a frequency that is characteristic of the circuit. The characteristic frequency changes based on the change in the size of the inductor, i.e., the coil, as it changes with the vessel wall. Because the inductance value depends on the geometry of the implant, which changes based on dimensional changes in the IVC in response to fluid status, heart rate, etc., as described above, the ringback signal is interpreted by the control system 14 to provide information regarding the geometry of the IVC and therefore fluid status, and other physiological information such as respiratory rate and heart rate.

[0016] The control system 14 includes functional modules for, for example, signal generation, signal processing, and power supply (generally including excitation and feedback monitoring ("EFM") circuitry, and shown as modules 20 including a signal generation module 20a and a receiving amplifier module 20b as shown in FIG. 2), and a communications and data acquisition module 22 that facilitates communications and data transfer to various external or remote systems 18 via a data link 26 and optionally other local or cloud-based networks 28. After analyzing the signals received from the RC-WVM implant 12, the results may be communicated manually or automatically in any suitable manner (e.g., verbally, by printing a report, by sending a text message or email, or otherwise) via the external or remote systems 18 to the patient, a caregiver, a medical professional, a health insurance company, and / or any other desired authorized party. 2, the components of the control system 14 may consist of a transmit / receive (T / R) switch 92, a transmitter tuning and matching circuit 94, a receiver tuning and matching circuit 96, a direct digital synthesizer (DDS) 98, an anti-aliasing filter 100, a preamplifier 102, an output amplifier 104, a single-ended to differential input amplifier (SE to DIFF) 106, a variable gain amplifier (VGA) 108, a filter amplifier (e.g., an active bandpass filter amplifier) ​​110, an output filter (e.g., a passive high-order lowpass filter) 112, a high-speed analog-to-digital converter (ADC) 114, a microcontroller 116, and a communication sub-module 118. Signal discrimination, selection, and other signal processing functions after amplification and filtering may be embedded within the microcontroller 116 or may be performed by an external interface device 18 (e.g., a computing system executing program instructions to perform the steps disclosed herein).

[0017]

[0015] The antenna module 16 is connected to the control system 14 by a power and communication link 24, which may be a wired or wireless connection. Based on the signal provided by the signal generation module 20a of the control system 14, the antenna module 16 creates a magnetic field of appropriate shape and direction around the RC-WVM implant 12 to excite the resonant circuit as described above. The antenna module 16 thus provides both a receiving function / antenna and a transmitting function / antenna. In some embodiments, the transmitting and receiving functions are performed by a single antenna that is switched between a transmitting mode and a receiving mode, for example, by a transmit / receive switch 92 (which may be a single-pole double-throw switch). In other embodiments, each function is performed by a separate antenna. The antenna module 16 may also optionally include an input bandpass filter to reduce noise (e.g., resulting from intermodulation) and improve signal quality. The input bandpass filter may also help improve immunity to external electromagnetic interference.

[0018]

[0016] As will be appreciated by those skilled in the art, optimal excitation of an LC resonant circuit occurs when an excitation signal is provided at the natural frequency of the circuit. However, in the RC-WVM implant 12 described herein, the natural frequency of the circuit at any time is not known in advance, since the size of the RC-WVM sensor varies depending on its intended use. In one embodiment, a typical sensor is adapted to a patient's IVC diameter that is nominally in the range of about 14 mm to about 28 mm. This means that the overall sensor diameter range will be from slightly less than about 14 mm to slightly more than 28 mm to detect changes in IVC dimensions above and below the nominal size range. If the sensor diameter is at the lower end of its size range, for example, less than about 19 mm, or less than about 15 mm, the amplitude of the ringback signal generated by the sensor will be relatively low due to reduced inductive coupling, and therefore challenges may arise with respect to detection and accurate signal analysis. Further challenges in determining an appropriate excitation signal may be imposed by regulatory requirements, which typically require limited bandwidth and power for such signals. These challenges can be solved in several ways.

[0019] In one embodiment, the excitation signal provided by the signal generating module 20a and transmitted by the antenna module 16 can be configured as a predefined transmit pulse (e.g., single frequency burst) for exciting the RC-WVM sensor. In this embodiment, the transmit pulse frequency is selected to optimally excite the sensor based on the assumption that the sensor is in a small diameter range. This is because the smaller the diameter of the sensor, the lower the amplitude of the ringback signal. In another embodiment, the transmit pulse frequency can be selected based on the assumption that the sensor is in a minimum diameter. In this case, the amplitude of the ringback signal will be the smallest, and therefore optimal excitation is required so that the ringback signal is at a sufficiently detectable level to provide a reliable reading. The same predefined transmit pulse frequency is used to excite the sensor for the duration of the signal measurement (e.g., 60 seconds). However, as the blood vessel expands, the optimal excitation frequency may change and the amplitude of the ringback signal may decrease, resulting in a less reliable reading.

[0020]

[0018] In another embodiment, a frequency sweep function can be used to more reliably transmit the excitation signal at or near the optimal frequency. In one example, the signal generating module 20a performs the frequency sweep function by continuously outputting a predetermined number of transmit pulses at a predetermined frequency over the range of the natural frequency of the expected implant (in one example, five transmit pulses are used). The ringback sensor signal captured during the frequency sweep function is processed via the receiving amplifier module 20b, the communication and data acquisition module 22, and optionally the external device 18. All ringback signals (corresponding to the predetermined number of transmit pulses) are received and processed. The resonant frequency detected from the predetermined number of transmitted transmit pulses with the highest amplitude is selected as the optimal transmit frequency. The optimal excitation frequency is then used as the excitation transmit pulse to power the sensor for the duration of the signal measurement (e.g., 60 seconds). Note that, depending on the size of the sensor during the transmit pulse sweep, all ringback signals from a pre-set number of transmit pulses may be detected and any one of them may be used as the optimal resonant frequency.

[0021]

[0019] In the frequency sweep method described above, the system selects the frequency with the maximum amplitude detected during the frequency sweep function. As described, the amplitude of the resonant frequency generated depends on the IVC dimensions (e.g., area or diameter) of the monitoring location, with larger dimensions resulting in larger signal amplitudes. When employing this methodology, the system therefore tends to select the optimal excitation frequency for larger sensor sizes. Then, during signal acquisition, if the vessel dimensions decrease (e.g., due to respiratory failure), the excitation may become suboptimal, and the signal quality may be reduced or insufficient when the vessel contracts. To address this, further alternative excitation frequency determination methods may be used.

[0022]

[0020] In one such further alternative embodiment, the excitation frequency is determined using a two-stage approach. First, an initial excitation frequency is determined, for example, using the frequency sweep function described above. Thus, the signal generating module 20a is configured to transmit at the frequency determined by the frequency sweep function during an initial observation period, which should be long enough to cover at least one respiratory cycle. During this period, the sensor resonant frequency is evaluated, and the highest frequency detected is then selected as the excitation frequency for the remaining signal measurements. In this approach, it may be advantageous to select a higher frequency, a corresponding smaller sensor area (which may be the worst case for signal quality), and thus provide a more reliable excitation.

[0023]

[0021] Considering the situation of significant IVC collapse due to breathing, the limitations of the method described in the previous paragraph are assumed. In this case, the initial frequency sweep tends to select a resonant frequency corresponding to a larger sensor / vessel dimension, so that when the IVC reaches a maximum level of collapse, the resonant frequency of the sensor may deviate significantly from the excitation frequency, resulting in a suboptimal excitation. This, combined with the reduced amplitude of the sensor response (due to the small sensor area), may lead to unreliable resonant frequency detection (due to poor signal quality) and inaccurate excitation frequency determination.

[0024]

[0022] To overcome this problem, a further improvement can be adopted in which the system repeatedly executes the above frequency sweep function for a period of a predetermined length, which should be long enough to cover at least one respiratory cycle. Since the excitation frequency is sequentially changed between predetermined frequencies (including the frequency corresponding to the smallest sensor area), more optimal excitation is achieved in situations where the IVC is highly collapsed and the sensor is small. As in the above method, the system selects the highest observed resonant frequency as the excitation frequency for the remaining signal measurements.

[0025] In another embodiment, the frequency of the excitation signal is dynamically adjusted during signal acquisition. In one embodiment, the amplitude or signal-to-noise ratio (SNR) of the response signal from the RC-WVM sensor is dynamically adjusted (sample by sample) or Periodically, if the signal amplitude is detected to fall below a predefined threshold (e.g., due to a larger collapse of the IVC), a new frequency sweep (using one of the methods mentioned above) can be performed to retune to the latest sensor resonant frequency.

[0026]

[0024] In a further embodiment, the output frequency of the signal generating module 20a is continuously adjusted after each measurement point. In this case, the resonant frequency of the sensor is calculated for each sample acquired between sample acquisitions. Thus, the excitation frequency of the next sample is adjusted to the last measured resonant frequency. If the sampling rate of the system is faster than the IVC decay dynamics, this method always guarantees optimal excitation.

[0027]

[0025] In the above described embodiment, a signal processing algorithm for frequency detection is required that can be executed in real time in the communication and data acquisition module 22. A fast Fourier transform (FFT) can be used for this purpose. However, if a high resolution of the detected IVC dimension is required, the length of the required FFT may lead to too long a calculation time, which is not suitable for determining the frequency during the sample acquisition. Instead, a variation of the conventional FFT can be used, such as a zoom FFT. This technique allows to focus the analysis on a specific part of the spectrum, thus shortening the length of the FFT and therefore the calculation time without compromising the resolution of the detected frequency.

[0028]

[0026] Since the amount of RF power that can be transmitted via the antenna 16 is subject to limitations imposed by applicable regulations aimed at ensuring efficient use of the frequency spectrum, determining the optimal transmission frequency using any of the methods described above is key to providing efficient excitation of the RC-WVM sensor. As an additional measure to minimize the level of intentional RF radiation, the dependency between the RC-WVM sensor area and the strength of the sensor response signal can be considered. As mentioned above, the larger the sensor area, the greater the mutual inductance (and therefore the magnetic field coupling) between the antenna 16 and the RC-WVM sensor will typically be. Taking this into account, the signal generating module 20a can be controlled such that the output RF power is adjusted as a function of the output frequency. In particular, the maximum power is transmitted when the detected resonant frequency of the sensor is at the upper limit of the expected sensor bandwidth, which corresponds to the smallest sensor area and therefore the weakest response. Thus, the output power decreases monotonically as the frequency is lowered, facilitating compliance with applicable wireless regulations.

[0029]

[0027] In another embodiment, the amplitude of the RC-WVM sensor response signal is monitored and the transmitter power is dynamically adjusted to achieve, for example, a constant signal amplitude (similar to an automatic gain control application). As explained in the previous paragraph, this methodology allows for tighter control of the radiated RF power. Furthermore, this methodology provides a means to ensure that the amplitude of the received signal does not cause saturation of the receiver stage, which can lead to inaccuracies in the signal processing algorithms subsequently applied to determine the fundamental components of the sensor.

[0030]

[0028] Figures 3A, 3B, and 3C show examples of signals from an in vivo test, namely the raw ringback signal, the detection of the resonant frequency, and the conversion to IVC dimensions using the reference characteristic curve, respectively. Figure 3A shows the raw ringback signal in the time domain, where the resonant response of the RC-WVM implant decays over time. Modulation of the implant shape due to changes in the IVC shape results in a change in the resonant frequency, which can be seen as the difference between the two different plotted traces. Figure 3B shows the RC-WVM implant signal of Figure 3A converted to the frequency domain and plotted over time. The resonant frequency of Figure 3A is determined (e.g., using a fast Fourier transform) and plotted over time. The larger and slower modulation of the signal (i.e., three broad peaks) indicates the IVC wall motion caused by breathing, while the faster and smaller modulation superimposed on this signal indicates the IVC wall motion in response to the cardiac cycle. Figure 3C shows the frequency modulation plotted in Figure 3A converted to a plot of sensor area versus time. (The conversion in this case is based on characteristic curves determined by bench testing over a range of sample diameter lumens, following standard laboratory / test procedures.) Thus, Figure 3C shows the change in IVC dimensions at the monitoring location in response to the respiratory and cardiac cycles.

[0031]

[0029] As can be appreciated by those skilled in the art, accurate and reliable interpretation of complex signals such as those shown in Figures 3A-3C requires good signal fidelity and reliability for both the excitation signal and the ringback signal from the RC-WVM. Thus, the embodiments disclosed herein provide a solution to a potential problem and help ensure the highest possible signal fidelity and reliability.

[0032] One way signal fidelity can be compromised is by imperfections in the hardware within the control system that result in inaccurate readings. Thus, a mechanism is needed to verify the accuracy of the data generated by the system. In one embodiment, the accuracy of the data can be verified by reading the known frequency signal generated by the signal generation module 20a with the receive amplifier module 20b and verifying that the output of the system matches the known input. Thus, in an embodiment, the raw data file can be verified offline because a known fixed frequency and amplitude signal portion is contained within the captured signal. The receive amplifier module 20b, in conjunction with the communications and data acquisition sub-module 22, begins capturing the generated signal as soon as the transmit cycle begins. Because the transmit signal is large in amplitude, a small leakage signal is generated through the transmit / receive (T / R) switch 92 that reaches the receiver channel. Because the gain of the receiver channel is very large, the signal generated at the receiver output can be detected and processed to determine its frequency. The frequency is known in advance because the transmitter is programmed to generate such a frequency. In another alternative, a known or fixed frequency signal portion can be included in the sensor's raw data capture by allowing the transmit / receive switch 92 to briefly leak a known excitation signal from the transmit side to the receive side when switching from transmit to receive.

[0033]

[0031] Thus, when the receive amplifier module 20b starts to capture the receive signal, the first part of the signal is a known frequency part. Comparing Figures 4A and 4B shows a short signal leakage. Figure 4A shows a ringback signal that the control system may receive after the RC-WVM sensor is energized by a signal from the transmit side in normal operation without signal leakage through the T / R switch 92. The signal in Figure 4A starts at maximum amplitude on the left side when the RC-WVM coil is first energized and decays over time as energy is dissipated. In this example, the ringback signal starts at time 14 μs, which represents the time delay between the transmit signal being sent and energizing the sensor. (The excitation signal is delivered from time 0, which is not shown in Figure 4A but is shown in Figure 4B.) The signal in Figure 4B shows the receive signal when leakage through the switch is allowed as in the above embodiment. The leakage part of the signal (LS) starts at approximately time 0 because there is no delay before the sensor is energized. Secondly, by limiting the leakage signal (LS) to a time before the sensor ringback signal is expected, the leakage signal does not interfere with readings from the sensor, while at the same time providing a known frequency verification signal that can be checked against the output of the control system.

[0034]

[0032] In one embodiment, the process of providing the leakage signal as a hardware verification signal of known frequency may include the following. 1. The RF transmitter outputs a known pulse through the antenna to power the sensor. 2. The transmit / receive switch is configured to allow signal leakage from the transmit side to the receive side. The receiver electronics begin capturing receiver data while the transmitter is active. 3. The transmit / receive switch completely changes the antenna connection to the receive electronics to detect the RF response of the sensor. 4. The receiving electronics continues to capture the sensor signal via the ADC. 5. The captured ADC data is stored in the microcontroller and sent to a laptop for long term storage. The data includes the transmit portion of the transmit / receive cycle in a data packet. The data packet also includes the frequency programmed into the RF transmitter. 6. The data can then be verified by comparing the frequency and amplitude of the transmitted portion of the data signal data to predefined thresholds of programmed frequency and expected amplitude.

[0035]

[0033] A further problem that may occur in systems of the type described herein is interference from background noise. Excessive electromagnetic noise or external electromagnetic interference from nearby devices may cause the system to detect readings that are unrelated to the sensor signal. During normal operation, the system attempts to detect a signal induced by the sensor in response to an excitation signal sent to the sensor during a transmission cycle. A sufficiently strong external signal may couple into the system and mask the sensor signal, leading to inaccurate measurements.

[0036]

[0034] This problem can be solved according to the present disclosure by providing a mechanism to evaluate the electromagnetic background noise before the measurement starts. In one embodiment, the system is operated in normal mode, i.e., the transmit mode is activated and a known test frequency is transmitted that is sufficiently far from the expected sensor bandwidth / excitation frequency. In this way, the sensor is not energized and therefore no ringback signal response is generated. The control system then switches to receive mode as in normal operation and the received signal is recorded. Since there is no response from the sensor (due to the "detuned" transmit frequency), the received signal is entirely composed of background electromagnetic noise. Then, based on the detected background noise, appropriate corrections or adjustments in the signal processing can be made. In one option, the control system evaluates the power of the maximum component of the background noise signal. This process is repeated a predetermined number of times and an average value is obtained for a more consistent measurement. The calculated signal level is then defined as the background noise.

[0037]

[0035] The above-mentioned background noise assessment process is not limited to being performed before starting to record the sensor signal. In other embodiments, the above-mentioned background noise assessment can be performed at different stages or points in the sensor signal acquisition process to mitigate risks associated with increased noise coupling due to intermittent noise sources, patient movement, etc.

[0038]

[0036] Following the evaluation of the background noise, the sensor signal is identified by a frequency sweep. Once a sensor response signal is detected, its amplitude is evaluated and the resulting value is compared to the previously measured background noise amplitude, effectively calculating the signal-to-noise ratio (SNR). A minimum threshold level is set for the SNR. An SNR below this limit indicates that external interference is high enough to prevent reliable measurements. This can alert the user to change location or remove possible sources of interference to continue using the system.

[0039]

[0037] The use of characteristic curves to convert the raw signal output of an RC-WVM sensor into physiologically relevant measurements of vessel size and size change was described above in connection with Figures 3A and 3C. In general, characterizing the raw sensor signal to provide a useful physiologically relevant measurement to a healthcare provider is understood in the art. However, the RC-WVM sensors described herein can pose unique characterization challenges because their characteristic inductance is intentionally varied by design. Furthermore, the inductance and capacitance characteristics that define the resonant circuit vary due to manufacturing variations in the sensor. To address these challenges in characterizing RC-WVM sensors, several new and different approaches are available.

[0040]

[0038] In one embodiment, a sensor characteristic curve, such as that shown in Figure 5, is created by passing the RC-WVM sensor through a series of increasingly larger tubes with known areas in sequence and recording the corresponding frequencies. A number of methods can then be used to generate a unique curve from these area-frequency measurements. For example, a curve fitting method can be used to fit a curve to the raw data and minimize the error between the fit and the raw data. Curve fitting can be performed using various fitting types, such as exponential fitting or logarithmic fitting based on the following function:

[0041]

number

[0042] In another example, interpolation may be used to create a curve by interpolating between recorded regional frequency data. Several interpolation methods can be used, including a linear interpolation function such as:

[0043]

number

[0044] In addition to the curve type selected, characteristic curves can be generated from individual sensor specific area-frequency data or from average area-frequency data of a set of sensors.

[0045]

[0039] Typically, each RC-WVM sensor characteristic curve is determined in a clean room during sensor manufacturing. However, these curves may shift slightly after manufacturing and sterilization processes. Because clinical sensors cannot be recharacterized after sterilization, sensor / batch-specific manufacturing curves can only be created before sterilization. Alternatively, reference characteristic curves can be generated after sterilization from independent sensors that are not clinically used, provided that they are manufactured and sterilized in a similar manner to the clinical sensor used as a reference.

[0046]

[0040] In a further embodiment, higher characterization accuracy can be achieved as follows: First, during manufacturing, area vs. frequency data for each sensor is determined. From this sensor or batch specific area vs. frequency data, a characterization curve is created by curve fitting or interpolation before or after sterilization as described above. Then, sensor measurements are taken and the results are converted to IVC dimensions using the characterization curve created in the previous step. In this way, measurement errors resulting from manufacturing variations are minimized by using sensor or batch specific characterization curves. Using a pre-determined characterization curve allows more accurate measurements over a wider dimensional range, avoiding the need for in vivo calibration for imaging modalities such as intravascular ultrasound (IVUS), which have other inherent accuracy issues.

[0047]

[0041] In yet another embodiment, information about the magnitude of the response signal induced by the resonant sensor is extracted from the sensor trace. Changes in the cross-sectional area of ​​the inductive element of the sensor affect the amount of magnetic flux captured by the sensor, which in turn affects the magnitude of the signal induced in the sensor coil. Thus, the magnitude of the sensor response signal can provide additional information about the cross-sectional area of ​​the sensor, among other parameters. The cross-sectional area of ​​the sensor can be complementary to information obtained from the natural frequency of the resonant circuit incorporated in the sensor.

[0048]

[0042] The extracted signal amplitude information can be used to establish an amplitude characteristic curve, mapping the received signal amplitude to the sensor cross-sectional area. As an example, this can be done by manipulating the sensor into different configurations (where the cross-sectional area is known) and determining the resulting sensor response signal amplitude detected by the system. Such amplitude characteristic curves can be used to further characterize the accuracy of the sensor response and interpretation of the received signal.

[0049]

[0043] Figure 6 shows an example of characteristic curves of area as a function of magnitude. For a given sensor response signal, both the magnitude and frequency of the resonant frequency component can be determined. Both parameters can be used together to determine the cross-sectional area of ​​the sensor. Using both magnitude and frequency characteristics can increase the robustness of the area estimation. For example, situations can arise where external interference can damage or affect the accuracy of the area estimation from the sensor frequency. In this case, area detection from magnitude can be used as a secondary mechanism to detect and possibly correct the estimated area.

[0050]

[0044] Although the signal amplitude can be used as described above, in the in vivo environment of the system application described in this disclosure, the detected sensor signal amplitude may be influenced by other functional parameters that may be independent of the sensor geometry and may cause errors when trying to extract sensor information from the response signal amplitude. To improve accuracy, such other functional parameters may be taken into account by the techniques described below.

[0051]

[0045] Saturation of the detection signal - an implantable sensor as described in this disclosure is expected to operate over a relatively wide range of vessel sizes and shapes. As explained, the magnitude of the response signal induced by the sensor is directly dependent on the cross-sectional area of ​​the vessel in which it is embedded, with the magnitude being lowest when the vessel area is at the small end of the scale. The receiving element in the system used to detect the sensor response signal must be able to sufficiently amplify this worst-case amplitude of the sensor response signal. However, as the area (and therefore the magnitude of the sensor response signal) increases, a point will eventually be reached where the linearity of the receiving amplifier cannot be maintained, and the output signal will saturate and clip. This effect can affect the fidelity of the determination of the magnitude of the sensor signal, leading to potential errors in the decoding of the information contained in the magnitude.

[0052]

[0046] To counteract the effects described in the previous paragraph, the receive amplifier gain can be adjusted depending on the dynamic operation of the embedded sensor. This can be accomplished by several means, including but not limited to the following: · Evaluate the amplitude of the sensor response signal compared to the dynamic range of the receiving amplifier and analog-to-digital converter. If the amplitude is at the limit of the dynamic range, the receiving gain can be reduced to bring the system back into the linear range. Such a gain reduction can be achieved using a variable gain amplifier (VGA) (108 in Figure 2). The gain of the VGA can be changed by a control voltage that can be generated, for example, by a microcontroller (116 in Figure 2), for example, using an internal digital-to-analog converter (DAC). Using safety thresholds can ensure that the gain is adjusted before saturation occurs (e.g., if the detected signal amplitude is rising and approaching the upper limit of the dynamic range, a gain reduction is triggered when the signal amplitude reaches a pre-determined threshold). These thresholds can be selected as a trade-off between the possibility of saturation and the effective dynamic range of the receiving stage (e.g., using a low threshold reduces the possibility of saturation, especially when the signal is changing rapidly, but uses a very limited dynamic range, reducing the effective resolution of the analog-to-digital conversion stage). As an example, in the case of a 12-bit ADC (where the maximum number of ADC counts is 4095), a receive gain control function can be implemented such that the receive gain is reduced when the peak value of the amplified response signal from the RC-WVM sensor reaches a count corresponding to 75% of the maximum ADC count (i.e., 3064). A second lower threshold can be added to the above method, so that the gain is increased when the sensor signal amplitude falls below that threshold. This occupies a larger part of the dynamic range of the receiver amplifier and optimally uses the resolution of the analog-to-digital converter. For example, for a 12-bit ADC (maximum number of ADC counts is 4095), the receiver gain control function can be implemented such that the receiver gain is increased when the peak value of the amplified response signal from the RC-WVM sensor falls below a count corresponding to 25% of the maximum ADC count (i.e. 1024). The optimal receiver gain can be calculated from the resonant frequency of the sensor. In particular, there is an inverse correlation between the cross-sectional area of ​​the sensor and the resonant frequency: the lower the frequency, the larger the area, which results in a larger signal amplitude as mentioned above. Based on this, a frequency vs. gain mapping can be created and the receiver gain can be adjusted depending on the detected resonant frequency of the sensor.

[0053]

[0047] Excitation signal effectiveness - Another item that affects the overall signal amplitude is the effectiveness of the excitation signal. This is defined as the amount of energy of the excitation signal transmitted by the control system and effectively captured by the resonant circuit of the RC-WVM sensor. As explained in paragraph

[0016] , maximum energy transfer to the sensor resonant circuit occurs when the frequency of the excitation signal is equal to the resonant frequency of the sensor. Any mismatch between the two reduces the effectiveness of the excitation signal and reduces the magnitude of the response signal induced by the RC-WVM sensor. This can lead to inaccurate area estimates (e.g., the sensor area may be assumed to be smaller than it actually is due to the reduced size, but this is actually due to inefficiency of the sensor excitation). To mitigate this issue, a transmission efficiency function can be derived. This takes the form of a transmission efficiency factor (a number between 0 and 1), which is a function of the difference between the transmitted and received signal frequencies (if the transmitted and received signal frequencies are identical, the factor will be 1). Knowing the transmission efficiency allows us to consider the effect of a less than optimal RC-WVM sensor excitation on the resulting signal amplitude and eliminate or reduce this confounding factor. As a result, the reliability of the response signal amplitude induced by the RC-WVM sensor as a predictor of the sensor cross-section is improved.

[0054]

[0048] In one embodiment, the effect of non-optimal sensor excitation can be taken into account by adjusting the measured signal amplitude upward by the inverse of the transmission efficiency function. This can be done by multiplying the measured signal amplitude by the inverse of the efficiency function (in other words, dividing by the efficiency function to obtain the adjusted signal amplitude). The adjusted signal amplitude is then used instead of the measured signal amplitude to determine the sensing parameter, such as lumen area, with the amplitude characteristic curve. For example, if the measured signal amplitude is 70 a.u. and the efficiency function is 0.7, then the adjusted signal amplitude is 100 a.u. (i.e., 70 a.u. / 0.7).

[0055]

[0049] This transmission efficiency function can be theoretically derived, for example, by calculating the spectrum of the transmission signal and the frequency response curve of the sensor, and shifting the frequency of the transmission signal over the expected transmission range. In a possible embodiment, the spectrum of the transmission signal is calculated (for example, using a Fourier transform). The amplitude of this spectrum is then sampled at the resonant frequency of the RC-WVM sensor. For a transmission signal consisting of a given number of sinusoidal pulses, whose spectrum corresponds to a Sin function, the efficiency can be calculated from the resonant frequency (f_rx) and transmission frequency (f_tx) of the RC-WVM sensor using the following formula:

[0056]

number

[0057] Alternatively, the transmit efficiency function can be derived empirically by acquiring the sensor signal for a given area, starting with an optimal tuning of the transmit and receive frequencies, and then shifting the transmit frequency up and down while evaluating the effect on the magnitude of the sensor response signal. This is shown in Figure 7, which shows an example of an empirically derived transmit efficiency curve.

[0058]

[0050] Dynamic transmit signal frequency adjustment based on signal efficiency -- An alternative approach to determining the transmit signal frequency includes dynamic frequency adjustment based on the difference between the detected sensor resonant frequency and the energized signal transmit frequency. In this technique, the system performs an initial frequency sweep that transmits at a series of discrete frequencies over the expected range of the sensor resonant frequency. The initial transmit frequency is derived using this approach, as described above. The frequency of the sensor response signal is then monitored at each acquisition, and the difference between the detected frequency and the transmit frequency is calculated. Thus, a threshold can be set so that the transmit frequency is not changed as long as the calculated difference between the transmit signal and the received signal frequency is below the set threshold. If the difference between the transmit signal and the received signal frequency exceeds the set threshold, the transmit frequency is re-adjusted to match the last detected sensor resonant frequency.

[0059]

[0051] In order to implement dynamic transmit signal frequency adjustment, the signal generating circuit must be capable of generating a signal of variable frequency as described above in connection with frequency sweeping (see paragraph

[0018] ). As illustrated in the block diagram of FIG. 2, system 14 has a feedback loop that enables the system to detect the resonant frequency of the sensor (e.g., using the zoom FFT described in paragraph

[0025] ) and reconfigure the frequency of the DDS of the transmit circuit to match the detected sensor frequency.

[0060] 8 and 9 show examples where the transmission frequency is fixed and where the transmission frequency is dynamically adjusted to approximate the resonant frequency of the RC-WVM sensor, respectively. By adjusting the transmission frequency, the system tends to operate closer to the maximum transmission efficiency (defined above), which results in the maximum signal amplitude, and thus improves the reliability of the response signal amplitude induced by the RC-WVM sensor to be used as a predictor of the sensor cross-section.

[0061]

[0053] The transmit signal frequency update threshold can be defined as a trade-off between the bandwidth of the transmit excitation signal and the expected range of the sensor resonant frequency change due to, for example, the occlusion of the inferior vena cava due to respiration. In one example, such a predetermined threshold can be set as a specific value of the difference between the sensor resonant frequency and the excitation signal transmit frequency, for example a difference of about 25 kHz or more. In another example, the predetermined threshold can be set based on a minimum transmit efficiency function, for example a transmit efficiency function of 0.7 or less. Following this approach, optimal or near-optimal excitation can be achieved while minimizing the number of transmit frequency changes and maintaining quasi-fixed frequency operation.

[0062]

[0054] Further features, advantages and limitations of the embodiments disclosed herein are described in the following numbered subparagraphs. 1. A method and system for validating a sensor signal received from a resonant circuit based sensor, the method and system enabling validation of raw data received from the sensor by including a known fixed frequency and amplitude partial signal in an output signal captured from the sensor, said validation optionally being able to be performed offline. 2. A method and system for determining an optimal transmit frequency for exciting a resonant circuit sensor, comprising: outputting a plurality of predetermined transmit pulses to excite the sensor over a range of expected sensor frequencies; and determining a maximum amplitude received sensor signal as corresponding to the optimal excitation frequency; A method and system that determines an optimal transmission frequency for a duration of a signal measurement, which may optionally be about 60 seconds. 3. A method and system for characterizing a dimensionally correlated output signal of a sensor, comprising: determining dimensional vs. frequency data for the sensor during manufacture of the sensor; creating a characterization curve or batch specific dimensional-frequency data for the sensor by curve fitting or interpolation before or after sterilization of one or more corresponding sensors; taking measurements on the sensor; converting the sensor results to desired dimensions using the created characterization curve; minimizing dimensional measurement errors resulting from manufacturing variations by using the sensor or batch specific characterization curve; and optionally enabling accurate measurements over a wide range of dimensions by using the predetermined characterization curve. 4. A method and system for assessing electromagnetic background noise in a sensor system, comprising: operating the sensing system in a normal mode, e.g., with a transmitter connected, transmitting a test frequency, the test frequency being far enough from the expected sensor bandwidth so as not to power the sensor or elicit a sensor response; switching the sensor to a receiver mode and recording a received signal at the sensing system, the received signal consisting of background electromagnetic noise; assessing the power of the maximum component of this background noise signal; optionally repeating this process a defined number of times to obtain an average value; and defining the calculated signal level as the background noise. 5. A method of controlling a wireless resonant circuit sensor, the sensor including a variable inductance coil that changes resonant frequency in response to changes in a monitored physical parameter and that, when energized, generates a ringback signal at a frequency that correlates with the physical parameter. The method includes outputting at least one excitation frequency sweep including a predetermined number of transmit pulses at a predetermined frequency over a range of expected implant resonant frequencies, receiving a ringback signal for each of the sequentially output transmit pulses, transmitting at least one initial transmit pulse over a predetermined initial period, where the at least one initial transmit pulse includes a pulse frequency corresponding to a maximum amplitude ringback signal received from the at least one frequency sweep or one of a plurality of excitation frequency sweeps, receiving a plurality of test ringback signals in response to the at least one initial transmit pulse transmitted over the initial period, identifying the initial ringback signal corresponding to a preferred excitation pulse frequency, selecting the preferred excitation pulse frequency as a measurement transmit pulse frequency, and outputting a measurement transmit pulse at the measurement transmit pulse frequency for a subsequent measurement period. 6. A control system for a wireless resonant circuit sensor, the sensor including a variable inductance coil that changes its resonant frequency in response to changes in a monitored physical parameter and that, when energized, generates a ringback signal at a frequency that correlates with the physical parameter. The control system includes a transmit / receive switch configured to control signal transmission to and reception from an antenna, a signal generation module configured to generate an excitation signal (the transmit / receive switch controls transmission of the generated signal to the antenna), and a receive amplifier module configured to receive and process the ringback signal received by the antenna and communicated to the receive amplifier module by the transmit / receive switch in communication with a processor configured to execute program instructions. The system is configured to: output at least one excitation frequency sweep including a preset number of transmit pulses at predefined frequencies over a range of expected implant resonant frequencies; receive a ringback signal for each of the sequentially output transmit pulses; transmit at least one initial transmit pulse during a predetermined initial period, where the at least one initial transmit pulse includes a pulse frequency corresponding to a maximum amplitude ringback signal received from the at least one frequency sweep or one of a plurality of excitation frequency sweeps; receive a plurality of test ringback signals in response to the at least one initial transmit pulse transmitted during the initial period; identify an initial ringback signal corresponding to a preferred excitation pulse frequency; select the preferred excitation pulse frequency as a measurement transmit pulse frequency; and output a measurement transmit pulse at the measurement transmit pulse frequency during a subsequent measurement period. 7. A method for characterizing a resonant circuit sensor and correlating the sensor output to a measured physical parameter, the sensor comprising a variable inductor that, when energized, changes its resonant frequency in response to changes in the physical parameter by generating a ringback signal at a frequency correlable to the physical parameter. The method includes: determining a physical parameter value for at least one sensor prior to placement on a patient, comparing the data of the physical parameter value and frequency over a range of parameter values ​​and frequencies; and creating a characterization curve for the at least one sensor by plotting a curve with the data using curve fitting or interpolation techniques. 8. A method of evaluating electromagnetic background noise prior to outputting an excitation signal for making a measurement with a resonant circuit sensor, the sensor comprising a variable inductance coil that, when energized, changes its resonant frequency in response to changes in a physical parameter by generating a ringback signal at a frequency correlable to the physical parameter. The method includes transmitting a predetermined test pulse at a test frequency, the test frequency being selected to be sufficiently far from an expected sensor excitation frequency so as not to power the sensor; receiving the test signal at a sensor ringback signal receiver, the received test signal being comprised of the test pulse and background electromagnetic noise; defining the background electromagnetic noise as a signal component different from the known test pulse based on the received test signal; and modulating signal processing of the received measurement ringback signal to eliminate or reduce the effect of the defined background electromagnetic noise. 9. A method of validating a sensor signal of a resonant circuit sensor, the sensor comprising a variable inductance coil that, when excited, changes its resonant frequency in response to changes in a physical parameter by generating a ringback signal at a frequency correlated to the physical parameter. The method includes transmitting a known fixed frequency and fixed amplitude signal; capturing a known signal as part of a captured signal that includes the ringback signal generated by the sensor; comparing the captured known signal portion to a transmitted known signal; and validating the sensor's ringback signal if the captured known signal portion matches the transmitted known signal within a predetermined range.

[0063]

[0055] The above is a detailed description of an exemplary embodiment of the present disclosure. In this specification and the appended claims, conjunctions such as "at least one of X, Y, and Z" and "one or more of X, Y, and Z" mean that each item in the connected list can be present in any number of times except for all other items in the list, or in any number of times in combination with any or all of the other items in the connected list, unless otherwise stated or indicated, and each item can also be present in any number of times. Applying this general rule, the conjunctions in the above example, where the connected list is composed of X, Y, and Z, respectively, include one or more of X, one or more of Y, one or more of Z, one or more of X and one or more of Z, and one or more of X, one or more of Y, and one or more of Z.

[0064]

[0056] Various modifications and additions can be made without departing from the spirit and scope of the present disclosure. The features of each of the various embodiments described above can be combined with the features of other embodiments as necessary to provide various combinations of features in related new embodiments. Moreover, although a number of separate embodiments have been described above, what has been described here is merely illustrative of the application of the principles of the present disclosure. Furthermore, although certain methods herein have been illustrated and / or described as being performed in a particular order, the order can be varied widely within the scope of ordinary skill in order to achieve the aspects of the present disclosure. Therefore, this description should be interpreted as an example only, and not as limiting the scope of the present invention.

[0065]

[0057] While exemplary embodiments have been disclosed above and illustrated in the accompanying drawings, it will be understood by those skilled in the art that various modifications, omissions, and additions can be made to what is specifically disclosed herein without departing from the spirit and scope of the present invention.

Claims

1. 1. A method for controlling a wireless resonant circuit sensor, comprising: the sensor includes a variable inductance coil that changes its resonant frequency in response to changes in a monitored physical parameter and that, when energized, generates a ringback signal having a signal amplitude that correlates with the physical parameter; The method comprises: outputting a selected excitation signal to generate a ringback signal from the sensor; receiving a ringback signal from the sensor with a receiving amplifier; Comparing the magnitude of the sensor ringback signal to the dynamic range of the receiving amplifier; and reducing the receive amplifier gain if the compared magnitude is equal to or exceeds the dynamic range of the receive amplifier.

2. The method of claim 1 , wherein reducing the receive amplifier gain comprises reducing the gain to within a linear range of the receive amplifier.

3. 3. The method of claim 1 or claim 2, wherein decreasing the receive amplifier gain comprises decreasing the gain when a ringback signal increases in magnitude and reaches a predetermined magnitude threshold.

4. The receiving amplifier includes an amplifier circuit including an analog-to-digital converter (ADC); a receiver gain control function implemented to reduce a receive amplifier gain when a peak value of an amplified response signal from the sensor reaches a count corresponding to a predetermined percentage of a maximum ADC count; The method according to any one of claims 1 to 3.

5. The method according to any one of claims 1 to 4, further comprising adjusting a receive amplifier gain in response to the detected sensor resonant frequency based on a predetermined map of sensor frequency and gain.

6. adjusting the received ringback signal amplitude according to a transmission efficiency function to provide an adjusted ringback signal amplitude; comparing the magnitude of the adjusted ringback signal to a physical parameter-magnitude correlation and determining a value of the physical parameter based on the correlation; The method of any one of claims 1 to 5, further comprising:

7. The transmission efficiency function is It is calculated by Here, f ｒｘ is the resonant frequency of the sensor, and f ｔｘ is the transmission frequency of the energizing signal, The method according to claim 6.

8. The method of claim 6 , wherein the transmit efficiency function is determined based on an empirically derived transmit frequency efficiency curve.

9. determining physical parameters and size data of at least one of said sensors prior to placement on a patient; generating, through curve fitting or interpolation, a magnitude versus physical parameter characteristic curve for at least one sensor based on said physical parameter versus magnitude data; Taking a measurement with a sensor; and converting the sensor measurements into values ​​of the physical parameters using said characteristic curve; The method of any one of claims 1 to 8, further comprising:

10. The method of claim 9 , wherein the at least one sensor comprises a sensor batch, and the magnitude data comprises batch-specific parameter versus magnitude data.

11. 11. The method of claim 9 or claim 10, further comprising minimizing physical parameter measurement errors resulting from sensor manufacturing variability through the use of sensor or sensor batch specific characteristic curves.

12. 10. The method of claim 1, wherein the resonant circuit sensor is configured to be placed in a blood vessel of a patient, and the physical parameter is a dimension of the blood vessel.

13. The method of claim 12 , wherein the sensor is specially configured for placement in a vena cava and the blood vessel dimension is an area of ​​the vena cava.

14. 14. The method of claim 13, further comprising correlating the measured area of ​​the vena cava with the patient's fluid status.

15. 1. A method for characterizing a resonant circuit sensor and correlating a sensor output to a measured physical parameter, comprising: the sensor includes a variable inductance coil that generates, when energized, a ringback signal having a signal amplitude that can be correlated to the physical parameter, thereby varying a resonant frequency in response to a change in the physical parameter; The method comprises: determining physical parameter value versus signal amplitude data over a range of parameter values ​​and signal amplitudes for at least one of said sensors prior to placement on a patient; and creating a signal amplitude characteristic curve for at least one sensor by plotting a curve including said signal amplitude data using curve fitting or interpolation techniques.

16. The physical parameters are the internal dimensions of the vessel lumen, including the area of ​​the vessel lumen; the sensor is implantable within a vascular lumen and is capable of expanding and contracting with the vascular lumen; said determining including sequentially placing a sensor in a series of increasingly larger or smaller tubes of known dimensions and recording the magnitude of the corresponding ringback signal when energized through each of the different sized tubes; The method of claim 15.

17. determining a data set of vessel dimensions and signal strength for each sensor in a batch of sensors during manufacturing; generating a characteristic curve from the size-dimension data of said batch of sensors by curve fitting or interpolation prior to sterilization of the sensors; 20. The method of claim 16, further comprising:

18. The ringback signal further comprises a frequency correlable with the physical parameter; The method comprises: determining physical parameter value versus frequency data over a range of parameter values ​​and frequencies for the at least one sensor prior to placement on a patient; creating a frequency response curve for the at least one sensor by plotting a curve with the frequency data using curve fitting or interpolation techniques; and correlating a sensor output of the at least one sensor with a measured parameter based on both signal amplitude and frequency characteristics; The method according to any one of claims 15 to 17, further comprising:

19. 1. A method for controlling a wireless resonant circuit sensor, comprising: the sensor includes a variable inductance coil that changes its resonant frequency in response to changes in a monitored physical parameter and that, when energized, produces a ringback signal at a frequency or magnitude that correlates with the physical parameter; The method comprises: outputting a sensor energization signal at an initial transmission frequency; receiving a ringback signal at a ringback frequency from the sensor in response to the sensor energization signal; determining a difference between a transmit frequency and a ringback frequency; periodically repeating the output, reception and determination while the difference between the transmission frequency and the ringback frequency is below a predetermined threshold, and when the difference meets or exceeds the predetermined threshold, changing the transmission frequency of the sensor energization signal to a new transmission frequency that matches the ringback frequency of the last received ringback signal; and periodically repeating said outputting at a new transmission frequency and then repeating said receiving and determining.

20. Outputting a sensor energization signal at the initial transmission frequency outputting at least one sensor energization signal frequency sweep comprising a predetermined number of transmit pulses at predetermined frequencies over a range of expected sensor resonant frequencies; receiving a ring-back signal for each of the sequentially output transmission pulses; transmitting at least one initial transmit pulse over a predetermined initial period, the at least one initial transmit pulse having a pulse frequency corresponding to a highest amplitude ringback signal received from at least one frequency sweep or one of a plurality of the energization signal frequency sweeps; receiving a plurality of test ringback signals in response to at least one initial transmit pulse transmitted over an initial period of time; identifying an initial ringback signal corresponding to a preferred energization signal pulse frequency; selecting the preferred energization signal pulse frequency as a measurement transmit pulse frequency; and outputting the sensor energization signal at an initial frequency as a measurement transmission pulse at a measurement transmission pulse frequency of a subsequent measurement period; 20. The method of claim 19

21. The method of claim 19 or 20, wherein the predetermined threshold is a numerical value.

22. 22. The method of claim 21, wherein the number is greater than or equal to 25 kHz.

23. 21. The method of claim 19 or 20, wherein the predetermined threshold is a transmission efficiency function.

24. 24. The method of claim 23, wherein the transmission efficiency function is less than or equal to 0.7.

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