System and method for pipeline fluid characterization

Abstract

The invention relates to systems and methods for pipeline fluid characterization. A system performs a method for characterizing passage of patient fluid through a catheter. The method includes quantifying a flow rate of fluid content through the catheter, wherein the fluid content includes a patient fluid; estimating a concentration of a fluid component of the patient fluid in the fluid content; and characterizing the passage of the patient fluid lost through the catheter based on the quantified flow rate and the concentration of the fluid component. At least one of the quantified flow or the concentration of the fluid component is based on sensor data from a sensor arrangement coupled to the conduit. Other apparatus and methods are also described.

Description

[0001] This application is a divisional application of an application with an application date of September 27, 2019, application number 201980077509.7, and invention name “System and method for pipeline fluid characterization”.

[0002] Related Applications

[0003] This application claims priority to U.S. Provisional Patent Application No. 62 / 737,730, filed on September 27, 2018, and entitled “SYSTEMS AND METHODS for IN-LINE FLUID CHARACTERIZATION,” the entire contents of which are incorporated herein by reference. Technical Field

[0004] The subject matter disclosed herein generally relates to the technical field of special purpose machines that facilitate characterization of the passage of fluids, which characterization may include estimation of blood loss or blood acquisition, including computerized variations of the software configurations of such special purpose machines and improvements to such variations, and the subject matter disclosed herein generally relates to the art of improving such special purpose machines. Background Art

[0005] Incorrect estimates of the passage of a patient's fluid (e.g., lost fluid, processed fluid, or acquired fluid), such as during a surgical procedure, may unnecessarily consume medical resources and threaten the patient's health. For example, in the case where the fluid is blood, overestimation of the patient's blood loss may result in unnecessary consumption of transfusion-grade blood and may have adverse effects, such as unnecessary clinical risks to the patient and shortages of transfusion-grade blood that may be required by other patients. As another example, underestimation of a patient's blood loss may result in delayed resuscitation and transfusion, increased risk of infection, tissue death, or even patient death in situations such as hemorrhage. Underestimation and overestimation of blood acquisition (e.g., from transfusion) may produce similar effects, respectively. Underestimation or overestimation of processed blood (e.g., by a dialysis machine) may unnecessarily prolong such treatment or reduce the benefits of such treatment.

[0006] In addition, inaccurate estimates of fluid passage (e.g., fluid lost, fluid processed, or fluid acquired) can be a significant contributor to high operating costs and high surgical costs for hospitals, clinics, and other medical facilities. In particular, unnecessary transfusions due to overestimation of patient blood loss result in higher operating costs for medical institutions. Furthermore, delayed transfusions due to underestimation of patient blood loss are associated with billions of dollars in avoidable patient infections and re-hospitalizations each year. Therefore, it may be desirable to have more accurate systems and methods for estimating or otherwise characterizing the passage of fluids for a patient. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Some example embodiments are shown by way of example and not limitation in the figures of the accompanying drawings.

[0009] Figure 1 is a schematic diagram illustrating a system for inline fluid characterization according to some example embodiments.

[0010] Figure 2A is a perspective view of a housing for a sensor arrangement according to some example embodiments.

[0011] Figure 2B and Figure 2C According to some example embodiments, Figure 2A A cross-sectional view of the housing depicted in FIG.

[0012] Figure 3A Schematic diagram illustrating a catheter segment insertion according to some example embodiments.

[0013] Figure 3B To illustrate the connection to Figure 3A Schematic diagram of the sensor arrangement of the catheter segment insertion is depicted in FIG.

[0014] Figure 4A is a schematic diagram illustrating a clamping mechanism for a catheter according to some example embodiments.

[0015] Figure 4B is a schematic diagram illustrating another clamping mechanism for a catheter according to some example embodiments.

[0016] Figure 5 is a schematic diagram illustrating a branch catheter with an alternating clamping mechanism according to some example embodiments.

[0017] Fig. 6A is a schematic diagram illustrating an ultrasonic flow sensor according to some example embodiments.

[0018] Figure 6B FIG. 1 is a schematic diagram illustrating another ultrasonic flow sensor according to some example embodiments.

[0019] Fig. 7A is a schematic diagram illustrating an optical flow sensor according to some example embodiments.

[0020] Figure 7B To illustrate the Fig. 7A A set of graphs of signal waveforms of detectors in the optical flow sensor arrangement depicted in .

[0021] Fig. 8A is a schematic diagram illustrating an optical flow sensor arrangement according to some example embodiments.

[0022] Figure 8B According to some example embodiments, Fig. 8A A cross-sectional view of the optical flow sensor arrangement depicted in FIG.

[0023] Figure 8C To illustrate the Figure 8B Illustration of the signal strength of the detectors in the optical flow sensor arrangement depicted in FIG.

[0024] Fig. 9 is a cross-sectional view of another optical flow sensor arrangement according to some example embodiments.

[0025] Fig.10 is a schematic diagram illustrating a thermal mass flow sensor according to some example embodiments.

[0026] Fig.11 is a schematic diagram illustrating a multi-spectral imaging arrangement according to some example embodiments.

[0027] Fig.12 1 is a flow chart illustrating operation of a system in performing a method of characterizing the contents of a fluid flowing through a catheter, according to some example embodiments.

[0028] Fig.13 is a diagram illustrating motion tracking of fluid contents according to some example embodiments.

[0029] Fig.14 A flow chart illustrating logical operations in characterizing fluid contents flowing through a catheter, according to some example embodiments.

[0030] Fig.15 is a graph illustrating optical quality estimation for fluid contents according to some example embodiments.

[0031] Fig.16 is a graph illustrating estimation of fluid component concentration based on particle scattering, according to some example embodiments.

[0032] Fig.17 is a diagram illustrating a mathematical merging of results from various types of sensors according to some example embodiments.

[0033] Fig.18 is a block diagram illustrating components of a machine capable of reading instructions from a machine-readable medium and performing any one or more of the methodologies discussed herein, according to some example embodiments. Detailed Description

[0035] Example methods (e.g., procedures or algorithms) help characterize the passage of a fluid (e.g., a patient fluid undergoing a medical procedure, which may include blood as a fluid component) flowing within a catheter, and example systems (e.g., a dedicated machine configured by dedicated software) are configured to help characterize the fluid flowing within the catheter. Examples represent possible variations only. Unless otherwise expressly stated, structures (e.g., structural components, such as modules) are optional and may be combined or subdivided, and operations (e.g., in procedures, algorithms, or other functions) may vary in order or be combined or subdivided. In the following description, for the purpose of explanation, many specific details are set forth to provide a thorough understanding of various example embodiments. However, it will be apparent to those skilled in the art that this subject matter may be practiced without these specific details.

[0036] In general, an exemplary method for characterizing the passage of a patient fluid includes: accessing sensor data of a sensor arrangement connected to a conduit through which fluid contents flow, wherein the fluid contents include patient fluid; quantifying the flow rate of the fluid contents through the conduit; estimating the concentration of a fluid component of the patient fluid in the fluid contents; and characterizing the passage of the patient fluid through the conduit based on the quantified flow rate and the concentration of the fluid component. For example, in some variations, characterizing the passage of the patient fluid includes quantifying the volume of the patient fluid flowing through the conduit. The flow rate, the concentration of the fluid component, or both can be determined (e.g., estimated) based on sensor data (e.g., sampled data) from a sensor arrangement connected to the conduit. In some variations, the patient fluid to be characterized is blood, and the fluid component whose concentration is estimated is hemoglobin. In some variations, the method includes reducing the flow rate of the fluid contents through the conduit while quantifying the flow rate of the fluid contents, while estimating the concentration of the fluid component of the patient fluid, or while quantifying the flow rate of the fluid contents and estimating the concentration of the fluid component of the patient fluid.

[0037] There are a variety of suitable ways to quantify the flow of fluid contents through a conduit. In some variations, quantifying the flow of fluid contents includes estimating the flow rate of the fluid contents. For example, estimating the flow rate can include using an ultrasonic Doppler flowmeter to emit ultrasound into the conduit and analyzing the frequency shift of the ultrasound reflected from the fluid contents. As another example, estimating the flow rate can include using a time-of-flight ultrasonic flowmeter to emit ultrasound into the conduit and analyzing the flight time of the ultrasound transmitted through the fluid contents. In another example, estimating the flow rate includes comparing a first optical signal and a second optical signal, wherein the first optical signal corresponds to light detected at a first position along the conduit, and the second optical signal corresponds to light detected at a second position along the conduit. The comparison of the first optical signal and the second optical signal can be used to estimate the flow rate of the fluid contents in the conduit. In some variations, quantifying the flow of fluid contents includes estimating the thermal mass flow of the fluid contents. For example, estimating the thermal mass flow of the fluid contents can include introducing a known amount of heat into the flow of the fluid contents and measuring the associated temperature changes (e.g., keeping the probe at a constant temperature in the fluid contents and measuring the energy consumed by doing so). As another example, estimating the thermal mass flow rate of the fluid contents may include introducing a known amount of heat into the flow of the fluid contents and measuring a change in the temperature of the fluid contents at some point downstream.

[0038] In addition, there are a variety of suitable ways to estimate the concentration of a fluid component in the fluid contents. For example, estimating the concentration of a fluid component may include analyzing a multispectral image of the catheter. As another example, estimating the concentration of a fluid component may include applying a machine learning algorithm to a color image of the catheter. In addition, in some variations, the method may include performing a spectral analysis to determine the composition of the fluid contents.

[0039] In general, an example system for characterizing the passage of a patient fluid through a catheter includes: a catheter configured to transport fluid contents including a patient fluid; a sensor arrangement connectable to the catheter, wherein the sensor arrangement includes at least one sensor configured to generate sensor data based on the fluid contents; and one or more processors configured to perform operations including: accessing the sensor data, quantifying a flow rate of the fluid contents through the catheter, estimating a concentration of a fluid component of the patient fluid in the fluid contents, and characterizing the passage of the patient fluid through the catheter based on the quantified flow rate and the concentration of the fluid component.

[0040] The sensor arrangement can include any suitable form factor configured to be coupled to a catheter. For example, in some variations, the sensor arrangement can include a housing configured to cover at least a portion of the catheter and can be configured to be clamped on or slide on the catheter. For example, the housing can include a clamp configured to be clamped on the catheter. As another example, the system can also include a catheter insert that can be coupled inline with the catheter line.

[0041] The sensor arrangement may include any combination of one or more suitable sensors for quantifying flow, determining the concentration of fluid components, or both. For example, the sensor arrangement may include an ultrasonic flow rate sensor, a thermal mass flow sensor, or any suitable combination thereof. In some variations, the sensor arrangement includes at least one optical sensor configured to detect light transmitted through the fluid contents. For example, the sensor arrangement may include a plurality of optical sensors, which are arranged at a plurality of axial positions along the conduit, at a plurality of circumferential positions around the conduit, or any suitable combination thereof. In some variations, the sensor arrangement includes one or more optical sensors, thermal sensors, ultrasonic sensors, or any suitable combination thereof. In addition, such sensors may include one or more optical sensor arrays, which are configured to perform multi-spectral or spectroscopic imaging, color imaging, or both, to facilitate estimating the concentration of the fluid components.

[0042] In some example embodiments, a system includes:

[0043] a catheter configured to deliver fluid contents including patient fluid;

[0044] a sensor arrangement coupled to the catheter and comprising at least one sensor configured to generate sensor data based on the fluid contents; and

[0045] One or more processors configured to perform operations including:

[0046] accessing sensor data from a sensor arrangement coupled to a conduit through which fluid contents flow, the fluid contents including patient fluid;

[0047] quantifying the flow rate of fluid contents through the catheter;

[0048] estimating a concentration of a fluid component of a patient fluid in the fluid contents flowing through the catheter; and

[0049] Passage of a patient fluid through the catheter is characterized based on a quantified flow rate of the fluid contents and an estimated concentration of a fluid constituent in the fluid contents, at least one of quantifying the flow rate or estimating the concentration based on sensor data from a sensor arrangement coupled to the catheter.

[0050] In certain example embodiments, a method includes:

[0051] accessing sensor data from a sensor arrangement coupled to a conduit through which fluid contents flow, the fluid contents including patient fluid;

[0052] quantifying the flow rate of fluid contents through the catheter;

[0053] estimating a concentration of a fluid component of a patient fluid in the fluid contents flowing through the catheter; and

[0054] Passage of a patient fluid through a catheter is characterized by one or more processors based on a quantified flow rate of the fluid contents and an estimated concentration of a fluid constituent in the fluid contents, at least one of the quantified flow rate or the estimated concentration being based on sensor data from a sensor arrangement coupled to the catheter.

[0055] In various example embodiments, a machine-readable medium includes instructions that, when executed by one or more processors of a machine, cause the machine to perform operations including:

[0056] accessing sensor data from a sensor arrangement coupled to a conduit through which fluid contents flow, the fluid contents including patient fluid;

[0057] quantifying the flow rate of fluid contents through the catheter;

[0058] estimating the concentration of a fluid component in the fluid contents flowing through the conduit; and

[0059] Passage of a patient fluid through the catheter is characterized based on a quantified flow rate of the fluid contents and an estimated concentration of a fluid constituent in the fluid contents, at least one of quantifying the flow rate or estimating the concentration being based on sensor data from a sensor arrangement coupled to the catheter.

[0060] In general, the methods and systems discussed herein are operable to characterize the passage of patient fluids (e.g., among other fluid contents) flowing through a catheter. Such passage of patient fluids includes the loss of patient fluids of a patient (e.g., in the case where blood collected by a catheter during surgery is lost), the acquisition of patient fluids by a patient (e.g., in the case where a catheter is transporting blood transfused into a patient), the processing of patient fluids (e.g., in the case where a catheter is transporting blood processed by a dialysis machine), or any suitable combination thereof. For the sake of clarity and brevity, many illustrative examples discussed herein focus on the case where patient fluids (e.g., blood) are lost by a patient. However, the methods and systems discussed herein are generally applicable to characterizing any passage of any patient fluid (e.g., urine or amniotic fluid), including passage into a patient, passage out of a patient, passage into and out of a patient (e.g., passage when processing a patient fluid), or passage that neither enters nor flows out of a patient (e.g., passage from one container to another container).

[0061] For example, the methods and systems described herein can be used to characterize the fluid (e.g., body fluid) lost by a patient during a medical process (e.g., childbirth, surgical procedures, etc.). For example, the methods and systems can be used to track or otherwise estimate the amount of fluid components (e.g., blood) lost by a patient throughout a medical process, and can be updated and displayed substantially in real time during the process, at the end of the process, or during and at the end of the process. These methods and systems can be used in various settings, including in the following settings: hospital or clinic settings (e.g., operating rooms), military settings (e.g., battlefields), or other suitable medical settings. This information can be used to improve the medical treatment of patients. For example, during a surgical procedure, after a surgical procedure, or during and after a surgical procedure, a medical staff (e.g., a nurse or surgeon) who receives this information can then make appropriate decisions for the treatment of the patient based on the improved accuracy of this information about the patient's condition (e.g., determining whether to provide a blood transfusion to the patient and how much blood to transfuse). For example, after obtaining more accurate information about a patient's fluid loss or patient's condition, medical staff can better avoid delaying a blood transfusion, thereby improving medical outcomes. Additionally, healthcare professionals can avoid providing unnecessary transfusions, which unnecessarily deplete transfusionable blood stocks, increase surgical costs and medical expenses, and increase patient health risks.

[0062] The estimate of the amount of patient fluid collected can be summarized as a running total or overall estimate of the amount of patient fluid lost by the patient during the procedure. In some example embodiments, such an estimate can be combined with an estimate of fluid collected in batches, an estimate of fluid collected cumulatively over time, or an estimate of fluid collected in batches and an estimate of fluid collected cumulatively over time. For example, the total volume of fluid, the total rate of patient fluid loss, or both can be estimated at any particular point during the procedure, at any particular point after the procedure, or at any particular point during and after the procedure.

[0063] In some variations, for the patient fluid of interest (e.g., blood), the estimated amount of patient fluid from multiple sources is aggregated to generate an estimate of the total loss of patient fluid. For example, the extracorporeal fluid lost by the patient can be collected in a container such as a tank or other fluid reservoir (e.g., collected with a suction rod as described below). Additionally or alternatively, surgical textiles or other absorbent articles (such as surgical sponges (e.g., laparotomy sponges), surgical dressings, surgical gauze, surgical towels, absorbent pads (e.g., cutting pads), absorbent drapes, vaginal packing, other textiles, other absorbent articles, or any suitable combination thereof) can be used to collect the fluid lost by the patient. For purposes of tracking, hygiene, etc., textiles or absorbent articles can be placed in bags (e.g., sponge counting bags). In addition, the collection of lost fluids can be performed with dedicated containers. For example, during childbirth, a drape with at least one pocket (e.g., a blood collection V-shaped drape with a triangular pocket) can be placed under the patient to collect blood, amniotic fluid, urine, etc. In some variations, the amount of fluid collected in an article (such as a surgical textile or canister) is estimated based on a measured weight (e.g., an indicated mass) of the article containing the fluid. In some variations, the amount of fluid collected in an article such as a surgical textile or canister is estimated using one or more of the methods or systems described in U.S. Pat. No. 8,792,693, U.S. Pat. No. 8,983,167, U.S. Pat. Publication No. 9,824,441, U.S. Pat. No. 9,773,320, U.S. Pat. Publication No. 2016 / 0335779, U.S. Pat. Publication No. 2017 / 0186160, U.S. Pat. Publication No. 2018 / 0199827, each of which is incorporated herein by reference in its entirety.

[0064] For example, the systems and methods for line fluid characterization described herein facilitate characterizing the fluid contents within a catheter. For example, during a medical procedure, patient fluids may be collected in a reservoir, transferred into a catheter, and then drained into another reservoir, such as into a sealed waste management system. Figure 1As shown, fluid recovery device 102 (for example, suction rod) or other patient fluid sources collect patient fluid from surgical site, tank, surgical textiles or other fluid sources containing fluid to be characterized or otherwise to be evaluated. The collected patient fluid can be delivered to conduit 120 via pipeline, and can continue to flow into reservoir 130 (for example, tank or sealed waste management system). In other words, conduit 120 can be placed to be communicated with fluid recovery device 102 (or other fluid sources) and reservoir 130 fluids. In some modifications, conduit 120, fluid recovery device 102, or conduit 120 and fluid recovery device 102 can be communicated with vacuum source 140 (for example, the vacuum pump of reservoir 130) fluid, and the vacuum source 140 is configured to provide suction to collect fluid to fluid recovery device 102.

[0065] In some variations, the circuit fluid characterization systems described herein can be integrated into a pre-existing setup with a waste management system for collecting patient fluids without adding or modifying a significant amount of equipment. Figure 1 As shown, a system 100 for characterizing patient fluid loss of a patient includes a sensor arrangement 110 that can be coupled to a catheter 120. The sensor arrangement 110 is capable of performing line fluid characterization and includes one or more sensors or other measurement devices (e.g., using various measurement methods) to characterize one or more characteristics of the fluid within the catheter 120. The various types of sensors that may be included in the sensor arrangement 110 will be described in further detail below. As further described below, the system 100 may also include at least one processor that is configured to characterize patient fluid loss based at least in part on sensor data. As further described below, the sensor data, the results of analyzing the sensor data, or both the sensor data and the results of analyzing the sensor data can be communicated to any suitable external device via, for example, a transmission system 112 (e.g., a wireless transmission system).

[0066] Unlike the systems and methods discussed herein, various existing systems for analyzing the concentration of fluid components in a catheter rely on a set of predefined conditions to perform their analysis. For example, simplified flow conditions, such as laminar flow at a constant or controlled volume flow rate, may limit certain existing systems. In contrast, the methods and systems described herein analyze a range of flow types in a catheter, including laminar flow, turbulent flow, flow that varies at different speeds or flow rates, intermittent flow, and flow of mixed fluid contents (e.g., a mixture of patient blood, patient urine, saline, and air), all of which may occur in an unpredictable manner when the fluid is collected by a fluid recovery device (e.g., fluid recovery device 102) during a medical procedure. In addition, some variations of the methods and systems described herein isolate parameters of interest regarding selected fluid components of fluid contents in a catheter. For example, the pipeline fluid characterization method and system can specifically quantify patient fluid loss (e.g., blood loss) when the patient fluid is collected and passed through a catheter (e.g., catheter 120) even under unpredictable flow conditions and when mixed with other fluids (e.g., saline and air).

[0067] Sensor arrangement example

[0068] In general, if Figure 1 As shown, system 100 includes sensor arrangement 110, and this sensor arrangement 110 is configured to be connected to conduit 120, to realize the pipeline characterization of the fluid content in conduit 120.Sensor arrangement 110 includes at least one sensor, and this at least one sensor can be configured to quantify the flow of the fluid content through conduit, estimate the concentration of the fluid component in patient fluid, or quantify the flow of the fluid content through conduit and estimate the concentration of the fluid component in patient fluid.Fluid content includes at least one patient fluid (for example, blood or urine), possible one or more other fluids (for example, saline or air), or their combination.Sensor arrangement can be arranged at least in part in the housing of supporting sensor component (for example, one or more sensors, corresponding sensor electronics, data transmitter, processor, etc.).

[0069] The sensor data may be stored locally, analyzed locally, or both by one or more processors located in or near the sensor arrangement 110. Figure 1 As shown, the sensor data may be transmitted via a transmission system 112 (eg, a wireless or wired transmitter) configured to communicate with a computing device 150 (eg, a remote computing device) for analysis. Fig.18An example of computing device 150 is further described. For example, as described further below, patient fluid loss can be characterized based at least in part on a quantified flow rate of patient fluid in conduit 120 and a concentration of a fluid component (eg, blood) in the patient fluid.

[0070] Example Shell

[0071] The sensor arrangement 110 may be at least partially arranged in a housing that supports at least some of the components of the sensor arrangement 110 and its accompanying electronics. The housing may also couple the sensor arrangement 110 to the conduit 120, one or more other conduits or conduit branches, or any suitable combination thereof. Alternatively, at least some of the sensors and other components of the sensor arrangement 110 may be separately coupled to the conduit 120 (e.g., outside of a single common housing), such as separately coupled to the conduit 120. Thus, in some variations, the sensor arrangement 110 may be adjustable or universal in the sense that, for example, the housing, individual components, or any suitable combination thereof (e.g., one or more groups of components) may be coupled to various types of conduits (e.g., not dependent on coupling to any particular type or brand of conduit).

[0072] In some variations, the housing is configured to clip onto the catheter 120. For example, Figure 2A As shown, the housing 220 for the sensor arrangement 210 may include at least a first jaw 222 and a second jaw 224 configured to be clamped together on the catheter 120. Each jaw 222 or 224 may, for example, include at least one conduit seat 226 shaped and sized to accommodate a section of the catheter 120 that is disposed in the Figure 2B and Figure 2C 250. For example, to accommodate a catheter having a circular cross-section (e.g., catheter 250), each jaw 222 or 224 may include a semicircular catheter seat (e.g., catheter seat 226). Catheter seat 226 may be configured (e.g., shaped) to position catheter 250 relative to one or more sensors 230 and other components within sensor arrangement 210. Figure 2A As shown, one or more catheter adapters 226 can be defined by a cutout on the sidewall of one or both jaws 222 and 224. Alternatively, each catheter adapter 226 can include an elongated semicircular concave surface extending along the length of the housing 220, such that when the housing 220 is clamped onto the catheter 250, the catheter adapters 226 collectively form an inner cavity extending along the length of the housing. A sensor (e.g., a sensor arrangement as described in further detail below) can be arranged along such a catheter adapter surface.

[0073] like Figure 2B and Figure 2CAs shown in the cross-sectional view of FIG. 1 , the first clamping jaw 222 and the second clamping jaw 224 may be connected by at least one joint 228, which enables the housing to be opened around a conduit (e.g., conduit 250) ( Figure 2B ) and closed ( Figure 2C ). Joint 228 may include, for example, a hinge or other pin joint. Jaws 222 and 224 may include one joint (e.g., joint 228) extending along the length of housing 220 or multiple such joints distributed along the length of housing 220. In some variations, joint 228 may be spring loaded, such as with a torsion spring, to be biased to be closed or biased to be open. Additionally or alternatively, joint 228 may include one or more detents that bias the jaws to be positioned at any angle in a predetermined, discrete set of angles. Although Figure 2B and Figure 2C The first jaw 222 and the second jaw 224 are shown to be substantially identical or symmetrical (e.g., each jaw forms half of the housing 220), but it should be understood that the housing 220 can include jaws having any suitable size relative to each other (e.g., a deeper main jaw coupled with a shallower cap-like jaw). In addition, the housing 220 can include three, four, or other suitable number of jaws. In other variations, the housing 220 can be configured to wrap around the catheter 250 (e.g., having a C-shaped cross-section that transversely engages the catheter 250).

[0074] The housing 220 may also include one or more securing elements 229 configured to secure the housing 220 in a closed position. The securing elements 229 may include, for example, latches, cooperating snap features, magnets, etc. In some variations, the housing 220 may include one or more sealing elements (e.g., around the catheter hub 226, around the interfaces 222 and 224 between the jaws, etc.), such as a gasket material, to completely enclose a section of the catheter 250 within the housing 220 in a substantially fluid-tight, air-tight, or both manner. Additionally, in some variations, the housing 220, the sealing elements, or both the housing 220 and the sealing elements may be opaque (e.g., made of an opaque material) to help prevent ambient light from entering the housing 220, as such ambient light may interfere with sensor readings within the housing 220.

[0075] The size of housing 220 can be arranged to be coupled to a conduit (e.g., conduit 250) with a predetermined diameter. For example, housing 220 can be configured to accommodate or otherwise be coupled to a conduit having a diameter between about 4mm and about 20mm or a conduit of any suitable size. In other variations, housing 220 can be adjustable to be securely coupled to a conduit with various diameters. For example, in order to adapt to a certain range of conduit diameters and not cause a loose connection around a conduit, one or more conduit seats in conduit seat 226 can include a deformable surface that can be compressed so that housing 220 can accommodate and adapt to a larger conduit diameter, increase volume to accommodate and adapt to a smaller conduit diameter, or both. For example, a deformable surface can include a cushion, other deformable materials, an inflatable surface, etc. In some variations, the size of conduit seat 226 can be adjustable, such as utilizing a mechanism similar to a leaf shutter.

[0076] Figure 3A and Figure 3B Another variation of a sensor arrangement 310 is shown having a catheter segment that can be coupled to one or more other catheter segments (eg, a reusable or disposable catheter insert). Figure 3A As shown, the system 100 may include a conduit segment 350 that may be inserted inline between other conduit portions 360a and 360b. The conduit segment 350 may include an internal volume that may be placed in fluid communication with the conduit portion 360a at an inlet end and in fluid communication with the conduit portion 360b at an outlet end. For example, the conduit segment 350 may be connected to the conduit portions 360a and 360b via connectors 352 and 354, which may be, for example, sleeve connectors, threaded connectors, or any suitable connectors. Figure 3B As shown, a housing 320 with a sensor can be placed above the catheter segment 350. The housing 320 can include an inner cavity or other catheter receiving surface. For example, the housing 320 can include a plurality of jaws (e.g., similar to those described above with respect to Figures 2A-2C The jaws 222 and 224 may have a C-shaped cross-section wrapped around the catheter segment 350. In some variations, the catheter segment 350 is disposable and intended for a single use, while the housing 320 is reusable. However, in other variations, the catheter segment 350 may be designed for multiple reuses, and the housing 320 may be discarded after a single use or a limited number of uses, or any suitable combination thereof.

[0077] In some variations, housing 320 includes a pinching mechanism to temporarily reduce the flow rate (e.g., pause or temporarily slow the flow rate) of the fluid contents through a fully or partially enclosed conduit (e.g., conduit segment 350) in order to transiently achieve a somewhat stable flow state for sensor measurements. The pinching mechanism can be configured to fully or partially enclose the conduit at one or more axial locations along the conduit. For example, Figure 4A As shown, the clamping mechanism may include opposing pincher elements 420 on the conduit 450 and actuated to move toward each other to reduce or stop flow through the conduit 450. As another example, Figure 4B As shown, the clamping mechanism may include a cam 430, at least one cam having a varying radius such that rotation of the cam 430 causes the cam 430 to reduce or stop flow through the conduit 450. In some variations, the reduction or stop of flow is cyclical (e.g., periodic) with continued rotation of the cam 430. Alternatively, the clamping mechanism may include only one clamping element 420 or only one cam 430 opposed to a static surface (e.g., a flat surface). In some variations, the housing may include two or more clamping mechanisms. For example, as Figure 5 As shown, conduit 550 can be bifurcated into two conduit branches 550a and 55b (for example, subsequently recombining in downstream), and two clamping mechanisms 510a and 510b can be connected to conduit branches 550a and 550b respectively.When a clamping mechanism is actuated to reduce the flow in its corresponding conduit branch, a group of sensors positioned at the clamping mechanism upstream can perform measurement.By actuating clamping mechanisms 510a and 510b in an alternating manner, system 100 can perform the measurement of the fluid contents in conduit 550, and does not substantially limit the overall volume flow or substantially do not hinder the upstream suction of patient fluid.In some modifications, the division of conduit (for example, conduit 550) into two or more conduit branches can be completed by conduit segment (such as the conduit segment 350 of the above-mentioned insertion).Any of the above-mentioned arrangements can be substantially contained in the housing.

[0078] Other variations of the housing can be coupled to the catheter in any suitable manner. For example, in addition to being clamped onto a catheter (e.g., catheter 120, 250, 450, or 550) as described above, the housing can also be configured to slide over the catheter like a sleeve, or wrap around the catheter (e.g., in a spiral shape). Furthermore, as described above, in some variations, a disposable catheter segment and a reusable housing unit can be coupled together and inserted with other catheter sections.

[0079] Example Sensor

[0080] The sensor arrangement (e.g., sensor arrangement 110, 210 or 310) may include one or more sensors configured to quantify flow (e.g., estimate the speed of flow, the mass flow rate of flow, or any suitable combination thereof), estimate the concentration of fluid components, or quantify both flow and estimate the concentration of fluid components. In general, one or more sensors may be located on or near the outer surface of a conduit (e.g., conduit 120, 250, 450 or 550). In some variations, as described below, the sensor may be configured to quantify the speed of flow through the conduit. In other variations, as described below, the sensor may be configured to quantify the mass of the fluid contents flowing through the conduit. In addition, the volume measurement of the fluid contents may be derived from the quantified flow measurement. For example, the volume flow rate through the conduit may be derived from the flow rate (e.g., flow velocity). In the case where the entire profile of the conduit is filled with fluid contents, the volume flow rate is the quantified flow velocity multiplied by the cross-sectional area of ​​the conduit. As another example, the volume of the fluid contents flowing through the conduit may be determined from the mass of the measured fluid contents. In the case of uniform fluid contents, the fluid content volume is the quantified mass of the fluid contents divided by the known density of the fluid contents. Other volume measurements can be derived based on the quantified flow and other information related to the composition of the fluid contents (e.g., by spectral analysis as described in further detail below). In some variations, one or more volume measurements are used to specifically quantify patient fluid passing through the catheter, which in turn can be used to help quantify overall patient fluid loss.

[0081] Example Ultrasonic Flow Sensor

[0082] In some variations, the sensor arrangement (eg, sensor arrangement 110, 210, or 310) includes one or more ultrasonic flow sensors. Fig. 6A As shown, the sensor arrangement may include at least one ultrasonic Doppler flowmeter 620 located near or adjacent to a conduit 650 in which the fluid contents flow. The ultrasonic Doppler meter 620 may include a transducer including a transmitter (Tx) configured to transmit an ultrasonic beam into the conduit 650 and a receiver (Rx) configured to detect ultrasonic waves reflected by the fluid contents in the conduit 650. The frequency shift of the reflected ultrasonic waves may be analyzed to determine the relative motion between the transmitter, the fluid contents, and the receiver. In the case where the transmitter and the receiver are fixed relative to the conduit 650, the measured relative motion may be related to the flow rate of the fluid contents in the conduit 650.

[0083] In general, the flow rate can be estimated according to Equation 1 below:

[0084]

[0085] Where V = flow rate, c = speed of sound in the fluid contents, f t = frequency of transmission, f r = received frequency, and φ = relative angle between the transmitted ultrasonic beam and the direction of fluid flow. Some of these parameters (such as the speed of sound in the fluid contents) depend on the composition of the fluid contents in the conduit 650 (e.g., fluid composition). Therefore, in some variations, a varying value of c with respect to the speed of sound may be used in Equation 1. For example, the composition of the fluid contents in the conduit 650 may be determined separately (e.g., by spectral analysis as described below) to determine the relative amounts of various fluid components (e.g., blood, saline, air, etc.). A representative value of c for Equation 1 may be generated based on the composition of the fluid contents. For example, the representative value of c may be a weighted average of c for various fluid components in the conduit 650. As another example, a representative value of c may be determined based on a velocity lookup table for different types of fluids, different compositions of various fluid components (e.g., mixtures), or any suitable combination thereof. In other variations, a fixed representative value of c (e.g., an average of the speeds of sound for all expected fluid components of the fluid contents) may be used in Equation 1.

[0086] In another variation, Figure 6B As shown, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) includes one or more time-of-flight (ToF) ultrasonic flow meters. For example, the ToF flow meter may include two transducers, including an upstream transducer 630 and a downstream transducer 640 located on opposite sides of a conduit 650. The upstream transducer 630 may include a transmitter configured to transmit an ultrasonic beam to a receiver in the downstream transducer 640 (e.g., substantially along the flow direction). Conversely, the downstream transducer 640 may include a transmitter configured to transmit a second ultrasonic beam to a receiver in the upstream transducer 630 (e.g., substantially opposite to the flow direction). In other variations, the upstream and downstream transducers are located on the same side of the conduit 650, but direct the ultrasonic waves to acoustically reflective (e.g., acoustically reflective) surfaces on opposite sides of the conduit 650. The difference in travel time of ultrasonic waves propagating in the flow direction and against the flow direction may be analyzed to determine the flow rate of the fluid contents in conduit 650 .

[0087] In general, the flow velocity along the acoustic path of the ultrasound beam (which may be an approximation of the flow velocity along the flow direction) can be estimated based on the following formula 2:

[0088]

[0089] Where V = flow rate, L = distance between upstream and downstream transducers, t up = Transmission time in the upstream direction, t down = the transit time in the downstream direction, and φ = the relative angle between the transmitted ultrasonic beam and the direction of fluid flow.

[0090] In some variations, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) includes multiple types of ultrasonic flow meters. For example, the sensor arrangement may include at least one ultrasonic Doppler flow meter (e.g., similar to the above description of Fig. 6A ) and at least one ToF flow meter (e.g., similar to the flow meter described above with respect to Figure 6B Flowmeter described herein). The combination of the two ultrasonic flowmeters can, for example, expand the range of conditions under which flow rates can be measured. Typically, an ultrasonic Doppler flowmeter can detect and analyze ultrasonic waves reflected from particles or other different features in the fluid contents flowing in conduit 650 (e.g., blood cells, bubbles, overall turbulence of the fluid itself, or any suitable combination thereof). Under certain conditions (e.g., laminar flow of pure saline in the absence of particles), an ultrasonic Doppler flowmeter may provide less accurate measurements. On the other hand, a ToF flowmeter can detect and analyze ultrasonic waves transmitted in laminar flow without particles. Therefore, the combination of a Doppler flowmeter and a ToF flowmeter can achieve accurate flow rate measurements over a wider range of operating conditions, including turbulent and laminar flows and flows of fluids with and without particles.

[0091] Example Optical Flow Sensor

[0092] In other variations, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) includes one or more optical sensors configured to measure the flow rate of the fluid contents in a conduit (e.g., conduit 120, 250, 450, 550, or 650). Fig. 7AAs shown, the sensor arrangement may include an emitter array 710 and a detector array 720 generally located on opposite sides of the catheter 750. The emitter array 710 may include a series of optical emitters (e.g., LEDs), and the detector array 720 may include a series of optical detectors (e.g., CMOS sensors), with the opposing optical emitters and optical detectors forming a series of emitter-detector pairs. Each optical emitter is configured to emit light toward its corresponding optical detector so that the emitted light is transmitted through the fluid contents in the catheter 750. In some variations, at least some of the optical emitters may be configured to emit light of a predetermined wavelength based on the absorption characteristics of the substance of interest (e.g., blood or hemoglobin). For example, at least some of the optical emitters may be configured to emit light having a wavelength of about 532 nm so that the emitted light is optimized for maximum absorption by hemoglobin in the fluid contents in the catheter 750. Additionally or alternatively, in some variations, at least some of the optical emitters may be configured to emit a wide range of wavelengths (e.g., white light having a wide spectrum).

[0093] The intensity of the signal output by the optical detector can be used to distinguish between different fluid components of the fluid contents of the conduit 750 passing between the optical detector and its corresponding optical emitter. Fig. 7A In the example shown in FIG. 7 , three doses B1, B2, and B3 of a patient fluid (e.g., blood) are depicted flowing through a conduit 750 between an optical emitter and its corresponding optical detector (e.g., between emitter LED1 and corresponding detector PD1). The doses B1, B2, and B3 are interspersed with air. Figure 7B As shown, the signal intensity I from PD1 varies with time (t) as the dose and dispersed air pass through the conduit 750. Specifically, since the patient fluid absorbs the emitted light, a lower signal intensity corresponds to the passage of the patient fluid (e.g., doses B1, B2, and B3), while a higher signal intensity corresponds to the passage of air. Therefore, based on the signal intensity output by one or more optical detectors, patient fluids (such as blood) can be distinguished from air. In addition, in some variations, since different fluids can absorb different amounts of light, the type of non-air fluid (e.g., blood, saline, urine, etc.) can be identified based on the signal intensity from one or more optical detectors.

[0094] like Fig. 7AAs shown, at least some of the emitter-detector pairs are spaced axially along the catheter 750. For example, the second emitter-detector pair may be located downstream of the first emitter-detector pair. Specifically, the first emitter-detector pair may include a first optical emitter LED1 opposite to the first photodetector PD1, and the first photodetector PD1 is configured to detect light emitted by the first optical emitter LED1. Similarly, the second emitter-detector pair may include a second optical emitter LED2 opposite to the second photodetector PD2, and the second photodetector PD2 is configured to detect light emitted by the second optical emitter LED2. Since the second emitter-detector pair is located downstream of the first emitter-detector pair, the second photodetector PD2 detects the same segment of fluid contents after the first photodetector PD1 detects the same segment. This time offset between patient fluid detection events in the first photodetector PD1 and the second photodetector PD2 signals can be associated with the estimated flow rate between the first emitter-detector pair and the second emitter-detector pair by Equation 3:

[0095]

[0096] Where V = flow velocity, L = distance between the first emitter-detector pair and the second emitter-detector pair, and Δt = time offset between patient fluid detection events by the first optical detector and the second optical detector (e.g., photodetectors PD1 and PD2). Thus, the cross-correlation between photodetectors PD1 and PD2 can be used to measure flow velocity. In some embodiments, the addition of a third, fourth, or more axially spaced emitter-detector pairs can be used to supplement or increase accuracy or precision (e.g., by averaging cross-correlations of different groups of emitter-detector pairs), to verify flow velocity measurements (e.g., by checking for changes in time offset or redundancy), or both. The volume flow rate can then be estimated, for example, by multiplying the flow velocity V by the cross-sectional area A of the fluid in the catheter.

[0097] like Fig. 7AAs shown by the dotted lines in , the emitted light may be refracted when it is transmitted through certain media. To take into account this refraction problem and to be able to detect refracted light whose incident position on the detector is not directly opposite to its emission position, the optical detector in the emitter-detector pair can have a detection area that is wide enough, long enough, or both wide enough and long enough to capture the refracted light. For example, at least some of the optical detectors can be or be used as area sensors configured to detect light falling on a two-dimensional (e.g., rectangular) area, or can be linear sensors configured to detect light falling on a one-dimensional (e.g., linear) area. In addition, in some variations, the spectral characteristics of the fluid contents (e.g., as described below, determined by spectral analysis) can be used to quantify the refractive characteristics of the fluid contents (such as by a lookup table or a formula based on weighted values ​​of the spectral characteristics). Assuming that L in equation 3 above may be affected by the refraction of the fluid, the refractive value representing the refractive characteristics of the fluid contents can be used to dynamically adjust the value of L to account for the different compositions of the fluid passing through the conduit 750. Furthermore, in some variations, the type of fluid (e.g., blood, saline, urine, air, etc.) can be identified based on the incident position of the detected light relative to the emission position, as different fluids typically have different refractive indices.

[0098] In some variations, a sensor arrangement (e.g., sensor arrangement 110, 210, or 310) includes emitter-detector pairs arranged at a plurality of circumferential locations around a catheter (e.g., catheter 120, 250, 450, 550, 650, or 750). For example, Fig. 8A As shown, although the first emitter-detector pair (LED11, PD11) and the second emitter-detector pair (LED12, PD12) are located at the same approximate axial position, the first emitter-detector pair is circumferentially offset relative to the second emitter-detector pair. In some variations, in order to reduce interference between emitter-detector pairs located at the same approximate axial position, each emitter-detector pair at the axial position can operate at a different corresponding wavelength. For example, the optical emitter LED11 can be configured to emit only light of a first wavelength, and its corresponding photodetector PD11 can be configured to detect only light of the first wavelength. Similarly, the optical emitter LED12 can be configured to emit light of a second wavelength different from the first wavelength, and the photodetector PD12 can be configured to detect only light of the second wavelength.

[0099] In some variations, interference between axially aligned emitter-detector pairs may additionally or alternatively be reduced by alternating optical emitters and optical detectors. Fig. 9As shown, a set of three emitter-detector pairs (LED11, PD11), (LED12, PD12), and (LED13, PD13) can be arranged in an alternating manner (e.g., where two optical emitters are not directly adjacent to each other and two optical detectors are not directly adjacent to each other). Thus, for example, the photodetector PD11 in the first emitter-detector pair is unlikely to receive light from the optical emitter LED12 or the optical emitter LED13 from the second emitter-detector pair and the third emitter-detector pair, respectively. Thus, each optical detector will substantially only receive light emitted from its corresponding optical emitter.

[0100] Figure 8B shows a first emitter-detector pair and a second emitter-detector pair taken at the axial position Fig. 8A 850. When the cross-sectional area of ​​the conduit 850 is not completely filled with non-air fluid, the circumferentially distributed emitter-detector pairs can achieve measurement of the flow rate. For example, Figure 8B As shown, the conduit 850 may be only partially filled with a dose B of patient fluid (e.g., blood). In this illustrative example, the dose B does not traverse the entire distance between the first optical emitter LED11 and its corresponding first photodetector PD11, and the signal from the first photodetector PD11 may not be sufficient to reliably indicate the presence of the dose B. Therefore, as described above with respect to Fig. 7A and Figure 7B As described above, the first emitter-detector pair with the first photodetector PD11 may not be sufficient to facilitate reliable flow rate measurement. Figure 8B As shown, dose B does traverse the entire distance between the second optical emitter LED12 and its corresponding second photodetector PD12, so that the signal from the second photodetector PD12 can be used for flow rate measurement (e.g., alone or together with the output from at least one of the downstream emitter-detector pairs (LED21, PD21) and (LED22, PD22)). Therefore, even if the conduit 850 is only partially filled (e.g., half full), such circumferentially arranged emitter-detector pairs can achieve measurement of flow rate. It should be understood that more than two emitter-detector pairs (e.g., three, four, five, or any suitable number) can be arranged circumferentially around the conduit 850 to provide greater sensitivity to the presence of non-air fluid in the conduit.

[0101] Furthermore, in some variations, circumferentially arranged optical detectors may inform the distribution of fluid, the amount of fluid, or both at their shared axial location on conduit 850. For example, referring to Figure 8B, because dose B absorbs less light from the first optical emitter LED11 and more light from the second optical emitter LED12, the signal intensity from the first photodetector PD11 is higher than the signal intensity from the second photodetector PD12. Therefore, the relative signal intensities of the first photodetector PD11 and the second photodetector PD12 can indicate the distribution and amount of the patient fluid at the axial position of the first photodetector PD11 and the second photodetector PD12. For example, two orthogonally arranged emitter-detector pairs can detect whether the catheter is half full or completely full. More emitter-detector pairs can be arranged circumferentially around the catheter 850 (e.g., at the same axial position on the catheter 850) to provide higher resolution in the cross-sectional area of ​​the catheter 850 containing the fluid being measured.

[0102] As described above, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) can include optical emitter-detector pairs arranged at multiple axial locations along a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, or 850), arranged at multiple circumferential locations around the conduit, or arranged at multiple axial locations along a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, or 850) and at multiple circumferential locations around the conduit. For example, as Fig. 8A As shown, at least some of the plurality of emitter-detector pairs can be arranged in a series of axially spaced rings. As another example, at least some of the plurality of emitter-detector pairs can be arranged helically around the catheter. The helical arrangement can, for example, help avoid optical interference between adjacent emitter-detector pairs.

[0103] Example Thermal Mass Flow Sensor

[0104] In some variations, such as Fig.10 As shown, a sensor arrangement (e.g., sensor arrangement 110, 210, or 310) includes a thermal mass flow sensor 1010 configured to quantify the mass of fluid contents flowing through conduit 1050. For example, estimating the thermal mass flow of the fluid contents may include introducing a known amount of heat into the flow of the fluid contents and measuring a related (e.g., corresponding) temperature change in the fluid contents. For example, this may be performed by maintaining a probe at a constant temperature and measuring the energy consumed to do so. As another example, estimating the thermal mass flow of the fluid contents may include introducing a known amount of heat into the flow of the fluid contents and measuring a temperature change of the fluid contents at a point downstream.

[0105] For example, Fig.10As shown, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) may include at least a first temperature sensor TS1 and a second temperature sensor TS2 located downstream of the first temperature sensor TS1. The first temperature sensor TS1 and the second temperature sensor TS2 may be based on a micro-electromechanical system (MEMS), for example. One or more heat sources 1012 (such as a heating coil or other suitable heating element) may introduce a known amount of thermal energy into the fluid contents of the conduit 1050 between the first temperature sensor TS1 and the second temperature sensor TS2 (e.g., through the wall of the conduit 1050). Generally according to Equation 4, the temperature measurement difference between the first temperature sensor TS1 and the second temperature sensor TS2 caused by the heating of the fluid contents in the conduit 1050 may be related to the measurement result of the mass flow rate:

[0106]

[0107] Where, m = mass flow, K = conduit constant, C p = specific heat of the fluid contents of conduit 1050, T2 = temperature measurement by second temperature sensor TS2, and T1 = temperature measurement by first temperature sensor TS1. The value of K may be known or found based on characteristics of conduit 1050 (e.g., conduit material, conduit wall thickness, conduit diameter, etc.), or may be determined, for example, based on previous experimental data. The value of K may be manually entered (e.g., by a user), recorded in a computer-readable storage medium, received from a computer-readable storage medium, automatically recognized by system 100, such as by optical character recognition of a label or another suitable reference code on conduit 1050, or any suitable combination thereof. In some embodiments, the value of K may be derived from an optical or resistive sensor, wherein the output of the sensor may be used to determine the value of K (e.g., via a lookup table, formula, etc.). Multiple methods for determining the value of K may be combined (e.g., averaged) or used for redundancy purposes. The specific heat of the fluid contents of conduit 1050 may be known or assumed to be a constant value representing a known fluid passing through conduit 1050. However, in some embodiments, C p The value of may vary depending on other factors. For example, C p The value of may depend on the composition of the fluid contents (e.g., by taking a weighted average of the respective specific heat values ​​of each fluid component), which may be determined, for example, by spectral analysis, as described below. Once the composition of the fluid contents is determined, the value of C in Equation 4 may be determined using a lookup table, a heuristic derived formula, other suitable tools, or any suitable combination thereof. p The appropriate value of .

[0108] In some variations, one or more heat sources 1012 (e.g., heating coils or other heating elements) may be positioned on or near an outer surface of the conduit 1050. For example, the heating element may be mounted in a housing (e.g., housing 220) of a sensor arrangement (e.g., sensor arrangement 110, 210, or 310) such that when the conduit 1050 is housed in the housing, the conduit 1050 is self-aligned and contacts the heating element. In other variations, one or more heating elements may be integrated into the material of the conduit 1050 to more directly heat the fluid contents in the conduit 1050.

[0109] Despite Fig.10 Two temperature sensors (e.g., a first temperature sensor TS1 and a second temperature sensor TS2) are shown in FIG, but it should be understood that three, four, five or more temperature sensors may be included to measure thermal mass flow. For example, an array of temperature sensors (e.g., having one or more heating elements) may be arranged at multiple axial positions, arranged at multiple circumferential positions (e.g., in a series of rings, in a spiral manner, etc.), or arranged at multiple axial positions and at multiple circumferential positions. Similar to the arrangement of optical flow sensors described above, the combination of axial and circumferential arrangements of thermal mass flow sensors may enable averaging of thermal mass flow results, verification of thermal mass flow results, or both averaging of thermal mass flow results and verification of thermal mass flow results. In addition, such a combined arrangement may provide thermal mass flow measurements under a wider variety of filling conditions (e.g., when conduit 1050 is partially filled or fully filled).

[0110] In some variations, any of the above-described optical flow sensor arrangements and thermal mass flow sensor arrangements may be combined to enable quantification of flow under a wider range of conditions. For example, when the flow is intermittent (e.g., including a bolus of fluid dispersed in the air), the optical flow sensor may more accurately quantify the flow (e.g., estimate the flow rate) within a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, or 1050), while when the flow is continuous, the thermal mass flow sensor may more accurately quantify the flow (e.g., estimate the thermal mass flow). Thus, using an optical flow sensor and a thermal mass flow sensor together may enable accurate quantification of flow in a conduit across a wider range of flow conditions in the conduit (e.g., intermittent and continuous flow), making the system 100 robust despite unpredictable flow conditions. Furthermore, in some variations, the fluid contents may not need to be pre-conditioned to have predetermined characteristics (e.g., to move in laminar flow) in order for the system 100 to accurately quantify patient fluid loss.

[0111] Example Color Imaging Flow Sensor

[0112] In other variations, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) includes one or more image sensors configured to quantify the flow rate of fluid contents in a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, or 1050), estimate the composition or concentration of a component of the fluid contents, or both. For example, an optical image sensor (e.g., CCD, CMOS, etc.) can capture a color optical digital image of pixels having red, green, and blue (RGB) color components (e.g., and other suitable optical components). For example, the image sensor can be a single image sensor paired with suitable corresponding optics, filters (e.g., a color filter array, such as a Bayer pattern filter), or any suitable combination thereof. As another example, the sensor arrangement may include a plurality of image sensors paired with suitable corresponding optics (such as at least one prism or diffractive surface) to separate white light into separate color channels, each channel being detected by a respective image sensor (e.g., through a suitable filter corresponding to the color channel). However, the sensor arrangement may include any suitable image sensors and other optical components to enable the sensor arrangement to generate an image of the conduit and its fluid contents.

[0113] A machine learning algorithm (e.g., a neural network or other suitable algorithm) can be applied to the image data to distinguish different types of flows in a conduit (e.g., conduits 120, 250, 450, 550, 650, 750, 850, or 1050), such as laminar flow, turbulent flow, and air. For example, a machine configured according to such a machine learning algorithm can be trained using experimentally derived training data to classify the flow. The image of the fluid contents of the conduit can then be provided as input to a trained machine (e.g., a machine trained by inputting the training data into a machine learning algorithm). In some variations, the trained machine can analyze color component values ​​(e.g., RGB, CYMK, or other suitable color spaces) to determine conduit regions that may be air, laminar flow, turbulent flow, etc. By identifying features in the image of the fluid contents, the trained machine can additionally or alternatively quantify various aspects of the flow in the conduit (e.g., flow rate). Other example methods for characterizing the fluid in the conduit by analyzing a color image of the fluid are described in U.S. Patent Publication No. 2016 / 0335779, which is incorporated herein by reference.

[0114] Additionally or alternatively, the color component information can be related to the composition of the fluid contents. For example, the concentration of the fluid components of the fluid contents can be determined from the color component pixel values ​​using the method described in U.S. Patent No. 8,792,693, which is incorporated herein by reference above. In some variations, the same one or more color image sensors can be used to quantify the flow rate of the fluid contents (e.g., as described above) and estimate the aspects of the composition of the fluid contents. In some variations, a machine learning algorithm (e.g., a neural network or other suitable algorithm) can be applied to the image data to identify the fluid components of the composition of the fluid contents in the catheter (e.g., catheter 120, 250, 450, 550, 650, 750, 850 or 1050). For example, experimentally derived training data can be used to train a machine configured according to this machine learning algorithm. The image of the fluid contents of the catheter can then be provided as an input to a trained machine (e.g., by inputting the training data into the machine learning algorithm to train the machine). In some variations, the trained machine may analyze color component values ​​(e.g., RGB, CYMK, other suitable color spaces) to determine color-associated pixel values ​​associated with various fluid components (e.g., where the intensity of the red channel is used for pixels associated with blood). By identifying features in the image of the fluid contents, the trained machine may identify information about the relative amounts of fluid types within the catheter, the relative concentrations of fluid components, etc.

[0115] Example Multispectral Image Sensor

[0116] In some variations, the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) further includes one or more sensors configured to estimate the concentration of one or more fluid components of the fluid contents, other composition of the fluid contents of the conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, or 1050), or both. For example, Fig.11As shown, the sensor arrangement may include a multi-spectral imaging arrangement 1110, which includes a multi-spectral emitter array LEDc configured to emit light in a certain wavelength range and a multi-spectral detector array PDc configured to detect light in a certain wavelength range reflected by the fluid contents in the conduit 1150. For example, the multi-spectral emitter array LEDc, which may include LEDs or other suitable optical emitters, may be configured to emit light generally in the visible spectrum, near infrared spectrum, or in the visible and near infrared spectrum (e.g., emitting light generally having a wavelength between 400nm and 900nm). The multi-spectral emitter array LEDc may include a plurality of LEDs, each LED emitting light of a subset of a certain wavelength range (e.g., 400nm-450nm, 450nm-500nm, etc.), so that the emitter array LEDc collectively emits a suitable multi-spectral range. The multi-spectral detector array PDc, which may include a CMOS sensor or other suitable image sensor, may also be configured to detect light generally in the visible spectrum, infrared spectrum, or in the visible and infrared spectrum. For example, the multi-spectral detector array PDc may include a plurality of CMOS sensors, each CMOS sensor having a corresponding filter such that each CMOS sensor detects only light of wavelengths allowed by the filter. In an example embodiment, the multi-spectral imaging arrangement 1110 includes about 10 to about 100 LEDs (e.g., in the emitter array LEDc) and about 10 to 100 CMOS sensors (e.g., in the detector array PDc). Each LED may emit light of a corresponding discrete wavelength range and may have a corresponding CMOS sensor that detects light of the same wavelength range.

[0117] Various aspects of the composition of the fluid contents can be measured by analyzing the detector signals from the multi-spectral imaging arrangement 1110 in spectral analysis. Specifically, since different types of substances absorb or reflect light of different wavelengths, the spectral pattern measured by the multi-spectral detector array PDc can be analyzed to characterize the composition of the fluid contents. In some variations, the relative amount (e.g., concentration) of the type of fluid present (e.g., blood, urine, saline, etc.) can be determined by analyzing the signals from the detector array PDc. For example, blood typically has an absorption spectrum peak of about 530nm. Therefore, the signal from the sensor in the multi-spectral detector array PDc that detects 530nm light can be related to the amount of blood in the catheter 1150. As another example, urine typically has an absorption spectrum peak of about 430nm, so that the signal from the sensor in the multi-spectral detector array PDc that detects 430nm light can be related to the amount of urine in the catheter 1150. In some variations, the signal from the multi-spectral detector array PDc can be processed by spectral analysis to determine the concentration of fluid components (e.g., hemoglobin) and other fluid components in the fluid contents. Furthermore, in some variations, the same sensor signal may be processed by spectral analysis to determine the level of hemolysis, thereby obtaining a measure of the amount of whole blood relative to hemolysis.

[0118] For a fluid having multiple fluid components in the conduit 1150, the unscattered absorbance of each of the total n fluid components (n=1, 2, 3, ...) may be summed to provide a total absorbance ΣA, which may be directly measured at different wavelengths by the multi-spectral imaging arrangement 1110, for example according to Equation 5:

[0119]

[0120] Among them, ∈ i (λ) is the absorbance (known for many substances), c i is the concentration (to be determined), and d i is the optical path length of each fluid component in the conduit 1150. By measuring the total absorbance of light at n or more wavelengths, the system 100 can determine the concentration of each constituent fluid component of the fluid contents in the conduit 1150, such as according to Equation 6:

[0121]

[0122] Therefore, all fluid component concentrations may be estimated by placing Equation 6 above into matrix form and performing mathematical operations on the matrix (eg, by obtaining a least squares estimate).

[0123] Other variations of the sensor arrangement (e.g., sensor arrangement 110, 210, or 310) include any suitable combination of the above sensors (e.g., ultrasound, optical, thermal, color images, and multispectral images) that can be used to quantify the flow of fluid contents through a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, 1050, or 1150), estimate the composition of fluid contents (e.g., estimate fluid component concentration), or quantify the flow of fluid contents through a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, 1050, or 1150), estimate the composition of fluid contents (e.g., estimate fluid component concentration). For example, the analysis of data from multiple sensors can be averaged or otherwise combined in a fusion algorithm to improve accuracy. In addition, the use of multiple sensors can provide redundancy so that, for example, a failure of one sensor may not render the system 100 inoperable. As another example, as described above in some examples, multiple measurement modes can improve measurement sensitivity, reliability, or both sensitivity and reliability over a wider range of flow conditions (e.g., turbulent or laminar flow, continuous or intermittent, mixed fluid types, etc.). Additionally, in some variations, as described above, a single sensor arrangement (e.g., a color image sensor arrangement) can provide sufficient data to enable quantification of flow rate and estimation of concentration of one or more fluid components.

[0124] Example Processor and Example Memory Components

[0125] In general, system 100 may include one or more processors configured to execute instructions stored in a memory so that when one or more processors execute instructions, one or more processors perform various aspects of the methods described herein. For example, one or more processors may be configured to quantify the flow of fluid contents through a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, 1050, or 1150), estimate the concentration of fluid components in a patient's fluid, characterize patient fluid loss based at least in part on the quantified flow and concentration of fluid components, or any suitable combination thereof. In addition, other aspects of data analysis may be performed by one or more processors.

[0126] In an example variation, the system 100 estimates the amount of patient blood that has been collected and passed through the catheter based at least in part on the above-mentioned sensor measurements. For example, the mass of hemoglobin that has passed through the catheter during the measurement time period can be estimated by multiplying the blood volume flow rate through the catheter by the hemoglobin concentration in the catheter measured during the measurement time period. The volume flow rate of blood can be determined based on the total flow rate (e.g., quantified by one or more of the above-mentioned sensors) and the relative amount of blood compared to other fluid types in the catheter (e.g., analyzed by spectroscopy or optical analysis as described above). As described above, the concentration of hemoglobin can be measured by spectroscopy or optical analysis. In addition, the patient's blood loss can be estimated by dividing the estimated hemoglobin mass loss by the known serum-derived patient hemoglobin value. The patient's blood loss during the measurement time period estimated in multiple measurement time periods can be aggregated into the total blood loss of the running patient and aggregated with other estimates based on other fluid collection sources (such as surgical textiles described above), or both. As described in further detail below, such a measure of patient blood loss can be indicated to a user, such as by a display or audio device. In some variations, the estimated hemoglobin mass can itself be a measure of fluid loss indicative of the patient. In addition, in some variations, any of the methods described herein can be applied to determine the concentration and flow rate of other body fluids (e.g., urine, amniotic fluid, cerebrospinal fluid, bile) passing through a catheter. As described above, the values ​​measured over multiple measurement time periods can be aggregated into a running total amount of fluid loss, or the measured values ​​can be aggregated with other estimates based on other fluid collection sources, or both.

[0127] Reference again Figure 1 , one or more processors 154 may be located, for example, in a computing device 150, which may be a remote computing device relative to the sensor arrangement 110. Fig.18 An example of one or more processors 154 is further described. Computing device 150 may be or include a handheld or mobile device (e.g., a tablet computer, a laptop computer, a mobile smart phone, etc.). The instructions discussed above may be executed, for example, by a computer executable component integrated with an application, an applet, a host, a server, a network, a website, a communication service, a communication interface, a hardware element, a firmware element, a software element, a wristband, a smart phone, or any suitable combination thereof. In some example embodiments, the instructions may be executed at least in part by one or more processors separate from computing device 150 (e.g., on-site in an operating room or remotely outside an operating room), such as by a cloud-based computer system, a mainframe computer system, a grid computer system, or other suitable computer system.

[0128] The instructions may be stored in the memory 152 of the computing device 150 or in other computer-readable media, such as RAM, ROM, flash memory, EEPROM, optical devices (e.g., CD or DVD), hard drive, floppy drive, or any suitable storage device. Fig.18 Examples of memory 152 are described further below. Additionally or alternatively, one or more processors may be located in or near the sensor arrangement 100 to perform local analysis.

[0129] In addition, the sensor data, the results of any analysis performed by the local processor at the sensor arrangement 110, or both, can be communicated to a remote computing device (such as a Figure 1 In some variations, one or more local memory components may be included in the sensor arrangement 110 to store a queue or backlog of such data, similar to those described above. The queue or backlog may, for example, provide a buffer of stored data to avoid data loss in the event that data transfer to the computing device 150 is interrupted or otherwise fails.

[0130] Example User Interaction Widgets

[0131] In some variations, such as Figure 1 As shown, the system 100 may also include one or more displays 148 configured to display data, analysis of the data (e.g., an estimate of patient fluid loss), or both display data and analysis of the data to the user. The display 148 may include a screen on a handheld or mobile device (e.g., as part of the computing device 150 identical to the one or more processors 154 described above), a computer monitor, a television screen, a projector screen, or other suitable display. In some variations, the display 148 is configured to display a user interface (e.g., a graphical user interface) that enables a user to enter information (e.g., serum-derived patient hemoglobin values ​​or catheter information, such as brand, material, size, wall thickness, etc. that can be used to calibrate the system 100 to a specific catheter type), select display options (e.g., fonts, colors, languages, etc.), display content (e.g., patient information, fluid-related information, alarms, etc.), or any suitable combination thereof. In such variations, the display 148 may be user-interactive and include a resistive or capacitive touch screen that responds to skin, stylus, or other user contact. In other variations, display 148 may be user interactive via a cursor controlled by a mouse, keyboard, or other suitable input device.

[0132] In some variations, the system 100 may additionally or alternatively include an audio system 156 configured to convey information to the user (e.g., fluid-related information, warnings, etc.). For example, the display 148, the audio system 156, or both may provide a warning or alarm when an estimated amount of fluid loss trend reaches a threshold, which may be useful to prompt certain responsive actions (such as providing a transfusion to the patient).

[0133] For the purpose of illustration, the description herein uses specific terms to provide a thorough understanding of the subject matter. However, it will be apparent to those skilled in the art that specific details are not required to practice the subject matter. Therefore, the description of the specific example embodiments (e.g., variants or modifications) of the subject matter is for the purpose of illustration. They are not intended to be exhaustive or limit the subject matter to the exact form disclosed, because in view of the above teachings, many modifications and variations are possible. The example embodiments described herein explain the innovation involved and its practical application, and they thus enable other persons skilled in the art to utilize the subject matter and its various example embodiments and various modifications suitable for the intended specific use.

[0134] Example system module

[0135] Fig.12 Flowchart showing the operation of system 100 for performing a method 1200 for characterizing fluid contents flowing through a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, 1050, or 1150) according to some example embodiments. In such example embodiments, images (e.g., video images) of fluid contents flowing through a conduit are captured by an optical sensor (e.g., a camera) and input into an optical mass flow algorithm 1210, which is shown to include fluid motion tracking, followed by fluid mass estimation. The output of optical mass flow algorithm 1210 is processed by optical mass flow calibration operation 1220, and the resulting output is provided to sensor combination operation 1240.

[0136] In a separate path, the image of the fluid contents is also provided as an input to a video classifier 1230, which can be configured to distinguish laminar flow from non-laminar flow. The output of the video classifier 1230 is also provided to a sensor combination operation 1240. Additionally, the output of the video classifier 1230 can be used as an input to an optical hemoglobin concentration detector 1250, the output of which is fed to the sensor combination operation 1240.

[0137] Additionally, sensor data from the ultrasound sensor is accessed and provided as input to ultrasound calibration operation 1215, and the resulting output is fed as input to optical hemoglobin concentration detector 1250. Output from optical hemoglobin concentration detector 1250 is provided to sensor combination operation 1240, as described above.

[0138] Thus, the sensor combination operation 1240 combines its inputs to obtain the concentration of a fluid component (e.g., hemoglobin) of a patient fluid (e.g., blood) contained in the fluid contents flowing through the conduit. In addition, using combined inputs based on multiple types of sensor data (e.g., video data and ultrasound data), the sensor combination operation 1240 outputs accurate results under various flow conditions of the fluid contents in the conduit. Examples of such conditions include regions of continuous flow, regions of discontinuous flow (e.g., intermittent flow or other irregular flow), regions of laminar flow, and regions of turbulent flow, and any suitable combination thereof.

[0139] Fig.13 is a diagram illustrating motion tracking of fluid contents according to some example embodiments. Fig.13 As shown, as the fluid contents pass through the catheter, light attenuation due to absorption results in optical markers that can be tracked using one or more optical sensors placed along the catheter to determine the movement of the moving fluid in pixels / second.

[0140] Thus, the system 100 may include a feature extraction module (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof) that is or includes an algorithm module that is configured to access a digital signal from an optical sensor or an optical measurement pattern as input and return a set of digital signals representing one or more unique features of the fluid for algorithmic analysis.

[0141] The feature extraction module extracts unique features in the moving fluid. The extractable features include, but are not limited to: (i) moving fluid head, (ii) moving fluid tail, (iii) moving bubbles, (iv) other moving patterns or gradients, and (v) other spatial or temporal clues to the motion (e.g., texture associated with the motion, temporal changes relative to spatial changes, blur, etc.).

[0142] In some variants, the feature extraction module extracts features in a two-dimensional (2D) space by calculating the difference of two consecutive optical sensor data in time order. The extracted 2D differential features are further classified into subcategories using a computer vision algorithm or other machine learning algorithm (e.g., a deep learning algorithm).

[0143] In certain variations, the feature extraction module extracts features in a one-dimensional (1D) space by rearranging the 2D digital data into 1D digital data before performing differential feature extraction and classification.

[0144] In some variants, the feature extraction module extracts features in a multidimensional space by processing multiple digital data from more than one source. Multidimensional features (such as three-dimensional (3D) features) will be extracted and classified by computer vision algorithms or other variants of machine learning algorithms.

[0145] In some variations, the feature extraction module uses a deep learning model to classify and segment features from the optical sensor output.

[0146] Fig.14 Flowchart showing a method for performing logical operations in characterizing the contents of a fluid flowing through a conduit according to some example embodiments. Although the method is described as being performed by the system 100 as an example, the method may be performed by other hardware configurations. Thus, the system 100 may include a fluid displacement estimation module (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof), the fluid displacement estimation module being an algorithm module or including an algorithm module configured to access the extracted features and calculate the displacement of the fluid from one time point to another time point.

[0147] In some variations, the fluid displacement estimation module utilizes a mathematical method to calculate the displacement of each extracted feature from different time stamps. Cross-correlation or any other similar mathematical method is used to calculate the shift in pixels / second for a given feature.

[0148] In some variations, the fluid displacement estimation module deploys a deep learning model to estimate fluid displacement from one or more optical sensors.

[0149] The system 100 may also include (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof) a fluid motion model module that is or includes an algorithm module configured to estimate the flow rate of fluid contents when there are no strong features to track during fluid flow (such as during laminar flow or continuous patches of fluid flow).

[0150] When the fluid displacement module does not output credible results, such as during laminar flow, where there are few or no obvious features for mathematical calculations, the fluid motion model module interpolates the motion of the fluid contents. The fluid motion model module estimates displacement relative to past fluid characteristics, future fluid characteristics (e.g., predicted fluid characteristics), or both.

[0151] In some variations, the fluid motion model module is controlled by internal parameters including, but not limited to, cross-correlation strength, feature size, and fluid occupancy. Fig.14 As shown, the fluid motion model module traverses multiple logic boxes (e.g., box 1, box 2, box 3, box 4, box 5 and box 6, or any suitable subset thereof) to determine the confidence of the estimate of the fluid displacement estimation module and to re-estimate the fluid displacement using past and future (e.g., predicted) events.

[0152] In box 1, according to some example embodiments, a decision 1410 (e.g., a first decision) is made to determine whether a different fluid pressure head exists. If so, the start of the fluid block is indicated by the fluid pressure head. Otherwise, no fluid pressure head exists, and the fluid motion model will continue to box 2.

[0153] In block 2, according to some example embodiments, a decision 1420 (e.g., a second decision) is made to determine whether a distinct fluid tail exists. If so, the end of the fluid block is indicated by the fluid tail. Otherwise, no fluid head or fluid tail exists, and the fluid motion model will proceed to block 3.

[0154] In block 3, according to some example embodiments, a decision 1430 (e.g., a third decision) is made to determine if a different correlation result exists. If so, the fluid motion model proceeds to block 4. Otherwise, in the absence of a fluid head or fluid tail, and in the absence of a different correlation result, the fluid type is classified to distinguish between laminar flow and no flow.

[0155] In box 4, according to some example embodiments, a decision 1440 (eg, a fourth decision) is made to determine whether to accept the different correlation results. If accepted, the fluid displacement is indicated by the correlation results. Otherwise, the fluid motion model will proceed to box 5.

[0156] In block 5, according to some example embodiments, a decision 1450 (e.g., a fifth decision) is made to determine whether an extreme case (e.g., an anomaly, an error, or other particularly exceptional case) exists. If so, the fluid displacement is indicated by an adjacent image (e.g., the next or previous video image in a sequence of video images depicting the fluid contents in the catheter). Otherwise, the fluid motion model proceeds to block 6.

[0157] In block 6, according to some example embodiments, a decision 1460 (e.g., a sixth decision) is made to determine whether there is extremely slow motion of the fluid contents (e.g., an apparent displacement below a detection threshold). If there is extremely slow motion, the fluid displacement is treated as no flow (e.g., zero displacement from image to image or displacement below a threshold amount from image to image) by the fluid motion model. Otherwise, the fluid displacement is indicated by an adjacent image (e.g., a next or previous video image in a series of video images depicting the fluid contents in the catheter), which may show more discernible apparent displacement than the current image.

[0158] Fig.15 is a graph illustrating optical quality estimation for fluid contents according to some example embodiments.

[0159] The system 100 may include an optical quality estimation module (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof) that is an algorithm module or includes an algorithm module configured to analyze a substance to be detected in the fluid content when the fluid content passes through a conduit (e.g., conduit 120, 250, 450, 550, 650, 750, 850, 1050, or 1150) paired with a sensor arrangement (e.g., sensor arrangement 110, 210, or 310) with an optical sensor (e.g., CMOS or CCD) and an LED. The substance to be detected may be a fluid component of the fluid content, and the fluid component may be a homogeneous fluid or a heterogeneous fluid, or may have other fluid characteristics.

[0160] Assembly of the optical quality estimation module may generally include placing one or more LEDs or other light sources having different intensities, wavelengths, orientations, or any suitable combination thereof at one end of a conduit segment (e.g., conduit segment 350) and placing one or more photodetectors or other optical sensors having the same or different configurations at the other end of the conduit segment. The optical quality estimation module may first measure absorbance or transmittance, and then analyze the target substance using physical principles (e.g., estimating the concentration of the substance being measured by applying Beer Lambert's Law given the transmittance of the substance being measured).

[0161] In some variations, multiple pairs of light sources and optical sensors are utilized. For each optical sensor looking toward a catheter segment (e.g., catheter segment 350), the light sources are placed at 180 degrees at opposite sides of the catheter segment. The optical quality estimation module estimates the amount of light absorbed by the fluid contents of a region of interest entering a catheter segment (which may be referred to as a differential segment). The optical quality estimation module uses a motion tracking algorithm to determine the length of the differential segment, quantify the average absorbance in the differential segment, and apply mathematical derivation based on Beer-Lambert's law.

[0162] A(δV)=a(λ)dc(δV)∝δm2(t) (7) Where A is the absorbance we calculated, δV = πd 2 δp is the differential volume, and δp is the differential segment length. The system 100 uses the Beer-Lambert law to express the absorbance as the absorbance of the substance being measured a(λ) multiplied by the path length d multiplied by the concentration c of the substance being measured in the fluid.

[0163] The optical quality estimation module then multiplies the calculated absorbance by the length (in pixels) of the difference segment to obtain an optical quality estimate in arbitrary units (au) for each frame. The optical quality estimation module also integrates the optical quality estimate for each frame to obtain a time-varying optical quality estimate in arbitrary units (au).

[0164] In some variations, the optical quality estimation module also utilizes one or more combinations of LEDs or other light sources, optical sensors, and catheter types to estimate the optical quality of the material being measured.

[0165] Fig.16 is a graph illustrating estimation of fluid component concentration based on particle scattering, according to some example embodiments.

[0166] The system 100 may include a fluid scattering estimation module (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof) that is or includes an algorithm module configured to determine the presence of scattering particles, which determination may be performed as part of estimating the hemoglobin concentration at different hemolysis levels in the blood that cause changes in the scattering parameters.

[0167] The fluid scattering estimation module utilizes a special heterogeneous illumination component to eliminate the scattering and absorption parameters of the fluid content.

[0168] In some embodiments, heterogeneous illumination is achieved by (i) spacing the LEDs or other light sources a certain distance apart, (ii) using structured LEDs or other light sources, or (iii) creating a custom structured light source by passing uniform light through a structured grating. Heterogeneous illumination may produce brighter patches and darker patches when viewed with an optical sensor. The fluid scattering estimation module analyzes the signal difference between the brighter patches and the darker patches to estimate (e.g., in conjunction with a computer vision algorithm or other machine learning algorithm, such as a deep learning algorithm) scattering parameters of the fluid contents.

[0169] In some variations, different types of catheters are used to create structural differences in the irradiation.

[0170] The system 100 may include an optical mass calibration module (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof) that is or includes an algorithm module configured to convert measurements from the optical sensor into a concentration or mass of a measured substance.

[0171] The measurements from the optical sensor (eg, video sensor) are expressed in arbitrary units, and the resulting information is converted to obtain various unique characteristics of the fluid contents, such as the concentration of a fluid component of the fluid contents or the mass of the fluid component.

[0172] In some variations, the optical quality calibration module converts the optical quality to the mass of the substance being measured (e.g., a fluid component of interest, such as blood) through a trained mathematical model. The learning machine is trained with the mathematical model by calibrating the differential optical quality against any ground truth measurements (e.g., using a scale). For each substance being measured, the learning machine can be trained with one or more data sets with different concentration combinations.

[0173] In some variations, the optical quality calibration module converts the optical quality into the concentration of the substance being measured (e.g., the fluid component of interest) through a trained mathematical model. The mathematical model can be trained through machine learning (e.g., using a deep learning algorithm).

[0174] The system 100 may include (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof) a fluid type classification module that is or includes an algorithm module configured to classify fluid contents (e.g., determine the fluid type of the fluid contents) within a given time range.

[0175] The fluid type classification module automatically classifies different fluid contents with different characteristics based on the output of the sensor arrangement or other measurement mode. Supplementary algorithm logic can be used to perform classification at any given time frame.

[0176] In some variations, the fluid type classification module classifies laminar flow and non-laminar flow from the optical sensor.

[0177] Fig.17 is a diagram illustrating a mathematical merging of results from various types of sensors according to some example embodiments.

[0178] The system 100 may include a sensor merging module (e.g., within the sensor arrangement 110, the computing device 150, or any suitable combination thereof), which is an algorithm module or includes an algorithm module configured to combine measurement results of the substance being measured between different sensors (e.g., using different measurement modes).

[0179] In order to maximize the advantages of different sensors with different characteristics, a mathematical combining function is used to assign importance weights to the different types of sensors. The mathematical combining function is derived from the characteristics and conditions of the fluid contents.

[0180] In some variations, the sensor merging module combines measurements between the ultrasonic sensor and the optical sensor using a merging function derived from the fluid type classification module and weights regarding the accuracy of the different sensors under different fluid conditions.

[0181] Any one or more components (e.g., modules) described herein can be implemented using separate hardware (e.g., one or more processors) or a combination of hardware and software. For example, any component described herein can physically include an arrangement of one or more processors, which are configured to perform the operations described herein about the component. As another example, any component described herein can include software, hardware, or both software and hardware that configure the arrangement of one or more processors to perform the operations described herein about the component. Therefore, the different components described herein can include and configure different arrangements of processors at different time points or a single arrangement of these processors at different time points. Each component described herein (e.g., module) is an example of a device for performing the operations described herein about the component. Moreover, any two or more components described herein can be combined into a single component, and the functions described herein about a single component can be subdivided between multiple components. In addition, according to various example embodiments, the components described herein as being implemented in a single system or machine (e.g., a single device) can be distributed on multiple systems or machines (e.g., multiple devices).

[0182] Any system or machine (e.g., apparatus) discussed herein may be, include, or otherwise be implemented in a special-purpose (e.g., special-purpose or other non-conventional and non-general-purpose) computer that has been modified to perform one or more of the functions described herein for the system or machine (e.g., configured or programmed by special-purpose software (e.g., one or more software modules such as a special-purpose application, operating system, firmware, middleware, or other software program)). For example, the following reference Fig.18 Discussion can realize the special-purpose computer system of any one or more methods in the method described herein, and such special-purpose computer can be the device for performing any one or more methods discussed herein accordingly.In the technical field of such special-purpose computer, compared with other special-purpose computers that lack the structure discussed herein or otherwise cannot perform the function discussed herein, the special-purpose computer that has been modified (for example, configured by special software) by the structure discussed herein to perform the function discussed herein has been improved technically.Therefore, the technology of similar special-purpose machine is provided to be improved according to the special-purpose machine of the system and method configuration discussed herein.In addition, any two or more systems or machines discussed herein can be combined into a single system or machine, and the function described herein for any single system or machine can be subdivided between multiple systems or machines.

[0183] Fig.18 1 is a block diagram illustrating components of a machine 1800 (e.g., computing device 150) capable of reading instructions 1824 from a machine-readable medium 1822 (e.g., a non-transitory machine-readable medium, a machine-readable storage medium, a computer-readable storage medium, or any suitable combination thereof) and performing, in whole or in part, any one or more of the methods discussed herein, according to some example embodiments. Specifically, Fig.18 Machine 1800 is shown in the example form of a computer system (e.g., a computer) in which instructions 1824 (e.g., software, programs, applications, applet, app, or other executable code) for causing the machine 1800 to perform any one or more of the methodologies discussed herein may be executed in whole or in part within the machine 1800.

[0184] In alternative embodiments, the machine 1800 operates as a standalone device, or can be communicatively connected (e.g., networked) to other machines. In a networked deployment, the machine 1800 can operate in the capacity of a server machine or a client machine in a server-client network environment, or as a peer machine in a distributed (e.g., peer-to-peer network) environment. The machine 1800 can be a server computer, a client computer, a personal computer (PC), a tablet computer, a laptop computer, a netbook, a cellular phone, a smart phone, a set-top box (STB), a personal digital assistant (PDA), a Web appliance, a network router, a network switch, a bridge, or any machine capable of sequentially or otherwise executing instructions 1824 specifying the actions to be taken by the machine. In addition, although only a single machine is shown, the term "machine" should also be considered to include any collection of machines that execute instructions 1824 individually or collectively to perform all or part of any one or more methods discussed herein.

[0185] The machine 1800 includes a processor 1802 (e.g., one or more central processing units (CPUs), one or more graphics processing units (GPUs), one or more digital signal processors (DSPs), one or more application specific integrated circuits (ASICs), one or more radio frequency integrated circuits (RFICs), or any suitable combination thereof), a main memory 1804, and a static memory 1806, which are configured to communicate with each other via a bus 1808. The processor 1802 includes a solid-state digital microcircuit (e.g., electronic, optical, or electronic and optical) that can be temporarily or permanently configured by some or all of the instructions 1824, so that the processor 1802 can be configured to perform any one or more of the methods described herein in whole or in part. For example, a set of one or more microcircuits of the processor 1802 can be configured to execute one or more modules (e.g., software modules) described herein. In some example embodiments, processor 1802 is a multi-core CPU (e.g., a dual-core CPU, a quad-core CPU, an 8-core CPU, or a 128-core CPU), wherein each of the multiple cores behaves as an independent processor that is capable of performing, in whole or in part, any one or more of the methods discussed herein. Although the benefits described herein may be provided by a machine 1800 having at least processor 1802, if a different type of machine that does not include a processor is configured to perform one or more of the methods described herein, the same benefits may also be provided by these processor-free machines (e.g., a pure mechanical system, a pure hydraulic system, or a hybrid mechanical hydraulic system).

[0186] The machine 1800 may also include a graphics display 1810 (e.g., a plasma display panel (PDP), a light emitting diode (LED) display, a liquid crystal display (LCD), a projector, a cathode ray tube (CRT), or any other display capable of displaying graphics or video). The machine 1800 may also include an alphanumeric input device 1812 (e.g., a keyboard or keypad), a pointing input device 1814 (e.g., a mouse, a touch pad, a touch screen, a trackball, a joystick, a stylus, a motion sensor, an eye tracking device, a data glove, or other pointing tool), a data storage 1316, an audio generation device 1318 (e.g., a sound card, an amplifier, a speaker, a headphone jack, or any suitable combination thereof), and a network interface device 1820.

[0187] The data store 1316 (e.g., a data storage device) includes a machine-readable medium 1822 (e.g., a tangible and non-transitory machine-readable storage medium) on which are stored instructions 1824 that implement any one or more of the methods or functions described herein. The instructions 1824 may also reside, in whole or in part, in the main memory 1804, in the static memory 1806, in the processor 1802 (e.g., in a cache of the processor), or any suitable combination thereof before or during execution by the machine 1800. Thus, the main memory 1804, the static memory 1806, and the processor 1802 may be considered to be machine-readable media (e.g., tangible and non-transitory machine-readable media). The instructions 1824 may be sent or received over the network 1890 via the network interface device 1820. For example, the network interface device 1820 may communicate the instructions 1824 using any one or more transmission protocols (e.g., Hypertext Transfer Protocol (HTTP)).

[0188] In some example embodiments, the machine 1800 may be a portable computing device (e.g., a smartphone, a tablet computer, or a wearable device), and may have one or more additional input components 1830 (e.g., sensors or gauges). Examples of such input components 1830 include image input components (e.g., one or more cameras), audio input components (e.g., one or more microphones), direction input components (e.g., a compass), location input components (e.g., a global positioning system (GPS) receiver), orientation components (e.g., a gyroscope), motion detection components (e.g., one or more accelerometers), altitude detection components (e.g., an altimeter), temperature input components (e.g., a thermometer), and gas detection components (e.g., a gas sensor). Input data collected by any one or more of these input components 1830 may be accessed and used by any module described herein (e.g., implementing appropriate privacy notices and protections, such as opt-in or opt-out consent, based on user preferences, applicable regulations, or any appropriate combination thereof).

[0189] As used herein, the term "memory" refers to a machine-readable medium capable of storing data temporarily or permanently, and may be considered to include, but is not limited to, random access memory (RAM), read-only memory (ROM), buffer memory, flash memory, and cache. Although the machine-readable medium 1822 is shown as a single medium in the example embodiment, the term "machine-readable medium" should be considered to include a single medium or multiple media (e.g., a centralized or distributed database or associated caches and servers) capable of storing instructions. The term "machine-readable medium" should also be considered to include any medium or combination of multiple media capable of carrying (e.g., storing or conveying) instructions 1824 for execution by the machine 1800 so that the instructions 1824, when executed by one or more processors (e.g., processor 1802) of the machine 1800, cause the machine 1800 to perform, in whole or in part, any one or more of the methods described herein. Therefore, "machine-readable medium" refers to a single storage device or apparatus, as well as a cloud-based storage system or storage network including multiple storage devices or apparatuses. Accordingly, the term "machine-readable medium" shall be taken to include, but is not limited to, one or more tangible and non-transitory data storage repositories (e.g., data volumes) in the example form of solid-state memory chips, optical disks, magnetic disks, or any suitable combination thereof.

[0190] As used herein, "non-transitory" machine-readable media specifically excludes propagating signals per se. According to various example embodiments, instructions 1824 for execution by machine 1800 may be communicated via a carrier medium (e.g., a machine-readable carrier medium). Examples of such carrier media include non-transitory carrier media (e.g., non-transitory machine-readable storage media such as solid-state memory that can be physically moved from one location to another) and transient carrier media (e.g., a carrier wave or other propagating signal that conveys instructions 1824).

[0191] The various operations of the example methods described herein may be performed at least in part by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions described herein. As used herein, "processor-implemented modules" refers to hardware modules in which the hardware includes one or more processors. Therefore, since the processor is an example of hardware, the operations described herein may be at least partially implemented by a processor, implemented by hardware, or implemented by a processor and hardware, and at least some of the operations in any one or more of the methods discussed herein may be performed by one or more processor-implemented modules, hardware-implemented modules, or any suitable combination thereof.

[0192] In addition, such one or more processors may perform operations in a "cloud computing" environment or as a service (e.g., in a "software as a service" (SaaS) implementation). For example, at least some of the operations in any one or more of the methods discussed herein may be performed by a group of computers (e.g., as an example of a machine including a processor), and these operations may be accessed via a network (e.g., the Internet) and accessed via one or more appropriate interfaces (e.g., application program interfaces (APIs)). The performance of certain operations may be distributed among one or more processors, either resident only in a single machine, or deployed across multiple machines. In some example embodiments, one or more processors or hardware modules (e.g., modules implemented by a processor) may be located in a single geographic location (e.g., in a home environment, an office environment, or a server farm). In other example embodiments, one or more processors or hardware modules may be distributed in multiple geographic locations.

[0193] Throughout the specification, multiple instances can be implemented as parts, operations or structures described as single instances. Although the individual operations of one or more methods are shown and described as individual operations, one or more individual operations can be performed simultaneously, and it is not necessary to perform the operations in the order shown. The structure and function thereof represented as individual parts and functions in the example configuration can be implemented as a combined structure or parts with combined functions. Similarly, the structure and function presented as a single part can be implemented as individual parts and functions. These and other variations, modifications, additions and improvements fall within the scope of this paper theme.

[0194] Some parts of the subject matter discussed herein can be presented in the form of an algorithm or symbolic representation of the operation of data stored in a memory (e.g., a computer memory or other machine memory) as a bit or binary digital signal. Such an algorithm or symbolic representation is an example of a technology used by ordinary technicians in the field of data processing to convey the essence of their work to other technicians in the field. As used herein, an "algorithm" is a self-consistent sequence of operations or similar processes that lead to a desired result. In this case, the algorithm and operation involve the physical manipulation of physical quantities. Usually, but not necessarily, such a quantity can take the form of an electrical, magnetic or optical signal that can be stored, accessed, transmitted, combined, compared or otherwise manipulated by a machine. Mainly for general purposes, it is sometimes convenient to use words such as "data", "content", "bit", "value", "element", "symbol", "character", "term", "number", "numerical value", etc. to refer to such signals. However, these words are only convenient labels and should be associated with appropriate physical quantities.

[0195] Unless expressly stated otherwise, the discussion herein uses words such as "access," "process," "detect," "computing," "calculating," "determine," "generate," "present," "display," and the like to refer to an action or process performed by a machine (e.g., a computer) that manipulates or transforms data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, nonvolatile memory, or any suitable combination thereof), registers, or other machine components that receive, store, transmit, or display information. In addition, unless expressly stated otherwise, as is common in patent literature, the terms "a" or "an" herein include one or more than one instance. Finally, unless expressly stated otherwise, as used herein, the conjunction "or" refers to a non-exclusive "or."

[0196] The following enumerated description describes several examples of the methods, machine-readable media, and systems (eg, machines, apparatuses, or other devices) discussed herein.

[0197] A first example provides a method for characterizing patient fluid loss in a patient, the method comprising:

[0198] quantifying flow of fluid contents, including patient fluid, through a catheter;

[0199] estimating the concentration of a fluid constituent in a patient fluid; and

[0200] characterizing patient fluid loss based at least in part on the quantified flow and concentration of fluid components,

[0201] Wherein at least one of a flow rate and a concentration of a fluid component is based on sampled data from a sensor arrangement coupled to the conduit.

[0202] A second example provides a method according to the first example, wherein the patient fluid is blood and the fluid component is hemoglobin.

[0203] A third example provides the method according to the first example or the second example, wherein characterizing the patient fluid loss includes quantifying an amount of blood flowing through the catheter.

[0204] A fourth example provides the method according to any one of the first to third examples, further comprising measuring a composition of the fluid contents.

[0205] A fifth example provides the method according to the fourth example, wherein measuring the composition of the fluid contents includes performing spectroscopic analysis.

[0206] A sixth example provides the method according to any one of the first to fifth examples, wherein quantifying the flow rate of the fluid contents includes estimating the flow rate of the fluid contents.

[0207] A seventh example provides the method according to the sixth example, wherein estimating the flow rate includes transmitting ultrasound into the conduit and analyzing a frequency shift of the ultrasound reflected from the fluid contents.

[0208] An eighth example provides the method according to the sixth example, wherein estimating the flow rate includes transmitting ultrasound waves into the conduit and analyzing a time of flight of the ultrasound waves transmitted through the fluid contents.

[0209] A ninth example provides a method according to the sixth example, wherein estimating the flow rate includes comparing a first optical signal and a second optical signal, the first optical signal corresponding to light detected at a first position along the catheter, and the second optical signal corresponding to light detected at a second position along the catheter.

[0210] A tenth example provides the method of any one of the first to ninth examples, wherein quantifying the flow rate of the fluid contents includes estimating the thermal mass flow rate of the fluid contents.

[0211] An eleventh example provides the method of any one of the first to tenth examples, wherein estimating the concentration of the fluid component comprises analyzing a multispectral image of the catheter.

[0212] A twelfth example provides the method of any one of the first to eleventh examples, further comprising reducing the flow rate of the fluid contents through the catheter while quantifying the flow rate of the fluid contents.

[0213] A thirteenth example provides a system for characterizing patient fluid loss in a patient, the system comprising:

[0214] A sensor arrangement, the sensor arrangement being connectable to the catheter, the sensor arrangement comprising:

[0215] At least one sensor is configured to quantify flow of fluid contents through the catheter, the fluid contents including patient fluid, and the at least one sensor is configured to estimate a concentration of a fluid constituent in the patient fluid.

[0216] A fourteenth example provides the system according to the thirteenth example, wherein the sensor arrangement includes a housing configured to cover at least a portion of the conduit.

[0217] A fifteenth example provides the system of the thirteenth example or the fourteenth example, wherein the housing includes a jaw configured to clamp onto a catheter.

[0218] A sixteenth example provides the system of any one of the thirteenth to fifteenth examples, further comprising a catheter inserter tubing-coupled to the catheter.

[0219] A seventeenth example provides a system according to any one of the thirteenth to sixteenth examples, wherein at least one sensor comprises an ultrasonic flow rate sensor.

[0220] An eighteenth example provides a system according to any one of the thirteenth to seventeenth examples, wherein at least one sensor includes an optical sensor configured to detect light transmitted through the fluid content.

[0221] A nineteenth example provides a system according to any one of the thirteenth to eighteenth examples, wherein the sensor arrangement comprises a plurality of optical sensors arranged at a plurality of axial positions along the catheter.

[0222] A twentieth example provides a system according to any one of the thirteenth to nineteenth examples, wherein the sensor arrangement includes a plurality of optical sensors arranged at a plurality of circumferential positions around the catheter.

[0223] A twenty-first example provides a system according to any one of the thirteenth to twentieth examples, wherein the sensor arrangement includes a plurality of optical sensors arranged helically around the catheter.

[0224] A twenty-second example provides a system according to any one of the thirteenth to twenty-first examples, wherein the at least one sensor comprises a thermal mass flow sensor.

[0225] A twenty-third example provides a system according to any one of the thirteenth to twenty-second examples, wherein at least one sensor includes an optical sensor array configured to perform multi-spectral imaging.

[0226] A twenty-fourth example provides a system according to any one of the thirteenth to twenty-third examples, wherein at least one sensor includes an optical sensor array configured to perform color imaging.

[0227] A twenty-fifth example provides a system according to any one of the thirteenth to twenty-fourth examples, further comprising a processor configured to characterize patient fluid loss based at least in part on the quantified flow and concentration of the fluid component.

[0228] The twenty-sixth example provides a carrier medium carrying machine-readable instructions for controlling a machine to perform the operations (eg, method operations) performed in any one of the preceding examples.

Claims

1. A method comprising: accessing sensor data from a sensor arrangement coupled to a conduit through which fluid contents of a patient fluid flow, wherein the sensor arrangement includes an ultrasonic sensor associated with a first region of continuous flow of the patient fluid and an optical sensor associated with a second region of discontinuous flow of the patient fluid; quantifying a flow rate of fluid contents flowing through the conduit by estimating a flow rate based on a first output from the ultrasonic sensor and a second output from the optical sensor; estimating a concentration of a fluid component of the patient fluid in the fluid contents flowing through a catheter; and Based on the quantified flow rate of the fluid contents and the estimated concentration of the fluid constituent, volumetric passage of the patient fluid through the catheter is estimated. 2 . The method of claim 1 , wherein quantification of the flow rate of the fluid contents comprises estimating a volume flow rate of the fluid contents.

3. The method of claim 2, wherein the estimation of the volume flow rate of the fluid contents comprises transmitting an outgoing ultrasonic wave into a conduit and determining a frequency shift of an incident ultrasonic wave reflected from the fluid contents.

4. The method of claim 2, wherein the estimating of the volume flow rate of the fluid contents comprises transmitting ultrasound into a conduit and determining a time of flight of the ultrasound transmitted through the fluid contents. 5 . The method of claim 1 , wherein estimating the concentration of the fluid contents comprises performing a spectroscopic analysis of the fluid contents flowing through the conduit.

6. The method according to claim 1, further comprising: reducing the flow rate of the fluid contents through the conduit; as well as The reduced flow of the fluid contents is quantified.

7. The method of claim 1, wherein the estimation of the concentration of the fluid constituent in the fluid contents is based on a multispectral image of the conduit through which the fluid contents flow.

8. The method of any one of claims 1-7, wherein the patient fluid is blood, the fluid component is hemoglobin, and wherein the estimation of the passage of the volume of the patient fluid through the catheter is a quantification of the volume of blood flowing through the catheter.

9. A system comprising: a sensor arrangement, coupleable by a coupling device to a conduit configured to convey fluid contents including a patient fluid, wherein the sensor arrangement comprises an ultrasound sensor associated with a first region of continuous flow of the patient fluid and at least one optical sensor associated with a second region of discontinuous flow of the patient fluid; One or more processors in communication with the sensor arrangement and configured to perform operations comprising: accessing sensor data from the sensor arrangement; quantifying a flow rate of the fluid contents through the conduit by estimating a flow rate based on a first output from an ultrasonic sensor and a second output from an optical sensor; estimating a concentration of a fluid component of the patient fluid in the fluid contents flowing through the conduit; and Based on the quantified flow rate of the fluid contents and the estimated concentration of the fluid constituent, volumetric passage of the patient fluid through the catheter is estimated.

10. The system of claim 9, wherein the at least one optical sensor in the sensor arrangement is an optical sensor array configured to perform color imaging of the fluid contents.

11. The system of claim 10, wherein the optical sensor array is disposed at a plurality of axial locations along the catheter.

12. The system of claim 10, wherein the optical sensor array is arranged at a plurality of circumferential locations around the catheter.

13. The system of claim 10, wherein the optical sensor array is arranged helically around the catheter.

14. The system of claim 10, wherein the optical sensor array is configured to perform multispectral imaging of the fluid contents.

15. The system of claim 9, the sensor arrangement comprising a housing configured to cover at least a portion of the conduit.

16. The system of claim 9, wherein the coupling device comprises a jaw configured to clamp onto the catheter.

17. The system of claim 9, wherein the operations performed by the one or more processors further comprise causing a display to provide an alert based on the estimated passage of the patient fluid through a conduit.

18. The system of any one of claims 9-17, wherein the patient fluid is blood, the fluid component is hemoglobin, and wherein estimating the passage of the volume of the patient fluid through the catheter is quantifying the volume of blood flowing through the catheter.

19. A system according to any one of claims 9-18, wherein the operations performed by the one or more processors also include inputting the sensor data into a learning machine trained to quantify candidate flow rates based on a training set of reference flow rates represented by reference sensor data, wherein the trained learning machine is configured to output the quantified flow rate of the fluid contents.

Images