Hemodynamic monitor with nociceptive detection

Abstract

A method for monitoring a patient's arterial pressure and detecting nociception in the patient includes receiving, by a hemodynamic monitor, sensed hemodynamic data representing the patient's arterial pressure waveform. A hardware processor of the hemodynamic monitor performs waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data. The hardware processor of the hemodynamic monitor calculates a cross-correlation measurement between each of the signal measurements. The cross-correlation measurements are output to a user interface. The cross-correlation measurements are monitored for bursts in the cross-correlation measurements. A nociceptive event in the patient is detected when one or more bursts of cross-correlation measurements are output to the user interface.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit of U.S. Provisional Patent Application No. 63 / 307,240, filed February 7, 2022, and entitled “HEMODYNAMIC MONITOR WITH NOCICEPTION DETECTION,” the disclosure of which is hereby incorporated by reference in its entirety. [Background technology]

[0002] The present disclosure relates generally to hemodynamic monitoring, and more particularly to using monitored hemodynamic data to detect and predict nociception in a patient.

[0003] Nociception is the process by which nerve endings called nociceptors detect noxious stimuli and send signals to the central nervous system that are interpreted as pain. Harmful injury causes a "sharp" signal to be emitted from the source of injury. Locally, nociception initiates an inflammatory response. The signal then travels through neurons to the spinal column, where a muscle reflex is triggered. The signal continues to the brain, where, upon reaching the base of the brain, the nociceptive signal triggers a sympathetic nervous system response. Nociception can trigger a sympathetic nervous system response without or before reaching consciousness, and thus an unconscious patient during surgery or intensive care may experience pain. To prevent patients from waking up from surgery or intensive care in pain, medical personnel administer painkillers to patients at various times before and / or during surgery, as well as during intensive care. However, because pain thresholds and tolerances vary from patient to patient, and because patients cannot verbally communicate or provide feedback of signals while unconscious, it can be difficult to know how much painkiller to administer. Giving a patient too little pain medication during surgery can result in the patient waking up in pain after surgery. Giving a patient too much pain medication during surgery can result in the patient experiencing nausea, drowsiness, impaired thinking ability, and impaired function. Summary of the Invention [Problem to be solved by the invention]

[0004] Given the negative consequences of administering too little pain medication to a patient, and the negative consequences of administering too much pain medication to a patient, a solution is needed that gives medical personnel the ability to detect or predict nociception in an unconscious patient during surgery. Accurately detecting or predicting nociception in a patient during surgery can help medical personnel know the appropriate amount of pain medication to administer to a patient so that the patient does not wake up from surgery in significant pain and without giving the patient too much pain medication. [Means for solving the problem]

[0005] In one example, a method for monitoring a patient's arterial pressure and detecting nociception in the patient includes receiving, by a hemodynamic monitor, sensed hemodynamic data representative of the patient's arterial pressure waveform from a hemodynamic sensor. The method further includes performing, by a hardware processor of the hemodynamic monitor, a waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data. The hardware processor of the hemodynamic monitor organizes the plurality of signal measurements into signal measurement pairs. The hardware processor of the hemodynamic monitor measures a cross-correlation of each of the signal measurement pairs. The measured cross-correlation of each of the signal measurement pairs is output to a display device. The measured cross-correlation of each of the signal measurement pairs is monitored for an increase in the measured cross-correlation of at least one of the signal measurement pairs above a predetermined threshold. The hemodynamic monitor transmits an alert of a nociceptive event in the patient to a medical professional when the measured cross-correlation of at least one of the signal measurement pairs increases above a predetermined threshold.

[0006] In another example, a method for monitoring a patient's arterial pressure and detecting nociception in the patient includes receiving, by a hemodynamic monitor, sensed hemodynamic data representative of the patient's arterial pressure waveform. A hardware processor of the hemodynamic monitor performs waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data. The hardware processor of the hemodynamic monitor calculates a cross-correlation between each of the signal measurements. The cross-correlation measurements are output to a user interface. The cross-correlation measurements are monitored for bursts in the cross-correlation measurements. A nociceptive event in the patient is detected when one or more bursts of cross-correlation are output to the user interface.

[0007] In another embodiment, a system for monitoring a patient's arterial pressure and providing alerts to a healthcare professional of a patient's nociception includes a hemodynamic sensor generating hemodynamic data representative of the patient's arterial pressure waveform. The system further includes a system memory storing nociception detection software code and a user interface with a sensory alarm providing a sensory signal to alert a healthcare professional of a nociceptive event in the patient. A hardware processor is configured to execute the nociception detection software code to perform a waveform analysis of the hemodynamic data to determine a plurality of signal measurements. The plurality of signal measurements are organized into signal measurement pairs and a cross-correlation of each of the signal measurement pairs is measured. The cross-correlation measurements of the signal measurement pairs are output to the user interface. The cross-correlation measurements of the signal measurement pairs are monitored for bursts in the cross-correlation measurements of the signal measurement pairs. A sensory alarm of the user interface is invoked in response to a burst in one or more of the cross-correlation measurements of the signal measurement pairs to indicate a nociceptive event. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a perspective view of an exemplary hemodynamic monitor that analyzes a patient's arterial pressure and provides alerts to medical personnel about the patient's nociceptive events. [Diagram 2] FIG. 2 is a perspective view of an example of a minimally invasive pressure sensor for sensing hemodynamic data representative of a patient's arterial pressure. [Diagram 3] FIG. 3 is a perspective view of an example of a non-invasive sensor for sensing hemodynamic data representative of a patient's arterial pressure. [Figure 4] FIG. 4 is a block diagram illustrating an exemplary hemodynamic monitoring system that detects a patient's current nociceptive events based on the patient's arterial blood pressure. [Diagram 5] FIG. 5 is a graph showing an example tracing of an arterial pressure waveform, including example indices corresponding to signal measurements used by a hemodynamic monitoring system to detect a current nociceptive event in a patient. [Figure 6] FIG. 6 is a graph of a collection of plots of systolic blood pressure, heart rate, and the cross-correlation measurements relating to systolic blood pressure and heart rate, all plotted over time. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] As described herein, a hemodynamic monitoring system senses hemodynamic data from a patient and uses the hemodynamic data to detect whether the patient is experiencing a current nociceptive event. The hemodynamic monitoring system can detect a current nociceptive event from the patient's hemodynamic data by deriving signal measurements from the hemodynamic data, piecing the signal measurements together, calculating cross-correlations for each of the pairs of signal measurements, and monitoring the cross-correlations for each of the pairs of signal measurements. Upon a burst of values ​​in at least one of the cross-correlations of the pairs of signal measurements, the hemodynamic monitoring system can issue a signal or alarm to a medical professional to alert the medical professional that the patient is experiencing a current nociceptive event. After receiving the signal, the medical professional can administer a painkiller to the patient to alleviate the nociceptive event. The hemodynamic monitoring system is described in detail below with reference to Figures 1-6.

[0010] FIG. 1 is a perspective view of a hemodynamic monitor 10 for detecting nociceptive events in a patient. As illustrated in FIG. 1, the hemodynamic monitor 10 includes a display device 12 that, in the embodiment of FIG. 1, presents a graphical user interface including control elements (e.g., graphical control elements) that enable user interaction with the hemodynamic monitor 10. The hemodynamic monitor 10 may also include a number of input and / or output (I / O) connectors configured for wired connection (e.g., electrical connection and / or communicative connection) with one or more peripheral components, such as one or more hemodynamic sensors, as described further below. For example, as shown in FIG. 1, the hemodynamic monitor 10 may include an I / O connector 14. Although the embodiment of FIG. 1 shows five separate I / O connectors 14, it should be understood that in other embodiments, the hemodynamic monitor 10 may include less than five I / O connectors, or more than five I / O connectors. In still other embodiments, the hemodynamic monitor 10 may not include an I / O connector 14, but rather may communicate wirelessly with various peripheral devices.

[0011] As described further below, hemodynamic monitor 10 includes one or more processors and computer readable memory storing nociception detection software code executable to generate a score representative of the patient's probability of a current (i.e., present) nociceptive event. Hemodynamic monitor 10 can receive sensed hemodynamic data representative of the patient's arterial pressure waveform, for example, via one or more hemodynamic sensors connected to hemodynamic monitor 10 via I / O connector 14. Hemodynamic monitor 10 executes the nociception detection software code to use the received hemodynamic data to obtain a plurality of signal measurements, which may include one or more vital sign parameters characterizing the patient's vital sign data, as described further below.

[0012] As shown in Figure 1, hemodynamic monitor 10 can present a graphical user interface on display device 12. Display device 12 can be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, or other display device suitable for providing information to a user in a graphical format. In some implementations, such as the implementation of Figure 1, display device 12 can be a touch-sensitive and / or presence-sensitive display device configured to receive user input in the form of gestures, such as touch gestures, scroll gestures, zoom gestures, swipe gestures, or other gesture input.

[0013] Figure 2 is a perspective view of a hemodynamic sensor 16 that may be attached to a patient to sense hemodynamic data representative of the patient's arterial pressure. The hemodynamic sensor 16 illustrated in Figure 2 is an example of a minimally invasive hemodynamic sensor that may be attached to the patient, for example, via a fluid-filled tube inserted in the patient's arm and connected to a radial artery catheter to which the hemodynamic sensor 16 is attached. In other examples, the hemodynamic sensor 16 may be attached to the patient via a femoral artery catheter inserted in the patient's leg.

[0014] As shown in FIG. 2, the hemodynamic sensor 16 includes a housing 18, a fluid input port 20, a catheter-side fluid port 22, and an I / O cable 24. The fluid input port 20 is configured to be connected via tubing or other hydraulic connection to a fluid source, such as a saline bag or other fluid input source. The catheter-side fluid port 22 is configured to be connected via tubing or other hydraulic connection to a catheter (e.g., a radial artery catheter or a femoral artery catheter) inserted into a patient's arm (i.e., a radial artery catheter) or a patient's leg (i.e., a femoral artery catheter). The I / O cable 24 is configured to be connected to the hemodynamic monitor 10 (FIG. 1), for example, via one or more of the I / O connectors 14. The housing 18 of the hemodynamic sensor 16 encloses one or more pressure transducers, communication circuitry, processing circuitry, and corresponding electronic components for sensing fluid pressure corresponding to the patient's arterial pressure, which is transmitted to the hemodynamic monitor 10 (FIG. 1) via the I / O cable 24.

[0015] In operation, a column of fluid (e.g., saline) is introduced from a fluid source (e.g., a saline bag) through hemodynamic sensor 16 via fluid input port 20 to catheter side fluid port 22 toward a catheter inserted into a patient. Arterial pressure is transmitted through the fluid column to a pressure sensor located within housing 16 that senses the pressure of the fluid column. Hemodynamic sensor 16 converts the sensed pressure of the fluid column into an electrical signal via a pressure transducer and outputs a corresponding electrical signal to hemodynamic monitor 10 (FIG. 1) via I / O cable 24. Hemodynamic sensor 16 thus transmits analog sensor data (or a digital representation of the analog sensor data) to hemodynamic monitor 10 (FIG. 1) that represents a substantially continuous, beat-to-beat monitoring of the patient's arterial pressure.

[0016] FIG. 3 is a perspective view of a hemodynamic sensor 26 for sensing hemodynamic data representative of a patient's arterial pressure. The hemodynamic sensor 26 illustrated in FIG. 3 is an example of a non-invasive hemodynamic sensor that may be attached to a patient via one or more finger cuffs to sense data representative of the patient's arterial pressure. As shown in FIG. 3, the hemodynamic sensor 26 includes an inflatable finger cuff 28 and a cardiac reference sensor 30. The inflatable finger cuff 28 includes an inflatable blood pressure bladder configured to inflate and deflate as controlled by a pressure controller (not shown) that is pneumatically connected to the inflatable finger cuff 28. The inflatable finger cuff 28 also includes an optical (e.g., infrared) transmitter and an optical receiver that are electrically connected to the pressure controller (not shown) to measure the changing volume of the artery below the finger cuff.

[0017] In operation, the pressure controller continuously adjusts the pressure in the finger cuff to maintain a constant volume in the finger's artery (i.e., the arterial unloaded volume) as measured via the optical transmitter and receiver in the inflatable finger cuff 28. The pressure applied by the pressure controller to continuously maintain the unloaded volume represents the blood pressure in the finger and is communicated by the pressure controller to the hemodynamic monitor 10 shown in FIG. 1. The cardiac reference sensor 30 measures the hydrostatic height difference between the level at which the finger is held and the reference level for pressure measurement, which is typically the cardiac level. Thus, the hemodynamic sensor 26 transmits sensor data representing a substantially continuous beat-to-beat monitoring of the patient's arterial pressure waveform.

[0018] 4 is a block diagram of a hemodynamic monitoring system 32 that determines a nociceptive score representing the probability of a current nociceptive event in a patient 36 based on multiple signal measurements derived from the patient's arterial blood pressure. The hemodynamic monitoring system 32 monitors the arterial blood pressure of the patient 36 and provides an alert to a medical professional 38 when the patient's 36 nociceptive score exceeds a predetermined threshold. The medical professional 38 can respond to the alert by administering an appropriate analgesic to the patient 36 to alleviate the current nociceptive event.

[0019] As shown in Figure 4, the hemodynamic monitoring system 32 includes the hemodynamic monitor 10 and a hemodynamic sensor 34. The hemodynamic monitoring system 32 can be implemented in a patient care environment, such as an ICU, an OR, or other patient care environment. As shown in Figure 4, the patient care environment can include a patient 36 and a healthcare worker 38 trained to utilize the hemodynamic monitoring system 32.

[0020] As discussed above with respect to FIG. 1, hemodynamic monitor 10 may be an integrated hardware unit including, for example, system processor 40, system memory 42, display device 12, analog-to-digital (ADC) converter 44, and digital-to-analog (DAC) converter 46. In other embodiments, any one or more of the components and / or described functionality of hemodynamic monitor 10 may be distributed among multiple hardware units. For example, in some embodiments, display device 12 may be a separate display device that is remote from and operably coupled to hemodynamic monitor 10. Although generally illustrated and described in the embodiment of FIG. 4 as an integrated hardware unit, it should be understood that hemodynamic monitor 10 may include any combination of devices and components that are electrically, communicatively, or otherwise operably connected to perform the functions attributed to hemodynamic monitor 10 herein.

[0021] 4, the system memory 42 stores nociceptive software code 48 that forms a sensing model of the hemodynamic monitor 10. The nociceptive software code 48 includes a first module 50 for extracting and calculating waveform features and a plurality of signal measurements from the arterial pressure of the patient 36, a second module 51 for organizing the plurality of signal measurements into signal measurement pairs, a third module 52 for measuring the cross-correlation of each of the signal measurement pairs, and a fourth module 53 for monitoring the measured cross-correlation of each of the signal measurement pairs for a burst (i.e., an increase above a predetermined threshold) in the measured cross-correlation of at least one of the signal measurement pairs.

[0022] The display device 12 provides a user interface 54 including control elements 56 that enable user interaction with the hemodynamic monitor 10 and / or other components of the hemodynamic monitoring system 32. As illustrated in FIG. 4, the user interface 54 also provides a sensory alarm 58 to provide an alert to a medical professional of a current nociceptive event in the patient 36, as described further below. The sensory alarm 58 may be implemented as one or more of a visual alarm, an audible alarm, a tactile alarm, or other type of sensory alarm. For example, the sensory alarm 58 may be triggered as any combination of a flashing and / or colored graphic presented by the user interface 54 on the display device 12, a display of a nociceptive score via the user interface 54 on the display device 12, an alert sound such as a siren or a repeating tone, and a tactile alarm configured to cause the hemodynamic monitor 10 to vibrate or otherwise deliver a physical impulse that is perceptible to the medical professional 38 or other user.

[0023] The hemodynamic sensor 34 can be attached to the patient 36 to sense hemodynamic data representative of the arterial pressure waveform of the patient 36. The hemodynamic sensor 34 is operatively connected (e.g., electrically and / or communicatively connected via a wired or wireless connection or both) to the hemodynamic monitor 10 to provide the sensed hemodynamic data to the hemodynamic monitor 10. In some examples, the hemodynamic sensor 34 provides the hemodynamic data representative of the arterial pressure waveform of the patient 36 to the hemodynamic monitor 10 as an analog signal, which is converted by the ADC 44 into digital hemodynamic data representative of the arterial pressure waveform. In other examples, the hemodynamic sensor 34 can provide the sensed hemodynamic data to the hemodynamic monitor 10 in a digital format, in which case the hemodynamic monitor 10 may not include or utilize the ADC 44. In yet another embodiment, hemodynamic sensor 34 can provide hemodynamic data representative of the arterial pressure waveform of patient 36 to hemodynamic monitor 10 as an analog signal that is analyzed by hemodynamic monitor 10 in its analog form.

[0024] Hemodynamic sensor 34 may be a non-invasive or minimally invasive sensor attached to patient 36. For example, hemodynamic sensor 34 may take the form of minimally invasive hemodynamic sensor 16 (FIG. 2), non-invasive hemodynamic sensor 26 (FIG. 3), or other minimally invasive or non-invasive hemodynamic sensor. In some examples, hemodynamic sensor 34 may be non-invasively attached to an extremity of patient 36, such as the wrist, arm, finger, ankle, toe, or other extremity of patient 36. In this manner, hemodynamic sensor 34 may take the form of a small, lightweight, comfortable hemodynamic sensor suitable for extended wear by patient 36 to provide substantially continuous beat-to-beat monitoring of arterial pressure of patient 36 over extended periods of time, such as minutes or hours.

[0025] In certain embodiments, the hemodynamic sensor 34 may be configured to sense the arterial pressure of the patient 36 in a minimally invasive manner. For example, the hemodynamic sensor 34 may be attached to the patient 36 via a radial artery catheter inserted in the arm of the patient 36. In other embodiments, the hemodynamic sensor 34 may be attached to the patient 36 via a femoral artery catheter inserted in the leg of the patient 36. Such minimally invasive techniques may similarly enable the hemodynamic sensor 34 to provide substantially continuous beat-to-beat monitoring of the arterial pressure of the patient 36 over extended periods of time, such as minutes or hours.

[0026] The system processor 40 is a hardware processor configured to execute nociceptive software code 48, which implements a first module 50, a second module 51, a third module 52, and a fourth module 53 to generate a nociceptive score representing the probability of a current nociceptive event for the patient 36. Examples of the system processor 40 may include any one or more of a microprocessor, a controller, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other equivalent discrete or integrated logic circuitry.

[0027] The system memory 42 may be configured to store information within the hemodynamic monitor 10 during operation. In some examples, the system memory 42 is described as a computer-readable storage medium. In some examples, the computer-readable storage medium may include a non-transitory medium. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier wave or a propagating signal. In certain examples, the non-transitory storage medium may store data that may change over time (e.g., in RAM or cache). The system memory 42 may include volatile and non-volatile computer-readable memory. Examples of volatile memory may include random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), and other forms of volatile memory. Examples of non-volatile memory may include, for example, magnetic hard disks, optical disks, flash memory, or forms of electrically programmable memory (EPROM) or electrically erasable programmable (EEPROM) memory.

[0028] Display device 12 may be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (OLED) display, or other display suitable for providing information to a user in a graphical format. User interface 54 may include graphical and / or physical control elements that enable user input to interact with hemodynamic monitor 10 and / or other components of hemodynamic monitoring system 32. In some examples, user interface 54 may take the form of a graphical user interface (GUI) that presents graphical control elements presented on a touch-sensitive and / or presence-sensitive display screen of display device 12, for example. In such examples, user input may be received in the form of gesture input, such as touch gestures, scroll gestures, zoom gestures, or other gesture input. In certain examples, user interface 54 may take the form of and / or include physical control elements, such as physical buttons, keys, knobs, or other physical control elements configured to receive user input that interacts with components of hemodynamic monitoring system 32. User interface 54 may include a speaker that enables the hemodynamic monitor 10 to be capable of generating audible alarms.

[0029] During operation, the hemodynamic sensor 34 senses hemodynamic data representative of the arterial pressure waveform of the patient 36. The hemodynamic sensor 34 provides the hemodynamic data (e.g., as analog sensor data) to the hemodynamic monitor 10. The ADC 44 converts the analog hemodynamic data to digital hemodynamic data representative of the arterial pressure waveform of the patient 36.

[0030] The system processor 40 executes the nociceptive software code 48 to determine a nociceptive detection score, which represents the probability of a current nociceptive event for the patient 36, using the received hemodynamic data. For example, the system processor 40 may execute a first module 50 to perform a waveform analysis of the hemodynamic data to determine a plurality of signal measurements. The system processor 40 executes a second module 51 to organize the plurality of signal measurements into signal measurement pairs. The system processor 40 executes a third module 52 to measure or calculate a cross-correlation of each pair of signal measurements. The system processor 40 then executes a fourth module 53 to monitor the measured cross-correlation of each of the signal measurement pairs over time. As the fourth module 53 monitors the measured cross-correlation of each of the signal measurement pairs, the fourth module 53 may output a plot of the measured cross-correlation of each of the signal measurement pairs over time to the display device 12 to allow the medical practitioner 38 to view the measured cross-correlation value of each of the signal measurement pairs. If the fourth module 53 detects a burst (i.e., an increase above a predetermined threshold) in the measured cross-correlation of at least one of the pairs of signal measurements, the system processor 40 activates a sensory alarm 58 in the user interface 54 to send a sensory signal alerting the medical practitioner 38 that the patient 36 is now experiencing a current nociceptive event. The medical practitioner 38 can respond to the alert by administering a painkiller to the patient 36, or by administering any other form of treatment to the patient 36, to alleviate the current nociceptive event. How the first module 50 performs waveform analysis of the hemodynamic data to determine the multiple signal measurements is described in more detail below with reference to FIG. 5.

[0031] 5 provides an exemplary graph showing an example trace of an arterial pressure waveform of a patient 36 with individual cardiac cycles identified and magnified. Performing a waveform analysis of the hemodynamic data of the patient 36 sensed by the hemodynamic sensor 34 may include identifying individual cardiac cycles in the arterial pressure waveform of the patient 36, similar to the example shown in FIG. 5, and identifying dicrotic notches in each of the individual cardiac cycles of each of the arterial pressure waveforms of the sensed hemodynamic data. The waveform analysis of the sensed hemodynamic data then includes identifying a systolic up phase, a systolic down phase, and a diastolic phase in each of the individual cardiac cycles of each of the arterial pressure waveforms of the hemodynamic data, similar to the example shown in FIG. 5.

[0032] Signal measurements are extracted from each of the systolic up phase, systolic down phase, and diastole from each of the individual cardiac cycles of each of the arterial pressure waveforms of the patient 36 sensed by the hemodynamic sensor 34. The signal measurements may correspond to hemodynamic effects from each of the systolic up phase, systolic down phase, and diastole from each of the individual cardiac cycles. These hemodynamic effects may include contractility, aortic compliance, stroke volume, vascular tone, afterload, and the entire cardiac cycle, all of which may be affected by the sympathetic response induced by the nociceptive event. Signal measurements calculated or extracted by waveform analysis include mean, maximum, minimum, duration, area, standard deviation, derivative, and / or morphological measurements from each of the systolic up phase, systolic down phase, and diastole from each of the individual cardiac cycles. The signal measurements may also include heart rate, respiratory rate, stroke volume, pulse pressure, pulse pressure variation, stroke volume variation, mean arterial pressure (MAP), systolic pressure (SYS), diastolic pressure (DIA), heart rate variability, cardiac output, peripheral resistance, vascular compliance, and / or left ventricular contractility extracted from each individual cardiac cycle of each arterial pressure waveform of the patient 36 sensed by the hemodynamic sensor 34. As described above with reference to FIG. 4, the system processor 40 may execute a first module 50 to perform waveform analysis of the hemodynamic data to determine the plurality of signal measurements. After the plurality of signal measurements are determined, the hemodynamic monitor 10 groups the plurality of signal measurements into pairs and calculates a cross-correlation measurement (CCAM) for each pair of signal measurements, as described below with reference to FIG. 6.

[0033] FIG. 6 is a graph of a collection of plots of systolic, diastolic, and mean blood pressure 60, a plot of heart rate 62, and a cross-correlation measurement (CCAM) plot 64 of a patient 36, all plotted over time. FIG. 6 also shows a burst 66 of the CCAM plot 64, a drug administration event 68 where an analgesic was administered (fentanyl), and a stable period 70 of the CCAM plot 64. The graphs of FIG. 6 may be examples of what may be output by the fourth module 53 of the nociception software code 48 and shown on the display 12 of the hemodynamic monitor 10. The systolic blood pressure 60 and the heart rate 62 are signal measurements derived from performing a waveform analysis of the hemodynamic data of the patient 36 sensed by the hemodynamic sensor 34 (as described and discussed above with respect to FIGS. 4 and 5). The hemodynamic monitor 10 calculates the cross-correlation measurement between the systolic blood pressure 60 and the heart rate 62, and outputs the cross-correlation measurement as shown in the CCAM plot 64. By taking the ratio of the standard deviation of the heart rate 62 to the standard deviation of the systolic blood pressure 60, the hemodynamic monitor 10 can calculate a cross-correlation measurement (CCAM) between the systolic blood pressure 60 and the heart rate 62, expressed as follows:

[0034]

number

[0035] where y is the heart rate 62, x is the systolic blood pressure 60, SD(y) is the standard deviation of the heart rate 62, SD(x) is the standard deviation of the systolic blood pressure 60, and CCAM is a cross-correlation measurement of the heart rate 62 and the systolic pressure 60. The CCAM values ​​are then plotted over time as a CCAM plot 64. Equation 1 can be applied to all other pairs of signal measurements extracted from each of the systolic upstroke phase, systolic downstroke phase, diastole, and the entire waveform from each of the individual cardiac cycles of FIG. 5 to derive additional cross-correlation plots all grouped together as CCAM plot 64. The CCAM plot 64 for each of the signal measurement pairs can be normalized before output to the display device 12 to allow all of the CCAMs measured for the signal measurement pairs to fit on the display device 12 and overlay each other.

[0036] The CCAM plot 64 is monitored for bursts 66 by the system processor 40 of the hemodynamic monitor 10. A burst 66 occurs in the CCAM plot 64 when at least one of the plots in the CCAM plot 64 increases beyond a predetermined threshold. Monitoring / detection of a burst 66 can be performed using a wide range of mathematical methods, such as detecting changes in amplitude, changes in the area under the curve of each burst 66, and / or changes in the standard deviation of each burst 66. Monitoring / detection of a burst 66 can also be performed using more complex time and frequency domain methods, such as Fast Fourier Transform (FFT)-based methods and wavelet-based methods. In one embodiment, the predetermined threshold is 50% greater than the moving average of the CCAM plot 64. Thus, in this embodiment, a burst 66 occurs when at least one of the CCAM plots 64 is at least 50% greater than the moving average of the CCAM plot 64 of the pair of signal measurements. If a burst 66 occurs in the CCAMs of systolic blood pressure 60 and heart rate 62, as shown in CCAM plot 64 of FIG. 6, hemodynamic monitor 10 will interpret the burst 66 as a current nociceptive event in patient 36 and send an alert to medical personnel. In response to the alert, medical personnel may administer a pain medication, represented by drug administration event 68 in FIG. 6, to patient 36 to reduce nociception in patient 36. If patient 36 responds to the pain medication, burst 66 should dissipate below the threshold in CCAM plot 64 followed by a stable period 70. During stable period 70, none of the CCAM plots 64 of signal measurements exceed the threshold, indicating that patient 36 is not experiencing nociception.

[0037] While FIG. 6 has been described with respect to a pair of signal measurements of systolic blood pressure 60 and heart rate 62, additional signal measurement pairs may be analyzed by hemodynamic monitor 10 and cross-correlation measurements of those signal measurement pairs may be calculated and included in CCAM plot 64. In some embodiments, hemodynamic monitor 10 may monitor and plot all possible combinations of any two signal measurements derived from sensed hemodynamic data representative of the arterial pressure waveform of patient 36, which may include thousands to hundreds of thousands of signal pairs and their corresponding cross-correlation measurements. Nociception is indicated in different patients by different signal measurements from those sensed hemodynamic data. By configuring hemodynamic monitor 10 to plot and monitor cross-correlation measurements for as many signal measurement combinations as possible, hemodynamic monitor 10 may detect nociception in different patients.

[0038] 6 uses Equation 1 to calculate the cross-correlation measurements for pairs of signal measurements, in other embodiments, the CCAMs for systolic blood pressure 60 and heart rate 62 can be measured by calculating a product between the signal measurements, or by calculating a ratio of the signal measurements, or by any known mathematical method for calculating the cross-correlation between two variables. Hemodynamic monitor 10 can be programmed to calculate the cross-correlation for pairs of signal measurements using multiple equations or methods.

[0039] In another embodiment, the hemodynamic monitor 10 may be programmed to calculate a generalized cross-correlation (GGC) between a pair of signal measurements prior to calculating the CCAM for the pair of signal measurements. The hemodynamic monitor 10 may calculate the GGC between a pair of signal measurements by first measuring a 10 second window for both the first signal measurement (e.g., systolic blood pressure) and the second signal measurement (e.g., heart rate) as represented by the following equation:

[0040]

number

[0041] where m is a time window measured in seconds, x is a first signal measurement (such as systolic blood pressure), y is a second signal measurement (such as heart rate), τ is a time shift, and GGC is a generalized cross-correlation between the first and second signal measurements. As shown in Equation 2, both the first and second signal measurements are interpolated and resampled in 10 second windows at 1 second intervals. The 10 second window of the first signal measurement is cross-correlated with the 10 second window of the second signal measurement. The time shift τ is applied to one of the signal measurements with repeated cross-correlation to achieve a pattern of cross-correlation that includes the maximum cross-correlation between the first and second signal measurements. The maximum cross-correlation (or maximum GGC) indicates the best time delay between the first and second signal measurements to achieve the highest cross-correlation between the first and second signal measurements. If the highest cross-correlation is significant with a p-value (probability that the null hypothesis is true) less than 0.05 or any other threshold, then Equation 1 can be applied to the first and second signal measurements at the best time delay to obtain the CCAM for the first and second signal measurements. Equation 2 and Equation 1 can be applied to other pairs of signal measurements to derive additional plots that are aggregated together as the CCAM plot 64. Although the above example discloses a time window m of 10 seconds, the time window m can be less than or greater than 10 seconds. Also, although the above example discloses a time shift τ of 0 to 5 seconds with a resampling interval of 1 second, the time shift τ can be of a series of delays (e.g., 0 to 10 seconds long or negative 10 to positive 10 seconds long), and the resampling interval can be at any time increment (e.g., 0.1 seconds, 0.5 seconds, 1 second, or 2 seconds). For example, the resampling interval can be any value between 0.1 seconds and 2 seconds.

[0042] Discussion of Possible Embodiments

[0043] Below is a comprehensive description of possible embodiments of the present invention.

[0044] 11. A method for monitoring a patient's arterial pressure and detecting nociception in a patient, comprising: receiving, by a hemodynamic monitor, sensed hemodynamic data representing the patient's arterial pressure waveform from a hemodynamic sensor; performing, by a hardware processor of the hemodynamic monitor, waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data; consolidating, by the hardware processor of the hemodynamic monitor, the plurality of signal measurements into signal measurement pairs; measuring, by the hardware processor of the hemodynamic monitor, a cross-correlation of each of the signal measurement pairs; outputting the measured cross-correlation of each of the signal measurement pairs to a display device; monitoring the measured cross-correlation of each of the signal measurement pairs for an increase in the measured cross-correlation for at least one of the signal measurement pairs above a predetermined threshold; and transmitting, by the hemodynamic monitor, an alert of a nociceptive event in the patient to a medical professional when the measured cross-correlation for at least one of the signal measurement pairs increases above a predetermined threshold.

[0045] The method of the preceding paragraph may additionally and / or alternatively optionally include any one or more of the following features, configurations, and / or additional components.

[0046] The predetermined threshold is at least 50% greater than a running average of the measured cross-correlation of at least one of the pairs of signal measurements.

[0047] Normalizing the measured cross-correlation of each pair of signal measurements before outputting the measured cross-correlation of each pair of signal measurements to a display device.

[0048] The signal measurements include hemodynamic effects from the systolic upstroke phase, the systolic downstroke phase, and the diastole phase from each individual cardiac cycle, the hemodynamic effects including contractility, aortic compliance, stroke volume, vascular tone, afterload, and the entire cardiac cycle.

[0049] The signal measurements include mean, maximum, minimum, duration, area, standard deviation, derivative, and / or morphological measurements from each of the systolic upstroke phase, systolic downstroke phase, and diastole phase from each individual cardiac cycle.

[0050] The signal measurements include heart rate, respiratory rate, stroke volume, pulse pressure, pulse pressure variation, stroke volume variation, mean arterial pressure (MAP), systolic pressure (SYS), diastolic pressure (DIA), heart rate variability, cardiac output, peripheral resistance, vascular compliance, and / or left ventricular contractility extracted from each individual cardiac cycle.

[0051] Measuring the cross-correlation of each pair of signal measurements by the hardware processor includes measuring a time window of data for each of the signal measurements, interpolating each of the signal measurements and resampling each of the signal measurements at one second intervals, calculating cross-correlation values ​​between pairs of signal measurements at a series of delays, selecting the delay providing the highest cross-correlation value, measuring the standard deviation of the first signal measurement at the delay providing the highest cross-correlation value, measuring the standard deviation of the second signal measurement at the delay providing the highest cross-correlation value, and if the highest cross-correlation value has a p-value less than 0.05, calculating a ratio between the standard deviation of the first signal measurement and the standard deviation of the second signal measurement.

[0052] The time window encompasses 10 seconds.

[0053] The time window is greater than 10 seconds.

[0054] The time window is less than 10 seconds.

[0055] The series of delays ranges from zero to 10 seconds, with a resampling interval of 1 second.

[0056] The series of delays ranges from negative 10 seconds to positive 10 seconds, with resampling intervals of 0.1 to 2 seconds.

[0057] The series of delays range from zero to 5 seconds, with resampling intervals of 0.1 to 2 seconds.

[0058] 1. A method for monitoring a patient's arterial pressure and detecting nociception in a patient, comprising: receiving, by a hemodynamic monitor, sensed hemodynamic data representing the patient's arterial pressure waveform; performing, by a hardware processor of the hemodynamic monitor, waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data; calculating, by the hardware processor of the hemodynamic monitor, a cross-correlation measurement between each of the signal measurements; outputting the cross-correlation measurement to a user interface; monitoring the cross-correlation measurement for bursts in the cross-correlation measurement; and detecting a nociceptive event in the patient when one or more bursts of cross-correlation measurements are output to the user interface.

[0059] The method of the preceding paragraph may additionally and / or alternatively optionally include any one or more of the following features, configurations, and / or additional components.

[0060] Performing waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data includes identifying individual cardiac cycles within the arterial pressure waveform, identifying a dicrotic notch in each of the individual cardiac cycles, identifying a systolic up phase, a systolic decay phase, and a diastole in each of the individual cardiac cycles, and extracting a plurality of signal measurements from each of the systolic up phase, the systolic decay phase, and the diastole from each of the individual cardiac cycles.

[0061] The multiple signal measurements include hemodynamic effects from each of the systolic up-phase, systolic down-phase, and diastole from each individual cardiac cycle, the hemodynamic effects including contractility, aortic compliance, stroke volume, vascular tone, afterload, and the entire cardiac cycle.

[0062] The multiple signal measurements include mean, maximum, minimum, duration, area, standard deviation, derivative, and / or morphological measurements from each of the systolic upstroke phase, systolic downstroke phase, and diastole phase from each individual cardiac cycle.

[0063] The multiple signal measurements include heart rate, respiratory rate, stroke volume, pulse pressure, pulse pressure variation, stroke volume variation, mean arterial pressure (MAP), systolic pressure (SYS), diastolic pressure (DIA), heart rate variability, cardiac output, peripheral resistance, vascular compliance, and / or left ventricular contractility extracted from each individual cardiac cycle.

[0064] The user interface includes at least one of a display screen and a speaker.

[0065] 1. A system for monitoring a patient's arterial pressure and providing an alert to medical personnel of a nociceptive event in a patient, comprising: a hemodynamic sensor that generates hemodynamic data representative of a patient's arterial pressure waveform; a system memory that stores nociceptive detection software code; a user interface including a sensory alarm that provides a sensory signal to alert medical personnel to a nociceptive event in the patient; and a hardware processor configured to execute the nociceptive detection software code to perform waveform analysis of the hemodynamic data to determine a plurality of signal measurements, organize the plurality of signal measurements into signal measurement pairs, measure a cross-correlation of each of the signal measurement pairs, output the cross-correlation measurements of the signal measurement pairs to the user interface, monitor the cross-correlation measurements of the signal measurement pairs for bursts in the cross-correlation measurements of the signal measurement pairs, and activate a sensory alarm of the user interface indicative of a nociceptive event in response to a burst in one or more of the cross-correlation measurements of the signal measurement pairs.

[0066] The system of the preceding paragraph may additionally and / or alternatively optionally include any one or more of the following features, configurations, and / or additional components.

[0067] The hemodynamic sensor is a non-invasive hemodynamic sensor that can be attached to an extremity of a patient.

[0068] The hemodynamic sensor is a minimally invasive arterial catheter-based hemodynamic sensor.

[0069] A hemodynamic sensor generates the hemodynamic data as an analog hemodynamic sensor signal representative of the patient's arterial pressure waveform.

[0070] An analog-to-digital converter converts analog hemodynamic sensor signals into digital hemodynamic data representative of the arterial pressure waveform of the patient.

[0071] Although the invention has been described with reference to exemplary embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the invention. In addition, many modifications may be made to adapt a particular situation or material to the teachings of the invention without departing from its essential scope. Therefore, it is not intended that the invention be limited to the particular embodiments disclosed, but the invention is intended to include all embodiments falling within the scope of the appended claims.

Claims

1. 1. A method for monitoring arterial blood pressure in a patient and detecting nociception in said patient, comprising: receiving, by a hemodynamic monitor, sensed hemodynamic data from a hemodynamic sensor representative of an arterial pressure waveform of the patient; performing, by a hardware processor of the hemodynamic monitor, a waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data; grouping, by the hardware processor of the hemodynamic monitor, the plurality of signal measurements into signal measurement pairs; measuring, by the hardware processor of the hemodynamic monitor, a cross-correlation between each of the pairs of signal measurements; outputting the measured cross-correlation of each of said pairs of signal measurements on a display device; monitoring the measured cross-correlation of each of the pairs of signal measurements for an increase in the measured cross-correlation of at least one of the pairs of signal measurements above a predetermined threshold; and transmitting, by the hemodynamic monitor, an alert of a nociceptive event in the patient to medical personnel when the measured cross-correlation of at least one of the pairs of signal measurements increases above the predetermined threshold.

2. The method of claim 1 , wherein the predetermined threshold is at least 50% greater than a running average of the measured cross-correlation of the at least one of the pairs of signal measurements.

3. 3. The method of claim 1, further comprising normalizing the measured cross-correlation of each pair of signal measurements before outputting the measured cross-correlation of each pair of signal measurements to the display device.

4. 4. The method of claim 1, wherein the signal measurements comprise hemodynamic effects from each of the systolic up phase, systolic decay phase and diastole from each individual cardiac cycle, the hemodynamic effects comprising contractility, aortic compliance, stroke volume, vascular tone, afterload and total cardiac cycle; and / or the signal measurements comprise mean, maximum, minimum, duration, area, standard deviation, derivative and / or morphological measurements from each of the systolic up phase, systolic decay phase and diastole from each individual cardiac cycle; and / or the signal measurements comprise heart rate, respiratory rate, stroke volume, pulse pressure, pulse pressure variability, stroke volume variability, mean arterial pressure (MAP), systolic pressure (SYS), diastolic pressure (DIA), heart rate variability, cardiac output, peripheral resistance, vascular compliance and / or left ventricular contractility extracted from each individual cardiac cycle.

5. measuring, by the hardware processor, the cross-correlation of each of the pairs of signal measurements; measuring a time window of data for each of said signal measurements; interpolating each of said signal measurements and resampling each of said signal measurements at one second intervals; calculating cross-correlation values ​​between said pairs of said signal measurements at a series of delays; selecting the delay that provides the highest cross-correlation value; measuring a standard deviation of a first signal measurement at the delay that provides the highest cross-correlation value; measuring the standard deviation of the second signal measurements at the delay that provides the highest cross-correlation value; and if the highest cross-correlation value has a p-value less than 0.05, calculating a ratio between the standard deviation of the first signal measurement and the standard deviation of the second signal measurement.

6. The method of claim 5 , wherein the time window comprises 10 seconds.

7. The method of claim 5 , wherein the time window is greater than 10 seconds.

8. The method of claim 5 , wherein the time window is less than 10 seconds.

9. A method according to any one of claims 5 to 8, wherein the series of delays ranges from zero to 10 seconds with a resampling interval of 1 second.

10. A method according to any one of claims 5 to 8, wherein the series of delays has a resampling interval of 0.1 to 2 seconds and is from negative 10 seconds to positive 10 seconds.

11. A method according to any one of claims 5 to 8, wherein the series of delays is from zero to 5 seconds with a resampling interval of 0.1 to 2 seconds.

12. 1. A method for monitoring arterial blood pressure in a patient and detecting nociception in said patient, comprising: receiving, by a hemodynamic monitor, sensed hemodynamic data representative of an arterial pressure waveform of the patient; performing, by a hardware processor of the hemodynamic monitor, a waveform analysis of the sensed hemodynamic data to calculate a plurality of signal measurements of the sensed hemodynamic data; calculating, by the hardware processor of the hemodynamic monitor, a cross-correlation measurement between each of the signal measurements; outputting the cross-correlation measurements to a user interface; and monitoring the cross-correlation measurements for bursts in the cross-correlation measurements; detecting a nociceptive event in the patient when a burst in one or more of the cross-correlation measurements is output to the user interface.

13. performing a waveform analysis of the sensed hemodynamic data to calculate the plurality of signal measurements of the sensed hemodynamic data; identifying individual cardiac cycles in the arterial pressure waveform; identifying a dicrotic notch in each of said individual cardiac cycles; identifying a systolic up phase, a systolic down phase, and a diastole in each of said individual cardiac cycles; and extracting the plurality of signal measurements from each of the systolic up phase, the systolic down phase, and the diastole from each of the individual cardiac cycles.

14. 14. The method of claim 13, wherein the plurality of signal measurements comprises hemodynamic effects from each of the systolic rise phase, the systolic decay phase, and the diastole from each of the individual cardiac cycles, the hemodynamic effects comprising contractility, aortic compliance, stroke volume, vascular tone, afterload, and total cardiac cycle, and the plurality of signal measurements comprises mean, maximum, minimum, duration, area, standard deviation, derivative, and / or morphological measurements from each of the systolic rise phase, the systolic decay phase, and the diastole from each of the individual cardiac cycles, and / or the plurality of signal measurements comprises heart rate, respiratory rate, stroke volume, pulse pressure, pulse pressure variation, stroke volume variation, mean arterial pressure (MAP), systolic pressure (SYS), diastolic pressure (DIA), heart rate variability, cardiac output, peripheral resistance, vascular compliance, and / or left ventricular contractility extracted from each of the individual cardiac cycles.

15. The method of any of claims 12 to 14, wherein the user interface includes at least one of a display screen and a speaker.

16. 1. A system for monitoring arterial blood pressure in a patient and providing alerts to a healthcare professional regarding nociception in said patient, comprising: a hemodynamic sensor for generating hemodynamic data representative of an arterial pressure waveform of the patient; a system memory storing nociceptive detection software code; a user interface including a sensory alarm that provides a sensory signal to alert the healthcare professional of a nociceptive event in the patient; a hardware processor executing the nociceptive detection software code, performing a waveform analysis of the hemodynamic data to determine a plurality of signal measurements; grouping the plurality of signal measurements into signal measurement pairs; measuring a cross-correlation between each of said pairs of signal measurements; outputting the cross-correlation measurements of the pairs of signal measurements to the user interface; monitoring the measurements of cross-correlation between pairs of signal measurements for bursts in the measurements of cross-correlation between pairs of signal measurements; a hardware processor configured to invoke a sensory alarm in the user interface indicating a nociceptive event in response to a burst in one or more of the measurements of cross-correlation of pairs of the signal measurements.

17. The system of claim 16 , wherein the hemodynamic sensor is a non-invasive hemodynamic sensor mountable at an extremity of the patient.

18. The system of claim 16 , wherein the hemodynamic sensor is a minimally invasive arterial catheter-based hemodynamic sensor.

19. The system of any of claims 16 to 18, wherein the hemodynamic sensor generates the hemodynamic data as an analog hemodynamic sensor signal representative of the arterial pressure waveform of the patient.

20. 20. The system of claim 19, further comprising an analog-to-digital converter that converts the analog hemodynamic sensor signal into digital hemodynamic data representative of the arterial pressure waveform of the patient.

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