Systems and methods for taking into account confounding factors in determining physiological parameters or conditions

Abstract

A system and method for determining a target physiological parameter of a subject is provided. The method includes sensing a subject with a first sensing device, a second sensing device, and a third sensing device, the first sensing device, the second sensing device, and the third sensing device being configured to sense a first physiological parameter and a second physiological parameter and a target physiological parameter during a period of time, respectively, generating a corresponding first physiological data signal, a corresponding second physiological data signal and a target physiological data signal; determining the presence or absence of a confounding factor that interferes with the determination of the target physiological parameter; advancing the first physiological data signal, the second physiological data signal and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelving the first physiological data signal, the second physiological data signal and the target physiological data signal generated in the presence of the confounding factor; and f) determining a value of the target physiological parameter using the first data signal, the second data signal and the target data signal generated in the absence of the confounding factor.

Description

Background Art 1. Technical Field

[0001] The present disclosure relates generally to medical devices and methods, and in particular to medical devices and methods for accounting for confounding factors in the determination of a physiological parameter or condition.

[0002] 2. Background Information

[0003] The determination of a physiological parameter or condition is often dependent on the determination of other physiological parameters. Many times, physiological parameters are subject to unrelated influences (referred to herein as "confounding factors"). For example, a first physiological parameter may increase or decrease due to the influence of a confounding factor. Using this first physiological parameter to determine a second physiological parameter may adversely affect or interfere with the determination of the second physiological parameter; for example, the determination may be less accurate due to the influence of a confounding factor. The autoregulatory state is an example of a physiological condition that may be affected by factors independent of the subject's autoregulatory system. Multiple factors (e.g., hardening of the arteries that occurs with age) may change the characteristics of the vascular reactivity response, and these factors, in turn, may change the related autoregulatory characteristics. Therefore, the autoregulatory range of blood flow due to changed blood pressure may vary between subjects and cannot be assumed to be constant. In addition, the physiological parameter data used to determine or measure the autoregulatory state of a subject may be affected by factors independent of the subject's autoregulatory system. For example, one or more NIRS indices (e.g., tissue oxygen saturation (StO2), relative total hemoglobin concentration per tissue volume (rTHb), differential changes in oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb), HbD (i.e., O2Hb-HHb), etc.) may be at levels that are not attributable to autoregulation. In these cases, autoregulatory determinations or measurements made using these values ​​may negatively impact the accuracy of the autoregulatory determinations or measurements. As another example, if the subject's blood carbon dioxide level is outside the normal range (normocapnia), the accuracy of the autoregulatory determinations or measurements may be negatively impacted.

[0004] What is needed is an apparatus and method that takes into account one or more confounding factors during the determination of a physiological parameter or condition. Summary of the invention

[0005] According to one aspect of the present disclosure, a method for determining a target physiological parameter of a subject is provided. The method comprises: a) sensing the subject using a first sensing device configured to sense a first physiological parameter, the first sensing device generating a first physiological data signal representing the first physiological parameter during a time period; b) sensing the subject using a second sensing device configured to sense a second physiological parameter, the second sensing device generating a second physiological data signal representing the second physiological parameter during the time period; c) sensing the subject using a third sensing device configured to sense a target physiological parameter, the third sensing device generating a target physiological data signal representing the target physiological parameter during the time period; d) determining interference with the determination of the target physiological parameter The present invention relates to a method for determining the presence or absence of a confounding factor, the determination using the first physiological data signal, the second physiological data signal, and the target physiological data signal; e) advancing the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelving the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor; and f) determining the value of the target physiological parameter using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor.

[0006] In any of the aspects or embodiments described above and herein, the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor are not used in the step of determining the value of the target physiological parameter.

[0007] In any of the aspects or embodiments described above and herein, the step of determining the presence or the absence of the confounding factor may include comparing processed signals representing the first physiological data signal, the second physiological data signal, and the target physiological data signal.

[0008] In any of the aspects or embodiments described above and herein, the step of determining the presence or the absence of the confounding factor may use a frequency domain method.

[0009] In any of the aspects or embodiments described above and herein, the step of determining the presence or absence of the confounding factor may include determining a first coherence between the first physiological data signal and the target physiological data signal and a second coherence between the second physiological data signal and the target physiological data signal.

[0010] In any of the aspects or embodiments described above and herein, the first coherence may be based on a single frequency band.

[0011] In any of the aspects or embodiments described above and herein, the first coherence may represent coherence values ​​at different individual frequencies within the single frequency band.

[0012] In any of the aspects or embodiments described above and herein, the first coherence may be based on a plurality of frequency bands.

[0013] In any of the aspects or embodiments described above and herein, the first coherence may collectively represent a respective coherence value from each respective frequency band of the plurality of frequency bands.

[0014] In any of the aspects or embodiments described above and herein, the method may further include determining a first trend of the first physiological parameter, a second trend of the second physiological parameter, and a third trend of the target physiological parameter, and comparing the first trend, the second trend, and the third trend relative to each other.

[0015] In any of the aspects or embodiments described above and herein, the step of determining the presence or the absence of the confounding factor may utilize one or more polarity filters configured to evaluate the first trend, the second trend, and the third trend.

[0016] In any of the aspects or embodiments described above and herein, the step of determining the presence or absence of the confounding factor may use an index table.

[0017] In any of the aspects or embodiments described above and herein, the step of determining the presence or the absence of the confounding factor may use a correlation method.

[0018] In any of the aspects or embodiments described above and herein, the shelving step may include discarding the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor.

[0019] In any of the aspects or embodiments described above and herein, steps a through f may be performed on a continuous basis during the time period.

[0020] In any of the aspects or embodiments described above and herein, the target physiological parameter may be related to the sensed total hemoglobin concentration (THb) per tissue volume.

[0021] In any of the aspects or embodiments described above and herein, the target physiological parameter may be a relative total hemoglobin concentration (rTHb) per tissue volume of the sensed tissue.

[0022] In any of the aspects or embodiments described above and herein, the third sensing device may be a near infrared spectroscopy (NIRS) tissue oximeter.

[0023] In any of the aspects or embodiments described above and herein, the first physiological parameter may be related to the subject's blood pressure, and the first sensing device is a blood pressure sensing device.

[0024] In any of the aspects or embodiments described above and herein, the second physiological parameter may be related to the subject's heart rate.

[0025] According to one aspect of the present disclosure, a system for determining a target physiological parameter of a subject is provided. The system includes a first sensing device, a second sensing device, a third sensing device, and a system controller. The first sensing device is configured to continuously sense a first physiological parameter during a time period, and is configured to generate a first physiological data signal representing the first physiological parameter during the time period. The second sensing device is configured to continuously sense a second physiological parameter during the time period, and is configured to generate a second physiological data signal representing the second physiological parameter during the time period. The third sensing device is configured to continuously sense a target physiological parameter during the time period, and is configured to generate a target physiological data signal representing the target physiological parameter during the time period. The system controller communicates with the first sensing device, the second sensing device, and the target sensing device. The system controller includes at least one processor and a memory device configured to store instructions, which when executed cause the system controller to: a) determine the presence or absence of a confounding factor that interferes with the determination of the target physiological parameter, the determination using the first physiological data signal, the second physiological data signal, and the target physiological data signal; b) advance the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelve the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor; and c) determine the value of the target physiological parameter using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor.

[0026] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine the value of the target physiological parameter without using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor.

[0027] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine the presence or absence of the confounding factor using a comparison of processed signals representing the first physiological data signal, the second physiological data signal, and the target physiological data signal.

[0028] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine the presence or the absence of the confounding factor using a frequency domain method.

[0029] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine the presence or absence of the confounding factor and further cause the system controller to determine a first coherence between the first physiological data signal and the target physiological data signal and a second coherence between the second physiological data signal and the target physiological data signal.

[0030] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine a first trend of the first physiological parameter, a second trend of the second physiological parameter, and a third trend of the target physiological parameter, and compare the first trend, the second trend, and the third trend relative to each other.

[0031] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine the presence or absence of the confounding factor using one or more polarity filters configured to evaluate the first trend, the second trend, and the third trend.

[0032] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to use an index table to determine the presence or the absence of the confounding factor.

[0033] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to determine the presence or the absence of the confounding factor using a correlation method.

[0034] In any of the aspects or embodiments described above and herein, the shelved first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor may be discarded.

[0035] In any of the aspects or embodiments described above and herein, the stored instructions, when executed, may cause the system controller to perform functions a through c on a continuous basis during the time period.

[0036] According to another aspect of the present disclosure, a method for determining a target physiological parameter of a subject is provided, the method comprising the following steps: a) sensing “N” number of physiological parameters of the subject, wherein “N” is an integer equal to or greater than three, the sensing generating “N” groups of physiological data signals, and each physiological data signal group corresponds to a corresponding one of the “N” number of physiological parameters during a time period, and wherein one of the “N” number of physiological parameters is a target physiological parameter; b) determining the presence or absence of a confounding factor interfering with the determination of the target physiological parameter, the determination using the “N” group of physiological data signals of the target physiological parameter group including the physiological data signals; c) advancing the “N” group of physiological data signals generated in the absence of the confounding factor for further processing, and shelving the “N” group of physiological data signals generated in the presence of the confounding factor; and d) determining the value of the target physiological parameter using the “N” group of physiological data signals generated in the absence of the confounding factor.

[0037] According to another aspect of the present disclosure, a non-transitory computer-readable medium is provided, the medium storing executable instructions, which when executed, cause at least one processor to: a) control a first sensing device, the first sensing device being configured to sense a first physiological parameter to sense a subject, and being configured to generate a first physiological data signal representing the first physiological parameter during a time period; b) control a second sensing device, the second sensing device being configured to sense a second physiological parameter to sense a subject, and being configured to generate a second physiological data signal representing the second physiological parameter during the time period; c) control a third sensing device, the third sensing device being configured to sense a target physiological parameter to sense a subject, and being configured to generate a second physiological data signal representing the second physiological parameter during the time period; d) determining the presence or absence of a confounding factor that interferes with the determination of the target physiological parameter, the determination using the first physiological data signal, the second physiological data signal, and the target physiological data signal; e) advancing the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelving the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor; and f) determining the value of the target physiological parameter using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor.

[0038] Unless otherwise clearly indicated, the aforementioned features and elements can be combined in various combinations without exclusivity. According to the following description and accompanying drawings, these features and elements and their operation will become more apparent. However, it should be understood that the following description and accompanying drawings are intended to be exemplary in nature and non-restrictive. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 is a schematic representation of an automatic adjustment system according to one embodiment of the present disclosure.

[0040] Figure 2 is a schematic representation of an automatic adjustment system according to one embodiment of the present disclosure.

[0041] Figure 3 is a schematic representation of an exemplary frequency domain method.

[0042] Figure 4 is a schematic flow chart of an embodiment of the present disclosure.

[0043] Figure 5 is an exemplary index table embodiment that may be used with the present disclosure, illustrating exemplary data from a variety of different situations.

[0044] Figure 6 is a schematic flow chart of an embodiment of the present disclosure.

[0045] Figure 7 is a schematic flow chart of an embodiment of the present disclosure.

[0046] Figure 8 is a schematic flow chart of an embodiment of the present disclosure.

[0047] Fig. 9 is a schematic flow chart of an embodiment of the present disclosure.

[0048] Fig.10 is an exemplary index table embodiment that may be used with the present disclosure, illustrating exemplary data from a variety of different situations.

[0049] Fig.11 It is a schematic diagram of physiological parameter values ​​and time.

[0050] Fig.12 is a graph of physiological parameter values ​​versus time. DETAILED DESCRIPTION

[0051] The present disclosure provides a system 20 ("CFA system"), method, and computer-readable medium for considering one or more confounding factors during the determination of a physiological parameter. Non-limiting examples of physiological parameters that can be determined using the present disclosure include NIRS index, autoregulatory state, pain, etc. as defined herein. Embodiments of the present disclosure can be implemented in a variety of different ways. In some embodiments, the present disclosure can be implemented to determine whether there are one or more confounding factors that can negatively affect the determination of the physiological parameter, and if so, consider the sensed data collected when the one or more confounding factors are present. In this way, the physiological parameter can be determined to be unaffected by the confounding factor. Non-limiting examples of physiological parameter determinations that may be affected by one or more confounding factors include determinations of different types of total hemoglobin content, determinations of the autoregulatory state of a subject, and the like. As used herein, the term "confounding factor" refers to a physiological parameter or condition that affects or interferes with the determination of another physiological parameter in a manner that can negatively affect the determination of another physiological parameter when present; for example, due to the influence of the confounding factor, the determination of a physiological parameter that is susceptible to the influence from the confounding factor may be less accurate. The present disclosure is configured to account for confounding factors, when present, and thereby mitigate any impact they may otherwise have on the aforementioned determinations, thereby resulting in improved physiological parameter determinations.

[0052] Figure 1 and Figure 2Schematically illustrated are non-limiting examples of embodiments of the disclosed system 20, including their respective system components. The illustrated embodiments of the system 20 are not intended to be limiting; for example, alternative system 20 embodiments may include additional components, or alternative components, or different component implementations, etc. In some embodiments, the system 20 includes system components such as a tissue oximeter 22 and a system controller 24, and may include other system components such as a blood pressure sensing device 26, a carbon dioxide (CO2) sensor (e.g., a transcutaneous blood gas monitor or an exhaled bread CO2 sensor, etc.), a heart rate monitor (e.g., an electrocardiogram-"ECG", etc.), a device configured to sense hemodynamic parameters (such as vascular reactivity, cardiac output, blood flow, etc.), one or more output devices, and one or more input devices. In some embodiments, these system components may be integrated into a single system 20 device; for example, a system controller 24 integrally connected to sensing hardware (e.g., hardware associated with the tissue oximeter 22, hardware associated with the BP sensing device 26, etc.). In other embodiments, the system 20 may include a system controller 24 and may be configured to communicate with independent system components (e.g., receive signal data from and / or send signal data to independent system components). In other words, in embodiments in which the system 20 includes independent system components, the system 20 may be configured to communicate with a tissue oximeter 22 that can operate independently of the system 20, with a BP sensing device 26 that can operate independently of the system 20, with a CO2 sensor that can operate independently of the system 20, with a heart rate monitor that can operate independently of the system 20, and the like. In other embodiments, the system 20 may include some combination of these system components in an integrated and independent form. In those embodiments in which one or more of the foregoing system components are independent of the system 20, such independent system components may communicate with the system controller 24 in any manner.

[0053] The tissue oximeter 22 may be a device configured to continuously sense tissue oxygenation parameters (which may be individually referred to as "NIRS indices" or collectively referred to as "NIRS indices" hereinafter) that vary with blood flow in the subject's tissue; for example, tissue oxygen saturation (StO2), total hemoglobin concentration per tissue volume (THb), relative total hemoglobin concentration per tissue volume (rTHb), deoxyhemoglobin (HHb), relative deoxyhemoglobin (rHHb), oxygenated hemoglobin (O2Hb), relative oxygenated hemoglobin (rO2Hb), deoxyhemoglobin (HHb), etc. For clarity, the present disclosure is not limited to these specific NIRS indices, and the various acronyms used herein (e.g., StO2, THb, rTHb, HHb, rHHb, O2Hb, and rO2Hb) are non-limiting examples of acronyms that a person skilled in the art may use to refer to the corresponding NIRS indices. Those skilled in the art will recognize that different acronyms are sometimes used to refer to the same NIRS index.

[0054] An example of an acceptable tissue oximeter 22 is a near infrared spectroscopy ("NIRS") type tissue oximeter ("NIRS tissue oximeter"). 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 herein in its entirety) disclose non-limiting examples of non-invasive NIRS tissue oximeters 22 that may be used in the present disclosure. As used herein, the term "continuously" (used to describe that the tissue oximeter 22 continuously senses tissue oxygenation parameters) means that the tissue oximeter 22 senses and collects subject data on a periodic basis during a monitoring period that is frequent enough to be considered clinically continuous. For example, some tissue oximeters sample data every ten seconds or less, and may be configured to sample data more frequently (e.g., every two seconds or less).

[0055] The tissue oximeter 22 includes one or more sensors that communicate with the controller portion. Each sensor includes one or more light sources (e.g., light emitting diodes or "LEDs") and one or more light detectors (e.g., photodiodes, etc.). The light sources are configured to emit light at different wavelengths, for example, wavelengths of light in the red or near infrared range; 400 to 1000 nm. In some sensor embodiments, the sensor may be configured to include a light source, a near detector, and a far detector. The near detector is disposed closer to the light source than the far detector. A non-limiting example of such a sensor is disclosed in U.S. Pat. No. 8,965,472, which is incorporated herein by reference in its entirety as indicated above. The tissue oximeter 22 is configured to communicate with the system controller 24; for example, a signal representing one or more NIRS indices (or a signal that can be used to determine one or more NIRS indices) is sent to the system controller 24, and a control signal may be received from the system controller 24, etc. Communication between the tissue oximeter 22 and the system controller 24 may be performed by any known means; for example, hard wiring, wireless, etc.

[0056] The NIRS tissue oximeter 22 may utilize one or more algorithms to determine 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 the 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 in whole or in part with the present disclosure, and are all incorporated herein by reference in their respective entireties.

[0057] The blood pressure sensing device 26 ("BP sensing device 26") can be any sensor or device configured to continuously determine the blood pressure (e.g., arterial blood pressure) of a subject. For example, the BP sensing device 26 can be a device 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. However, the present disclosure is not limited to these specific examples of using blood pressure sensing / measuring / monitoring devices. The BP sensing device 26 is configured to generate a blood pressure value signal indicating the blood pressure (e.g., arterial blood pressure) of the subject during a period of time. The BP sensing device 26 is configured to communicate with the system controller 24; for example, the blood pressure value signal is sent to the system controller 24, and a control signal can be received from the system controller 24, etc. Communication between the BP sensing device 26 and the system controller 24 can be performed by any known means; for example, hard wiring, wireless, etc. As used herein, the term "continuously" (used to describe that BP sensing device 26 continuously determines the blood pressure of the subject) means that BP sensing device 26 senses and collects subject data during the monitoring period on a periodic basis that is frequent enough to be considered clinically continuous. For example, some BP sensing devices sample data every ten seconds or less, and may be configured to sample data more frequently (e.g., every two seconds or less).

[0058] One or both of BP sensing device 26 or tissue oximeter 22 may be further configured to measure other parameters, such as respiratory rate, respiratory effort, heart rate (HR), etc. BP sensing device 26 and tissue oximeter 22 may be placed on the same or different parts of the patient's body.

[0059] As described above, the system 20 includes a system controller 24 and may include one or more output devices and one or more input devices. Non-limiting examples of input devices include a keyboard, touch pad, or other device in which a user can enter data, commands, or signal information, or a port configured to communicate with an external input device via a hardwired or wireless connection, etc. Non-limiting examples of output devices include any type of display, printer, or other device configured to display or transmit information or data generated by the system 20. The system 20 can be configured to connect to an input device or an output device via a hardwired connection or a wireless connection.

[0060] In some embodiments, the system controller 24 may be configured (e.g., via circuitry) to process various received signals (received from integrated or independent components) and may be configured to generate certain signals thereto; for example, signals configured to control one or more components within the system 20. Alternatively, the system 20 may be configured such that signals from the respective components are sent to one or more intermediate processing devices, and the intermediate processing devices, in turn, may provide processed signals or data to the system controller 24. As will be explained below, the system controller 24 may also be configured to execute stored instructions (e.g., algorithmic instructions) that cause the system 20 to perform the steps or functions described herein, generate data (e.g., determine physiological parameter values ​​in a manner that takes into account one or more confounding factors, etc.), communicate, etc.

[0061] The system controller 24 may include any type of computing device, computing circuit, or any type of process or processing circuit capable of executing a series of instructions stored in a memory. The controller may include multiple processors and / or multi-core CPUs, and may include any type of processor, such as a microprocessor, a digital signal processor, a coprocessor, a microcontroller, a microcomputer, a central processing unit, a field programmable gate array, a programmable logic device, a state machine, a logic circuit, an analog circuit, a digital circuit, etc., and any combination thereof. For example, in those embodiments of the system 20 described above that include multiple components integrated with the system 20 (e.g., BP sensing device 26, tissue oximeter 22, CO2 sensor, etc.), the controller may include multiple processors; for example, independent processors dedicated to each respective component, any and all of which may communicate with the central processor of the system 20 that coordinates the functions of the system 20. The instructions stored in the memory may represent one or more algorithms for controlling the system 20, and the stored instructions are not limited to any particular form (e.g., program files, system data, buffers, drivers, utilities, system programs, etc.), as long as they can be executed by the controller. These instructions are configured to perform the methods and functions described herein.

[0062] The memory may be a machine-readable storage medium configured to store instructions that, when executed by one or more processors, cause the one or more processors to perform certain functions or cause the performance of certain functions. The memory may be a single memory device or multiple memory devices. The memory device may be a non-transitory device and may include a storage area network, a network attached storage device, and a disk drive, a read-only memory, a random access memory, a volatile memory, a non-volatile memory, a static memory, a dynamic memory, a flash memory, a cache memory, and / or any device that stores digital information. Based on a review of the present disclosure, it should be understood by those skilled in the art that the implementation of the controller may be implemented via the use of hardware, software, firmware, or any combination thereof.

[0063] The implementation of the techniques, blocks, steps, and means described herein can be accomplished in various ways. For example, these techniques, blocks, steps, and means can be implemented in hardware, software, or a combination thereof. For hardware implementations, a processing device configured to implement the described functions and steps (e.g., by executing stored instructions) can 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, microcontrollers, microprocessors, or other electronic units designed to perform the functions described herein and / or any combination thereof.

[0064] Embodiments of the present disclosure may be described herein as processes depicted as flow charts, flow diagrams, block diagrams, and the like. Although any of these structures may describe the operations as a sequential process, many of these operations may be performed in parallel and / or concurrently. In addition, the order of these operations may be rearranged. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, and the like.

[0065] The system components are configured to continuously sense multiple physiological parameters (e.g., tissue oximeter data, blood pressure data, heart rate, CO2 data, etc., associated with one or more NIRS indices) and generate signal data representing the multiple physiological parameters in real time. The specific functions of the system components that generate the physiological signal data (e.g., sampling rate, etc.) can be set as appropriate for the operation of the system 20, and the present disclosure is not limited to any specific component settings.

[0066] The system 20 may be configured to process this "input" physiological signal data using an algorithm based on a frequency domain approach or using an algorithm based on a correlation / regression technique or some combination thereof to produce a coherence ("COHZ") analysis, as will be described in more detail below. For ease of description, the present disclosure is described below using a frequency domain approach to produce coherence ("COHZ") values, but as indicated, the present disclosure is not limited to use of a frequency domain approach. Reference Figure 3 , the frequency domain method transforms the input physiological parameter signal data pair from the time domain (eg, via Fourier transform) to the frequency domain. Figure 3 Corresponding plots of a first physiological parameter ("C1") versus frequency and a second physiological parameter ("Cn," where "n" is an integer greater than 1) versus frequency are shown. The transformed data is further analyzed to determine the degree of coherence within a single frequency band (i.e., a single frequency band). The degree of coherence may be indicated on an arbitrarily assigned scale of zero to one (0-1), where the degree of coherence increases from zero to one (shown as a plot of coherence values ​​versus frequency). A coherence value of one indicates a stronger relationship between C1 and Cn, while coherence values ​​approaching zero indicate a decreasing relationship between C1 and Cn. The process of determining the degree of coherence (COHZ) is performed for at least two different physiological parameter pairs (e.g., C1 and Cn, C2 and Cn), and is not limited to any particular number of physiological parameter pairs; for example, the process of determining the degree of coherence (COHZ) may be performed for more than two different physiological parameter pairs - C1 and Cn, C2 and Cn, C3 and Cn, etc.

[0067] refer to Figure 4 The determined coherence values ​​for the corresponding physiological parameter pairs are then evaluated to determine whether the collected physiological parameter data is affected by confounding factors. The aforementioned evaluation can 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, etc.

[0068] An example of an index table that may be used is an index table that permits comparison of the coherence value of each physiological parameter pair relative to the coherence value of another physiological parameter pair. The index table may contain empirically collected data that permits characterization of the coherence values ​​of the physiological parameter pairs. The table may take the form of any data structure that permits the aforementioned comparison. Figure 5The table shown illustrates four example coherence value scenarios for the C1 / Cn physiological parameter pair and the C2 / Cn physiological parameter pair. In Example 1, both the C1 / Cn physiological parameter pair and the C2 / Cn physiological parameter pair are indicated as having low coherence values. The instructions stored in the memory may include information (e.g., a threshold) that can be used to determine what is a "low" coherence value, or a "high" coherence value, or an uncertain coherence value. Based on the empirical data stored in the index table, the consistency between the coherence values ​​of the C1 / Cn and C2 / Cn physiological parameter pairs (i.e., both are low) indicates that the collected physiological data is valid, not interfered with by confounding factors, and can be used in subsequent determinations of the physiological parameters (e.g., binning or otherwise processed). In Example 2, both the C1 / Cn physiological parameter pair and the C2 / Cn physiological parameter pair are indicated as having high coherence values. Based on the empirical data stored in the index table, the consistency between the coherence values ​​of the C1 / Cn and C2 / Cn physiological parameter pairs (i.e., both are high) indicates that the collected physiological data is valid, not interfered with by confounding factors, and can be used in the subsequent determination of the physiological parameters (e.g., binning or otherwise processed). In Examples 3 and 4, the C1 / Cn and C2 / Cn physiological parameter pairs are indicated as having different coherence values ​​(i.e., one high and one low). Based on the empirical data stored in the index table, the inconsistency between the coherence values ​​of the C1 / Cn and C2 / Cn physiological parameter pairs (i.e., both are high) indicates that the collected physiological data may be interfered with by confounding factors and therefore should not be used in the subsequent determination of the physiological parameters (e.g., not binned). In these cases, the collected physiological data used to determine the coherence value (determined to be interfered with by confounding factors) can be frozen (e.g., shelved) or discarded. It should be noted that the present disclosure provides information on a continuous, real-time basis. Thus, physiological data collected during a first time period may be deemed acceptable and may be used to determine a physiological parameter, followed by a second time period in which the physiological data may be deemed unacceptable and therefore not used to determine the physiological parameter. The present disclosure contemplates that the process of distinguishing physiological data that is confounded by confounding factors from physiological data that is not confounded by confounding factors may be a real-time process that occurs continuously during the sensing period. The stored instructions may cause physiological data that is not confounded by confounding factors to be binned or otherwise processed into a form (e.g., representing the value of a physiological parameter of tissue in a bin of a MAP range, etc.) that can subsequently be used to determine a physiological parameter (e.g., THb, AR, etc.) as a function of time. In this manner, the present disclosure facilitates real-time determination of physiological parameters based on data that is not confounded by confounding factors. As Figure 4As shown, physiological data that is confounded by one or more confounding factors is not binned or otherwise processed, and therefore cannot be used to determine physiological parameters in the same manner as uncontaminated physiological data. In some cases, the contaminated physiological data - now frozen (e.g., on hold) relative to the normal process of determining the physiological parameter - can be discarded, but it is not required to discard the contaminated physiological data. The contaminated physiological data is not used in the real-time determination of the physiological parameter.

[0069] refer to Figure 6 , when determining a coherence value within a single frequency band between two physiological parameters, the coherence value may vary as a function of a particular frequency within the frequency band; see, for example, Figure 3 . In some embodiments, the present disclosure may be operable to select values ​​representing coherence values ​​at different frequencies within a frequency band. For example, in some embodiments, the present disclosure may be operable to select a peak coherence value (i.e., a maximum magnitude) from the coherence values ​​at corresponding frequencies within the frequency band as a representative coherence value. This peak coherence value may then be used to determine the physiological parameter signal data for the purpose of determining the acceptability of the physiological parameter value. In some embodiments, the selected coherence values ​​within a single frequency band may be processed to produce a collective coherence parameter (hereinafter referred to as a "CP index") representing the coherence values ​​within the frequency band. The CP index may then be used to determine the physiological parameter signal data for the purpose of determining the acceptability of the physiological parameter value. A first example of how the CP index value may be determined is the averaging (or a process similar to averaging) of the coherence values ​​at selected frequencies within the frequency band. A second example of how the CP index value may be determined is a process in which the coherence values ​​at selected frequencies within the frequency band are multiplied and the square root of the product is determined to produce the CP index value. The present disclosure is not limited to these examples of determining the CP index, and alternative processes may be used to determine the CP index value. The present disclosure is also not limited to these examples of selecting values ​​that represent coherence values ​​at different frequencies within a frequency band (ie, peak COHZ, CP index).

[0070] In the above examples provided to illustrate embodiments of the present disclosure configured to evaluate physiological parameter data for the presence of confounding factors, a coherence value (e.g., peak value, CP index, etc.) of a pair of physiological parameters (e.g., C1 and Cn or C2 and Cn) is determined within a single frequency band (e.g., see Figure 3 ). refer to Figure 7 and Figure 8In some embodiments, coherence values ​​for a given pair of physiological parameters may be determined in multiple different frequency bands. For certain physiological parameters, sensing physiological parameter data in different frequency bands may produce more robust information about the physiological parameter. For example, a first frequency band having a first duration sampling window may be used to provide coherence data associated with rapid changes in the physiological parameter, a second frequency band having a second duration sampling window may be used to provide coherence data associated with changes in the physiological parameter that occur slower than those changes that may be sensed in the first frequency band (e.g., changes that are not easily determined in the first frequency band), and a third frequency band having a third duration sampling window may be used to provide coherence data associated with changes in the physiological parameter that occur slower than those changes that may be sensed in the second frequency band, etc. Other frequency bands may be selected based on their ability to assess a subject's physiological characteristic and their ability to identify coherence between the physiological characteristic and the physiological parameter under consideration.

[0071] In those cases where a coherence value for a given pair of physiological parameters (e.g., COHZ, peak COHZ, CP index, etc. at a given frequency) is determined within each of a plurality of different frequency bands, the determined coherence values ​​for the given pair of physiological parameters may be further processed to determine a collective coherence value (e.g., peak COHZ, CP index, etc.) based on the determined coherence values ​​from the different frequency bands. As an example (see Figure 7 ), the selected coherence values ​​from each frequency band for each given physiological parameter pair can be processed to produce a collective coherence value (e.g., peak COHZ or CP index, etc.) for all frequency bands for this physiological parameter pair in the manner described above.

[0072] Figure 8 The above and Figure 6 and Figure 7 More specifically, for each respective frequency band in a plurality of frequency bands, selected coherence values ​​within each of these frequency bands may be processed to produce a collective coherence parameter (e.g., peak COHZ, CP index, etc.) representing the coherence value within this frequency band. This process is repeated for each of the frequency bands for each respective pair of physiological parameters; for example, as described above in Figure 6 The collective coherence values ​​for each frequency band for a given physiological pair are then processed in the same manner to provide collective coherence values ​​(e.g., peak COHZ or CP index, etc.) for all frequency bands for this physiological pair. This process is performed for each corresponding physiological parameter pair, and the corresponding collective coherence values ​​(e.g., peak COHZ or CP index, etc.) are then passed to the evaluation of confounding factors step.

[0073] In some embodiments, the present disclosure may determine a coherence value or a value representing a coherence value (e.g., peak COHZ, CP index, etc.) over a time period and process these values ​​to determine trend information; for example, whether a physiological parameter is trending upward over a time period, or is trending downward over a time period, or remains stable over a time period. In some applications, trend information can be used to determine whether the collected physiological parameter data is acceptable and therefore can be used to determine the physiological parameter, or is unacceptable and therefore should not be used to determine the physiological parameter. For example, a physiological parameter that is increasing over a time period may be characterized as being in an increasing trend ("Incr"), a physiological parameter that is decreasing over a time period may be characterized as being in a decreasing trend ("Decr"), and a physiological parameter that is stable over a time period may be characterized as being stable ("N / C"). The relative trends between different physiological parameters may provide information about the usefulness of the collected physiological parameter data. In some embodiments, trend information may be used within a polarity filter. For example, if a first physiological parameter is trending upward and a second physiological parameter is trending downward, the fact that the two physiological parameters have opposite trending "polarities" (one decreasing, one increasing) may provide a basis for determining whether the collected physiological parameter data is acceptable or unacceptable. As another example, if the two physiological parameters are trending in the same direction (i.e., similar polarity), this may provide a basis for determining whether the collected physiological parameter data is acceptable or unacceptable. In some embodiments, the disclosed process (e.g., within stored instructions) may include a polarity filter that operates to determine whether the collected physiological parameter data is acceptable or unacceptable. The stored instructions may provide a means for determining whether a physiological parameter is trending upward, trending downward, or remaining stable; for example, a rate of change threshold, a change magnitude threshold, etc.

[0074] As described above, the present disclosure relates to a process for distinguishing physiological data that is perturbed by confounding factors from physiological data that is not perturbed by confounding factors, which process can be a real-time continuous process. The undisturbed physiological data can then be used to determine physiological parameters as a function of time. Therefore, the present disclosure, including the exemplary embodiments disclosed above, permits the determination of physiological parameters with a greater degree of certainty than would otherwise be possible without considering confounding factors. Figure 4 and Figures 6 to 9The flowchart in illustrates the present disclosure on a continuous basis; for example, processing steps may be performed continuously during a time period in which a subject is sensed to generate physiological data. The sensed physiological data is processed (e.g., "process input physiological data"), and the processed data then undergoes various additional steps indicated in the corresponding steps indicated in the corresponding process steps, including evaluating the data to determine whether it is confounded by confounding factors (if so, the data is frozen or shelved) or is not confounded by confounding factors (if so, it is advanced for further processing). The last step shown in the exemplary embodiment ("determine physiological parameters" or "determine THb" - i.e., further processing) may then include displaying the determined values ​​as a function of time; for example, in a manner similar to Fig.12 As described herein, the present disclosure may be used with a variety of different methods for determining physiological parameter values ​​and / or for displaying physiological parameter values, and is therefore not limited to any particular method for determining physiological parameter values ​​and / or for displaying physiological parameter values.

[0075] To facilitate understanding of the scope and applicability of the present disclosure, specific examples of the present disclosure are provided below. Fig. 9 Schematically illustrated is a process for evaluating physiological data collected to determine total hemoglobin data (THb) and whether there are hemodynamic confounders (e.g., changes in heart rate, changes in BP, hemodilution, etc.) that may interfere with the determination of THb. In this example, three physiological parameters are sensed (e.g., THb, BP, and HR) and two pairs of physiological parameters are utilized.

[0076] In this example, the disclosed system 20 includes a tissue oximeter 22 configured to continuously generate data representing the subject's THb, a BP sensing device configured to continuously generate data representing the subject's blood pressure, and a HR monitor configured to generate data representing the subject's heart rate. Alternatively, the system 20 may be configured to generate heart rate data using the tissue oximeter 22 or the BP sensing device. The tissue oximeter 22, the BP sensing device, and the HR monitor may be integrated into the system 20 or independent devices that communicate with the system controller 24.

[0077] The system 20 is operated to generate signal data representing the subject's THb, BP, and HR. The signal data representing the subject's THb, BP, and HR are processed by the disclosed system 20 using an algorithm based on a frequency domain method to generate a coherence analysis. The frequency domain method transforms the input physiological parameter signal data pair from the time domain (e.g., via Fourier transform) to the frequency domain (e.g., see Figure 3). In this example, the physiological parameter signal data pairs are BP and THb and HR and THb. The process then determines the degree of coherence within a single frequency band or within multiple frequency bands, as described above. If the system 20 is configured to determine the coherence in a single frequency band, a single coherence value may be determined for the BP and THb pair, and a single coherence value may be determined for the HR and THb pair. Those coherence values ​​are then evaluated to determine whether the THb data is interfered with by confounding factors. If the system 20 is configured to determine the coherence in multiple frequency bands, a coherence value may be determined for each frequency band, and a collective coherence value (e.g., peak COHZ) or a value that collectively represents the coherence value for the frequency band (e.g., CP index) may be determined. The collective coherence value is then evaluated to determine whether the THb data is interfered with by confounding factors.

[0078] As described above, the disclosed system 20 can be configured to evaluate the coherence value in a variety of different ways to determine whether the THb data is confounded by confounding factors. In some embodiments, an index table containing empirically collected data can be used to characterize the corresponding coherence value. For example, as described above and Figure 5 As shown, the coherence value can be characterized as low, high, or uncertain. The index table can be configured to generate an output indicating whether the input physiological parameter data is interfered with by confounding factors. The output can be binary; that is, if it is determined that the input physiological parameter data (e.g., THb, BP, and HR) is interfered with by confounding factors, the data is shelved (i.e., frozen) or discarded, or if it is determined that the input physiological parameter data is not interfered with by confounding factors, the data is advanced for determining the subject's THb.

[0079] refer to Fig.10 As another example, the system 20 may be configured to determine the above coherence values ​​over a period of time and perform an evaluation. Physiological parameter (e.g., THb, BP, and HR) data may be stored and trend data may be developed for each physiological parameter. The trend data may then be used as a basis for determining whether the physiological parameter data of interest (i.e., THb) is interfered with by confounding factors. Fig.10 The input table shown illustrates trend data for each physiological parameter for ten (10) different cases. Fig.10The input table shown includes a binary determination column, where for each case, a determination is indicated whether the physiological parameter data of interest (i.e., THb) is valid for use based on the physiological parameter pair coherence and polarity. In cases 1, 2, and 7 to 10, the input physiological parameter data (e.g., THb, BP, and HR) is determined to be not confounded by confounding factors, and the data can be passed for use in the determination of the subject's THb. In cases 3 to 6, the input physiological parameter data (e.g., THb, BP, and HR) is determined to be confounded by one or more confounding factors, and the data is either set aside ("frozen") or discarded, and therefore will not be passed for use in the determination of the subject's THb.

[0080] As described above, the evaluation of whether the physiological parameter data of interest (THb in this example) is valid for use in the determination of the physiological parameter of interest may be performed in a variety of different ways and is therefore not limited to the use of an index table.

[0081] For clarity, the examples provided above are given in the context of physiological parameter data collected for the purpose of generating a THb determination. The present disclosure is not limited to determining the impact of assessing confounding factors on physiological parameter data collected for the purpose of generating a THb determination. Instead, the present disclosure can be used to assess the impact of confounding factors on a variety of different physiological parameters.

[0082] As described above, the present disclosure relates to a process (which may be a real-time continuous process) of distinguishing physiological data that is interfered with by confounding factors from physiological data that is not interfered with by confounding factors, and thereby permitting the determination of physiological parameters based solely on the uninterrupted physiological data. In some cases, including sensed physiological data that is interfered with by confounding factors in the determination of physiological parameters may result in a determined physiological parameter value that is different from a value that would be determined based solely on the uninterrupted physiological data. Fig.11A diagram of physiological parameter values ​​versus time is schematically illustrated. The figure schematically illustrates two data curves; one solid line, one dotted line. The solid curve represents the physiological parameter values ​​based on physiological data that are not disturbed by confounding factors as a function of time. The dotted curve represents the physiological parameter values ​​based on physiological data without checking confounding factors as a function of time. Initially (i.e., from t0 to t1), the two data curves are parallel and substantially equal (separated in the figure so that they can be seen). Between t1 and t2, the sensed physiological data is disturbed by confounding factors. The disturbed confounding factor data causes the determined physiological parameter to have a data value different from the data value it would have if the physiological parameter value was determined based only on the uninterrupted physiological data. The difference between the disturbed physiological parameter value and the uninterrupted physiological parameter value is identified on the figure as an offset caused by the confounding factor. In the case where the physiological parameter value is determined based on the binned physiological data, the influence of the disturbed physiological sensing data (if included) may have an influence after the time period when the confounding factor event occurs; for example, after t2.

[0083] Fig.12 is a graph of physiological parameter values ​​(e.g., THb) versus time. The figure schematically illustrates a confounding factor event starting from about twelve minutes (12 minutes) and extending to about twenty-one minutes (21 minutes). As described above, in accordance with the present disclosure, physiological sensing data can be continuously evaluated to determine the presence of confounding factors. After determining the presence of confounding factors (e.g., at the 12 minute mark), the sensed physiological data is frozen / put on hold and is not used for any determination of the physiological parameter (e.g., THb). The displayed data since the point of "freezing" the data (e.g., during the confounding event period) can be displayed in a variety of ways; for example, the data can be displayed in a manner indicating the presence of interfering physiological sensing data; or can be displayed as a constant value based on the last uninterfered physiological parameter value, or other. The present disclosure is not limited to these display options. When it is determined that the sensed physiological data is no longer interfered by the confounding factor (e.g., at the 21 minute mark), the system 20 can resume using the sensed physiological data (now uninterfered) in the determination of the physiological parameter, and the determined physiological parameter value can be displayed again.

[0084] In some embodiments, the system instructions, when executed, may cause the controller to use the effective physiological parameter value just before the start of the confounding factor event (i.e., the 12 minute mark) and the effective physiological parameter value just after the end of the confounding factor event (i.e., the 21 minute mark) to determine a displayed value curve between the start and end of the confounding factor event. For example, the system instructions may determine the difference between the physiological parameter value at the start of the confounding factor (i.e., the 12 minute mark) and the physiological parameter value at the end of the confounding factor (i.e., the 21 minute mark), and use this difference to generate a displayed value curve between the start and end of the confounding factor event; for example, the displayed values ​​may be a straight line or otherwise. The present disclosure is not limited to any particular method for displaying physiological parameter values ​​determined in accordance with the present disclosure.

[0085] Although the principles of the present disclosure have been described above in conjunction with specific devices and methods, it should be clearly understood that this description is only carried out by way of example, rather than as a limitation on the scope of the present disclosure. Specific details are given in the above description to provide a thorough understanding of the embodiments. However, it should be understood that the embodiments can be practiced without these specific details.

[0086] It is noted that the embodiments may be described as a process depicted as a flow chart, a flowchart, a block diagram, etc. Although any of these structures may describe the operations as a sequential process, many of these operations may be performed in parallel or concurrently. In addition, the order of these operations may be rearranged. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0087] The singular forms "a", "an", and "the" refer to one or more than one, unless the context clearly indicates otherwise. For example, the term "comprising a sample" includes a single or multiple samples and is considered equivalent to the phrase "comprising at least one sample". The term "or" refers to a single element or a combination of two or more elements of the stated alternative elements, unless the context clearly indicates otherwise. As used herein, "comprising" means "including". Thus, "comprising A or B" means "comprising A, or B, or A and B", without excluding additional elements.

[0088] It is noted that various connections between elements are set forth in this specification and the drawings (the contents of which are incorporated by reference into this disclosure). It is noted that these connections are general and, unless otherwise specified, may be direct or indirect, and this specification is not intended to be limiting in this regard. Any reference to attaching, fixing, connecting, etc. may include permanent, removable, temporary, partial, complete, and / or any other possible attachment options.

[0089] No element, component, or method step in this disclosure is intended to be dedicated to the public, regardless of whether the element, component, or method step is explicitly stated in the claims. No claim element herein shall be interpreted under the provisions of 35 U.S.C. 112(f) unless the element is explicitly stated using the phrase "means for..." As used herein, the term "comprises" or any other variation thereof is intended to cover non-exclusive inclusions, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements, but may also include other elements that are not explicitly listed or inherent to the process, method, article, or apparatus.

[0090] Although various inventive aspects, concepts and features of the present disclosure may be described and illustrated herein as being embodied in combination in exemplary embodiments, these various aspects, concepts and features may be used in many alternative embodiments 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. Further, although various alternative embodiments of various aspects, concepts and features of the present disclosure may be described herein, such as alternative materials, structures, configurations, methods, devices and components, etc., such descriptions are not intended to be a complete or exhaustive list of available alternative embodiments, whether currently known or later developed. A person skilled in the art may easily make one or more of the inventive aspects, concepts and features suitable for use in additional embodiments and within the scope of the present application, even if such embodiments are not explicitly disclosed herein. For example, in the above exemplary embodiments within the specific embodiments section of this specification, elements may be described as separate units and are shown as being independent of each other for ease of description. In alternative embodiments, such elements may be configured as combined elements. It should be further noted that various methods or process steps of embodiments of the present disclosure are described herein. The description may present methods and / or process steps as a specific sequence. However, to the extent that the method or process does not rely on the specific order of steps listed herein before, the method or process should not be limited to the specific sequence of steps described. As will be appreciated by those of ordinary skill in the art, other step sequences are also possible. Therefore, the specific order of steps set forth in this description should not be construed as limiting.

[0091] In addition, although some features, concepts or aspects of the present disclosure may be described herein as preferred arrangements or methods, such descriptions are not intended to indicate that such features are required or essential unless explicitly stated. Further, exemplary or representative values ​​and ranges may be included to aid in understanding the present application, however, such values ​​and ranges are not to be interpreted as limiting and are intended to be critical values ​​or ranges only when so explicitly stated.

[0092] The treatment techniques, methods, and procedures described or suggested herein or in references incorporated herein may be performed on living animals or in non-living simulations, such as on cadavers, cadaver hearts, anthropomorphic phantoms, or mimics (e.g., having simulated body parts or tissues).

[0093] Any of the various systems, devices, equipment, etc. in the present disclosure may be sterilized (e.g., using heat, radiation, ethylene oxide, hydrogen peroxide) to ensure that they are safe for use by patients, and the methods herein may include sterilizing the associated systems, devices, equipment, etc.; e.g., using heat, radiation, ethylene oxide, hydrogen peroxide.

Claims

1. A method for determining a target physiological parameter of a subject, the method comprising: a) sensing a subject using a first sensing device configured to sense a first physiological parameter, the first sensing device generating a first physiological data signal representing the first physiological parameter during a time period; b) sensing the subject using a second sensing device configured to sense a second physiological parameter, the second sensing device generating a second physiological data signal representative of the second physiological parameter during the time period; c) sensing the subject using a third sensing device configured to sense a target physiological parameter, the third sensing device generating a target physiological data signal representative of the target physiological parameter during the time period; d) determining the presence or absence of a confounding factor that interferes with the determination of the target physiological parameter, the determining using the first physiological data signal, the second physiological data signal, and the target physiological data signal; e) advancing the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelving the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor; as well as f) determining a value of the target physiological parameter using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor. 2 . The method according to claim 1 , wherein the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor are not used in the step of determining the value of the target physiological parameter. 3 . The method of claim 1 , wherein the step of determining the presence or absence of the confounding factor comprises comparing processed signals representing the first physiological data signal, the second physiological data signal, and the target physiological data signal. The method according to claim 1 , wherein the step of determining the presence or the absence of the confounding factor uses a frequency domain method.

5. The method of claim 4, wherein the step of determining the presence or absence of the confounding factor comprises determining a first coherence between the first physiological data signal and the target physiological data signal and a second coherence between the second physiological data signal and the target physiological data signal. The method of claim 5 , wherein the first coherence is based on a single frequency band. The method of claim 6 , wherein the first coherence represents coherence values ​​at different individual frequencies within the single frequency band. The method of claim 5 , wherein the first coherence is based on a plurality of frequency bands. 9 . The method of claim 8 , wherein the first coherence collectively represents a respective coherence value from each respective frequency band of the plurality of frequency bands.

10. The method of claim 5, further comprising determining a first trend of the first physiological parameter, a second trend of the second physiological parameter, and a third trend of the target physiological parameter, and comparing the first trend, the second trend, and the third trend relative to each other.

11. The method of claim 10, wherein the step of determining the presence or absence of the confounding factor utilizes one or more polarity filters configured to evaluate the first trend, the second trend, and the third trend.

12. The method of claim 1, wherein the step of determining the presence or the absence of the confounding factor uses an index table.

13. The method of claim 1, wherein the step of determining the presence or the absence of the confounding factor uses a correlation method.

14. The method of claim 1, wherein the shelving step includes discarding the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor.

15. The method of claim 1, wherein steps a through f are performed on a continuous basis during the time period.

16. The method of claim 1, wherein the target physiological parameter is related to a sensed total hemoglobin concentration (THb) per tissue volume.

17. The method of claim 16, wherein the target physiological parameter is the relative total hemoglobin concentration (rTHb) per tissue volume of the sensed tissue.

18. The method of claim 17, wherein the third sensing device is a near infrared spectroscopy (NIRS) tissue oximeter.

19. The method of claim 16, wherein the first physiological parameter is related to the subject's blood pressure and the first sensing device is a blood pressure sensing device.

20. The method of claim 16, wherein the second physiological parameter is related to the subject's heart rate.

21. A system for determining a target physiological parameter of a subject, the system comprising: a first sensing device configured to continuously sense a first physiological parameter during a time period and configured to generate a first physiological data signal representative of the first physiological parameter during the time period; a second sensing device configured to continuously sense a second physiological parameter during the time period and configured to generate a second physiological data signal representative of the second physiological parameter during the time period; a third sensing device configured to continuously sense a target physiological parameter during the time period and configured to generate a target physiological data signal representing the target physiological parameter during the time period; a system controller in communication with the first sensing device, the second sensing device, and a target sensing device, the system controller comprising at least one processor and a memory device configured to store instructions that, when executed, cause the system controller to: a) determining the presence or absence of a confounding factor interfering with determination of the target physiological parameter, the determining using the first physiological data signal, the second physiological data signal, and the target physiological data signal; b) advancing the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelving the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor; as well as c) determining a value of the target physiological parameter using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor.

22. The system of claim 21, wherein the stored instructions, when executed, cause the system controller to determine the value of the target physiological parameter without using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor.

23. The system of claim 21, wherein the stored instructions, when executed, cause the system controller to determine the presence or absence of the confounding factor using a comparison of processed signals representing the first physiological data signal, the second physiological data signal, and the target physiological data signal.

24. The system of claim 21, wherein the stored instructions, when executed, cause the system controller to determine the presence or the absence of the confounding factor using a frequency domain method.

25. A system according to claim 24, wherein the stored instructions, when executed, cause the system controller to determine the presence or absence of the confounding factor further causing the system controller to determine a first coherence between the first physiological data signal and the target physiological data signal and a second coherence between the second physiological data signal and the target physiological data signal.

26. The system of claim 25, wherein the first coherence is based on a single frequency band.

27. The system of claim 26, wherein the first coherence represents coherence values ​​at different individual frequencies within the single frequency band.

28. The system of claim 25, wherein the first coherence is based on a plurality of frequency bands.

29. The system of claim 28, wherein the first coherence collectively represents a respective coherence value from each respective frequency band of the plurality of frequency bands.

30. The system of claim 25, wherein the stored instructions, when executed, cause the system controller to determine a first trend of the first physiological parameter, a second trend of the second physiological parameter, and a third trend of the target physiological parameter, and to compare the first trend, the second trend, and the third trend relative to each other.

31. The system of claim 30, wherein the stored instructions, when executed, cause the system controller to determine the presence or the absence of the confounding factor using one or more polarity filters configured to evaluate the first trend, the second trend, and the third trend.

32. The system of claim 21, wherein the stored instructions, when executed, cause the system controller to use an index table to determine the presence or the absence of the confounding factor.

33. The system of claim 21, wherein the stored instructions, when executed, cause the system controller to determine the presence or the absence of the confounding factor using a correlation method.

34. The system of claim 21, wherein the shelved first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor are discarded.

35. The system of claim 21, wherein the stored instructions, when executed, cause the system controller to perform functions a through c on a continuous basis during the time period.

36. The system of claim 21, wherein the target physiological parameter is related to a sensed total hemoglobin concentration (THb) per tissue volume.

37. The system of claim 36, wherein the target physiological parameter is relative total hemoglobin concentration (rTHb) per tissue volume of the sensed tissue.

38. The system of claim 37, wherein the third sensing device is a near infrared spectroscopy (NIRS) tissue oximeter.

39. The system of claim 36, wherein the first physiological parameter is related to the subject's blood pressure and the first sensing device is a blood pressure sensing device.

40. The system of claim 36, wherein the second physiological parameter is related to the subject's heart rate.

41. A method for determining a target physiological parameter of a subject, the method comprising: sensing "N" number of physiological parameters of a subject, wherein "N" is an integer equal to or greater than three, the sensing generating "N" sets of physiological data signals, and each set of physiological data signals corresponding to a respective one of the "N" number of physiological parameters during a time period, and wherein one of the "N" number of physiological parameters is a target physiological parameter; determining the presence or absence of confounding factors that interfere with determination of the target physiological parameter, the determination using the "N" sets of physiological data signals including the target physiological parameter set of physiological data signals; advancing the "N" sets of physiological data signals generated in the absence of the confounding factors for further processing, and shelving the "N" sets of physiological data signals generated in the presence of the confounding factors; as well as The value of the target physiological parameter is determined using the "N" sets of physiological data signals generated in the absence of the confounding factors.

42. A non-transitory computer readable medium storing executable instructions that, when executed, cause at least one processor to: controlling a first sensing device configured to sense a first physiological parameter to sense a subject and configured to generate a first physiological data signal representing the first physiological parameter during a time period; controlling a second sensing device configured to sense a second physiological parameter to sense the subject and configured to generate a second physiological data signal representing the second physiological parameter during the time period; controlling a third sensing device, the third sensing device being configured to sense a target physiological parameter to sense the subject and being configured to generate a target physiological data signal representing the target physiological parameter during the time period; determining the presence or absence of a confounding factor that interferes with determination of the target physiological parameter, the determining using the first physiological data signal, the second physiological data signal, and the target physiological data signal; advancing the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor for further processing, and shelving the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the presence of the confounding factor; as well as The value of the target physiological parameter is determined using the first physiological data signal, the second physiological data signal, and the target physiological data signal generated in the absence of the confounding factor.

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