This application relates to a system and methods of non-invasive, autonomous health monitoring, and in particular a health monitoring sensor that non-invasively monitors Nitric Oxide (NO) levels in blood vessels.
Various invasive methods have been developed for measurement of Nitric Oxide (NO) levels using one or more types of techniques to remove cells from various types of bodily fluids. The methods usually require drawing blood from a blood vessel using a needle and syringe. The blood sample is then transported to a lab for analysis to determine NO levels using physical or chemical measurements. For example, in one current method, a blood sample is inserted into a semi-permeable vessel including an NO reacting substance that traps NO diffusing thereinto. A simple physical or chemical detection method is then used to measure the levels of the NO.
These known in vitro measurements of NO levels have disadvantages. The process of obtaining blood samples is time consuming, inconvenient and painful to a patient. It may also disrupt sleep of the patient. The measurements of the NO levels are not continuous and may only be updated by taking another blood sample. The measurements must often then be manually recorded into the patient's electronic medical record.
One current non-invasive method is known for measuring oxygen saturation in blood vessels using pulse oximeters. Pulse oximeters detect oxygen saturation of hemoglobin by using, e.g., spectrophotometry to determine spectral absorbencies and determining concentration levels of oxygen based on Beer-Lambert law principles. In addition, pulse oximetry may use photoplethysmography (PPG) methods for the assessment of oxygen saturation in pulsatile arterial blood flow. The subject's skin at a ‘measurement location’ is illuminated with two distinct wavelengths of light and the relative absorbance at each of the wavelengths is determined. For example, a wavelength in the visible red spectrum (for example, at 660 nm) has an extinction coefficient of hemoglobin that exceeds the extinction coefficient of oxihemoglobin. At a wavelength in the near infrared spectrum (for example, at 940 nm), the extinction coefficient of oxihemoglobin exceeds the extinction coefficient of hemoglobin. The pulse oximeter filters the absorbance of the pulsatile fraction of the blood, i.e. that due to arterial blood (AC components), from the constant absorbance by nonpulsatile venous or capillary blood and other tissue pigments (DC components), to eliminate the effect of tissue absorbance to measure the oxygen saturation of arterial blood. Such PPG techniques are heretofore been limited to determining oxygen saturation.
As such, there is a need for a patient monitoring system and method that includes a continuous and non-invasive biosensor configured to monitor concentration levels of NO in blood flow in vivo.
According to a first aspect, a device includes an optical circuit configured to obtain a first photoplethysmography (PPG) signal at a first wavelength using light reflected from skin tissue of a patient, wherein the first wavelength has a high absorption coefficient for nitric oxide (NO) in blood flow; and obtain a second PPG signal at a second wavelength using light reflected from skin tissue of the patient, wherein the second wavelength has a low absorption coefficient for NO in blood flow. The device also includes at least one processing circuit configured to determine a measurement using the first PPG signal and the second PPG signal and determine a risk of a health condition using the measurement, wherein the health condition includes hyperglycemia or hypoglycemia.
According to a second aspect, a device includes an optical circuit configured to obtain a first PPG signal at a first wavelength using light reflected from skin tissue of a patient, wherein the first wavelength has a high absorption coefficient for nitric oxide (NO) in blood flow and obtain a second PPG signal at a second wavelength using light reflected from skin tissue of the patient, wherein the second wavelength has a low absorption coefficient for NO in blood flow. The device also includes at least one processing circuit configured to determine a measurement of a level of NO in blood flow using the first PPG signal and the second PPG signal and determine a risk of a health condition using the measurement of the level of NO.
According to a third aspect, a device includes at least one processing circuit configured to process a first PPG signal at a first wavelength of light that is reflected from skin tissue of a patient, wherein the first wavelength has a high absorption coefficient for nitric oxide (NO) in blood flow and process a second PPG signal at a second wavelength of light reflected from skin tissue of the patient, wherein the second wavelength has a low absorption coefficient for NO in blood flow. The at least one processing circuit is further configured to determine a measurement of a level of NO in blood flow using the first spectral response and the second spectral response and determine a risk of a health condition using the measurement of the level of NO.
In one or more of the above aspects, the measurement determined using the first PPG signal and the second PPG signal includes an AC component of the first PPG signal.
In one or more of the above aspects, the measurement determined using the first PPG signal and the second PPG signal includes a ratio of an AC component of the first PPG signal and an AC component of the second PPG signal.
In one or more of the above aspects, the measurement determined using the first PPG signal and the second PPG signal includes a level of NO in the blood flow of the patient.
In one or more of the above aspects, the measurement determined using the first PPG signal and the second PPG signal includes a level of glucose in the blood flow of the patient.
In one or more of the above aspects, the optical circuit is configured on a patch, wrist band, finger attachment or ear piece.
In one or more of the above aspects, the optical circuit and the at least one processing circuit is configured on a patch, wrist band, finger attachment or ear piece.
In one or more of the above aspects, the at least one processing circuit is further configured to generate an alert in response to determination of the risk of the health condition.
In one or more of the above aspects, the processing circuit is configured to determine the risk of the health condition using the measurement of the level of NO by comparing the measurement of the level of NO to a predetermined normal range and determining the measurement of the level of NO is higher or lower than the predetermined normal range.
In one or more of the above aspects, the processing circuit is configured to generate an alert when the measurement of the level of NO is higher or lower than the predetermined normal range or generate a display of the measurement of the level of NO.
In one or more of the above aspects, the health condition includes one or more of: hyperglycemia, hypoglycemia, diabetic condition, insulin response, hypovolemia, vascular health, dementia, Alzheimer' s disease, post-traumatic stress syndrome (PTSD), infection or sepsis. The health condition may include a presence of one or more compounds that lead to unsafe levels of NO in blood vessels, wherein the one or more compounds include one or more of: lidocaine, nitrates such as nitroglycerin, nitric oxide, nitrogen based fertilizers, dapsone, benzocaine, cyanide, or anesthesia.
In one or more of the above aspects, the first wavelength having a high absorption coefficient for NO in blood flow is in a range of approximately 380 nm to 400 nm.
In one or more of the above aspects, the device further comprises a transceiver configured to transmit data to a remote user device, wherein the data includes an alert in response to determination of the risk of the health condition.
The word “exemplary” or “embodiment” is used herein to mean “serving as an example, instance, or illustration.” Any implementation or aspect described herein as “exemplary” or as an “embodiment” is not necessarily to be construed as preferred or advantageous over other aspects of the disclosure. Likewise, the term “aspects” does not require that all aspects of the disclosure include the discussed feature, advantage, or mode of operation.
Embodiments will now be described in detail with reference to the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the aspects described herein. It will be apparent, however, to one skilled in the art, that these and other aspects may be practiced without some or all of these specific details. In addition, well known steps in a method of a process may be omitted from flow diagrams presented herein in order not to obscure the aspects of the disclosure. Similarly, well known components in a device may be omitted from figures and descriptions thereof presented herein in order not to obscure the aspects of the disclosure.
Overview of Measurement of NO Levels
Embodiments described herein include a biosensor having an optical multi-band wavelength PPG sensor configured to determine NO levels in vitro in arterial blood, arteries, vessels and/or surrounding tissue. The non-invasive methods of embodiments of the biosensor may have a variety of uses, e.g., for monitoring of NO levels and diagnosis of various conditions related to NO levels. The biosensor may detect overproduction or underproduction of NO levels that have been associated with many different conditions. For example, NO production is related to endothelium-derived relaxing factor (EDRF). In addition, NO is a highly potent endogenous vasodilator. NO levels may also be used as indicator of inflammation, blood clotting, diabetes, dementia, Alzheimer's, post-traumatic stress syndrome (PTSD), and infections like sepsis.
Nitric oxide (NO) is produced by a group of enzymes called nitric oxide synthases. These enzymes convert arginine into citrulline, producing NO in the process. Oxygen and NADPH are necessary co-factors. There are three isoforms of nitric oxide synthase (NOS) named according to their activity or the tissue type in which they were first described. The isoforms of NOS are neural NOS (or nNOS, type 1), inducible NOS (or iNOS, type 2), and endothelial NOS (or eNOS, type 3). These enzymes are also sometimes referred to by number, so that nNOS is known as NOS1, iNOS is known as NOS2, and eNOS is NOS3. Despite the names of the enzymes, all three isoforms can be found in variety of tissues and cell types. Two of the enzymes (nNOS and eNOS) are constitutively expressed in mammalian cells and synthesize NO in response to increases in intracellular calcium levels. In some cases, however, they are able to increase NO production independently of calcium levels in response to stimuli such as shear stress.
In most cases NO production increases in proportion to the amount of calories or food consumed. Normally this is derived from the eNOS type NO production, and the body uses the NO first as a vasodilator and also as a protective oxidation layer to prevent undesired oxides from passing thru the cells in the blood vessels walls. The amount of NO released in this case is measured in small pulses and builds up as part of the normal digestion process. In the case of type 1 or type 2 diabetics, the normal levels of eNOS are abnormally low as found in recent clinical studies.
However iNOS activity is independent of the level of calcium in the cell, and all forms of the NOS isoforms are dependent on the binding of calmodulin. Increases in cellular calcium lead to increase in levels of calmodulin and the increased binding of calmodulin to eNOS and nNOS leads to a transient increase in NO production by these enzymes. By contrast iNOS is able to bind tightly to calmodulin even at extremely low concentrations of calcium. Therefore iNOS activity does not respond to changes in calcium levels in the cell. As a result of the production of NO by iNOS, it lasts much longer than other forms of isoforms of NOS and tends to produce much higher concentrations of NO in the body. This is likely the reason that iNOS levels are known to be elevated in dementia & Alzheimer's patents and have increased calcium deposits in their brain tissue.
Inducible iNOS levels are highly connected with sepsis infections which typically lead to large levels of NO in the blood stream, which in turns leads to organ failure. Lastly abnormal amounts of nNOS levels are typically associated with issues with blood pressure regulation, neurotransmission issues, and penal erection. Table 1 below summarizes the NOS isoforms.
Thus, the overproduction or underproduction of NO levels may be associated with many different health conditions. Embodiments of the biosensor described herein may continuously monitor NO levels non-invasively in vivo without need for blood samples. The NO levels of a patient may be continuously displayed and monitored. The NO levels may be used for diagnosis of one or more of these or other health conditions. Measuring NO or related compounds may provide early warning information about a patient's condition and allow for more immediate medical intervention. Since current measurement methods of NO do not allow health care professionals or even home care patients to measure NO continuously in blood vessels, the biosensor described herein may be potentially lifesaving for critical conditions. Very often trauma patients require frequent monitoring and invasive blood tests are the only method to sense worsening conditions prior to emergency conditions. The described non-invasive biosensor measures NO levels in blood vessels and provides efficiency to a host of current methods and treatment procedures in medical facilities around the globe. For example, the measurement of nitric oxide (NO) levels in blood vessels described herein provides a much earlier warning to care providers that intervention is needed for patient care.
Overview of Biosensor
In an embodiment, a biosensor includes a PPG circuit, a processing circuit, optional on-board display and a wireless or wired transceiver. The PPG circuit is configured to transmit light at a plurality of wavelengths directed at skin tissue of a patient. The PPG circuit is configured to detect light reflected from the skin tissue of the patient and generate spectral responses at a plurality of wavelengths. The processing circuit is configured to obtain a measurement of NO levels using the spectral responses at the plurality of wavelengths using one or more measurement techniques described herein. An indication of the NO level may then be displayed on a display of the biosensor. The biosensor may transmit the measurements of NO levels via a wireless or wired transceiver to a remote display.
Embodiments—Biosensor Form Factors
In use, a patient places a finger inside the finger attachment 102. The biosensor 100 is configured to monitor nitric oxide (NO) levels in the blood vessels of the patient. A PPG circuit 110 in the biosensor 100 is configured to transmit light at a plurality of wavelengths directed at skin tissue of the finger of the patient. The PPG circuit 110 is configured to detect light reflected from the skin tissue of the finger and generate spectral responses at a plurality of wavelengths. A processing circuit in the biosensor 100 is configured to obtain a measurement of NO levels from the spectral responses at the plurality of wavelengths using one or more measurement techniques described herein. The NO levels may be continuously monitored, e.g. the NO measurements may be obtained a plurality of times per minute and averaged over a predetermined time period. An indication of the NO levels may then be displayed on a display of the biosensor 100.
The biosensor 100 includes one or more types of displays of the measured nitric oxide (NO) levels. The displays may include, e.g., arterial nitric oxide saturation level 104 (such as SpNO). The display may include a bar meter 106 illustrating a relative measured nitric oxide level. The display may include a dial type display 108 that indicates a relative measured nitric oxide level. The biosensor 100 may display the measured nitric oxide level in mmol/liter units 112. These types of displays are examples only and other types of display may be employed to indicate the level of NO measured in a patient.
The biosensor 100 may also display other patient vitals such as heart rate, e.g. beats per minute (bpm) 114. The biosensor 100 may also include a power control.
The biosensor 100 may be implemented in other compact form factors, such as on a patch, wrist band or ear piece. Due to its compact form factor, the biosensor 100 may be configured for measurements on various skin surfaces of a patient, including on a forehead, arm, wrist, abdominal area, chest, leg, ear, ear lobe, finger, toe, ear canal, etc.
In another embodiment, the biosensor 100 is may be configured in an earpiece (not shown). The biosensor 100 is configured to transmit light into the ear canal from one or more optical fibers in an ear bud and detect light from the ear canal using one or more optical fibers.
In one study, a mechanical contact of glass with the subject's skin substantially increased the amplitude of the observed PPG signal. Moreover, by increasing the force of the contact, the amplitude of the PPG signal in the area is increased. As such, increased compression of the biosensor 100 against skin tissue may enhance intensity of the PPG signal. So compression of the biosensor 100 against the skin of a patient may be considered during use of biosensor 100 in its one or more form factors. The article by Kamshilin AA, Nippolainen E, Sidorov IS, et al. entitled “A new look at the essence of the imaging photoplethysmography” in Scientific Reports, May 21, 2015, 5:10494 and doi:10.1038/srep10494 includes further details on spatial distribution of PPG intensity amplitude for different forces of contact, and is hereby incorporated by reference herein.
Embodiment—Biosensor Components
The biosensor 100 also includes one or more processing circuits 402 communicatively coupled to a memory device 404. In one aspect, the memory device 404 may include one or more non-transitory processor readable memories that store instructions which when executed by the one or more processing circuits 402, causes the one or more processing circuits 402 to perform one or more functions described herein. The memory device 404 may also include an EEPROM or other type of memory to store a patient identification (ID) 406 that is associated with a patient being monitored by the biosensor 100. The patient identification 406 may include a number, name, date of birth, password, etc. The memory device 404 may also store an electronic medical record (EMR) 408 or portion of the EMR 408 associated with the patient being monitored by the biosensor 100. The biosensor data obtained by the biosensor 100 may be stored in the EMR 408. The processing circuit 42 may be co-located with one or more of the other circuits in the biosensor 100 in a same physical encasement or located separately in a different physical encasement or located remotely. In an embodiment, the biosensor 100 is battery operated and includes a battery 420, such as a lithium ion battery.
The biosensor 100 further includes a transceiver 412. The transceiver 412 may include a wireless or wired transceiver configured to communicate with one or more devices over a LAN, MAN and/or WAN. In one aspect, the transceiver 412 may include a Bluetooth enabled (BLE) transceiver or IEEE 802.11ah, Zigbee, IEEE 802.15-11 or WLAN (such as an IEEE 802.11 standard protocol) compliant wireless transceiver. In another aspect, the transceiver 412 may operate using RFID, short range radio frequency, infrared link, or other short range wireless communication protocol. In another aspect, the transceiver 412 may also include or alternatively include an interface for communicating over a cellular radio access network, such as an Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access Network (UTRAN), Long Term Evolution (LTE) Evolved UTRAN (E-UTRAN), and/or LTE-Advanced (LTE-A) or other types of cellular networks. In an embodiment, the transceiver 412 may include a thin foil for an antenna that is specially cut and includes a carbon pad contact to a main printed circuit board (PCB) of the biosensor 100. This type of antenna is inexpensive to manufacture and may be printed on the inside of an enclosure for the biosensor 100 situated away from the skin of the patient to minimize absorption. The transceiver 412 may also include a wired transceiver including a port or interface, e.g., a USB port or other type of wired connection port, for communication with one or more other devices using Ethernet, IP, or other protocols over a LAN, MAN and/or WAN.
The biosensor 100 may also include a temperature sensor 414 configured to detect a temperature of a patient. For example, the temperature sensor 414 may include an array of sensors (e.g., 16×16 pixels) positioned on a side of the biosensor 100 with the PPG circuit 110 such that the array of sensors are adjacent to the skin of the patient. The array of sensors is configured to detect a temperature of the patient from the skin. The temperature sensor 414 may also be used to calibrate the PPG circuit 110.
The biosensor 100 may also include a display 416 for displaying biosensor data. Alternatively or in addition thereto, the transceiver 412 may communicate biosensor data, such as NO levels, to a remote device for display.
Embodiment-PPG Circuit
In an embodiment, the driver circuit 118 is configured to control the one or more LEDs 122a-n to generate light at one or more frequencies for predetermined periods of time. The driver circuit 118 may control the LEDs 122a-n to operate concurrently or consecutively. The driver circuit 118 is configured to control a power level, emission period and frequency of emission of the LEDs 122a-n. The biosensor 100 is thus configured to emit one or more wavelengths of light in one or more spectrums that is directed at the surface or epidermal layer of the skin tissue of a patient.
The PPG circuit 110 further includes one or more photodetector circuits 130a-n. For example, a first photodetector circuit 130 may be configured to detect visible light and the second photodetector circuit 130 may be configured to detect IR light. The first photodetector circuit 130 and the second photodetector circuit 130 may also include a first filter 160 and a second filter 162 configured to filter ambient light and/or scattered light. For example, in some embodiments, only light reflected at an approximately perpendicular angle to the skin surface of the patient is desired to pass through the filters. The first photodetector circuit 130 and the second photodetector circuit 132 are coupled to a first A/D circuit 138 and a second A/D circuit 140. Alternatively, a single A/D circuit may be coupled to each of the photodetector circuits 130a-n.
In another embodiment, a single photodetector circuit 130 may be implemented operable to detect light over multiple spectrums or frequency ranges. For example, the photodetector circuit 130 may include a Digital UV Index/IR/Visible Light Sensor such as Part No. Si1145 from Silicon Labs™.
The one or more photodetector circuits 130 include a spectrometer or other type of circuit configured to detect an intensity of light as a function of wavelength or frequency to obtain a spectral response. The one or more photodetector circuits 130 detect the intensity of light either transmitted through or reflected from tissue of a patient that enters one or more apertures 128b-n of the biosensor 100. For example, the light may be detected from transmissive absorption (e.g., through a fingertip or ear lobe) or from reflection (e.g., reflected from a forehead or stomach tissue). The one or more photodetector circuits 130a-n then obtain a spectral response of the reflected light by measuring the intensity of light at one or more wavelengths.
In another embodiment, the light source 120 may include a broad spectrum light source, such as a white light to infrared (IR) or near IR LED 122, that emits light with wavelengths from e.g. 350 nm to 2500 nm. Broad spectrum light sources with different ranges may be implemented. In an aspect, a broad spectrum light source is implemented with a range across 100 nm wavelengths to 2000 nm range of wavelengths in the visible, IR and/or UV frequencies. For example, a broadband tungsten light source for spectroscopy may be used. The spectral response of the reflected light is then measured across the wavelengths in the broad spectrum, e.g. from 350 nm to 2500 nm, concurrently. In an aspect, a charge coupled device (CCD) spectrometer may be configured in the photodetector circuit 130 to measure the spectral response of the detected light over the broad spectrum.
A care provider may then determine health conditions or risks using the NO measurement and determine to perform additional tests or provide medical care. For example, the biosensor 100 non-invasively monitors an NO measurement, such as the NO concentration level or indicator of amount of nitric oxide, in blood vessels. The NO measurement may be represented by a saturation of nitric oxide SpNO in the blood or other values representing NO levels in the blood vessels, such as mmol/liter.
The NO measurement of a patient may be compared to predetermined levels at 606. For example, the predetermined thresholds may be a range of average or mean NO measurements of a sample healthy population. The NO measurement of an individual patient may then be compared to the normal range derived from the sample population. Depending on the comparison, the NO measurement may be determined within normal ranges. Alternatively, the NO measurement may be determined to be lower or higher than predetermined normal ranges indicating one or more health risks. For example, diabetic conditions may result in lower than normal NO levels while carbon monoxide poisoning or septic risk may result in higher than normal NO levels. Other compounds may also cause unsafe levels of NO in blood vessels, such as lidocaine and nitrates such as nitroglycerine, nitric oxide, or water sources contaminated by runoff containing nitrogen based fertilizers, anti-malaria drug dapsone, benzocaine, cyanide, anesthesia, nitroglycerin, nitrate drugs, water contaminated with nitro based fertilizers, landocaine, etc. An indication may be displayed that the NO measurement is within the predetermined normal range. In addition, a warning may be displayed when the NO measurement of the patient is not within a predetermined normal range at 608.
Embodiment—PPG Measurement of NO Levels
One or more of the embodiments of the biosensor 100 described herein is configured to detect a concentration level or indicator of one or more substances within arterial blood flow using photoplethysmography (PPG) techniques. The biosensor 100 may detect NO concentration level, insulin response, vascular health, cardiovascular sensor, cytochrome P450 proteins (e.g. one or more liver enzymes or reactions), digestion phase 1 and 2 or caloric intake. The biosensor 100 may even be configured to detect proteins or other elements or compounds associated with cancer. The biosensor 100 may also detect various electrolytes and many common blood analytic levels, such as bilirubin amount and sodium and potassium. For example, the biosensor 100 may detect sodium NACL concentration levels in the arterial blood flow to determine dehydration. The biosensor 100 may also detect blood alcohol levels in vivo in the arterial blood flow. The biosensor 100 may also detect blood pressure, peripheral oxygen (SpO2 or SaO2) saturation, heart rate, respiration rate or other patient vitals. Because blood flow to the skin can be modulated by multiple other physiological systems, the PPG sensor 110 may also be used to monitor breathing, hypovolemia, and other circulatory conditions.
In use, the biosensor 100 performs PPG techniques using the PPG circuit 110 to detect the concentration levels of one or more substances in blood flow. In one aspect, the biosensor 100 receives reflected light from skin tissue to obtain a spectral response. The spectral response includes a spectral curve that illustrates an intensity or power or energy at a frequency or wavelength in a spectral region of the detected light.
The ratio of the resonance absorption peaks from two different frequencies can be calculated and based on the Beer-Lambert law used to obtain various levels of substances in the blood flow. First, the spectral response of a substance or substances in the arterial blood flow is determined in a controlled environment, so that an absorption coefficient αg1 can be obtained at a first light wavelength λ1 and at a second wavelength λ2. According to the Beer-Lambert law, light intensity will decrease logarithmically with path length l (such as through an artery of length l). Assuming then an initial intensity Iin of light is passed through a path length l, a concentration Cg of a substance may be determined using the following equations:
At the first wavelength λ1, I1=Iin1*10−(60
At the second wavelength λ2, I2=Iin2*10−(α
wherein:
Iin1 is the intensity of the initial light at λ1
Iin2 is the intensity of the initial light at λ2
αg1 is the absorption coefficient of the substance in arterial blood at λ1
αg2 is the absorption coefficient of the substance in arterial blood at λ2
αw1 is the absorption coefficient of arterial blood at λ1
αw2 is the absorption coefficient of arterial blood at λ2
Cgw is the concentration of the substance and arterial blood
Cw is the concentration of arterial blood
Then letting R equal:
The concentration of the substance Cg may then be equal to:
The biosensor 100 may thus determine the concentration of various substances in arterial blood using spectroscopy of at least two different wavelengths from the Beer-Lambert principles. For example, the biosensor 100 may function as a pulse oximeter using similar principles under Beer-lambert law to determine pulse and oxygen saturation levels in pulsating arterial blood flow. For example, a first wavelength at approximately 940 nm and a second wavelength at approximately 660 nm may be used to determine oxygen saturation levels (SpO2). In addition, the biosensor 100 may determine concentration levels of one or more additional substances in blood vessels.
In another aspect, the biosensor 100 may transmit light at the first predetermined wavelength in a range of approximately 1 nm to 50 nm around the first predetermined wavelength. Similarly, the biosensor 100 may transmit light at the second predetermined wavelength in a range of approximately 1 nm to 50 nm around the second predetermined wavelength. The range of wavelengths is determined based on the spectral response since a spectral response may extend over a range of frequencies, not a single frequency (i.e., it has a nonzero linewidth). The light that is reflected or transmitted by NO may spread over a range of wavelengths rather than just the single predetermined wavelength. In addition, the center of the spectral response may be shifted from its nominal central wavelength or the predetermined wavelength. The range of 1 nm to 50 nm is based on the bandwidth of the spectral response line and should include wavelengths with increased light intensity detected for the targeted substance around the predetermined wavelength.
The first spectral response of the light over the first range of wavelengths including the first predetermined wavelength and the second spectral response of the light over the second range of wavelengths including the second predetermined wavelengths is then generated at 702 and 704. The biosensor 100 analyzes the first and second spectral responses to detect an indicator or concentration level of NO in the arterial blood flow at 706.
Incident light IO 812 is directed at a tissue site and a certain amount of light is reflected or transmitted 818 and a certain amount of light is absorbed 820. At a peak of arterial blood flow or arterial volume, the reflected/transmitted light IL 814 is at a minimum due to absorption by the venous blood 808, nonpulsating arterial blood 806, pulsating arterial blood 804, other tissue 810, etc. At a minimum of arterial blood flow or arterial volume during the cardiac cycle, the transmitted/reflected light IH 816 is at a maximum due to lack of absorption from the pulsating arterial blood 804.
The biosensor 100 is configured to filter the reflected/transmitted light IL 814 of the pulsating arterial blood 804 from the transmitted/reflected light IH 816. This filtering isolates the light due to reflection/transmission of substances in the pulsating arterial blood 804 from the light due to reflection/transmission from venous (or capillary) blood 808, other tissues 810, etc. The biosensor 100 may then measure the concentration levels of one or more substances from the reflected/transmitted light IL 814 in the pulsating arterial blood 804.
For example, as shown in
In general, the relative magnitudes of the AC and DC contributions to the reflected/transmitted light signal I 818 may be used to substantially determine the differences between the diastolic time and the systolic points. In this case, the difference between the reflected light IL 814 and reflected light IH 816 corresponds to the AC contribution of the reflected light 818 (e.g. due to the pulsating arterial blood flow). A difference function may thus be computed to determine the relative magnitudes of the AC and DC components of the reflected light I 818 to determine the magnitude of the reflected light IL 814 due to the pulsating arterial blood 804. The described techniques herein for determining the relative magnitudes of the AC and DC contributions is not intended as limiting. It will be appreciated that other methods may be employed to isolate or otherwise determine the relative magnitude of the light IL 814 due to pulsating arterial blood flow.
In one aspect, the spectral response of each wavelength may be aligned based on the systolic 602 and diastolic 604 points in their spectral responses. This alignment is useful to associate each spectral response with a particular stage or phase of the pulse-induced local pressure wave within the blood vessel (which may mimic the cardiac cycle 906 and thus include systolic and diastolic stages and sub-stages thereof). This temporal alignment helps to determine the absorption measurements acquired near a systolic point in time of the cardiac cycle and near the diastolic point in time of the cardiac cycle 906 associated with the local pressure wave within the patient's blood vessels. This measured local pulse timing information may be useful for properly interpreting the absorption measurements in order to determine the relative contributions of the AC and DC components measured by the biosensor 100. So for one or more wavelengths, the systolic points 902 and diastolic points 904 in the spectral response are determined. These systolic points 902 and diastolic points 904 for the one or more wavelengths may then be aligned as a method to discern concurrent responses across the one or more wavelengths.
In another embodiment, the the systolic points 902 and diastolic points 904 in the absorbance measurements are temporally correlated to the pulse-driven pressure wave within the arterial blood vessels—which may differ from the cardiac cycle. In another embodiment, the biosensor 100 may concurrently measure the intensity reflected at each the plurality of wavelengths. Since the measurements are concurrent, no alignment of the spectral responses of the plurality of wavelengths may be necessary.
The spectral responses are obtained around the plurality of wavelengths, including at least a first wavelength and a second wavelength at 1002. The spectral responses may be measured over a predetermined period (such as 300 usec.). This measurement process is repeated continuously, e.g., pulsing the light at 10-100 Hz and obtaining spectral responses over a desired measurement period, e.g. from 1-2 seconds to 1-2 minutes or from 2-3 hours to continuously over days or weeks. The absorption levels are measured over one or more cardiac cycles and systolic and diastolic points of the spectral response are determined. Because the human pulse is typically on the order of magnitude of one 1 Hz, typically the time differences between the systolic and diastolic points are on the order of magnitude of milliseconds or tens of milliseconds or hundreds of milliseconds. Thus, spectral response measurements may be obtained at a frequency of around 10-100 Hz over the desired measurement period. The spectral responses are obtained over one or more cardiac cycles and systolic and diastolic points of the spectral responses are determined.
A low pass filter (such as a 5 Hz low pass filter) is applied to the spectral response signal at 1004. The relative contributions of the AC and DC components are obtained IAC+DC and IAC. A peak detection algorithm is applied to determine the systolic and diastolic points at 1006. The systolic and diastolic points of the spectral response for each of the wavelengths may be aligned and may also be aligned with systolic and diastolic points of an arterial pulse waveform or cardiac cycle.
Beer Lambert equations are then applied as described herein at 1008. For example, the Lλ values are then calculated for the wavelengths λ, wherein the Lλ values for a wavelength equals:
wherein IAC+DC is the intensity of the detected light with AC and DC components and IDC is the intensity of the detected light with the AC filtered by the low pass filter. The value Lλ isolates the spectral response due to pulsating arterial blood flow, e.g. the AC component of the spectral response.
A ratio R of the Lλ values at two wavelengths may then be determined. For example,
The spectral responses may be measured and the Lλ values and Ratio R determined continuously, e.g. every 1-2 seconds, and the obtained Lλ values and/or Ratio R averaged over a predetermined time period, such as over 1-2 minutes. The NO concentration levels may then be obtained from the averaged R values and a calibration database. The NO level measurements are then displayed. The biosensor 100 may continuously monitor a patient over 2-3 hours or continuously over days or weeks.
The R390,940 value with Lλ1=390 nm and Lλ2=940 may be non-invasively and quickly and easily obtained using the biosensor 100 in a physician's office or other clinical setting or at home. In particular, in unexpected results, it is believed that nitric oxide NO levels in the arterial blood flow is being measured at least in part by the biosensor 100 at λ1=390 nm. The wavelengths around 390 nm may also be used, e.g. 395 nm or a range from 370 nm to 410 nm. Since NO is partly in a gaseous form in blood vessels (prior to adhesion to hemoglobin), the total NO concentration levels of in vitro blood samples, e.g. from a finger prick, are not detected as the NO gas dissipates. Thus, the biosensor 100 measurements to determine the L390 nm values are the first time NO concentration levels in arterial blood flow have been measured directly in vivo. These and other aspects of the biosensor 100 are described in more detail herein with clinical trial results.
Embodiment—Determination of NO Concentration Levels at a Plurality of Wavelengths
LN(I1−n)=Σi=0nμi*Ci
wherein,
I1−n=intensity of light at wavelengths λ1−n
μn=absorption coefficient of substance 1, 2, . . . n at wavelengths λ1−n
Cn=Concentration level of substance 1, 2, . . . n
When the absorption coefficients μ1−n of NO or NOS isoforms or other NO compounds are known at the wavelengths λ1−n, then the concentration level C of the substances may be determined from the spectral responses at the wavelengths λ1−n (and e.g., including a range of 1 nm to 50 nm around each of the wavelengths). The concentration level of NO may be isolated from the NOS isoforms or other NO compounds by compensating for the concentration of the hemoglobin compounds. Thus, using the spectral responses at multiple frequencies provides a more robust determination of the concentration level of NO.
In use, the biosensor 100 transmits light directed at skin tissue at a plurality of wavelengths or over a broad spectrum at 1102. The spectral response of light from the skin tissue is detected at 1104, and the spectral response is analyzed for a plurality of wavelengths (and in one aspect including a range of +/− 10 to 50 nm around each of the wavelengths) at 1106. Then, the concentration level C of the substance may be determined using the spectral response at the plurality of wavelengths at 1108.
The IAC+DC and IDC components are then used to compute the L values at 1210. For example, a logarithmic function may be applied to the ratio of IAC+DC and IDC to obtain an L value for each of the wavelengths Lλ1−n . Since the respiratory cycle affects the PPG signals, the L values may be averaged over a respiratory cycle and/or over another predetermined time period (such as over a 1-2 minute time period).
In an embodiment, NO isoforms may be attached in the blood stream to one or more hemoglobin compounds. The concentration level of the hemoglobin compounds may then need to be accounted for to isolate the concentration level of NO from the hemoglobin compounds. For example, nitric oxide (NO) is found in the blood stream in a gaseous form and also attached to hemoglobin compounds as described herein. Thus, the spectral responses obtained around 390 nm may include a concentration level of the hemoglobin compounds as well as nitric oxide. The hemoglobin compound concentration levels must thus be compensated for to isolate the nitric oxide concentration levels. Multiple wavelengths and absorption coefficients for hemoglobin are used to determine a concentration of the hemoglobin compounds at 1214. This process is discussed in more detail herein below. Other methods may also be used to obtain a concentration level of hemoglobin in the arterial blood flow as explained herein. The concentration of the hemoglobin compounds is then adjusted from the concentration level of NO at 1216. The R values are then determined at 1218.
To determine a concentration level of NO, a calibration database is used that associates R values to concentration levels of NO at 1220. The calibration database correlates the R value with an NO concentration level. The calibration database may be generated for a specific patient or may be generated from clinical data of a large sample population. It is determined that the R values should correlate to similar NO concentration levels across a large sample population. Thus, the calibration database may be generated from testing of a large sample of a general population.
In addition, the R values may vary depending on various factors, such as underlying skin tissue. For example, the R values may vary for spectral responses obtained from an abdominal area versus measurements from a wrist or finger due to the varying tissue characteristics. The calibration database may thus provide different correlations between the R values and NO concentration levels depending on the underlying skin tissue characteristics.
The NO concentration level is then obtained at 1224. The NO concentration level may be expressed as mmol/liter, as a saturation level percentage, as a relative level on a scale, etc. In order to remove the hemoglobin concentration(s) from the original PPG signals, a mapping function may be created which is constructed through clinical data and tissue modeling. For example, known SpO2 values in the infrared region and the same signals at the UV side of the spectrum are obtained. Then a linear inversion map can be constructed where the R values are input into a function and the desired concentration(s) can be determined. For example, a curve that correlates R values to concentration levels (similar to
For example, a regression curve similar to the curve in
Embodiment—Determination of a Concentration of Hemoglobin Compounds
The Beer-Lambert theory may be generalized for a multi-wavelength system to determine a concentration of known hemoglobin species using the following matrix notation:
wherein
dAλLB is a differential absorption within the Beer-Lambert model
ελn1,HbX1 is an extinction coefficient
HbX are hemoglobin fractions
Δlλ is the optical path-length for wavelength λ
c(Hb) is the hemoglobin concentration
This matrix equation for determining hemoglobin concentration levels may be solved when m is equal or greater than n, e.g., which means that at least four wavelengths are needed to solve for four hemoglobin species.
A direct calibration method for calculating hemoglobin species may be implemented by the biosensor 100. Using four wavelengths and applying a direct model for four hemoglobin species in the blood, the following equation results:
wherein
dAλ is the differential absorption signal
an and bn are calibration coefficients
The calibration coefficients an and bn may be experimentally determined over a large population average. The biosensor 100 may include a calibration database to account for variances in the calibration coefficients a1 and b1 (or extinction coefficients) for the hemoglobin species for various underlying tissue characteristics.
A two-stage statistical calibration and measurement method for performing PPG measurement of blood analyte concentrations may also be implemented by the biosensor 100. Concentrations of MetHb, HbO2, RHb and HbCO are estimated by first estimating a concentration of MetHb (in a first stage) and subsequently, if the concentration of MetHb is within a predetermined range, then the estimated concentration of MetHb is assumed to be accurate and this estimated concentration of MetHb is utilized as a “known value” in determining the concentrations of the remaining analytes HbO2, RHb and HbCO (in a second stage). This method for determining a concentration of hemoglobin species using a two stage calibration and analyte measurement method is described in more detail in U.S. Pat. No. 5,891,024 issued on Apr. 6, 1999, which is hereby incorporated by reference herein.
The concentration of the hemoglobin compounds may thus be determined and then the hemoglobin concentration removed when determining the concentration level of NO by the biosensor 100. Though several methods are described herein for obtaining a concentration of hemoglobin analytes, other methods or processes may be used by the biosensor 100 to determine the concentration of hemoglobin analytes or otherwise adjusting the obtained measurements to account for a hemoglobin concentration when determining the concentration levels of NO in a blood stream.
Embodiment—Determination of NO Concentration Levels using Shifts in Absorbance Peaks
In another embodiment, a concentration level of NO may be obtained from measuring a characteristic shift in an absorbance peak of hemoglobin. For example, the absorbance peak for methemoglobin shifts from around 433 nm to 406 nm in the presence of NO. The advantage of the measurement of NO by monitoring methemoglobin production includes the wide availability of spectrophotometers, avoidance of sample acidification, and the relative stability of methemoglobin. Furthermore, as the reduced hemoglobin is present from the beginning of an experiment, NO synthesis can be measured continuously, removing the uncertainty as to when to sample for NO.
Though the absorbance spectrums shown in the graph 1400 were measured using in vitro assays, the biosensor 100 may detect nitric oxide in vivo using PPG techniques by measuring the shift in the absorbance spectra curve of reduced hemoglobin 1402 in tissue and/or arterial blood flow. The absorbance spectra curve 1402 shifts with a peak from around 430 nm to a peak around 411 nm depending on the production of methemoglobin. The greater the degree of the shift of the peak of the curve 1402, the higher the production of methemoglobin and NO concentration level. Correlations may be determined between the degree of the measured shift in the absorbance spectra curve 1402 of reduced hemoglobin to an NO concentration level. The correlations may be determined from a large sample population or for a particular patient and stored in a calibration database. The biosensor 100 may thus obtain an NO concentration level by measuring the shift of the absorbance spectra curve 1402 of reduced hemoglobin.
Though the absorbance spectrums shown in the graph 1500 were measured using in vitro assays, the biosensor 100 may obtain an NO concentration level by measuring the shift of the absorbance spectra curve 1502 of deoxygenated hemoglobin and/or by measuring the shift of the absorbance spectra curve 1506 of oxygenated hemoglobin in vivo. The biosensor 100 may then access a calibration database that correlates the measured shift in the absorbance spectra curve 1502 of deoxygenated hemoglobin to an NO concentration level. Similarly, the biosensor may access a calibration database that correlates the measured shift in the absorbance spectra curve 1506 of oxygenated hemoglobin to an NO concentration level.
The biosensor 100 accesses a calibration database that correlates the relative shift in the absorbance spectra of the substance with a concentration level of NO at 1606. The biosensor 100 may thus obtain an NO concentration level using calibration database and the measured relative shift in absorbance spectra of the spectrum at 1608.
The biosensor 100 may use a plurality of these methods to determine a plurality of values for the concentration level of NO at 1708. The biosensor 100 may determine a final concentration value using the plurality of values. For example, the biosensor 100 may average the values, obtain a mean of the values, etc.
The biosensor 100 displays the baseline NO measurement in 1804 and then non-invasively and continuously monitors the NO measurement in blood vessels in 1806. For example, the biosensor 100 may obtain the NO measurement at least once per minute or more frequently, such as every 10 seconds or 30 seconds, and continues to display the NO concentration level. The biosensor 100 may average the obtained L values and/or R values over one or more respiratory cycles or over a predetermined time period (such as one minute) to obtain the NO concentration level.
One or more of the NO measurements (Such as Lλ1=390 nm, R value, NO concentration level) may be compared to predetermined thresholds at 1808. For example, normal ranges of the NO measurement from the baseline measurement are determined. Depending on the comparison, one or more health risks may be determined. For example, diabetic risk or potential carbon monoxide poisoning or septic risk may be determined. The one or more health risks or a general warning of abnormal NO measurements may then be displayed at 1810. In addition, the NO measurements or warnings may be transmitted by the biosensor either wirelessly or over a wired connection over a LAN or WAN to a user device or monitoring station or physician's office or other third party in 1812. For example, the warning may be transmitted to a nursing station, an emergency alert service or physician's office to provide emergency services to the patient.
Embodiment—Adjustments in Response to Positioning of the Biosensor
The biosensor 100 is configured to obtain position information on a patient at 1902. The position information may be input from a user interface. In another aspect, the biosensor 100 may determine its own positioning. For example, the PPG circuit 110 may be configured to detect characteristics of underlying tissue. The biosensor 100 then correlates the detected characteristics of the underlying tissue with known or predetermined characteristics of underlying tissue (e.g. measured from an abdominal area, wrist, forearm, leg, etc.) to determine its positioning. Information of amount and types of movement from an activity monitoring circuit implemented within the biosensor 100 may also be used in the determination of position.
In response to the determined position and/or detected characteristics of the underlying tissue, the operation of the biosensor 100 is adjusted at 1904. For example, the biosensor 100 may adjust operation of the PPG circuit 110 at 1906. The article, “Optical Properties of Biological Tissues: A Review,” by Steven L. Jacques, Phys. Med. Biol. 58 (2013), which is hereby incorporated by reference herein, describes wavelength-dependent behavior of scattering and absorption of different tissues. The PPG circuit 110 may adjust a power of the LEDs or a frequency or wavelength of the LEDs based on the underlying tissue. The biosensor 100 may adjust processing of the data at 1908. For example, an absorption coefficient may be adjusted when determining a concentration level of a substance based on Beer-Lambert principles due to the characteristics of the underlying tissue.
In addition, the calibrations utilized by the biosensor 100 may vary depending on the positioning of the biosensor at 1908. For example, the calibration database may include different table or other correlations between R values and NO concentration level depending on position of the biosensor. Due to the different density of tissue and vessels, the R value obtained from measurements over an abdominal area may be different than measurements over a wrist or forehead. The calibration database may thus include different correlations of the R value and NO concentration level depending on the underlying tissue. Other adjustments may also be implemented by the biosensor 100 depending on predetermined or measured characteristics of the underlying tissue.
The biosensor 100 is thus configured to obtain position information and perform adjustments to its operation in response to the position information.
Embodiment—EMR Network
The biosensor 100 may communicate to one or more user devices 2010, such as a smart phone, laptop, desktop, smart tablet, smart watch, or any other processing device. In one aspect, the user device 2010 or biosensor 100 may communicate the patient's vitals to a local or remote monitoring station 2012 of a caregiver or physician.
One or more biosensors 100 are communicatively coupled to an EMR application server 2030 through one or more user devices 2010 and/or networks in the EMR network 2000. The EMR server 2030 includes a network interface card (NIC) 2032, a server processing circuit 2034, a server memory device 2036 and EMR server application 2038. The network interface circuit (NIC) 2032 includes an interface for wireless and/or wired network communications with one or more of the exemplary networks in the EMR network 2000. The network interface circuit 2032 may also include authentication capability that provides authentication prior to allowing access to some or all of the resources of the EMR application server 2030. The network interface circuit 2032 may also include firewall, gateway and proxy server functions.
The EMR application server 2030 also includes a server processing circuit 2034 and a memory device 2036. For example, the memory device 2036 is a non-transitory, processor readable medium that stores instructions which when executed by the server processing circuit 2034, causes the server processing circuit 2034 to perform one or more functions described herein. In an embodiment, the memory device 2036 stores a patient EMR 408 that includes biosensor data and historical data of a patient associated with the patient ID 406.
The EMR application server 2030 includes an EMR server application 2038. The EMR server application 2038 is operable to communicate with the biosensors 100 and/or user devices 2010 and monitoring stations 2012. The EMR server application 2038 may be a web-based application supported by the EMR application server 2030. For example, the EMR application server 2030 may be a web server and support the EMR server application 2038 via a website. In another embodiment, the EMR server application 2038 is a stand-alone application that is downloaded to the user devices 2010 by the EMR application server 2030 and is operable on the user devices 2010 without access to the EMR application server 2030 or only needs to accesses the EMR application server 2030 for additional information and updates.
In use, the biosensors 100 may communicate patient's biosensor data (such as NO concentration level, heart rate, temperature, respiratory cycle, etc.) to the EMR application server 2030. A biosensor 100 may be programmed with a patient identification 406 that is associated with a patient's EMR 408. The biosensor 100 measures the patient's vitals, such as heart rate, pulse, blood oxygen levels, NO levels, etc. and may also communicate information to a drug delivery system to administer medications to the patient. The biosensor 100 is configured to transmit the patient vitals to the EMR application server 2030. The EMR server application 2038 updates an EMR 408 associated with the patient identification 406 with the patient vitals.
The EMR application server 2030 may also be operable to communicate with a physician's office 2018 or pharmacy 2020 or other third party health care provider over the EMR network 2000 to provide biosensor data and receive instructions on dosages of medication. For example, the EMR server application 2038 may transmit NO level information, heart rate information or pulse rate information or medication dosages or blood concentration levels of one or more relevant substances to a physician's office 2018. The EMR server application 2038 may also be configured to provide medical alerts to notify a user, physician or other caregiver when vitals are critical or reach a certain predetermined threshold.
The EMR server application 2030 may also receive instructions from a physician's office 2018, pharmacy 2020 or hospital 2022 or other caregiver regarding a prescription or administration of a dosage of medication. The EMR server application 2038 may then transmit the instructions to the biosensor 100. The instructions may include a dosage amount, rate of administration or frequency of dosages of a medication. The biosensor 100 may then control a drug delivery system to administer the medication automatically as per the transmitted instructions.
Embodiment—Interoperability of Biosensors and Other Devices
In another example, a plurality of biosensors 100, such as the first biosensor 100a and the second biosensor 100b, may be positioned on a patient to monitor an ECG of the patient. The biosensors 100 may communicate the ECG measurements directly or indirectly to each other to generate an electrocardiogram. The electrocardiogram is transmitted to an EMR application server 2030 or monitoring station 2012 or to a user device 2010. Based on the electrocardiogram, a doctor or user may provide instructions to one of the medical devices 2102a-b. For example, one of the medical devices 2102a-b may include a pacemaker.
Embodiment—Clinical Data
Clinical data obtained using an embodiment of the biosensor 100 is now described herein. The biosensor 100 was used to monitor concentration levels or indicators of Nitric Oxide in the blood flow of a patient in clinical trials over a measurement time period.
The L values 2700 fluctuate between 0.005 and 0.045 over the four second time period illustrated in the graph.
The averaged R values 2900 may be obtained from averaging the Ratio R over a predetermined time period or may be calculated from the averaged L values. As shown in
as described hereinabove. The R FFT curve 3004 is determined using FFT techniques. The R differential absorption curve 3008 is determined using the shift in absorbance spectra as described hereinabove with respect to
From the clinical trials, the L390 values are measuring NO levels in the arterial blood flow. The R value for L390/L940 nm may thus be used to provide NO concentration levels in the pulsating arterial blood flow. From the clinical trials, it seems that the NO levels are reflected in the R values obtained from L390 nm/L940 nm. The NO concentration level may be obtained from the R values and a calibration database that correlates the R value with known concentration level of NO for the patient or for a large general population.
In other embodiments, rather than Lλ1=390 nm, the L value may be measured at wavelengths in a range around 390 nm such as from 400 nm to 380 nm, e.g., as seen in the graphs wherein Lλ1=395 nm is used to obtain a concentration level of NO. In addition, Lλ2 may be obtained at any wavelength at approximately 660 nm or above. Thus, R obtained at approximately Lλ1=380 nm-400 nm and Lλ2≥660 nm may also be used to determine concentration levels of NO.
A first spectral response is obtained from the first photodetector and a second spectral response is obtained from the second photodetector at 3502. A phase difference is obtained between the arterial pressure wave in the first spectral response and the second spectral response at 3504. A pulse rate is then obtained using a calibration database at 3506.
The higher the UV wavelength, the less the penetration depth in the skin tissue. Thus, by projecting a plurality of different UV wavelengths at the skin tissue, the biosensor 100 may determine absorption rate of a substance into the skin tissue.
The biosensor 100 obtains the spectral responses from a plurality of different wavelengths, wherein the different wavelengths have varying penetration depths of skin tissue at 3702. The absorption spectra of a substance at different depths in the skin tissue may be determined from the different spectral responses. The biosensor 100 determines the difference in absorption spectra of a substance from the plurality of different spectral responses at 3704. The biosensor 100 may continue to obtain and monitor the difference in absorption spectra of a substance at different depths in the skin tissue over a period of time. The biosensor 100 may then obtain an absorption rate of the substance into the skin tissue from the difference in absorption spectra of a substance at the plurality of different wavelengths at 3706.
The calibration tables 3802 include one or more calibration tables for one or more underlying skin tissue type 3808a-n. In one aspect, the calibration tables 3808 correlate an R value to a concentration level of NO for a plurality of underlying skin tissue types. For example, a first set of tables 3808a-n may correlate R values to NO concentration levels for a wrist area, a second table for an abdominal area, a third table for a forehead area, etc.
In another aspect, a set of calibration tables 3810a-n correlate an absorption spectra shift to a concentration level of NO for a plurality of underlying skin tissue types. For example, a first table 3810 may correlate a degree of absorption spectra shift of oxygenated hemoglobin to NO concentration levels for a wrist area, a second table 3810 for an abdominal area, a third table 3810 for a forehead area, etc. The degree of shift may be for the peak of the absorbance spectra curve of oxygenated hemoglobin from around 421 nm. In another example, the set of table 3810s may correlate a degree of absorption spectra shift of deoxygenated hemoglobin to NO concentration levels for a wrist area, a second table for an abdominal area, a third table for a forehead area, etc. The degree of shift may be for the peak of the absorbance spectra curve of deoxygenated hemoglobin from around 430 nm.
The calibration database 3802 may also include a set of calibration curves 3804 for a plurality of underlying skin tissue types. The calibration curves may correlate R values or degree of shifts to concentration levels of NO.
The calibration database 3802 may also include calibration functions 3806. The calibration functions 3806 may be derived (e.g., using regressive functions) from the correlation data from the calibration curves 3804 or the calibration tables 3802. The calibration functions 3806 may correlate R values or degree of shifts to concentration levels of NO for a plurality of underlying skin tissue types.
Based on these unexpected results, in one aspect, the biosensor 100 may determine non-invasively an indicator of the NO concentration level in vivo of a patient. The biosensor 100 detects a plurality of spectral responses from light directed at skin tissue of a patient. The spectral responses are used to determine an R value from Lλ1/Lλ2, wherein λ1 has a high absorption coefficient for NO and is in a range from 370 nm to 410 nm and preferably in a range from 390-395 nm. The second wavelength λ2 has a lower absorption coefficient for NO than the first wavelength λ1 and may be in a range equal to or greater than 660 nm.
In the clinical trials herein, the R value was in a range of 0-8. Other ranges, weights or functions derived using the R value described herein may be implemented that changes the numerical value of the R values described herein or the range of the R values described herein. A calibration database may then correlate the R value to a concentration level of NO.
The R value may be non-invasively and quickly and easily obtained using the biosensor 100 in a physician's office or other clinical setting or at home. In one aspect, the R value may be used to determine whether further testing for health conditions need to be performed. For example, upon detection of a low R value of less than 1, a clinician may then determine to perform further testing and monitoring, e.g. for diabetes.
A wide range of conditions require frequent monitoring such as diabetes, hypotension, hypertension, cardiac arrest, carbon monoxide poisoning, seizures, strokes, respiratory arrest, dyspnea, and sepsis. The biosensor 100 may be used to continuously monitor patients with one or more of these conditions. The biosensor 100 may monitor NO levels, as well as other patient vitals such as heart rate, blood pressure, and/or SpO2.
Embodiment-Measurements of Other Substances
Using similar principles described herein, the biosensor 100 may measure concentration levels or indicators of other substances in pulsating blood flow. For example, absorption coefficients for one or more frequencies that have an intensity level responsive to concentration level of substance may be determined. The biosensor 100 may then detect the substance at the determined one or more frequencies as described herein and determine the concentration levels using the Beer-Lambert principles and the absorption coefficients. The L values and R values may be calculated based on the obtained spectral response. In one aspect, the biosensor 100 may detect various electrolyte concentration levels or blood analyte levels, such as bilirubin and sodium and potassium. In another aspect, the biosensor 100 may detect sodium NACL concentration levels in the arterial blood flow to determine dehydration. In yet another aspect, the biosensor 100 may be configured to detect proteins or abnormal cells or other elements or compounds associated with cancer. In another aspect, the PPG sensor may detect white blood cell counts. In another aspect, the biosensor may detect blood alcohol levels.
For example, the biosensor 100 may also determine alcohol levels in the blood using wavelengths at approximately 390 nm and/or 468 nm. In another embodiment, an R468,940 value for at least L468 nm/L940 nm may be used as a liver enzyme indicator, e.g. P450 enzyme indicator. In another embodiment, an R592,940 value for at least L592 nm/L940 nm may be used as a digestive indicator to measure digestive responses, such as phase 1 and phase 2 digestive stages. In another aspect, the biosensor 100 may detect white blood cell counts or concentration levels in arterial blood flow using similar PPG techniques. The presence of white blood cell counts may indicate the presence of infection.
In another aspect, abnormal cells or proteins or compounds that are present or have higher concentrations in the blood with persons having cancer, may be detected using similar PPG techniques described herein at one or more other wavelengths. Thus, cancer risk may then be obtained through non-invasive testing by the biosensor 100. Since the biosensor 100 may operate in multiple frequencies, various health monitoring tests may be performed concurrently.
One or more embodiments have been described herein for the non-invasive and continuous biosensor 100. Due to its compact form factor, the biosensor 100 may be configured for measurements on various skin surfaces of a patient, including on a forehead, arm, wrist, abdominal area, chest, leg, ear lobe, finger, toe, ear canal, etc. The biosensor includes one or more sensors for detecting biosensor data, such as a patient's vitals, activity levels, or concentrations of substances in the blood flow of the patient. In particular, the PPG sensor is configured to monitor concentration levels or indicators of one or more substances in the blood flow of the patient. In one aspect, the PPG sensor may non-invasively and continuously detect nitric oxide (NO) levels in pulsatile arterial blood flow.
In one or more aspects herein, a processing module or circuit includes at least one processing device, such as a microprocessor, micro-controller, digital signal processor, microcomputer, central processing unit, field programmable gate array, programmable logic device, state machine, logic circuitry, analog circuitry, digital circuitry, and/or any device that manipulates signals (analog and/or digital) based on hard coding of the circuitry and/or operational instructions. A memory is a non-transitory memory device and may be an internal memory or an external memory, and the memory may be a single memory device or a plurality of memory devices. The memory may be a read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and/or any non-transitory memory device that stores digital information.
As may be used herein, the term “operable to” or “configurable to” indicates that an element includes one or more of circuits, instructions, modules, data, input(s), output(s), etc., to perform one or more of the described or necessary corresponding functions and may further include inferred coupling to one or more other items to perform the described or necessary corresponding functions. As may also be used herein, the term(s) “coupled”, “coupled to”, “connected to” and/or “connecting” or “interconnecting” includes direct connection or link between nodes/devices and/or indirect connection between nodes/devices via an intervening item (e.g., an item includes, but is not limited to, a component, an element, a circuit, a module, a node, device, network element, etc.). As may further be used herein, inferred connections (i.e., where one element is connected to another element by inference) includes direct and indirect connection between two items in the same manner as “connected to”.
As may be used herein, the terms “substantially” and “approximately” provides an industry-accepted tolerance for its corresponding term and/or relativity between items. Such an industry-accepted tolerance ranges from less than one percent to fifty percent and corresponds to, but is not limited to, frequencies, wavelengths, component values, integrated circuit process variations, temperature variations, rise and fall times, and/or thermal noise. Such relativity between items ranges from a difference of a few percent to magnitude differences.
Note that the aspects of the present disclosure may be described herein as a process that is depicted as a schematic, a flowchart, a flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination corresponds to a return of the function to the calling function or the main function.
The various features of the disclosure described herein can be implemented in different systems and devices without departing from the disclosure. It should be noted that the foregoing aspects of the disclosure are merely examples and are not to be construed as limiting the disclosure. The description of the aspects of the present disclosure is intended to be illustrative, and not to limit the scope of the claims. As such, the present teachings can be readily applied to other types of apparatuses and many alternatives, modifications, and variations will be apparent to those skilled in the art.
In the foregoing specification, certain representative aspects of the invention have been described with reference to specific examples. Various modifications and changes may be made, however, without departing from the scope of the present invention as set forth in the claims. The specification and figures are illustrative, rather than restrictive, and modifications are intended to be included within the scope of the present invention. Accordingly, the scope of the invention should be determined by the claims and their legal equivalents rather than by merely the examples described. For example, the components and/or elements recited in any apparatus claims may be assembled or otherwise operationally configured in a variety of permutations and are accordingly not limited to the specific configuration recited in the claims.
Furthermore, certain benefits, other advantages and solutions to problems have been described above with regard to particular embodiments; however, any benefit, advantage, solution to a problem, or any element that may cause any particular benefit, advantage, or solution to occur or to become more pronounced are not to be construed as critical, required, or essential features or components of any or all the claims.
As used herein, the terms “comprise,” “comprises,” “comprising,” “having,” “including,” “includes” or any variation thereof, are intended to reference a nonexclusive inclusion, such that a process, method, article, composition or apparatus that comprises a list of elements does not include only those elements recited, but may also include other elements not expressly listed or inherent to such process, method, article, composition, or apparatus. Other combinations and/or modifications of the above-described structures, arrangements, applications, proportions, elements, materials, or components used in the practice of the present invention, in addition to those not specifically recited, may be varied or otherwise particularly adapted to specific environments, manufacturing specifications, design parameters, or other operating requirements without departing from the general principles of the same.
Moreover, reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” Unless specifically stated otherwise, the term “some” refers to one or more. All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. No claim element is intended to be construed under the provisions of 35 U.S.C. § 112(f) as a “means-plus-function” type element, unless the element is expressly recited using the phrase “means for” or, in the case of a method claim, the element is recited using the phrase “step for.”
The present application claims priority under 35 U.S.C. § 120 as a continuation to U.S. patent application Ser. No. 15/718,721 entitled “SYSTEM AND METHOD FOR MONITORING NITRIC OXIDE LEVELS USING A NON-INVASIVE, MULTI-BAND BIOSENSOR,” filed Sep. 28, 2017 and U.S. patent application Ser. No. 15/622,941 entitled, “SYSTEM AND METHOD FOR MONITORING NITRIC OXIDE LEVELS USING A NON-INVASIVE, MULTI-BAND BIOSENSOR,” filed Jun. 14, 2017, which are hereby expressly incorporated by reference herein, which claims priority under 35 U.S.C. § 119 to U.S. Provisional Application No. 62/463,104 entitled, “SYSTEM AND METHOD FOR MONITORING NITRIC OXIDE LEVELS USING A NON-INVASIVE, MULTI-BAND BIOSENSOR,” filed Feb. 24, 2017, and hereby expressly incorporated by reference herein.
Number | Name | Date | Kind |
---|---|---|---|
4913150 | Cheung et al. | Apr 1990 | A |
5115133 | Knudson | May 1992 | A |
5269310 | Jones et al. | Dec 1993 | A |
5358703 | Ching | Oct 1994 | A |
5515847 | Braig et al. | May 1996 | A |
5582170 | Soller | Dec 1996 | A |
5673692 | Schulze et al. | Oct 1997 | A |
5823966 | Buchert | Oct 1998 | A |
5885842 | Lai | Mar 1999 | A |
5947911 | Wong et al. | Sep 1999 | A |
5983121 | Tsuchiya | Nov 1999 | A |
6087087 | Yonetani et al. | Jul 2000 | A |
6280390 | Akselrod et al. | Aug 2001 | B1 |
6285896 | Tobler et al. | Sep 2001 | B1 |
6305804 | Rice et al. | Oct 2001 | B1 |
6537225 | Mills | Mar 2003 | B1 |
6694180 | Boesen | Feb 2004 | B1 |
6719705 | Mills | Apr 2004 | B2 |
6819950 | Mills | Nov 2004 | B2 |
6921367 | Mills | Jul 2005 | B2 |
6985763 | Boas et al. | Jan 2006 | B2 |
7154592 | Reynolds et al. | Dec 2006 | B2 |
7167736 | Winther | Jan 2007 | B2 |
7171251 | Sarussi et al. | Jan 2007 | B2 |
7179228 | Banet | Feb 2007 | B2 |
7209775 | Bae et al. | Apr 2007 | B2 |
7291497 | Holmes et al. | Nov 2007 | B2 |
7371562 | Cunningham et al. | May 2008 | B2 |
7608045 | Mills | Oct 2009 | B2 |
7647083 | Al-Ali et al. | Jan 2010 | B2 |
7761127 | Al-Ali et al. | Jul 2010 | B2 |
7763472 | Doctor et al. | Jul 2010 | B2 |
7764982 | Dalke et al. | Jul 2010 | B2 |
7941199 | Kiani | May 2011 | B2 |
8224411 | Al-Ali et al. | Jul 2012 | B2 |
8255027 | Al-Ali et al. | Aug 2012 | B2 |
8328420 | Abreu | Dec 2012 | B2 |
8385996 | Smith et al. | Feb 2013 | B2 |
8401605 | Huiku | Mar 2013 | B2 |
8483787 | Al-Ali et al. | Jul 2013 | B2 |
8494507 | Tedesco et al. | Jul 2013 | B1 |
8597274 | Sloan et al. | Dec 2013 | B2 |
8652040 | Leboeuf et al. | Feb 2014 | B2 |
8676284 | He | Mar 2014 | B2 |
8730047 | Ridder et al. | May 2014 | B2 |
8868149 | Eisen et al. | Oct 2014 | B2 |
8888701 | Leboeuf et al. | Nov 2014 | B2 |
8906693 | Schultz et al. | Dec 2014 | B2 |
8923918 | Kreger et al. | Dec 2014 | B2 |
8961932 | Silverman | Feb 2015 | B2 |
9022973 | Sexton et al. | May 2015 | B2 |
9131882 | Al-Ali et al. | Sep 2015 | B2 |
9149216 | Eisen et al. | Oct 2015 | B1 |
9149646 | Keswarpu et al. | Oct 2015 | B2 |
9387033 | Yodfat et al. | Jul 2016 | B2 |
9442092 | Lane | Sep 2016 | B2 |
9521970 | Hoppe et al. | Dec 2016 | B2 |
9554738 | Gulati et al. | Jan 2017 | B1 |
9562913 | Stamler | Feb 2017 | B2 |
9642578 | Newberry | May 2017 | B2 |
9668701 | Maarek | Jun 2017 | B2 |
9713428 | Chon et al. | Jul 2017 | B2 |
9739663 | Halder et al. | Aug 2017 | B2 |
9820656 | Olivier | Nov 2017 | B2 |
9839381 | Weber et al. | Dec 2017 | B1 |
9924895 | Rawicz et al. | Mar 2018 | B2 |
9949675 | Miller | Apr 2018 | B2 |
9999355 | Kirenko | Jun 2018 | B2 |
10028682 | Thiele | Jul 2018 | B2 |
D824937 | Sparandara et al. | Aug 2018 | S |
10099554 | Steeg et al. | Oct 2018 | B2 |
10130285 | Singamsetty et al. | Nov 2018 | B1 |
10153796 | Fung et al. | Dec 2018 | B2 |
10181021 | Venkatraman et al. | Jan 2019 | B2 |
10206619 | Lee et al. | Feb 2019 | B1 |
10215698 | Han et al. | Feb 2019 | B2 |
10227063 | Abreu | Mar 2019 | B2 |
10232156 | Netzel et al. | Mar 2019 | B2 |
10278591 | Gil | May 2019 | B2 |
D850316 | Ennis et al. | Jun 2019 | S |
10314500 | Olivier | Jun 2019 | B2 |
10322728 | Porikli et al. | Jun 2019 | B1 |
10342495 | Melkoniemi et al. | Jul 2019 | B2 |
10349847 | Kwon et al. | Jul 2019 | B2 |
10420470 | Kwon et al. | Sep 2019 | B2 |
10420491 | Rajan et al. | Sep 2019 | B2 |
10433726 | Ramesh et al. | Oct 2019 | B2 |
10433738 | Thomas et al. | Oct 2019 | B2 |
10433739 | Weekly et al. | Oct 2019 | B2 |
10463283 | Ferber et al. | Nov 2019 | B2 |
20020049389 | Abreu | Apr 2002 | A1 |
20030229276 | Sarussi et al. | Dec 2003 | A1 |
20040078219 | Kaylor et al. | Apr 2004 | A1 |
20040100376 | Lye et al. | May 2004 | A1 |
20040157341 | Reynolds et al. | Aug 2004 | A1 |
20050101841 | Kaylor et al. | May 2005 | A9 |
20050209516 | Fraden | Sep 2005 | A1 |
20050228244 | Banet | Oct 2005 | A1 |
20050228299 | Banet | Oct 2005 | A1 |
20050245831 | Banet | Nov 2005 | A1 |
20060009698 | Banet | Jan 2006 | A1 |
20060094942 | Winther | May 2006 | A1 |
20060287589 | Wobermin et al. | Dec 2006 | A1 |
20070202605 | Doctor et al. | Aug 2007 | A1 |
20070203405 | Shimomura | Aug 2007 | A1 |
20070260132 | Sterling | Nov 2007 | A1 |
20080146890 | Leboeuf et al. | Jun 2008 | A1 |
20080165017 | Schwartz | Jul 2008 | A1 |
20080208019 | Nitzan | Aug 2008 | A1 |
20080241199 | Silverman | Oct 2008 | A1 |
20090043178 | Belotserkovsky | Feb 2009 | A1 |
20090156988 | Ferren et al. | Jun 2009 | A1 |
20090187167 | Sexton et al. | Jul 2009 | A1 |
20090287120 | Ferren et al. | Nov 2009 | A1 |
20100049020 | Dalke et al. | Feb 2010 | A1 |
20100191080 | Mills | Jul 2010 | A1 |
20100274101 | Lin et al. | Oct 2010 | A1 |
20100331631 | Maclaughlin | Dec 2010 | A1 |
20110082355 | Eisen et al. | Apr 2011 | A1 |
20110106050 | Yodfat et al. | May 2011 | A1 |
20110137141 | Razoumov et al. | Jun 2011 | A1 |
20110160697 | Yodfat et al. | Jun 2011 | A1 |
20110166553 | Holmes et al. | Jul 2011 | A1 |
20110224518 | Tindi | Sep 2011 | A1 |
20110237464 | Cunningham et al. | Sep 2011 | A1 |
20110275978 | Hyde | Nov 2011 | A1 |
20120010683 | Keswarpu et al. | Jan 2012 | A1 |
20120029363 | Lund | Feb 2012 | A1 |
20120095302 | Adhikari | Apr 2012 | A1 |
20120131507 | Sparandara et al. | May 2012 | A1 |
20120136054 | Schultz et al. | May 2012 | A1 |
20120156933 | Kreger et al. | Jun 2012 | A1 |
20120203077 | He et al. | Aug 2012 | A1 |
20120238844 | Grata et al. | Sep 2012 | A1 |
20120330126 | Hoppe et al. | Dec 2012 | A1 |
20130030259 | Thomsen et al. | Jan 2013 | A1 |
20130060098 | Thomsen et al. | Mar 2013 | A1 |
20130066176 | Addison et al. | Mar 2013 | A1 |
20130110311 | Ver Steeg et al. | May 2013 | A1 |
20130310669 | Nitzan | Nov 2013 | A1 |
20140046160 | Terashima et al. | Feb 2014 | A1 |
20140100432 | Golda et al. | Apr 2014 | A1 |
20140112940 | Lane | Apr 2014 | A1 |
20140194342 | Zhang et al. | Jul 2014 | A1 |
20140243648 | Dubielczyk | Aug 2014 | A1 |
20140253709 | Bresch et al. | Sep 2014 | A1 |
20140275852 | Hong et al. | Sep 2014 | A1 |
20140297313 | Condurso et al. | Oct 2014 | A1 |
20140316226 | Ferber et al. | Oct 2014 | A1 |
20150066238 | Todd et al. | Mar 2015 | A1 |
20150088007 | Bardy et al. | Mar 2015 | A1 |
20150094914 | Abreu | Apr 2015 | A1 |
20150105633 | LeBoeuf | Apr 2015 | A1 |
20150105638 | Eisen et al. | Apr 2015 | A1 |
20150109617 | Gilbert et al. | Apr 2015 | A1 |
20150148622 | Moyer et al. | May 2015 | A1 |
20150148635 | Benaron | May 2015 | A1 |
20150150453 | Abreu | Jun 2015 | A1 |
20150182172 | Shelley et al. | Jul 2015 | A1 |
20150229341 | Fung et al. | Aug 2015 | A1 |
20150250404 | Maarek | Sep 2015 | A1 |
20150282747 | Thiele | Oct 2015 | A1 |
20150366471 | Leboeuf et al. | Dec 2015 | A1 |
20160018257 | Mirov et al. | Jan 2016 | A1 |
20160058308 | Robinson | Mar 2016 | A1 |
20160058347 | Reichgott et al. | Mar 2016 | A1 |
20160066863 | Thaveeprungsrporn et al. | Mar 2016 | A1 |
20160100781 | Bechtel et al. | Apr 2016 | A1 |
20160262707 | Devries | Sep 2016 | A1 |
20160345912 | Maarek | Dec 2016 | A1 |
20160367154 | Gladshtein et al. | Dec 2016 | A1 |
20170014035 | Newberry | Jan 2017 | A1 |
20170027521 | Geva et al. | Feb 2017 | A1 |
20170050518 | Steeg et al. | Feb 2017 | A1 |
20170071550 | Newberry | Mar 2017 | A1 |
20170091436 | Cao et al. | Mar 2017 | A1 |
20170172477 | Adusumilli et al. | Jun 2017 | A1 |
20170215811 | Newberry | Aug 2017 | A1 |
20170256110 | Divincent et al. | Sep 2017 | A1 |
20170347894 | Bhushan et al. | Dec 2017 | A1 |
20170347899 | Bhushan et al. | Dec 2017 | A1 |
20180117291 | Netzel et al. | May 2018 | A1 |
20180140210 | Jelfs et al. | May 2018 | A1 |
20180140237 | Rajan et al. | May 2018 | A1 |
20180177416 | Church et al. | Jun 2018 | A1 |
20180177440 | Jelfs et al. | Jun 2018 | A1 |
20180200433 | Cirit | Jul 2018 | A1 |
20180264242 | Hoffman et al. | Sep 2018 | A1 |
20180353137 | Balajadia et al. | Dec 2018 | A1 |
20180358119 | Bhushan et al. | Dec 2018 | A1 |
20190046039 | Ramesh et al. | Feb 2019 | A1 |
20190050622 | Cabibihan et al. | Feb 2019 | A1 |
20190086331 | Han | Mar 2019 | A1 |
20190099114 | Radian et al. | Apr 2019 | A1 |
20190110745 | Linnes et al. | Apr 2019 | A1 |
20190125963 | Mou et al. | May 2019 | A1 |
20190125964 | Mou et al. | May 2019 | A1 |
20190133471 | Olson et al. | May 2019 | A1 |
20190192085 | Krishna et al. | Jun 2019 | A1 |
20190192086 | Krishna et al. | Jun 2019 | A1 |
20190251238 | Venkatraman et al. | Aug 2019 | A1 |
20190358387 | Elbadry et al. | Nov 2019 | A1 |
Number | Date | Country |
---|---|---|
102609627 | Jul 2012 | CN |
2017001250 | Jan 2017 | EP |
3488776 | May 2019 | EP |
2004047630 | Jun 2004 | WO |
2007013054 | Feb 2007 | WO |
2008006150 | Jan 2008 | WO |
2010128852 | Nov 2010 | WO |
2010147968 | Dec 2010 | WO |
2012108895 | Aug 2012 | WO |
2013052318 | Apr 2013 | WO |
2013127564 | Sep 2013 | WO |
2014163583 | Oct 2014 | WO |
2015143197 | Sep 2015 | WO |
2015200148 | Dec 2015 | WO |
2017001249 | Jan 2017 | WO |
2018025257 | Feb 2018 | WO |
2018206875 | Nov 2018 | WO |
2019030700 | Feb 2019 | WO |
2019118053 | Jun 2019 | WO |
Entry |
---|
EP Ser. No. 18758516.1. Extended Search Report (dated Nov. 12, 2020). |
Ignarro et al. “Endothelium-derived relaxing factor produced and released from artery and vein is nitric oxide.” Proc. Natl. Acad. Sci. USA vol. 84, pp. 9265,9269 (Dec. 1987). |
Noack et al. “Spectrophotometric determination of nitric oxide using hemoglobin.” Neuroprotocols: A Companion to Methods in Neurosciences, vol. 1, No. 2,. pp. 133-139 (Oct. 1992). |
Alonso et al. “The nitric oxide-endothelin-1 connection.” Heart Failure Review, 8, 107-115 (2003). |
PCT/US2018/0019273. International Search Report & Written Opinion (dated May 15, 2018). |
Titheradge, “Nitric oxide in septic shock.” Biochimica et Biophysica acta 1411, pp. 437-455 (1998). |
Ogurek et al. “Carbon monoxide poisoning, smoke inhalation, cyanide poisoning.” Condell EMS System CE, pp. 1-102 (Mar. 2009). |
Archer, “Measurement of nitric oxide in biological models.” The FASEB Journal, vol. 7, pp. 349-360 (Feb. 1993). |
Oosthuizen et al., “Nitric oxide as inflammatory mediator in post-traumatic stress disorder (PTSD): evidence from an animal model.” Neuropsychiatr Dis Treat. (2), pp. 109-123 (Jun. 2005). |
Prasad et al. “Common biochemical defects linkage between post-traumatic stress disorders, mild traumatic brain injury (TBI) and penetrating TBI.” Brain Res. 1599, UC Irvine (Jan. 2015). |
Sudarma et al. “Effect of dark chocolate on nitric oxide serum levels and blood pressure in prehypertension subjects.” Acta Med Indones-Indones J Intern. Med. vol. 43:4 (Oct. 2011). |
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---|---|---|---|
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---|---|---|---|
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