Method and apparatus for non-invasively measuring blood circulatory hemoglobin

Abstract

A method of non-invasively determining a total hemoglobin content of blood within a tissue region of a subject is provided that includes: non-invasively sensing a tissue region during a period of time using a NIRS tissue oximeter, the sensing producing first signals representative of a NIRS index of the blood within the tissue region; measuring a blood pressure level of the subject using a blood pressure sensing device during the period of time, the measuring of the blood pressure level producing second signals representative of the blood pressure level of the subject; determining whether a cerebral autoregulation state of the subject is within or outside an autoregulation zone of the subject during the period of time; and determining a total hemoglobin content of blood within the tissue region using the first signals when the cerebral autoregulation state of the subject is within the autoregulation zone.

Description

METHOD AND APPARATUS FOR NON-INVASIVELY MEASURING BLOODCIRCULATORY HEMOGLOBIN

[0001] This application claims priority to U.S. Patent Appln. No. 63 / 557,908 filed February 26, 2024, which is hereby incorporated herein by reference in its entirety.1. Technical Field

[0002] This invention relates to methods and apparatus for determining blood circulatory hemoglobin values in general, and to non-invasive methods and apparatus for determining blood circulatory hemoglobin values in particular.2. Background Information

[0003] The determination of a physiologic parameter such as hemoglobin concentration may be subject to unrelated influences (referred to herein as a “confounding factor”). For example, a first physiologic parameter may be elevated or depressed because of the influence of a confounding factor. Using that first physiologic parameter to determine a second physiologic parameter may detrimentally influence or taint the determination of the second physiologic parameter; e.g., making the determination less accurate as a result of the influence of the confounding factor. What is needed is an apparatus and method that accounts for one or more confounding factors during the determination of a physiologic parameter or condition.SUMMARY

[0004] According to an aspect of the present disclosure, a method of non-invasively determining a total hemoglobin content of blood within a tissue region of a subject is provided. The method includes: non-invasively sensing a tissue region of a subject during a period of time using a near infrared spectrophotometric (NIRS) tissue oximeter, the sensing producing first signals representative of a NIRS index of the blood within the tissue region during the period of time; measuring a blood pressure level of the subject using a blood pressure sensing device during the period of time, the measuring of the blood pressure level producing second signals representative of the blood pressure level of the subject during the period of time; determining whether a cerebral autoregulation state of the subject is within an autoregulation zone of thesubject during the period of time or outside of the autoregulation zone of the subject during the period of time; and determining a total hemoglobin content of blood within the tissue region (NIRS circulatory THb value) using the first signals when the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject during the period of time.

[0005] In any of the aspects or embodiments described above and herein, the method may include identifying AR zone acceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject, and AR zone unacceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be outside of the autoregulation zone of the subject, and the step of determining the NIRS circulatory THb value may use the first signals produced during the AR zone acceptable portions of the period of time.

[0006] In any of the aspects or embodiments described above and herein, the step of determining the NIRS circulatory THb value may not use the first signals produced during the AR zone unacceptable portions of the period of time.

[0007] In any of the aspects or embodiments described above and herein, the step of determining the NIRS circulatory THb value may only use the first signals produced during the AR zone acceptable portions of the period of time.

[0008] In any of the aspects or embodiments described above and herein, the first signals produced during the AR zone acceptable portions of the period of time may be separated from the first signals produced during the AR zone unacceptable portions of the period of time.

[0009] In any of the aspects or embodiments described above and herein, the first signals produced during the AR zone unacceptable portions of the period of time may be discarded.

[0010] In any of the aspects or embodiments described above and herein, the step of determining whether the cerebral autoregulation state of the subject is within the autoregulation zone of the subject during the period of time or outside of the autoregulation zone of the subject during the period of time may utilize the first signals and the second signals.

[0011] In any of the aspects or embodiments described above and herein, the method may include producing an operator flag in the event an AR zone unacceptable portion of the period of time is identified, and may include performing a calibration of the NIRS tissue oximeter.

[0012] According to an aspect of the present disclosure, a system for non-invasively determining a total hemoglobin content of blood within a tissue region of a subject is provided that includes a near infra-red spectroscopy (NIRS) tissue oximeter, a blood pressure sensing device, and a controller. The controller is in communication with the NIRS tissue oximeter and the blood pressure sensing device. The controller includes at least one processor and a memory device configured to store instructions. The stored instructions when executed cause the controller to: control the NIRS tissue oximeter to sense a tissue region of the subject during a period of time, and to produce first signals representative of a NIRS index sensed within the tissue region during the period of time; control the blood pressure sensing device to measure a blood pressure level of the subject during the period of time, and to produce second signals representative of the blood pressure level of the subject during the period of time; determine whether a cerebral autoregulation state of the subject is within an autoregulation zone of the subject during the period of time or outside of the autoregulation zone of the subject during the period of time; and determine a total hemoglobin content of blood within the tissue region (NIRS circulatory THb value) using the first signals when the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject during the period of time.

[0013] In any of the aspects or embodiments described above and herein, the stored instructions when executed may cause the controller to identify AR zone acceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject, and AR zone unacceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be outside of the autoregulation zone of the subject, and the determination of the NIRS circulatory THb value may use the first signals produced during the AR zone acceptable portions of the period of time.

[0014] In any of the aspects or embodiments described above and herein, the stored instructions when executed may cause the controller to separate the first signals produced during the AR zone acceptable portions of the period of time from the first signals produced during the AR zone unacceptable portions of the period of time.

[0015] In any of the aspects or embodiments described above and herein, the stored instructions when executed may cause the controller to discard the first signals produced during the AR zone unacceptable portions of the period of time.

[0016] In any of the aspects or embodiments described above and herein, the stored instructions when executed may cause the controller to produce an operator flag in the event an AR zone unacceptable portion of the period of time is identified, and may cause the controller to perform a calibration of the NIRS tissue oximeter when the flag is produced.

[0017] The foregoing features and elements may be combined in various combinations without exclusivity, unless expressly indicated otherwise. These features and elements as well as the operation thereof will become more apparent in light of the following description and the accompanying drawings. It should be understood, however, the following description and drawings are intended to be exemplary in nature and non-limiting.BRIEF DESCRIPTION OF THE DRAWINGS

[0018] FIG. 1 is a diagrammatic representation of a present disclosure system embodiment.

[0019] FIG. 1A is a diagrammatic representation of a present disclosure system embodiment.

[0020] FIG. 2 is a diagrammatic representation of a NIRS tissue oximeter and a transducer applied to a subject’s head as may be used with the present disclosure.

[0021] FIG. 3 is a diagrammatic representation of a NIRS tissue oximeter transducer.

[0022] FIG. 4 is a scatter plot of data points shown on a chart having a Y-axis representing blood circulatory THb values and an X-axis showing NIRS tissue THb values, and a trend line determined from the data points.

[0023] FIG. 5 is a scatter plot of data points from a plurality of data sets shown on a chart having a Y-axis representing blood circulatory THb values and an X-axis showing NIRS tissue THb values. A trend line is fit to each data set.

[0024] FIG. 6 is a diagrammatic representation of an exemplary frequency domain method for use with physiologic parameter pairs.

[0025] FIG. 7 is a diagrammatic flow chart illustrating how coherence values for physiologic parameter pairs may be used to determine whether the collected physiologic paramater data is influenced by a confounding factor.

[0026] FIG. 8 is an exemplary index table embodiment that may be used with the present disclosure, illustrating exemplary data from a number of different cases.

[0027] FIG. 9 is an exemplary index table embodiment that may be used with the present disclosure, illustrating exemplary data from a number of different cases.

[0028] FIG. 10 is a diagrammatic representation of an exemplary frequency domain method for use with blood pressure data and NIRS index data.

[0029] FIG. 11 is an example of an autoregulation profile plot.

[0030] FIG. 12 is a block diagram example illustrating coherence values determined in a plurality of different frequency bands with different temporal durations.

[0031] FIG. 13 is a diagrammatic representation of cerebral autoregulation index (CAI) methodology.

[0032] FIG. 14 is a block diagram illustrating an example of present disclosure embodiment.

[0033] FIG. 15 is a block diagram illustrating an example of present disclosure embodiment.

[0034] FIG. 16 is a block diagram illustrating an example of present disclosure embodiment.DETAILED DESCRIPTION

[0035] Embodiments of the present disclosure include a method and system 20 configured to simultaneously and noninvasively measure blood hemoglobin (e g., NIRS circulatory THb) and configured to utilize information indicative of cerebral autoregulation status in a manner that improves measurement of blood hemoglobin. The term “simultaneously” is used herein to mean that the sensing utilized within the present disclosure (e.g., noninvasive NIRS sensing, hemodynamic parameter sensing, blood pressure sensing, and the like) for purposes of measuring blood hemoglobin and for purposes of providing information indicative of cerebral autoregulation status are temporally performed such that the data collected for each reflects the same subject physiologic conditions within clinically acceptable standards. As will be detailed herein, in some embodiments the same NIRS tissue data may be used to measure blood hemoglobin and to provide information indicative of cerebral autoregulation status. In other embodiments, the sensed data used to provide information indicative of cerebral autoregulation status may be produced without the use of a NIRS tissue oximeter. In suchinstances, there may be a temporal shift in data collection with the collective data still reflecting the same subject physiologic conditions within clinically acceptable standards.

[0036] A physiological condition that affects cerebral blood flow has the potential of negatively affecting cerebral blood hemoglobin measurements. The present disclosure recognizes that autoregulation data may be used as an indicator of cerebral blood flow stability.Embodiments of the present disclosure utilize data indicating a subject’s cerebral autoregulation function is within an acceptable range (i.e., within the autoregulation zone) as an indicator of stable cerebral blood flow, and data indicating a subject’s cerebral autoregulation function is outside of an acceptable range as an indicator of unstable cerebral blood flow. An indication of unstable cerebral blood flow may be used (e.g., as a confounder) within a NIRS noninvasive blood hemoglobin measurement.

[0037] FIGS. 1 and 1A diagrammatically illustrate nonlimiting examples of present disclosure system 20 embodiments, including their respective system components such as a NIRS tissue oximeter 22, a blood pressure (BP) sensing device 24, input devices, output devices, and a system controller 26. In some embodiments, the system 20 may include a hemodynamic parameter sensing device 28. FIG. 1 diagrammatically illustrates an embodiment wherein system components are integrated into a single system device with a system controller 26 integrally connected and in communication (e.g., receive signal data from and / or send signal data to) with the aforesaid system components. FIG. 1A diagrammatically illustrates an embodiment wherein system components are independent of the system 20 but in communication with the system 20 and a system controller 26 provided therein. A system component that is “independent” of the system 20 may be a component that is capable of performing its respective function independently of the system 20 (e.g., a blood pressure sensing device that can be used by itself to sense blood pressure) and is configured to communicate with the system 20. The present disclosure also contemplates a hybrid of the above described system 20 embodiments; e.g., wherein certain system components are integral with the system 20 and other system components are independent of the system 20 and in communication with the system 20. The system 20 embodiments shown in FIGS. 1 and 1A are not intended to be limiting; e.g., alternative system 20 embodiments may include additional components, or alternative components, or different component implementations, and the like.

[0038] The term “controller” as used herein refers to a device that may include any type of computing device, computational circuit, processor(s), CPU, computer, or the like capable of executing a series of instructions that are stored in memory. The instructions may include an operating system, and / or executable software modules such as program files, system data, buffers, drivers, utilities, and the like. The executable instructions may apply to any functionality described herein to enable the system 20 (or a system component) to accomplish the same algorithmically and / or coordination of system components. A controller may include or may be in communication with one or more memory devices. The present disclosure is not limited to any particular type of memory device, and the memory device may store instructions and / or data in a non-transitory manner. Examples of memory devices that may be used include read-only memory, random access memory, volatile memory, non-volatile memory, static memory, dynamic memory, flash memory, cache memory, and / or any device that stores digital information. A controller may include, or may be in communication with, an input device that enables a user to enter data and / or instructions, and may include, or be in communication with, an output device configured, for example to display information (e.g., a visual display or a printer), or to transfer data, etc. Communications between a controller and other system components may be via a hardwire connection or via a wireless connection. Specific details regarding the functionality of a controller as may be included in a system component or as a system controller 26 are provided herein.

[0039] As indicated above, some present disclosure system 20 embodiments have integrated system components and a system controller 26 may be utilized to control those system components and to perform the functionality described herein. In other system 20 embodiments, one or more system components may include a dedicated controller for the respective component and that component controller is in communication with a system controller 26. In other system 20 embodiments, system component controllers may be in communication with one another and collectively configured as a system controller 26. The present disclosure is not limited to any particular controller architecture unless specifically stated herein. To facilitate the description, herein, the present disclosure system 20 will be described in terms of having a “system controller 26” and that system controller 26 is not intended to be limited to any particular controller architecture unless specifically stated.

[0040] Implementation of the techniques, blocks, steps, and means described herein may be done in various ways. For example, these techniques, blocks, steps, and means may be implemented in hardware, software, or a combination thereof. For a hardware implementation, processing devices configured to carry out the described functions and steps (e.g., by executing stored instructions) may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, or other electronic units designed to perform the functions described herein, and / or any combination thereof.

[0041] Embodiments of the present disclosure may be described herein as a process which is depicted as a flowchart, a flow diagram, a block diagram, etc. Although any one of these structures may describe the operations as a sequential process, many of the operations can be performed in parallel and / or concurrently. In addition, the order of the operations may be rearranged. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0042] Examples of hemodynamic parameter sensing devices 28 that may be used within the present disclosure system 20 include any device configured to sense a hemodynamic parameter such, but not limited to, heart rate, blood pressure, vasoreactivity, cardiac output, blood flow, and partial pressure of carbon dioxide in arterial blood (PaCO2). A specific example of a device that may be used to measure heart rate (HR) is an electrocardiogram (“ECG”). A specific example of a blood pressure sensing device is a ClearSight® system from Edwards Lifesciences Corporation. A specific example of a device that may be used to measure cardiac output is a cardiac output monitor utilizing doppler echocardiography. Devices and methods configured to determine a subject’s vasoreactivity will likely depend on the vasoactive stimulus utilized, and are known in the art. Specific examples of a device configured to measure the level of carbon dioxide (CO2) within blood is a transcutaneous blood gas monitor (PtcCO2), or an exhaled breath CO2 sensor (EtCO2), or the like. The above listed hemodynamic parameter sensing devices 28 are provided to illustrate types of devices that may be used to sense parameters that relate to a subject’s hemodynamic state, and are not intended to be limiting.

[0043] A blood pressure sensing device ("BP sensing device 24") may be any sensor or device configured to continuously determine a subject's blood pressure (e.g., arterial bloodpressure). For example, the BP sensing device 24 may be a device that is configured to provide continuous blood pressure measurement, such as an arterial catheter line, or a continuous non- invasive blood pressure device, or a pulse oximetry sensor. The present disclosure is not, however, limited to using these particular examples of blood pressure sensing / measuring / monitoring devices. The BP sensing device 24 is configured to produce blood pressure value signals indicative of the subject's blood pressure (e.g., arterial blood pressure) during a period of time. The BP sensing device 24 may be configured for communication with the system controller 26; e.g., send blood pressure value signals to the system controller 26, and may receive control signals, etc. from the system controller 26. Communications between the BP sensing device 24 and the system controller 26 may be by any known means; e.g., hardwire, wireless, etc. The term "continuously" as used herein (to describe a BP sensing device 24 continuously determining a subject's blood pressure) means that the BP sensing device 24 senses and collects subject data on a periodic basis during the monitoring time period, which periodic basis is sufficiently frequent that it may be considered to be clinically continuous. For example, some BP sensing devices 24 sample data every ten seconds or less (> 10 seconds), and can be configured to sample data more frequently (e g., every two seconds or less).

[0044] Referring to FIGS. 2 and 3, the NIRS tissue oximeter 22 includes at least one transducer 30 and may include a controller (“NTO controller 32”). As stated herein, within the present disclosure, a system component may include a controller dedicated to that system component, or the functionality of such a controller may be performed by a system controller 26. To simplify the description herein the NIRS tissue oximeter 22 will be described hereinafter as having a dedicated NTO controller 32, but the present disclosure is not limited to this configuration. The transducer 30 may be connected to the NTO controller 32 by a cable (e.g., configured to provide signal communication between the transducer 30 and the NTO controller 32) or the transducer 30 may be in wireless communication with the NTO controller 32.

[0045] The transducer 30 includes at least one light source 34 and at least one light detector 36. FIG. 2 diagrammatically illustrates an example of a transducer 30 that may be used with the present disclosure. The transducer 30 includes a transducer body 38, at least one light source 34, and a pair of light detectors 36A, 36B. The transducer body 38 is typically configured for attachment directly to a subject's skin surface. The light source 34 and light detectors 36A, 36B may be attached to or incorporated within the transducer body 38. The pair of light detectors36A, 36B may be described as a "near" detector 36A and a "far" detector 36B. The terms "near" and "far" indicate the relative distances from the light source 34. The light source 34 may include a plurality of light emitting diodes ("LEDs") that each emit light within a narrow spectral bandwidth at predetermined wavelengths. The light source 34 is not, however, limited to LEDs. The light detectors 36A, 36B may each include one or more photodiodes, or other light detecting devices. Nondimiting examples of acceptable NIRS tissue oximeter transducers 30 are described in U.S. Patent Nos. 9,988,873 and 8,428,674, both of which are hereby incorporated by reference in their entirety. The present disclosure is not limited to any particular transducer 30 configuration.

[0046] The NIRS tissue oximeter 22 is configured to spectrophotometrically, noninvasively sense a subject’s tissue and to determine a tissue oxygenation parameter that varies with blood flow in a subject’s tissue; e g., tissue oxygen saturation (StCh), total hemoglobin concentration per volume of tissue (THb), relative total hemoglobin concentration per volume of tissue (rTHb), deoxyhemoglobin (HHb), relative deoxyhemoglobin (rHHb), oxyhemoglobin (O2Hb), relative oxyhemoglobin (rO2Hb), deoxyhemoglobin (HHb), and the like (any of which may be referred to herein as a NIRS “index”, or collectively as NIRS “indices”). To be clear, the present disclosure is not limited to these particular NIRS indices and the various acronyms used herein (e.g., StCh, THb, rTHb, HHb, rHHb, O2Hb, and rO2Hb) are non-limited examples of acronyms that may be used by those skilled in the art to refer to the respective NIRS indices. A person of skill in the art will recognize that the same NIRS indices are sometimes referred to using different acronyms.

[0047] To facilitate the present description, the following terms used herein are defined as follows:• “THb” is used herein to mean the total hemoglobin content, collectively including the various types of hemoglobin that may be present within a blood sample such as oxyhemoglobin (HbCh), deoxyhemoglobin (Hb), carboxyhemoglobin (COHb), methemoglobin (MetHb), etc. Typically, the amount of oxyhemoglobin (HbO2) and deoxyhemoglobin (Hb) in a blood sample are disproportionately greater than the amounts of other types of hemoglobin present within a blood sample. To facilitate the description herein “THb” may be described herein as the sum of HbCh and Hb.• “blood circulatory THb” is used herein to mean the total hemoglobin content within a collected blood sample. Because a “blood circulatory THb” value is determined from a collected blood sample, it is independent of any hemodynamic effects that may be present in a subject’s tissue.• “NIRS tissue THb” is used to mean the total hemoglobin content of blood within a tissue sample sensed using a NIRS tissue oximeter that does not account for hemodynamic effects that may be present within the sensed tissue.• “NIRS circulatory THb” is used to mean the total hemoglobin content of blood within a tissue sample sensed using a NIRS tissue oximeter adapted to account for hemodynamic effects that may be present within the sensed tissue.

[0048] U.S. Patent Nos. 6,456,862; 7,072,701; 8,078,250; 8,396,526; and 8,965,472; and 10,117,610, each of which is hereby incorporated by reference in its entirety, disclose nonlimiting examples of a non-invasive NIRS tissue oximeter 22 that may be used within the present disclosure. The NIRS tissue oximeter 22 may be configured to continuously sense a tissue region. The term “continuously” as used herein (to describe a NIRS tissue oximeter 22 continuously sensing a tissue oxygenation parameter) means that the NIRS tissue oximeter 22 senses and collects subject data on a periodic basis during the monitoring time period, which periodic basis is sufficiently frequent that it may be considered to be clinically continuous. For example, some NIRS tissue oximeters 22 sample data every ten seconds or less and can be configured to sample data more frequently (e.g., every two seconds or less).

[0049] The NIRS tissue oximeter 22 may utilize one or more algorithms for determining one or more of the NIRS indices. The present disclosure is not limited to any particular NIRS tissue oximeter 22 or any algorithm for determining a NIRS index of the sensed tissue. U.S. Patent Nos. 9,913,601; 9,848,808; 9,456,773; 9,364,175; 9,923,943; 8,788,004; 8,396,526; 8,078,250; 7,072,701; and 6,456,862 all describe non-limiting examples of algorithms for determining NIRS indices that may be used totally or in part with the present disclosure, and all are incorporated by reference herein in their respective entirety.

[0050] In some embodiments, the NIRS tissue oximeter 22 may be adapted to determine NIRS circulatory data. U.S. Patent No. 11,454,589 (i.e., the “ ‘589 Patent”), commonly assigned herewith and hereby incorporated by reference in its entirety, discloses a method and system for non-invasively measuring circulatory hemoglobin that accounts for or mitigates the aforesaidphysiological parameters. The ‘589 Patent discloses that blood circulatory THb data produced from blood samples invasively drawn from a subject at about the same time as the subject’s tissue is sensed using a NIRS tissue oximeter may be used to calibrate a NIRS tissue oximeter. The ‘589 Patent provides an example of how the tissue oximeter may be calibrated to produce NIRS circulatory THb data that includes plotting the NIRS tissue oximeter data relative to the blood circulatory THb data to determine the slope of one or more trend lines and intercept values. FIG. 4 diagrammatically illustrates NIRS tissue oximeter data and blood circulatory THb data collected from a clinically sufficient number of data sets from a clinically sufficient population of subjects. FIG. 5 diagrammatically illustrates NIRS tissue oximeter data and blood circulatory THb data from a single subject that has been subjected to a stepwise hemodilution protocol. In both cases, a linear regression technique may be used to define a trend line 40, a slope value, and a intercept value. The slope lines and intercept values may be used subsequently calibration purposes and to determine NIRS circulatory THb values from NIRS tissue THb values. The ‘589 Patent discloses that a NIRS tissue oximeter 22 may be calibrated relative to a specific subject (i.e., subject specific) or may be calibrated using empirical data not associated with any particular subject (i.e., subject independent). In some instances, calibration may involve producing a slope constant as described above, but may not involve determining an intercept value. Without an intercept value, changes in blood hemoglobin data may be determined from a zero value. The present disclosure is not limited to the teachings of the ‘589 Patent regarding producing NIRS circulatory THb data using a NIRS tissue oximeter 22. For example, as an alternative to the slope / intercept methodology described above, machine learning may be used to correlate NIRS tissue oximeter data to NIRS circulatory THb data; e.g., machine learning may be used to derive an algorithmic solution (e.g., an equation) that correlates NIRS tissue oximeter data to NIRS circulatory THb data.

[0051] In some embodiments, the present disclosure system 20 may be adapted to account for factors that may confound a NIRS circulatory Hb measurement. Hemoglobin data determined by a conventional NIRS tissue oximeter can be affected by physiological parameters including circulatory blood hemoglobin, hemoglobin concentration per volume of tissue, vasoreactivity, cardiac output, blood flow, partial pressure of carbon dioxide in arterial blood (PaCO2), heart rate, blood volume, hematomas, hyperemia, and the like. PCT Publication No. WO 2023 / 283171 (i.e., “ ‘ 171 PCT Publication”), commonly assigned herewith and incorporatedby reference in its entirety, discloses a method and apparatus for noninvasively measuring blood circulatory hemoglobin using a NIRS tissue oximeter that accounts for hemodynamic parameters. More specifically, the method and apparatus disclosed in the ‘ 171 PCT Publication accounts for “Hb confounding factors”. As used herein, the term “Hb confounding factor” may refer to vasoreactivity and / or hemodynamic effects that may confound a NIRS circulatory THb determination. The term “confounding factor” is also used herein to describe other physiologic conditions that may confound a NIRS circulatory THb determination. The method and apparatus disclosed in the ‘ 171 PCT Publication utilizes a NIRS tissue oximeter adapted to determine NIRS circulatory data (e.g., adapted in a manner as disclosed in the ‘589 Patent) and a hemodynamic parameter sensing device 28. In some embodiments, the method and apparatus disclosed in the ‘ 171 PCT Publication may also utilize an invasive blood sample analyzing device; e.g., a CO-oximeter, a blood-gas analyzer, or the like. The adapted NIRS tissue oximeter disclosed in the ‘ 171 PCT Publication may be configured to identify the presence of an Hb confounding factor based on empirical data stored within the NIRS tissue oximeter controller and configured to produce hemoglobin data (e.g., NIRS circulatory THb) that accounts for the HB confounding factor:NIRS circulatory THb = f NIRS tissue THb(cal. or uncal), HR, BP, CO, PaC02, etc. ) (Eqn. 1)As noted in Equation 1 above, NIRS circulatory THb data may be determined using a NIRS tissue oximeter 22 that is calibrated or uncalibrated. For clarity sake, the aforesaid empirical data and stored instructions directed to using the empirical data need not be stored within the NIRS tissue oximeter controller 32. As disclosed in the ‘ 171 PCT Publication and herein, the functionality provided by a controller may be accomplished in a variety of different controller architectures. To facilitate the discussion herein, the functionality is described in terms of the NIRS tissue oximeter controller 32 but is not limited to that particular controller configuration.

[0052] A variety of different hemodynamic parameter sensing device 28 types may be used. For heart rate as a confounding factor, an independent hemodynamic parameter sensing device 28 in the form of a HR monitor such as an electrocardiogram (“ECG”) or the like may be used. For purposes of measuring heart rate as a confounding factor, the NIRS tissue oximeter 22may be used to measure heart rate without the need for an independent hemodynamic parameter sensing device 28. For blood pressure as a confounding factor, an independent hemodynamic parameter sensing device 28 in the form of a BP sensing device 24 may be used. For cardiac output as a confounding factor, an independent hemodynamic parameter sensing device 28 in the form of a cardiac output monitor utilizing doppler echocardiography, or the like, may be used. For vasoreactivity as an Hb confounding factor, an independent hemodynamic parameter sensing device 28 operable to determine vasoreactivity may be used as described above. Carbon dioxide (CO2) within blood affects cerebrovascular reactivity independently of cerebral perfusion pressure. For CO2 as a confounding factor, an independent hemodynamic parameter sensing device 28 in the form of a transcutaneous blood gas monitor (PtcCO2), or an exhaled breath CO2 sensor (EtCO2), or the like may be used. If the NIRS tissue oximeter 22 is operable to provide a pulsatile waveform (e.g., a waveform that reflects pulsatile blood flow), then signals / features may be extracted from the pulsatile waveform that can be used to identify vasoreactivity and / or hemodynamic changes that may confound a NIRS circulatory THb determination. Regardless of whether AR is used in the present disclosure as an indicator of stable or unstable CBF, or as a confounding factor within an Hb determination, AR status data may be determined using a variety of techniques. Using NIRS tissue oximeter data and BP sensing device data, as will be described herein, is a nonlimiting example of such a technique.

[0053] The Hb confounding factors examples and the hemodynamic parameter sensing device 28 examples provided above are intended to illustrate aspects of the present disclosure to facilitate an appreciation and understanding of the present disclosure, but do not reflect all possible types of Hb confounding factors and / or hemodynamic parameter sensing devices 28.

[0054] In some embodiments, the present disclosure system 20 may be configured to account for confounding factors by determining the presence or absence of confounding factors using a coherence analysis or similar correlation / regression technique. The coherence analysis utilizes physiologic signal data from a plurality of different physiologic parameters. PCT Application No. PCT / US2023 / 029404 (the “ ‘404 Application”), commonly assigned herewith and incorporated by reference in its entirety, discloses an example of such a method and system. The ‘404 Application discloses a frequency domain methodology within a coherence (“COHZ”) analysis (or an algorithm based on correlation / regression technique) that transforms (e.g., via a Fourier transformation) pairs of input physiologic parameter signal data from a time domain to afrequency domain. FIG. 6 shows respective plots of a first physiologic parameter (“Cl”) versus frequency and a second physiologic parameter (“Cn”, where “n” is an integer greater than 1) versus frequency. The transformed data is further analyzed to determine the degree of coherence within a single band of frequencies (i.e., a single frequency band). The degree of coherence may be indicated in terms of an arbitrarily assigned scale of zero to one (0 - 1), wherein the degree of coherence increases from zero to one (shown as a plot of coherence values versus frequency). A coherence value of one represents a stronger relationship between parameters Cl and Cn, and a coherence value that approaches zero indicates increasingly less relationship between parameters Cl and Cn. The process of determining the degree of coherence (COHZ) is performed for at least two different physiologic parameter pairs (e.g., Cl and Cn, C2 and Cn) and is not limited to any particular number of physiologic parameter pairs; e.g., the process of determining the degree of coherence (COHZ) may be performed for more than two different physiologic parameter pairs - Cl and Cn, C2 and Cn, C3 and Cn, etc.

[0055] Referring to FIG. 7, the determined coherence values for the respective physiologic parameter pairs are then evaluated to determine whether the collected physiologic parameter data is influenced by a confounding factor. The aforesaid evaluation may be performed in a variety of different ways, including but not limited to using an index table, or a flat filter, or a polarity filter, or the like. An index table, for example, may assume a data structure form that permits comparisons between the COHZ value of a physiologic parameter pair (e.g., Cl / Cn) relative to the COHZ value of another physiologic parameter pair (e.g., C2 / Cn). The physiologic parameter pair COHZ values (e.g., Cl / Cn and C2 / Cn) may be characterized in view of empirically collected data and other information (e.g., a threshold values) as a “low” COHZ value, a “high” COHZ value, or an indeterminate COHZ value. The relative values of the physiologic parameter pair COHZ values may then be used to determine whether the physiologic data collected is likely tainted by a confounding factor. FIG. 8 is an example index table for illustration purposes. If the physiologic data is determined to be tainted, then that physiologic data may be flagged and not used (e.g., not binned, discarded, or the like) in a subsequent determination of the physiologic parameter; e.g., THb. If the physiologic data is determined to be untainted, then that physiologic data may be used (e.g., binned) in a subsequent determination of the physiologic parameter as a function of time.

[0056] The ‘404 Application discloses that the above described COHZ analysis may also be performed for physiologic parameter pairs in a plurality of frequencies disposed within a particular frequency band. The COHZ values determined for each frequency may then be used to determine a peak COHZ value from the collective individual frequency COHZ values (e.g., a “Peak COHZ”), or the collective individual frequency COHZ values may be processed to produce a collective coherence parameter (e.g., a “CP Index”) representative of the coherence values within the band of frequencies. Still further, collective COHZ values (e.g., Peak COHZ value, CP index value, and the like) can be further processed on a frequency band basis. The frequency bands may be selected to reflect time periods relative to changes in the physiologic parameter. Different time periods (i.e., different sampling periods) may be useful in identifying changes in the physiologic parameter that occur more or less rapidly.

[0057] The ‘404 Application also discloses that the above described COHZ analyses may be performed over a period of time and processed further to determine trend information; e.g., whether a physiologic parameter is trending upward over the period of time, or trending downward over the period of time, or remaining stable over the period of time. In some applications, trending information may be used in the determination of whether collected physiologic parameter data is acceptable for use in the determination of a physiologic parameter (e.g., THb), or unacceptable and therefore should not be used to determine the physiologic parameter. The input table shown in FIG. 9 illustrates trend data (“Deer” = decreasing, “Incr” = increasing, and “N / C” = no change) for three different physiologic parameters (THb, BP and HR) for ten (10) different cases. The input table includes a binary determination column wherein for each case a determination of whether the physiologic parameter data of interest (i.e., THb) is valid for use is indicated based on physiologic parameter pair coherence and polarity. In cases 1, 2, and 7-10 the input physiologic parameter data (e.g., THb, BP and HR) is determined to untainted by a confounding factor and the data may be passed on for use in a determination of the subject’s THb. In cases 3-6, the input physiologic parameter data (e.g., THb, BP and HR) is determined to be tainted by one or more confounding factors and the data is either set aside (“frozen”) or discarded and therefore not passed on for use in a determination of the subject’s THb. The input table is provided to illustrate an example of how physiologic parameter trending data may be evaluated. As stated above, the evaluation of whether the physiologic parameter dataof interest is valid for use in a determination of the physiologic parameter of interest may be performed in a variety of different ways and is not therefore limited to using an index table.

[0058] Embodiments of the present disclosure may be configured with logic (e.g., stored instructions) for determining whether a calibration or recalibration of the NIRS tissue oximeter 22 is appropriate (e.g., in view of hemodynamic instability and / or changes), when a calibration / recalibration is appropriate, and techniques for performing the calibration. Examples of logic that may be used in a determination of whether a calibration or recalibration of the NIRS tissue oximeter 22 is appropriate include determining instability in the NIRS tissue sensing data; e.g., variability outside of a predetermined threshold range within a predetermined period of time, or cumulative variability (e.g., from a mean value) over a predetermined period of time, raw signal quality or variability, or the like. The aforesaid techniques for determining whether a calibration or recalibration of the NIRS tissue oximeter 22 is appropriate may evaluate data over an extended period of time that is sufficient to identify NIRS tissue oximeter data trends. The extended period of time evaluation may identify data signal instability or changes that may not be apparent in a shorter window of time. In some instances, the determination of whether a calibration or recalibration of the NIRS tissue oximeter 22 is appropriate may also be based on determined NIRS index values (e.g., THb). The present disclosure is not limited to any particular technique or logic for determining whether a calibration or recalibration of the NIRS tissue oximeter 22 is appropriate. In those instances where it is determined that calibration or recalibration of the NIRS tissue oximeter 22 is appropriate, the NIRS tissue oximeter signal data used in the evaluation may be removed (“frozen”) and not used in the NIRS circulatory THb determination. A calibration or recalibration of the NIRS tissue oximeter 22 may be performed using data collected from an invasively collected blood sample. PCT Publication No. WO 2023 / 033832 (the “ ‘832 PCT Publication”), entitled “Method and Apparatus for Non-invasively Measuring Blood Circulatory Hemoglobin”, commonly assigned herewith and incorporated by reference in their entirety, further details calibration techniques.

[0059] Embodiments of the present disclosure are configured to produce data relating to a subject’s cerebral autoregulation status and use that AR data as an indicator of the presence or absence of a physiologic condition that may negatively affect a cerebral NIRS circulatory Hb measurement. As will be detailed herein, the data relating to the subject’s cerebral autoregulation 1status may be utilized in several different ways to account for the presence or absence of a physiologic condition that may negatively affect a cerebral NIRS circulatory Hb measurement.

[0060] A subject’s cerebral autoregulation (AR) functions to maintain constant cerebral blood flow (CBF) despite perfusion pressure changes. AR data may be produced using a NIRS tissue oximeter 22 as described herein and a blood pressure sensing device as described herein. Fluctuations in a NIRS index (e.g., StCh. THb, rTHb, and the like) can be attributed to CBF. AR data can be produced by correlating the NIRS index data to perfusion pressure (e.g., using MAP as a surrogate). PCT Publication No. WO 2022 / 245530 (the “ ‘530 PCT Publication”), entitled “Autoregulation System and Method Using Tissue Oximetry and Blood Pressure”, and PCT Publication No. WO 2022 / 231888 (the “ ‘888 PCT Publication”), entitled “System and Method for Autoregulation Data Determination”, both commonly assigned herewith and incorporated by reference in their entirety, describe systems and methods for determining AR data that may be used to determine a subject’s AR status. The systems and methods disclosed in the ‘530 PCT Publication and the ‘888 PCT Publication are detailed herein to illustrate an example of a system and method for determining AR data and the present disclosure is not intended to be limited to these examples. A variety of different techniques may be used to provide the AR data utilized within the present disclosure and the present disclosure is not limited to an AR measurement system that utilizes a NIRS tissue oximeter 22.

[0061] The ‘530 PCT Publication and the ‘888 PCT Publication describe a system configured to produce a data value (e.g., a coherence value) that can be measured and / or monitored, or a data value (e.g., AR Index) that is indicative of the state of a subject’s autoregulation system status; e.g., the degree to which the subject’s autoregulation system is functioning. FIG. 10 diagramatically depicts an exemplary frequency domain method that involves taking synchronous blood pressure and NIRS index values over a predetermined sampling window (e.g., period of time). As stated herein, aspects of the present disclosure are not limited to using a frequency domain method. In this exemplary frequency domain method, the blood pressure and NIRS index values are each transformed (e.g., via a Fourier transformation) from a time domain to a frequency domain (shown as respective plots of blood pressure versus frequency and NIRS index versus frequency). The transformed data is further analyzed to determine the degree of coherence between the NIRS index and blood pressure parameters at various frequencies within a single band of frequencies. The degree of coherence may beindicated in terms of an arbitrarily assigned scale of zero to one (0 - 1), wherein the degree of coherence increases from zero to one (shown as a plot of coherence values versus frequency). A coherence (“COHZ”) value of one represents a pressure passive condition. Conversely, a COHZ value that approaches zero indicates increasingly less relationship between relation between the NIRS index and blood pressure parameters. A COHZ value that is representative of substantially all frequencies in the single frequency band may be used as an autoregulation index (“AR Index”) or pressure passive index (“PPI”). For purposes of the present description, the terms “AR Index” and pressure passive index “PPI” are intended to be substantially equivalent, and for sake of clarity the term “AR Index” will be used hereinafter. The representative COHZ value for a single frequency band may be an average of the COHZ values within the single frequency band, or a mean value, or a median value, or any similar value that collectively represents the COHZ values over all frequencies in the single frequency band. The COHZ values (within the single frequency band) determined over a period of time may be binned in blood pressure increments (e.g., every 5 mmHg) or in incremental blood pressure ranges (e.g., 0-20 mmHg, 20-25 mmHg, 25-30 mmHg, etc.). FIG. 11 is a nonlimiting example of an autoregulation profile plot based on human neonate data, depicting Y-axes of an AR Index and a representative StO2 (i.e., a NIRS Index), an X-axis of a representative blood pressure range (shown in 5 mmHg bins), and COHZ values per blood pressure bin. As stated above, the autoregulation profile plot may include a NIRS index other than SK ; i.e., rTHb, differential changes in HbO2 and HHb, HbD, etc. The data depicted in FIG. 11 indicates that the autoregulation of the human neonate subject becomes increasingly pressure passive at a blood pressure value less than about fifty mmHg (50 mmHg). FIG. 11 includes a horizontal line 42 at about the AR Index value of 0.3 to reflect an AR Index value inflection point above which the subject’s autoregulation system may be described as being pressure passive to some degree, and below which the subject’s autoregulation function is substantially normal. As stated above, the present disclosure is not limited to the AR Index value inflection point of 0.3, or to any particular AR Index value inflection point.

[0062] In addition to the above described methodology that determines a COHZ value representative of the COHZ values for all the frequencies in the single frequency band, the ‘530 PCT Publication and the ‘888 PCT Publication further describe embodiments wherein COHZ values are determined within a plurality of different frequency bands and a MAX COHZ value is determined from amongst the different frequency bands. The frequency bands may be selected toreflect time periods relative to changes in a subject’s blood pressure (e g., slow rate of change, fast rate of change), or respiratory effects such as breathing rate, or Mayer waves, or the like. FIG. 12 diagrammatically illustrates a flow chart having a plurality of different frequency bands with different temporal durations. The identified frequency bands and temporal durations are provided as examples and are not intended to be limiting.

[0063] The COHZ values or the MAX COHZ may be used as an autoregulation index (“AR Index”) or pressure passive index (“PPI”) in a manner like that diagrammatically shown in FIG. 11. Furthermore, the COHZ values or the MAX COHZ may be utilized to determine cerebral autoregulation index (“CAI”) data. The determination of the CAI data may include correlating COHZ values with MAP bins to produce CAI data points. The ‘888 PCT Publication discloses examples of how CAI data may be determined using COHZ values (determined from noninvasively collected NIRS index data and blood pressure data) and MAP bins to produce CAI data points. In these examples, the CAI data is provided as a function of time. FIG. 13 diagrammatically illustrates a profile plot of COHZ values versus MAP bins, and a graph of CAI values (vertical axis) versus time (horizontal axis). The CAI graph advantageously provides CAI data, as well as historical CAI data which may reveal a trend. In some embodiments, CAI data may be weight averaged, filtered, or otherwise processed to smooth the data and mitigate sharp differences. The present disclosure is not limited to any particular method or technique for determining CAI data.

[0064] If the subject’s cerebral AR status is determined to be within the subject’s autoregulation zone (i.e., between the upper limit of autoregulation or “ULA” and the lower limit of autoregulation or “LLA” for that subject), that is an indication that the subject’s CBF is stable. An indication that a subject’s CBF is stable, in turn, is an indicator of the absence of a physiologic condition that may negatively affect a cerebral NIRS circulatory Hb measurement. Conversely, if the subject’s AR status is determined to be outside of the subject’s autoregulation zone (i.e., above the ULA or below LLA), that is an indication that the subject’s CBF is unstable. An indication that a subject’s CBF is unstable, in turn, is an indicator of the presence of a physiologic condition that may negatively affect a cerebral NIRS circulatory Hb measurement.

[0065] In the operation of the present disclosure system 20, embodiments of the system 20 are configured to produce data NIRS circulatory Hb data and information indicative of cerebral autoregulation status. The NIRS circulatory Hb data may be determined noninvasivelyusing any of the examples described herein; e g., using a NIRS tissue oximeter 22 that is configured to determine NIRS circulatory Hb, which NIRS tissue oximeter 22 may also be configured to account for confounding factors associated with hemodynamic effects that may be present within the sensed tissue. The information indicative of cerebral AR status may also be determined using the examples as described herein but is not limited to the given examples.

[0066] Referring to FIG. 14, in some present disclosure embodiments the information indicative of cerebral AR status may be used as a confounding factor. FIG. 14 is a diagrammatic block diagram that illustrates a present disclosure embodiment that accounts for Hb confounding factors. Block 44 is representative of a subject’s tissue being sensed using a NIRS tissue oximeter 22. The signal data produced by the NIRS tissue oximeter 22 sensing includes a THb blood hemoglobin component attributable to blood circulatory Hb and may include a hemodynamic portion attributable to hemodynamic factors depending on whether hemodynamic factors are present during the sensing (no hemodynamic factors - no hemodynamic portion). The “Potential Hemodynamic Parameters” 46 block represents input from one or more hemodynamic parameter sensing devices 28 configured to sense a hemodynamic parameter (or a related parameter) or input relating to hemodynamic conditions. In the embodiment depicted in FIG. 14, “devices for providing AR status” are shown within the “Potential Hemodynamic Parameters” block 46 to indicate that AR status is being evaluated as a potential Hb confounding factor.

[0067] FIG. 14 includes an “Identify THb Confounding Parameter” block 48. Within present disclosure embodiments that utilize information indicative of cerebral AR status as a confounding factor, the aforesaid information provides an indication of whether the subject’s CBF is stable or unstable. An indication of a stable CBF is an indicator of the absence of a physiologic condition that may negatively affect a cerebral NIRS circulatory Hb measurement. An indication of an unstable CBF is an indicator of the presence of a physiologic condition that may negatively affect a cerebral NIRS circulatory Hb measurement.

[0068] In the “Account for the THb Confounding Factor” block 50, if the information indicative of cerebral AR status provides an indication of that the subject’s CBF is stable (or at least sufficiently stable to not have a detrimental effect on a NIRS circulatory THb determination), then the present disclosure NIRS tissue oximeter 22 (or system 20) and method may be configured (e.g., via stored instructions) to utilize the input physiologic parameter data (e g., NIRS tissue oximeter signals) for a determination of the subject’s NIRS circulatory THb. Itshould be noted, however, that an indication of stable CBF (e.g., via information indicative of cerebral AR such as AR Index, CAI, or the like) is not necessarily an indication that no other Hb confounding factor is present. The presence of another Hb confounding factor may be used to determine whether input physiologic parameter data (e.g., NIRS tissue oximeter signals) is tainted and should not be used in a determination of the subject’s NIRS circulatory THb.

[0069] In the “Account for the THb Confounding Factor” block 50, if the information indicative of cerebral AR status provides an indication of that the subject’s CBF is unstable, then the present disclosure NIRS tissue oximeter 22 (or system 20) and method may be configured (e.g., via stored instructions) to separate the input physiologic parameter data (i.e., the “tainted” NIRS tissue oximeter signals). In some embodiments, the tainted physiologic parameter data may be discarded (i.e., “frozen”) or stored but not used in the NIRS circulatory THb determination. In some embodiments, the tainted physiologic parameter data may be processed in a manner that recognizes the effect of the confounding factor. The processing may include modifying the tainted physiologic parameter data into a useful form. In this manner, the accounting permits a non-invasive determination of the blood THb data (e.g., a NIRS circulatory THb data) that is either not subject to hemodynamic effects or is only subject to hemodynamic effects in a clinically inconsequential way. In some embodiments, the tainted physiologic parameter data may be utilized as an input into a machine learning protocol that permits the confounding factor to be accounted for.

[0070] The “NIRS Circulatory THB data (w / confounding factor accounting)” block 52 represents the processing of the input physiologic parameter data (e g., NIRS tissue oximeter signals) now accounting for the presence or absence of confounding factors such as AR status into NIRS circulatory THb data.

[0071] The “NIRS tissue THb Calibration Parameter” block 54 represents an alternative calibration process that may be used in applications wherein the NIRS tissue oximeter 22 is not calibrated to produce circulatory THb data (i.e., within block 44). The functionality of this block 54 is not required in all embodiments as indicated above.

[0072] Referring to FIG. 15, in some present disclosure embodiments the information indicative of cerebral AR status may be used as a flag to trigger the NIRS tissue oximeter 22 to perform a calibration or recalibration. The diagrammatic block diagram shown in FIG. 15 is similar to that shown in FIG. 14. The method diagrammatically shown in FIG. 15, however,includes logic (e g., stored instructions) for performing a calibration or recalibration of the NIRS tissue oximeter 22 based on cerebral AR status information (see block 56). If the information indicative of cerebral AR status provides an indication that the subject’s CBF is stable (or at least sufficiently stable to not have a detrimental effect on a NIRS circulatory THb determination), then the present disclosure NIRS tissue oximeter 22 (or system 20) and method may be configured (e.g., via stored instructions) to not perform or require a calibration or recalibration of the NIRS tissue oximeter 22. If the information indicative of cerebral AR status provides an indication that the subject’s CBF is unstable, then the present disclosure NIRS tissue oximeter 22 (or system 20) and method may be configured (e.g., via stored instructions) to perform or require a calibration or recalibration of the NIRS tissue oximeter 22. In addition, if the system logic flags NIRS tissue oximeter data as being collected during a period of CBF instability, the NIRS tissue oximeter data used in that determination (potentially collected over different duration periods of time) may be removed (“frozen”) and not used in the NIRS circulatory THb determination or utilized within a machine learning protocol. Nonlimiting examples of logic (e.g., stored instructions) that may be used in a determination of whether a calibration or recalibration of the NIRS tissue oximeter 22 is appropriate and how a calibration or recalibration may be performed are detailed hereinabove.

[0073] As described above and diagrammatically shown in FIGS. 14 and 15, present disclosure embodiments may use input from any one of a number of different hemodynamic parameter sensing devices 28 relating to hemodynamic conditions (e.g., see “Potential Hemodynamic Parameters” block 46), including devices for providing autoregulation function status data. FIGS. 14 and 15 illustrate that data input into the “Identify THb Confounding Parameter” block 48 and / or the “Account for the THb Confounding Factor” block 50. The block diagram shown in FIG. 16 illustrates a modified version of the methodologies shown in FIGS. 14 and 15 to make clear that the present disclosure does not require the separate functionality of each block shown in FIGS. 14 and 15. In FIG. 16, the signal data produced by the NIRS tissue oximeter 22 sensing (i.e., block 44) and / or input from a hemodynamic parameter sensing device 28 (i.e., block 46) may be input into a block 58 that determines whether the subject’s cerebral AR function is active (e.g., CBF is constant) or whether the subject’s cerebral AR function is poor (e.g., CBF is variable or unstable). If the subject’s cerebral AR function is determined to be active, then the present disclosure NIRS tissue oximeter 22 (or system 20) and method may beconfigured (e.g., via stored instructions) to utilize the input physiologic parameter data (e.g., NIRS tissue oximeter signals) for a determination of the subject’s NIRS circulatory THb. Conversely, if the subject’s cerebral AR function is determined to be poor, then the present disclosure NIRS tissue oximeter 22 (or system 20) and method may be configured (e.g., via stored instructions) to not use the input physiologic parameter data (e.g., NIRS tissue oximeter signals) for a determination of the subject’s NIRS circulatory THb. As indicated above, the input physiologic parameter data (e.g., NIRS tissue oximeter signals) that is not used may be separated from acceptable input physiologic parameter data and may be discarded, or stored for a later use. Any determination that a subject’s AR function is “active” or “poor” may be made based on predeterimined factors or logic or empirical data, or the like, and may be predicated on the physiological characteristics of the subject.

[0074] In any of the present disclosure method embodiments (e.g., like those shown in FIGS. 14-16), if a subject’s cerebral AR function is determined to be poor and the input physiologic parameter data (e.g., NIRS tissue oximeter signals) is not used for a determination of the subject’s NIRS circulatory THb, the system may be configured to utilize acceptable input physiologic parameter data acquired earlier in time (but still clinically proximate to the time period wherein the unacceptable input physiologic parameter data is acquired) and display NIRS circulatory THb data based thereon. In this manner, NIRS circulatory THb data with improved stability can be determined and displayed and outlier data can be “filtered” out. The methodology may include logic that determines when and if utilizing input physiologic parameter data acquired earlier in time is appropriate.

[0075] In some embodiments of the present disclosure, artificial intelligence or more specifically machine learning may be used to facilitate application of the algorithms described herein; e.g., algorithms that account for hemodynamic effects, algorithms for determining AR information, or the like. As described herein, aspects of the present disclosure include an accounting that includes separating (i.e., “freezing”) the portion of the NIRS tissue Hb data attributable to the Hb confounding factor. Machine learning may be used to facilitate that process or others described herein; e.g., as detailed herein, machine learning may utilized to process physiologic parameter data determined to be subject to a confounding factor (“tainted parameter data”) to account for that confounding factor in a manner other than “freezing” the data. Machinelearning techniques are known, and the present disclosure is not limited to any particular machine learning technique or process.

[0076] As indicated above, the functionality described herein may be implemented, for example, in hardware, software tangibly embodied in a computer-readable medium, firmware, or any combination thereof. In some embodiments, at least a portion of the functionality described herein may be implemented in one or more computer programs. Each such computer program may be implemented in a computer program product tangibly embodied in non-transitory signals in a machine-readable storage device for execution by a computer processor. Method steps of the present disclosure may be performed by a computer processor executing a program tangibly embodied on a computer-readable medium to perform functions of the present disclosure by operating on input and generating output. Each computer program within the scope of the present claims below may be implemented in any programming language, such as assembly language, machine language, a high-level procedural programming language, or an object-oriented programming language. The programming language may, for example, be a compiled or interpreted programming language.

[0077] It is noted that the embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a block diagram, etc. Although any one of these structures may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be rearranged. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0078] The singular forms "a," "an," and "the" refer to one or more than one, unless the context clearly dictates otherwise. For example, the term "comprising a specimen" includes single or plural specimens and is considered equivalent to the phrase "comprising at least one specimen." The term "or" refers to a single element of stated alternative elements or a combination of two or more elements unless the context clearly indicates otherwise. As used herein, "comprises" means "includes." Thus, "comprising A or B," means "including A or B, or A and B," without excluding additional elements.

[0079] It is noted that various connections are set forth between elements in the present description and drawings (the contents of which are included in this disclosure by way of reference). It is noted that these connections are general and, unless specified otherwise, may be direct or indirect and that this specification is not intended to be limiting in this respect. Anyreference to attached, fixed, connected or the like may include permanent, removable, temporary, partial, full and / or any other possible attachment option.

[0080] No element, component, or method step in the present disclosure is intended to be dedicated to the public regardless of whether the element, component, or method step is explicitly recited in the claims. No claim element herein is to be construed under the provisions of 35 U.S.C. 112(f) unless the element is expressly recited using the phrase “means for.” As used herein, the terms “comprises”, “comprising”, or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0081] While various inventive aspects, concepts and features of the disclosures may be described and illustrated herein as embodied in combination in the exemplary embodiments, these various aspects, concepts, and features may be used in many alternative embodiments, either individually or in various combinations and sub-combinations thereof. Unless expressly excluded herein all such combinations and sub-combinations are intended to be within the scope of the present application. Still further, while various alternative embodiments as to the various aspects, concepts, and features of the disclosures— such as alternative materials, structures, configurations, methods, devices, and components, and so on— may be described herein, such descriptions are not intended to be a complete or exhaustive list of available alternative embodiments, whether presently known or later developed. Those skilled in the art may readily adopt one or more of the inventive aspects, concepts, or features into additional embodiments and uses within the scope of the present application even if such embodiments are not expressly disclosed herein. For example, in the exemplary embodiments described above within the Detailed Description portion of the present specification, elements may be described as individual units and shown as independent of one another to facilitate the description. In alternative embodiments, such elements may be configured as combined elements. It is further noted that various method or process steps for embodiments of the present disclosure are described herein. The description may present method and / or process steps as a particular sequence. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. As one of ordinary skill in the art would appreciate, other sequences of stepsmay be possible. Therefore, the particular order of the steps set forth in the description should not be construed as a limitation.

[0082] Additionally, even though some features, concepts, or aspects of the disclosures may be described herein as being a preferred arrangement or method, such description is not intended to suggest that such feature is required or necessary unless expressly so stated. Still further, exemplary or representative values and ranges may be included to assist in understanding the present application, however, such values and ranges are not to be construed in a limiting sense and are intended to be critical values or ranges only if so expressly stated.

[0083] The treatment techniques, methods, and steps described or suggested herein or in references incorporated herein may be performed on a living animal or on a non-living simulation, such as on a cadaver, cadaver heart, anthropomorphic ghost, or simulator (e.g., with the body parts, or tissue being simulated).

[0084] Any of the various systems, devices, apparatuses, etc. in this disclosure may be sterilized (e.g., with heat, radiation, ethylene oxide, hydrogen peroxide) to ensure they are safe for use with patients, and the methods herein may comprise sterilization of the associated system, device, apparatus, etc.; e.g., with heat, radiation, ethylene oxide, hydrogen peroxide. 1

Claims

Claims:

1. A method of non-invasively determining a total hemoglobin content of blood within a tissue region of a subject, comprising: non-invasively sensing a tissue region of a subject during a period of time using a near infrared spectrophotometric (NIRS) tissue oximeter, the sensing producing first signals representative of a NIRS index of the blood within the tissue region during the period of time; measuring a blood pressure level of the subject using a blood pressure sensing device during the period of time, the measuring of the blood pressure level producing second signals representative of the blood pressure level of the subject during the period of time; determining whether a cerebral autoregulation state of the subject is within an autoregulation zone of the subject during the period of time or outside of the autoregulation zone of the subject during the period of time; and determining a total hemoglobin content of blood within the tissue region (NIRS circulatory THb value) using the first signals when the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject during the period of time.

2. The method of claim 1, further comprising identifying AR zone acceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject, and AR zone unacceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be outside of the autoregulation zone of the subject; and wherein the step of determining the NIRS circulatory THb value uses the first signals produced during the AR zone acceptable portions of the period of time.

3. The method of claim 2, wherein the step of determining the NIRS circulatory THb value does not use the first signals produced during the AR zone unacceptable portions of the period of time.

4. The method of claim 2, wherein the step of determining the NIRS circulatory THb value uses only the first signals produced during the AR zone acceptable portions of the period of time.

5. The method of claim 2, wherein the first signals produced during the AR zone acceptable portions of the period of time are separated from the first signals produced during the AR zone unacceptable portions of the period of time.

6. The method of claim 5, wherein the first signals produced during the AR zone unacceptable portions of the period of time are discarded.

7. The method of claim 2, wherein the step of determining whether the cerebral autoregulation state of the subject is within the autoregulation zone of the subject during the period of time or outside of the autoregulation zone of the subject during the period of time utilizes the first signals and the second signals.

8. The method of claim 2, further comprises the step of producing an operator flag in the event a said AR zone unacceptable portion of the period of time is identified.

9. The method of claim 8, wherein the step of producing an operator flag includes performing a calibration of the NIRS tissue oximeter.

10. A system for non-invasively determining a total hemoglobin content of blood within a tissue region of a subject, comprising: a near infra-red spectroscopy (NIRS) tissue oximeter; a blood pressure sensing device; and a controller in communication with the NIRS tissue oximeter and the blood pressure sensing device, the controller including at least one processor and a memory device configured to store instructions, the stored instructions when executed cause the controller to: control the NIRS tissue oximeter to sense a tissue region of the subject during a period of time, and to produce first signals representative of a NIRS index sensed within the tissue region during the period of time;control the blood pressure sensing device to measure a blood pressure level of the subject during the period of time, and to produce second signals representative of the blood pressure level of the subject during the period of time; determine whether a cerebral autoregulation state of the subject is within an autoregulation zone of the subject during the period of time or outside of the autoregulation zone of the subject during the period of time; and determine a total hemoglobin content of blood within the tissue region (NIRS circulatory THb value) using the first signals when the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject during the period of time.

11. The system of claim 10, wherein the stored instructions when executed cause the controller to identify AR zone acceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be within the autoregulation zone of the subject, and AR zone unacceptable portions of the period of time in which the cerebral autoregulation state of the subject is determined to be outside of the autoregulation zone of the subject; and wherein the determination of the NIRS circulatory THb value uses the first signals produced during the AR zone acceptable portions of the period of time.

12. The system of claim 11, wherein the determination of the NIRS circulatory THb value does not use the first signals produced during the AR zone unacceptable portions of the period of time.

13. The system of claim 11, wherein the determination of the NIRS circulatory THb value uses only the first signals produced during the AR zone acceptable portions of the period of time.

14. The system of claim 11, wherein the stored instructions when executed cause the controller to separate the first signals produced during the AR zone acceptable portions of the period of time from the first signals produced during the AR zone unacceptable portions of the period of time.

15. The system of claim 14, wherein the stored instructions when executed cause the controller to discard the first signals produced during the AR zone unacceptable portions of the period of time.

16. The system of claim 11, wherein the determination of whether the cerebral autoregulation state of the subject is within the autoregulation zone of the subject during the period of time or outside of the autoregulation zone of the subject during the period of time utilizes the first signals and the second signals.

17. The system of claim 11, wherein the stored instructions when executed cause the controller to produce an operator flag in the event a said AR zone unacceptable portion of the period of time is identified.

18. The system of claim 17, wherein the stored instructions when executed cause the controller to perform a calibration of the NIRS tissue oximeter when the flag is produced.

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