Patent Grant
10779737
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.
Chronotropic incompetence (hereinafter “CI”) can be a debilitating condition associated with high mortality and morbidity. Chronotropic incompetence can be defined as the inability for a patient to elevate heart rate to 85% of the age-predicted maximum heart rate (hereinafter “APMHR”) level during exercise in a clinical environment. The determination of the ability of the patient to raise HR can be done by subjecting a patient to exercise in a clinic to elevate the patient HR, for example with a treadmill in a clinic.
Work in relation to embodiments of the present invention suggests that known methods and apparatus for determining CI may be less than ideal. At least some of the known methods and apparatus test the patient in a clinical setting and may not determine the presence of CI when the patient is located remote from the clinic, for example located at home. Although successful in determining the presence of CI in a clinical setting, current methods that rely on a controlled environment such as a treadmill in a clinic may not be well suited to determine CI when the patient is located remote from the clinic. For example, in at least some instances the patient may be somewhat frail and not well suited to exercise on his or her own. Also, current methods of determining the maximum HR of the patient assume that the patient is able to exercise the level of his or her capacity when the maximum HR is measured, and in at least some instances such an assumption may not be appropriate, such as for patients with respiratory and cardiac diseases, as well as patients with physical disability.
Another approach to determining cardiac function related to CI in a patient can be to determine the heart rate reserve (hereinafter “HRR”) of the patient, in which the HRR is determined with the resting HR of the patient. However, in at least some instances it can be difficult to determine the resting HR of the patient in the clinic. In at least some instances, measurements of a patient in a clinic can be nervous and the heart rate can be elevated, for example with white coat syndrome, and the patient may receive an incorrect diagnosis in at least some instances. Further, at least some of the present methods of measuring HR remotely may not provide appropriate data to determine the resting HR when the patient is located remote from the clinic.
Therefore, a need exists for improved patient monitoring. Ideally, such improved patient monitoring would avoid at least some of the short-comings of the present methods and devices.
Embodiments of the present invention provide methods and apparatus to determine the presence of and track functional CI in an in-home setting under conditions of daily living. The remote monitoring of the patient can determine the presence of functional CI and identify functional CI so as to allow appropriate intervention and treatment. The functional CI of the patient can be determined safely and in many ways with the patient located outside the clinic. For example, the functional CI of the patient may be determined with one or more of a profile of measured patient heart rates, a measured maximum patient heart rate, or a peak of the heart rate profile, such as the peak of a heart rate distribution profile. The functional CI of the patient may be determined with the measured heart rate profile, in which the measured heart rate profile may correspond to heart rates substantially less than the maximum heart rate of the patient, such that the heart rate can be safely measured when the patient is remote from a health care provider. Alternatively or in combination, the functional CI of the patient may be determined based on a peak of the remotely measured heart rate profile. Further, the functional CI may be determined based on statistical measurements of the heart rate profile such as a location, for example central tendency, and variability, for example dispersion, of the measured heart rate. For example, the relative amounts of the profile of heart rates above the peak and heart rates below the peak can be compared to determine the functional CI. The peak of the heart rate profile of the remote heart rate data may be used to determine the heart rate reserve and functional CI of the patient.
The measured distribution of heart rates of the remotely measured patient heart rate data can be combined with one or more of the measured activity data, measured respiration data, the measured orientation and the measured impedance data so as to determine the functional CI of the patient. The measured activity data of the patient can be combined with the heart rate data to determine a measured maximum heart rate of the patient when the patient exercises. For example, the peak activity of the patient can be determined and compared to a threshold value, and the maximum heart rate of the patient may correspond to the activity of the patient above the threshold. Alternatively or in combination, the maximum heart rate of the patient may comprise an estimated maximum heart rate of the patient, and the presence of functional CI determined based on the estimated maximum heart rate and the age predicted maximum heart rate, such that the functional CI may be determined without requiring elevation of the heart rate of the patient.
The measured patient data can come from one or more of many sources of data such as an adherent device, or an implantable device, or combinations thereof. An implantable device can be used to measure heart rate data. Alternatively or in combination an adherent device can be used to measure heart rate data. Additional data can be measured, for example accelerometer data from an adherent device.
In a first aspect, embodiments provide an apparatus to monitor a patient. A processor system comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon, the processor system configured to receive heart rate data of the patient and determine a profile of the heart rates and wherein the processor is configured to identify chronotropic incompetence of the patient based on the profile of the heart rates.
In many embodiments, the computer program comprises instructions to identify the functional CI with one or more measurement of location of the heart rate data, measures of dispersion and variability of the heart rate data, skewness and kurtosis of the heart rate data, or comparison of portions around a mode of a single modal mounded distribution.
In many embodiments, the computer program comprises instructions to determine a peak of the profile and a first portion of the profile and a second portion of the profile, the first portion corresponding to a first amount of occurrences of first heart rates less than the peak and the second portion corresponding to a second amount of occurrences of second heart rates greater than the peak and wherein the chronotropic incompetence is identified based on the second amount smaller than the first amount.
In another aspect, embodiments provide an apparatus to monitor a remote patient, the apparatus comprises a processor system comprising at least one processor having a tangible medium with instructions of a computer program embodied thereon. The processor system is configured to receive heart rate data of the remote patient and determine a distribution of the heart rates, and the processor is configured to identify a chronotropic incompetence of the patient based on the distribution of heart rates.
In many embodiments, the computer program comprises instructions to receive respiration data of the patient and activity data of the patient and instructions to combine the heart rate data with the respiration data and activity data to identify the chronotropic incompetence.
In many embodiments, the computer program comprises instructions to determine a peak of the distribution and a first portion of the distribution and a second portion of the distribution, the first portion corresponding to a first amount of occurrences of first heart rates less than the peak and the second portion of the distribution corresponding to a second amount of occurrences of second heart rates greater than the peak. The chronotropic incompetence is identified based on the second amount smaller than the first amount.
In another aspect, embodiments provide a method of monitoring a patient. A processor system is provided which comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon, the processor system configured to receive heart rate data of the patient and determine a profile of the heart rates. The chronotropic incompetence of the patient is identified based on the profile of the heart rates.
In another aspect, embodiments provide an apparatus to monitor a remote patient. A processor system comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon, the processor system configured to receive data of the remote patient comprising heart rate data of the patient and activity data of the patient. The processor system comprises instructions to determine activity of the patient to a threshold activity amount, and the processor system comprises instructions to identify a chronotropic incompetence of the patient based on the heart rate data corresponding to activity of the patient above the threshold.
In many embodiments, the processor system comprises instructions to determine a maximum heart rate of the heart rate data corresponding to the activity of the patient above the threshold.
In many embodiments, the processor system comprises instructions to determine a correlation of the maximum heart rate with one or more of the patient activity, patient body posture, patient breath rate or patient respiration rate and wherein the processor system is configured to identify CI based on the correlation.
In many embodiments, the data of the patient comprises drug data of the patient and wherein the processor system comprises instructions to identify CI based on the drug data and the correlation.
In many embodiments, the patient data comprises data from an adherent device measured remotely and wherein the processor system comprises instructions to determine the threshold amount from a plurality of remote patients and corresponds to a percentile of patient activity of the plurality of remote patients.
In another aspect, embodiments provide a method of monitoring a remote patient. A processor system is provided that comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon, and the processor system is configured to receive data of the remote patient comprising heart rate data of the patient and activity data of the patient. The processor system comprises instructions to determine activity of the patient to a threshold activity amount. A chronotropic incompetence of the patient is identified based on the heart rate data corresponding to activity of the patient above the threshold.
In another aspect, embodiments provide an apparatus to monitor a remote patient. A processor system comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon, and the processor system comprises instructions to receive heart rate data of the remote patient and to determine a peak of heart rates of the remote patient. The processor system comprises instructions to identify a chronotropic incompetence of the patient based on the peak.
In many embodiments, the heart rates comprise a profile of heart rates, and the peak comprises a peak of the profile.
In many embodiments, the heart rates comprise a distribution of heart rates, and the peak comprises a mode of the distribution.
In many embodiments, the processor system comprises instructions to determine a heart rate reserve based on a difference of a maximum age predicted maximum heart rate and the peak, and the processor system is configured to determine the CI based on the heart rate reserve determined with the peak.
In another aspect, embodiments provide a method of monitoring a remote patient. A processor system is provided that comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon, and the processor system comprises instructions to receive heart rate data of the remote patient and to determine a peak of heart rates of the remote patient. A chronotropic incompetence of the patient is identified based on the peak.
In another aspect, embodiments provide an apparatus to monitor a patient having a skin. An adherent device to measure patient data comprises wireless communication circuitry and measurement circuitry, the measurement circuitry is coupled to at least two electrodes, a respiration sensor and an activity sensor. The adherent device comprising a support with an adhesive to adhere the at least two electrodes to the skin and support the wireless communication circuitry, the processor circuitry and the measurement circuitry with the skin. A server is located remote from the patient to receive the patient data. A gateway is coupled to each of the adherent device and the server with wireless communication to transmit the patient data. One or more of the adherent device, the server or the gateway comprises at least one processor having a tangible memory medium with instructions of a computer program embodied thereon to determine a chronotropic incompetence of the patient based on the patient data measured with the at least two electrodes, the respiration sensor and the activity sensor.
In many embodiments, the at least one processor comprises instructions to determine a distribution of heart rates of the patient and wherein the at least one processor is configured to determine the chronotropic incompetence based on the distribution heart rates.
In many embodiments, the distribution of heart rates of the patient corresponds to a plurality of heart levels and an occurrence of each level.
In many embodiments, the computer program comprises instructions to determine a peak of the distribution and a first portion of the distribution and a second portion of the distribution, the first portion corresponding to a first amount of occurrences of first heart rates less than the peak and the second portion of the distribution corresponding to a second amount of occurrences of second heart rates greater than the peak and wherein the chronotropic incompetence is determined based on the second amount smaller than the first amount.
In many embodiments, the at least one processor comprises instructions to fit the distribution to a Gaussian distribution and determine a skew of the distribution and wherein the chronotropic incompetence is determined based on the skew.
In many embodiments, the at least one processor comprises instructions to determine a distribution of heart rates of the patient, the distribution corresponding heart rates less than a maximum heart rate of the patient and wherein the at least one processor is configured to determine the chronotropic incompetence based on the distribution heart rate intervals corresponding to less than the maximum heart rate of the patient.
In many embodiments, the at least one processor comprises instructions to determine a distribution of heart rates of the patient, the distribution corresponding to heart rates less than a maximum heart rate of the patient and wherein the at least one processor comprises instructions to determine the maximum heart rate of the patient based on the distribution heart rate intervals corresponding to less than the maximum heart rate of the patient.
In many embodiments, the at least one processor comprises instructions to determine the chronotropic incompetence of the patient based on the maximum heart rate of the patient.
In many embodiments, the at least one processor comprises instructions to determine the maximum heart rate of the patient based on the distribution of heart rates corresponding to less than the maximum heart rate of the patient.
In another aspect, embodiments provide a method of monitoring a patient. Heart rate data of the patient is measured. A processor system is provided which comprises at least one processor having a tangible medium with instructions of a computer program embodied thereon. The processor system receives heart rate data of the patient and determines a distribution of the heart rates, and the processor determines a chronotropic incompetence of the patient based on the distribution of heart rates.
In many embodiments, the heart rate data comprise data measured from a patch adhered to the patient for at least about one week, and the heart rate data is transmitted with wireless communication.
In another aspect, embodiments provide an apparatus to monitor a patient. The apparatus comprises an adherent device means for measuring patient data, and a processor means for determining a chronotropic incompetence of the patient. The adherent device means may comprise the adherent device as described herein and the processor means for determining the chronotropic incompetence of the patient may comprise the computer readable instructions embedded on one or more processor as described herein.
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. 1D2 shows adherent devices as in
FIG. 1D3 shows vectors from a 3D accelerometer to determine orientation of the measurement axis of the patch adhered on the patient, according to embodiments of the present invention;
FIGS. 1I1 and 1J1 show a side cross-sectional view and an exploded view, respectively, of embodiments of the adherent device with a temperature sensor affixed to the gel cover;
FIGS. 3A1 to 3A5 show heart rate, activity index, body posture, impedance, and respiration rate measured from an adherent device adhered to the skin of the patient;
FIG. 3D1 shows correlation of heart rate with activity for patients without functional CI; and
FIG. 3D2 shows correlation of heart rate with activity for patients with functional CI.
Embodiments comprise an adherent wireless communication apparatus and methods to measure patient data and determine the presence of functional chronotropic incompetence (CI). The patient measurement device may comprise one or more of an adherent device or an implantable device, and processor system can determine CI with heart rate and activity data collected from the patient under conditions of daily living, for example when the patient is home.
As used herein, chronotropic incompetence encompasses a failure of the heart rate to elevate sufficiently when the patient is active. For example, although CI may comprise a failure of the heart rate to elevate to a percentage amount of 85% of the age predicted maximum heart rate during exercise, this amount can change based on pharmacological modification of heart rate response. Therefore, the determination of the CI of the patient can change based on treatment of the patient with pharmacologic compositions, and the determination of the CI of the patient can be based on patient treatment with medication in additional to measure physiological patient data as described herein.
As used herein functional CI encompasses a CI condition where the patient's heart rate fails to accommodate the patient's activities of daily living, resulting in debilitation under sub-maximum activity levels and heart rates.
The adherent device and processor system are capable of monitoring and tracking patient activity and heart rate (hereinafter “HR”) so as to assess CI in a natural living environment outside the clinic, such as at home. The adherent device can also measure and compute respiratory rate and patient activity, such that correspondence among CI, respiration and activity can be determined. For example one or more processors may comprise instructions of a computer program so as to correlate the impact of CI to changes in other physiological parameters and patient symptoms. This combination of patient data can improve determination of the CI and correlate the CI to patient symptoms. For example the level of debilitation that CI is causing can be correlated to patient symptoms.
The adherent device and processor system can measure patient heart rate data and determine a maximum heart rate of the patient that can be used to monitor the patient. For example, the maximum heart rate of the patient may be determined without a cardiac stress test, and with patient heart rate data that is less than the actual maximum heart rate of the patient, such that the maximum heart rate can be determined safely when the patient is remote from a clinic. For example, an estimated maximum heart rate of the patient can be determined based on a patient a histogram distribution of the heart rate. Alternatively or in combination, the measured heart rate data can be adjusted based on one or more of patient activity and patient respiration.
The determined maximum heart rate of the patient can be combined in many ways with patient data to monitor the patient and trigger alerts when the patient is at risk, for example. The adherent device and processor system can determine the age predicted maximum heart rate, the age predicted heart rate reserve, the percent heart rate reserve. For example the adherent device and processor system can be configured to determine the age predicted maximum heart rate (APMHR) based on the patient age (hereinafter “AGE”) with the formula:
APHRR=APMHR−resting HR
The APMHR can be combined with the determined maximum heart rate of the patient to determine the CI of the patient. For example, the ratio of the maximum heart rate to the APMHR and corresponding percentage can be determined. When the maximum HR of the patient corresponds to less than about 85% of the APMHR, the patient be identified as having CI.
The adherent device and processor system can determine the age predicted heart rate reserve (hereinafter “APHRR”) with the formula
APHRR=APMHR−resting HR.
The adherent device and processor system can determine the percent heart rate reserve (hereinafter “% HRR”) with the formula
% HRR=[(maximum HR)−(Resting HR)]*100/APHRR.
The adherent device and processor system can determine histograms for each of the HR, the RR interval and the activity, and determine the correlation between these measurement data and derive indices from each of these measurement data.
In the many embodiments, the adherent device can communicate wirelessly so as to transmit the multi-sensor data to a server located remote from the patient. The adherent device can communicate to the server with a wireless communication gateway. The wireless communication gateway can receive data from the adherent device with wireless communication, for example Bluetooth™, and the gateway can transmit the data to the server with wireless communication, for example a cellular communication protocol.
The remote server may comprise a computer program having instructions embodied in a tangible memory medium so as to instruct the processor to combine the collected data from the device as well as demographic and medication information resident on the server, in order to determine the presence of patient CI. The instructions of the program can also calculate the CI parameters and raise an alert if a adverse condition is detected. Alternatively or in combination, the gateway near the patient may comprise a processor having a tangible memory medium, and the gateway may comprise instructions of a computer program embodied on the tangible medium, so as to instruct the gateway processor to combine the collected data from the adherent device as well as the demographic and the medication information.
In many embodiments, the adherent device may comprise a processor and perform real-time diagnostic assessment of CI and alert the patient and/or care provider via audio and/or visual cues based on standard CI classification cut-off levels. This is possible with an adherent device that can store the theoretical age predicted maximum heart rate (hereinafter “APMHR”) and then track patient activity and heart rate so as to assess CI in real time. Alternatively or in combination, the adherent device can retrieve patient data related to the APMHR from the server, for example the patient's age when the patient has used the adherent device before and the patient data is stored on a database of the server. This retrieval of the APMHR data can improve the accuracy of the device as used and prevent errors, as the patient age, for example, can be stored in the data base such that the physician or patient from entering the age manually and may also avoid data entry errors.
Alternatively or in combination, the adherent device may store the CI assessment data for future offline data download, or transmit the data in real-time directly or indirectly (through an intermediary device that is paired to the adherent device) to a data storage entity.
The systems, methods and apparatus as described herein may comprise instructions of a processor system so as to determine functional CI based on an analysis of the envelop of HR histogram profile and the profile of HR change with activity so as to assess cardio-acceleration and cardio-blunting.
There may be additional embodiments and implementations for this method and apparatus based on the teachings described herein that will be apparent to a person of ordinary skill in the art.
Monitoring system 10 includes components to transmit data to a remote center 106. Remote center 106 can be located in a different building from the patient, for example in the same town as the patient, and can be located as far from the patient as a separate continent from the patient, for example the patient located on a first continent and the remote center located on a second continent. 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 and/or with a cellular connection. In many embodiments, monitoring system 10 comprises a distributed processor system with at least one processor comprising a tangible medium of device 100, at least one processor 102P of intermediate device 102, and at least one processor 106P at remote center 106, each of which processors can be in electronic communication with the other processors. At least one processor 102P comprises a tangible medium 102T, and at least one processor 106P comprises a tangible medium 106T. Remote processor 106P may comprise a backend server located at the remote center. 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, or 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 communicate with the remote center, via the intermediate device in the patient's home. In some embodiments, remote center 106 receives the patient data and applies a patient evaluation algorithm, for example the prediction algorithm to predict patient physiological or mental deterioration. In some embodiments, the algorithm may comprise an algorithm to predict impending patient physiological or mental deterioration, for example based on decreased hydration and activity. When a flag is raised, the center may communicate with the patient, hospital, nurse, and/or physician to allow for therapeutic intervention, for example to prevent further physiological or mental deterioration.
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 guidelremove old patchlplace new patchlremove 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 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, and each of the replaceable patches may include a battery. The module may collect 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 patch with connectors. 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.
System 10 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, heart rate variability (HRV), heart rate turbulence (HRT), heart sounds (e.g. S3), respiratory sounds, blood pressure, activity, posture, wake/sleep, orthopnea, temperature/heat flux, and weight. The activity sensor may comprise one or more of the following: ball switch, accelerometer, minute ventilation, HR, bioimpedance noise, skin temperature/heat flux, BP, muscle noise, posture.
The adherent device can wirelessly communicate with remote center 106. 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 can communicate wired or wirelessly to relay data to remote center 106.
In many embodiments, instructions are transmitted from remote site 106 to a processor supported with the adherent patch on 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.
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 in contact with the skin of the patient, and temperature sensor circuitry 144 to measure a temperature of the patient, for example a temperature of the skin of the patient. A temperature sensor may be used to determine the sleep and wake state of the patient. The temperature of the patient can decrease as the patient goes to sleep and increase when the patient wakes up.
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 vasodilation 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 comprises 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. Printed circuit board 120 may comprise an antenna to facilitate wireless communication. The antenna may be integral with printed circuit board 120 or may be separately coupled thereto. 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.
Intermediate device 102 may comprise 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. 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 in a four pole configuration, such that electrodes 112A and 112D comprise outer electrodes that are driven with a current and comprise force electrodes that force the current through the tissue. 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, sense, electrodes that sense and/or measure the voltage in response to the current from the force electrodes. In some embodiments, electrodes 112B and 112C may comprise force electrodes and electrodes 112A and 112D may comprise sense electrodes. The voltage measured by the sense electrodes can be used to measure the impedance of the patient and determine the respiration rate and/or hydration of the patient. The electrocardiogram circuitry may be coupled to the sense electrodes to measure the electrocardiogram signal, for example as described in U.S. patent application Ser. No. 12/209,288, entitled “Adherent Device with Multiple Physiological Sensors”, filed on Sep. 12, 2008.
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 patient physiological or mental physiological or mental deterioration, 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 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 two or more of electrodes 112A, 112B, 112C and 112D in many ways. In some embodiments, ECG circuitry 138 is connected to inner electrodes 112B and 122C, which may comprise sense electrodes of the impedance circuitry as described above. In some embodiments, ECG circuitry 138 can be connected to electrodes 112A and 112D so as to increase spacing of the electrodes. The inner electrodes may be positioned near the outer electrodes to increase the voltage of the ECG signal measured by ECG circuitry 138. In many embodiments, the ECG circuitry may measure the ECG signal from electrodes 112A and 112D when current is not passed through electrodes 112A and 112D, for example with switches as described in U.S. App. No. 60/972,527, the full disclosure of which has been previously incorporated herein by reference.
FIG. 1D2 shows an adherent device, for example adherent device 100, positioned on patient P to determine orientation of the adherent patch. X-axis 112X of device 100 is inclined at an angle .alpha. to horizontal axis Px of patient P. Z-axis 112Z of device 100 is inclined at angle .alpha. to vertical axis Pz of patient P. Y-axis 112Y may be inclined at a second angle, for example .alpha., to anterior posterior axis Py and vertical axis Pz. As the accelerometer of adherent device 100 can be sensitive to gravity, inclination of the patch relative to axis of the patient can be measured, for example when the patient stands.
ECG circuitry 138 can be coupled to the electrodes in many ways to define an electrocardiogram vector. For example electrode 112A can be coupled to a positive amplifier terminal of ECG circuitry 138 and electrode 112D can be coupled to a negative amplifier terminal of ECG circuitry 138 to define an orientation of an electrocardiogram vector along the electrode measurement axis. To define an electrocardiogram vector with an opposite orientation electrode 112D can be couple to the positive amplifier terminal of ECG circuitry 138 and electrode 112A can be coupled to the negative amplifier terminal of ECG circuitry 138. The ECG circuitry may be coupled to the inner electrodes so as to define an ECG vector along a measurement axis of the inner electrodes.
FIG. 1D3 shows vectors from a 3D accelerometer to determine orientation of the measurement axis of the patch adhered on the patient. The orientation can be determined for each patch adhered to the patient. A Z-axis vector 112ZV can be measured along vertical axis 112Z with an accelerometer signal from axis 134Z of accelerometer 134A. An X-axis vector 112XV can be measured along horizontal axis 112X with an accelerometer signal from axis 134X of accelerometer 134A. Inclination angle .alpha. can be determined in response to X-axis vector 112XV and Z-axis vector 112ZV, for example with vector addition of X-axis vector 112XV and Z-axis vector 112ZV. An inclination angle .alpha. for the patch along the Y and Z axes can be similarly obtained an accelerometer signal from axis 134Y of accelerometer 134A and vector 112ZV.
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, nylon 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.
FIGS. 1I1 and 1J1 show a side cross-sectional view and an exploded view, respectively, of embodiments of the adherent device with a temperature sensor affixed to the gel cover. In these embodiments, gel cover 180 extends over a wider area than in the embodiments shown in
The adherent device comprises electrodes 112A1, 112B1, 112C1 and 112D1 configured to couple to tissue through apertures in the breathable tape 110T. Electrodes 112A1, 112B1, 112C1 and 112D1 can be fabricated in many ways. For example, electrodes 112A1, 112B1, 112C1 and 112D1 can be printed on a flexible connector 112F, such as silver ink on polyurethane. Breathable tape 110T comprise apertures 180A1, 180B1, 180C1 and 180D1. Electrodes 112A1, 112B1, 112C1 and 112D1 are exposed to the gel through apertures 180A1, 180B1, 180C1 and 180D1 of breathable tape 110T. Gel 114A, gel 114B, gel 114C and gel 114D can be positioned over electrodes 112A1, 112B1, 112C1 and 112D1 and the respective portions of breathable tape 110T proximate apertures 180A1, 180B1, 180C1 and 180D1, so as to couple electrodes 112A1, 112B1, 112C1 and 112D1 to the skin of the patient. The flexible connector 112F comprising the electrodes can extend from under the gel cover to the printed circuit board to connect to the printed circuit boards and/or components supported thereon. For example, flexible connector 112F may comprise flexible connector 122A to provide strain relief, as described above.
In many embodiments, gel 114A, or gel layer, comprises a hydrogel that is positioned on electrode 112A to provide electrical conductivity between the electrode and the skin. In many embodiments, gel 114A comprises a hydrogel that provides a conductive interface between skin and electrode, so as to reduce impedance between electrode/skin interface. In many embodiments, gel may comprise water, glycerol, and electrolytes, pharmacological agents, such as beta blockers, ace inhibiters, diuretics, steroid for inflammation, antibiotic, antifungal agent. In specific embodiments the gel may comprise cortisone steroid. The gel layer may comprise many shapes, for example, square, circular, oblong, star shaped, many any polygon shapes. In specific embodiments, the gel layer may comprise at least one of a square or circular geometry with a dimension in a range from about 0.005″ to about 0.100″, for example within a range from about 0.015″-0.070″, in some embodiments within a range from about 0.015″-0.040″, and in specific embodiments within a range from about 0.020″-0.040″. In many embodiments, the gel layer of each electrode comprises an exposed surface area to contact the skin within a range from about 100 mm 2 to about 1500 mm 2, for example a range from about 250 mm 2 to about 750 mm 2, and in specific embodiments within a range from about 350 mm 2 to about 650 mm 2. Work in relation with embodiments of the present invention suggests that such dimensions and/or exposed surface areas can provide enough gel area for robust skin interface without excessive skin coverage. In many embodiments, the gel may comprise an adhesion to skin, as may be tested with a 1800 degree peel test on stainless steel, of at least about 3 oz/in, for example an adhesion within a range from about 5-10 oz/in. In many embodiments, a spacing between gels is at least about 5 mm, for example at least about 10 mm. Work in relation to embodiments of the present invention suggests that this spacing may inhibit the gels from running together so as to avoid crosstalk between the electrodes. In many embodiments, the gels comprise a water content within a range from about 20% to about 30%, a volume resistivity within a range from about 500 to 2000 ohm-cm, and a pH within a range from about 3 to about 5.
In many embodiments, the electrodes, for example electrodes 112A to 112D, may comprise an electrode layer. A 0.001″-0.005″ polyester strip with silver ink for traces can extend to silver/silver chloride electrode pads. In many embodiments, the electrodes can provide electrical conduction through hydrogel to skin, and in some embodiments may be coupled directly to the skin. Although at least 4 electrodes are shown, some embodiments comprise at least two electrodes, for example 2 electrodes. In some embodiments, the electrodes may comprise at least one of carbon-filled ABS plastic, silver, nickel, or electrically conductive acrylic tape. In specific embodiments, the electrodes may comprise at least one of carbon-filled ABS plastic, Ag/AgCl. The electrodes may comprise many geometric shapes to contact the skin, for example at least one of square, circular, oblong, star shaped, polygon shaped, or round. In specific embodiments, a dimension across a width of each electrodes is within a range from about 002″ to about 0.050″, for example from about 0.010 to about 0.040″. In many a surface area of the electrode toward the skin of the patient is within a range from about 25 mm 2 to about 1500 mm 2, for example from about 75 mm 2 to about 150 mm 2. In many embodiments, the electrode comprises a tape that may cover the gel near the skin of the patient. In specific embodiments, the two inside electrodes may comprise force, or current electrodes, with a center to center spacing within a range from about 20 to about 50 mm. In specific embodiments, the two outside electrodes may comprise measurement electrodes, for example voltage electrodes, and a center-center spacing between adjacent voltage and current electrodes is within a range from about 15 mm to about 35 mm. Therefore, in many embodiments, a spacing between inner electrodes may be greater than a spacing between an inner electrode and an outer electrode.
In many embodiments, adherent patch 110 may comprise a layer of breathable tape 110T, for example a known breathable tape, such as tricot-knit polyester fabric. In many embodiments, breathable tape 110T comprises a backing material, or backing 111, with an adhesive. In many embodiments, the patch adheres to the skin of the patient's body, and comprises a breathable material to allow moisture vapor and air to circulate to and from the skin of the patient through the tape. In many embodiments, the backing is conformable and/or flexible, such that the device and/or patch does not become detached with body movement. In many embodiments, backing can sufficiently regulate gel moisture in absence of gel cover. In many embodiments, adhesive patch may comprise from 1 to 2 pieces, for example 1 piece. In many embodiments, adherent patch 110 comprises pharmacological agents, such as at least one of beta blockers, ace inhibiters, diuretics, steroid for inflammation, antibiotic, or antifungal agent. In specific embodiments, patch 110 comprises cortisone steroid. Patch 110 may comprise many geometric shapes, for example at least one of oblong, oval, butterfly, dogbone, dumbbell, round, square with rounded corners, rectangular with rounded corners, or a polygon with rounded corners. In specific embodiments, a geometric shape of patch 110 comprises at least one of an oblong, an oval or round. In many embodiments, the geometric shape of the patch comprises a radius on each corner that is no less than about one half a width and/or diameter of tape. Work in relation to embodiments of the present invention suggests that rounding the corner can improve adherence of the patch to the skin for an extended period of time because sharp corners, for example right angle corners, can be easy to peel. In specific embodiments, a thickness of adherent patch 110 is within a range from about 0.001″ to about 0.020″, for example within a range from about 0.005″ to about 0.010″. Work in relation to embodiments of the present invention indicates that these ranges of patch thickness can improve adhesion of the device to the skin of the patient for extended periods as a thicker adhesive patch, for example tape, may peel more readily. In many embodiments, length 170 of the patch is within a range from about 2″ to about 10″, width 174 of the patch is within a range from about 1″ to about 5″. In specific embodiments, length 170 is within a range from about 4″ to about 8″ and width 174 is within a range from about 2″ to about 4″. In many embodiments, an adhesion to the skin, as measured with a 180 degree peel test on stainless steel, can be within a range from about 10 to about 100 oz/in width, for example within a range from about 30 to about 70 oz/in width. Work in relation to embodiments of the present invention suggests that adhesion within these ranges may improve the measurement capabilities of the patch because if the adhesion is too low, patch will not adhere to the skin of the patient for a sufficient period of time and if the adhesion is too high, the patch may cause skin irritation upon removal. In many embodiments adherent patch 110 comprises a moisture vapor transmission rate (MVTR, g/m{circumflex over ( )} 2/24 hrs) per American Standard for Testing and Materials E-96 (ASTM E-96) is at least about 400, for example at least about 1000. Work in relation to embodiments of the present invention suggest that MVTR values as specified above can provide improved comfort, for example such that in many embodiments skin does not itch. In some embodiments, the breathable tape 110T of adherent patch 110 may comprise a porosity (sec./100 cc/in2) within a wide range of values, for example within a range from about 0 to about 200. The porosity of breathable tape 110T may be within a range from about 0 to about 5. The above amounts of porosity can minimize itching of the patient's skin when the patch is positioned on the skin of the patient. In many embodiments, the MVTR values above may correspond to a MVTR through both the gel cover and the breathable tape. The above MVTR values may also correspond to an MVTR through the breathable tape, the gel cover and the breathable cover. The MVTR can be selected to minimize patient discomfort, for example itching of the patient's skin.
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, tape 110T of adherent patch 110 may comprise backing material, or backing 111, such as a fabric configured to provide properties of patch 110 as described above. In many embodiments backing 111 provides structure to breathable tape 110T, and many functional properties of breathable tape 110T as described above. In many embodiments, backing 111 comprises at least one of polyester, polyurethane, rayon, nylon, breathable plastic film; woven, nonwoven, spun lace, knit, film, or foam. In specific embodiments, backing 111 may comprise polyester tricot knit fabric. In many embodiments, backing 111 comprises a thickness within a range from about 0.0005″ to about 0.020″, for example within a range from about 0.005″ to about 0.010″.
In many embodiments, an adhesive 116A, for example breathable tape adhesive comprising a layer of acrylate pressure sensitive adhesive, can be disposed on underside 110A of patch 110. In many embodiments, adhesive 116A adheres adherent patch 110 comprising backing 111 to the skin of the patient, so as not to interfere with the functionality of breathable tape, for example water vapor transmission as described above. In many embodiments, adhesive 116A comprises at least one of acrylate, silicone, synthetic rubber, synthetic resin, hydrocolloid adhesive, pressure sensitive adhesive (PSA), or acrylate pressure sensitive adhesive. In many embodiments, adhesive 116A comprises a thickness from about 0.0005″ to about 0.005″, in specific embodiments no more than about 0.003″. Work in relation to embodiments of the present invention suggests that these thicknesses can allow the tape to breathe and/or transmit moisture, so as to provide patient comfort.
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 printed circuit board 120, or flex PCB layer, can be positioned over gel cover 180 with electronic components 130 connected and/or mounted to flex printed circuit board 120, for example mounted on flex PCB so as to comprise an electronics layer disposed on the flex PCB layer. In many embodiments, the adherent device may comprise a segmented inner component, for example the PCB may be segmented to provide at least some 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 printed circuit board 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. For example gel cover 180 can keep liquid water from penetrating though the gel cover into gel 114A, while allowing moisture vapor from the gel, for example moisture vapor from the skin, to transmit through the gel cover. The gel cover may comprise a porosity at least 200 sec./100 cc/in.sup.2, and this porosity can ensure that there is a certain amount of protection from external moisture for the hydrogel.
In many embodiments, the gel cover can regulate moisture of the gel near the electrodes so as to keeps excessive moisture, for example from a patient shower, from penetrating gels near the electrodes. In many embodiments, the gel cover may avoid release of excessive moisture form the gel, for example toward the electronics and/or PCB modules. Gel cover 180 may comprise at least one of a polyurethane, polyethylene, polyolefin, rayon, PVC, silicone, non-woven material, foam, or a film. In many embodiments gel cover 180 may comprise an adhesive, for example a acrylate pressure sensitive adhesive, to adhere the gel cover to adherent patch 110. In specific embodiments gel cover 180 may comprise a polyurethane film with acrylate pressure sensitive adhesive. In many embodiments, a geometric shape of gel cover 180 comprises at least one of oblong, oval, butterfly, dogbone, dumbbell, round, square, rectangular with rounded corners, or polygonal with rounded corners. In specific embodiments, a geometric shape of gel cover 180 comprises at least one of oblong, oval, or round. In many embodiments, a thickness of gel cover is within a range from about 0.0005″ to about 0.020″, for example within a range from about 0.0005 to about 0.010″. In many embodiments, gel cover 180 can extend outward from about 0-20 mm from an edge of gels, for example from about 5-15 mm outward from an edge of the gels.
In many embodiments, the breathable tape of adherent patch 110 comprises a first mesh with a first porosity and gel cover 180 comprises a breathable tape with a second 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, device 100 includes a printed circuitry, for example a printed circuitry board (PCB) module that includes at least one PCB with electronics component mounted thereon on and the battery, as described above. In many embodiments, the PCB module comprises two rigid PCB modules with associated components mounted therein, and the two rigid PCB modules are connected by flex circuit, for example a flex PCB. In specific embodiments, the PCB module comprises a known rigid FR4 type PCB and a flex PCB comprising known polyimide type PCB. In specific embodiments, the PCB module comprises a rigid PCB with flex interconnects to allow the device to flex with patient movement. The geometry of flex PCB module may comprise many shapes, for example at least one of oblong, oval, butterfly, dogbone, dumbbell, round, square, rectangular with rounded corners, or polygon with rounded corners. In specific embodiments the geometric shape of the flex PCB module comprises at least one of dogbone or dumbbell. The PCB module may comprise a PCB layer with flex PCB 120 can be positioned over gel cover 180 and electronic components 130 connected and/or mounted to flex PCB 120 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. The printed circuit may comprise polyester film with silver traces printed thereon.
In many embodiments, the electronics layer may be encapsulated in electronics housing 160. Electronics housing 160 may comprise an encapsulant, such as a dip coating, which may comprise a waterproof material, for example silicone and/or epoxy. In many embodiments, the PCB encapsulant protects the PCB and/or electronic components from moisture and/or mechanical forces. The encapsulant may comprise silicone, epoxy, other adhesives and/or sealants. In some embodiments, the electronics housing may comprising metal and/or plastic housing and potted with aforementioned sealants and/or adhesives.
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. In such embodiments, motion of the electrodes relative to the electronics modules, for example rigid PCB's 120A, 120B, 120C and 120D with the electronic components mounted thereon, does not compromise integrity of the electrode/hydrogel/skin contact. In some embodiments, the electrodes can be connected to the PCB and/or electronics module with a flex PCB 120, such that the electrodes and adherent patch can move independently from the PCB module. In many embodiments, the flex connection comprises at least one of wires, shielded wires, non-shielded wires, a flex circuit, or a flex PCB. In specific embodiments, the flex connection may comprise insulated, non-shielded wires with loops to allow independent motion of the PCB module relative to the electrodes.
In specific embodiments, cover 162 comprises at least one of polyester, 5-25% elastane/spandex, polyamide fabric; silicone, a polyester knit, a polyester knit without elastane, or a thermoplastic elastomer. In many embodiments cover 162 comprises at least 400% elongation. In specific embodiments, cover 162 comprises at least one of a polyester knit with 10-20% spandex or a woven polyamide with 10-20% spandex. In many embodiments, cover 162 comprises a water repellent coating and/or layer on outside, for example a hydrophobic coating, and a hydrophilic coating on inside to wick moisture from body. In many embodiments the water repellent coating on the outside comprises a stain resistant coating. Work in relation to embodiments of the present invention suggests that these coatings can be important to keep excessive moisture from the gels near the electrodes and to remove moisture from body so as to provide patient comfort.
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 adherent patch 110, so as to protect at least the electronics components and the PCB. Cover 162 can attach to adherent patch 110 with adhesive 116B. Cover 162 can comprise many known biocompatible cover materials, for example silicone. Cover 162 can comprise an outer polymer cover to provide smooth contour without limiting flexibility. In many 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 cover may comprise a breathable water resistant cover. In some embodiments, the breathable fabric may comprise polyester, nylon, 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.
The breathable cover 162 and adherent patch 110 comprise breathable tape can be configured to couple continuously for at least one week the at least one electrode to the skin so as to measure breathing of the patient. The breathable tape may comprise the stretchable breathable material with the adhesive and the breathable cover may comprises a stretchable breathable material connected to the breathable tape, as described above, such that both the adherent patch and cover can stretch with the skin of the patient. The breathable cover may also comprise a water resistant material. Arrows 182 show stretching of adherent patch 110, and the stretching of adherent patch can be at least two dimensional along the surface of the skin of the patient. As noted above, connectors 122A, 122B, 122C and 122D between PCB 130 and electrodes 112A, 112B, 112C and 112D may comprise insulated wires that provide strain relief between the PCB and the electrodes, such that the electrodes can move with the adherent patch as the adherent patch comprising breathable tape stretches. Arrows 184 show stretching of cover 162, and the stretching of the cover can be at least two dimensional along the surface of the skin of the patient.
Cover 162 can be attached to adherent patch 110 with adhesive 116B such that cover 162 stretches and/or retracts when adherent patch 110 stretches and/or retracts with the skin of the patient. For example, cover 162 and adherent patch 110 can stretch in two dimensions along length 170 and width 174 with the skin of the patient, and stretching along length 170 can increase spacing between electrodes. Stretching of the cover and adherent patch 110, for example in two dimensions, can extend the time the patch is adhered to the skin as the patch can move with the skin such that the patch remains adhered to the skin. Electronics housing 160 can be smooth and allow breathable cover 162 to slide over electronics housing 160, such that motion and/or stretching of cover 162 is slidably coupled with housing 160. The printed circuit board can be slidably coupled with adherent patch 110 that comprises breathable tape 110T, such that the breathable tape can stretch with the skin of the patient when the breathable tape is adhered to the skin of the patient, for example along two dimensions comprising length 170 and width 174.
The stretching of the adherent device 100 along length 170 and width 174 can be characterized with a composite modulus of elasticity determined by stretching of cover 162, adherent patch 110 comprising breathable tape 110T and gel cover 180. For the composite modulus of the composite fabric cover-breathable tape-gel cover structure that surrounds the electronics, the composite modulus may comprise no more than about 1 MPa, for example no more than about 0.3 MPa at strain of no more than about 5%. These values apply to any transverse direction against the skin.
The stretching of the adherent device 100 along length 170 and width 174, may also be described with a composite stretching elongation of cover 162, adherent patch 110 comprising breathable tape breathable tape 110T and gel cover 180. The composite stretching elongation may comprise a percentage of at least about 10% when 3 kg load is a applied, for example at least about 100% when the 3 kg load applied. These percentages apply to any transverse direction against the skin.
The printed circuit board may be adhered to the adherent patch 110 comprising breathable tape 110T at a central portion, for example a single central location, such that adherent patch 110 can stretch around this central region. The central portion can be sized such that the adherence of the printed circuit board to the breathable tape does not have a substantial effect of the modulus of the composite modulus for the fabric cover, breathable tape and gel cover, as described above. For example, the central portion adhered to the patch may be less than about 100 mm.sup.2, for example with dimensions of approximately 10 mm by 10 mm (about 0.5″ by 0.5″). Such a central region may comprise no more than about 10% of the area of patch 110, such that patch 110 can stretch with the skin of the patient along length 170 and width 174 when the patch is adhered to the patient.
The cover material may comprise a material with a low recovery, which can minimize retraction of the breathable tape from the pulling by the cover. Suitable cover materials with a low recovery include at least one of polyester or nylon, for example polyester or nylon with a loose knit. The recovery of the cover material may be within a range from about 0% recovery to about 25% recovery. Recovery can refer to the percentage of retraction the cover material that occurs after the material has been stretched from a first length to a second length. For example, with 25% recovery, a cover that is stretched from a 4 inch length to a 5 inch length will retract by 25% to a final length of 4.75 inches.
Electronics components 130 can be affixed to printed circuit board 120, for example with solder, and the electronics housing can be affixed over the PCB and electronics components, for example with dip coating, such that electronics components 130, printed circuit board 120 and electronics housing 160 are coupled together. Electronics components 130, printed circuit board 120, and electronics housing 160 are disposed between the stretchable breathable material of adherent patch 110 and the stretchable breathable material of cover 160 so as to allow the adherent patch 110 and cover 160 to stretch together while electronics components 130, printed circuit board 120, and electronics housing 160 do not stretch substantially, if at all. This decoupling of electronics housing 160, printed circuit board 120 and electronic components 130 can allow the adherent patch 110 comprising breathable tape to move with the skin of the patient, such that the adherent patch can remain adhered to the skin for an extended time of at least one week, for example two or more weeks.
An air gap 169 may extend from adherent patch 110 to the electronics module and/or PCB, so as to provide patient comfort. Air gap 169 allows adherent patch 110 and breathable tape 110T to remain supple and move, for example bend, with the skin of the patient with minimal flexing and/or bending of printed circuit board 120 and electronic components 130, as indicated by arrows 186. Printed circuit board 120 and electronics components 130 that are separated from the breathable tape 110T with air gap 169 can allow the skin to release moisture as water vapor through the breathable tape, gel cover, and breathable cover. This release of moisture from the skin through the air gap can minimize, and even avoid, excess moisture, for example when the patient sweats and/or showers.
The breathable tape of adherent patch 110 may comprise a first mesh with a first porosity and gel cover 180 may comprise a breathable tape with a second porosity, in which the second porosity is less than the first porosity to minimize, and even inhibit, flow of the gel through the breathable tape. The gel cover may comprise a polyurethane film with the second porosity.
Cover 162 may comprise many shapes. In many embodiments, a geometry of cover 162 comprises at least one of oblong, oval, butterfly, dogbone, dumbbell, round, square, rectangular with rounded corners, or polygonal with rounded corners. In specific embodiments, the geometric of cover 162 comprises at least one of an oblong, an oval or a round shape.
Cover 162 may comprise many thicknesses and/or weights. In many embodiments, cover 162 comprises a fabric weight: within a range from about 100 to about 200 g/m{circumflex over ( )}2, for example a fabric weight within a range from about 130 to about 170 g/m{circumflex over ( )}2.
In many embodiments, cover 162 can attach the PCB module to adherent patch 110 with cover 162, so as to avoid interaction of adherent patch 110C with the PCB having the electronics mounted therein. Cover 162 can be attached to breathable tape 110T and/or electronics housing 160 comprising over the encapsulated PCB. In many embodiments, adhesive 116B attaches cover 162 to adherent patch 110. In many embodiments, cover 162 attaches to adherent 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. Thus, the PCB module can be suspended above the adherent patch via connection to cover 162, for example with a gap 169 between the PCB module and adherent patch. In many embodiments, gap 169 permits air and/or water vapor to flow between the adherent patch and cover, for example through adherent patch 110 and cover 162, so as to provide patient comfort.
In many embodiments, adhesive 116B is configured such that adherent patch 110 and cover 162 can be breathable from the skin to above cover 162 and so as to allow moisture vapor and air to travel from the skin to outside cover 162. In many embodiments, adhesive 116B is applied in a pattern on adherent patch 110 such that the patch and cover can be flexible so as to avoid detachment with body movement. Adhesive 116B can be applied to upper side 110B of patch 110 and comprise many shapes, for example a continuous ring, dots, dashes around the perimeter of adherent patch 110 and cover 162. Adhesive 116B may comprise at least one of acrylate, silicone, synthetic rubber, synthetic resin, pressure sensitive adhesive (PSA), or acrylate pressure sensitive adhesive. Adhesive 16B may comprise a thickness within a range from about 0.0005″ to about 0.005″, for example within a range from about 0.001-0.005″. In many embodiments, adhesive 116B comprises a width near the edge of patch 110 and/or cover 162 within a range from about 2 to about 15 mm, for example from about 3 to about 7 near the periphery. In many embodiments with such widths and/or thickness near the edge of the patch and/or cover, the tissue adhesion may be at least about 30 oz/in, for example at least about 40 oz/in, such that the cover remains attached to the adhesive patch when the patient moves.
In many embodiments, the cover is adhered to adherent patch 110 comprising breathable tape 110T at least about 1 mm away from an outer edge of adherent patch 110. This positioning protects the adherent patch comprising breathable tape 110T from peeling away from the skin and minimizes edge peeling, for example because the edge of the patch can be thinner. In some embodiments, the edge of the cover may be adhered at the edge of the adherent patch, such that the cover can be slightly thicker at the edge of the patch which may, in some instances, facilitate peeling of the breathable tape from the skin of the patient.
Gap 169 extend from adherent patch 110 to the electronics module and/or PCB a distance within a range from about 0.25 mm to about 4 mm, for example within a range from about 0.5 mm to about 2 mm.
In many embodiments, the adherent device comprises a patch component and at least one electronics module. The patch component may comprise adherent patch 110 comprising the breathable tape with adhesive coating 116A, at least one electrode, for example electrode 114A and gel 114. The at least one electronics module can be separable from the patch component. In many embodiments, the at least one electronics module comprises the flex printed circuit board 120, electronic components 130, electronics housing 160 and cover 162, such that the flex printed circuit board, electronic components, electronics housing and 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 adherent patch 110B, such that the electronics module can be adhered to and/or separated from the adhesive component. 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. 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. Monitoring with multiple adherent patches for an extended period is described in U.S. Pat. App. No. 60/972,537, the full disclosure of which has been previously incorporated herein by reference. Many patch components can be provided for monitoring over the extended period. For example, about 12 patches can be used to monitor the patient for at least 90 days with at least one electronics module, for example with two reusable electronics modules.
In many embodiments, the adherent device comprises a patch component and at least one electronics module. The patch component may comprise adherent patch 110 comprising the breathable tape with adhesive coating 116A, at least one electrode, for example electrode 114A and gel 114. The at least one electronics module can be separable from the patch component. In many embodiments, the at least one electronics module comprises the flex printed circuit board 120, electronic components 130, electronics housing 160 and cover 162, such that the flex printed circuit board, electronic components, electronics housing and 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 adherent patch 110B, such that the electronics module can be adhered to and/or separated from the adhesive component. 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. 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. Monitoring with multiple adherent patches for an extended period is described in U.S. Pat. App. No. 60/972,537, the full disclosure of which has been previously incorporated herein by reference. Many patch components can be provided for monitoring over the extended period. For example, about 12 patches can be used to monitor the patient for at least 90 days with at least one electronics module, for example with two reusable electronics modules.
At least one electrode 112A can extend through at least one aperture 180A in the breathable tape 110 and gel cover 180.
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. 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.
A step 205 adheres a measurement device to patient to measure heart rate, activity, body posture, respiration rate and bioimpedance. The adherent device may comprise an adherent device as described above. The device may comprise ECG circuitry to measure the HR, an accelerometer to measure patient activity and orientation, impedance circuitry to measure breathing and patient hydration. Additional or alternative sensors can be used. For example, breathing may be determined with a sensor that provides a signal in response to expansion of the chest and expansion of the skin of the patient.
A step 210 measures, stores and processes patient data with adherent device. The adherent device may measure HR, patient activity and orientation, breathing and hydration, and these data can be stored on the adherent device, for example stored on the processor at least prior to communication with the gateway. The processor may determine a heart rate of the patient based on the ECG and may determine hydration and breathing based on an impedance signal from the impedance circuitry, for example.
A step 212 determines patient drug treatment. The drug treatment can be determined based on a prescription from a physician, for example.
A step 215 transmits patient data from adherent device to the gateway, as described above. A step 220 receives the patient data with the gateway.
A step 225 measures, stores and processes patient data with gateway. The gateway can store data of the adherent device and process the data. For example, the gateway can perform one or more of the steps of sub-steps so as to identify the CI. Also, the gateway may comprise at least one sensor to measure additional patient data, and may also combine data with data from additional measurement devices.
A step 230 transmits patient data from the gateway to the remote server.
A step 235 stores and processed patient data with remote server. The remoter server can store data of the adherent device and process the data. For example, the remote server can perform one or more of the steps of sub-steps so as to identify the CI.
A step 240 identifies functional CI with profile of remote heart rates. This functional CI can be identified in many ways, for example with one or more measurement of location of the heart rate data, measures of dispersion and variability of the heart rate data, skewness and kurtosis of the heart rate data, or comparison of portions around a mode of a single modal mounded distribution.
A sub-step 241-determines a profile of remote heart rates. A sub-step 242 determines a peak of the profile of remote heart rates. For example, the profile may comprise a histogram or Gaussian probability function and the peak may comprise the mode of the distribution or probability function. A sub-step 243 determines a portion of profile above peak. A sub-step 244 determines a portion of profile below peak. A sub-step 245 compares a portion above peak to a portion below peak. A sub-step 246 identifies functional CI when the portion above peak is less than portion below. For example, the portion above may correspond to the occurrence of heart rates above the peak hear rate and the portion below the peak may correspond to the occurrence of heart rates below the peak.
Based on the teachings described herein one can determine relevant parameters from the heart rate distribution profile so as to identify the functional CI.
A step 250 identifies functional CI with resting remote HR. A sub-step 251-determines the occurrence of heart rates corresponding to profile. A sub-step 252 determines a peak of the remote heart rates. A sub-step 254 determine the remote resting HR based on the peak of the remote HR. A sub-step 255 determines age corrected maximum HR. A sub-step 256 determines the HRR based on age corrected maximum HR and remote resting HR. A sub-step 257 identifies functional CI when the HRR is below the threshold.
A step 260 identifies functional CI with maximum HR. A sub-step 261 determines the threshold activity amount based on patient data from a plurality of other patients, for example from a patient population measured with substantially similar adherent devices when the patients are at home. A sub-step 262 determines the patient activity above threshold. A sub-step 263 determines heart rates of the patient corresponding to patient activity above threshold. For example, the heart rate of the patient may comprise a maximum HR of the patient and the maximum HR of the patient can be compared to the threshold. A sub-step 264 determines a correlation of HR above threshold with one or more of activity, body posture, respiration rate and bioimpedance. A sub-step 265 determines patient drug treatment and compliance. A sub-step 266 determines functional CI based on patient drug treatment and correlation of HR above threshold with the one or more of activity, body posture, respiration rate or bioimpedance. A step 270 transmits notification to one or more of physician or patient based on identification of CI.
The 85% cut-off for functional CI classification can be modified to other cut-offs to account for pharmacological modification of heart rate response such as beta-blockers and other chronotropic/lusitropic medication.
The processor system, as described above, may comprise instructions of a computer program embedded thereon so as to perform many of the steps of the method 200. For example, many of the steps of the method 200 can be performed with processor system comprising the processor of the adherent device, the processor of the gateway and the processor of the remote server. The method 200 can be performed with one or more of the processor of the adherent device, the processor of the gateway and the processor of the remote server. Further the steps of the method 200 can be distributed among the processor of the processor system such that each processor performs at least one of the steps or sub-steps of method 200.
It should be appreciated that the specific steps illustrated in
The patient data as described above can be combined to determine the functional CI of the patient. For example, the data can be combined with one or more correlations of heart rate to one or more of the activity index (hereinafter “AI”), body posture (hereinafter “BP”), impedance of the patient (hereinafter “BioZ” or respiration rate (hereinafter “RR”). The AI may comprise an index based on the measurements from the three axes of the accelerometer as described above. The BP may comprise an angle of the patient based on orientation from accelerometer as described above. The BioZ may comprise impedance averaged over patient breathing cycles to correct for patient breathing or corrected for patient breathing with a portion of the breathing pattern. For example, the heart rate can be correlated with these data with the equation:
HR=a*AI+b*BP+c*BioZ+d*RR,
where a, b, c and d are respective correlation coefficients. The above equation is merely an example of a correlation equation as many additional equations can be used such as equations with cross terms, for example of AI with BP, and with squared terms, for example with coefficients of (BP)*(BP).
The patient data may also be combined with multi-dimensional look up tables, for example with look up tables comprising levels or tiers for each measured data parameter such as AI. For example, AI may comprise a level, or tier, based on counts of an accelerometer or other index.
Embodiments as described herein can be incorporated with many commercially available patient monitoring and treatment systems such as the OptiVol™ alert algorithm and computer programs embodying instructions thereof commercially available from Medtronic, the CareLink™ server commercially available from Medtronic, the Latitude™ patient management system commercially available from Boston Scientific, the Merlin™ system commercially available from St. Jude and the MCOT™ commercially available from CardioNet.
Experimental Clinical Studies
An experimental clinical study can be conducted on an empirical number of patients to determine empirically parameters of the above described adherent device and processor system so as to determine functional CI of the patient. The empirically determined parameters can be used with programs of the processor system to determine status of the patient, for example to determine deterioration in the status, based on the teachings as described herein.
FIGS. 3A1 to 3A5 show heart rate, activity index, body posture, impedance, and respiration rate measured from an adherent device adhered to the skin of the patient. Although the device can be adhered for at least about one week as described above, the data of
FIG. 3A1 shows the heart rate of the patient in beats per minute from 00:00 hours to 24:00 hours. The heart rate may be determined with one or more of the processor of the adherent device, the processor of the gateway or the processor of the remote server. The HR shows an elevation at about 11:00.
FIG. 3A2 shows patient activity amounts. The patient activity amounts may comprise an index and many measures of patient activity. For example, the activity index may comprise counts and/or an arbitrary scale, and the values can range from about 0 to about 300. The data show a peak at about 11:00.
FIG. 3A3 shows patient body posture angle. The patient body posture is shown to be upright, at around 80 degrees from about 07:00 to about 18:00. These data indicate that the patient is awake and upright from about 07:00 to about 18:00.
FIG. 3A4 shows patient impedance. The patient impedance is shown to vary from about 60 to about 80 Ohms. For example with local peaks around 11:00 and 14:00 corresponding to about 74 and 78 Ohms, respectively.
FIG. 3A5 shows patient breathing rate, also referred to as patient respiration rate. The respiration rate of the patient varies from about 10 breaths per minute to about 30 breaths per minute.
Based on the teachings described herein, the instruction of the processor system can identify functional CI from the HR data and data of one or more of the other sensors. The method and instructions of the processor system can identify functional CI of the patient based on HR and one or more sensors from about 10:00 to 11:00. For example, the patient activity comprises a peak around 11 am corresponding to an activity amount above the threshold determined with similar adherent devices from a population of patients or relative to the patient's own activity mean over a given 24 hour period. For example, the threshold may correspond to an activity amount of 100, such that the patient heart rates corresponding to the activity index above the threshold of 100 correspond to maximum HR of the patient. The processor system comprises patient data including the age of the patient such that the age corrected maximum HR can be determined and the functional CI of the patient can be identified based on the age corrected maximum HR and the maximum HR of the patient. The increase in activity was not paralleled by a comparable increase in HR so as to comprise a diagnostic marker to identify CI with the remote patient measurements as described herein.
The processor system and methods described herein can identify functional CI of the patient based on the profile of the HR data, for example based on histogram as described herein.
The functional CI can be identified with the profile of remote heart rates. This functional CI can be identified in many ways, for example with one or more measurement of location of the heart rate data, measures of dispersion and variability of the heart rate data, skewness and kurtosis of the heart rate data, or comparison of portions around a mode of a single modal mounded distribution.
The histogram distribution of each patient comprises a first side corresponding to a first amount of occurrences of heart rates below the peak and a second side corresponding to a second amount of occurrences of heart rates above the peak. The distribution of the first patient without functional CI has a first amount of occurrences below the peak at 90 bpm and a second amount of occurrence above the peak at 90 bpm, and the first amount is substantially equal to the second amount. The distribution of the second patient with functional CI has a first amount of occurrences below the peak at 105 bpm and a second amount of occurrence above the peak at 105 bpm, and the first amount is substantially greater than the second amount.
Alternatively or in combination, the histogram distribution of each patient can be fit to a Gaussian distribution and a skew of the distribution for each patient determined. For example, the first patient without functional CI comprises substantially no skew of the histogram distribution, and the second patient with functional CI comprises significant skew of the histogram distribution.
The peak of the HR data of
Clinical Studies for Remote Monitoring and Diagnosis of Chronotropic Incompetence in HF Patients.
A study can be conducted to diagnose functional CI during activities of daily living, through remote monitoring, so as to provide important information for effectively managing HF and understanding the role of functional CI in contributing to HF symptoms. The study may comprise HF patients having an ejection fraction (hereinafter “EF”) of 40% or less.
Study Design: The study may comprise a prospective monitoring study of patients with chronic HF using an external multi-sensor monitor, for example an adherent monitor as described above. The study may comprise data from multiple centers and enroll approximately 200 enrolled patients with NYHA Class III/IV, EF.ltoreq.40%. The wireless monitoring device can be applied to the patient's chest and replaced weekly during a 90-day monitoring period. Heart rate (HR), respiratory rate, activity level and body impedance data from the device were transmitted at regular interval via phone and used for offline analysis.
The data can be analyzed to determine results and compare the determined functional CI to similar study populations. The following can be determined for the population: gender, age, body mass index, EF, percentage of patient with beta-blockers. For each patient, the modal HR during daily activity was calculated and used to perform functional CI determination. The percentage of patients with functional CI can be determined when defined as an inability to reach 85% of age-predicted maximum HR. When adjusted for beta-blocker use, the percentage of patient having functional CI can be determined.
Applicants note that a study design as described above has been conducted on a population of approximately 300 patients.
FIG. 3D1 shows correlation of heart rate data with activity data for patients without functional CI from the study. The fit parameters are HR (bpm)=0.0985*(Activity)+75.4 (R2=0.151)
FIG. 3D2 shows correlation of heart rate data with activity data for patients with functional CI from the study. The fit parameters are HR (bpm)=0.0126*(Activity)+82.651 (R2=0.0026)
The correlations shown in FIGS. 3D1 and 3D2 are examples of linear correlations of heart rate with activity that can be determined. The correlation coefficient of the patients without functional CI shows a steeper slope for a linear fit between HR and activity when compared to patients with functional CI. The less steep curve of the patients with CI shows a blunting of heart rate response to activities of daily living, when adjusted for age. This blunting of HR elevation can be combined with additional patient measurement data, as described above.
Applicants note that the presence of functional CI in the study was determined based on measured activity above a percentage of the mean age adjusted maximum heart rate as shown above with reference to
Additional correlations and correspondence among patient data can be made with additional variables as described above so as to identify functional CI in a patient population. The correlations may comprise a plurality of variables correlated with the HR profile, as described above. Look up tables can also be determined to compare functional CI with measurement data such as activity, orientation, activity, respiration rate and body temperature.
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.
This application is a continuation of U.S. patent application Ser. No. 14/310,105 filed on Jun. 20, 2014 and titled “Method And Apparatus For Remote Detection And Monitoring Of Functional Chronotropic Incompetence”, which is a continuation of U.S. patent application Ser. No. 12/910,076 filed Oct. 22, 2010 and titled “Method and Apparatus for Remote Detection and Monitoring of Functional Chronotropic Incompetence”, which claims the benefit under 35 USC 119(e) of U.S. Provisional Application No. 61/253,866, filed on Oct. 22, 2009 and titled “Method and Apparatus for Remote Detection and Monitoring of Functional Chronotropic Incompetence”, the entire disclosures of which are hereby incorporated by reference herein for all purposes.
| 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 | Wyer | 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 | DiGaicomo 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 |
| 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 | 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 |
| 5309919 | Snell | May 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 | 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 |
| 5718234 | Warden et al. | Feb 1998 | A |
| 5718235 | Golosarkey 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 |
| 5803915 | Kremenchugsky et al. | Sep 1998 | A |
| 5807272 | Kun et al. | Sep 1998 | A |
| 5814079 | Kieval | 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 |
| 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 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 et al. | 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 | 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 |
| 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 |
| 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 |
| 6411853 | Millot et al. | Jun 2002 | B1 |
| 6416471 | Kumar et al. | Jul 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 |
| 6459934 | Kadhiresan | 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 |
| 6490478 | Zhang et al. | Dec 2002 | B1 |
| 6491647 | Bridger et al. | Dec 2002 | B1 |
| 6494829 | New, Jr. 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 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 | Sarbra | Aug 2005 | B2 |
| 6940403 | Kail | 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 |
| 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 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 et al. | Jan 2007 | B2 |
| 7160252 | Cho et al. | Jan 2007 | B2 |
| 7160253 | Nissila et al. | 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 | Doab 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 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 |
| 8116841 | Bly et al. | Feb 2012 | B2 |
| 8249686 | Libbus et al. | Aug 2012 | B2 |
| 8790259 | Katra et al. | Jul 2014 | B2 |
| 9615757 | Katra et al. | Apr 2017 | B2 |
| 20010047127 | New, Jr. et al. | Nov 2001 | 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 et al. | 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 |
| 20030009092 | Parker | Jan 2003 | A1 |
| 20030023184 | Pitts-Crick et al. | Jan 2003 | A1 |
| 20030028221 | Zhu et al. | Feb 2003 | A1 |
| 20030028321 | Upadhyaya et al. | Feb 2003 | A1 |
| 20030028327 | Brunner et al. | Feb 2003 | A1 |
| 20030051144 | Williams | Mar 2003 | A1 |
| 20030055460 | Owen 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 |
| 20030135127 | Sackner et al. | Jul 2003 | A1 |
| 20030143544 | McCarthy | Jul 2003 | A1 |
| 20030149349 | Jensen | Aug 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 |
| 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 |
| 20040073094 | Baker | Apr 2004 | A1 |
| 20040073126 | Rowlandson | Apr 2004 | A1 |
| 20040077954 | Oakley et al. | Apr 2004 | A1 |
| 20040098060 | Ternes | May 2004 | A1 |
| 20040100376 | Lye et al. | May 2004 | A1 |
| 20040102683 | Khanuja et al. | May 2004 | A1 |
| 20040106951 | Edman 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 | Chung | 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 |
| 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 |
| 20050267541 | Scheiner | Dec 2005 | A1 |
| 20050273023 | Bystrom et al. | Dec 2005 | A1 |
| 20050277841 | Shennib | Dec 2005 | A1 |
| 20050277842 | Silva | Dec 2005 | A1 |
| 20050277992 | Koh | 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 |
| 20060030892 | Kadhiresan | 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 |
| 20060079793 | Mann 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 |
| 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 |
| 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 |
| 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 |
| 20060238333 | Welch 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 et al. | 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 |
| 20070048224 | Howell et al. | Mar 2007 | A1 |
| 20070060800 | Drinan et al. | Mar 2007 | A1 |
| 20070060802 | Ghevondian et al. | Mar 2007 | A1 |
| 20070069887 | Welch 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 |
| 20070208263 | John | Sep 2007 | A1 |
| 20070232867 | Hansmann | 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 |
| 20080004664 | Hopper et al. | 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 |
| 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 et al. | 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 |
| 20090182204 | Semler et al. | Jul 2009 | A1 |
| 20090234410 | Libbus et al. | Sep 2009 | A1 |
| 20090264792 | Mazar | Oct 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 |
| Number | Date | Country |
|---|---|---|
| 1579801 | Sep 2005 | EP |
| WO 2000079255 | Dec 2000 | WO |
| WO 2001089362 | 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 | Oct 2006 | WO |
| WO 2007041783 | Apr 2007 | WO |
| WO 2007106455 | Sep 2007 | WO |
| WO 2009116906 | Sep 2009 | WO |
| Entry |
|---|
| Abraham, “New approaches to monitoring heart failure before symptoms appear”, Rev. Cardiovasc. Med., vol. 7 Suppl 1, 2006, pp. 33-41. |
| Acute Decompensated Heart Failure, Wikipedia Entry, downloaded from: http://en.wikipedia.org/wiki/Acute_decompensated_heart_failure, downloaded Feb. 11, 2011, 6 pages. |
| AD5934: 250kSPS 12-Bit Impedance Converter Network Analyzer, Analog Devices, retrieved from http://www.analog.com/static/imported-files/data_sheets/AD5934.pdf, date unknown, 32 pages. |
| Adams, Jr., “Guiding heart failure care by invasive hemodynamic measurements: possible or useful?”, Journal of Cardiac Failure, vol. 8 (2), 2002, pp. 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, vol. 110, 2004, pp. 2389-2394. |
| Adamson, “Integrating device monitoring into the infrastructure and workflow of routine practice”, Rev. Cardiovasc. Med., vol. 7 Suppl 1, 2006, pp. 42-60. |
| Adamson et al., “Ongoing right ventricular hemodynamics in heart failure”, J. Am. Coll. Cardiol, vol. 41, 2003, pp. 565-570. |
| Adhere, “Insights from the Adhere Registry: Data from over 1000,000 patient cases”, Presentation, date unknown, 70 pages. |
| Advamed, “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., vol. 3 Suppl 4, 2002, pp. S3-S9. |
| Albert, “Bioimpedance to prevent heart failure hospitalization”, Curr Heart Fail Rep., vol. 3 (3), Sep. 2006, pp. 136-142. |
| 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, 115, 2007, pp. e69-e171. |
| Amurthur et al., U.S. Appl. No. 60/972,359, filed Sep. 14, 2007. |
| Amurthur et al., U.S. Appl. No. 60/972,363, filed Sep. 14, 2007. |
| Azarbal B, Hayes SW, Lewin HC, Hachamovitch R, Cohen I, Berman OS. The incremental prognostic value of percentage of heart rate reserve achieved over myocardial perfusion single-photon emission computed tomography in the prediction of cardiac death and all-cause mortality: Superiority over 85% of maximal age-predicted heart rate. J Am Coli Cardiol, American College of Cariology Foundation, Journal of the American College of Cardiology, vol. 44, No. 2, Jul. 21, 2004, 8 pp. |
| Belalcazar et al., “Monitoring lung edema using the pacemaker pulse and skin electrodes”, Physiol. Meas., vol. 26, 2005, pp. S153-S163. |
| Bennett, “Development of implantable devices for continuous ambulatory monitoring of central hemodynamic values in heart failure patients”, PACE, vol. 28, Jun. 2005, pp. 573-584. |
| Bly, et al., U.S. Appl. No. 60/972,333, filed Sep. 14, 2007. |
| Bly et al., U.S. Appl. No. 60/972,629, filed Sep. 14, 2007. |
| Bly et al., U.S. Appl. No. 61/055,645, filed May 23, 2008. |
| Bly, U.S. Appl. No. 61/084,567, filed Jul. 29, 2008. |
| Bourge, “Case studies in advanced monitoring with the chronicle device”, Rev Cardiovasc Med., vol. 7 Suppl 1, 2006, pp. S56-S61. |
| Braunschweig, “Continuous hemodynamic monitoring during withdrawal of diuretics in patients with congestive heart failure”, European Heart Journal, vol. 23 (1), 2002, pp. 59-69. |
| Brennan, “Measuring a Grounded Impedance Profile Using the AD5933”, Analog Devices, retrieved from http://www.analog.com/static/imported-files/application_notes/427095282381510189AN847_0.pdf, date unknown, 12 pages. |
| Buono et al., “The effect of ambient air temperature on whole-body bioelectrical impedance”, Physiol. Meas., vol. 25, 2004, pp. 119-123. |
| Burkhoff et al., “Heart failure with a normal ejection fraction: Is it really a disorder of diastolic function?”, Circulation, vol. 107, 2003, pp. 656-658. |
| Burr et al., “Heart rate variability and 24-hour minimum heart rate”, Biological Research for Nursing, vol. 7 (4), 2006, pp. 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, vol. 29 (6), 2001, pp. 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, vol. 22 (4), 2007, pp. 464-469. |
| Chaudhry et al., “Telemonitoring for patients with chronic heart failure: a systematic review”, J Card Fail., vol. 13 (1), Feb. 2007, pp. 56-62. |
| Chung et al., “White coat hypertension: Not so benign after all?”, Journal of Human Hypertension, vol. 17, 2003, pp. 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, vol. 24 (5), 2003, pp. 442-463. |
| Cooley, “The Parameters of Transthoracic Electrical Conduction”, Annals of the New York Academy of Sciences, vol. 170 (2), 1970, pp. 702-713. |
| Cowie et al., “Hospitalization of patients with heart failure. A population-based study”, European Heart Journal, vol. 23 (11), 2002, pp. 877-885. |
| DIMRI, , “Chapter 1: Fractals in geophysics and semiology: an introduction”, Fractal Behaviour of the Earth System, Springer Berlin Heidelberg, Summary and 1st page Only, 2005, pp. 1-22. |
| El-Dawlatly et al., “Impedance cardiography: noninvasive assessment of hemodynamics and thoracic fluid content during bariatric surgery”, Obesity Surgery, vol. 15 (5), May 2005, pp. 655-658. |
| EM Microelectronic, Marin SA, “Plastic Flexible LCD”, Product Brochure, retrieved from http://www.emmicroelectronic.com/Line.asp?IdLine=48, 2009, 2 pages. |
| Erdmann, “Editorials: The value of diuretics in chronic heart failure demonstrated by an implanted hemodynamic monitor”, European Heart Journal, vol. 23 (1), 2002, pp. 7-9. |
| FDA—Draft questions for Chronicle Advisory Panel Meeting, retrieved from http://www.fda.gov/ohrms/dockets/ac/07/questions/2007-4284q1_draft.pdf, 2007, 3 pages. |
| FDA—Medtronic Chronicle Implantable Hemodynamic Monitoring System P050032, Panel Package Section 11: Chronicle IHM Summary of Safety and Effectiveness, 2007, 77 pages. |
| FDA—References for Circulatory System Devices Panel, retrieved from http://www.fda.gov/OHRMS/DOCKETS/AC/07/briefing/2007-4284bibl_01.pdf, Mar. 1, 2007, 1 page. |
| FDA Executive Summary Memorandum, meeting of the Circulatory Systems Devices Advisory Panel, P050032 Medtronic, Inc. Chronicle Implantable Hemodynamic Monitor (IHM) System, retrieved from http://www.fda.gov.ohrms/dockets/ac/07/briefing/2007-4284b1_02.pdf, Mar. 1, 2007, 23 pages. |
| FDA Executive Summary, Medtronic Chronicle Implantable Hemodynamic Monitoring System P050032: Executive Summary, Panel Package Sponsor Executive Summary, vol. 1, Sec. 4, retrieved from http://www.fda.gov/OHRMS/DOCKETS/AC/07/briefing/2007-4284b1_03.pdf, 2007, 12 pages. |
| FDA—Medtronic Inc., “Chronicle 9520B Implantable Hemodynamic Monitor Reference Manual”, 2007, 112 pages. |
| Flach, U.S. Appl. No. 60/006,600, filed Nov. 13, 1995. |
| Fonarow, “How well are chronic heart failure patients being managed”, Rev Cardiovasc Med., vol. 7 Suppl 1, 2006, pp. S3-S11. |
| Fonarow, “Maximizing Heart Failure Care”, PowerPoint Presentation, downloaded from http://www.medreviews.com/media/MaxHFCore.ppt, date unknown, 130 pages. |
| Fonarow, “Proactive monitoring and management of the chronic heart failure patient”, Rev Cardiovasc Med., vol. 7 Suppl 1, 2006, pp. S1-S2. |
| Fonarow et al., “Risk stratification for in-hospital mortality in acutely decompensated heart failure: classification and regression tree analysis”, JAMA, vol. 293 (5), Feb. 2, 2005, pp. 572-580. |
| Fonarow, “The Acute Decompensated Heart Failure National Registry (ADHERE): opportunities to improve care of patients hospitalized with acute decompensated heart failure”, Rev Cardiovasc Med., vol. 4 Suppl 7, 2003, pp. 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., vol. 11 (4), 2005, pp. 177-181, 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. |
| Gheorghiade et al., “Congestion is an important diagnostic and therapeutic target in heart failure”, Rev Cardiovasc Med., vol. 7 Suppl 1, 2006, pp. 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, vol. 30 (1), Jan. 18, 2007, pp. 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., vol. 40 (4), Oct. 2007, pp. 336-342. |
| Gniadecka et al., “Localization of dermal edema in lipodermatosclerosis, lymphedema, and cardiac insufficiency high-frequency ultrasound examination of intradermal echogenicity”, J Am Acad oDermatol, vol. 35 (1), Jul. 1996, pp. 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, vol. 416 (4), Oct. 2003, pp. 705-712. |
| Grap et al., “Actigraphy in the Critically III: Correlation with Activity, Agitation, and Sedation”, American Journal of Critical Care, vol. 14, 2005, pp. 52-60. |
| Gudivaka et al., “Single and multifrequency models for bioelectrical impedance analysis of body water compartments”, J Appl Physiol, vol. 87 (3), 1999, pp. 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 and 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., vol. 68 (4), 2004, pp. 343-347. |
| Hallstrom et al., “Structural relationships between measures based on heart beat intervals: potential for improved risk assessment”, IEEE Biomedical Engineering, vol. 51 (8), 2004, pp. 1414-1420 |
| Heart Failure, Wikipedia Entry, downloaded from http://en.wikipedia.org/wiki/Heart_failure, downloaded Feb. 11, 2011, 17 pages. |
| HFSA Comprehensive Heart Failure Practice Guideline—Executive Summary: HFSA Comprehensive Heart Failure Practice Guideline, Journal of Cardiac Failure, vol. 12 (1), 2006, pp. E86-E103. |
| HFSA Comprehensive Heart Failure Practice Guideline—Section 12: Evaluation and Management of Patients with Acute Decompensated Heart Failure, Journal of Cardiac Failure, vol. 12 (1), 2006, pp. E86-E103. |
| HFSA Comprehensive Heart Failure Practice Guideline—Section 2: Conceptualization and Working Definition of Heart Failure, Journal of Cardiac Failure, vol. 12 (1), 2006, pp. E10-E11. |
| HFSA Comprehensive Heart Failure Practice Guideline—Section 4: Evaluation of Patients for Ventricular Dysfunction and Heart Failure, Journal of Cardiac Failure, vol. 12 (1), 2006, pp. E16-E25. |
| HFSA Comprehensive Heart Failure Practice Guideline—Section 8: Disease Management in Heart Failure Education and Counseling, Journal of Cardiac Failure, vol. 12 (1), 2006, pp. E58-E68. |
| HFSA Comprehensive Heart Failure Practice Guideline—Section 3: Prevention of Ventricular Remodeling Cardiac Dysfunction, and Heart Failure Overview, Journal of Cardiac Failure, vol. 12 (1), 2006, pp. E12-E15. |
| HRV Enterprises LLC, “Heart Rate Variability Seminars”, downloaded from http://hrventerprise.com, downloaded Apr. 24, 2008, 3 pages. |
| HRV Enterprises LLC, “LoggerPro HRV Biosignal Analysis”, downloaded from http://hrventerprise.com/products.html, downloaded Apr. 24, 2008, 3 pages. |
| Hunt et al., “ACC/AHA 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:”, 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, vol. 112, 2005, E154-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”, Circulation, vol. 104, 2001, pp. 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, vol. 28 (8), 2000, pp. 21812-2818. |
| Jaeger et al., “Evidence for Increased Intrathoracic Fluid Volume in Man at High Altitude”, J Appl Physiol., vol. 47 (6), 1979, pp. 670-676. |
| 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. |
| Jerant et al., “Reducing the cost of frequent hospital admissions for congestive heart failure: a randomized trial of a home telecare intervention”, Medical Care, vol. 39 (11), 2001, pp. 1234-1245. |
| 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, vol. 39, 2002, pp. 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, vol. 17 (2), 2003, pp. 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, vol. 107, 2003, pp. 714-720. |
| Kawasaki et al., “Heart rate turbulence and clinical prognosis in hypertrophic cardiomyopathy and myocardial infarction”, Circ J., vol. 67 (7), 2003, pp. 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, vol. 40 (10), 2002, pp. 1801-1808. |
| Kitzman et al., “Pathophysiological characterization of isolated diastolic heart failure in comparison to systolic heart failure”, JAMA, vol. 288 (17), Nov. 2002, pp. 2144-2150. |
| Koobi 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, vol. 23 (11), 1997, pp. 1132-1137. |
| Koyama et al., “Evaluation of heart-rate turbulence as a new prognostic marker in patients with chronic heart failure”, Circ J, vol. 66 (10), 2002, pp. 902-907. |
| Kristofer et al., U.S. Appl. No. 60/972,336, filed Sep. 14, 2007. |
| Kristofer et al., U.S. Appl. No. 60/972,340, filed Sep. 14, 2007. |
| Kristofer et al., U.S. Appl. No. 60/972,343, filed Sep. 14, 2007. |
| Krumholz et al., “Predictors of readmission among elderly survivors of admission with heart failure”, American Heart Journal, vol. 139 (1), 2000, pp. 72-77. |
| Kyle et al., “Bioelectrical Impedance Analysis—part I: review of principles and methods”, Clin Nutr., vol. 23 (5), Oct. 2004, pp. 1226-1243. |
| Kyle et al., “Bioelectrical Impedance Analysis—part II: utilization in clinical practice”, Clin Nutr., vol. 23 (5), Oct. 2004, pp. 1430-1453. |
| Lauer et al., “Impaired Chronotropic Response to Exercise Stress Testing as a Predictor of Mortality”, JAMA, vol. 281 (6), 1999, pp. 524-529. |
| Lee et al., “Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model”, JAMA, vol. 290 (19), 2003, pp. 2581-2587. |
| Leier, “The Physical Examination in Heart Failure—Part I”, Congest Hear Fail., vol. 13 (1), Jan.-Feb. 2007, pp. 41-47. |
| Libbus et al., U.S. Appl. No. 60/972,316, filed Sep. 12, 2008. |
| Libbus et al., U.S. Appl. No. 60/972,512, filed Sep. 14, 2007. |
| Libbus et al., U.S. Appl. No. 60/972,581, filed Sep. 14, 2007. |
| Libbus et al., U.S. Appl. No. 60/972,616, filed Sep. 14, 2007. |
| Libbus et al., U.S. Appl. No. 61/035,970, filed Mar. 12, 2008. |
| Libbus et al., U.S. Appl. No. 61/047,875, filed Apr. 25, 2008. |
| Libbus et al., U.S. Appl. No. 61/055,656, filed May 23, 2008. |
| LifeShirt Model 200 Directions for Use, Introduction, VivoMetrics, Inc., date unknown, 9 pages. |
| Liu et al., “Fractal analysis with applications to seismological pattern recognition of underground nuclear explosions”, Signal Processing, vol. 80 (9), Sep. 2000, pp. 1849-1861. |
| 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, vol. 139 (6), 2000, pp. 1088-1095. |
| Luthje et al., “Detection of heart failure decompensation using intrathoracic impedance monitoring by a triple-chamber implantable defibrillator”, Heart Rhythm, vol. 2 (9), Sep. 2005, pp. 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, vol. 8 (2), 2002, pp. 63-70. |
| Mahlberg et al., “Actigraphy in agitated patients with dementia: Monitoring treatment outcomes”, Zeitschrift fur Gerontologie und Geriatrie, vol. 40 (3), Jun. 2007, pp. 178-184. |
| Manicka et al., U.S. Appl. No. 60/972,329, filed Sep. 14, 2007. |
| Manicka et al., U.S. Appl. No. 60/972,537, filed Sep. 14, 2007. |
| Manicka et al., U.S. Appl. No. 61/055,666, filed May 23, 2008. |
| Matthie et al., “Analytic assessment of the various bioimpedance methods used to estimate body water”, Appl Physiol, vol. 84 (5), 1998, pp. 1801-1816. |
| Matthie et al., “Second generation mixture theory equation for estimating intracellular water using bioimpedance spectroscopy”, J Appl Physiol, vol. 99, 2005, pp. 780-781. |
| Mazar et al., U.S. Appl. No. 60/972,354, filed Sep. 14, 2007. |
| Mazar, U.S. Appl. No. 61/046,196, filed Apr. 18, 2008. |
| McMurray et al., “Heart Failure: Epidemiology, Aetiology, and Prognosis of Heart Failure”, Heart, vol. 83, 2000, pp. 596-602. |
| Miller, “Home monitoring for congestive heart failure patients”, Caring Magazine, Aug. 1995, pp. 53-54. |
| Moser et al., “Improving outcomes in heart failure: it's not unusual beyond usual Care”, Circulation, vol. 105, 2002, pp. 2810-2812. |
| Nagels et al., “Actigraphic measurement of agitated behaviour in dementia”, International Journal of Geriatric Psychiatry, vol. 21 (4), 2009, pp. 388-393. |
| Nakamura et al., “Universal scaling law in human behavioral organization”, Physical Review Letters, vol. 99 (13), Sep. 28, 2007, 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, vol. 11 (B1), Jan. 2005, pp. B01310.1-B01310.15. |
| Naylor et al., “Comprehensive discharge planning for the hospitalized elderly: a randomized clinical trial”, Amer. College Physicians, vol. 120 (12), 1994, pp. 999-1006. |
| Nesiritide (Natrecor), “Acutely Decompensated Congestive Heart Failure: Burden of Disease”, Presentation, downloaded from http://www.huntsvillehospital.org/foundation/events/cardiologyupdate/CHF.ppt, date unknown, 39 pages. |
| Nieminen et al., “EuroHeart Failure Survey II (EHFSII): a survey on hospitalized acute heart failure patients: description of population”, European Heart Journal, vol. 27 (22), 2006, pp. 2725-2736. |
| Nijsen et al., “The potential value of three-dimensional accelerometry for detection of motor seizures in severe epilepsy”, Epilepsy Behav., vol. 7 (1), Aug. 2005, pp. 74-84. |
| Noble et al., “Diuretic induced change in lung water assessed by electrical impedance tomography”, Physiol. Meas., vol. 21 (1), 2000, pp. 155-163. |
| Noble et al., “Monitoring patients with left ventricular failure by electrical impedance tomography”, Eur J Heart Fail., vol. 1 (4), Dec. 1999, pp. 379-384. |
| O'Connell et al., “Economic impact of heart failure in the United States: time for a different approach”, J Heart Lung Transplant., vol. 13, (4), Jul.-Aug. 1994, p. S107-S112. |
| Ohlsson et al., “Central hemodynamic responses during serial exercise tests in heart failure patients using implantable hemodynamic monitors”, Eur J Heart Fail., vol. 5 (3), Jun. 2003, pp. 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 hemodynamic monitor”, European Heart Journal, vol. 22 (11), 2001, pp. 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, vol. 47 (11), 2006, pp. 2245-2252. |
| Palatini et al., “Predictive value of clinic and ambulatory heart rate for mortality in elderly subjects with systolic hypertension”, Arch Intern Med., vol. 162, 2002, pp. 2313-2321. |
| Piiria et al., “Crackles in patients with fibrosing alveolitis bronchiectasis, COPD, and Heart Failure”, Chest, vol. 99 (5), May 1991, pp. 1076-1083. |
| Pocock et al., “Predictors of mortality in patients with chronic heart failure”, Eur Heart J, vol. 27, 2006, pp. 65-75. |
| Poole-Wilson et al., “Importance of control of fluid volumes in heart failure”, European Heart Journal, vol. 22 (11), 2000, pp. 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, vol. 112, 2005, pp. E37-E38. |
| Ramirez et al., “Prognostic value of hemodynamic findings from impedance cardiography in hypertensive stroke”, AJH, vol. 18 (20), 2005, pp. 65-72. |
| Rich et al., “A multidisciplinary intervention to prevent the readmission of elderly patients with congestive heart failure”, New Engl. J. Med., vol. 333, 1995, pp. 1190-1195. |
| Roglieri et al., “Disease management interventions to improve outcomes in congestive heart failure”, Am J. Manag Care., vol. 3 (12), Dec. 1997, pp. 1831-1839. |
| Sahalos et al., “The electrical impedance of the human thorax as a guide in evaluation of intrathoracic fluid volume”, Phys. Med. Biol., vol. 31, 1986, pp. 425-439. |
| Saxon et al., “Remote active monitoring in patients with heart failure (rapid-rf): design and rationale”, Journal of Cardiac Failure, vol. 13 (4), 2007, pp. 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, vol. 41, 2003, pp. 572-573. |
| Small, “Integrating monitoring into the infrastructure and workflow of routine practice: OptiVol”, Rev Cardiovasc Med., vol. 7 Supp 1, 2006, pp. S47-S55. |
| Smith et al., “Outcomes in heart failure patients with preserved ejection fraction: mortality, readmission, and functional decline”, J Am Coll Cardiol, vol. 41, 2003, pp. 1510-1518. |
| Starling, “Improving care of chronic heart failure: advances from drugs to devices”, Cleveland Clinic Journal of Medicine, vol. 70 (2), Feb. 2003, pp. 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, vol. 21 (10), Oct. 1997, pp. 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., vol. 158, 1998, pp. 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 randomized controlled study”, The Lancet, vol. 354 (9184), Sep. 1999, pp. 1077-1083. |
| Stewart et al., “Home-based intervention in congestive heart failure: long-term implications on readmission and survival”, Circulation, vol. 105, 2002, pp. 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., vol. 159, 1999, pp. 257-261. |
| Stewart et al., “Trends in Hospitalization for Heart Failure in Scotland. An Epidemic that has Reached Its Peak?”, European Heart Journal, vol. 22 (3), 2001, pp. 209-217. |
| Swedberg et al., “Guidelines for the diagnosis and treatment of chronic heart failure: executive summary: The task force for the diagnosis and treatment of chronic heart failure of the European Society of Cardiology”, Eur Heart J., vol. 26 (11), Jun. 2005, pp. 1115-1140. |
| Tang, “Case studies in advanced monitoring: OptiVol”, Rev Cardiovasc Med., vol. 7 Suppl 1, 2006, pp. S62-S66. |
| The Economist, “Something in the way he moves”, retrieved from http://www.economist.com/science/printerFriendly.cfm?storyid=9861412, 2007. |
| The Escape Investigators, and Escapte Study Coordinators, “Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness”, JAMA, vol. 294, 2005, pp. 1625-1633. |
| Tosi et al., “Seismic signal detection by fractal dimension analysis”, Bulletin of the Seismological Society of America, vol. 89 (4), Aug. 1999, pp. 970-977. |
| Van De Water et al., “Monitoring the chest with impedance”, Chest, vol. 64, 1973, pp. 597-603. |
| Van Someren, “Actigraphic monitoring of movement and rest-activity rhythms in aging, Alzheimer's disease, and Parkinson's disease”, IEEE Transactions on Rehabilitation Engineering, vol. 5 (4), Dec. 1997, pp. 394-398. |
| Vasan et al., “Congestive heart failure in subjects with normal versus reduced left ventricular ejection fraction”, J Am Coll Cardiol, vol. 33, 1999, pp. 1948-1955. |
| Verdecchia et al., “Adverse prognostic value of an blunted circadian rhythm of heart rate in essential hypertension”, Journal of Hypertension, vol. 16 (9), 1998, pp. 1335-1343. |
| Verdecchia et al., “Ambulatory pulse pressure: a potent predictor of total cardiovascular risk in hypertension”, Hypertension, vol. 32, 1998, pp. 983-988. |
| Vollmann et al., “Clinical utility of intrathoracic impedance monitoring to alert patients with an implanted device of deteriorating chronic heart failure”, European Heart Journal Advance Access, downloaded from http://eurheartj.oxfordjournals.org/cgi/content/full/ehl506v1, Feb. 19, 2007, 6 pages. |
| Vuksanovic et al., “Effect of posture on heart rate variability spectral measures in children and young adults with heart disease”, International Journal of Cardiology, vol. 101 (2), 2005, pp. 273-278. |
| Wang et al., “Feasibility of using an implantable system to measure thoracic congestion in an ambulatory chronic heart failure canine model”, PACE, vol. 28 (5), 2005, pp. 404-411. |
| Wickemeyer et al., “Association between atrial and ventricular tachyarrhythmias, intrathoracic impedance and heart failure decompensation in CRT-D Patients”, Journal of Cardiac Failure, vol. 13 (6), 2007, pp. S131-S132. |
| 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, vol. 150 (5), date unknown, pp. E1-E983. |
| Wonisch et al., “Continuous hemodynamic monitoring during exercise in patients with pulmonary hypertension”, Int J Cardiol., vol. 101 (3), Jun. 8, 2005, pp. 415-420. |
| Wynne et al., “Impedance cardiography: a potential monitor for hemodialysis”, Journal of Surgical Research, vol. 133 (1), 2006, pp. 55-60. |
| Yancy, “Current approaches to monitoring and management of heart failure”, Rev Cardiovasc Med., vol. 7 Suppl 1, 2006, pp. S25-S32. |
| Ypenburg et al., “Intrathoracic Impedance Monitoring of Predict Decompensated Heart Failure”, Am J Cardiol, vol. 99 (4), 2007, pp. 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, vol. 112, 2005, pp. 841-848. |
| Zannad et al., “Incidence, clinical and etiologic features, and outcomes of advanced chronic heart failure: The EPICAL Study”, J Am Coll Cardiol, vol. 33 (3), 1999, pp. 734-742. |
| Zile, “Heart failure with preserved ejection fraction: is this diastolic heart failure?”, J Am Coll Cardiol., vol. 41 (9), 2003, pp. 1519-1522. |
| 3M Corporation, “3M Surgical Tapes—Choose the Correct Tape”, quicksheet, 2004. |
| Braunschweig et al., “Dynamic Changes in Right Ventricular Pressures During Haemodialysis Recorded with an Implantable Haemodynamic Monitor,” Nephrology Dialysis Transplantation, vol. 21, No. 1, Feb. 2006, pp. 176-183. |
| Prosecution History from U.S. Appl. No. 12/910,076, dated Feb. 1, 2013 through Jun. 6, 2014, 68 pp. |
| Prosecution History from U.S. Appl. No. 14/310,105, dated Sep. 2, 2014 through Dec. 22, 2016, 68 pp. |
| International Preliminary Report on Patentability from International Application No. PCT/US2010/053788, dated Apr. 24, 2012, 12 pp. |
| International Search Report and Written Opinion of International Application No. PCT/US2010/053788, dated May 17, 2011,17 pp. |
| Number | Date | Country | |
|---|---|---|---|
| 20170164841 A1 | Jun 2017 | US |
| Number | Date | Country | |
|---|---|---|---|
| 61253866 | Oct 2009 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 14310105 | Jun 2014 | US |
| Child | 15441400 | US | |
| Parent | 12910076 | Oct 2010 | US |
| Child | 14310105 | US |
