Method and apparatus to measure bioelectric impedance of patient tissue

Abstract
A device to measure tissue impedance comprises drive circuitry coupled to calibration circuitry, such that a calibration signal from the calibration circuitry corresponds to the current delivered through the tissue. Measurement circuitry can be coupled to measurement electrodes and the calibration circuitry, such that the tissue impedance can be determined in response to the measured calibration signal from the calibration circuitry and the measured tissue impedance signal from the measurement electrodes. Processor circuitry comprising a tangible medium can be configured to determine a complex tissue impedance in response to the calibration signal and the tissue impedance signal. The processor can be configured to select a frequency for the drive current, and the amount of drive current at increased frequencies may exceed a safety threshold for the drive current at lower frequencies.
Description
BACKGROUND OF THE INVENTION

The present invention relates to patient monitoring. Although embodiments make specific reference to monitoring impedance and electrocardiogram signals with an adherent patch, the system methods and device described herein may be applicable to many applications in which physiological monitoring is used, for example physiological monitoring with implantable devices.


Patients are often treated for diseases and/or conditions associated with a compromised status of the patient, for example a compromised physiologic status. In some instances, a patient may report symptoms that require diagnosis to determine the underlying cause. For example, a patient may report fainting or dizziness that requires diagnosis, in which long term monitoring of the patient can provide useful information as to the physiologic status of the patient. In some instances a patient may have suffered a heart attack and require care and/or monitoring after release from the hospital. One example of a device to provide long term monitoring of a patient is the Holter monitor, or ambulatory electrocardiography device. In addition to measuring heart signals with electrocardiograms, known physiologic measurements include impedance measurements that can be used to assess the status of the patient.


Impedance measurements can be used to measure hydration and respiration of a patient. Long term impedance measurements used to determine patient hydration in relation to cardiac status represents one area where impedance measurements may be useful. Although current methodologies have been somewhat successful in measuring hydration, work in relation to embodiments of the present invention suggests that known methods and apparatus for monitoring patient hydration with impedance may be less than ideal. Some current devices may not accurately measure the impedance of the internal tissue of the patient, thereby making accurate hydration measurements more difficult. In some instances, the skin of the patient and/or coupling of electrodes to the skin may affect the impedance measurements. For example, environmental factors external to the patient may effect the measurements, for example when the patient showers. The electronics used to measure complex impedance signals of the patient may be somewhat larger than ideal and may not provide as much accuracy as would be ideal. Thus, devices that are worn by the patient may be somewhat uncomfortable, which may lead to patients not wearing the devices and not complying with direction from the health care provider, such that data collected may be less than ideal. As a compromise to reduce size and improve patient comfort, some devices to measure impedance may use circuitry that measures part of the tissue impedance without determining the resistance and reactance components of the complex impedance of the tissue.


Although implantable devices may be used in some instances, many of these devices can be invasive and/or costly, and may suffer at least some of the shortcomings of known wearable devices described above. In addition, implantable devices can be invasive and/or costly such that many patients cannot receive a therapeutic benefit. Although injectable devices may decrease invasiveness, the size requirements of injectable devices can place limitations on the circuitry and may limit the accuracy of such devices.


Therefore, a need exists for improved patient monitoring with impedance measurements. Ideally, such improved patient monitoring would avoid at least some of the shortcomings of the present methods and devices.


BRIEF SUMMARY OF THE INVENTION

The present invention relates to patient monitoring. Although embodiments make specific reference to monitoring impedance and electrocardiogram signals with an adherent patch, the system methods and device described herein may be applicable to many applications in which physiological monitoring with impedance measurements are used, for example physiological monitoring with implantable devices.


In many embodiments of the present invention, tissue impedance is determined in response a calibration signal from calibration circuitry and a tissue impedance signal from the tissue. Because the tissue impedance can be determined from both a tissue impedance signal and a calibration signal, errors can be minimized, for example errors that correspond to fluctuations in drive current, variations in measurement circuitry gain, time delays of the drive circuitry, time delays of the measurement circuitry, and parasitic impedance of the tissue, for example skin. The drive circuitry can be coupled to the calibration circuitry and at least two drive electrodes so as to drive current through the tissue and the calibration circuitry. Thus, a calibration signal from the calibration circuitry can be measured when the electrodes are connected to the patient, such that the calibration signal substantially corresponds to the current actually delivered through the tissue. Measurement circuitry can be connected to at least two measurement electrodes so as to measure a tissue impedance signal in response to the impedance of the tissue and the current through the tissue. The measurement circuitry can also be coupled to the calibration circuitry to measure the calibration signal, such that the tissue impedance can be determined in response to the measured calibration signal and the measured tissue impedance signal. Processor circuitry comprising a tangible medium can be configured to determine a complex tissue impedance in response to the calibration signal and the tissue impedance signal, such errors are minimized which correspond to fluctuations in drive current, variations in measurement circuitry gain, time delays of the drive circuitry, time delays of the measurement circuitry, and parasitic impedance of the tissue. As the calibration resistor can be provided with the drive circuitry and measurement circuitry, the system can be self calibrating, thereby eliminating a time consuming step at manufacture and minimizing memory resources of the controlling computer and/or processor. In many embodiments, the processor can be configured to select a frequency for the drive current, and the drive circuitry can be configured to increase the amount of drive current with increasing frequency, such that the signal to noise ratio can be improved. The amount of drive current at a selected increased frequency may even exceed a safety threshold for the amount of drive current at a lower frequency. The measurement circuitry can be configured to decrease the gain of the impedance signal with increasing frequency, such that the increased amount of current does not saturated the measurement circuitry and/or digitization electronics such as an analog to digital converter.


In a first aspect, embodiments of the present invention provide a device for measuring an impedance of a tissue of a patient. The calibration circuitry comprises an impedance. At least four electrodes are configured to couple to the tissue of the patient. The at least four electrodes may comprise at least two measurement electrodes and at least two drive electrodes. Drive circuitry is coupled to the at least two drive electrodes and the calibration circuitry to pass a current through the at least two drive electrodes and the calibration circuitry. Measurement circuitry is configured to couple to the at least two measurement electrodes and the calibration circuitry, such that the measurement circuitry can be configured to measure a calibration signal from the calibration circuitry and a tissue impedance signal from the at least two measurement electrodes. Processor circuitry comprising a tangible medium is configured to determine the impedance of the tissue in response to the calibration signal and the tissue impedance signal.


In many embodiments, the processor circuitry comprises as least one of an impedance converter or a microcontroller. The processor circuitry can be configured to determine the impedance of the tissue with a discrete Fourier transform of at least one of measurement signal or the current signal.


In many embodiments, the calibration circuitry can be connected in series between the drive circuitry and the at least two measurement electrodes to calibrate the tissue impedance measurement when the at least two electrodes are connected to the patient. The drive circuitry can be configured to pass the current through the tissue and the calibration circuitry to generate the tissue measurement signal and the calibration signal when the at least four electrodes are connected to the tissue. The calibration circuitry may comprise a calibration resistor, and the measurement circuitry can be configured to measure the calibration signal in response to the current through the calibration resistor and the tissue. The measurement circuitry can be configured to measure the tissue measurement signal in response to the current through the tissue and the calibration resistor. The processor can be configured to determine the tissue impedance from the calibration signal and the tissue measurement signal.


In many embodiments, at least one switch is coupled to the drive circuitry, the measurement circuitry, the calibration circuitry and the at least four electrodes. The at least one switch comprises a first configuration and a second configuration, In the first configuration the at least one switch couples the measurement circuitry to the calibration circuitry to measure the calibration signal. In the second configuration the at least one switch couples the measurement circuitry to the at least two measurement electrodes to measure the tissue impedance signal. The processor circuitry can be coupled to the at least one switch to select the first configuration or the second configuration.


In many embodiments, the measurement circuitry comprises a first measurement circuit configured to measure the calibration signal and a second measurement circuit configured to measure the tissue impedance signal.


In many embodiments, the calibration circuitry comprises at least one resistor connected in series to the drive circuitry and the at least two drive electrodes, such that a resistance of the resistor corresponds to at least 90% the impedance of the calibration circuitry. The calibration circuitry may comprise a resistance, and the calibration signal may comprise a complex calibration signal. The tissue impedance signal may comprise a complex tissue impedance signal, and the processor can be configured to determine a complex impedance of the tissue in response to the complex calibration signal and the complex tissue impedance signal.


In many embodiments, the processor is configured to store a calibration value comprising a resistance of the calibration circuitry that corresponds to a real number, and the calibration signal corresponds to the resistance of the calibration circuitry, delays of the drive circuitry and delays of the measurement circuitry. The processor can be configured to determine a complex calibration coefficient in response to the calibration value and the calibration signal. The tissue impedance may comprise a complex tissue impedance and processor can be configured to determine the complex tissue impedance in response to the complex calibration coefficient and the tissue impedance signal. For example, the processor can be configured to determine a complex tissue parameter from the tissue impedance signal, and the processor can be configured to determine the complex tissue impedance with at least one of a complex multiplication or a complex division of the complex calibration coefficient and the complex tissue parameter. The processor can be configured to determine the complex tissue parameter with a discrete Fourier transform of the tissue impedance signal and determine the complex calibration coefficient with a discrete Fourier transform of the calibration signal. The delays of the drive circuitry and the measurement circuitry can correspond to a phase angle of the calibration signal of at least about 90 degrees.


In many embodiments, the processor is configured to select a first frequency and a second frequency to measure impedance signals of the calibration circuitry at each of the first frequency and the second frequency, and the processor is configured to measure impedance signals of the tissue at each of the first frequency and the second frequency. The processor can be configured to determine an impedance of the tissue at the each of the first frequency and the second frequency in response to the impedance signals of the calibration circuitry measured at each of the first frequency and the second frequency and the impedance signals of the tissue measured at each of the first frequency and the second frequency.


In many embodiments, the processor is configured to store a tolerance range and measure the calibration circuitry in response to the impedance signal of the tissue and the tolerance range. The tolerance range may comprise plus or minus twenty percent of a baseline tissue impedance measurement, and the processor can be configured to measure the calibration circuitry in response to the tissue impedance outside the tolerance range.


In another aspect, embodiments of the present invention provide a device for measuring an impedance of a tissue of a patient. The device comprises at least four electrodes configured to couple to the tissue of the patient. The at least four electrodes comprising at least two drive electrodes, and at least two measurement electrodes. Drive circuitry is coupled to the at least two drive electrodes to pass a variable current through the tissue to generate a tissue measurement signal. The drive circuitry is configured to increase the current from a first current amount at a first frequency to a second current amount at a second frequency, in which the second frequency greater than the first frequency. Measurement circuitry is coupled to the at least two measurement electrodes to determine the impedance of the tissue in response to the tissue measurement signal. The measurement circuitry comprises a variable gain of the measurement signal, and the variable gain is configured to decrease from a first gain at the first frequency to a second gain at the second frequency.


In many embodiments, the variable current of the drive circuitry comprises a drive current frequency response, and the variable gain of the measurement circuitry comprises variable gain frequency response, in which the variable gain frequency response comprises an inverse of the drive current frequency response.


In many embodiments, the drive circuitry is configured to increase the second current amount to at least four times the first current amount, and the measurement circuitry is configured to decrease the second gain to no more than about one half of the first gain. In specific embodiments, the drive circuitry is configured to increase the second current amount to at least ten times the first current amount, and the measurement circuitry is configured to decrease the second gain to no more than about one third of the first gain.


In many embodiments, the second frequency is at least 1 kHz, and the second current amount is at least 10 μA and no more than 1000 μA. The first frequency corresponds to a first safety threshold of the first current, and the second frequency corresponds to a second safety threshold of the second current. The drive circuitry can be configured to exceed the first safety threshold with the second current amount and not to exceed the second safety threshold with the second current amount. The drive circuitry can be configured to exceed the first safety threshold with the second current by at least a factor of two. The safety threshold of the first current may correspond to 10 μA or a product of the first current in μA times the first frequency in kHz, whichever is greater.


In another aspect, embodiments of the present invention provide a method of measuring patient impedance. The method comprises providing at least four electrodes comprising at least two drive electrodes and at least two measurement electrodes. The at least two drive electrodes can be connected in series to a calibration resistor. Measurement circuitry is provided to measure a tissue impedance signal from the measurement electrodes. A drive current is passed through the at least two drive electrodes and the calibration resistor with drive circuitry. A current signal is measured from the calibration resistor in response to the current through the calibration resistor. The tissue impedance signal is measured from the measurement electrodes. The tissue impedance is determined in response to the current signal and the tissue impedance signal.


In many embodiments, the current signal from the calibration resistor is measured with the measurement circuitry.


In many embodiments, the tissue impedance can be determined with an impedance converter. The current signal from the calibration resistor may comprise a first voltage that is converted into a first current and the first current can be fed into the impedance converter. The tissue impedance signal from the measurement electrodes may comprise a second voltage that can be converted to a second current and the second current fed into the impedance converter.


In many embodiments, the drive circuitry may comprise a network to limit the drive current through the patient, such that the network increases the drive current through the patient as a frequency of the drive current increases. The measurement circuitry may comprise a variable gain that decreases when the frequency is increases and the drive current increases.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1A shows a patient and a monitoring system comprising an adherent device, according to embodiments of the present invention;



FIG. 1B shows a bottom view of the adherent device as in FIG. 1A comprising an adherent patch;



FIG. 1C shows a top view of the adherent patch, as in FIG. 1B;



FIG. 1D shows a printed circuit boards and electronic components over the adherent patch, as in FIG. 1C;


FIG. 1D1 shows an equivalent circuit that can be used to determine optimal frequencies for determining patient hydration, according to embodiments of the present invention;



FIG. 1E shows batteries positioned over the printed circuit board and electronic components as in FIG. 1D;



FIG. 1F shows a top view of an electronics housing and a breathable cover over the batteries, electronic components and printed circuit board as in FIG. 1E;



FIG. 1G shows a side view of the adherent device as in FIGS. 1A to 1F;



FIG. 1H shown a bottom isometric view of the adherent device as in FIGS. 1A to 1G;



FIGS. 1I and 1J show a side cross-sectional view and an exploded view, respectively, of the adherent device as in FIGS. 1A to 1H;



FIG. 1K shows at least one electrode configured to electrically couple to a skin of the patient through a breathable tape, according to embodiments of the present invention;



FIG. 2A shows a simplified schematic illustration of a circuit diagram for measuring patient impedance, according to embodiments of the present invention;



FIG. 2B shows an inverse frequency response of the drive circuitry and measurement circuitry, according to embodiments of the present invention;



FIG. 3A shows circuitry for measuring patient impedance with an impedance converter, according to embodiments of the present invention;



FIG. 3B shows a model for measuring patient impedance with circuitry as in FIG. 3A;



FIG. 3C shows a model equivalent to the model of FIG. 3B that allows for correction of parasitic impedance, according to embodiments of the present invention; and



FIG. 4 shows a method of measuring patient impedance, according to embodiments of the present invention.





DETAILED DESCRIPTION OF THE INVENTION

Embodiments of the present invention relate to patient monitoring. Although embodiments make specific reference to monitoring impedance and electrocardiogram signals with an adherent patch, the system methods and device described herein may be applicable to many application in which physiological monitoring is used, for example physiological monitoring with implantable devices.


In many embodiments, the adherent devices described herein may be used for 90 day monitoring, or more, and may comprise completely disposable components and/or reusable components, and can provide reliable data acquisition and transfer. In many embodiments, the patch is configured for patient comfort, such that the patch can be worn and/or tolerated by the patient for extended periods, for example 90 days or more. In many embodiments, the adherent patch comprises a tape, which comprises a material, preferably breathable, with an adhesive, such that trauma to the patient skin can be minimized while the patch is worn for the extended period. In many embodiments, the printed circuit board comprises a flex printed circuit board that can flex with the patient to provide improved patient comfort.



FIG. 1A shows a patient P and a monitoring system 10. Patient P comprises a midline M, a first side S1, for example a right side, and a second side S2, for example a left side. Monitoring system 10 comprises an adherent device 100. Adherent device 100 can be adhered to a patient P at many locations, for example thorax T of patient P. In many embodiments, the adherent device may adhere to one side of the patient, from which side data can be collected. Work in relation with embodiments of the present invention suggests that location on a side of the patient can provide comfort for the patient while the device is adhered to the patient.


Monitoring system 10 includes components to transmit data to a remote center 106. Adherent device 100 can communicate wirelessly to an intermediate device 102, for example with a single wireless hop from the adherent device on the patient to the intermediate device. Intermediate device 102 can communicate with remote center 106 in many ways, for example with an internet connection. In many embodiments, monitoring system 10 comprises a distributed processing system with at least one processor on device 100, at least one processor on intermediate device 102, and at least one process at remote center 106, each of which processors is in electronic communication with the other processors. Remote center 106 can be in communication with a health care provider 108A with a communication system 107A, such as the Internet, an intranet, phone lines, wireless and/or satellite phone. Health care provider 108A, for example a family member, can be in communication with patient P with a communication, for example with a two way communication system, as indicated by arrow 109A, for example by cell phone, email, landline. Remote center 106 can be in communication with a health care professional, for example a physician 108B, with a communication system 107B, such as the Internet, an intranet, phone lines, wireless and/or satellite phone. Physician 108B can be in communication with patient P with a communication, for example with a two way communication system, as indicated by arrow 109B, for example by cell phone, email, landline. Remote center 106 can be in communication with an emergency responder 108C, for example a 911 operator and/or paramedic, with a communication system 107C, such as the Internet, an intranet, phone lines, wireless and/or satellite phone. Emergency responder 108C can travel to the patient as indicated by arrow 109C. Thus, in many embodiments, monitoring system 10 comprises a closed loop system in which patient care can be monitored and implemented from the remote center in response to signals from the adherent device.


In many embodiments, the adherent device may continuously monitor physiological parameters, communicate wirelessly with a remote center, and provide alerts when necessary. The system may comprise an adherent patch, which attaches to the patient's thorax and contains sensing electrodes, battery, memory, logic, and wireless communication capabilities. In some embodiments, the patch can communicates with the remote center, via the intermediate device in the patient's home. In the many embodiments, the remote center receives the data and applies the prediction algorithm. When a flag is raised, the center may communicate with the patient, hospital, nurse, and/or physician to allow for therapeutic intervention to prevent decompensation.


The adherent device may be affixed and/or adhered to the body in many ways. For example, with at least one of the following an adhesive tape, a constant-force spring, suspenders around shoulders, a screw-in microneedle electrode, a pre-shaped electronics module to shape fabric to a thorax, a pinch onto roll of skin, or transcutaneous anchoring. Patch and/or device replacement may occur with a keyed patch (e.g. two-part patch), an outline or anatomical mark, a low-adhesive guide (place guide|remove old patch|place new patch|remove guide), or a keyed attachment for chatter reduction. The patch and/or device may comprise an adhesiveless embodiment (e.g. chest strap), and/or a low-irritation adhesive model for sensitive skin. The adherent patch and/or device can comprise many shapes, for example at least one of a dogbone, an hourglass, an oblong, a circular or an oval shape.


In many embodiments, the adherent device may comprise a reusable electronics module with replaceable patches (the module collects cumulative data for approximately 90 days) and/or the entire adherent component (electronics+patch) may be disposable. In a completely disposable embodiment, a “baton” mechanism may be used for data transfer and retention, for example baton transfer may include baseline information. In some embodiments, the device may have a rechargeable module, and may use dual battery and/or electronics modules, wherein one module 101A can be recharged using a charging station 103 while the other module 101B is placed on the adherent device. In some embodiments, the intermediate device 102 may comprise the charging module, data transfer, storage and/or transmission, such that one of the electronics modules can be placed in the intermediate device for charging and/or data transfer while the other electronics module is worn by the patient.


In many embodiments, the system can perform the following functions: initiation, programming, measuring, storing, analyzing, communicating, predicting, and displaying. The adherent device may contain a subset of the following physiological sensors: bioimpedance, respiration, respiration rate variability, heart rate (ave, min, max), heart rhythm, HRV, HRT, heart sounds (e.g. S3), respiratory sounds, blood pressure, activity, posture, wake/sleep, orthopnea, temperature/heat flux, and weight. The activity sensor may be one of the following: ball switch, accelerometer, minute ventilation, HR, bioimpedance noise, skin temperature/heat flux, BP, muscle noise, posture.


In many embodiments, the patch wirelessly communicates with a remote center. In some embodiments, the communication may occur directly (via a cellular or Wi-Fi network), or indirectly through intermediate device 102. Intermediate device 102 may consist of multiple devices which communicate wired or wirelessly to relay data to remote center 106.


In many embodiments, instructions are transmitted from a remote site to a processor supported with the patient, and the processor supported with the patient can receive updated instructions for the patient treatment and/or monitoring, for example while worn by the patient.



FIG. 1B shows a bottom view of adherent device 100 as in FIG. 1A comprising an adherent patch 110. Adherent patch 110 comprises a first side, or a lower side 110A, that is oriented toward the skin of the patient when placed on the patient. In many embodiments, adherent patch 110 comprises a tape 110T which is a material, preferably breathable, with an adhesive 116A. Patient side 110A comprises adhesive 116A to adhere the patch 110 and adherent device 100 to patient P. Electrodes 112A, 112B, 112C and 112D are affixed to adherent patch 110. In many embodiments, at least four electrodes are attached to the patch, for example six electrodes. In some embodiments the patch comprises two electrodes, for example two electrodes to measure the electrocardiogram (ECG) of the patient. Gel 114A, gel 114B, gel 114C and gel 114D can each be positioned over electrodes 112A, 112B, 112C and 112D, respectively, to provide electrical conductivity between the electrodes and the skin of the patient. In many embodiments, the electrodes can be affixed to the patch 110, for example with known methods and structures such as rivets, adhesive, stitches, etc. In many embodiments, patch 110 comprises a breathable material to permit air and/or vapor to flow to and from the surface of the skin.



FIG. 1C shows a top view of the adherent patch 100, as in FIG. 1B. Adherent patch 100 comprises a second side, or upper side 110B. In many embodiments, electrodes 110A, 110B, 110C and 110D extend from lower side 110A through the adherent patch to upper side 110B. In some embodiments, an adhesive 116B can be applied to upper side 110B to adhere structures, for example electronic structures, to the patch such that the patch can support the electronics and other structures when the patch is adhered to the patient. The PCB comprise completely flex PCB, rigid PCB combined flex PCB and/or rigid PCB boards connected by cable.



FIG. 1D shows a printed circuit boards and electronic components over adherent patch 110, as in FIG. 1C. In some embodiments, a printed circuit board (PCB), for example flex PCB 120, may be connected to upper side 100B of patch 110 with connectors 122A, 122B, 122C and 122D. Flex PCB 120 can include traces 123A, 123B, 123C and 123D that extend to connectors 122A, 122B, 122C and 122D, respectively, on the flex PCB. Connectors 122A, 122B, 122C and 122D can be positioned on flex PCB 120 in alignment with electrodes 112A, 112B, 112C and 112D so as to electrically couple the flex PCB with the electrodes. In some embodiments, connectors 122A, 122B, 122C and 122D may comprise insulated wires that provide strain relief between the PCB and the electrodes. In some embodiments, additional PCB's, for example rigid PCB's 120A, 120B, 120C and 120D, can be connected to flex PCB 120. Electronic components 130 can be connected to flex PCB 120 and/or mounted thereon. In some embodiments, electronic components 130 can be mounted on the additional PCB's.


Electronic components 130 comprise components to take physiologic measurements, transmit data to remote center 106 and receive commands from remote center 106. In many embodiments, electronics components 130 may comprise known low power circuitry, for example complementary metal oxide semiconductor (CMOS) circuitry components. Electronics components 130 comprise an activity sensor and activity circuitry 134, impedance circuitry 136 and electrocardiogram circuitry, for example ECG circuitry 136. In some embodiments, electronics circuitry 130 may comprise a microphone and microphone circuitry 142 to detect an audio signal from within the patient, and the audio signal may comprise a heart sound and/or a respiratory sound, for example an S3 heart sound and a respiratory sound with rales and/or crackles. Electronics circuitry 130 may comprise a temperature sensor, for example a thermistor, and temperature sensor circuitry 144 to measure a temperature of the patient, for example a temperature of a skin of the patient.


Work in relation to embodiments of the present invention suggests that skin temperature may effect impedance and/or hydration measurements, and that skin temperature measurements may be used to correct impedance and/or hydration measurements. In some embodiments, increase in skin temperature or heat flux can be associated with increased vaso-dilation near the skin surface, such that measured impedance measurement decreased, even through the hydration of the patient in deeper tissues under the skin remains substantially unchanged. Thus, use of the temperature sensor can allow for correction of the hydration signals to more accurately assess the hydration, for example extra cellular hydration, of deeper tissues of the patient, for example deeper tissues in the thorax.


Electronics circuitry 130 may comprise a processor 146. Processor 146 comprises a tangible medium, for example read only memory (ROM), electrically erasable programmable read only memory (EEPROM) and/or random access memory (RAM). Electronic circuitry 130 may comprise real time clock and frequency generator circuitry 148. In some embodiments, processor 136 may comprise the frequency generator and real time clock. The processor can be configured to control a collection and transmission of data from the impedance circuitry electrocardiogram circuitry and the accelerometer. In many embodiments, device 100 comprise a distributed processor system, for example with multiple processors on device 100.


In many embodiments, electronics components 130 comprise wireless communications circuitry 132 to communicate with remote center 106. The wireless communication circuitry can be coupled to the impedance circuitry, the electrocardiogram circuitry and the accelerometer to transmit to a remote center with a communication protocol at least one of the hydration signal, the electrocardiogram signal or the inclination signal. In specific embodiments, wireless communication circuitry is configured to transmit the hydration signal, the electrocardiogram signal and the inclination signal to the remote center with a single wireless hop, for example from wireless communication circuitry 132 to intermediate device 102. The communication protocol comprises at least one of Bluetooth, Zigbee, WiFi, WiMax, IR, amplitude modulation or frequency modulation. In many embodiments, the communications protocol comprises a two way protocol such that the remote center is capable of issuing commands to control data collection.


In some embodiments, intermediate device 102 comprises a data collection system to collect and store data from the wireless transmitter. The data collection system can be configured to communicate periodically with the remote center. In many embodiments, the data collection system can transmit data in response to commands from remote center 106 and/or in response to commands from the adherent device.


Activity sensor and activity circuitry 134 can comprise many known activity sensors and circuitry. In many embodiments, the accelerometer comprises at least one of a piezoelectric accelerometer, capacitive accelerometer or electromechanical accelerometer. The accelerometer may comprises a 3-axis accelerometer to measure at least one of an inclination, a position, an orientation or acceleration of the patient in three dimensions. Work in relation to embodiments of the present invention suggests that three dimensional orientation of the patient and associated positions, for example sitting, standing, lying down, can be very useful when combined with data from other sensors, for example ECG data and/or hydration data.


Impedance circuitry 136 can generate both hydration data and respiration data. In many embodiments, impedance circuitry 136 is electrically connected to electrodes 112A, 112B, 112C and 112D such that electrodes 112A and 112D comprise outer electrodes that are driven with a current, or force electrodes. The current delivered between electrodes 112A and 112D generates a measurable voltage between electrodes 112B and 112C, such that electrodes 112B and 112C comprise inner electrodes, or measurement electrodes that measure the voltage in response to the current from the force electrodes. The voltage measured by the measurement electrodes can be used to determine the hydration of the patient.


FIG. 1D1 shows an equivalent circuit 152 that can be used to determine optimal frequencies for measuring patient hydration. Work in relation to embodiments of the present invention indicates that the frequency of the current and/or voltage at the force electrodes can be selected so as to provide impedance signals related to the extracellular and/or intracellular hydration of the patient tissue. Equivalent circuit 152 comprises an intracellular resistance 156, or R(ICW) in series with a capacitor 154, and an extracellular resistance 158, or R(ECW). Extracellular resistance 158 is in parallel with intracellular resistance 156 and capacitor 154 related to capacitance of cell membranes. In many embodiments, impedances can be measured and provide useful information over a wide range of frequencies, for example from about 0.5 kHz to about 200 KHz. Work in relation to embodiments of the present invention suggests that extracellular resistance 158 can be significantly related extracellular fluid and to cardiac decompensation, and that extracellular resistance 158 and extracellular fluid can be effectively measured with frequencies in a range from about 0.5 kHz to about 20 kHz, for example from about 1 kHz to about 10 kHz. In some embodiments, a single frequency can be used to determine the extracellular resistance and/or fluid. As sample frequencies increase from about 10 kHz to about 20 kHz, capacitance related to cell membranes decrease the impedance, such that the intracellular fluid contributes to the impedance and/or hydration measurements. Thus, many embodiments of the present invention employ measure hydration with frequencies from about 0.5 kHz to about 20 kHz to determine patient hydration.


In many embodiments, impedance circuitry 136 can be configured to determine respiration of the patient. In specific embodiments, the impedance circuitry can measure the hydration at 25 Hz intervals, for example at 25 Hz intervals using impedance measurements with a frequency from about 0.5 kHz to about 20 kHz.


ECG circuitry 138 can generate electrocardiogram signals and data from electrodes 112A, 112B, 112C and 112D. In some embodiments, ECG circuitry 138 is connected to inner electrodes 112B and 122C, which may comprise measurement electrodes of the impedance circuitry as described above. In some embodiments, the inner electrodes may be positioned near the outer electrodes to increase the voltage of the ECG signal measured by ECG circuitry 138. In some embodiments, the ECG circuitry can share components with the impedance circuitry.



FIG. 1E shows batteries 150 positioned over the flex printed circuit board and electronic components as in FIG. 1D. Batteries 150 may comprise rechargeable batteries that can be removed and/or recharged. In some embodiments, batteries 150 can be removed from the adherent patch and recharged and/or replaced.



FIG. 1F shows a top view of a cover 162 over the batteries, electronic components and flex printed circuit board as in FIG. 1E. In many embodiments, an electronics housing 160 may be disposed under cover 162 to protect the electronic components, and in some embodiments electronics housing 160 may comprise an encapsulant over the electronic components and PCB. In some embodiments, cover 162 can be adhered to adhesive patch with an adhesive 164 on an underside of cover 162. In some embodiments, electronics housing 160 can be adhered to cover 162 with an adhesive 166 where cover 162 contacts electronics housing 160. In many embodiments, electronics housing 160 may comprise a water proof material, for example a sealant adhesive such as epoxy or silicone coated over the electronics components and/or PCB. In some embodiments, electronics housing 160 may comprise metal and/or plastic. Metal or plastic may be potted with a material such as epoxy or silicone.


Cover 162 may comprise many known biocompatible cover, casing and/or housing materials, such as elastomers, for example silicone. The elastomer may be fenestrated to improve breathability. In some embodiments, cover 162 may comprise many known breathable materials, for example polyester, polyamide, and/or elastane (Spandex). The breathable fabric may be coated to make it water resistant, waterproof, and/or to aid in wicking moisture away from the patch.



FIG. 1G shows a side view of adherent device 100 as in FIGS. 1A to 1F. Adherent device 100 comprises a maximum dimension, for example a length 170 from about 4 to 10 inches (from about 100 mm to about 250 mm), for example from about 6 to 8 inches (from about 150 mm to about 200 mm). In some embodiments, length 170 may be no more than about 6 inches (no more than about 150 mm). Adherent device 100 comprises a thickness 172. Thickness 172 may comprise a maximum thickness along a profile of the device. Thickness 172 can be from about 0.2 inches to about 0.4 inches (from about 5 mm to about 10 mm), for example about 0.3 inches (about 7.5 mm).



FIG. 1H shown a bottom isometric view of adherent device 100 as in FIGS. 1A to 1G. Adherent device 100 comprises a width 174, for example a maximum width along a width profile of adherent device 100. Width 174 can be from about 2 to about 4 inches (from about 50 mm to 100 mm), for example about 3 inches (about 75 mm).



FIGS. 1I and 1J show a side cross-sectional view and an exploded view, respectively, of adherent device 100 as in FIGS. 1A to 1H. Device 100 comprises several layers. Gel 114A, or gel layer, is positioned on electrode 112A to provide electrical conductivity between the electrode and the skin. Electrode 112A may comprise an electrode layer. Adhesive patch 110 may comprise a layer of breathable tape 110T, for example a known breathable tape, such as tricot-knit polyester fabric. An adhesive 116A, for example a layer of acrylate pressure sensitive adhesive, can be disposed on underside 110A of patch 110. A gel cover 180, or gel cover layer, for example a polyurethane non-woven tape, can be positioned over patch 110 comprising the breathable tape. A PCB layer, for example flex PCB 120, or flex PCB layer, can be positioned over gel cover 180 with electronic components 130 connected and/or mounted to flex PCB 120, for example mounted on flex PCB so as to comprise an electronics layer disposed on the flex PCB. In many embodiments, the adherent device may comprise a segmented inner component, for example the PCB, for limited flexibility. In many embodiments, the electronics layer may be encapsulated in electronics housing 160 which may comprise a waterproof material, for example silicone or epoxy. In many embodiments, the electrodes are connected to the PCB with a flex connection, for example trace 123A of flex PCB 120, so as to provide strain relive between the electrodes 112A, 112B, 112C and 112D and the PCB. Gel cover 180 can inhibit flow of gel 114A and liquid. In many embodiments, gel cover 180 can inhibit gel 114A from seeping through breathable tape 110T to maintain gel integrity over time. Gel cover 180 can also keep external moisture from penetrating into gel 114A. In many embodiments, cover 162 can encase the flex PCB and/or electronics and can be adhered to at least one of the electronics, the flex PCB or the adherent patch, so as to protect the device. In some embodiments, cover 162 attaches to adhesive patch 110 with adhesive 116B, and cover 162 is adhered to the PCB module with an adhesive 161 on the upper surface of the electronics housing. Cover 162 can comprise many known biocompatible cover, housing and/or casing materials, for example silicone. In many embodiments, cover 162 comprises an outer polymer cover to provide smooth contour without limiting flexibility. In some embodiments, cover 162 may comprise a breathable fabric. Cover 162 may comprise many known breathable fabrics, for example breathable fabrics as described above. In some embodiments, the breathable fabric may comprise polyester, polyamide, and/or elastane (Spandex) to allow the breathable fabric to stretch with body movement. In some embodiments, the breathable tape may contain and elute a pharmaceutical agent, such as an antibiotic, anti-inflammatory or antifungal agent, when the adherent device is placed on the patient.


In many embodiments, the breathable tape of adhesive patch 110 comprises a first mesh with a first porosity and gel cover 180 comprises a breathable tape with a second mesh porosity, in which the second porosity is less than the first porosity to inhibit flow of the gel through the breathable tape.


In many embodiments, a gap 169 extends from adherent patch 110 to the electronics module and/or PCB, such that breathable tape 110T can breath to provide patient comfort.


In many embodiments, the adherent device comprises a patch component and at least one electronics module. The patch component may comprise adhesive patch 110 comprising the breathable tape with adhesive coating 116A, at least one electrode 114A and gel 114, for example a gel coating. The at least one electronics module can be is separable from the patch component. In many embodiments, the at least one electronics module comprises the flex printed circuit board 120, electronic component 130, electronics housing 160 and waterproof cover 162, such that the flex printed circuit board, electronic components electronics housing and water proof cover are reusable and/or removable for recharging and data transfer, for example as described above. In many embodiments, adhesive 116B is coated on upper side 110A of adhesive patch 110B, such that the electronics module, or electronics layers, can be adhered to and/or separated from the adhesive component, or adhesive layers. In specific embodiments, the electronic module can be adhered to the patch component with a releasable connection, for example with Velcro™, a known hook and loop connection, and/or snap directly to the electrodes. In some embodiments, two electronics modules can be provided, such that one electronics module can be worn by the patient while the other is charged as described above.


In many embodiments, at least one electrode 112A extends through at least one aperture in the breathable tape 110.


In some embodiments, the adhesive patch may comprise a medicated patch that releases a medicament, such as antibiotic, beta-blocker, ACE inhibitor, diuretic, or steroid to reduce skin irritation. In some embodiments, the adhesive patch may comprise a thin, flexible, breathable patch with a polymer grid for stiffening. This grid may be anisotropic, may use electronic components to act as a stiffener, may use electronics-enhanced adhesive elution, and may use an alternating elution of adhesive and steroid.



FIG. 1K shows at least one electrode 190 configured to electrically couple to a skin of the patient through a breathable tape 192. In many embodiments, at least one electrode 190 and breathable tape 192 comprise electrodes and materials similar to those described above. Electrode 190 and breathable tape 192 can be incorporated into adherent devices as described above, so as to provide electrical coupling between the skin an electrode through the breathable tape, for example with the gel.



FIG. 2A shows a simplified schematic illustration of circuitry 200 for measuring patient signals, such as impedance signals to measure hydration, ECG signals. Circuitry 200 comprises drive circuitry 210 to drive a current through the patient tissue, and measurement circuitry 250 to measure an impedance signal from the patient tissue. Circuitry 200 may comprise at least four electrodes 240 to couple drive circuitry 210 and measurement circuitry 250 to the patient tissue. Circuitry 200 comprises calibration circuitry 220 to calibrate the drive circuitry and measurement circuitry. Circuitry 200 may comprise a processor system 260 that comprises at least one processor, for example a processor 262 on the adherent device as described above. Circuitry 200 may comprise at least one switch 230 that can be used to select for measurement either on board calibration circuitry 220 or electrodes 240 that are coupled to the skin of the patient. Circuitry 200 may comprise ECG circuitry 270 to measure electrocardiogram signals from the patient, accelerometer 280 to measure patient position and/or activity, and wireless circuitry 290 to transmit the data.


Drive circuitry 210 may comprise a drive module 212. Drive module 212 can be used to generate a drive current at a selected frequency. For example, drive module 212 may comprise direct digital synthesis (DDS) and digital to analog conversion (DAC) and amplifiers to generate the drive current at the selected frequency. The amplifiers to generate the drive current may comprise a gain, and in some embodiments the gain of the drive current amplifiers increases with increasing frequency. In some embodiments, drive module 212 may comprise analog electronics, for example a frequency generator to generate the drive current at the selected frequency. The drive current may comprise an AC component at the selected frequency and a DC component. Drive circuitry 210 comprises circuitry to adjust the current delivered to the patient in response to the selected frequency. In many embodiments, drive circuitry 210 can increase the current delivered to the patient as the drive frequency increases, such that the amount of current complies with safe current requirements, for example known AAMI ES1 requirements. The drive current is generally below a safety threshold that corresponds to 10 μA for frequencies below 1 kHz, increases by 10 μA per decade kHz from 1 kHz to 100 kHz, and remains at 1 mA for frequencies above 100 kHz, for example from 100 kHz to 1 MHz. In many embodiments, drive circuitry 210 comprises an attenuation network that decreases current from the drive module to the tissue. In many embodiments, the attenuation of drive current from the drive module decreases with increasing frequency, such that the amount of current delivered to the patient increases with increasing frequency. In specific embodiments, attenuation circuitry 212 may comprise a high pass RC circuit network such that the current delivered to tissue increases from about 200 Hz to about 1 kHz, for example with a corner frequency, fc, within a range from about 200 Hz to about 1 kHz. Alternatively or in combination, drive circuitry 210 may comprise a high pass amplifier that increases the gain of current delivered to the patient as the selected frequency increases.


Calibration circuitry 220 can comprise components of known impedance to calibrate circuitry 200. Calibration circuitry 220 can be connected to drive circuitry 210 and measurement circuitry 250 to calibrate the electronics of circuitry 200, for example drive circuitry 210 and measurement circuitry 250. In specific embodiments, calibration circuitry 220 comprises a resistor of known resistance that can be used to calibrate drive circuitry 210 and measurement circuitry 250. Calibration circuitry 220 may comprise a substantial resistance with very little reactance, for example resistance may comprise at least 90% of the magnitude of the impedance of calibration circuitry 220. The use of calibration circuitry that comprises substantial resistance can facilitate calibration, as phase delay and amplitude changes in the measured calibration signal may be attributed to changes in drive circuitry 210 and measurement circuitry 250. In many embodiments, the resistor of calibration circuitry 220 comprises a known resistance that is close to the impedance of tissue measured such that the calibration circuitry comprises an impedance with a magnitude within the range of physiologic tissue impedances likely to be measured with the electrodes, for example from about 10 Ohms to about 200 Ohms. In some embodiments, calibration circuitry 220 may comprises a plurality of selectable resistors to select a resistance that is close to the measured tissue impedance.


At least one electrode 240 comprises at least two drive electrodes, for example V+ electrode 244 and V− electrode 248. The at least two drive electrodes can be coupled to drive circuitry 210 to pass a current through the tissue of the patient. At least one electrode 240 comprises at least two measurement electrodes, for example I+ electrode 244 and I− electrode 246. The at least two measurement electrodes can be coupled to measurement circuitry 250 to measure an impedance signal from the tissue, for example a voltage drop across the tissue from the current passed through the tissue.


Circuitry 200 may comprise at least one switch 230. At least one switch 230 may comprise a first package of high performance switches SW1, a second package of high performance switches SW2 and a third package of high performance switches SW3. At least one switch 230 can be configured in many ways. In specific embodiments, a first configuration of at least one switch 230 couples drive circuitry 210 and measurement circuitry 250 to calibration circuitry 230 to measure an impedance signal from calibration circuitry 230 to calibrate the circuitry. A second configuration of at least one switch 230 couples drive circuitry 210 to the at least two drive electrodes and measurement circuitry 250 to the at least two measurement electrodes to measure the impedance of the tissue of the patient.


Although at least one switch 230 is shown, in some embodiments calibration can be performed without switches, for example with substantially parallel drive and measurement circuits. In specific embodiments, drive circuitry 210 may comprise substantially similar parallel drive circuits with one of the parallel drive circuits coupled to the resistance circuitry and the other of the parallel drive circuits coupled to the tissue with the drive electrodes. Measurement circuitry 250 may comprise substantially similar measurement circuits with one of the substantially similar measurement circuits coupled to the resistance circuitry and the other of the substantially similar measurement circuits coupled to the tissue with the measurement electrodes. Thus, in at least some embodiments, calibration based on the resistance circuitry can be performed without the at least one switch.


Measurement circuitry 250 may comprise a differential amplifier, for example an instrumentation amplifier 252 with high input impedance. Instrumentation amplifier 252 may comprise known instrumentation amplifier circuits. Measurement circuitry can be configured with a variable gain that decreases as the current to the tissue increases. Measurement circuitry 250 may comprise a pre-emphasis before analog to digital converter 256, for example de-emphasis network that decreases the gain of the measurement circuitry as the frequency increases. In specific embodiments, an RC network can be used to provide a decrease in gain of the measurement circuitry with an increase in drive frequency and drive current. Measurement circuitry 250 may comprise an analog to digital converter 256 (A/D) to convert the analog measurement signal to a digital measurement signal the analog to digital converter communicates the digitized measurement signal to the processor system.


Circuitry 200 may comprise ECG circuitry 270. ECG circuitry 270 can be connected to the drive electrodes of at least one electrode 240 and may be connected to the measurement electrodes of at least one electrode 240 to measure the ECG signal from the patient. ECG circuitry may comprise known ECG circuitry with variable gain, for example known instrumentation amplifiers and known bandpass filters to select the frequencies of the ECG signal with variable gain. ECG circuitry 270 can be connected to processor 262 to process the ECG signals.


Circuitry 200 may comprise an accelerometer 280 to measure patient orientation, acceleration and/or activity of the patient. Accelerometer 280 may comprise many known accelerometers. Accelerometer 280 may be connected to processor 262 to process signals from accelerometer 280.


Circuitry 200 may comprise wireless circuitry 290. Wireless circuitry 290 may comprise known wireless circuitry for wireless communication from the device. Wireless communications circuitry 290 can communicate with remote center as described above. The wireless communication circuitry can be coupled to the impedance circuitry, the electrocardiogram circuitry and the accelerometer to transmit to a remote center with a communication protocol at least one of the hydration signal, the electrocardiogram signal or the inclination signal from the accelerometer. In specific embodiments, wireless communication circuitry is configured to transmit the hydration signal, the electrocardiogram signal and the inclination signal to the remote center with a single wireless hop, for example from wireless communication circuitry 290 to the intermediate device as described above. The communication protocol may comprise at least one of Bluetooth, Zigbee, WiFi, WiMax, IR, amplitude modulation or frequency modulation. In many embodiments, the communications protocol comprises a two way protocol such that the remote center is capable of issuing commands to control data collection.


Processor system 260 may comprise processors in addition to processor 262, for example a remote processor as described above. Processor 262 comprises a tangible medium that can be configured with instructions, for example known processor memory. Processor 262 may comprise a known single chip processor with random access memory (RAM), read only memory (ROM), erasable read only memory (EPROM) and a central processing unit. Processor system 260 may also comprise an onboard impedance converter 264, for example AD5934 commercially available from Analog Devices of Norwood, Mass., USA. Impedance converter 264 and/or processor 262 can be configured to synthesize a drive signal with drive circuitry 212 comprising direct digital synthesis (DDS) and digital to analog conversion (DAC). Impedance converter 262 and/or processor 262 can also be configured to measure the impedance signal with analog to digital conversion (ADC) and a digital Fourier transform (DFT). In many embodiments, processor 262 is connected to a precision oscillator, for example a know quartz 16 MHz oscillator, so as to provide an accurate and synchronous time base. The synchronous time base is provided for the drive signal and analog to digital conversion, such that time and/or phase delay of the circuitry and tissue impedance measurement can be accurately determined. Thus, the measured phase angle of a signal may correspond to the time delay from digitization of the drive signal at the DAC to measurement of the signal at the ADC. Work in relation to embodiments of the present invention suggests that time delays of the drive circuitry and time delays of the measurement circuitry can correspond to a phase angle of 270 degrees at some measurement frequencies, such that calibration that includes delays of the drive circuitry and measurement circuitry can provide improved accuracy of the determined complex tissue impedance.


The four wire, for four electrode, impedance determination uses that property that current through a series circuit will create a voltage drop across each component that is proportional to their respective impedances. The general form of this, realizing that each variable is a complex number, is:

Zunknown/Rcal=Vu/Vr


which becomes

Zunknown=(Vu/Vr)*Rcal


where Zunknown comprises the unknown impedance, or tissue impedance, Rcal, comprises the resistance of the calibration circuitry, Vu comprises the voltage signal across the unknown impedance, and Vr, comprises the voltage across the calibration resistor.


Processor system 260 can be configured to make complex calibration and tissue impedance measurements at many frequencies as described above. In specific embodiments, processor system 262 can store a known value of the resistance of calibration circuitry in memory of the processor. For example, the calibration circuitry may comprise a known resistance, Rcal, that can be measured with an ohm meter and stored in processor memory as a real number. The processor system can select calibration circuitry 220 in a first configuration of at least one switch 230, as described above. A drive current is passed through calibration circuitry 220 and an impedance signal measured with measurement circuitry 250. The impedance signal is digitized with the analog to digital converter 256, for example with quadrature sampling for about 256 cycles corresponding to 1024 samples of the measurement calibration signal. Processor system 260, for example processor 262 and/or impedance converter 262, calculates a digital transform of the signal, for example at least one of a discrete Fourier transform (DFT), a cosine transform or a sine transform of the measurement signal. In a specific embodiment, processor 262 calculates a cosine transform of the measurement signal and a sine transform of the measurement signal at the tissue excitation frequency with the current. The cosine transform comprises a known transform and calculating the cosine transform of the measurement signal may comprise multiplying the measurement signal by the cosine of the phase of the drive signal at each sampled data point and summing the values. The sine transform comprises a known transform and calculating the sine transform of the measurement signal may comprise multiplying the measurement signal by the sine of the phase of the drive signal at each sampled data point and summing the values. The cosine transform of the measured impedance calibration signal, Cc, corresponds to the real component, or resistance, of the measured impedance calibration signal, and the sine transform of the measured impedance calibration signal, Cs, corresponds to the imaginary component, or reactance, of the measured impedance calibration signal.


The measured complex impedance calibration signal can be expressed as

Zcal=(Cc+jCs)


The complex calibration coefficient, Zcoef, can be expressed as

Zcoeff=Rcal/Zcal=Rcal/(Cc+jCs)


As noted above, although the calibration circuit comprises a substantial resistance, often without a substantial reactance component, the complex calibration coefficient may include a substantial reactance component due to the phase and/or time delay of the drive circuitry, time delay of the measurement circuitry, and/or additional parasitic impedances such as the electrode to tissue coupling. The complex calibration coefficient can be used to calculate the tissue impedance, such that the phase and/or time delays can be calibrated out of the tissue impedance measurement along with the parasitic impedances such as the electrode to tissue coupling. Work in relation to embodiments of the present invention suggests that the phase delay due to the drive circuitry and/or measurement circuitry can be 90 degrees or more, for example 270 degrees, such that a much more accurate determination impedance can be made using the calibration circuitry and complex calibration coefficient.


The tissue can be selected for measurement with the at least one switch in the second configuration, as described above. A drive current can be passed through measurement electrodes with measurement circuitry 210 and a tissue impedance signal measured from the measurement electrodes with measurement circuitry 250. The tissue impedance signal is digitized and the cosine and sine transforms of the measured tissue impedance signal calculated. The cosine transform of the tissue measured tissue impedance signal, Tc, corresponds to the real component, or resistance, of the measured tissue impedance signal and the sine transform of the measured tissue impedance signal, Ts, corresponds to the imaginary component, or reactance, of the measured tissue impedance signal. The complex tissue impedance signal, Zts, can be expressed as

Zts=Tc+jTs


The complex impedance of the tissue, Ztissue, can be determined and/or calculated in response to the complex impedance calibration signal and the complex tissue impedance signal. In specific embodiments, the complex impedance of the tissue can be calculated in response to the measured complex calibration coefficient and the measured complex tissue impedance signal by multiplying the measured complex calibration coefficient and the measured complex tissue impedance signal, expressed as

Ztissue=Zcal*Zts=Zcal*(T1+jT2)=[(T1+jT2)/(Cc+jCs)]*Rcal


Therefore, the complex impedance of the tissue can be calculated in response to the measured calibration impedance signal and the measured tissue impedance signal, such that phase and/or time delays of the drive circuitry, measurement circuitry and/or parasitic impedance of tissue are corrected. In some embodiments, the complex impedance of the tissue can be determined from the complex ratio of the complex tissue impedance signal over the complex calibration impedance signal times the resistance of the calibration resistor. The changes in the current applied to the tissue with the drive circuitry and changes in the gain of the measurement circuitry can be corrected by repeating the above measurements and calculations at additional frequencies. As the impedance of the calibration circuitry, for example the calibration resistor, remains substantially constant at different measurement frequencies these additional measurements can provide very accurate measurements of tissue impedance at many frequencies.


Although the complex calibration impedance measurements and complex tissue impedance measurements are explained with reference to digital transforms, similar results can be obtained with known methods using lock-in detection and/or synchronous demodulation. In some embodiments, lock-in detection with first and second lock-in amplifiers can be driven at the measurement frequency, in which the first and second lock-in amplifiers are phase shifted by ninety degrees to obtain the real and imaginary components, respectively, of the measured impedance signal. A switch, as described above, can select the calibration circuitry or the tissue electrodes for measurement with the phase shifted lock-in amplifiers.



FIG. 2B shows an inverse frequency response of the drive circuitry 210 and measurement circuitry 250. Drive circuitry 210 generates a drive current 211. Measurement circuitry 250 comprises a gain 251. A safety threshold 213 is shown that corresponds to known safe current requirements, for example AAMI ES1 requirements. Drive current 211 is below a safety threshold 213. Drive current 211, safety threshold 213 and gain 211 change with frequency. At a first frequency 215, for example about 1 kHz, safety threshold 213 corresponds to about 10 μA. Safety threshold 213 corresponds to about 10 μA for frequencies below 1 kHz. From about 1 kHz to about 100 kHz, threshold 213 increases by about 10 μA per decade from about 1 kHz to about 100 kHz. At frequencies above about 100 kHz, for example from 100 kHz to 1 MHz, safety threshold 213 comprises a safe currently limit of about 1000 μA or 1 mA. As drive current 211 increase from first frequency 211 to a second frequency 217, for example 10 kHz, drive current 213 increases substantially, for example about an order of magnitude, such that the drive current at the second frequency is above the safety threshold at the first frequency. As drive frequency 211 increases above 1 kHz, gain 251 of the measurement circuitry decreases. In specific embodiments, gain 251 is about 100 at first frequency 215 of about 1 kHz and gain 251 is about 10 at second frequency 217 of about 10 kHz. The total system gain of the impedance circuitry can be defined as the product of the drive current times the measurement circuitry. The inverse frequency response of the drive circuitry and measurement circuitry is such that the total system gain is substantially uniform, for example to within 25%, over from the first frequency to the second frequency, even though the drive current increase by at least a factor of two, for example by a factor of 10. Therefore, the impedance circuitry provides a substantially uniform total system gain when the drive current at higher frequency exceeds a safety threshold at the lower frequency.



FIG. 3A shows circuitry 300 for measuring patient impedance with an impedance converter, according to embodiments of the present invention. The impedance converter circuitry can be configured to determine tissue impedance with a four point measurement technique comprising a grounded unknown impedance and distributed parasitic impedance. In many embodiments, circuitry 300 comprises an impedance converter 302. Impedance converter 302 may comprise a known impedance converter, for example an Analog Devices AD5934 and/or AD5933. Circuitry 300 comprises drive circuitry 310, calibration circuitry 304, measurement circuitry 320 and processor circuitry 350. In many embodiments, measurement circuitry 300 can be used to separate the excitation signal from the measurement signal in the AD5934. In many embodiments, measurement of the impedance is grounded, such that any distributed parasitic impedance can be factored out.


Drive circuitry 310 may comprise a master clock signal 312, for example from a known 16 MHz oscillator. The oscillator and/or master clock are coupled to a digital data synthesis core, for example DDS core 314. DDS core 314 can generate a digital representation of a waveform. DDS core 314 is coupled to a digital to analog converter, for example DAC 316. An amplifier 318 is coupled to the output of DAC 316 to provide an excitation voltage at an output 319 of impedance converter 302. Output 317 can be connected to patient protection circuitry, for example network 317 that limits current to the patient in response to frequency, as described above. A parasitic impedance 308 can be distributed among components of circuitry 300 and may comprise capacitance from electrodes coupled to the patient, among other sources.


Calibration circuitry 304 may comprise a resistor 305. Current from the drive circuitry can pass a current through resistor 305 that can be measured to calibrate the system. Current through calibration circuitry 304 that comprises resistor 305 generates a calibration signal 326.


Measurement circuitry 320 comprises an amplifier 322, for example instrumentation amplifier, to measure voltage across resistor 305, such that the current through the resistor can be measured. Measurement circuitry 320 comprises an amplifier 324, for example an instrumentation amplifier, to measure a tissue impedance signal 328. Amplifier 322 and amplifier 324 are coupled to a switch 330. Switch 330 can select amplifier 322 or amplifier 324. A control signal 331 to switch 330 can select output of amplifier 322 or output of amplifier 324 for further processing with the impedance converter. In some embodiments, the output of amplifier 322 and the output of amplifier 324 can be measured in parallel, for example with two digital to analog converters on a processor. The output of switch 330 is coupled to a resistor 332 to convert the output voltage from the selected amplifier, either amplifier 322 or amplifier 324, to current that is measured with components of impedance converter 302. Impedance converter 302 may comprise components of measurement circuitry 320 such as an amplifier 334, a selectable gain 336, a low pass filter 338 and an analog to digital converter, for example ADC 340. Amplifier 334 comprises a current follower that converts an input current to a voltage. Selectable gain 336 may comprise switches to select a 1× or 5× gain from amplifier 334. Low pass filter 338 may comprise a known low pass filter to pass low frequencies and inhibit high frequencies. ADC 340 may comprise a known ADC with 12 bit resolution.


Circuitry 300 comprises processor circuitry 350, for example circuitry on an AD 5934 that processes signals from ADC 340. Processor circuitry 350 may comprise 1024-point DFT circuitry 356 to compute the discrete Fourier transform of the signal. In some embodiments, circuitry 300 can be configured to provide 1024 samples for 256 cycles at the selected excitation frequency, such that the data are sampled four times, or quadrature sampled, for each cycle at the measurement frequency. A real register 352 comprises memory that stores the real component of the 1024 point DFT from circuitry 356. An imaginary register 354 comprises memory that stores the imaginary component of the 1024 point DFT from circuitry 356. An interface 358 allows another device, such as microcontroller, to access the real and imaginary components written in memory. The real and imaginary components of the DFT can be processed to determine the tissue impedance in response to the DFT of calibration signal 326 and the DFT of the tissue impedance signal 328. The real and imaginary components of the DFT of calibration signal 326 may comprise a complex calibration signal, and the real and imaginary components of the DFT of the tissue impedance signal 328 may comprise a complex tissue signal. The impedance of the tissue can be determined by computing the complex ratio of the complex tissue signal over the complex calibration signal time and multiplying the complex ratio by the resistance of calibration resistor 305.


Impedance converter 302 may comprise as an synchronous exciter/voltmeter that drives a series connected combination of calibration resistor 305 and tissue impedance 306 and one or more parasitic impedances 308 with a substantially fixed voltage. To determine the tissue impedance, impedance converter 302 can be commanded to make two measurements, one across the calibration resistor 305, and one across the tissue impedance 306. Instrumentation amplifier inputs and/or outputs can be switched accordingly for each measurement with switch 330. Since substantially the same current flows through both components, the relative phasor voltage across each is proportional to the impedance. A current sensing component may comprise calibration resistor 305 so as to give a reference phase angle of zero degrees. By simply computing the complex ratio of the real and imaginary components of complex tissue signal over the real and imaginary components of the complex calibration signal, and multiplying by the resistance value of resistor 305, the complex tissue impedance can be determined. In some embodiments, the excitation voltage may be replaced with a controlled excitation current such that measurement of voltage across the calibration resistor can be replaced with the constant current. This constant current method may use a complex energy efficient bipolar voltage to current converter. The constant voltage method and constant drive current can factor out distributed parasitic impedances, since the impedances are in series and current is consistent through all the impedances. In addition to the benefits described above, these methods easily allow one side of the load to be at either DC or AC ground and do not require a finite DC resistance return path.



FIG. 3B shows an equivalent circuit 390 that may comprise a model for measuring tissue impedance with circuitry 300 that shows components that contribute to the impedance measurements. Drive circuitry 310 and network 317 pass the drive current through the calibration circuitry comprising calibration resistor 305. Calibration impedance signal 326 corresponds to a voltage across the resistor. At least four electrodes that can couple the patient tissue to the circuit include electrode 362, electrode 364, electrode 366 and electrode 368. Electrode 362 and electrode 368 may comprise at least two drive electrodes to pass current through the tissue. Electrode 364 and electrode 366 may comprise at least two measurement electrodes. Tissue impedance signal 328 may correspond to a voltage measured between the at least two measurement electrodes comprising electrode 364 and electrode 366. At least four parasitic tissue impedances comprise parasitic impedance 372, parasitic impedance 374, parasitic impedance 376, and parasitic impedance 378. A tissue of interest 380 may comprise a tissue below the skin of the patient, for which tissue hydration can be determined based on the impedance. The drive current passed through electrode 632 and electrode 368 generates a voltage signal 382 across tissue of interest 380.


Measurement of the impedance of tissue of interest 380 can be affected by a significant number of uncontrolled series impedances, such as the at least four parasitic impedances. In addition, patient protection circuit comprising network 317 that limits maximum applied current as a function of frequency introduces a frequency dependent excitation voltage and may also introduce a non-zero equivalent series impedance. In many embodiments, an assumption about circuit 390 may comprise that Vu is measured by a very high input impedance amplifier, for example an instrumentation amplifier, so that any sensing channel parasitic series impedance is negligible in comparison.



FIG. 3C shows an equivalent circuit 395 of a model that is similar to the model of FIG. 3B and allows for correction of parasitic impedance. For analysis simplification, many of the parasitic impedances of FIG. 3B can be lumped into a single value of lumped parasitic impedance 396. With this method, the tissue impedance signal 328 may more closely correspond to the voltage signal 382 across tissue of interest 380. Equivalent circuit 395 shows lumped parasitic impedance 396 connected to ground, although the lumped parasitic impedance can be disposed anywhere in the series circuit as needed during analysis, for example to determine worst case operating conditions. In many embodiments, one can assume that the excitation voltage corresponding to the drive current is whatever voltage is available between ground and the high-side of the calibration resistor.


When making Vr and Vu differential voltage measurements with the instrumentation amplifiers, a significant common mode component of the excitation signal may be present at the instrumentation amplifier input. Known instrumentation amplifiers with high common mode rejection ratios, and appropriate known models can be used to select the instrumentation amplifiers in the measurement circuitry.


The four point, or four electrode, method of measuring voltage across the series connected calibration resistor and series connected tissue impedance produces a maximum analog to digital conversion signal when the unknown impedance is large. The largest calibration resistor voltage, Vr, may occur when the unknown tissue impedance is zero ohms. The value of calibration resistor can be chosen during design, so that saturation of the calibration signal and tissue measurement signal does not occur. The tissue impedance can be from about 50 to 100 ohms. The calibration resistance may be about twice the maximum tissue impedance, for example about 200 ohms. The measurable limits of impedance, the impedance resolution limits, the gains of each of the impedance converter and instrumentation amplifier stages and the effects of parasitic impedance on measurement limits can be calculated using known engineering analysis techniques to determine an optimal configuration of the circuitry components for resolution and dynamic range.



FIG. 4 shows a method 400 of measuring patient impedance. Method 400 can be implemented with the impedance converter, processor and/or circuits shown above. In specific embodiments, the processor comprises a tangible medium configured to perform method 400. A step 405 selects a frequency. The selected frequency is within a range from about DC to about 1 Mhz, and can be from about 100 Hz to about 100 kHz.


A step 410 selects calibration, for example by configuring switches coupled to the drive circuitry and measurement circuitry, such that the calibration circuitry is measurement with the drive circuitry and measurement circuitry. The calibration circuitry can be selected with switches such that on board calibration circuitry located on the measurement device is selected. The calibration circuitry may comprise a resistor, such that the selected calibration circuitry substantially comprises a resistance with very little reactance. The resistance of the calibration circuitry may comprises a known resistance, for example a DC resistance from a resistor, that is used as a calibration value stored on the processor and/or impedance converter. A step 415 generates a source signal. The source signal is generated at the selected frequency. The source signal generally comprises a time base that is synchronous with the digitization/detection circuitry to determine both amplitude and phase of the measurement signal. A step 420 samples the impedance signal such that the calibration circuitry is measured at the selected frequency. The drive electronics, measurement electronics and time delay, for example phase lag, of the system electronics are calibrated with the selected frequency. As the calibration circuitry substantially comprises a resistance, most of the phase of the measured calibration signal can be attributed to delays in the drive circuitry and the measurement circuitry. The impedance signal sampled from the resistance circuitry can be digitized with an A/D converter and may comprise quadrature sampling of about 1024 data points at the selected frequency for about 256 full cycles. The cosine and sine transforms of the impedance signal can be calculated to determine the complex impedance of the calibration signal. The complex impedance of the calibration signal can then be multiplied and/or divided by the known calibration value, for example known impedance of the calibration resistor, to determine the real and imaginary components of the complex calibration coefficient. A step 425 determines the complex calibration coefficients. The complex calibration coefficients generally comprise a magnitude that corresponds to the resistance of the calibration circuitry and a phase that corresponds to delays in the drive circuitry and measurement circuitry.


A step 430 selects tissue, for example by configuring the switches coupled to the drive circuitry and measurement circuitry, such that an outer two of the at least four electrodes are coupled to the drive circuitry to pass current through the tissue and an inner two, or remaining two, of the at least four electrodes are coupled to the measurement circuitry to measure an impedance signal from the tissue. A step 440 samples the impedance of the tissue. The impedance signal from the sampled tissue can be digitized with an A/D converter and may comprise quadrature sampling of about 1024 data points at the selected frequency for about 256 full cycles. The cosine and sine transforms of the impedance signal can be calculated to determine the complex impedance of the tissue signal. The complex impedance of the tissue signal can then be multiplied and/or divided by the complex calibration coefficients to determine the impedance of the tissue. This use of complex impedance calibration coefficients, based on a known resistance in the calibration circuitry, can cause inaccuracies of the gain and phase of the drive and measurement circuitry to drop out of the calculated tissue impedance, such that the determined tissue impedance corresponds to the actual impedance of the tissue. A step 445 determines the tissue impedance in response to the complex impedance calibration coefficients and the complex impedance of the tissue signal, for example with complex multiplication.


A step 450 determines whether the tissue impedance is within a calibration tolerance. For example, the processor may check to determine whether the tissue impedance is within 20% of the calibration circuitry and/or within 20% of a previous tissue measurement. A step 455 repeats calibration. Calibration can be repeated with the calibration circuitry, as described above, for example in response to the tissue measurement outside the tolerance range. A step 460 repeats the tissue measurement. The tissue measurement may be repeated when the calibration step is repeated.


A step 465 selects a new frequency, for example a second frequency greater than the first frequency. In many embodiments, the amount of injected current will increase above a safety threshold of the current injected at the first frequency, and the gain will decrease, for example with an inverse frequency response, such that the signal remains within the range of the A/D converter. New calibration and tissue measurements are taken at the new frequency. The impedance signal of the calibration circuitry can be measured at the new frequency to determine the complex calibration coefficients, as described above, at the second frequency. One will appreciate that a resistor will have a substantially fixed resistance at the new frequencies, such that the resistance, for example the real calibration value, of the calibration circuitry may be the same at the second frequency as the first frequency. Therefore, changes in the measured calibration signal can be substantially attributed to changes in the drive current of the drive circuitry and/or gain and time delay measurement circuitry. The tissue impedance signal at the new frequency can be determined with the complex calibration coefficient and complex tissue signal. Steps 465 and 470 can be repeated to measure impedance and hydration at many frequencies.


It should be appreciated that the specific steps illustrated in FIG. 4 provide a particular method of measuring impedance of a patient, according to an embodiment of the present invention. Other sequences of steps may also be performed according to alternative embodiments. For example, alternative embodiments of the present invention may perform the steps outlined above in a different order. Moreover, the individual steps illustrated in FIG. 4 may include multiple sub-steps that may be performed in various sequences as appropriate to the individual step. Furthermore, additional steps may be added or removed depending on the particular applications. One of ordinary skill in the art would recognize many variations, modifications, and alternatives. For example, although the processor system and circuitry, as described above, can perform the method 400, additional analog circuits may be used, for example lock-in detection and synchronous demodulation circuits.


While the exemplary embodiments have been described in some detail, by way of example and for clarity of understanding, those of skill in the art will recognize that a variety of modifications, adaptations, and changes may be employed. Hence, the scope of the present invention should be limited solely by the appended claims.

Claims
  • 1. A device for measuring an impedance of a tissue of a patient, the device comprising: calibration circuitry comprising an impedance;at least four electrodes configured to couple to the tissue of the patient, the at least four electrodes comprising at least two measurement electrodes and at least two drive electrodes;drive circuitry coupled to the at least two drive electrodes and the calibration circuitry to pass a current through the tissue and the calibration circuitry simultaneously, the drive circuitry configured to increase the current from a first current amount at a first frequency to a second current amount at a second frequency, the second frequency greater than the first frequency;measurement circuitry configured to couple to the at least two measurement electrodes and the calibration circuitry, the measurement circuitry configured to measure a calibration signal from the calibration circuitry and a tissue impedance signal from the at least two measurement electrodes; andprocessor circuitry comprising a tangible medium configured to determine the impedance of the tissue in response to the calibration signal and the tissue impedance signal.
  • 2. The device of claim 1 wherein the processor circuitry comprises as least one of an impedance converter or a microcontroller.
  • 3. The device of claim 1 wherein the processor circuitry is configured to determine the impedance of the tissue with a discrete Fourier transform of at least one of measurement signal or the current signal.
  • 4. The device of claim 1 wherein the calibration circuitry is connected in series between the drive circuitry and the at least two measurement electrodes to calibrate the tissue impedance measurement when the at least two electrodes are connected to the patient.
  • 5. The device of claim 1 wherein the drive circuitry is configured to pass the current through the tissue and the calibration circuitry to generate the tissue measurement signal and the calibration signal when the at least four electrodes are connected to the tissue.
  • 6. The device of claim 5 wherein the calibration circuitry comprises a calibration resistor, and the measurement circuitry is configured to measure the calibration signal in response to the current through the calibration resistor and the tissue.
  • 7. The device of claim 6 wherein the measurement circuitry is configured to measure the tissue measurement signal in response to the current through the tissue and the calibration resistor.
  • 8. The device of claim 7 wherein the processor is configured to determine the tissue impedance in response to the calibration signal and the tissue measurement signal.
  • 9. The device of claim 1 further comprising at least one switch coupled to the drive circuitry, the measurement circuitry, the calibration circuitry and the at least four electrodes, the at least one switch comprising a first configuration and a second configuration, wherein in the first configuration the at least one switch couples the measurement circuitry to the calibration circuitry to measure the calibration signal and wherein in the second configuration the at least one switch couples the measurement circuitry to the at least two measurement electrodes to measure the tissue impedance signal.
  • 10. The device of claim 9, wherein the processor circuitry is coupled to the at least one switch to select the first configuration or the second configuration.
  • 11. The device of claim 1, wherein the measurement circuitry comprises a first measurement circuit configured to measure the calibration signal and a second measurement circuit configured to measure the tissue impedance signal.
  • 12. The device of claim 1, wherein the calibration circuitry comprises at least one resistor connected in series to the drive circuitry and the at least two drive electrodes, such that a resistance of the resistor corresponds to at least 90% the impedance of the calibration circuitry.
  • 13. The device of claim 1, wherein the calibration circuitry comprises a resistance, wherein the calibration signal comprises a complex calibration signal, wherein the tissue impedance signal comprises a complex tissue impedance signal, and wherein the processor is configured to determine a complex impedance of the tissue in response to the complex calibration signal and the complex tissue impedance signal.
  • 14. The device of claim 1, wherein the processor is configured to store a calibration value comprising a resistance of the calibration circuitry that corresponds to a real number, and wherein the calibration signal corresponds to the resistance of the calibration circuitry, delays of the drive circuitry and delays of the measurement circuitry.
  • 15. The device of claim 14, wherein the processor is configured to determine a complex calibration coefficient in response to the calibration value and the calibration signal.
  • 16. The device of claim 15, wherein the tissue impedance comprises a complex tissue impedance and processor is configured to determine the complex tissue impedance in response to the complex calibration coefficient and the tissue impedance signal.
  • 17. The device of claim 16, wherein the processor is configured to determine a complex tissue parameter from the tissue impedance signal and wherein the processor is configured to determine the complex tissue impedance with at least one of a complex multiplication or a complex division of the complex calibration coefficient and the complex tissue parameter.
  • 18. The device of claim 17, wherein the processor is configured to determine the complex tissue parameter with a discrete Fourier transform of the tissue impedance signal and determine the complex calibration coefficient with a discrete Fourier transform of the calibration signal.
  • 19. The device of claim 14, wherein the delays of the drive circuitry and the measurement circuitry correspond to a phase angle of the calibration signal of at least about 90 degrees.
  • 20. The device of claim 1, wherein the processor is configured to select a first frequency and a second frequency to measure impedance signals of the calibration circuitry at each of the first frequency and the second frequency, and configured to measure impedance signals of the tissue at each of the first frequency and the second frequency.
  • 21. The device of claim 20, wherein the processor is configured to determine impedance of the tissue at the each of the first frequency and the second frequency in response to impedance signals of the calibration circuitry measured at each of the first frequency and the second frequency and impedance signals of the tissue measured at each of the first frequency and the second frequency.
  • 22. The device of claim 1, wherein the processor is configured to store a tolerance range and measure the calibration circuitry in response to the impedance signal of the tissue and the tolerance range.
  • 23. The device of claim 22, wherein the tolerance range comprises plus or minus twenty percent of a baseline tissue impedance measurement and the processor is configured to measure the calibration circuitry in response to the tissue impedance outside the tolerance range.
  • 24. A device for measuring an impedance of a tissue of a patient, the device comprising: at least four electrodes configured to couple to the tissue of the patient, the at least four electrodes comprising at least two drive electrodes and at least two measurement electrodes;drive circuitry coupled to the at least two drive electrodes to pass a variable current through the tissue to generate a tissue measurement signal, the drive circuitry configured to increase the current from a first current amount at a first frequency to a second current amount at a second frequency, the second frequency greater than the first frequency; andmeasurement circuitry coupled to the at least two measurement electrodes to determine the impedance of the tissue in response to the tissue measurement signal, the measurement circuitry comprising a variable gain of the measurement signal configured to decrease from a first gain at the first frequency to a second gain at the second frequency.
  • 25. The device of claim 24, wherein the variable current of the drive circuitry comprises a drive current frequency response and the variable gain of the measurement circuitry comprises variable gain frequency response and wherein the variable gain frequency response comprises an inverse of the drive current frequency response.
  • 26. The device of claim 24, wherein the drive circuitry is configured to increase the second current amount to at least four times the first current amount and wherein the measurement circuitry is configured to decrease the second gain to no more than about one half of the first gain.
  • 27. The device of claim 24, wherein the drive circuitry is configured to increase the second current amount to at least ten times the first current amount and wherein the measurement circuitry is configured to decrease the second gain to no more than about one third of the first gain.
  • 28. The device of claim 24, wherein the second frequency is at least 1 kHz and the second current amount is at least 10 μA and no more than 1000 μA and wherein the first frequency corresponds to a first safety threshold of the first current and the second frequency corresponds to a second safety threshold of the second current and wherein the drive circuitry is configured to exceed the first safety threshold with the second current amount and not to exceed the second safety threshold with the second current amount.
  • 29. The device of claim 28 wherein the drive circuitry is configured to exceed the first safety threshold with the second current by at least a factor of two.
  • 30. The device of claim 28 wherein the safety threshold of the first current corresponds to 10 μA or a product of the first current in μA times the first frequency in kHz, whichever is greater.
  • 31. A method of measuring patient impedance, the method comprising: providing at least four electrodes comprising at least two drive electrodes and at least two measurement electrodes, the at least two drive electrodes connected in series to a calibration resistor;providing measurement circuitry to measure a tissue impedance signal from the measurement electrodes;passing a drive current through the patient impedance and the calibration resistor simultaneously with the drive circuitry, wherein the drive circuitry increases the drive current through the patient as a frequency of the drive current increases;measuring a current signal from the calibration resistor in response to the current through the calibration resistor;measuring the tissue impedance signal from the measurement electrodes; anddetermining the tissue impedance in response to the current signal and the tissue impedance signal.
  • 32. The method of claim 31 wherein the current signal from the calibration resistor is measured with the measurement circuitry.
  • 33. The method of claim 31 wherein the tissue impedance is determined with an impedance converter.
  • 34. The method of claim 33 wherein the current signal from the calibration resistor comprises a first voltage that is converted into a first current and the first current is fed into the impedance converter and wherein the tissue impedance signal from the measurement electrodes comprises a second voltage that is converted to a second current and the second current fed into the impedance converter.
  • 35. The method of claim 33 wherein the drive circuitry comprises a network to limit the drive current through the patient.
  • 36. The method of claim 35 wherein the measurement circuitry comprises a variable gain that decreases when the frequency is increases and the drive current increases.
  • 37. The device of claim 1, wherein the devices places the calibration circuitry in series with the tissue impedance.
  • 38. The method of claim 31, wherein the calibration circuitry and the patient impedance are placed in series.
CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims the benefit under 35 USC 119(e) of U.S. Provisional Application No. 61/046,221 filed Apr. 18, 2008; the full disclosure of which is incorporated herein by reference in its entirety.

US Referenced Citations (734)
Number Name Date Kind
834261 Chambers Oct 1906 A
2087124 Smith et al. Jul 1937 A
2184511 Bagno et al. Dec 1939 A
3170459 Phipps et al. Feb 1965 A
3232291 Parker Feb 1966 A
3370459 Cescati Feb 1968 A
3517999 Weaver Jun 1970 A
3620216 Szymanski Nov 1971 A
3677260 Funfstuck et al. Jul 1972 A
3805769 Sessions Apr 1974 A
3845757 Weyer Nov 1974 A
3874368 Asrican Apr 1975 A
3882853 Gofman et al. May 1975 A
3942517 Bowles et al. Mar 1976 A
3972329 Kaufman Aug 1976 A
4008712 Nyboer Feb 1977 A
4024312 Korpman May 1977 A
4077406 Sandhage et al. Mar 1978 A
4121573 Crovella et al. Oct 1978 A
4141366 Cross, Jr. et al. Feb 1979 A
RE30101 Kubicek et al. Sep 1979 E
4185621 Morrow Jan 1980 A
4216462 McGrath et al. Aug 1980 A
4300575 Wilson Nov 1981 A
4308872 Watson et al. Jan 1982 A
4358678 Lawrence Nov 1982 A
4409983 Albert Oct 1983 A
4450527 Sramek May 1984 A
4451254 Dinius et al. May 1984 A
4478223 Allor Oct 1984 A
4498479 Martio et al. Feb 1985 A
4522211 Bare et al. Jun 1985 A
4661103 Harman Apr 1987 A
4664129 Helzel et al. May 1987 A
4669480 Hoffman Jun 1987 A
4673387 Phillips et al. Jun 1987 A
4681118 Asai et al. Jul 1987 A
4692685 Blaze Sep 1987 A
4699146 Sieverding Oct 1987 A
4721110 Lampadius Jan 1988 A
4730611 Lamb Mar 1988 A
4733107 O'Shaughnessy et al. Mar 1988 A
4781200 Baker Nov 1988 A
4793362 Tedner Dec 1988 A
4838273 Cartmell Jun 1989 A
4838279 Fore Jun 1989 A
4850370 Dower Jul 1989 A
4880004 Baker, Jr. et al. Nov 1989 A
4895163 Libke et al. Jan 1990 A
4911175 Shizgal Mar 1990 A
4945916 Kretschmer et al. Aug 1990 A
4955381 Way et al. Sep 1990 A
4966158 Honma et al. Oct 1990 A
4981139 Pfohl Jan 1991 A
4988335 Prindle et al. Jan 1991 A
4989612 Fore Feb 1991 A
5001632 Hall-Tipping Mar 1991 A
5012810 Strand et al. May 1991 A
5025791 Niwa Jun 1991 A
5027824 Dougherty et al. Jul 1991 A
5050612 Matsumura Sep 1991 A
5063937 Ezenwa et al. Nov 1991 A
5080099 Way et al. Jan 1992 A
5083563 Collins Jan 1992 A
5086781 Bookspan Feb 1992 A
5113869 Nappholz et al. May 1992 A
5125412 Thornton Jun 1992 A
5133355 Strand et al. Jul 1992 A
5140985 Schroeder et al. Aug 1992 A
5150708 Brooks Sep 1992 A
5168874 Segalowitz Dec 1992 A
5226417 Swedlow et al. Jul 1993 A
5241300 Buschmann Aug 1993 A
5257627 Rapoport Nov 1993 A
5271411 Ripley et al. Dec 1993 A
5273532 Niezink et al. Dec 1993 A
5282840 Hudrlik Feb 1994 A
5291013 Nafarrate et al. Mar 1994 A
5297556 Shankar Mar 1994 A
5301677 Hsung Apr 1994 A
5319363 Welch et al. Jun 1994 A
5331966 Bennett et al. Jul 1994 A
5335664 Nagashima Aug 1994 A
5343869 Pross et al. Sep 1994 A
5353793 Bornn Oct 1994 A
5362069 Hall-Tipping Nov 1994 A
5375604 Kelly et al. Dec 1994 A
5411530 Akhtar May 1995 A
5437285 Verrier et al. Aug 1995 A
5443073 Wang et al. Aug 1995 A
5449000 Libke et al. Sep 1995 A
5450845 Axelgaard Sep 1995 A
5454377 Dzwonczyk et al. Oct 1995 A
5464012 Falcone Nov 1995 A
5469859 Tsoglin et al. Nov 1995 A
5482036 Diab et al. Jan 1996 A
5496361 Moberg et al. Mar 1996 A
5503157 Sramek Apr 1996 A
5511548 Riazzi et al. Apr 1996 A
5511553 Segalowitz Apr 1996 A
5518001 Snell May 1996 A
5523742 Simkins et al. Jun 1996 A
5529072 Sramek Jun 1996 A
5544661 Davis et al. Aug 1996 A
5558638 Evers et al. Sep 1996 A
5560368 Berger Oct 1996 A
5564429 Bornn et al. Oct 1996 A
5564434 Halperin et al. Oct 1996 A
5566671 Lyons Oct 1996 A
5575284 Athan et al. Nov 1996 A
5607454 Cameron et al. Mar 1997 A
5632272 Diab et al. May 1997 A
5634468 Platt et al. Jun 1997 A
5642734 Ruben et al. Jul 1997 A
5673704 Marchlinski et al. Oct 1997 A
5678562 Sellers Oct 1997 A
5687717 Halpern et al. Nov 1997 A
5710376 Weber Jan 1998 A
5718234 Warden et al. Feb 1998 A
5724025 Tavori Mar 1998 A
5738107 Martinsen et al. Apr 1998 A
5748103 Flach et al. May 1998 A
5767791 Stoop et al. Jun 1998 A
5769793 Pincus et al. Jun 1998 A
5772508 Sugita et al. Jun 1998 A
5772586 Heinonen et al. Jun 1998 A
5778882 Raymond et al. Jul 1998 A
5788643 Feldman Aug 1998 A
5788682 Maget Aug 1998 A
5803915 Kremenchugsky et al. Sep 1998 A
5807272 Kun Sep 1998 A
5814079 Kieval et al. Sep 1998 A
5817035 Sullivan Oct 1998 A
5833603 Kovacs et al. Nov 1998 A
5836990 Li Nov 1998 A
5855614 Stevens et al. Jan 1999 A
5860860 Clayman Jan 1999 A
5862802 Bird Jan 1999 A
5862803 Besson et al. Jan 1999 A
5865733 Malinouskas et al. Feb 1999 A
5876353 Riff Mar 1999 A
5904708 Goedeke May 1999 A
5935079 Swanson et al. Aug 1999 A
5941831 Turcott Aug 1999 A
5944659 Flach et al. Aug 1999 A
5949636 Johnson et al. Sep 1999 A
5957854 Besson et al. Sep 1999 A
5957861 Combs et al. Sep 1999 A
5964703 Goodman et al. Oct 1999 A
5970986 Bolz et al. Oct 1999 A
5984102 Tay Nov 1999 A
5987352 Klein et al. Nov 1999 A
6007532 Netherly Dec 1999 A
6027523 Schmieding Feb 2000 A
6045513 Stone et al. Apr 2000 A
6047203 Sackner et al. Apr 2000 A
6047259 Campbell et al. Apr 2000 A
6049730 Kristbjarnarson Apr 2000 A
6050267 Nardella et al. Apr 2000 A
6050951 Friedman et al. Apr 2000 A
6052615 Feild et al. Apr 2000 A
6067467 John May 2000 A
6080106 Lloyd et al. Jun 2000 A
6081735 Diab et al. Jun 2000 A
6095991 Krausman et al. Aug 2000 A
6102856 Groff et al. Aug 2000 A
6104949 Pitts Crick et al. Aug 2000 A
6112224 Peifer et al. Aug 2000 A
6117077 Del Mar et al. Sep 2000 A
6125297 Siconolfi Sep 2000 A
6129744 Boute Oct 2000 A
6141575 Price Oct 2000 A
6144878 Schroeppel et al. Nov 2000 A
6164284 Schulman et al. Dec 2000 A
6181963 Chin et al. Jan 2001 B1
6185452 Schulman et al. Feb 2001 B1
6190313 Hinkle Feb 2001 B1
6190324 Kieval et al. Feb 2001 B1
6198394 Jacobsen et al. Mar 2001 B1
6198955 Axelgaard et al. Mar 2001 B1
6208894 Schulman et al. Mar 2001 B1
6212427 Hoover Apr 2001 B1
6213942 Flach et al. Apr 2001 B1
6225901 Kail, IV May 2001 B1
6245021 Stampfer Jun 2001 B1
6259939 Rogel Jul 2001 B1
6267730 Pacunas Jul 2001 B1
6272377 Sweeney et al. Aug 2001 B1
6277078 Porat et al. Aug 2001 B1
6287252 Lugo Sep 2001 B1
6289238 Besson et al. Sep 2001 B1
6290646 Cosentino et al. Sep 2001 B1
6295466 Ishikawa et al. Sep 2001 B1
6305943 Pougatchev et al. Oct 2001 B1
6306088 Krausman et al. Oct 2001 B1
6308094 Shusterman et al. Oct 2001 B1
6312378 Bardy Nov 2001 B1
6315721 Schulman et al. Nov 2001 B2
6327487 Stratbucker Dec 2001 B1
6330464 Colvin et al. Dec 2001 B1
6336903 Bardy Jan 2002 B1
6339722 Heethaar et al. Jan 2002 B1
6343140 Brooks Jan 2002 B1
6347245 Lee et al. Feb 2002 B1
6358208 Lang et al. Mar 2002 B1
6385473 Haines et al. May 2002 B1
6398727 Bui et al. Jun 2002 B1
6400982 Sweeney et al. Jun 2002 B2
6409674 Brockway et al. Jun 2002 B1
6411853 Millot et al. Jun 2002 B1
6416471 Kumar et al. Jul 2002 B1
6440069 Raymond et al. Aug 2002 B1
6442422 Duckert Aug 2002 B1
6450820 Palsson et al. Sep 2002 B1
6450953 Place et al. Sep 2002 B1
6453186 Lovejoy et al. Sep 2002 B1
6454707 Casscells, III et al. Sep 2002 B1
6454708 Ferguson et al. Sep 2002 B1
6459930 Takehara et al. Oct 2002 B1
6463328 John Oct 2002 B1
6473640 Erlebacher Oct 2002 B1
6480733 Turcott Nov 2002 B1
6480734 Zhang et al. Nov 2002 B1
6485461 Mason et al. Nov 2002 B1
6490478 Zhang et al. Dec 2002 B1
6491647 Bridger et al. Dec 2002 B1
6494829 New, Jr. et al. Dec 2002 B1
6496715 Lee et al. Dec 2002 B1
6512949 Combs et al. Jan 2003 B1
6520967 Cauthen Feb 2003 B1
6527711 Stivoric et al. Mar 2003 B1
6527729 Turcott Mar 2003 B1
6544173 West et al. Apr 2003 B2
6544174 West et al. Apr 2003 B2
6551251 Zuckerwar et al. Apr 2003 B2
6551252 Sackner et al. Apr 2003 B2
6569160 Goldin et al. May 2003 B1
6572557 Tchou et al. Jun 2003 B2
6572636 Hagen et al. Jun 2003 B1
6577139 Cooper Jun 2003 B2
6577893 Besson et al. Jun 2003 B1
6577897 Shurubura et al. Jun 2003 B1
6579231 Phipps Jun 2003 B1
6580942 Willshire Jun 2003 B1
6584343 Ransbury et al. Jun 2003 B1
6587715 Singer Jul 2003 B2
6589170 Flach et al. Jul 2003 B1
6595927 Pitts-Crick et al. Jul 2003 B2
6595929 Stivoric et al. Jul 2003 B2
6600949 Turcott Jul 2003 B1
6602201 Hepp et al. Aug 2003 B1
6605038 Teller et al. Aug 2003 B1
6611705 Hopman et al. Aug 2003 B2
6611783 Kelly et al. Aug 2003 B2
6616606 Petersen et al. Sep 2003 B1
6622042 Thacker Sep 2003 B1
6636754 Baura et al. Oct 2003 B1
6641542 Cho et al. Nov 2003 B2
6645153 Kroll et al. Nov 2003 B2
6649829 Garber et al. Nov 2003 B2
6650917 Diab et al. Nov 2003 B2
6658300 Govari et al. Dec 2003 B2
6659947 Carter et al. Dec 2003 B1
6659949 Lang et al. Dec 2003 B1
6687540 Marcovecchio Feb 2004 B2
6697658 Al-Ali Feb 2004 B2
RE38476 Diab et al. Mar 2004 E
6699200 Cao et al. Mar 2004 B2
6701271 Willner et al. Mar 2004 B2
6714813 Ishigooka et al. Mar 2004 B2
RE38492 Diab et al. Apr 2004 E
6721594 Conley et al. Apr 2004 B2
6728572 Hsu et al. Apr 2004 B2
6748269 Thompson et al. Jun 2004 B2
6749566 Russ Jun 2004 B2
6751498 Greenberg et al. Jun 2004 B1
6760617 Ward et al. Jul 2004 B2
6773396 Flach et al. Aug 2004 B2
6775566 Nissila Aug 2004 B2
6790178 Mault et al. Sep 2004 B1
6795722 Sheraton et al. Sep 2004 B2
6814706 Barton et al. Nov 2004 B2
6816744 Garfield et al. Nov 2004 B2
6821249 Casscells, III et al. Nov 2004 B2
6824515 Suorsa et al. Nov 2004 B2
6827690 Bardy Dec 2004 B2
6829503 Alt Dec 2004 B2
6858006 MacCarter et al. Feb 2005 B2
6871211 Labounty et al. Mar 2005 B2
6878121 Krausman et al. Apr 2005 B2
6879850 Kimball Apr 2005 B2
6881191 Oakley et al. Apr 2005 B2
6887201 Bardy May 2005 B2
6890096 Tokita et al. May 2005 B2
6893396 Schulze et al. May 2005 B2
6894204 Dunshee May 2005 B2
6906530 Geisel Jun 2005 B2
6912414 Tong Jun 2005 B2
6936006 Sabra Aug 2005 B2
6940403 Kail, IV Sep 2005 B2
6942622 Turcott Sep 2005 B1
6952695 Trinks et al. Oct 2005 B1
6970742 Mann et al. Nov 2005 B2
6972683 Lestienne et al. Dec 2005 B2
6978177 Chen et al. Dec 2005 B1
6980851 Zhu et al. Dec 2005 B2
6980852 Jersey-Willuhn et al. Dec 2005 B2
6985078 Suzuki et al. Jan 2006 B2
6987965 Ng et al. Jan 2006 B2
6988989 Weiner et al. Jan 2006 B2
6993378 Wiederhold et al. Jan 2006 B2
6997879 Turcott Feb 2006 B1
7003346 Singer Feb 2006 B2
7009362 Tsukamoto et al. Mar 2006 B2
7010340 Scarantino et al. Mar 2006 B2
7018338 Vetter et al. Mar 2006 B2
7020508 Stivoric et al. Mar 2006 B2
7027862 Dahl et al. Apr 2006 B2
7041062 Friedrichs et al. May 2006 B2
7044911 Drinan et al. May 2006 B2
7047067 Gray et al. May 2006 B2
7050846 Sweeney et al. May 2006 B2
7054679 Hirsh May 2006 B2
7059767 Tokita et al. Jun 2006 B2
7088242 Aupperle et al. Aug 2006 B2
7113826 Henry et al. Sep 2006 B2
7118531 Krill Oct 2006 B2
7127370 Kelly, Jr. et al. Oct 2006 B2
7129836 Lawson et al. Oct 2006 B2
7130396 Rogers et al. Oct 2006 B2
7130679 Parsonnet et al. Oct 2006 B2
7133716 Kraemer et al. Nov 2006 B2
7136697 Singer Nov 2006 B2
7136703 Cappa et al. Nov 2006 B1
7142907 Xue et al. Nov 2006 B2
7149574 Yun et al. Dec 2006 B2
7149773 Haller et al. Dec 2006 B2
7153262 Stivoric et al. Dec 2006 B2
7156807 Carter et al. Jan 2007 B2
7156808 Quy Jan 2007 B2
7160252 Cho et al. Jan 2007 B2
7160253 Nissila Jan 2007 B2
7166063 Rahman et al. Jan 2007 B2
7167743 Heruth et al. Jan 2007 B2
7184821 Belalcazar et al. Feb 2007 B2
7191000 Zhu et al. Mar 2007 B2
7194306 Turcott Mar 2007 B1
7206630 Tarler Apr 2007 B1
7212849 Zhang et al. May 2007 B2
7215984 Diab et al. May 2007 B2
7215991 Besson et al. May 2007 B2
7238159 Banet et al. Jul 2007 B2
7248916 Bardy Jul 2007 B2
7251524 Hepp et al. Jul 2007 B1
7257438 Kinast Aug 2007 B2
7261690 Teller et al. Aug 2007 B2
7277741 Debreczeny et al. Oct 2007 B2
7284904 Tokita et al. Oct 2007 B2
7285090 Stivoric et al. Oct 2007 B2
7294105 Islam Nov 2007 B1
7295879 Denker et al. Nov 2007 B2
7297119 Westbrook et al. Nov 2007 B2
7318808 Tarassenko et al. Jan 2008 B2
7319386 Collins, Jr. et al. Jan 2008 B2
7336187 Hubbard, Jr. et al. Feb 2008 B2
7346380 Axelgaard et al. Mar 2008 B2
7382247 Welch et al. Jun 2008 B2
7384398 Gagnadre et al. Jun 2008 B2
7390299 Weiner et al. Jun 2008 B2
7395106 Ryu et al. Jul 2008 B2
7423526 Despotis Sep 2008 B2
7423537 Bonnet et al. Sep 2008 B2
7443302 Reeder et al. Oct 2008 B2
7450024 Wildman et al. Nov 2008 B2
7468032 Stahmann et al. Dec 2008 B2
7510699 Black et al. Mar 2009 B2
7660632 Kirby et al. Feb 2010 B2
7701227 Saulnier et al. Apr 2010 B2
7813778 Benaron et al. Oct 2010 B2
7881763 Brauker et al. Feb 2011 B2
7942824 Kayyali et al. May 2011 B1
20010047127 New, Jr. et al. Nov 2001 A1
20020004640 Conn et al. Jan 2002 A1
20020019586 Teller et al. Feb 2002 A1
20020019588 Marro et al. Feb 2002 A1
20020028989 Pelletier et al. Mar 2002 A1
20020032581 Reitberg Mar 2002 A1
20020045836 Alkawwas Apr 2002 A1
20020088465 Hill Jul 2002 A1
20020099277 Harry et al. Jul 2002 A1
20020116009 Fraser et al. Aug 2002 A1
20020123672 Christophersom et al. Sep 2002 A1
20020123674 Plicchi et al. Sep 2002 A1
20020138017 Bui et al. Sep 2002 A1
20020167389 Uchikoba et al. Nov 2002 A1
20020182485 Anderson et al. Dec 2002 A1
20030009092 Parker Jan 2003 A1
20030023184 Pitts-Crick et al. Jan 2003 A1
20030028221 Zhu et al. Feb 2003 A1
20030028327 Brunner et al. Feb 2003 A1
20030045922 Northrop Mar 2003 A1
20030051144 Williams Mar 2003 A1
20030055460 Owens et al. Mar 2003 A1
20030083581 Taha et al. May 2003 A1
20030085717 Cooper May 2003 A1
20030087244 McCarthy May 2003 A1
20030092975 Casscells, III et al. May 2003 A1
20030093125 Zhu et al. May 2003 A1
20030093298 Hernandez et al. May 2003 A1
20030100367 Cooke May 2003 A1
20030105411 Smallwood et al. Jun 2003 A1
20030135127 Sackner et al. Jul 2003 A1
20030143544 McCarthy Jul 2003 A1
20030149349 Jensen Aug 2003 A1
20030181815 Ebner et al. Sep 2003 A1
20030187370 Kodama Oct 2003 A1
20030191503 Zhu et al. Oct 2003 A1
20030212319 Magill Nov 2003 A1
20030221687 Kaigler Dec 2003 A1
20030233129 Matos Dec 2003 A1
20040006279 Arad (Abboud) Jan 2004 A1
20040010303 Bolea et al. Jan 2004 A1
20040014422 Kallio Jan 2004 A1
20040015058 Besson et al. Jan 2004 A1
20040019292 Drinan et al. Jan 2004 A1
20040044293 Burton Mar 2004 A1
20040049132 Barron et al. Mar 2004 A1
20040064133 Miller et al. Apr 2004 A1
20040073094 Baker Apr 2004 A1
20040073126 Rowlandson Apr 2004 A1
20040077954 Oakley et al. Apr 2004 A1
20040100376 Lye et al. May 2004 A1
20040102683 Khanuja et al. May 2004 A1
20040106951 Edman et al. Jun 2004 A1
20040122489 Mazar et al. Jun 2004 A1
20040127790 Lang et al. Jul 2004 A1
20040133079 Mazar et al. Jul 2004 A1
20040133081 Teller et al. Jul 2004 A1
20040134496 Cho et al. Jul 2004 A1
20040143170 DuRousseau Jul 2004 A1
20040147969 Mann et al. Jul 2004 A1
20040152956 Korman Aug 2004 A1
20040158132 Zaleski Aug 2004 A1
20040167389 Brabrand Aug 2004 A1
20040172080 Stadler et al. Sep 2004 A1
20040199056 Husemann et al. Oct 2004 A1
20040215240 Lovett et al. Oct 2004 A1
20040215247 Bolz Oct 2004 A1
20040220639 Mulligan et al. Nov 2004 A1
20040225199 Evanyk et al. Nov 2004 A1
20040225203 Jemison et al. Nov 2004 A1
20040243018 Organ et al. Dec 2004 A1
20040267142 Paul Dec 2004 A1
20050004506 Gyory Jan 2005 A1
20050015094 Keller Jan 2005 A1
20050015095 Keller Jan 2005 A1
20050020935 Helzel et al. Jan 2005 A1
20050027175 Yang Feb 2005 A1
20050027204 Kligfield et al. Feb 2005 A1
20050027207 Westbrook et al. Feb 2005 A1
20050027918 Govindarajulu et al. Feb 2005 A1
20050043675 Pastore et al. Feb 2005 A1
20050054944 Nakada et al. Mar 2005 A1
20050059867 Cheng Mar 2005 A1
20050065445 Arzbaecher et al. Mar 2005 A1
20050065571 Imran Mar 2005 A1
20050070768 Zhu et al. Mar 2005 A1
20050070778 Lackey et al. Mar 2005 A1
20050080346 Gianchandani et al. Apr 2005 A1
20050080460 Wang et al. Apr 2005 A1
20050080463 Stahmann et al. Apr 2005 A1
20050085734 Tehrani Apr 2005 A1
20050091338 de la Huerga Apr 2005 A1
20050096513 Ozguz et al. May 2005 A1
20050113703 Farringdon et al. May 2005 A1
20050124878 Sharony Jun 2005 A1
20050124901 Misczynski et al. Jun 2005 A1
20050124908 Belalcazar et al. Jun 2005 A1
20050131288 Turner et al. Jun 2005 A1
20050137464 Bomba Jun 2005 A1
20050137626 Pastore et al. Jun 2005 A1
20050148895 Misczynski et al. Jul 2005 A1
20050158539 Murphy et al. Jul 2005 A1
20050177038 Kolpin et al. Aug 2005 A1
20050187482 O'Brien et al. Aug 2005 A1
20050187796 Rosenfeld et al. Aug 2005 A1
20050192488 Bryenton et al. Sep 2005 A1
20050197654 Edman et al. Sep 2005 A1
20050203433 Singer Sep 2005 A1
20050203435 Nakada Sep 2005 A1
20050203436 Davies Sep 2005 A1
20050203637 Edman et al. Sep 2005 A1
20050206518 Welch et al. Sep 2005 A1
20050215914 Bornzin et al. Sep 2005 A1
20050215918 Frantz et al. Sep 2005 A1
20050228234 Yang Oct 2005 A1
20050228238 Monitzer Oct 2005 A1
20050228244 Banet Oct 2005 A1
20050239493 Batkin et al. Oct 2005 A1
20050240087 Keenan et al. Oct 2005 A1
20050251044 Hoctor et al. Nov 2005 A1
20050256418 Mietus et al. Nov 2005 A1
20050261598 Banet et al. Nov 2005 A1
20050261743 Kroll Nov 2005 A1
20050267376 Marossero et al. Dec 2005 A1
20050267377 Marossero et al. Dec 2005 A1
20050267381 Benditt et al. Dec 2005 A1
20050273023 Bystrom et al. Dec 2005 A1
20050277841 Shennib Dec 2005 A1
20050277842 Silva Dec 2005 A1
20050277992 Koh et al. Dec 2005 A1
20050280531 Fadem et al. Dec 2005 A1
20050283197 Daum et al. Dec 2005 A1
20050288601 Wood et al. Dec 2005 A1
20060004300 Kennedy Jan 2006 A1
20060004377 Keller Jan 2006 A1
20060009697 Banet et al. Jan 2006 A1
20060009701 Nissila et al. Jan 2006 A1
20060010090 Brockway et al. Jan 2006 A1
20060020218 Freeman et al. Jan 2006 A1
20060025661 Sweeney et al. Feb 2006 A1
20060030781 Shennib Feb 2006 A1
20060030782 Shennib Feb 2006 A1
20060031102 Teller et al. Feb 2006 A1
20060041280 Stahmann et al. Feb 2006 A1
20060047215 Newman et al. Mar 2006 A1
20060052678 Drinan et al. Mar 2006 A1
20060058543 Walter et al. Mar 2006 A1
20060058593 Drinan et al. Mar 2006 A1
20060064030 Cosentino et al. Mar 2006 A1
20060064040 Berger et al. Mar 2006 A1
20060064142 Chavan et al. Mar 2006 A1
20060066449 Johnson Mar 2006 A1
20060074283 Henderson et al. Apr 2006 A1
20060074462 Verhoef Apr 2006 A1
20060075257 Martis et al. Apr 2006 A1
20060084881 Korzinov et al. Apr 2006 A1
20060085049 Cory et al. Apr 2006 A1
20060089679 Zhu et al. Apr 2006 A1
20060094948 Gough et al. May 2006 A1
20060102476 Niwa et al. May 2006 A1
20060116592 Zhou et al. Jun 2006 A1
20060122474 Teller et al. Jun 2006 A1
20060135858 Nidd et al. Jun 2006 A1
20060142654 Rytky Jun 2006 A1
20060142820 Von Arx et al. Jun 2006 A1
20060149168 Czarnek Jul 2006 A1
20060155174 Glukhovsky et al. Jul 2006 A1
20060155183 Kroecker et al. Jul 2006 A1
20060155200 Ng Jul 2006 A1
20060161073 Singer Jul 2006 A1
20060161205 Mitrani et al. Jul 2006 A1
20060161459 Rosenfeld et al. Jul 2006 A9
20060167374 Takehara et al. Jul 2006 A1
20060173257 Nagai et al. Aug 2006 A1
20060173269 Glossop Aug 2006 A1
20060195020 Martin et al. Aug 2006 A1
20060195039 Drew et al. Aug 2006 A1
20060195097 Evans et al. Aug 2006 A1
20060195144 Giftakis et al. Aug 2006 A1
20060202816 Crump et al. Sep 2006 A1
20060212097 Varadan et al. Sep 2006 A1
20060224051 Teller et al. Oct 2006 A1
20060224072 Shennib Oct 2006 A1
20060224079 Washchuk Oct 2006 A1
20060235281 Tuccillo Oct 2006 A1
20060235316 Ungless et al. Oct 2006 A1
20060235489 Drew et al. Oct 2006 A1
20060241641 Albans et al. Oct 2006 A1
20060241701 Markowitz et al. Oct 2006 A1
20060241722 Thacker et al. Oct 2006 A1
20060247545 St. Martin Nov 2006 A1
20060252999 Devaul et al. Nov 2006 A1
20060253005 Drinan et al. Nov 2006 A1
20060253044 Zhang et al. Nov 2006 A1
20060258952 Stahmann et al. Nov 2006 A1
20060264730 Stivoric et al. Nov 2006 A1
20060264767 Shennib Nov 2006 A1
20060264776 Stahmann et al. Nov 2006 A1
20060271116 Stahmann et al. Nov 2006 A1
20060276714 Holt et al. Dec 2006 A1
20060281981 Jang et al. Dec 2006 A1
20060281996 Kuo et al. Dec 2006 A1
20060293571 Bao et al. Dec 2006 A1
20060293609 Stahmann et al. Dec 2006 A1
20070010721 Chen et al. Jan 2007 A1
20070010750 Ueno et al. Jan 2007 A1
20070015973 Nanikashvili Jan 2007 A1
20070015976 Miesel et al. Jan 2007 A1
20070016089 Fischell et al. Jan 2007 A1
20070021678 Beck et al. Jan 2007 A1
20070021790 Kieval et al. Jan 2007 A1
20070021792 Kieval et al. Jan 2007 A1
20070021794 Kieval et al. Jan 2007 A1
20070021796 Kieval et al. Jan 2007 A1
20070021797 Kieval et al. Jan 2007 A1
20070021798 Kieval et al. Jan 2007 A1
20070021799 Kieval et al. Jan 2007 A1
20070027388 Chou Feb 2007 A1
20070027497 Parnis Feb 2007 A1
20070032749 Overall et al. Feb 2007 A1
20070038038 Stivoric et al. Feb 2007 A1
20070038078 Osadchy Feb 2007 A1
20070038255 Kieval et al. Feb 2007 A1
20070038262 Kieval et al. Feb 2007 A1
20070043301 Martinsen et al. Feb 2007 A1
20070043303 Osypka et al. Feb 2007 A1
20070048224 Howell et al. Mar 2007 A1
20070060800 Drinan et al. Mar 2007 A1
20070060802 Ghevondian et al. Mar 2007 A1
20070073132 Vosch Mar 2007 A1
20070073168 Zhang et al. Mar 2007 A1
20070073181 Pu et al. Mar 2007 A1
20070073361 Goren et al. Mar 2007 A1
20070082189 Gillette Apr 2007 A1
20070083092 Rippo et al. Apr 2007 A1
20070092862 Gerber Apr 2007 A1
20070104840 Singer May 2007 A1
20070106132 Elhag et al. May 2007 A1
20070106137 Baker, Jr. et al. May 2007 A1
20070106167 Kinast May 2007 A1
20070118039 Bodecker et al. May 2007 A1
20070123756 Kitajima et al. May 2007 A1
20070123903 Raymond et al. May 2007 A1
20070123904 Stad et al. May 2007 A1
20070129622 Bourget et al. Jun 2007 A1
20070129643 Kwok et al. Jun 2007 A1
20070129769 Bourget et al. Jun 2007 A1
20070142715 Banet et al. Jun 2007 A1
20070142732 Brockway et al. Jun 2007 A1
20070149282 Lu et al. Jun 2007 A1
20070150008 Jones et al. Jun 2007 A1
20070150009 Kveen et al. Jun 2007 A1
20070150029 Bourget et al. Jun 2007 A1
20070162089 Mosesov Jul 2007 A1
20070167753 Van Wyk et al. Jul 2007 A1
20070167848 Kuo et al. Jul 2007 A1
20070167849 Zhang et al. Jul 2007 A1
20070167850 Russell et al. Jul 2007 A1
20070172424 Roser Jul 2007 A1
20070173705 Teller et al. Jul 2007 A1
20070180047 Dong et al. Aug 2007 A1
20070180140 Welch et al. Aug 2007 A1
20070191723 Prystowsky et al. Aug 2007 A1
20070207858 Breving Sep 2007 A1
20070208233 Kovacs Sep 2007 A1
20070208235 Besson et al. Sep 2007 A1
20070208262 Kovacs Sep 2007 A1
20070232867 Hansmann Oct 2007 A1
20070244403 Natarajan et al. Oct 2007 A1
20070249946 Kumar et al. Oct 2007 A1
20070250121 Miesel et al. Oct 2007 A1
20070255120 Rosnov Nov 2007 A1
20070255153 Kumar et al. Nov 2007 A1
20070255184 Shennib Nov 2007 A1
20070255531 Drew Nov 2007 A1
20070260133 Meyer Nov 2007 A1
20070260155 Rapoport et al. Nov 2007 A1
20070260289 Giftakis et al. Nov 2007 A1
20070273504 Tran Nov 2007 A1
20070276273 Watson, Jr Nov 2007 A1
20070282173 Wang et al. Dec 2007 A1
20070299325 Farrell et al. Dec 2007 A1
20080004499 Davis Jan 2008 A1
20080004904 Tran Jan 2008 A1
20080021336 Dobak Jan 2008 A1
20080024293 Stylos Jan 2008 A1
20080024294 Mazar Jan 2008 A1
20080033260 Sheppard et al. Feb 2008 A1
20080039700 Drinan et al. Feb 2008 A1
20080058614 Banet et al. Mar 2008 A1
20080058656 Costello et al. Mar 2008 A1
20080059239 Gerst et al. Mar 2008 A1
20080091089 Guillory et al. Apr 2008 A1
20080114220 Banet et al. May 2008 A1
20080120784 Warner et al. May 2008 A1
20080139934 McMorrow et al. Jun 2008 A1
20080146892 LeBoeuf et al. Jun 2008 A1
20080167538 Teller et al. Jul 2008 A1
20080171918 Teller et al. Jul 2008 A1
20080171922 Teller et al. Jul 2008 A1
20080171929 Katims Jul 2008 A1
20080183052 Teller et al. Jul 2008 A1
20080200774 Luo Aug 2008 A1
20080214903 Orbach Sep 2008 A1
20080220865 Hsu Sep 2008 A1
20080221399 Zhou et al. Sep 2008 A1
20080221402 Despotis Sep 2008 A1
20080224852 Dicks et al. Sep 2008 A1
20080228084 Bedard et al. Sep 2008 A1
20080275465 Paul et al. Nov 2008 A1
20080287751 Stivoric et al. Nov 2008 A1
20080287752 Stroetz et al. Nov 2008 A1
20080293491 Wu et al. Nov 2008 A1
20080294019 Tran Nov 2008 A1
20080294020 Sapounas Nov 2008 A1
20080318681 Rofougaran et al. Dec 2008 A1
20080319279 Ramsay et al. Dec 2008 A1
20080319282 Tran Dec 2008 A1
20080319290 Mao et al. Dec 2008 A1
20090005016 Eng et al. Jan 2009 A1
20090018410 Coene et al. Jan 2009 A1
20090018456 Hung Jan 2009 A1
20090048526 Aarts Feb 2009 A1
20090054737 Magar et al. Feb 2009 A1
20090062670 Sterling et al. Mar 2009 A1
20090073991 Landrum et al. Mar 2009 A1
20090076336 Mazar et al. Mar 2009 A1
20090076340 Libbus et al. Mar 2009 A1
20090076341 James et al. Mar 2009 A1
20090076342 Amurthur et al. Mar 2009 A1
20090076343 James et al. Mar 2009 A1
20090076344 Libbus et al. Mar 2009 A1
20090076345 Manicka et al. Mar 2009 A1
20090076346 James et al. Mar 2009 A1
20090076348 Manicka et al. Mar 2009 A1
20090076349 Libbus et al. Mar 2009 A1
20090076350 Bly et al. Mar 2009 A1
20090076363 Bly et al. Mar 2009 A1
20090076364 Libbus et al. Mar 2009 A1
20090076397 Libbus et al. Mar 2009 A1
20090076401 Mazar et al. Mar 2009 A1
20090076405 Amurthur et al. Mar 2009 A1
20090076410 Libbus et al. Mar 2009 A1
20090076559 Libbus et al. Mar 2009 A1
20090177145 Ohlander et al. Jul 2009 A1
20090182204 Semler et al. Jul 2009 A1
20090234410 Libbus et al. Sep 2009 A1
20090292194 Libbus et al. Nov 2009 A1
20100056881 Libbus et al. Mar 2010 A1
20100191310 Bly et al. Jul 2010 A1
20110144470 Mazar et al. Jun 2011 A1
20110245711 Katra et al. Oct 2011 A1
20110270049 Katra et al. Nov 2011 A1
Foreign Referenced Citations (16)
Number Date Country
2003-220574 Oct 2003 AU
1487535 Dec 2004 EP
1579801 Sep 2005 EP
2005-521448 Jul 2005 JP
WO 0079255 Dec 2000 WO
WO 200189362 Nov 2001 WO
WO 02092101 Nov 2002 WO
WO 03082080 Oct 2003 WO
WO 2005051164 Jun 2005 WO
WO 2005104930 Nov 2005 WO
WO 2006008745 Jan 2006 WO
WO 2006102476 Sep 2006 WO
WO 2006111878 Nov 2006 WO
WO 2007041783 Apr 2007 WO
WO 2007106455 Sep 2007 WO
2009116906 Sep 2009 WO
Non-Patent Literature Citations (182)
Entry
International Search Report and Written Opinion of PCT Application No. PCT/US09/41143, dated Jun. 11, 2009, 9 pages total.
AD5934: 250 kSPS 12-Bit Impedance Converter Network Analyzer, Analog Devices, retrieved from the Internet: <<http://www.analog.com/static/imported-files/data—sheets/AD5934.pdf>>, 40 pages.
Something in the way he moves, The Economist, 2007, retrieved from the Internet: <<http://www.economist.com/science/printerFriendly.cfm?story id=9861412>>.
Abraham, “New approaches to monitoring heart failure before symptoms appear,” Rev Cardiovasc Med. 2006 ;7 Suppl 1 :33-41.
Adams, Jr. “Guiding heart failure care by invasive hemodynamic measurements: possible or useful?”, Journal of Cardiac Failure 2002; 8(2):71-73.
Adamson et al., “Continuous autonomic assessment in patients with symptomatic heart failure: prognostic value of heart rate variability measured by an implanted cardiac resynchronization device ,” Circulation. 2004;110:2389-2394.
Adamson et al., “Ongoing right ventricular hemodynamics in heart failure,” J Am Coll Cardiol, 2003; 41:565-57.
Adamson, “Integrating device monitoring into the infrastructure and workflow of routine practice,” Rev Cardiovasc Med. 2006 ;7 Suppl 1:42-6.
Adhere [presentation], “Insights from the ADHERE Registry: Data from over 100,000 patient cases,” 70 pages total, 2005.
Advamed White Sheet, “Health Information Technology: Improving Patient Safety and Quality of Care,” Jun. 2005, 23 pages.
Aghababian, “Acutely decompensated heart failure: opportunities to improve care and outcomes in the emergency department,” Rev Cardiovasc Med. 2002;3 Suppl 4:S3-9.
Albert, “Bioimpedance to prevent heart failure hospitalization,” Curr Heart Fail Rep. Sep. 2006;3(3):136-42.
American Heart Association, “Heart Disease and Stroke Statistics-2006 Update,” 2006, 43 pages.
American Heart Association, “Heart Disease and Stroke Statistics-2007 Update. A Report From the American Heart Association Statistics Committee and Stroke Statistics Subcommittee,” Circulation 2007; 115;e69-e171.
Belalcazar et al., “Monitoring lung edema using the pacemaker pulse and skin electrodes,” Physiol. Meas. 2005; 26:S153-S163.
Bennet, “Development of implantable devices for continuous ambulatory monitoring of central hemodynamic values in heart failure patients,” PACE Jun. 2005; 28:573-584.
Bourge, “Case studies in advanced monitoring with the chronicle device,” Rev Cardiovasc Med. 2006 ;7 Suppl 1:S56-61.
Braunschweig, “Continous haemodynamic monitoring during withdrawal of diuretics in patients with congestive heart failure,” European Heart Journal 2002 23(1):59-69.
Braunschweig, “Dynamic changes in right ventricular pressures during haemodialysis recorded with an implantable haemodynamic monitor ,” Nephrol Dial Transplant 2006; 21:176-183.
Brennan, “Measuring a Grounded Impedance Profile Using the AD5933,” Analog Devices, retrieved from the internet <<http://http://www.analog.com/static/imported-files/application—notes/427095282381510189AN847—0.pdf>>, 12 pages total. 2006.
Buono et al., “The effect of ambient air temperature on whole-body bioelectrical impedance,” Physiol. Meas. 2004;25:119-123.
Burkhoff et al., “Heart failure with a normal ejection fraction: Is it really a disorder of diastolic function?” Circulation 2003; 107:656-658.
Burr et al., “Heart rate variability and 24-hour minimum heart rate,” Biological Research for Nursing, 2006; 7(4):256-267.
Cardionet, “CardioNet Mobile Cardiac Outpatient Telemetry: Addendum to Patient Education Guide”, CardioNet, Inc., 2007, 2 pages.
Cardionet, “Patient Education Guide”, CardioNet, Inc., 2007, 7 pages.
Charach et al., “Transthoracic monitoring of the impedance of the right lung in patients with cardiogenic pulmonary edema,” Crit Care Med Jun. 2001;29(6):1137-1144.
Charlson et al., “Can disease management target patients most likely to generate high costs? The Impact of Comorbidity,” Journal of General Internal Medicine, Apr. 2007, 22(4):464-469.
Chaudhry et al., “Telemonitoring for patients with chronic heart failure: a systematic review,” J Card Fail. Feb. 2007; 13(1): 56-62.
Chung et al., “White coat hypertension: Not so benign after all?,” Journal of Human Hypertension (2003) 17, 807-809.
Cleland et al., “The EuroHeart Failure survey programme—a survey on the quality of care among patients with heart failure in Europe-Part 1: patient characteristics and diagnosis,” European Heart Journal 2003 24(5):442-463.
Cowie et al., “Hospitalization of patients with heart failure. A population-based study,” European Heart Journal 2002 23(11):877-885.
Dimri, Chapter 1: Fractals in geophysics and seimology: an introduction, Fractal Behaviour of the Earth System, Springer Berlin Heidelberg 2005, pp. 1-22. [Summary and 1st page Only].
El-Dawlatly et al., “Impedance cardiography: noninvasive assessment of hemodynamics and thoracic fluid content during bariatric surgery,” Obesity Surgery, May 2005, 15(5):655-658.
Erdmann, “Editorials: The value of diuretics in chronic heart failure demonstrated by an implanted haemodynamic monitor,” European Heart Journal 2002 23(1):7-9.
FDA—Medtronic Inc., Chronicle 9520B Implantable Hemodynamic Monitor Reference Manual, 2007, 112 pages.
FDA Executive Summary Memorandum, prepared for Mar. 1, 2007 meeting of the Circulatory Systems Devices Advisory Panel, P050032 Medtronic, Inc. Chronicle Implantable Hemodynamic Monitor (IHM) System, 23 pages. Retrieved from the Internet: http://www.fda.gov/ohrms/dockets/ac/07/briefing/2007-4284b1—02.pdf>>.
FDA Executive Summary, Medtronic Chronicle Implantable Hemodynamic Monitoring System P050032: Panel Package Sponsor Executive Summary; vol. 1, section 4: Executive Summary. 12 pp. total. Retrieved from the Internet: http://www.fda.gov/Ohrms/Dockets/Ac/07/briefing/2007-4284b1—03.pdf>>.
FDA—Medtronic Chronicle Implantable Hemodynamic Monitoring System P050032: Panel Package Section 11: Chronicle IHM Summary of Safety and Effectiveness, 2007; retrieved from the Internet: <http://www.fda.gov/OHRMS/DOCKETS/AC/07/briefing/2007-4284b1—04.pdf>, 77 pages total.
FDA, Draft questions for Chronicle Advisory Panel Meeting, 3 pages. Retrieved from the Internet: <<http://www.fda.gov/ohrms/dockets/ac/07/questions/2007-4284q1—draft.pdf>>.
FDA, References for Mar. 1 Circulatory System Devices Panel, 2007, 1 page total. Retrieved from the Internet: <<http://www.fda.gov/OHRMS/DOCKETS/AC/07/briefing/2007-4284bib1—01.pdf>>.
FDA Panel Recommendation, “Chronicle Analysis,” Mar. 1, 2007, 14 pages total.
Fonarow et al., “Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis,” JAMA. 2005 Feb. 2, 2005;293(5):572-580.
Fonarow, “How well are chronic heart failure patients being managed?”, Rev Cardiovasc Med. 2006;7 Suppl 1:S3-11.
Fonarow, “Maximizing Heart Failure Care” [Powerpoint Presentation], downloaded from the Internet <<http://www.medreviews.com/media/MaxHFCore.ppt>>, 130 pages total.
Fonarow, “Proactive monitoring and management of the chronic heart failure patient,” Rev Cardiovasc Med. 2006; 7 Suppl 1:S1-2.
Fonarow, “The Acute Decompensated Heart Failure National Registry (ADHERE): opportunities to improve care of patients hospitalized with acute decompensated heart failure,” Rev Cardiovasc Med. 2003;4 Suppl 7:S21-S30.
Ganion et al., “Intrathoracic impedance to monitor heart failure status: a comparison of two methods in a chronic heart failure dog model,” Congest Heart Fail. Jul.-Aug. 2005;11(4):177-81, 211.
Gass et al., “Critical pathways in the management of acute decompensated heart failure: A CME-Accredited monograph,” Mount Sinai School of Medicine, 2004, 32 pages total.
Gheorghiade et al., “Congestion is an important diagnostic and therapeutic target in heart failure,” Rev Cardiovasc Med. 2006 ;7 Suppl 1 :12-24.
Gilliam, III et al., “Changes in heart rate variability, quality of life, and activity in cardiac resynchronization therapy patients: results of the HF-HRV registry,” Pacing and Clinical Electrophysiology, Jan. 18, 2007; 30(1): 56-64.
Gilliam, III et al., “Prognostic value of heart rate variability footprint and standard deviation of average 5-minute intrinsic R-R intervals for mortality in cardiac resynchronization therapy patients.,” J Electrocardiol. Oct. 2007;40(4):336-42.
Gniadecka, “Localization of dermal edema in lipodermatosclerosis, lymphedema, and cardiac insufficiency high-frequency ultrasound examination of intradermal echogenicity,” J Am Acad oDermatol, Jul. 1996; 35(1):37-41.
Goldberg et al., “Randomized trial of a daily electronic home monitoring system in patients with advanced heart failure: The Weight Monitoring in Heart Failure (Wharf) Trial,” American Heart Journal, Oct 2003; 416(4):705-712.
Grap et al., “Actigraphy in the Critically III: Correlation With Activity, Agitation, and Sedation,” American Journal of Critical Care. 2005;14: 52-60.
Gudivaka et al., “Single- and multifrequency models for bioelectrical impedance analysis of body water compartments,” J Appl Physiol, 1999;87(3):1087-1096.
Guyton et al., Unit V: The Body Fluids and Kidneys, Chapter 25: The Body Fluid Compartments: Extracellular and Intracellular Fluids; Interstitial Fluid and Edema, Guyton & Hall Textbook Of Medical Physiology 11th Edition, Saunders 2005; pp. 291-306.
Hadase et al., “Very low frequency power of heart rate variability is a powerful predictor of clinical prognosis in patients with congestive heart Failure,” Circ J 2004; 68(4):343-347.
Hallstrom et al., “Structural relationships between measures based on heart beat intervals: potential for improved risk assessment,” IEEE Biomedical Engineering 2004, 51(8):1414-1420.
HFSA 2006 Comprehensive Heart Failure Practice Guideline—Executive Summary: HFSA 2006 Comprehensive Heart Failure Practice Guideline, Journal of Cardiac Failure 2006;12(1):10-e38.
HFSA 2006 Comprehensive Heart Failure Practice Guideline-Section 12: Evaluation and Management of Patients With Acute Decompensated Heart Failure, Journal of Cardiac Failure 2006;12(1):e86-e103.
HFSA 2006 Comprehensive Heart Failure Practice Guideline-Section 2: Conceptualization and Working Definition of Heart Failure, Journal of Cardiac Failure 2006;12(1):e10-e11. n.
HFSA 2006 Comprehensive Heart Failure Practice Guideline-Section 3: Prevention of Ventricular Remodeling Cardiac Dysfunction, and Heart Failure Overview, Journal of Cardiac Failure 2006;12(1):e12-e15.
HFSA 2006 Comprehensive Heart Failure Practice Guideline-Section 4: Evaluation of Patients for Ventricular Dysfunction and Heart Failure, Journal of Cardiac Failure 2006;12(1):e16-e25.
HFSA 2006 Comprehensive Heart Failure Practice Guideline-Section 8: Disease Management in Heart Failure Education and Counseling, Journal of Cardiac Failure 2006;12(1):e58-e68.
Hunt et al., “ACC/AHA 2005 Guideline Update for the Diagnosis and Management of Chronic Heart Failure in the Adult: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure): Developed in Collaboration With the American College of Chest Physicians and the International Society for Heart and Lung Transplantation: Endorsed by the Heart Rhythm Society,” Circulation. 2005;112e154-e235.
Hunt et al., ACC/AHA Guidelines for the Evaluation and Management of Chronic Heart Failure in the Adult: Executive Summary A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Revise the 1995 Guidelines for the Evaluation and Management of Heart Failure), Circulation. 2001;104:2996-3007.
Imhoff et al., “Noninvasive whole-body electrical bioimpedance cardiac output and invasive thermodilution cardiac output in high-risk surgical patients,” Critical Care Medicine 2000; 28(8):2812-2818.
Jaeger et al., “Evidence for Increased Intrathoracic Fluid volume in Man at High Altitude,” J Appl Physiol 1979; 47(6): 670-676.
Jerant et al., “Reducing the cost of frequent hospital admissions for congestive heart failure: a randomized trial of a home telecare intervention,” Medical Care 2001, 39(11):1234-1245.
Jaio et al., “Variance fractal dimension analysis of seismic refraction signals,” WESCANEX 97: Communications, Power and Computing. IEEE Conference Proceedings., May 22-23, 1997, pp. 163-167 [Abstract Only].
Kasper et al., “A randomized trial of the efficacy of multidisciplinary care in heart failure outpatients at high risk of hospital readmission,” J Am Coll Cardiol, 2002; 39:471-480.
Kaukinen, “Cardiac output measurement after coronary artery bypass grafting using bolus thermodilution, continuous thermodilution, and whole-body impedance cardiography,” Journal of Cardiothoracic and Vascular Anesthesia 2003; 17(2):199-203.
Kawaguchi et al., “Combined ventricular systolic and arterial stiffening in patients with heart failure and preserved ejection fraction: implications for systolic and diastolic reserve limitations,” Circulation. 2003;107:714-720.
Kawasaki et al., “Heart rate turbulence and clinical prognosis in hypertrophic cardiomyopathy and myocardial infarction,” Circ J. Jul. 2003;67(7):601-604.
Kearney et al., “Predicting death due to progressive heart failure in patients with mild-to-moderate chronic heart failure,” J Am Coll Cardiol, 2002; 40(10):1801-1808.
Kitzman et al., “Pathophysiological characterization of isolated diastolic heart failure in comparison to systolic heart failure,” JAMA Nov. 2002; 288(17):2144-2150.
Kööbi et al., “Non-invasive measurement of cardiac output: whole-body impedance cardiography in simultaneous comparison with thermodilution and direct oxygen Fick methods,” Intensive Care Medicine 1997; 23(11):1132-1137.
Koyama et al., “Evaluation of heart-rate turbulence as a new prognostic marker in patients with chronic heart failure,” Circ J 2002; 66(10):902-907.
Krumholz et al., “Predictors of readmission among elderly survivors of admission with heart failure,” American Heart Journal 2000; 139 (1):72-77.
Kyle et al., “Bioelectrical Impedance Analysis-part I: review of principles and methods,” Clin Nutr. Oct. 2004;23(5):1226-1243.
Kyle et al., “Bioelectrical Impedance Analysis-part II: utilization in clinical practice,” Clin Nutr. Oct. 2004;23(5):1430-1453.
Lee et al., “Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model,” JAMA 2003;290(19):2581-2587.
Leier “The Physical Examination in Heart Failure-Part I,” Congest Heart Fail. Jan.-Feb. 2007;13(1):41-47.
Libbus, “BioZ Analysis,” Corventis, Inc., 7 pages. (date unknown).
LifeShirt® Model 200 Directions for Use, “Introduction”, VivoMetrics, Inc. 9 page total.
Liu et al., “Fractal analysis with applications to seismological pattern recognition of underground nuclear explosions,” Singal Processing, Sep. 2000, 80(9):1849-1861. [Abstract Only].
Lozano-Nieto, “Impedance ratio in bioelectrical impedance measurements for body fluid shift determination,” Proceedings of the IEEE 24th Annual Northeast Bioengineering Conference, Apr. 9-10, 1998, pp. 24 -25.
Lucreziotti et al., “Five-minute recording of heart rate variability in severe chronic heart failure : Correlates with right ventricular function and prognostic implications,” American Heart Journal 2000; 139(6):1088-1095.
Lüthje et al., “Detection of heart failure decompensation using intrathoracic impedance monitoring by a triple-chamber implantable defibrillator,” Heart Rhythm Sep. 2005;2(9):997- 999.
Magalski et al., “Continuous ambulatory right heart pressure measurements with an implantable hemodynamic monitor: a multicenter, 12-Month Follow-up Study of Patients With Chronic Heart Failure,” J Card Fail 2002, 8(2):63-70.
Mahlberg et al., “Actigraphy in agitated patients with dementia: Monitoring treatment outcomes,” Zeitschrift für Gerontologie und Geriatrie, Jun. 2007; 40(3)178-184. [Abstract Only].
Matthie et al., “Analytic assessment of the various bioimpedance methods used to estimate body water,” Appl Physiol 1998; 84(5):1801-1816.
Matthie, “Second generation mixture theory equation for estimating intracellular water using bioimpedance spectroscopy,” J Appl Physiol 2005; 99:780-781.
McMurray et al., “Heart Failure: Epidemiology, Aetiology, and Prognosis of Heart Failure,” Heart 2000;83:596-602.
Miller, “Home monitoring for congestive heart failure patients,” Caring Magazine, Aug. 1995: 53-54.
Moser et al., “Improving outcomes in heart failure: it's not unusual beyond usual Care,” Circulation. 2002;105:2810-2812.
Nagels et al., “Actigraphic measurement of agitated behaviour in dementia,” International journal of geriatric psychiatry , 2009; 21(4):388-393. [Abstract Only].
Nakamura et al., “Universal scaling law in human behavioral organization,” Physical Review Letters, Sep. 28, 2007; 99(13):138103 (4 pages).
Nakaya, “Fractal properties of seismicity in regions affected by large, shallow earthquakes in western Japan: Implications for fault formation processes based on a binary fractal fracture network model,” Journal of geophysical research, Jan. 2005; 11(61):B01310.1-B01310.15. [Abstract Only].
Naylor et al., “Comprehensive discharge planning for the hospitalized elderly: a randomized clinical trial ,” Amer. College Physicians 1994; 120(12):999-1006.
Nesiritide (Natrecor),, [Presentation] Acutely Decompensated Congestive Heart Failure: Burden of Disease, downloaded from the Internet: http://www.huntsvillehospital.org/foundation/events/cardiologyupdate/CHF.ppt.>>, 39 pages.
Nieminen et al., “EuroHeart Failure Survey II (EHFS II): a survey on hospitalized acute heart failure patients: description of population,” European Heart Journal 2006; 27(22):2725-2736.
Nijsen et al., “The potential value of three-dimensional accelerometry for detection of motor seizures in severe epilepsy,” Epilepsy Behav. Aug. 2005;7(1):74-84.
Noble et al., “Diuretic induced change in lung water assessed by electrical impedance tomography,” Physiol. Meas. 2000; 21(1):155-163.
Noble et al., “Monitoring patients with left ventricular failure by electrical impedance tomography,” Eur J Heart Fail. Dec. 1999;1(4):379-84.
O'Connell et al., “Economic impact of heart failure in the United States: time for a different approach,” J Heart Lung Transplant., Jul.-Aug. 1994 ; 13(4):S107-S112.
Ohlsson et al., “Central hemodynamic responses during serial exercise tests in heart failure patients using implantable hemodynamic monitors,” Eur J Heart Fail. Jun. 2003;5(3):253-259.
Ohlsson et al., “Continuous ambulatory monitoring of absolute right ventricular pressure and mixed venous oxygen saturation in patients with heart failure using an implantable haemodynamic monitor,” European Heart Journal 2001 22(11):942-954.
Packer et al., “Utility of impedance cardiography for the identification of short-term risk of clinical decompensation in stable patients with chronic heart failure,” J Am Coll Cardiol, 2006; 47(11):2245-2252.
Palatini et al., “Predictive value of clinic and ambulatory heart rate for mortality in elderly subjects with systolic hypertension” Arch Intern Med. 2002;162:2313-2321.
Piiria et al., “Crackles in patients with fibrosing alveolitis bronchiectasis, COPD, and Heart Failure,” Chest May 1991; 99(5):1076-1083.
Pocock et al., “Predictors of mortality in patients with chronic heart failure,” Eur Heart J 2006; (27): 65-75.
Poole-Wilson, “Importance of control of fluid volumes in heart failure,” European Heart Journal 2000; 22(11):893-894.
Raj et al., ‘Letter Regarding Article by Adamson et al, “Continuous Autonomic Assessment in Patients With Symptomatic Heart Failure: Prognostic Value of Heart Rate Variability Measured by an Implanted Cardiac Resynchronization Device’”, Circulation 2005;112:e37-e38.
Ramirez et al., “Prognostic value of hemodynamic findings from impedance cardiography in hypertensive stroke,” AJH 2005; 18(20):65-72.
Rich et al., “A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure,” New Engl. J. Med. 1995;333:1190-1195.
Roglieri et al., “Disease management interventions to improve outcomes in congestive heart failure,” Am J Manag Care. Dec. 1997;3(12):1831-1839.
Sahalos et al., “The Electrical impedance of the human thorax as a guide in evaluation of intrathoracic fluid volume,” Phys. Med. Biol. 1986; 31:425-439.
Saxon et al., “Remote active monitoring in patients with heart failure (rapid-rf): design and rationale,” Journal of Cardiac Failure 2007; 13(4):241-246.
Scharf et al., “Direct digital capture of pulse oximetry waveforms,” Proceedings of the Twelfth Southern Biomedical Engineering Conference, 1993., pp. 230-232.
Shabetai, “Monitoring heart failure hemodynamics with an implanted device: its potential to improve outcome,” J Am Coll Cardiol, 2003; 41:572-573.
Small, “Integrating monitoring into the Infrastructure and Workflow of Routine Practice: OptiVol,” Rev Cardiovasc Med. 2006 ;7 Supp 1: S47-S55.
Smith et al., “Outcomes in heart failure patients with preserved ejection fraction: mortality, readmission, and functional decline ,” J Am Coll Cardiol, 2003; 41:1510-1518.
Van Someren, “Actigraphic monitoring of movement and rest-activity rhythms inaging, Alzheimer's disease, and Parkinson's disease,” IEEE Transactions on Rehabilitation Engineering, Dec. 1997; 5(4):394-398. [Abstract Only].
Starling, “Improving care of chronic heart failure: advances from drugs to devices,” Cleveland Clinic Journal of Medicine Feb. 2003; 70(2):141-146.
Steijaert et al., “The use of multi-frequency impedance to determine total body water and extracellular water in obese and lean female individuals,” International Journal of Obesity Oct. 1997; 21(10):930-934.
Stewart et al., “Effects of a home-based intervention among patients with congestive heart failure discharged from acute hospital care,” Arch Intern Med. 1998;158:1067-1072.
Stewart et al., “Effects of a multidisciplinary, home-based intervention on planned readmissions and survival among patients with chronic congestive heart failure: a randomised controlled study,” The Lancet Sep. 1999, 354(9184):1077-1083.
Stewart et al., “Home-based intervention in congestive heart failure: long-term implications on readmission and survival,” Circulation. 2002;105:2861-2866.
Stewart et al., “Prolonged beneficial effects of a home-based intervention on unplanned readmissions and mortality among patients with congestive heart failure,” Arch Intern Med. 1999;159:257-261.
Stewart et al., “Trends in Hospitalization for Heart Failure in Scotland, 1990-1996. An Epidemic that has Reached Its Peak?,” European Heart Journal 2001 22(3):209-217.
Swedberg et al., “Guidelines for the diagnosis and treatment of chronic heart failure: executive summary (update 2005): The Task Force for the Diagnosis and Treatment of Chronic Heart Failure of the European Society of Cardiology,” Eur Heart J. Jun. 2005; 26(11):1115-1140.
Tang, “Case studies in advanced monitoring: OptiVol,” Rev Cardiovasc Med. 2006;7 Suppl 1:S62-S66.
The ESCAPE Investigators and ESCAPE Study Coordinators, “Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness,” JAMA 2005;294:1625-1633.
Tosi et al., “Seismic signal detection by fractal dimension analysis ,” Bulletin of the Seismological Society of America; Aug. 1999; 89(4):970-977. [Abstract Only].
Van De Water et al., “Monitoring the chest with impedance,” Chest. 1973;64:597-603.
Vasan et al., “Congestive heart failure in subjects with normal versus reduced left ventricular ejection fraction,” J Am Coll Cardiol, 1999; 33:1948-1955.
Verdecchia et al., “Adverse prognostic value of a blunted circadian rhythm of heart rate in essential hypertension,” Journal of Hypertension 1998; 16(9):1335-1343.
Verdecchia et al., “Ambulatory pulse pressure: a potent predictor of total cardiovascular risk in hypertension,” Hypertension. 1998;32:983-988.
Vollmann et al., “Clinical utility of intrathoracic impedance monitoring to alert patients with an implanted device of deteriorating chronic heart failure,” Euorpean Heart Journal Advance Access published on Feb. 19, 2007, downloaded from the Internet:<<http://eurheartj.oxfordjournals.org/cgi/content/full/ehl506v1>>, 6 pages total.
Vuksanovic et al., “Effect of posture on heart rate variability spectral measures in children and young adults with heart disease,” International Journal of Cardiology 2005;101(2): 273-278.
Wang et al., “Feasibility of using an implantable system to measure thoracic congestion in an ambulatory chronic heart failure canine model,” PACE 2005;28(5):404-411.
Wickemeyer et al., #197—“Association between atrial and ventricular tachyarrhythmias, intrathoracic impedance and heart failure decompensation in CRT-D Patients,” Journal of Cardiac Failure 2007; 13 (6) Suppl.; S131-132.
Williams et al, “How do different indicators of cardiac pump function impact upon the long-term prognosis of patients with chronic heart failure,” American Heart Journal, 150(5):983.e1-983.e6.
Wonisch et al., “Continuous haemodynamic monitoring during exercise in patients with pulmonary hypertension,” Int J Cardiol. Jun. 8, 2005;101(3):415-420.
Wynne et al., “Impedance cardiography: a potential monitor for hemodialysis,” Journal of Surgical Research 2006, 133(1):55-60.
Yancy “Current approaches to monitoring and management of heart failure,” Rev Cardiovasc Med 2006; 7 Suppl 1:S25-32.
Ypenburg et al., “Intrathoracic Impedance Monitoring to Predict Decompensated Heart Failure,” Am J Cardiol 2007, 99(4):554-557.
Yu et al., “Intrathoracic Impedance Monitoring in Patients With Heart Failure: Correlation With Fluid Status and Feasibility of Early Warning Preceding Hospitalization,” Circulation. 2005;112:841-848.
Zannad et al.; “Incidence, clinical and etiologic features, and outcomes of advanced chronic heart failure: The EPICAL Study,” J Am Coll Cardiol, 1999; 33(3):734-742.
Zile, “Heart failure with preserved ejection fraction: is this diastolic heart failure?” J Am Coll Cardiol, 2003; 41(9):1519-1522.
U.S. Appl. No. 60/006,600, filed Nov. 13, 1995; inventor: Terry E. Flach.
U.S. Appl. No. 60/972,316, filed Sep. 12, 2008; inventor: Imad Libbus et al.
U.S. Appl. No. 60/972,329, filed Sep. 14, 2007; inventor: Yatheendhar Manicka et al.
U.S. Appl. No. 60/972,333, filed Sep. 14, 2007; inventor: Mark Bly et al.
U.S. Appl. No. 60/972,336, filed Sep. 14, 2007; inventor: James Kristofer et al.
U.S. Appl. No. 60/972,340, filed Sep. 14, 2007; inventor: James Kristofer et al.
U.S. Appl. No. 60/972,343, filed Sep. 14, 2007; inventor: James Kristofer et al.
U.S. Appl. No. 60/972,354, filed Sep. 14, 2007; inventor: Scott Thomas Mazar et al.
U.S. Appl. No. 60/972,359, filed Sep. 14, 2007; inventor: Badri Amurthur et al.
U.S. Appl. No. 60/972,363, filed Sep. 14, 2007; inventor: Badri Amurthur et al.
U.S. Appl. No. 60/972,512, filed Sep. 14, 2007; inventor: Imad Libbus et al.
U.S. Appl. No. 60/972,537 filed Sep. 14, 2007; inventor: Yatheendhar Manicka et al.
U.S. Appl. No. 60/972,581, filed Sep. 14, 2007; inventor: Imad Libbus et al.
U.S. Appl. No. 60/972,616, filed Sep. 14, 2007; inventor: Imad Libbus et al.
U.S. Appl. No. 60/972,629, filed Sep. 14, 2007; inventor: Mark Bly et al.
U.S. Appl. No. 61/035,970, filed Mar. 12, 2008; inventor: Imad Libbus et al.
U.S. Appl. No. 61/046,196, filed Apr. 18, 2008; inventor: Scott T. Mazar.
U.S. Appl. No. 61/047,875, filed Apr. 25, 2008; inventor: Imad Libbus et al.
U.S. Appl. No. 61/055,645, filed May 23, 2008; inventor: Mark Bly et al.
U.S. Appl. No. 61/055,656, filed May 23, 2008; inventor: Imad Libbus et al.
U.S. Appl. No. 61/055,662, filed May 23, 2008; inventor: Imad Libbus et al.
U.S. Appl. No. 61/055,666, filed May 23, 2008; inventor: Yatheendhar Manicka et al.
U.S. Appl. No. 61/079,746, filed Jul. 10, 2008; inventor: Brett Landrum.
U.S. Appl. No. 61/084,567, filed Jul. 29, 2008; inventor: Mark Bly.
“Acute Decompensated Heart Failure”—Wikipedia Entry, downloaded from: <http://en.wikipedia.org/wiki/Acute—decompensated—heart—failure>, submitted version downloaded Feb. 11, 2011, 6 pages total.
“Heart Failure”—Wikipedia Entry, downloaded from the Internet: <http://en.wikipedia.org/wiki/Heart—failure>, submitted version downloaded Feb. 11, 2011, 17 pages total.
3M Corporation, “3M Surgical Tapes—Choose the Correct Tape” quicksheet (2004).
Cooper, “The Parameters of Transthoracic Electical Conduction,” Annals of the New York Academy of Sciences, 1970; 170(2):702-713.
EM Microelectronic-Marin SA, “Plastic Flexible LCD,” [product brochure]; retrieved from the Internet: <<http://www.emmicroelectronic.com/Line.asp?IdLine=48>>, copyright 2009, 2 pages total.
HRV Enterprises, LLC,“Heart Rate Variability Seminars,” downloaded from the Internet: <<http://hrventerprise.com/>> on Apr. 24, 2008, 3 pages total.
HRV Enterprises, LLC, “LoggerPro HRV Biosignal Analysis,” downloaded from the Internet: <<http://hrventerprise.com/products.html>> on Apr. 24, 2008, 3 pages total.
Related Publications (1)
Number Date Country
20090264792 A1 Oct 2009 US
Provisional Applications (1)
Number Date Country
61046221 Apr 2008 US