Non-invasive optics-based method for monitoring central venous pressure

Abstract

A system for estimating a central venous pressure (CVP) of a patient includes a sensor array configured to (1) emit light toward a target vein in the patient, and (2) capture non- invasive measurements. The non-invasive measurements includes an amount of the light that interacts with blood in the target vein. The system also includes a holder configured to hold the sensor array in contact with skin of the patient over the target vein. The system also includes a computing system configured to receive the non-invasive measurements from the sensor array, generate a waveform based upon the non-invasive measurements, identify an artifact in the waveform, determine a pulse transit time (PTT) of the blood in the target vein based upon the waveform, determine a venous pulse wave velocity (PWV) based upon the PTT, and determine the CVP of the patient based upon the venous PWV.

Description

NON-INVASIVE OPTICS-BASED METHOD FOR MONITORINGCENTRAL VENOUS PRESSURECross-Reference to Related Applications

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 567,625, filed March 20, 2024, the disclosure of which is incorporated herein by reference.Field of the Disclosure

[0002] The present disclosure relates generally to systems and methods for monitoring central venous pressure (CVP) in a patient. More particularly, the present disclosure relates to non- invasive, optics-based systems and methods for monitoring the CVP.Background of the Disclosure

[0003] Pediatric congestive heart failure (CHF) is a complex disease that presents as an endstage condition due to various structural, functional, and biologic etiologies. Every patient that develops or is born with heart abnormalities is by nature at risk of developing CHF. In addition, a group of genetic abnormalities are known to produce inherited or acquired forms of cardiomyopathy, diseases in which the contractile function of the heart deteriorates over time. These patients are also at risk of developing CHF.

[0004] Symptoms of CHF occur when the heart fails to meet the circulatory demands of the body, leading to an increase in intravascular fluid pressure in the venous system, known as central venous pressure (CVP). CVP is clinically used as an indicator of the state of compensation of a patient with CHF. While CVP is critical to adjusting heart failure medications, such as diuretics, it is currently only measurable in a hospital setting through the use of an invasive central line placed through a central vein into, or in proximity to, the right atrium of the heart. In adult patients, symptoms and patient weights guide outpatient therapies, and additional invasive devices are utilized. For children at home who are at risk of heart failure, such as those with congenital heart disease and / or cardiomyopathy, parents are left monitoring non-specific qualitative symptoms such as irritability and fatigue, resulting in imprecise care lacking data and therapeutic targets. Particularly for pre-verbal children, parent observation is the sole indicator of a change in an infant’s heart condition in the home environment. Thus, relying on monitoring these qualitative symptoms at home is setting these children up for inferior care.Summary

[0005] A system for estimating a central venous pressure (CVP) of a patient is disclosed. The system includes a sensor array configured to (1) emit light toward a target vein in the patient, and (2) capture non-invasive measurements. The non-invasive measurements includes an amount of the light that interacts with blood in the target vein. The system also includes a holder configured to hold the sensor array in contact with skin of the patient over the target vein. The system also includes a computing system configured to receive the non-invasive measurements from the sensor array, generate a waveform based upon the non-invasive measurements, identify an artifact in the waveform, determine a pulse transit time (PTT) of the blood in the target vein based upon the waveform, determine a venous pulse wave velocity (PWV) based upon the PTT, and determine the CVP of the patient based upon the venous PWV.

[0006] In another embodiment, the system includes a sensor array having a plurality of sensors that are spaced apart from one another. The sensors are optical sensors. The sensors are configured to capture non-invasive measurements by emitting light toward a target vein in the patient. The light is in a red wavelength. Part of the emitted light is absorbed by blood in the target vein. The remaining emitted light is either scattered or is reflected by the blood in the target vein. The target vein is a jugular vein in a neck of the patient. The non-invasive measurements include an amount of the light that interacts with the blood in the target vein. The interaction includes scattering or absorption. The system also includes a holder configured to hold the sensor array in contact with skin of the patient over the target vein. The holder is configured to be positioned at least partially around or on a neck of the patient. The system also includes a computing system configured to receive the non-invasive measurements from the sensors. The computing system is also configured to generate a plurality of waveforms based upon the non-invasive measurements. The waveforms include venous or arterial waveforms. The waveforms include at least a first waveform from a first of the sensors, and a second waveform from a second of the sensors. The computing system is also configured to identify artifacts in the first and second waveforms. The artifacts include venous artifacts and arterial artifacts. The computing system is also configured to filter the first and second waveforms to remove non-venous artifacts to produce a first filtered waveform and a second filtered waveform. The non-venous artifacts comprise the arterial artifacts. The computing system is also configured to determine a pulse transit time (PTT) of venous blood in the jugular vein based upon a time delay between the first and second filtered waveforms. The PTT includes a time for the venous blood to move through the jugular vein between the first andsecond sensors. The computing system is also configured to determine a venous pulse wave velocity (vPWV) based upon the PTT and a distance between the first and second sensors. The vPWV includes a velocity at which the venous blood moves through the distance in the jugular vein between the first and second sensors. The computing system is also configured to determine the CVP of the patient based upon the vPWV. The computing system is also configured to display the CVP.

[0007] A method for non-invasively estimating a central venous pressure (CVP) of a patient is also disclosed. The method includes emitting light toward a target vein in the patient. The method also includes capturing non-invasive measurements. The non-invasive measurements include an amount of the light that interacts with blood in the target vein. The method also includes generating a plurality of waveforms based upon the non-invasive measurements. The method also includes identifying artifacts in the waveforms. The method also includes determining a pulse transit time (PTT) of venous blood in the target vein based upon a time delay between the waveforms. The method also includes determining a venous pulse wave velocity (vPWV) based upon the PTT. The method also includes determining the CVP of the patient based upon the vPWV.Brief Description of the Figures

[0008] Figure 1 illustrates a perspective view of a system for non-invasively estimating a central venous pressure (CVP) of a patient, according to an embodiment. Figures IB and 1C illustrate schematic side views of a sensor array of the system, according to an embodiment.

[0009] Figure 2 illustrates a schematic view of the neck of the patient showing the jugular vein and carotid artery, according to an embodiment.

[0010] Figure 3 illustrates a flowchart of a method for non-invasively estimating the CVP of the patient, according to an embodiment.

[0011] Figure 4 illustrates a graph showing a molar extinction coefficient (cm- 1 / M) representing the absorption vs wavelength of light (in nanometers) of deoxygenated (Hb) and oxygenated blood (HbO2), according to an embodiment.

[0012] Figure 5 illustrates an example of an ideal shape of a waveform of the jugular vein, according to an embodiment.

[0013] Figure 6A illustrates a non-invasive measurement of the jugular waveform during normal breathing, and Figure 6B illustrates a non-invasive measurement of the waveform with the administration of a Valsalva Maneuver, which exemplifies an increased CVP, according to an embodiment.

[0014] Figure 7A illustrates a waveform being filtered by a smoothening filter to produce a filtered waveform, and Figure 7B illustrates the waveform being filtered by the smoothening filter, a fast Fourier transform (FFT), and shielding to produce the filtered waveform, according to an embodiment.

[0015] Figure 8A illustrates a graph showing regular breathing data, and Figure 8B illustrates a graph showing Valsalva Maneuver data, according to an embodiment.

[0016] Figure 9 illustrates a linear regression from the vPWV to the CVP, according to an embodiment.

[0017] Figure 10 illustrates a schematic view of a sensor array of the system, according to an embodiment.Detailed Description

[0018] The present disclosure includes a system and method that are configured to non- invasively monitor central venous pressure (CVP) in (e.g., pediatric) patients to better understand and treat congestive heart failure (e.g., in an at-home setting). Pulse wave velocity (PWV) is a metric that is easily obtained noninvasively. The system and method may convert venous PWV readings directly into CVP readings to facilitate monitoring the risk of heart failure.

[0019] The system includes a device that can properly and safely be implemented in the neonate and infant age group as a viable wearable form factor that can hold optical sensors a predetermined distance apart and at a constant pressure on the target vein on the skin. The system and method may be used in a hospital setting or at home. Applying this to the patient twice a day may provide a comprehensive look into the patient’s congestion status in heart failure as the data is relayed to the clinician to titrate medications such as diuretics for more personalized management.

[0020] Figure 1A illustrates a perspective view of a system 100 for non-invasively estimating a central venous pressure (CVP) of a patient 140, according to an embodiment. The system 100 may include a sensor array 110. Figures IB and 1C illustrate schematic side views of the sensor array 110, according to an embodiment. As shown in Figure IB, the sensor array 110 may include a plurality of sensors (e.g., including at least a first sensor 112A and a second sensor 112B) that are spaced apart from one another. The sensors 112A, 112B may be or include optical sensors. For example, the sensors 112A, 112B may be or include photoplethysmography sensors. The sensors 112A, 112B may be configured to capture non- invasive measurements, as described below. The sensor array 110 may also include one ormore potentiometers (two are shown: 114A, 114B) for varying the intensity of the light emitted (e.g., by light-emitting diodes).

[0021] The system 100 may also include a holder 120. The holder 120 may be configured to hold the sensor array 110 in contact with skin of the patient 140 over a target. The target may be or include a vein (e.g., the jugular vein in the neck of the patient 140). Figure 2 illustrates a schematic view of the neck of the patient 140 showing the jugular vein 210A, 210B and carotid artery 220A-220C, according to an embodiment. More particularly, Figure 2 shows the internal jugular vein 210A and the external jugular vein 210B, as well as the internal carotid artery 220A, the external carotid artery 220B, and the common carotid artery 220C. The target may be the internal jugular vein 210A and / or the external jugular vein 210B.

[0022] The holder 120 may be configured to hold the sensor array 110 against the skin at a substantially constant and minimal pressure. The holder 120 may substantially conform to a shape of an anatomy in which it is harbored. For example, the holder 120 may wrap at least partially on and / or around the neck. The holder 120 may be a portion of a circle (e.g., semicircular) with the open portion configured to be aligned with the throat so that the throat is unobstructed. The holder 120 may be attached to the skin of the neck by an adhesive. The holder 120 may include a flexible / malleable material that is configured to fit around necks of varying diameters. The holder 120 may include an organic bamboo interlock and a cushion on an inner (e.g., radial) surface thereof to provide a shock-absorbing buffer. The holder 120 may be biocompatible.

[0023] The system 100 may also include a computing system 130. The computing system 130 may be in wired or wireless communication with the sensor array 110. In the embodiment shown, the computing system 130 is coupled to the holder 120 via one or more wires. In another embodiment, the computing system 130 may not be coupled to the holder 120. The computing system 130 may be configured to perform operations, which are described in greater detail below with respect to Figure 3.

[0024] Figure 3 illustrates a flowchart of a method for non-invasively estimating the CVP of the patient 140, according to an embodiment. An illustrative order of the method 300 is provided below; however, one or more steps of the method 300 may be performed in a different order, simultaneously, repeated, or omitted. At least a portion of the method 300 may be performed by the sensor array 110 and / or the computing system 130.

[0025] The method 300 may include positioning the system 100 in contact with the patient 140, as at 305. As mentioned above, positioning the system 100 may include positioning the sensor array 110 against the skin of the patient 140 and proximate to (e.g., above) a target veinin the patient 140. The target vein may be or include the jugular vein (e.g., the internal jugular vein 210A). Positioning the system 100 may also include positioning the holder 120 at least partially on and / or around (e.g., the neck of) the patient 140 such that the holder 120 holds the sensor array 110 against the skin with a constant and minimal pressure without covering the throat.

[0026] The method 300 may also include emitting light toward the target vein (e.g., the internal jugular vein 210A) in the patient 140, as at 310. In an embodiment, no discernable venous pulse may be detected using light having a green light wavelength. However, testing has shown that light having a red light wavelength (e.g., about 650 nm to about 750 nm) may be used to detect a venous pulse. Figure 4 illustrates a graph showing absorbance through the molar extinction coefficient vs wavelength, according to an embodiment. The red wavelength has the highest absorption of deoxygenated blood and the most significant difference with the oxygenated bloods absorption, and is where the signals are the most decoupled. Part of the emitted light may be absorbed by blood in the target vein (e.g., the internal jugular vein 210A), and the remaining emitted light may be scattered and / or is reflected by the blood in the target vein (e.g., the internal jugular vein 210A).

[0027] The method 300 may also include capturing non-invasive measurements with the sensor array 110, as at 315. The non-invasive measurements may be based upon and / or in response to the emitted light. More particularly, the non-invasive measurements may include an amount of the light that interacts with the blood in the target vein (e.g., the internal jugular vein 210A). The interaction may include scattering and / or absorption. The sampling rate of the non-invasive measurements may be from about 7000 Hz to about 1000 Hz. For example, the sampling rate may be from about 7900 Hz to 8500 Hz (e.g., assuming that the sensors 112A, 112B are about 2 cm apart).

[0028] The method 300 may also include transmitting the non-invasive measurements from the sensor array 110 to the computing system 130, as at 320. Said another way, the computing system 130 may receive the non-invasive measurements from the sensor array 110.

[0029] The method 300 may also include generating (with the computing system 130) one or more waveforms based upon the non-invasive measurements, as at 325. The one or more waveforms may be or include venous and / or arterial waveforms. The one or more waveforms may include a plurality of waveforms including at least a first waveform from the first sensor 112A in the sensor array 110, and a second waveform from the second sensor 112B in the sensor array 110. Figure 5 illustrates an example of an ideal shape of a waveform of the jugular vein 210A, according to an embodiment.

[0030] The method 300 may also include identifying (with the computing system 130) artifacts in the waveform(s), as at 330. This may include identifying the artifacts in the first and / or second waveforms. The artifacts may include venous artifacts and / or arterial artifacts. The venous artifacts correspond to a blood volume and / or motion artifacts from the jugular vein 210A, 210B or other venous vessels. The arterial artifacts correspond to other artifacts from respective vasculature including the carotid artery 220A-220C and arterial vessels.

[0031] The method 300 may also include generating (with the computing system 130) an instruction to move the sensor array 110, as at 335. More particularly, the instruction may be to move the sensor array 110 in a direction toward the jugular vein 210A, 210B in response to the waveform(s) (e.g., the first and / or second waveforms) differing from a predetermined venous waveform by more than a predetermined threshold, which indicates that the sensor array 110 is too far from the jugular vein 210A, 210B and / or too close to the carotid artery 220A-220C. An amount that the waveform(s) differ may be based upon the number of the identified venous artifacts and / or the presence and / or number of identified arterial artifacts. A machine learning (ML) algorithm, such as a random forest classifier, can be implemented by the computing system 130 to determine the amount that the waveform differs from the venous artifacts by comparing it to the venous and non-venous artifacts. Figure 6 A illustrates a non- invasive measurement of the jugular waveform during normal breathing, and Figure 6B illustrates a non-invasive measurement of the waveform with the administration of a Valsalva Maneuver, which exemplifies an increased CVP, according to an embodiment. In Figure 6B, an arterial artifact 600 is identified.

[0032] The method 300 may also include filtering (with the computing system 130) the waveform(s) to produce filtered waveform(s), as at 340. More particularly, this may include removing the non-venous (e.g., arterial) artifacts from the first waveform and the second waveform to produce a first filtered waveform and a second filtered waveform. Figure 7A illustrates a waveform being filtered by a smoothening filter to produce a filtered waveform, and Figure 7B illustrates the waveform being filtered by various signal processing filters and methods for example (1) the smoothening filter, (2) filtering in the frequency domain by applying a Fast Fourier transform (FFT), and (3) shielding to produce the filtered waveform, according to an embodiment.

[0033] The method 300 may also include determining (with the computing system 130) a pulse transit time (PTT) of blood in the target (e.g., jugular) vein 210A, 210B, as at 345. More particularly, this may include determining the PTT of venous blood in the jugular vein 210A, 210B over one pulse wave based upon a time delay between the first and second (e.g., filtered)waveforms. The PTT may include a time for the blood to move through the jugular vein 210A, 210B between two or more of the sensors 112A, 112B in the sensor array 110.

[0034] The method 300 may also include determining (with the computing system 130) a pulse wave velocity (PWV) metric based upon the PTT, as at 350. More particularly, this may include determining a venous pulse wave velocity (vPWV) based upon the PTT and a distance between two or more of the sensors 112A, 112B in the sensor array 110. For example, the distance between the sensors 112A, 112B divided by the PTT may yield the venous PWV. The vPWV may be or include a velocity at which the blood moves through the distance in the jugular vein 210A, 210B between the sensors 112A, 112B. Figure 8A illustrates a graph showing regular breathing data, and Figure 8B illustrates a graph showing Valsalva Maneuver data, according to an embodiment.

[0035] The method 300 may also include determining (with the computing system 130) the CVP of the patient, as at 355. The CVP may be determined based upon the vPWV. Figure 9 illustrates a linear regression from the vPWV to the CVP, according to an embodiment. The CVP may also be determined based upon the patient’s age, weight, and / or height. The method 300 may determine the CVP within 2 mmHg or less. The CVP is a measure of pressure in the vena cava, can be used as an estimation of preload and / or the right atrial pressure (RAP).

[0036] The method 300 may also include displaying the CVP and / or RAP, as at 360. The CVP and / or RAP may be displayed on a screen on the computing system 130 or on a screen that is in wired or wireless communication with the computing system 130.

[0037] The method 300 may also include performing an action in response to the CVP and / or RAP, as at 365. The action may include generating and / or transmitting a signal (with the computing system 130) that instructs or causes a physical action to occur. In another embodiment, the action may be or include the physical action.

[0038] For example, in response to the CVP and / or RAP being less than a first threshold (e.g., 8 mmHg), a diagnosis of hypovolemia and / or dehydration may be made. As a result, doses of diuretics may be decreased, fluid administration may be performed (e.g., either by oral or IV intake), and / or heart failure medication dosages may be adjusted. Cardiologists and / or care team may also be contacted.

[0039] In response to the CVP and / or RAP being greater than a second threshold (e.g., 12 mmHg), the cardiologist and / or care team may be contacted. The cardiologist and / or care team may increase diuretic doses or ask the patient to undergo additional tests, such as a serum BNP or echocardiogram, to determine whether changes in heart or valve structure or function haveoccurred. The patient may also or instead be called in for further imaging and testing in the hospital setting.

[0040] Care teams may predominantly follow CVP / RAP trends to guide diuretic therapies, to determine timing for in-person evaluation, and to determine timing of appropriate hospital admission in the event of elevating or elevated CVP / RAP indicating the need for more aggressive medical management or transplant evaluation.

[0041] Figure 10 illustrates a schematic view of the sensor array 110, according to an embodiment. This sensor array 110 may include connectivity between the sensors 112A, 112B and a microprocessor. As described above, the sensors 112A, 112B, which may be or include optical sensors, have varying LED intensities to allow for adequate absorption of venous blood. The microprocessor is additionally connected via rainbow wiring to ensure safety.

[0042] In current clinical care pathways, care teams are unable to evaluate the trajectory of heart failure in the outpatient setting for several reasons. First, symptoms are difficult to determine until they are severe, denoting uncompensated heart failure. When children with uncompensated heart failure are identified in the medical system, they require costly hospital admissions, and therapies are late stage. The system 100 described herein will change the care paradigm to provide actionable data in the outpatient setting that can help to avoid hospitalizations for decompensated heart failure and indicate timing for appropriate earlier intervention. With data collected over larger groups of patients, predictive algorithms and machine learning applications generate the opportunity to predict decompensation even before it begins.

[0043] As used herein, the terms “inner” and “outer”; “up” and “down”; “upper” and “lower”; “upward” and “downward”; “upstream” and “downstream”; “above” and “below”; “inward” and “outward”; and other like terms as used herein refer to relative positions to one another and are not intended to denote a particular direction or spatial orientation. The terms “couple,” “coupled,” “connect,” “connection,” “connected,” “in connection with,” and “connecting” refer to “in direct connection with” or “in connection with via one or more intermediate elements or members.”

[0044] The foregoing description, for purposes of explanation, used specific nomenclature to provide a thorough understanding of the disclosure. However, it will be apparent to one skilled in the art that the specific details are not required in order to practice the systems and methods described herein. The foregoing descriptions of specific examples are presented for purposes of illustration and description. They are not intended to be exhaustive of or to limit this disclosure to the precise forms described. Many modifications and variations are possible inview of the above teachings. The examples are shown and described in order to best explain the principles of this disclosure and practical applications, to thereby enable others skilled in the art to best utilize this disclosure and various examples with various modifications as are suited to the particular use contemplated. It is intended that the scope of this disclosure be defined by the claims and their equivalents below.

Claims

Claims1. A system for estimating a central venous pressure (CVP) of a patient, the system comprising: a sensor array configured to: emit light toward a target vein in the patient; and capture non-invasive measurements, wherein the non-invasive measurements comprise an amount of the light that interacts with blood in the target vein; a holder configured to hold the sensor array in contact with skin of the patient over the target vein; and a computing system configured to: receive the non-invasive measurements from the sensor array; generate a waveform based upon the non-invasive measurements; identify an artifact in the waveform; determine a pulse transit time (PTT) of the blood in the target vein based upon the waveform; determine a venous pulse wave velocity (PWV) based upon the PTT; and determine the CVP of the patient based upon the venous PWV.

2. The system of claim 1, wherein the sensor array comprises a plurality of sensors that are spaced apart from one another, and wherein the venous PWV is also based upon a distance between the sensors.

3. The system of claim 2, wherein the sensors comprise optical sensors.

4. The system of claim 1, wherein the light is in a red wavelength.

5. The system of claim 1, wherein a first portion of the emitted light is absorbed by the blood in the target vein, and wherein a second portion of the emitted light is either scattered or is reflected by the blood in the target vein.

6. The system of claim 1, wherein the target vein comprises a jugular vein in a neck of the patient.

7. The system of claim 1, wherein the interaction comprises scattering or absorption.

8. The system of claim 1, wherein the holder is configured to be positioned at least partially around or on a neck of the patient, and wherein the holder does not cover a throat of the patient.

9. The system of claim 1 , wherein the waveform comprises a venous waveform, an arterial waveform, or a combination thereof, and wherein the artifact comprises a venous artifact or an arterial artifact.

10. The system of claim 1, wherein the waveform comprises a plurality of waveforms, wherein the artifact comprises a plurality of artifacts, and wherein the computing system is further configured to filter the waveforms to remove a portion of the artifacts to produce filtered waveforms, wherein the removed artifacts comprise non-venous artifacts, and wherein PTT of the blood in the target vein is based upon a time delay between the filtered waveforms.

11. A system for non-invasively estimating a central venous pressure (CVP) of a patient, the system comprising: a sensor array comprising a plurality of sensors that are spaced apart from one another, wherein the sensors comprise optical sensors, and wherein the sensors are configured to capture non-invasive measurements by: emitting light toward a target vein in the patient, wherein the light is in a red wavelength, wherein part of the emitted light is absorbed by blood in the target vein, wherein the remaining emitted light is either scattered or is reflected by the blood in the target vein, and wherein the target vein comprises a jugular vein in a neck of the patient; and capturing the non-invasive measurements, wherein the non-invasive measurements comprise an amount of the light that interacts with the blood in the target vein, and wherein the interaction comprises scattering or absorption; a holder configured to hold the sensor array in contact with skin of the patient over the target vein, wherein the holder is configured to be positioned at least partially around or on a neck of the patient; and a computing system configured to: receive the non-invasive measurements from the sensors;generate a plurality of waveforms based upon the non-invasive measurements, wherein the waveforms comprise venous or arterial waveforms, wherein the waveforms comprise at least a first waveform from a first of the sensors, and a second waveform from a second of the sensors; identify artifacts in the first and second waveforms, wherein the artifacts comprise venous artifacts and arterial artifacts; filter the first and second waveforms to remove non-venous artifacts to produce a first filtered waveform and a second filtered waveform, wherein the non-venous artifacts comprise the arterial artifacts; determine a pulse transit time (PTT) of venous blood in the jugular vein based upon a time delay between the first and second filtered waveforms, wherein the PTT comprises a time for the venous blood to move through the jugular vein between the first and second sensors; determine a venous pulse wave velocity (vPWV) based upon the PTT and a distance between the first and second sensors, wherein the vPWV comprises a velocity at which the venous blood moves through the distance in the jugular vein between the first and second sensors; determine the CVP of the patient based upon the vPWV; and display the CVP.

12. The system of claim 11, wherein the optical sensors comprise photoplethysmography sensors.

13. The system of claim 11, wherein the holder is configured to hold the sensor array against the skin at a substantially constant pressure, wherein the holder is attached to the skin of the neck by an adhesive, wherein the holder is biocompatible, and wherein the holder does not cover a throat of the patient.

14. The system of claim 11, wherein the venous artifacts correspond to a blood volume and motion artifacts from the jugular vein, and wherein the arterial artifacts correspond to other artifacts from a carotid artery.

15. The system of claim 11, wherein the computing system is further configured to:determine that the first and / or second waveforms differ from a predetermined venous waveform by more than a threshold, wherein an amount that the first and / or second waveforms differ is based upon the number of the venous artifacts; and generate an instruction to move the sensor array in a direction toward the jugular vein in response to determining that the first and / or second waveforms differ from the predetermined venous waveform by more than the threshold.

16. A method for non-invasively estimating a central venous pressure (CVP) of a patient, the method comprising: emitting light toward a target vein in the patient; capturing non-invasive measurements, wherein the non-invasive measurements comprise an amount of the light that interacts with blood in the target vein; generating a plurality of waveforms based upon the non-invasive measurements; identifying artifacts in the waveforms; determining a pulse transit time (PTT) of venous blood in the target vein based upon a time delay between the waveforms; determining a venous pulse wave velocity (vPWV) based upon the PTT; and determining the CVP of the patient based upon the vPWV.

17. The method of claim 16, further comprising positioning a holder at least partially around a neck of the patient without covering a throat of the patient, wherein the holder holds a sensor array in contact with skin of the patient proximate to the target vein, and wherein the sensor array captures the non-invasive measurements.

18. The method of claim 16, wherein the non-invasive measurements are captured by a plurality of sensors, and wherein the vPWV is also determined based upon a distance between the sensors.

19. The method of claim 16, further comprising determining that the waveforms differ from a predetermined venous waveform by more than a threshold, wherein an amount that the differ is based upon the artifacts.

20. The method of claim 19, further comprising generating an instruction to move a sensor array toward the target vein in response to determining that the waveforms differ from thepredetermined venous waveform by more than the threshold, wherein the sensor array captures the non-invasive measurements.

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