The present invention relates generally to pressure transducers, and particularly to calibration of pressure transducers.
Sensory implants are used for monitoring physiological parameters of patients, such as for measuring blood pressure in a cardiac chamber. Various types of sensory implants and associated methods are known in the art. For example, U.S. Patent Application Publication 2007/0261496, whose disclosure is incorporated herein by reference, describes biological fluid device that comprises a pressure sensor. The pressure sensor comprises a compressible container, the compression of which is indicative of the pressure, and is capable of wireless communication.
U.S. Pat. No. 7,335,161, whose disclosure is incorporated herein by reference, describes an implantable cardiac device that is configured and programmed to collect blood pressure waveforms from one or more implantable pressure sensors. Techniques are described for extracting features and reducing noise in the pressure waveforms by averaging waveforms which are aligned with a detected cardiac cycle. Noise can also be reduced by gating and calibration functions performed in accordance with other sensor data.
U.S. Pat. No. 5,942,692, whose disclosure is incorporated herein by reference, describes a capacitive pressure sensor that includes a chamber coupled to a region whose pressure is to be determined. The sensor includes a conductive flexible diaphragm and a pair of electrodes, each defining a capacitance with the diaphragm. Variations in pressure in the chamber cause deflection of the diaphragm which in turn causes variation in the capacitances. A processing circuit applies an excitation signal to the capacitances and couples the capacitances to inductive elements. A current through the inductive elements is detected to determine the difference in the sensor capacitances and, therefore, the deflection of the diaphragm and the pressure in the chamber.
U.S. Patent Application Publication 2007/0142727, whose disclosure is incorporated herein by reference, describes a cardiovascular pressure data analyzing system having one or more implanted pressure sensors, an implanted communication device in wireless communication with the sensor and an external data processing unit adapted to use real-time barometric data to calibrate un-calibrated pressure data received from the communication device. The external data processing unit can be portable, is in communication with a remote database to transfer the calibrated pressure data to the remote database, and is capable of providing reprogramming information to the communication device. A method for analyzing pressure data includes gathering pressure data from an implanted pressure sensor in a human body, retrieving the pressure data through a communication device implanted in the human body, transmitting pressure data from the communication device to an external data processing unit, and calibrating the pressure data at the external processing unit to compensate for inherent characteristics of the sensor.
U.S. Patent Application Publication 2011/0160560, whose disclosure is incorporated herein by reference, describes an implantable pressure sensor system having a sensor assembly configured and adapted to measure pressure in a volume. The sensor assembly includes at least a first MEMS pressure sensor, an application-specific integrated circuit (ASIC) having memory means, temperature compensation system, drift compensation system, and power supply means for powering the sensor assembly. The first MEMS pressure sensor has a pressure sensing element that is responsive to exposed pressure, the pressure sensing element being adapted to generate a pressure sensor signal representative of the exposed pressure. The temperature compensation system is adapted to correct for temperature induced variations in the pressure sensor signal, and the drift compensation system is adapted to correct for pressure and temperature induced pressure sensor signal drift.
An embodiment of the present invention that is described herein provides a method including, in a living organ in which an ambient pressure varies as a function of time, sensing the ambient pressure using a pressure sensor, which has a capacitance that varies in response to the ambient pressure, so as to produce a time-varying waveform. A calibration voltage, which modifies the capacitance and thus the time-varying waveform, is applied to the pressure sensor. The time-varying waveform is processed so as to isolate and measure a contribution of the calibration voltage to the waveform. A dependence of the capacitance on the ambient pressure is calibrated using the measured contribution of the calibration voltage.
In some embodiments, applying the calibration voltage includes automatically identifying one or more time intervals in which the waveform meets a predefined criterion, and applying the calibration voltage during the identified time intervals. In some embodiments, the ambient pressure oscillates as a function of time in accordance with a periodic cycle, and applying the calibration voltage includes activating the calibration voltage at a predefined phase of the cycle. Applying the calibration voltage may include activating the calibration voltage during a portion of the periodic cycle in which the waveform varies by less than a predefined variation. Additionally or alternatively, applying the calibration voltage may include activating the calibration voltage at the phase of the cycle in which the waveform has a predefined value.
In an embodiment, processing the waveform includes analyzing the waveform so as to automatically identify one or more times at which the calibration voltage is applied, and measuring the contribution of the calibration voltage at the automatically-identified times. In another embodiment, applying the calibration voltage includes activating the calibration voltage at one or more predefined times, and processing the waveform includes measuring the contribution by synchronizing to the predefined times.
In another embodiment, processing the waveform includes identifying one or more first times at which the calibration voltage is applied, identifying one or more second times at which the calibration voltage is not applied, and measuring the contribution of the calibration voltage by comparing the waveform at the first times to the waveform at the second times. In yet another embodiment, applying the calibration voltage includes applying at least two different calibration voltage levels. In still another embodiment, processing the waveform includes determining a level of the calibration voltage that causes the capacitance to reach a given capacitance value. In another embodiment, processing the waveform includes determining a level of the calibration voltage that triggers a discrete event related to electrodes of the pressure sensor.
There is additionally provided, in accordance with an embodiment of the present invention, a method including, in a living organ in which an ambient pressure varies as a function of time, sensing the ambient pressure using a pressure sensor, which has a capacitance that varies in response to the ambient pressure. An oscillator circuit, which is coupled to the pressure sensor, is operated such that an output of the oscillator circuit depends on the capacitance and thus varies depending on the ambient pressure. An operating point of the oscillator circuit is modified, so as to apply to the pressure sensor a calibration voltage that modifies the capacitance. A change in the output of the oscillator circuit, caused by the calibration voltage, is sensed. A dependence of the capacitance on the ambient pressure is calibrated using the sensed change.
In some embodiments, modifying the operating point includes modifying a supply voltage of the oscillator circuit. In some embodiments, operating the oscillator circuit includes adjusting a frequency of the output of the oscillator circuit as a function of the capacitance. In an embodiment, operating the oscillator circuit includes operating a Schmidt trigger that is connected in a feedback loop including the pressure sensor. In a disclosed embodiment, operating the oscillator circuit includes switching the oscillator circuit between the pressure sensor and a reference capacitance, and calibrating the dependence includes comparing first and second outputs of the oscillator circuit when connected to the pressure sensor and to the reference capacitance, respectively.
There is additionally provided, in accordance with an embodiment of the present invention, apparatus including a pressure sensor and calibration circuitry. The pressure sensor is configured to be fitted in a living organ in which an ambient pressure varies as a function of time, and to sense the ambient pressure using a capacitance that varies in response to the ambient pressure, so as to produce a time-varying waveform. The calibration circuitry is configured to apply to the pressure sensor a calibration voltage that modifies the capacitance and thus the time-varying waveform, to process the time-varying waveform so as to isolate and measure a contribution of the calibration voltage to the waveform, and to calibrate a dependence of the capacitance on the ambient pressure using the measured contribution of the calibration voltage.
There is further provided, in accordance with an embodiment of the present invention, apparatus including a pressure sensor, an oscillator circuit and calibration circuitry. The pressure sensor is configured to be fitted in a living organ in which an ambient pressure varies as a function of time, and to sense the ambient pressure using a capacitance that varies in response to the ambient pressure. The oscillator circuit is coupled to the pressure sensor and is configured to oscillate such that an output of the oscillator circuit depends on the capacitance and thus varies depending on the ambient pressure. The calibration circuitry is configured to modify an operating point of the oscillator circuit so as to apply to the pressure sensor a calibration voltage that modifies the capacitance, to sense a change in the output of the oscillator circuit caused by the calibration voltage, and to calibrate a dependence of the capacitance on the ambient pressure using the sensed change.
The present invention will be more fully understood from the following detailed description of the embodiments thereof, taken together with the drawings in which:
Embodiments of the present invention that are described herein provide improved methods and systems for calibrating capacitance-based pressure sensors. The embodiments described herein refer mainly to measurement of blood pressure in the heart using a cardiac implant, but the disclosed techniques can be used in various other applications, as well.
The capacitance-based pressure sensor has a certain pressure-capacitance dependence, which is used for deriving the pressure from the sensor capacitance. In practice, however, the pressure-capacitance dependence of the sensor may drift considerably over time, for example due to aging of sensor elements or tissue build-up on or around the sensor. Unless calibrated and compensated for, this drift may distort the pressure estimation considerably.
The calibration task is further complicated by the fact that the measured ambient pressure is noisy and varies periodically in accordance with the patient's cardiac cycle. Thus, readout of the pressure sensor produces a noisy, time-varying waveform. The disclosed techniques calibrate the pressure-capacitance dependence of the sensor using this waveform.
In some embodiments, the implant comprises calibration circuitry that applies a calibration voltage to the pressure sensor. The calibration voltage modifies the sensor capacitance, which in turn modifies the time-varying waveform. In other words, the time-varying waveform is affected by two factors—The ambient pressure and the calibration voltage. The calibration circuitry processes the time-varying waveform so as to measure the contribution of the calibration voltage and isolate this contribution from other factors. The measured contribution of the calibration voltage is then used for calibrating the pressure-capacitance dependence of the sensor.
Several example calibration circuitry configurations are described herein. In some embodiments, the calibration voltage is applied directly to the pressure sensor electrodes. In other embodiments, the pressure sensor is coupled to an oscillator circuit, and the calibration is used to modify the operating point of the oscillator circuit, and thus indirectly modify the sensor capacitance.
Several example techniques for isolating and measuring the contribution of the calibration voltage to the time-varying waveform are described. Some of these techniques involve synchronizing to the periodic cardiac cycle and choosing suitable time intervals for applying the calibration voltage.
The disclosed techniques provide highly accurate compensation for drift in the pressure-capacitance dependence of capacitance-based pressure sensors. These techniques are particularly designed for environments in which the ambient pressure in noisy and time-varying, although they are suitable for static environments as well. The methods and systems described herein operate in real time and are entirely non-invasive. As such, they enable the pressure sensor to remain operative for years without performance degradation.
Implant 24 measures the time-varying ambient blood pressure in the Left Atrium (LA) of heart 28, and transmits a corresponding time-varying waveform to external unit 32. The external unit estimates the blood pressure based on the waveform received from implant 24 and outputs the estimated blood pressure to a user, e.g., a physician or the patient himself. In some embodiments the external unit also supplies electrical power to the implant, e.g., using inductive coupling.
In the embodiment of
Implant 24 comprises a control unit 40 that controls and reads pressure sensor 36. Among other tasks, unit 40 produces a time-varying waveform that is indicative of the time-varying capacitance of sensor 36, and thus the time-varying pressure. Implant 24 further comprises a transmission unit 44 that transmits the time-varying waveform via an antenna 48 to external unit 32 for subsequent processing. In an example embodiment, unit 44 transmits a square wave whose frequency is proportional to the amplitude of the waveform (and thus to the measured pressure).
External unit 32 receives the time-varying waveform from implant 24 using an antenna 52 and a receiver 56. A processor 60 then processes the received waveform so as to estimate the actual blood pressure sensed by sensor 36. The estimated blood pressure is provided as output to a user using a suitable interface.
In some embodiments, unit 40 in conjunction with external unit 32 carries out a calibration process that compensates for drift effects in the pressure-capacitance dependence of sensor 36. This calibration process, and several example configurations of unit 40 that support such calibration, are described in detail below.
The configurations of implant 24 and external unit 32 shown in
The disclosed calibration techniques can be carried out by control unit 40 in implant 24, by processor 60 in external unit 32, or by both. In the context of the present patent application and in the claims, the elements of unit 40 and/or processor 60 that carry out calibration tasks are referred to collectively as “calibration circuitry.” Elements of the implant and/or the external unit that are not necessary for understanding of the disclosed techniques have been omitted from the figures for the sake of clarity.
The various elements of implant 24 and external unit 32 can be implemented using hardware, such as using an Application Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA), using software, or using a combination of hardware and software elements. In some embodiments, elements of implant 24 and/or external unit 32 are implemented using a general-purpose processor, which is programmed in software to carry out the functions described herein. The software may be downloaded to the processor in electronic form, over a network, for example, or it may, alternatively or additionally, be provided and/or stored on non-transitory tangible media, such as magnetic, optical, or electronic memory.
System 20 measures the ambient blood pressure in heart 28 by assessing the capacitance of sensor 36. The underlying assumption is that the capacitance varies as a function of the pressure in accordance with some known dependence, which is then used for deriving the pressure from the measured capacitance.
In practice, however, the dependence of the sensor capacitance on the ambient pressure drifts over time. For example, the dependence may follow a certain function immediately after a new implant 24 is implanted in heart 28, but drift to follow a different function several months later. This drift may be caused, for example, by a change in the mass or stiffness of the sensor membrane, by growth or deposition of biological tissue on the sensor or in its vicinity, or by various other mechanisms.
The problem of calibrating the drift is further complicated by the fact that the measured pressure is not constant, but rather noisy and time-varying in accordance with the patient's cardiac cycle.
In some embodiments, the calibration circuitry in system 20 calibrates the drift in the pressure-capacitance dependence by applying a calibration voltage to sensor 36. The applied calibration voltage causes additional deflection of the sensor's membrane. The total deflection of the membrane is thus affected by two factors—The ambient blood pressure, and the calibration voltage.
Put in another way (since capacitance depends on membrane deflection), readout of sensor 36 produces a time-varying waveform that depends on two factors—The ambient blood pressure, and the calibration voltage. Typically, the calibration circuitry processes the waveform so as to distinguish between the two factors, i.e., to isolate the contribution of the calibration voltage to the time-varying waveform. The calibration circuitry then uses the isolated contribution of the calibration voltage to calibrate the drift in pressure-capacitance dependence of sensor 36.
In this example, the implant further comprises a reference capacitance-based sensor 94 and two fixed capacitors 98, all serving as reference capacitances. Reference sensor 94 is typically similar to sensor 90. Unlike sensor 90, however, sensor 94 is not exposed to the blood, and can therefore be used for obtaining reference measurements. Capacitors 98 typically have different known values within the capacitance range of sensor 90. A logic unit 110 in control unit 40 selects between the outputs of the four capacitors using a selector switch 102.
In an embodiment, unit 40 comprises a capacitance-to-frequency converter 106, which produces a waveform whose frequency is indicative of the capacitance of the selected capacitor. In the present example, converter 106 produces a square-wave clock signal (denoted “sensor clock out” in the figure) whose frequency is around 10 MHz. The exact frequency of the clock signal depends on the measured capacitance. The waveform is provided to logic unit 110. Subsequent processing of the signal (e.g., transmission to external unit 32 and calibration using the signal) are not shown in this figure for the sake of clarity.
Unit 40 comprises an operation voltage module 114, which applies an appropriate calibration voltage to one of the electrodes of the pressure sensor (sensor 90 or 94). In the present example, unit 110 selects the calibration voltage with a resolution of two or three bits, by controlling module 114 using suitable control signals. Module 114 generates the desired voltage levels from the main supply voltage of unit 40.
The scheme of
As explained above, the capacitance of the pressure sensor depends on (1) the ambient pressure and (2) the calibration voltage. The ambient pressure is typically both time-varying and noisy. In order to perform accurate drift compensation, system 20 processes the noisy, time-varying waveform produced from the pressure sensor, and isolates the contribution of the calibration sensor from the other factors.
System 20 may isolate the contribution of the calibration voltage in various ways. In some embodiments, system 20 applies the calibration voltage only is selected time intervals that meet some predefined criterion. Such intervals are typically selected in a particular phase of the cardiac cycle. For example, the system may activate the calibration voltage only in phases of the cardiac cycle in which the waveform amplitude varies by less than a predefined variation. In such intervals it is simpler to measure the contribution of the calibration voltage than in rapidly-varying portions of the cardiac cycle.
A curve 120 shows the waveform amplitude without applying any calibration voltage. A curve 130 shows the waveform amplitude when a calibration voltage is applied between times 140 and 150 (i.e., activated at time 140 and deactivated at time 150). As can be seen in the figure, during slowly-varying intervals of the cardiac cycle, such as an interval 154, it is relatively simple to measure the contribution of the calibration voltage to the waveform amplitude, whereas in rapidly-varying intervals this task is more complicated and less accurate.
In an example embodiment, system 20 measures the contribution of the calibration voltage by comparing one or more time intervals in which the calibration voltage is applied to corresponding intervals in which the calibration voltage is not applied. In the example of
In some embodiments, system 20 averages the above-described measurement over multiple cardiac cycles, in order to reduce the effect of noise and generally improve the measurement accuracy. In some embodiments, system 20 identifies automatically the intervals in which the calibration voltage is applied and the intervals in which the calibration voltage is not applied, in order to perform the above-described comparison.
In some embodiments, system 20 automatically synchronizes to the patient's cardiac cycle and identifies the time intervals that meet the desired criterion (e.g., intervals of slowly-varying waveform). System 20 then applies the calibration voltage in at least some of these intervals (while potentially leaving some of the intervals free of calibration voltage for comparison), and calculates the isolated contribution of the calibration voltage from the waveform amplitude in the intervals.
In alternative embodiments, system 20 activates the calibration voltage at the phase of the cardiac cycle in which the waveform has a predefined value. This technique is another possibility for synchronizing to the timing of the cardiac cycle and applying the calibration voltage at a desired phase of the cycle.
In another embodiment, system 20 applies multiple calibration voltages. This sort of calibration may enable highly accurate isolation of the contribution of the calibration voltage to the waveform amplitude. The system may apply the calibration voltage or voltages without necessarily synchronizing to the cardiac cycle. For example, the system may apply multiple voltages at specific times that are not correlated to the ambient pressure or to the cardiac cycle. In an example embodiment, a first voltage is applied three seconds after starting operation, a second voltage is applied six seconds after starting operation, and a third voltage is applied eight seconds after starting operation. In such a scheme, each calibration voltage will typically be applied over several cardiac cycles.
In other embodiments, system 20 identifies the calibration voltage value that is needed in order to set a predefined capacitance value. In some embodiments, system 20 applies a gradually-increasing calibration voltage, and finds the calibration voltage value that causes some discrete detectable event relating to the electrodes of the pressure sensor. For example, system 20 may find the calibration voltage value that corresponds to the “touch point”—The voltage that causes the sensor electrodes to make physical contact with each other.
As another example, system 20 may find the calibration voltage value that corresponds to the “pull-in” point. Pull-in is an effect in which the sensor membrane collapses toward the other electrode. This discrete event can be detected, for example, by detecting both a certain voltage-capacitance relation and a rapid change in current. Upon detecting such an event, system 20 is able to deduce the contribution of the calibration voltage, for example by comparing the measurement to baseline measurements taken at known conditions. Further alternatively, system 20 may identify any other suitable discrete event that is caused by some threshold calibration voltage.
Typically, the calibration process is performed jointly by control unit 40 in implant 24 and by processor 60 in external unit 32. In an example embodiment, the criteria and timing for applying the calibration voltage are determined and carried out internally in implant 24, and the direction of communication between implant 24 and external unit 32 is unidirectional (from the implant to the external unit). In other embodiments, the communication between the implant and the external unit may be bidirectional. In some embodiments, control unit 40 and processor 60 are synchronized with one another as to the times at which the calibration voltage is applied. The schemes described above are chosen purely by way of example. Alternatively, system 20 may isolate the contribution of the calibration voltage to the amplitude of the time-varying waveform in any other suitable way.
In the scheme of
Consider, for example, capacitance-to-frequency converter 106 of
In the present example, the oscillator circuit comprises a Schmidt trigger 184 that is connected in a feedback loop that comprises a resistor 180A. The output of Schmidt trigger 184 (denoted “OUT” in the figure) comprises a square wave whose frequency depends on the capacitance of sensor 174.
In some embodiments, unit 40 applies the calibration voltage as the supply voltage (denoted “V”) of Schmidt trigger 184. Changing the supply voltage V causes a respective change in the voltage falling on sensor 74 (denoted “Vc”), and thus changes the sensor capacitance.
In the present example, converter 170 comprises a fixed capacitor 178 and a resistor 180B, used as reference. Selection between pressure sensor 174 and capacitor 178 is performed using a switch 182. In some embodiments, the system calibrates the capacitance-pressure dependence of sensor 174 by comparing the respective outputs of converter 170 when connected to pressure sensor 174 and when connected to capacitor 178.
As can be seen in the figure, increasing the calibration voltage causes a reduction in the oscillation frequency, and vice versa. Since the oscillation frequency is relatively high (e.g., on the order of 10 MHz), the capacitance of sensor 174 is responsive to the average value of Vc (marked with dashed lines) and not to the instantaneous oscillating value.
Thus, the frequency of the output of converter 170 depends on two factors—The capacitance of sensor 174 and the calibration voltage. Thus, the equivalent effect of the calibration voltage is achieved by using the calibration voltage to modify the capacitance-frequency dependence of converter 170.
In the scheme of
System 20 processes the resulting time-varying waveform, at an analysis step 212. In particular, system 20 isolates the contribution of the calibration voltage to the waveform from other factors. Using the isolated contribution of the calibration voltage, system 20 calibrates the pressure-capacitance dependence of the sensor, at a calibration step 216.
Although the embodiments described herein mainly address measurement of ambient blood pressure in the LA, the methods and systems described herein can also be used in other applications, such as in other cardiac chambers or in other body organs.
For example, the disclosed techniques can be used for measuring blood pressure in the Aorta, renal artery, femoral artery or radial artery, e.g., for better management of hypertension patients. As another example, the disclosed techniques can be used for measuring pulmonary artery pressure for better management of heart failure patients. As yet another example, the disclosed techniques can be used for intracranial pressure (ICP) monitoring which can aid in the management of neurological disorders such as hydrocephalus, head trauma, tumors, colloid cysts and cerebral hematomas.
In another example embodiment, the disclosed techniques can be used for bladder pressure monitoring, e.g., as a diagnostic tool for urology. The disclosed techniques may also be used for intraocular pressure (IOP) monitoring for better treatment of glaucoma. Moreover, intra-cardiac pressure monitoring using the disclosed techniques can also be used as a complementary technology for ventricular assist devices (VAD) and CRT optimization.
Alternatively to measuring blood pressure, the disclosed techniques can be used in measurements of pressure in other liquids, in gases or in solids. Although the embodiments described herein refer mainly to an implanted device that operates in conjunction with an external unit, the disclosed techniques can be used in pressure sensors coupled to other kinds of medical devices, such as catheters or other probes.
It will thus be appreciated that the embodiments described above are cited by way of example, and that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and sub-combinations of the various features described hereinabove, as well as variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not disclosed in the prior art. Documents incorporated by reference in the present patent application are to be considered an integral part of the application except that to the extent any terms are defined in these incorporated documents in a manner that conflicts with the definitions made explicitly or implicitly in the present specification, only the definitions in the present specification should be considered.
This application claims the benefit of U.S. Provisional Patent Application 61/726,022, filed Nov. 14, 2012, whose disclosure is incorporated herein by reference.
Filing Document | Filing Date | Country | Kind |
---|---|---|---|
PCT/IB2013/060038 | 11/10/2013 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
---|---|---|---|
WO2014/076620 | 5/22/2014 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
3264861 | Miles | Aug 1966 | A |
4127110 | Bullara | Nov 1978 | A |
4206761 | Cosman | Jun 1980 | A |
4237900 | Ritchie et al. | Dec 1980 | A |
4256094 | Kapp et al. | Mar 1981 | A |
4377851 | McNamara | Mar 1983 | A |
4432372 | Monroe | Feb 1984 | A |
4519401 | Ko et al. | May 1985 | A |
4743836 | Grzybowski et al. | May 1988 | A |
4791934 | Brunnett | Dec 1988 | A |
4881939 | Newman | Nov 1989 | A |
5105190 | Kip et al. | Apr 1992 | A |
5113868 | Wise et al. | May 1992 | A |
5480412 | Mouchawar et al. | Jan 1996 | A |
5493470 | Zavracky et al. | Feb 1996 | A |
5514171 | Hoegnelid et al. | May 1996 | A |
5549646 | Katz | Aug 1996 | A |
5564434 | Halperin | Oct 1996 | A |
5942692 | Haase et al. | Aug 1999 | A |
6015386 | Kensey et al. | Jan 2000 | A |
6025725 | Gershenfeld et al. | Feb 2000 | A |
6051853 | Shimada et al. | Apr 2000 | A |
6111520 | Allen et al. | Aug 2000 | A |
6113553 | Chubbuck | Sep 2000 | A |
6171252 | Roberts | Jan 2001 | B1 |
6275681 | Vega et al. | Aug 2001 | B1 |
6309350 | VanTassel et al. | Oct 2001 | B1 |
6389371 | Tsuchiya et al. | May 2002 | B1 |
6409674 | Brockway et al. | Jun 2002 | B1 |
6622041 | Terry, Jr. et al. | Sep 2003 | B2 |
6667725 | Simons et al. | Dec 2003 | B1 |
6772070 | Gilmanshin et al. | Aug 2004 | B2 |
6778070 | Thomas | Aug 2004 | B1 |
6926670 | Rich et al. | Aug 2005 | B2 |
6936053 | Weiss | Aug 2005 | B1 |
7086270 | Weinberg et al. | Aug 2006 | B2 |
7149587 | Wardle et al. | Dec 2006 | B2 |
7216048 | Wang et al. | May 2007 | B2 |
7256695 | Hamel et al. | Aug 2007 | B2 |
7317951 | Schneider et al. | Jan 2008 | B2 |
7335161 | Von Arx et al. | Feb 2008 | B2 |
7413547 | Lichtscheidl et al. | Aug 2008 | B1 |
7425749 | Hartzell et al. | Sep 2008 | B2 |
7509169 | Eigler et al. | Mar 2009 | B2 |
7515971 | Doan | Apr 2009 | B1 |
7628054 | Hajishah et al. | Dec 2009 | B2 |
7634319 | Schneider et al. | Dec 2009 | B2 |
7635338 | Eide | Dec 2009 | B2 |
7647831 | Corcoran et al. | Jan 2010 | B2 |
7677107 | Nunez et al. | Mar 2010 | B2 |
7678123 | Chanduszko | Mar 2010 | B2 |
7684872 | Carney et al. | Mar 2010 | B2 |
7686768 | Bodecker et al. | Mar 2010 | B2 |
7762138 | Zdeblick et al. | Jul 2010 | B2 |
7860579 | Goetzinger et al. | Dec 2010 | B2 |
7899550 | Doan et al. | Mar 2011 | B1 |
8021307 | White et al. | Sep 2011 | B2 |
8118749 | White et al. | Feb 2012 | B2 |
8154389 | Rowland et al. | Apr 2012 | B2 |
8285204 | Martin | Oct 2012 | B2 |
8353841 | White et al. | Jan 2013 | B2 |
8355777 | White et al. | Jan 2013 | B2 |
8406358 | Uehara et al. | Mar 2013 | B1 |
8432265 | Rowland et al. | Apr 2013 | B2 |
8493187 | Rowland et al. | Jul 2013 | B2 |
8810405 | Stevenson et al. | Aug 2014 | B2 |
8894582 | Nunez et al. | Nov 2014 | B2 |
9513609 | Thueringer et al. | Dec 2016 | B2 |
9662066 | Ledet et al. | May 2017 | B2 |
9730764 | Van Der Weide et al. | Aug 2017 | B2 |
20010018596 | Selmon et al. | Aug 2001 | A1 |
20020045921 | Wolinsky et al. | Apr 2002 | A1 |
20020077556 | Schwartz | Jun 2002 | A1 |
20020120200 | Brockway et al. | Aug 2002 | A1 |
20030097073 | Bullister et al. | May 2003 | A1 |
20030139677 | Fonseca et al. | Jul 2003 | A1 |
20040103906 | Schulman et al. | Jun 2004 | A1 |
20040158167 | Smith | Aug 2004 | A1 |
20050004644 | Kelsch et al. | Jan 2005 | A1 |
20050065589 | Schneider et al. | Mar 2005 | A1 |
20050088184 | Burdick et al. | Apr 2005 | A1 |
20050288596 | Eigler et al. | Dec 2005 | A1 |
20060116572 | Case | Jun 2006 | A1 |
20060161364 | Wang | Jul 2006 | A1 |
20060206178 | Kim | Sep 2006 | A1 |
20060229488 | Ayre et al. | Oct 2006 | A1 |
20060287602 | O'Brien et al. | Dec 2006 | A1 |
20070049980 | Zielinski et al. | Mar 2007 | A1 |
20070049984 | Osypka | Mar 2007 | A1 |
20070118038 | Bodecker et al. | May 2007 | A1 |
20070135826 | Zaver et al. | Jun 2007 | A1 |
20070142727 | Zhang et al. | Jun 2007 | A1 |
20070179583 | Goetzinger et al. | Aug 2007 | A1 |
20070255144 | Tulkki et al. | Nov 2007 | A1 |
20070261496 | Jonsson et al. | Nov 2007 | A1 |
20070293779 | Bardy | Dec 2007 | A1 |
20080004673 | Rossing et al. | Jan 2008 | A1 |
20080033527 | Nunez et al. | Feb 2008 | A1 |
20080045242 | Dekock et al. | Feb 2008 | A1 |
20080064966 | Brockway et al. | Mar 2008 | A1 |
20080092663 | Corcoran et al. | Apr 2008 | A1 |
20080139959 | Miethke et al. | Jun 2008 | A1 |
20080154101 | Jain et al. | Jun 2008 | A1 |
20080227487 | Daniels et al. | Sep 2008 | A1 |
20080269573 | Najafi et al. | Oct 2008 | A1 |
20080281212 | Nunez et al. | Nov 2008 | A1 |
20090005859 | Keilman | Jan 2009 | A1 |
20090013791 | Zdeblick et al. | Jan 2009 | A1 |
20090024042 | Nunez et al. | Jan 2009 | A1 |
20090030291 | O'Brien et al. | Jan 2009 | A1 |
20090036754 | Pons et al. | Feb 2009 | A1 |
20090069648 | Irazogui et al. | Mar 2009 | A1 |
20090093729 | Zhang et al. | Apr 2009 | A1 |
20090192381 | Brockway et al. | Jul 2009 | A1 |
20090275924 | Lattanzio et al. | Nov 2009 | A1 |
20090281520 | Highley et al. | Nov 2009 | A1 |
20090299216 | Chen et al. | Dec 2009 | A1 |
20100179449 | Chow et al. | Jul 2010 | A1 |
20100179618 | Marnfeldt et al. | Jul 2010 | A1 |
20100249756 | Koh | Sep 2010 | A1 |
20100280330 | Samuelsson et al. | Nov 2010 | A1 |
20110021887 | Crivelli et al. | Jan 2011 | A1 |
20110040206 | Burger et al. | Feb 2011 | A1 |
20110043336 | Gueorguiev | Feb 2011 | A1 |
20110133894 | Hennig et al. | Jun 2011 | A1 |
20110160560 | Stone | Jun 2011 | A1 |
20110264217 | Qureshi | Oct 2011 | A1 |
20110303229 | Najafi et al. | Dec 2011 | A1 |
20120022507 | Najafi et al. | Jan 2012 | A1 |
20120319862 | Nagy et al. | Dec 2012 | A1 |
20130107913 | Savoj | May 2013 | A1 |
20130215979 | Yakovlev et al. | Aug 2013 | A1 |
20130222153 | Rowland et al. | Aug 2013 | A1 |
20130233086 | Besling et al. | Sep 2013 | A1 |
20140028467 | Nagy et al. | Jan 2014 | A1 |
20140062717 | Mudumbai et al. | Mar 2014 | A1 |
20140155710 | Rowland et al. | Jun 2014 | A1 |
20140306807 | Rowland et al. | Oct 2014 | A1 |
20150290465 | Mashiach | Oct 2015 | A1 |
20160058324 | Cao et al. | Mar 2016 | A1 |
20170018172 | He et al. | Jan 2017 | A1 |
20170118543 | Ha et al. | Apr 2017 | A1 |
20170155429 | Hung et al. | Jun 2017 | A1 |
Number | Date | Country |
---|---|---|
S5973747 | Apr 1984 | JP |
20040060577 | Jul 2004 | KR |
2006042280 | Apr 2006 | WO |
2008042229 | Apr 2008 | WO |
2008127525 | Oct 2008 | WO |
2009097485 | Aug 2009 | WO |
2011053246 | May 2011 | WO |
2012078861 | Jun 2012 | WO |
2012090206 | Jul 2012 | WO |
2014006471 | Jan 2014 | WO |
2014145012 | Sep 2014 | WO |
2014170771 | Oct 2014 | WO |
Entry |
---|
International Application # PCT/IB2015/060054 Search Report dated Mar. 21, 2016. |
Cleven et al., “A Novel Fully Implantable Wireless Sensor System for Monitoring Hypertension Patients”, IEEE Transactions on Biomedical Engineering vol. 59, No. 11, pp. 3124-3130, Nov. 2012. |
Jiang., “Design challenges of implantable pressure monitoring system”, Frontiers of Neuroscience, vol. 4, Art 29, pp. 1-4, Feb. 26, 2010. |
Simons et al., “Spiral chip implantable radiator and printed loop external receptor for RF telemetry in bio-sensor systems”, In Radian and Wireless Conference IEEE, 12 pages, 2004. |
Simons et al., “Wearable wireless telemetry system for implantable bio-Mems sensors”, In Engineering in Medicine and Biology Society Conference, IEEE, 12 pages, 2006. |
Maxim, “Approaches for Compensating Span and Offset in Pressure Sensors”, Application Note 743, 5 pages, Mar. 27, 2001. |
Coosemans., “An autonomous bladder pressure monitoring system”, Katholike Universiteit Leuven, Department ESAT-MICAS, Kasteelpark Arenberg, Belgium, Sensors and Actuators A: Physical, Elsevier BV, vol. 123-124, pp. 155-161, Sep. 23, 2005. |
Dai et al., “Capacitive Micro Pressure Sensor integrated with a Ring Oscillator Circuit on Chip”, Sensors 2009, vol. 9, Chapter 12, pp. 10158-10170, Jan. 1, 2009. |
European Application # 14785775.9 Search Report dated Oct. 24, 2016. |
JP Application # 2015-541286 Office Action dated Mar. 8, 2017. |
International Application # PCT/IB2013/060038 Search Report dated May 1, 2014. |
Yameogo et al., “Self Calibrating pressure sensor for biomedical applications”, IEEE Sensors Conference, pp. 691-694, Oct. 25-28, 2009. |
Goldshtein et al., U.S. Appl. No. 14/766,750, filed Aug. 9, 2015. |
International Application # PCT/IB2014/060085 Search Report dated Jul. 8, 2014. |
Olivo et al., “Electronic implants: Power delivery and management”, Integrated Systems Laboratory—EPFL, 6 pages, Mar. 22, 2013. |
Mandal et al., “Power-Efficient Impedance-Modulation Wireless Data Links for Biomedical Implants”, IEEE Transactions on Biomedical Circuits and Systems, vol. 2, No. 4, pp. 301-315, Dec. 4, 2008. |
Bradford et al., “Wireless Power and Data Transmission for a Pressure Sensing Medical Implant”, Proceedings BMT 2010, Rostock, Germany, 4 pages, Oct. 6-8, 2010. |
Zaie et al., “An Implantable Microsystem for Tonometric Blood Pressure Measurement”, Biomedical Microdevices, vol. 3, Issue 4, pp. 285-292, Dec. 2001. |
U.S. Appl. No. 14/766,750 office action dated Feb. 23, 2018. |
European Application # 13855953.9 office action dated Aug. 18, 2017. |
European Application # 13855953.9 search report dated May 30, 2016. |
Number | Date | Country | |
---|---|---|---|
20150282720 A1 | Oct 2015 | US |
Number | Date | Country | |
---|---|---|---|
61726022 | Nov 2012 | US |