Monitoring and diagnostics systems and methods

Information

  • Patent Grant
  • 11259715
  • Patent Number
    11,259,715
  • Date Filed
    Tuesday, September 8, 2015
    9 years ago
  • Date Issued
    Tuesday, March 1, 2022
    2 years ago
Abstract
Embodiments of the present disclosure provide methods, apparatuses, devices and systems for measuring vital signs in human and animals by interrogating electromagnetic signals reflected from tissues in a human or animal subject. Probes may transmit radio frequency electromagnetic waves into a living body and generate signals responsively to the waves that are scattered from within the body. Such embodiments may be suitable for wearable devices as well as for use by medical practitioners.
Description
FIELD OF THE DISCLOSURE

Radio-frequency (RF) electromagnetic radiation has been used for diagnostics and imaging purposes of body tissues. For example, RF electromagnetic waves may be transmitted into a living body and generate signals responsively to the waves that are scattered from within the body. Analysis of the received signals allow for the monitoring of the various tissues within the living body.


SUMMARY OF SOME OF THE EMBODIMENTS

Embodiments of the present disclosure provide methods, apparatuses, devices and systems for measuring vital signs of a subject, comprising a probe, at least one circuit and a processor having computer instructions operating thereon. In some embodiments, the probe is configured to be placed on or adjacent to skin of a subject, and generate one or more first radio-frequency (RF) waves for transmission towards a tissue and receive reflected RF waves therefrom. In some embodiments, the at least one circuit is configured to cause the probe to generate the first RF waves, and generate at least one signal corresponding to one or more of the reflected RF waves received by the probe. In some embodiments, the one or more first RF waves include one or more first characteristics, the one or more reflected RF waves include one or more second characteristics and the at least one signal includes information corresponding to at least one of the one or more second characteristics. Further, in some embodiments, the computer instructions are configured to cause the processor to determine at least one vital sign of the subject based upon one or more of the second characteristics and/or the difference between one or more of the second characteristics and one or more of the first characteristics of one or more of the reflected RF waves.


In some embodiments, the probe can comprise a monostatic radar, a bistatic radar, and/or a dielectrometer comprising a first conductor and a second conductor. The probe may be configured with flexibility for conforming the probe to the skin of the subject, and may also be configured to be placed on or adjacent to the skin of the subject via a wearable device or garment or an adhesive, or, an implantable device configured to be placed in proximity to the tissue. In some embodiments, the wearable garment comprises at least one of an article of clothing, a collar, a wrist strap, an ear tag, and a skin patch.


In some embodiments, the one or more first RF waves comprise stepped-frequency RF waves, continuous-frequency RF wave, and/or the like. Further, the at least one circuit is configured to cause the probe to generate the first RF waves and to receive the reflected RF wave at a plurality of frequencies, wherein the plurality of frequencies can range from about 200 MHz to about 3 GHz.


In some embodiments, the processor's computer instructions are further configured to cause the processor to resolve the at least one signal and/or the received reflected RF waves according to one or more depths into the subject from which one or more of the reflected RF waves occurred. Further, the computer instructions are configured to cause the processor to condition the at least one signal and/or the received, reflected RF waves using band pass filtering. In some embodiments, the probe may be placed in proximity to an artery, and the computer instructions are further configured to cause the processor to determine a time rate of occurrence of prominent peaks in a pulse waveform of the at least one signal and/or the received, reflected RF waves, and wherein the time rate corresponds to a heart rate of the subject. In such embodiments, the computer instructions can also be configured to cause the processor to identify a prominent peak frequency in a frequency range relevant to heartbeats of the subject from a power spectrum density of the at least one signal and/or the received, reflected RF waves. For example, the frequency range for the at least one signal and/or one or more first RF waves may correspond to between 0.5 Hz to 2.5 Hz. In some embodiments, the computer instructions are further configured to cause the processor to determine a heart rate of the subject as a function of the peak frequency.


In some embodiments, the probe can be placed at least in proximity to a torso of the subject, and the computer instructions are further configured to cause the processor to identify a prominent peak frequency in a frequency range of the received, reflected RF waves corresponding to respirations of the subject from a fast Fourier transform of the returned signal. For example, the frequency range can be between 0.1 Hz to 1 Hz. In some embodiments, the computer instructions are further configured to cause the processor to determine a respiration rate of the subject as a function of the peak frequency.


In some embodiments, the probe can be placed at least in proximity to a torso of the subject, and the computer instructions can be further configured to cause the processor to identify a prominent peak frequency in a frequency range of the received, reflected RF waves corresponding to respirations of the subject from a fast Fourier transform of the returned signal. For example, the frequency range can be between 0.1 Hz to 1 Hz. In some embodiments, the computer instructions are further configured to cause the processor to determine a respiration rate of the subject as a function of the peak frequency.


In some embodiments, the at least one signal and/or the received, reflected RF waves correspond to reflections from at least two different arterial tree locations of arteries of the subject, and the computer instructions can be further configured to cause the processor to: determine an arterial-pulse-arrival-time (PAT) at each of the two different arterial tree locations, and calculate a difference between the PAT at the two locations so as to determine an arterial-pulse-travel-time (PTT). In some embodiments, the at least one signal and/or the received, reflected one or more RF waves correspond to form at least two different arterial tree locations of arteries of the subject, and the computer instructions are further configured to cause the processor to: determine arterial-pulse-arrival-time (PAT) at each of the two different arterial tree locations, and calculate a difference between the PAT at the two locations so as to determine an arterial-pulse-travel-time (PTT). In some embodiments, the probe comprises a first sensor and a second sensor, the first sensor configured for receiving a first reflected RF wave from a first arterial tree location and the second sensor configured for receiving a second reflected RF wave from a second arterial tree location, the computer instructions are further configured to cause the processor to determine arterial-pulse-arrival-time (PAT) at each location, and calculate a difference between the PAT at the two locations so as to determine an arterial-pulse-travel-time (PTT).


In any of the above embodiments, the two arterial tree locations may comprise different locations on same arterial tree, locations on different arterial trees on same area of the body of a patient, locations on arterial trees on different areas of the body of a patient, and/or the like. Further, the computer instructions can be configured to cause the processor to determine a blood pressure of the subject as a function of the PTT.


In some embodiments, the probe comprises a dielectrometer comprising a first conductor and a second conductor; and the computer instructions can be further configured to cause the processor to calculate a complex permittivity from the at least one signal and/or one or more of the received, reflected RF waves by measuring an impedance between the first conductor and the second conductor.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows examples of use cases corresponding to some embodiments of the Vital Signs Radar and Dielectrometer (VSRD) systems to measure vital signs, in one embodiment of the VSRD.



FIG. 2 shows an example of the electrical components comprised in one embodiment of the VSRD sensor.



FIG. 3 shows example embodiments of the VSRD sensors, a human and an animal subject wearing the sensor.



FIG. 4 shows an example method to perform a heart rate calculation in one embodiment of the VSRD system.



FIGS. 5A-B show example heart rate measurements of a subject taken with the VSRD sensor, in one embodiment of the VSRD system.



FIG. 6 shows examples of measurements taken with the VSRD sensor: blood pulse wave (shown next to an electrocardiogram for reference), in one embodiment of the VSRD system.



FIG. 7 shows an example method to calculate pulse pressure based on systolic and diastolic blood pressure points, in one embodiment of the VSRD system.



FIG. 8 an example method performed by the VSRD process to calculate a subject's heart rate, in one embodiment of the VSRD system.





DETAILED DESCRIPTION OF SOME OF THE EMBODIMENTS

Embodiments of the present disclosure provide methods, apparatuses, devices and systems, for measuring humans and animals' vital signs utilizing a miniature medical RF sensor or transceiver and/or a dielectrometer. The vital signs of humans and animals alike that can be monitored include, but are not limited to, blood pressure, heart and respiration rates. Some of these embodiments may further include the monitoring of body temperature. For example, a temperature sensor incorporated in the apparatuses, devices and systems may be used to acquire a body temperature reading. In addition, the disclosed embodiments can provide means to detect muscle movements. In some instances, analysis of the monitored vital signs and/or the detected muscle movements may allow for the determination of the state, activity or behavior of the monitored animal or human. For example, by monitoring the muscle neck movements of cattle, one may determine that an animal is regurgitating. As another example, based on the vital signs readings (e.g., heart rate, body temperature, etc.) and/or muscle movement detection, embodiments of the present disclosure allow for determining the physical/physiological state of the animal or human body (e.g., active, stressed, fed, etc.).


Such embodiments of the present disclosure may be suitable for implementation as skin patches, ear tags, and/or may be integrated with wearable devices, embedded in clothing, mounted on a limb (e.g., wrist) or collar strap, and/or the like wearable embodiments. Other embodiments may comprise subcutaneous implements. In some embodiments, the apparatus or device is portable and is not physically tethered to other devices. Additionally, some embodiments may comprise an accelerometer or other movement sensor to determine the state of motion of the subject when a measurement is to be or being taken. For example, the device may be sensitive to motion, and the reliability of the measurements by the device may depend on the device's state of motion when the measurements are being taken. In some embodiments, an accelerometer (e.g., three-axial) may accompany the device, and the RF measurements may be calibrated based on the readings of the accelerometer (e.g., measurements may be conditioned or calibrated for low acceleration). In some embodiments, measurements may not take place or, if taken, the results may be discounted, if the readings show unacceptable state of motion (e.g., the measurements may not be accurate or reliable).


In some embodiments, the sensor is nonintrusive with respect to a subject and can read the subject's vital signs and other indications without requiring active intervention (from the subject or another), such vital signs and indications including heart rate, respiration rate, blood pressure, body temperature and/or RF-tonometry. Moreover, in some embodiments, the sensor can work directly over a subject's skin (e.g., with and without skin adhesives), clothing, fur and/or the like. The ease of use of the disclosed methods, apparatuses, devices and systems facilitates the monitoring of large numbers of subjects as is the case, for example, with livestock. For example, ear tags and neck collars comprising the disclosed RF sensor and/or dielectrometer can be used to measure the various physiological conditions and health state (e.g., vital signs, muscle movements, etc.) of large number of cattle, easing the difficulties presented when monitoring a large number of subjects.


In some of the embodiments of the present disclosure, apparatus, device and/or system configured to determine at least one of a subject's heart rate, respiration rate, blood pressure and body temperature are provided. In some embodiments, a sensor coupled to a subject's body may transmit radio frequency (RF) waves into the body tissue and receive reflected waves from the tissue. In one embodiment, the sensor can achieve range (depth) resolution allowing for the isolation of the reflections from the desired depth in the subject's body from other concurrent reflections or interferences. For example, based on an estimate of the depths of arteries and muscles in the line of sight of the transmitted and/or reflected signals, signals reflected from these tissues may be classified according to the reflecting tissue. For example, a frequency shift in the reflected signal can be used to determine the depths from which the reflections occurred, and knowledge of locations of tissues along the signal path leads to the identification of the tissue. As such, this resolution of the reflected signals allows for the proper identification of the tissue whose behavior is being monitored for determining vital signs and muscle activities of the subject body.


To determine the frequency shift of a reflected signal, in some embodiments, an analysis of the phase changes with respect to the transmitted signal may be performed. For example, a signal reflected from a distance d accrues a phase change proportional to the distance d compared to the transmitted signal, i.e., the transmitted signal's phase shifts to ei(t−2d/c) compared to the transmitted signal's eit. The change in the phase, e−jωi2d/c, which can be obtained after down conversion with e−jωit, can be interpreted as a frequency shift proportional to reflection distance d. Alternatively, the distance d can be determined based on the time of arrival of the signal after reflection. In some embodiments, a Fourier transform of the received signal may be performed to generate an image comprising frequency information of the reflected signal.


In some embodiments, the apparatus includes radar and/or a dielectrometric probe configured to transmitting signals of varied waveforms. For example, the radar and/or dielectrometric probe may transmit signals with continuous or stepped radio frequencies. In some embodiments, the radio frequencies can range from about 200 MHz to about 3 GHz, from about 200 MHz to about 300 MHz, from about 300 MHz to about 1 GHz, from about 1 GHz to about 2 GHz, from about 2 GHz to about 3 GHz, and/or the like. In some embodiments, a narrow band or a single frequency can be used for heart rate and respiration rate measurements. For example, a narrow band frequency range of from about 0.9 GHz to about 1 GHz, 1 GHz to about 1.1 GHz, 1.1 GHz to about 1.2 GHz, etc., and/or a single frequency of about 0.9 GHz, 1 GHz, 1.1 GHz, etc., can be used in monitoring heart and respiration rates of a human or animal subject.


In some embodiments, the sensor can be attached to a subject's body by a plurality of further embodiments, including but not limited to, skin patches enhanced with skin-friendly adhesive, pieces of clothing with the sensor embedded thereon (e.g., stockings, shirts, etc.), utilizing a wearable strap or collar, wrist based wears, an ear tag (e.g., for animals), a subcutaneous implant and/or the like embodiments. In some instances, the sensor may be configured with flexibility that allows the sensor to conform to the skin of the patient.


In some embodiments, when the sensor is attached to a subject's skin in proximity to an artery, the sensor can measure the subject's heart rate. In such embodiments, a plurality of reflected radar signals is received by the sensor modulated by the different tissue layers, positioned at different depths within the body. For example, the radar signals may be in the form of stepped-frequency. These signals can be filtered to isolate the signal corresponding to a subject's prominent artery thus, detecting the artery's modulation. For example, by estimating the depth of the different tissue layers (arteries, muscles, etc.), the signals reflected by a respective tissue layer may be identified. Upon the identification of reflected signals according to the reflecting tissue layer, the reflected signals may be analyzed to determine properties or behaviors of the tissue layers. For example, the sensor can analyze changes in amplitude from isolated signal reflected from an artery to determine the arterial pulse wave and thenceforth calculate the subject's heart rate, blood pressure, and/or the like. For example, the rate of the prominent peaks appearing in the signal waveforms can be used to calculate the heart rate. In some embodiments, “prominent peaks” refer to amplitude values in the signal waveform that exceed other nearby amplitude values (as a function of time, frequency, etc.).


In some embodiments, RF signal reflected from within a subject's body may be analyzed to determine the depths from which the signals are reflected from. For example, depths of tissues such as arteries, muscles, etc., may be estimated and a determination may be made as to which tissue a reflected signal came from. In this manner, changes in the reflected signal (for example, as they relate to the transmitted signal) may be analyzed to identify properties and/or behaviors of the reflecting tissue. For example, one may estimate the depth of an artery, and identify or isolate the RF signal whose reflection depth at least substantially matches the depth of the artery. This reflected wave then may be analyzed to obtain the arterial pulse waveform of the reflecting artery. For example, the signal may be filtered to enhance signal quality, examples of such filtering including low pass filtering to remove noise artifacts. In some embodiments, one may identify some or all prominent peaks in the filtered or unfiltered signals and estimate the rate of the peaks. For example, the time separation between peaks may at least substantially correspond to the period (e.g., average) of the heart rate of the subject being monitored. Alternatively, or in conjunction, in some embodiments, one may calculate the power spectrum density (PSD) of the signal and estimate from the PSD the frequency of the prominent peaks in the frequency range relevant to the heart rate, which one may then ascribe to the heart rate.


In some embodiments, when the sensor is attached to a subject's torso, the reflected signals can be modulated by a respiration cycle of the subject, i.e., the reflected signal may contain signatures of the subject's respiration, including the respiration rate. An analysis of the reflected signal can then isolate the frequency of the respiration. For example, the sensor can calculate the subject's respiration rate form the sensor signals by collecting the reflected signals received by the sensor, and performing a fast Fourier transformation (FFT) to the signals to determine the peak frequencies in the FFT signals. In some embodiments, one may identify a peak frequency in the respiration frequency range relevant to respirations of subjects as the respiration rate of the subject. The frequency range may depend on a variety of factors such as the subject's state (e.g., active vs. passive), etc. In any case, the range may be estimated and a peak in the range can then be ascribed to the respiration rate.


In some embodiments, a subject's blood pressure can be calculated from the arterial's pulse waveform detected by the sensor. For example, the sensor can estimate the depth of a prominent artery and utilize the received reflected signals substantially corresponding to such depth to obtain a signal corresponding to the arterial pulse waveform. In some embodiments, the reflected signals are modulated by the artery as it changes its radar cross section (RCS). In some embodiments, the pulse waveform signal can be substantially identical to a tonometry signal. For example, the systolic and diastolic blood pressures can be determined by assigning the maximum value of the pulse waveform and the minimum value of the pulse waveform respectively to each pressure measurement.


In some embodiments, a plurality of sensors may be used to determine blood pressure measurements. For example, a pair of RF sensors may be located over two respective arteries along an arterial tree, and the time difference between pulse wave arrivals at the two locations may be measured by the sensors. The pulse wave velocity (PWV), corresponding to the velocity of propagation of the arterial pressure pulse between points along the arterial tree, and/or the pulse transit time (PTT), corresponding to the transit time, may be determined from the measurements of the sensors. The PWV and/or the PTT can be related to the blood pressure, and as such, the blood pressure may be determined from these measurements. For example, changes in the PTT can be correlated to blood pressure changes. The determination of blood pressure measurements using electromagnetic waves is discussed in PCT Publication No. WO/2015/118544, incorporated herein by reference in its entirety.


In some embodiments, the PTT at some point along the arterial tree (e.g., peripheral location in the arterial system) may be represented as the difference between the arrival time of the pulse at the point, the pulse arrival time (PAT), and the pre-ejection period (PEP), i.e., PTT=PAT−PEP. The PEP can be the lapse between the ventricular polarization and the opening of the aortic valve, which corresponds to the time it takes for the myocardium to raise sufficient pressure to open the aortic valve and start pushing blood out of the ventricle. Upon determining or estimating the PTT, in some embodiments, the PWV may then be calculated based on the distance the pulse traveled to arrive at the point and the estimated/determined PTT. In some implementations, blood pressure values such as systolic and/or diastolic values can be determined non-invasively from the PWV and/or the PTT. For example, linear transformations relating the systolic blood pressure (SBP) and diastolic blood pressure (DBP) to the PTT may be expressed as follow:

SBP=(a×PTT)+b,
DBP=(c×PTT)+d,

where the coefficients a, b, c and d can be calibrated for each patient. In some embodiments, other types of transformations may be used to calculate blood pressures. For example, for a model that assumes constant artery thickness and radius, blood pressure P may be expressed as P=a×ln(PTT)+b, where, again a and b are constants to be calibrated for each patient. In any case, in some embodiments, obtaining PTT, or conversely PWV of a pulse in an artery, may lead to the determination of blood pressure levels in the artery.


In some embodiments, the PTT of the pulse can be determined if the times of arrival of the pulse at two distinct locations can be measured. This follows because the PEP values of the pulse that originated at the same ventricle but arrived at the two different locations is the same, and accordingly, the difference in PAT for the two locations is the same as the difference in PTT of the pulse at the two distinct locations. For example, two RF sensors located at different locations on a body (e.g., the sternum and the thorax, two suitable locations along the leg, etc. of a human subject) can be used to sense the pulse wave going through arteries close to each RF sensor, and the difference in the times of arrival at the two locations can represent and be used to determine the PTT.


In some embodiments, the sensor comprises a dielectrometer probe configured to measure the dielectric properties of the tissue, and dielectrometer probe may be used in measuring the heart rate of a subject. For example, the dielectrometer can sense changes in the dielectric properties induced by the blood flow in an artery when a sensor is attached to a subject's skin in proximity to the artery. The measurement of the dielectric properties of physiological tissues is discussed in US/2013/0190646, incorporated herein by reference in its entirety.


In some embodiments, the sensor comprises a dielectrometric probe with a pair of conductors, which can be attached to a subject's skin in proximity to an artery. Thereafter, a driving circuit applies a radio-frequency signal to the probe and senses a signal returned from the probe in order to measure the impedance between the aforementioned conductors. The impedance varies as a function of the dielectric properties of the target tissue, e.g., the artery, including the relative permittivity, the conductivity and the loss or dissipation factor, which can be used to define the complex permittivity of the tissue. The driving circuit can apply the radio-frequency signal to the probe at a plurality of frequencies, so that the complex permittivity can be measured as a function of the frequency. A processing circuit may then evaluate the dielectric properties of the target tissue and calculate the impedance. Following the impedance calculation over frequency, an analysis of the signal can be carried out to estimate the heart rate, respiratory rate and arterial pulse waveform.


In a general material including loss and permittivity, impedance is defined as follows: η=jωμ/γ. Here ω is the radial frequency, and μ is the material permeability (which in the case of a biological tissue can equal the free space permeability μ=μ0). γ is the complex propagation constant which can be defined as γ=jω√(με0)√(ε′−jε″), wherein ε′ and ε″ are the real and imaginary parts of the complex permittivity, and the imaginary part of the complex permittivity is related to the conductivity via ε″=σ/ωε0. In some embodiments, the above expressions are thus used to relate the measured impedance, as a function of frequency, to the complex permittivity.


The impedance between the conductors due to the target tissue can be measured in a number of ways. In some embodiments, the driving circuit measures the reflection of the signal from the probe, which is indicative of an impedance mismatch at the target tissue at the end of the probe. In other embodiments, the driving circuit measures the delay of the signal transmitted through the probe, which is indicative of the permittivity of the target tissue. In other embodiments, the driving circuit measures a resonating frequency of a printed resonator (such as a ring or other shaped circuit), which is indicative of the properties of tissues in its proximity.


Using a dielectrometer, in some embodiments, one may measure the dielectric properties of target tissues, and sample the output of the dielectrometer over time to obtain the time dependence of the dielectric property. For example, the time dependence of the permittivity of the target tissue ε(t) may be determined from the sampled outputs of the dielectrometer. In some embodiments, ε(t) may be low pass filtered to remove noises, and some or all prominent peaks of the permittivity may be detected. From the rate of the prominent peaks, in some embodiments, the heart rate of the subject to which the sensor comprising the dielectrometer is coupled may be determined.


In some embodiments, the above procedure may be repeated with a plurality of frequencies, and in such embodiments, the steps of i) sampling the dielectrometer output to determine ε(t), ii) low-pass filtering the output/ε(t) to remove noise, iii) detecting prominent peaks from the signals in the frequency range of interest, and iv) determining the rate of the prominent peaks in the desired range can be performed for each frequency, and those frequencies that at least closely correspond to the periodicity of the heart rate may be used in determining the heart rate of the subject.


In some embodiments, the sensor comprises means to calibrate the amplitude of a waveform using a reference blood measurement device. The systolic and diastolic blood pressures can be determined by assigning the maximum value of the calibrated pulse waveform and the minimum value of the calibrated pulse waveform respectively to each measurement.


In some embodiments, the Vital Signs Radar and Dielectrometer (VSRD) sensor 112 utilizes an embedded radar to calculate measures of vital signs such as but not limited to respiration rate, blood pressure, heart rate, and/or body temperature. Heart rate measurements can additionally or alternatively be measured with an embedded dielectrometer. Examples of use cases corresponding to some embodiments of the (VSRD) sensor to measure vital signs are shown in FIG. 1. In some embodiments, a patient 101 has a sensor attached to his chest in direct proximity to one of his arteries. The sensor 112 can continuously collect vital signs data and send it through a network access point to a VSRD server 104 via a monitoring packet e.g., 105. In some embodiments, the telemetry communications can be performed via Bluetooth, Wi-Fi, cellular and the like wireless interfaces. Thereafter, a request to view the subjects vital signs e.g., 106 and 109 can be received from a physician's or from the patient's mobile device e.g., smart phone 103. In another embodiment, the request to view the human or animal vital signs e.g., 106 and 109 can be received from a physician's or from the patient's computer station e.g., 102. After receiving a vital signs request e.g., 106 and 109, the VSRD server 107 computes the requested signs.


In some embodiments, the described telemetry can be performed according to a predetermined scheduled regime for example, once a week, day, hour and/or other predetermined time units. In some embodiments, a VSRD can comprise a plurality of sensors including but not limited to an accelerometer, gyros, compass, temperature sensors, proximity detectors, and/or the like sensors. For example, in some embodiments of the VSRD, an embedded accelerometer can be employed to determine the time when a human or animal remains inactive, such a moment can be used to take a scheduled RF-based measurement, gaining accuracy and reliability of the collected sample. In some embodiments, the RF measurements may be made while the subject is on a state of motion, and the obtained measurements may be conditioned or calibrated based on the indication of the accelerometer on whether the subject was active or inactive. In some embodiments, measurements may be taken only when the accelerometer indicates the subject's mobility state is below some threshold (e.g., if the person's velocity is below five miles an hour). Additionally, determining inactive states via an accelerometer and/or the like sensors before collecting an RF-based measurement sample can reduce the amount of energy consumed by the device because an RF sampling device coupled to an accelerometer can consume less energy than an RF device by itself when it is compared to the expended energy utilized on retaking defective samples. Further details with regard to the computation of vital signs can be found with respect to FIG. 7 an example method performed by the VSRD process to calculate a subject's heart rate. Continuing with FIG. 1, after the data received from the monitoring packets e.g., 105 are processed the calculated vital signs can be sent wirelessly to a smart phone e.g., 103 and/or to a computer station e.g., 102. In some embodiments, the sensor 112 determines the vital signs by analyzing the data or RF measurements collected by the sensor itself.


In some embodiments, the monitoring packet 105 can be sent to a smart phone 103 which can compute the requested signs from the gathered RF measurements. The smart phone 103 can then send a vital sign response with the requested measurements to another computer station e.g., 102. In other embodiments sensor telemetry is collected by wireless radios spread around the measurement premises (such as a livestock farm). For example, RF measurements from RF sensors and/or dielectrometers mounted on livestock can be transmitted to a standalone server directly or via a network distributed over the livestock farm. In any case, the telemetry information can be collected into one or more servers and can be accessed directly or via the internet (e.g. using a smartphone).



FIG. 2 shows an example of the electrical components comprised in one embodiment of the VSRD sensor. In some embodiments, an oscillator 205 produces a high frequency microwave signal, for example, a signal between about 200 MHZ and about 3 GHz modulated by, or simply mixed with the signal generator 207. The signal produced by the oscillator 205 may be amplified by the amplifier 203 and then is transmitted to a subject's tissue through an electrode, conductor, or antenna e.g., 201 of a dielectrometric probe and/or radar, e.g., 212. In some embodiments, the VSRD sensor can be implemented comprising a bistatic radar, where the radar includes a transmitter and a receiver located separately, and/or a monostatic radar, where the transmitter and the receiver are collocated. Thereafter, the signal can be propagated to a tissue, and reflected back to the sensor in a plurality of modified signals wherein each signal from said plurality of modified reflected signals corresponds to an intersected member within the tissue. For example, the signal may have been reflected from arteries (e.g. anterior tibial, popliteal, brachial, carotid, etc.), muscles, etc.


In some embodiments, the plurality of reflected signals is received by an electrode or a conductor, e.g., 202 (which may be different than the first electrode 201) of the dielectrometric probe e.g., 212. This plurality of signals is changed in amplitude and/or phase, with respect to the transmitted signals and can be mixed with the original transmitted signal as outputted by the oscillator 205 to obtain an intermediate frequency signal or a beat frequency which reflects signal change; this signal can be further filtered by the band pass filter 208 to discern the signal that will be used to determine the dielectric properties of the targeted tissue, i.e., the artery. For example, the signal may be low-pass filtered to remove noise artifacts. The discerned signal may then be input into an analogue to digital converter, e.g., 210 which samples the signal at a determined rate. Alternatively, some or all of the filtration can be performed digitally. The sampled digital signal may then be input into a fast Fourier transform circuit, e.g., 213, to be further processed by the dielectrometer and radar processing circuit which determines the dielectric properties of the target tissue. These dielectric properties can be transmitted wirelessly to a computer via the antenna 211 to be further processed into vital signs statistics so they can be viewed by a patient, physician and or other interested subjects. Alternatively, in some embodiments, the sensor's electrode, conductor, or antenna e.g., 201 can also be utilized to transmit the aforementioned telemetry signals.


In some embodiments, when the VSRD sensor does not include a dielectrometric probe, in such embodiments, the signals transmitted and received by the radar are sufficient to calculate a human or animal heart rate, respiration rate and blood pressure by the methods and apparatuses presented in this disclosure. In some instances, if a temperature sensor is included in the VSRD sensor, a body temperature of the subject may also be determined (e.g., calculated, estimated or derived) by the noted apparatuses and methods.



FIG. 3 shows various example embodiments of VSRD sensors, a human and an animal subject wearing the sensor. Reference 301 shows an example of the sensor housing, the housing has two antennae, electrodes or conductors 302 which are in direct contact with the subject's skin, fur or clothing to transmit and receive microwave signals.


In another embodiment, the sensor housing can be enhanced with a strap, e.g., 304 to be attached to an animal's neck, e.g., 303 to monitor the animal's vital signs. Moreover, in some embodiments, the VSRD can determine when an animal is regurgitating based on signals collected from the movements of the animal neck's muscles.


Alternatively, in some embodiments, the VSRD sensor can be secured to an animal's ear and/or limb e.g., 308. Moreover, in some embodiments the secured VSRD sensor can be implemented comprising a bistatic radar i.e., a radar with a transmitter and a receiver on each side of the ear or limb and/or comprising a monostatic radar i.e., a radar with a transmitter and a receiver collocated on the same side of the ear or limb. In other further embodiments, a preexisting collar tag and/or a preexisting housing can be utilized to mount or attached the VSRD.



FIG. 3 shows a human body 305 that has a plurality of sensors in direct contact with the skin in proximity with various arteries, e.g., 306 and 307 corresponding to some embodiments of the VSRD. Such sensors can be attached to the human skin by enhancing the sensors with patches with skin friendly adhesives. In some embodiments, a variety of methods including skin patches (with or without adhesives), straps (chest straps, vests, etc.), wrist straps, tags, and/or the like can be used to mount or couple the sensors to the subject. In some embodiments, the mounting may be strategic in that the sensors may be mounted in the vicinity of the tissue being monitored or investigated by the sensors. For example, for respiration measurements, the sensors may be mounted on the torso of the subject. For muscle movement detections, the sensors may be mounted on the neck an animal, and/or the like.



FIG. 4 shows an example method to perform a vital sign calculation in one embodiment of the VSRD system, for example, heart or respiration rate. In one embodiment, the VSRD sensor samples a plurality of continuous or stepped wave signals over a period of time reflected from a tissue in a human or animal subject, e.g., 401. Such signals comprise or carry dielectric properties. In some embodiments, the sampled signals are filtered to retain only the signal or signals at a particular frequency or frequency range 402. For example, the signal may be filtered to focus on the frequency range of human or animal respiration if the calculation is for respiration rate, on the frequency range of heart beatings if the calculation is for heart rate, etc., e.g., 404. Further the signal may be filtered to remove noise, for example, the signal may be low-pass filtered. Thereafter, the filtered signal or signals are further processed to determine a peak value, that is, the maximum instantaneous value of the continuous waveform during the sampled time 403. Subsequently the signal is processed to determine how frequently a peak value emerges from the continuous wave signal 304 and then the heart or respiration rate can be calculated 405.



FIG. 5 shows examples of heart rate measurements taken with the VSRD. With reference to FIG. 5A, in some embodiments, the depth of a prominent artery along the signal propagation path within the subject is estimated, and the signal reflections corresponding to the estimated depth are utilized to determine the heart rate. The gathered signal reflection is filtered, e.g., low pass filtered, to remove noise artifacts, which may reveal peaks in the signal. In such embodiments, the detection of the prominent peak in the frequency range of the vital sign one is interested in determining (e.g., respiration frequency, heart rate range, etc.) allows one to estimate the rate of the prominent peaks, and hence the periodicity of the occurrence of the peaks. In other words, from the rate of the prominent peaks, one may determine the rate being measured (e.g., the heart rate).


With reference to FIG. 5B, in some embodiments, the PSD of the signal may be calculated and peaks may be detected in the frequency range being considered. In some embodiments, the frequency of the prominent peak may be related to the frequency of the rate being monitored. For example, for a heart rate measurement, one may consider frequency range from about 0.5 Hz to about 3.5 Hz to be the relevant frequency range and the frequency of the most prominent peak appearing in this range may be considered as the frequency of the heart rate.



FIG. 6 shows examples of measurements taken with the VSRD system: blood pulse wave (shown next to an electrocardiogram for reference) in one embodiment of the VSRD. In some embodiments, heart rate sensor measurements can be obtained by utilizing the sensor's embedded radar by positioning the sensor in proximity to a subject's artery. The heart rate can be measured from received radio frequency signals that have been reflected from their intersection with the subject's artery. Similarly, the sensor can calculate the respiration rate from the sensor signals by collecting the reflected signals received by the sensor, and detecting the principal frequency corresponding to the respiratory rate as described above.



FIG. 7 shows an example signal obtained by the VSRD sensor showing the pulse pressure based on systolic and diastolic blood pressure points, in one embodiment of the VSRD. In some embodiments, the subject's blood pressure can be obtained from the signal reflected from the subject's artery, e.g., 700. The amplitude of the signal waveform can be calibrated by utilizing a blood measurement device that serves as a reference blood pressure meter. Thereafter, the systolic blood pressure can be determined as a function of the maximum point of the calibrated pulse waveform, e.g., 701. Similarly, the diastolic blood pressure can be determined as a function of the minimum point of the calibrated pulse waveform e.g., 702. The difference between the maximum and the minimum points of the calibrated pulse waveform can correspond to the subject's pulse pressure. In some alternative embodiments, the time difference between peaks of pulse pressure waveforms, or equivalently the frequency of a transformed signal (e.g., FFT-transformed) can be utilized to assess the systolic and diastolic blood pressure.


In some embodiments of the VSRD, the RF signals employed to calculate measurements can comprise signals reflected from muscles in addition or alternatively to not signals reflected from an artery. For example, signals reflected from specific muscles within a tissue may be analyzed to determine when a human or animal is chewing. Such muscle signals are reflected from a different depth than the arteries and thus, they can be processed utilizing the methods and devices as described herein by adapting the corresponding signal frequencies. For example, an estimate of the depth of the muscle and isolation of the signals reflected from such muscle (based on frequency shifts, for example) allows one to identify the reflected signals with the muscles and apply the systems and methods disclosed herein to determine the desired properties of the muscle.



FIG. 8 shows an example method performed by the VSRD process to calculate a subject's heart rate, in one embodiment of the VSRD system. In one embodiment, a client device 801 sends a request of vital signs 803 to the VSRD process 802. Thereafter, the VSRD process evaluates if the request includes a request of heart-rate dielectrometer based measurement e.g., 804. If the request does not include a request of heart-rate dielectrometer based measurement then, the process can proceed to check for other requested vital signs based on radar measurements e.g., 805. If however, the request includes a heart-rate dielectrometer based measurement then the VSRD process enters a loop wherein for each of a frequency (PF) in a predetermined set of frequencies e.g., 806, the process determines dielectric properties of a tissue and calculates a complex dielectric permittivity (CDP) of the tissue based on the tissue's dielectric properties and can append the calculated (CDP) and (PF) to a CDP sample vector (CDP-SV) containing the complex dielectric permittivity of each predetermined frequency PF in the aforementioned set. Thereafter, an impedance value is calculated based on the values contained in the CDP sample vector (CDP-SV) e.g., 809 to correlate the impedance with a heart-rate value e.g., 810 and further send the calculated rate to the client device. In some embodiments, the CDP-SV is sampled over time allowing for the creation of a time-varying signal that can be used for determining a heart rate value. For example, the heart rate can be derived from or estimated based on the variations in time of the sampled CDP signal (e.g., frequency of at least substantially periodic variation that occurs in the frequency range relevant to heart rates).


Communication between various components, including a processor which includes computer instructions operable thereon which are configured to at least one of control the disclosed devices and systems, and calculate diastolic and systolic values, heart rates, blood pressure, body temperature and respiration rates, as well as calibration of values, can be wired communication, and/or wireless via an analog short range communication mode, or a digital communication mode including, for example, WI-FI or BLUETOOTH®. Additional examples of such communication can include communication across a network. Such a network can include a local area network (“LAN”), a wide area network (“WAN”), or a global network, for example. The network can be part of, and/or can include any suitable networking system, such as the Internet, for example, and/or an Intranet.


Generally, the term “Internet” may refer to the worldwide collection of networks, gateways, routers, and computers that use Transmission Control Protocol/Internet Protocol (“TCP/IP”) and/or other packet based protocols to communicate therebetween.


In some embodiments, the disclosed systems and devices may comprise one or more transmission elements for communication between components thereof. In some embodiments, the transmission element can include at least one of the following: a wireless transponder, or a radio-frequency identification (“RFID”) device. The transmission element can include at least one of the following, for example: a transmitter, a transponder, an antenna, a transducer, and/or an RLC circuit or any suitable components for detecting, processing, storing and/or transmitting a signal, such as electrical circuitry, an analog-to digital (“A/D”) converter, and/or an electrical circuit for analog or digital short range communication.


In some embodiments, a controller/processor according to some embodiments and/or any other relevant component of disclosed devices and systems can include a memory, a storage device, and an input/output device. Various implementations of some of embodiments disclosed, in particular at least some of the processes discussed (or portions thereof), may be realized in digital electronic circuitry, integrated circuitry, specially configured ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof (e.g., the disclosed processor/controllers). These various implementations, such as associated with the disclosed devices/systems and the components thereof, for example, may include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.


Such computer programs (also known as programs, software, software applications or code) include machine instructions/code for a programmable processor, for example, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the term “machine-readable medium” refers to any computer program product, apparatus and/or device (e.g., nontransitory mediums including, for example, magnetic discs, optical disks, flash memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable controller/processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term “machine-readable signal” refers to any signal used to provide machine instructions and/or data to a programmable processor.


To provide for interaction with a user, the subject matter described herein may be implemented on a computing device which includes a display device (e.g., a LCD (liquid crystal display) monitor and the like) for displaying information to the user and a keyboard and/or a pointing device (e.g., a mouse or a trackball, touchscreen) by which the user may provide input to the computer. For example, this program can be stored, executed and operated by the dispensing unit, remote control, PC, laptop, smartphone, media player or personal data assistant (“PDA”). Other kinds of devices may be used to provide for interaction with a user as well.


For example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user may be received in any form, including acoustic, speech, or tactile input. Certain embodiments of the subject matter described herein may be implemented on a computing system and/or devices that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a client computer having a graphical user interface or a Web browser through which a user may interact with an implementation of the subject matter described herein), or any combination of such back-end, middleware, or front-end components.


While various inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be an example and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure. Still other embodiments of the present disclosure are patentable over prior art references for expressly lacking one or more features disclosed in the prior art (i.e., claims covering such embodiments may include negative limitations).


Any and all references to publications or other documents, including but not limited to, patents, patent applications, articles, webpages, books, etc., presented anywhere in the present application, are herein incorporated by reference in their entirety. One or more features and/or embodiments disclosed in one or more of incorporated by reference documents herein can also be combined with one or more features/embodiments of the present disclosure to yield yet further embodiments (of the present disclosure).


Moreover, all definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.


The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.”


The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.


As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of” or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law.


As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.


In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03.

Claims
  • 1. A vital sign measuring apparatus, comprising: one or more RF sensors configured to be arranged external to a subject and on or adjacent the skin of the subject at a first location proximate to one or more arteries of the subject;an external dielectrometer probe configured to be arranged external to the subject and on or adjacent the skin of the subject proximate to one or more arteries of the subject;circuitry for the probe and the one or more RF sensors configured to: generate one or more first radio-frequency (RF) waves for transmission towards the one or more arteries,transmit the one or more first radio-frequency (RF) waves towards the one or more arteries of the subject,receive one or more reflected RF waves therefrom, andreceive one or more dielectrometer probe signals from the external dielectrometer probe;anda processor communicably coupled to the circuitry and having computer instructions operating thereon configured to cause the processor to: receive one or more requests for one or more vital signs of the subject,determine if the one or more requests comprises a request for heart-rate measurement of the subject, or a request for at least one of blood pressure and respiration rate of the subject,process at least one of the one or more dielectrometer signals and the one or more reflected RF waves,determine the heart-rate measurement based on the processed one or more dielectrometer signals upon the one or more requests comprising the request for heart-rate measurement of the subject, anddetermine the at least one of blood pressure and respiration rate based on the processed one or more reflected RF waves upon the one or more requests comprising the request for at least one of blood pressure and respiration rate of the subject.
  • 2. The apparatus of claim 1, wherein the one or more RF sensors comprise a monostatic radar.
  • 3. The apparatus of claim 1, wherein the one or more RF sensors comprise a bistatic radar.
  • 4. The apparatus of claim 1, wherein the apparatus is configured with flexibility for conforming the apparatus to the skin of the subject.
  • 5. The apparatus of claim 1, wherein the one or more RF sensors are configured to be are placed on or adjacent to the skin of the subject via a wearable device, a wearable garment, or an adhesive.
  • 6. The apparatus of claim 5, wherein the wearable garment comprises one or more of an article of clothing, a collar, a wrist strap, an ear tag, and a skin patch.
  • 7. The apparatus of claim 1, wherein the dielectrometer probe is configured to be placed on or adjacent to the skin of the subject via a wearable device, a garment, or an adhesive.
  • 8. The apparatus of claim 1, wherein the transmitted RF waves range from 200 MHz to 3 GHz.
  • 9. The apparatus of claim 1, wherein the computer instructions are further configured to cause the processor to resolve the received reflected RF waves according to one or more depths into the subject from which one or more of the reflected RF waves occurred.
  • 10. The apparatus of claim 1, wherein the computer instructions are further configured to cause the processor to condition the received, reflected RF waves using band pass filtering.
  • 11. The apparatus of claim 1, wherein a frequency range for the one or more reflected RF waves corresponds between 0.5 Hz to 2.5 Hz.
  • 12. The apparatus of claim 1, wherein the computer instructions are further configured to cause the processor to identify a prominent peak frequency in a frequency range of the received, reflected RF waves corresponding to respirations of the subject from a fast Fourier transform of the one or more received reflected RF waves.
  • 13. The apparatus of claim 12, wherein the frequency range is between 0.1 Hz to 1 Hz.
  • 14. The apparatus of claim 13, wherein the computer instructions are further configured to cause the processor to determine the respiration rate of the subject as a function of the peak frequency.
  • 15. The apparatus of claim 1, wherein the computer instructions are further configured to cause the processor to: calibrate at least one amplitude of a pulse waveform based on the one or more received reflected RF waves with respect to a reference blood pressure measurement; andcalculate a difference between a maximum of the calibrated amplitude representing systolic blood pressure and a minimum of the calibrated amplitude representing diastolic blood pressure.
  • 16. The apparatus of claim 1, wherein the computer instructions are further configured to cause the processor to determine a complex permittivity from the one or more dielectrometer probe signals.
  • 17. The apparatus of claim 16, wherein the computer instructions are further configured to cause the processor to determine one or more changes in radar characteristics of the reflected RF waves.
  • 18. The apparatus of claim 17, wherein the computer instructions are further configured to cause the processor to determine other vital signs based on the one or more changes in the radar characteristics of the reflected RF waves.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a National Phase of PCT Patent Application No. PCT/US2015/048971 having International filing date of Sep. 8, 2015, which claims priority under 35 USC § 119(e) to U.S. Provisional Patent Application Ser. No. 62/047,534 filed Sep. 8, 2014. The disclosures of which are herein incorporated by reference in their entirety.

PCT Information
Filing Document Filing Date Country Kind
PCT/US2015/048971 9/8/2015 WO 00
Publishing Document Publishing Date Country Kind
WO2016/040337 3/17/2016 WO A
US Referenced Citations (236)
Number Name Date Kind
4240445 Iskander et al. Dec 1980 A
4344440 Aaby et al. Aug 1982 A
4557272 Carr Dec 1985 A
4632128 Paglione et al. Dec 1986 A
4640280 Sterzer Feb 1987 A
4641659 Sepponen Feb 1987 A
4774961 Carr Oct 1988 A
4825880 Stauffer et al. May 1989 A
4926868 Larsen May 1990 A
4945914 Allen Aug 1990 A
4958638 Sharpe Sep 1990 A
4986870 Frohlich Jan 1991 A
5003622 Ma et al. Mar 1991 A
5109855 Guner May 1992 A
5394882 Mawhinney Mar 1995 A
5404877 Nolan Apr 1995 A
5474574 Payne et al. Dec 1995 A
5540727 Tockman et al. Jul 1996 A
5549650 Bornzin et al. Aug 1996 A
5668555 Starr Sep 1997 A
5704355 Bridges Jan 1998 A
5766208 McEwan Jun 1998 A
5807257 Bridges Sep 1998 A
5829437 Bridges Nov 1998 A
5841288 Meaney et al. Nov 1998 A
5865177 Segawa Feb 1999 A
5967986 Cimochowski et al. Oct 1999 A
6019724 Gronningsaeter et al. Feb 2000 A
6025803 Bergen et al. Feb 2000 A
6061589 Bridges et al. May 2000 A
6064903 Riechers et al. May 2000 A
6093141 Mosseri et al. Jul 2000 A
6144344 Kim Nov 2000 A
6161036 Matsumara et al. Dec 2000 A
6193669 Degany et al. Feb 2001 B1
6208286 Rostislavovich et al. Mar 2001 B1
6233479 Haddad et al. May 2001 B1
6267723 Matsumura et al. Jul 2001 B1
6330479 Stauffer Dec 2001 B1
6409662 Lloyd et al. Jun 2002 B1
6454711 Haddad et al. Sep 2002 B1
6471655 Baura Oct 2002 B1
6480733 Turcott Nov 2002 B1
6526318 Ansarinia Feb 2003 B1
6592518 Denker et al. Jul 2003 B2
6604404 Paltieli et al. Aug 2003 B2
6729336 Da Silva et al. May 2004 B2
6730033 Yao et al. May 2004 B2
6755856 Fierens et al. Jun 2004 B2
6933811 Enokihara et al. Aug 2005 B2
6940457 Lee et al. Sep 2005 B2
7020508 Stivoric et al. Mar 2006 B2
7122012 Bouton et al. Oct 2006 B2
7130681 Gebhardt et al. Oct 2006 B2
7184824 Hashimshony Feb 2007 B2
7191000 Zhu et al. Mar 2007 B2
7197356 Carr Mar 2007 B2
7266407 Li et al. Sep 2007 B2
7267651 Nelson Sep 2007 B2
7272431 McGrath Sep 2007 B2
7280863 Shachar Oct 2007 B2
7454242 Fear et al. Nov 2008 B2
7474918 Frants et al. Jan 2009 B2
7479790 Choi Jan 2009 B2
7493154 Bonner et al. Feb 2009 B2
7529398 Zwirn et al. May 2009 B2
7570063 Van Veen et al. Aug 2009 B2
7591792 Bouton Sep 2009 B2
7697972 Verard et al. Apr 2010 B2
7719280 Lagae et al. May 2010 B2
7747302 Milledge et al. Jun 2010 B2
7868627 Turkovskyi Jan 2011 B2
8032211 Hashimshony et al. Oct 2011 B2
8211040 Kojima et al. Jul 2012 B2
8295920 Bouton et al. Oct 2012 B2
8352015 Bernstein et al. Jan 2013 B2
8473054 Pillai et al. Jun 2013 B2
8682399 Rabu Mar 2014 B2
8882759 Manley et al. Nov 2014 B2
8938292 Hettrick et al. Jan 2015 B2
8983592 Belalcazar Mar 2015 B2
8989837 Weinstein et al. Mar 2015 B2
9220420 Weinstein et al. Dec 2015 B2
9265438 Weinstein et al. Feb 2016 B2
9572512 Weinstein et al. Feb 2017 B2
9629561 Weinstein et al. Apr 2017 B2
9788752 Weinstein et al. Oct 2017 B2
10136833 Weinstein et al. Nov 2018 B2
10548485 Arditi et al. Feb 2020 B2
10561336 Rappaport et al. Feb 2020 B2
10588599 Weinstein et al. Mar 2020 B2
10660609 Weinstein et al. May 2020 B2
10680324 Weinstein et al. Jun 2020 B2
11013420 Ravid et al. May 2021 B2
11020002 Weinstein et al. Jun 2021 B2
11108153 Weinstein et al. Aug 2021 B2
20020032386 Sackner et al. Mar 2002 A1
20020045836 Alkawwas Apr 2002 A1
20020049394 Roy et al. Apr 2002 A1
20020050954 Jeong-Kun et al. May 2002 A1
20020147405 Denker et al. Oct 2002 A1
20020151816 Rich et al. Oct 2002 A1
20030036674 Bouton Feb 2003 A1
20030036713 Bouton et al. Feb 2003 A1
20030088180 Van Veen et al. May 2003 A1
20030100815 Da Silva et al. May 2003 A1
20030199770 Chen et al. Oct 2003 A1
20030219598 Sakurai Nov 2003 A1
20040015087 Boric-Lubecke et al. Jan 2004 A1
20040073081 Schramm Apr 2004 A1
20040077943 Meaney et al. Apr 2004 A1
20040077952 Rafter et al. Apr 2004 A1
20040249257 Tupin et al. Dec 2004 A1
20040254457 van der Weide Dec 2004 A1
20040261721 Steger Dec 2004 A1
20050038503 Greenhalgh et al. Feb 2005 A1
20050107693 Fear et al. May 2005 A1
20050192488 Bryenton Sep 2005 A1
20050245816 Candidus et al. Nov 2005 A1
20060004269 Caduff et al. Jan 2006 A9
20060009813 Taylor et al. Jan 2006 A1
20060025661 Sweeney et al. Feb 2006 A1
20060101917 Merkel May 2006 A1
20060237223 Chen et al. Oct 2006 A1
20060265034 Aknine et al. Nov 2006 A1
20070016032 Aknine Jan 2007 A1
20070016050 Moehring et al. Jan 2007 A1
20070055123 Takiguchi Mar 2007 A1
20070100385 Rawat May 2007 A1
20070123770 Bouton et al. May 2007 A1
20070123778 Kantorovich May 2007 A1
20070135721 Zdeblick Jun 2007 A1
20070152812 Wong et al. Jul 2007 A1
20070156057 Cho et al. Jul 2007 A1
20070162090 Penner Jul 2007 A1
20070191733 Gianchandani et al. Aug 2007 A1
20070263907 McMakin et al. Nov 2007 A1
20080027313 Shachar Jan 2008 A1
20080030284 Tanaka et al. Feb 2008 A1
20080036668 White et al. Feb 2008 A1
20080097199 Mullen Apr 2008 A1
20080129511 Yuen et al. Jun 2008 A1
20080139934 McMorrow et al. Jun 2008 A1
20080167566 Kamil et al. Jul 2008 A1
20080169961 Steinway et al. Jul 2008 A1
20080183247 Harding Jul 2008 A1
20080200802 Bahavaraju et al. Aug 2008 A1
20080224688 Rubinsky et al. Sep 2008 A1
20080269589 Thijs et al. Oct 2008 A1
20080283282 Kawasaki et al. Nov 2008 A1
20080294036 Hoi et al. Nov 2008 A1
20080316124 Hook Dec 2008 A1
20080319301 Busse Dec 2008 A1
20090021720 Hecker Jan 2009 A1
20090048500 Corn Feb 2009 A1
20090076350 Bly et al. Mar 2009 A1
20090153412 Chiang et al. Jun 2009 A1
20090153433 Nagai et al. Jun 2009 A1
20090187109 Hashimshony Jul 2009 A1
20090203972 Heneghan et al. Aug 2009 A1
20090227882 Foo Sep 2009 A1
20090240132 Friedman Sep 2009 A1
20090240133 Friedman Sep 2009 A1
20090248450 Fernandez Oct 2009 A1
20090262028 Mumbru et al. Oct 2009 A1
20090281412 Boyden et al. Nov 2009 A1
20090299175 Bernstein et al. Dec 2009 A1
20090312615 Caduff et al. Dec 2009 A1
20090322636 Brigham et al. Dec 2009 A1
20100004517 Bryenton Jan 2010 A1
20100013318 Iguchi et al. Jan 2010 A1
20100052992 Okamura et al. Mar 2010 A1
20100056907 Rappaport et al. Mar 2010 A1
20100076315 Erkamp et al. Mar 2010 A1
20100081895 Zand Apr 2010 A1
20100106223 Grevious Apr 2010 A1
20100152600 Droitcour et al. Jun 2010 A1
20100256462 Rappaport et al. Oct 2010 A1
20100265159 Ando et al. Oct 2010 A1
20100305460 Pinter et al. Dec 2010 A1
20100312301 Stahmann Dec 2010 A1
20100321253 Ayala Vazquez et al. Dec 2010 A1
20100332173 Watson et al. Dec 2010 A1
20110004076 Janna et al. Jan 2011 A1
20110009754 Wenzel et al. Jan 2011 A1
20110022325 Craddock et al. Jan 2011 A1
20110040176 Razansky et al. Feb 2011 A1
20110060215 Tupin et al. Mar 2011 A1
20110068995 Baliarda et al. Mar 2011 A1
20110125207 Nabutovsky et al. May 2011 A1
20110130800 Weinstein et al. Jun 2011 A1
20110257555 Banet et al. Oct 2011 A1
20120029323 Zhao Feb 2012 A1
20120065514 Naghavi et al. Mar 2012 A1
20120068906 Asher et al. Mar 2012 A1
20120098706 Lin et al. Apr 2012 A1
20120104103 Manzi May 2012 A1
20120330151 Weinstein et al. Dec 2012 A1
20130041268 Rimoldi et al. Feb 2013 A1
20130053671 Farra Feb 2013 A1
20130069780 Tran et al. Mar 2013 A1
20130090566 Muhlsteff et al. Apr 2013 A1
20130123614 Bernstein et al. May 2013 A1
20130184573 Pahlevan et al. Jul 2013 A1
20130190646 Weinstein et al. Jul 2013 A1
20130225989 Saroka et al. Aug 2013 A1
20130231550 Weinstein et al. Sep 2013 A1
20130281800 Saroka et al. Oct 2013 A1
20130297344 Cosentino et al. Nov 2013 A1
20130310700 Wiard et al. Nov 2013 A1
20140046690 Gunderson et al. Feb 2014 A1
20140081159 Tao et al. Mar 2014 A1
20140128032 Muthukumar May 2014 A1
20140163425 Tran Jun 2014 A1
20140288436 Venkatraman et al. Sep 2014 A1
20150025333 Weinstein Jan 2015 A1
20150150477 Weinstein et al. Jun 2015 A1
20150164349 Gopalakrishnan et al. Jun 2015 A1
20150335310 Bernstein et al. Nov 2015 A1
20160073924 Weinstein et al. Mar 2016 A1
20160095534 Thakur Apr 2016 A1
20160198957 Arditi et al. Jul 2016 A1
20160198976 Weinstein et al. Jul 2016 A1
20160213321 Weinstein et al. Jul 2016 A1
20160317054 Weinstein et al. Nov 2016 A1
20160345845 Ravid et al. Dec 2016 A1
20170035327 Yuen et al. Feb 2017 A1
20170135598 Weinstein et al. May 2017 A1
20170238966 Weinstein et al. Aug 2017 A1
20190046038 Weinstein et al. Feb 2019 A1
20190298208 Weinstein et al. Oct 2019 A1
20200113447 Arditi et al. Apr 2020 A1
20200297309 Weinstein et al. Sep 2020 A1
20200381819 Weinstein et al. Dec 2020 A1
20210244282 Weinstein et al. Aug 2021 A1
20210251507 Ravid et al. Aug 2021 A1
Foreign Referenced Citations (55)
Number Date Country
101032400 Sep 2007 CN
101516437 Aug 2009 CN
10008886 Sep 2001 DE
1834588 Sep 2007 EP
2506917 Oct 2012 EP
2 602 870 Jun 2013 EP
05-038957 May 1993 JP
10-137193 May 1998 JP
2000-235006 Aug 2000 JP
2001-525925 Dec 2001 JP
2002-094321 Mar 2002 JP
2003-141466 May 2003 JP
2004-526488 Sep 2004 JP
2006-208070 Aug 2006 JP
2006-319767 Nov 2006 JP
2007-061359 Mar 2007 JP
2007-149959 Jun 2007 JP
2008-515548 May 2008 JP
2008-148141 Jun 2008 JP
2008-518706 Jun 2008 JP
2008-530546 Jul 2008 JP
2008-542759 Nov 2008 JP
2008-545471 Dec 2008 JP
2009-514619 Apr 2009 JP
2009-522034 Jun 2009 JP
2010-507929 Mar 2010 JP
2010-072957 Apr 2010 JP
2010-512190 Apr 2010 JP
2010-530769 Sep 2010 JP
2010-537766 Dec 2010 JP
2011-507583 Mar 2011 JP
2011-524213 Sep 2011 JP
2012-090257 May 2012 JP
WO 0203499 Jan 2002 WO
WO 2003009752 Feb 2003 WO
WO 2006127719 Nov 2006 WO
WO 2006130798 Dec 2006 WO
WO 2007017861 Feb 2007 WO
WO 2007023426 Mar 2007 WO
WO 2008070856 Jun 2008 WO
WO 2008148040 Dec 2008 WO
WO 2009031149 Mar 2009 WO
WO 2009031150 Mar 2009 WO
WO 2009060182 May 2009 WO
WO 2009081331 Jul 2009 WO
WO 2009152625 Dec 2009 WO
WO 2011067623 Jun 2011 WO
WO 2011067685 Jun 2011 WO
WO 2011141915 Nov 2011 WO
WO 2012011065 Jan 2012 WO
WO 2012011066 Jan 2012 WO
WO 2013118121 Aug 2013 WO
WO 2013121290 Aug 2013 WO
WO 2015118544 Aug 2015 WO
WO 2016040337 Mar 2016 WO
Non-Patent Literature Citations (28)
Entry
International Search Report and Written Opinion dated Dec. 10, 2015 for PCT/US2015/048971, filed Sep. 8, 2015.
Alekseev, S. I., et al. “Human Skin permittivity determined by millimeter wave reflection measurements”, Bioelectromagnetics, vol. 28, No. 5, Jul. 1, 2007, pp. 331-339.
Ascension Technology Corporation, “TrakSTAR Adds Versatility to Ascension's New Product Line: Desktop Model Joins driveBAY Tracker for Fast Guidance of Miniaturized Sensor”, USA, Apr. 7, 2008.
Bell et al., “A Low-Profile Achimedean Spiral Antenna Using an EBG Ground Plane”, IEEE Antennas and Wireless Propagation Letters 3, pp. 223-226 (2004).
Beyer-Enke et al., Intra-arterial Doppler flowmetry in the superficial femoral artery following angioplasty., 2000, European Radiology, vol. 10, No. 4, p. 642-649.
Claron Technology Inc., “MicronTracker 3:A New Generation of Optical Trackers”, Canada, 2009.
Czum et al., “The Vascular Diagnostic Laboratory”, The Heart & Vascular Institute Newsletter, vol. 1, USA, Winter, 2001.
Ghosh, et al., Immediate Evaluation of Angioplasty and Stenting Results in Supra-Aortic Arteries by Use of a Doppler-Tipped Guidewire, Aug. 2004, American Journal of Neuroradiology, vol. 25, p. 1172-1176.
Gentili et al., “A Versatile Microwave Plethysmograph for the Monitoring of Physiological Parameters”, IEEE Transactions on Biomedical Engineering, IEEE Service Center, Pitscataway, NJ, US, vol. 49, No. 10, Oct. 1, 2002.
Haude et al., Intracoronary Doppler-and Quantitative Coronary Angiography-Derived Predictors of Major Adverse Cardiac Events After Stent Implantation, Mar. 6, 2001, Circulation, vol. 103(9), p. 1212-1217.
Immersion Corporation, “Immersion Introduces New 3D Digitizing Product-MicroScribe G2; Faster Data Transfer, USB Compatibility, New Industrial Design”, Press Release, San Jose, USA, Jul. 1, 2002.
Kantarci et al., Follow-Up of Extracranial Vertebral Artery Stents with Doppler Sonography., Sep. 2006, American Journal of Roentgenology, vol. 187, p. 779-787.
Lal et al., “Duplex ultrasound velocity criteria for the stented carotid artery”, Journal of Vascular Surgery, vol. 47, No. 1, pp. 63-73, Jan. 2008.
Larsson et al., “State Diagrams of the Heart—a New Approach to Describing Cardiac Mechanics”, Cardiovascular Ultrasound 7:22 (2009).
Liang, Jing et al., Microstrip Patch Antennas on Tunable Electromagnetic Band-Gap Substrates, IEEE Transactions on Antennas and Propagation, vol. 57, No. 6, Jun. 2009.
Lin, J.C. et al., “Microwave Imaging of Cerebral Edema”, Proceedings of the IEEE, IEEE, NY, US, vol. 70, No. 5; May 1, 1982, pp. 523-524.
Lin et al.: “Using dual-antenna nanosecond pulse near field sensing technology for non-contact and continuous blood pressure measurement”, Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE, IEEE, Aug. 28, 2012 (Aug. 28, 2012), pp. 219-222.
Miura et al. “Time Domain Reflectometry: Measurement of Free Water in Normal Lung and Pulmonary Edema,” American Journal of Physiology—Lung Physiology 276:1 (1999), pp. L207-L212.
Paulson, Christine N., et al. “Ultra-wideband radar methods and techniques of medical sensing and imaging” Proceedings of Spie, vol. 6007, Nov. 9, 2005, p. 60070L.
Pedersen, P. C., et al., “Microwave Reflection and Transmission Measurements for Pulmonary Diagnosis and Monitoring”, IEEE Transactions on Biomedical Engineering, IEEE Service Center, Piscataway, NJ, US, vol. BME-19, No. 1, Jan. 1, 1978; pp. 40-48.
Polhemus, “Fastrak: The Fast and Easy Digital Tracker”, USA, 2008.
Ringer et al., Follow-up of Stented Carotid Arteries by Doppler Ultrasound, Sep. 2002, Neurosurgery, vol. 51, No. 3, p. 639-643.
Solberg et al: “A feasibility study on aortic pressure estimation using UWB radar”, Ultra-Wideband, 2009. ICUWB 2009. IEEE International Conference on, IEEE, Piscataway, NJ, USA, Sep. 9, 2009 (Sep. 9, 2009), pp. 464-468.
Yang, F. et al. “Enhancement of Printed Dipole Antennas Characteristics Using Semi-EBG Ground Plane”, Journal of Electromagnetic Waves and Application, U.S., Taylor & Francis, Apr. 3, 2006, vol. 8, pp. 993-1006.
Lin et al., “Enhanced performances of a compact conical pattern annular-ring patch antenna using a slotted ground plane,” Microwave Conference, 2001. APMC 2001. 2001 Asia-Pacific Dec. 3-6, 201, IEEE, vol. 3, Dec. 3, 2001, pp. 1036-1039.
Matsugatani et al., “Surface Wave Distribution Over Electromagnetic Bandgap (EBG) And EBG Reflective Shield For Patch Antenna,” IEICE Transactions On Electronics, vol. E88-C, No. 12, Dec. 1, 2005, pp. 2341-2349.
Yang et al., “Reflection phase characterizations of the EBG ground plane for low profile wire antenna applications,” IEEE Transactions on Antennas and Propagation, vol. 51, No. 10, Oct. 1, 2003, pp. 2691-2703.
Zhang et al., “Planar artificial magnetic conductors and patch antennas,” IEEE Transactions on Antennasand Propagation, vol. 51, No. 10, Oct. 1, 2003, pp. 2704-2712.
Related Publications (1)
Number Date Country
20170296093 A1 Oct 2017 US
Provisional Applications (1)
Number Date Country
62047534 Sep 2014 US