System and method for detecting and correcting hemodynamic instability in hemodynamic measurements

Abstract

A system and method for detecting hemodynamic instability occurring in a subject and correcting hemodynamic measurements is provided. The system receives first measurement data corresponding to one or more hemodynamic parameters from a hemodynamic measurement system. One or more hemodynamic parameters are then derived from the second measurement data. A hemodynamic instability parameter is determined based on at least one of: i) calculating a difference between the first measurement data and the second measurement data, and ii) a characteristic derived from the second measurement data. In the event that the hemodynamic instability parameter is determined to exceed a predefined limit, the first measurement data is corrected in the hemodynamic measurement system and reported to the user.

Description

Technical Field

[0001] The present disclosure generally relates to non-invasive hemodynamic monitoring. More specifically, embodiments herein describe a system and method for detecting hemodynamic instability occurring in a subject and correcting hemodynamic measurement data in order to accurately and reliably measure hemodynamic parameters of the subject using a hemodynamic measurement system. Background Art

[0002] Hemodynamic measurement systems, such as for example a ShellCuff (SC) system or an Advanced Monitoring Cuff (AMC) system, are non-invasive hemodynamic monitoring techniques that can measure hemodynamic (HDM) parameters such as stroke volume (SV) and cardiac output (CO). The accuracy and precision of SV and CO measurements of the SC or AMC system are important aspects of the SC or AMC system compared to competing non-invasive HDM solutions.

[0003] The percentage error (PE) in CO is an important differentiating factor between various CO measurements. Therefore, a solution is needed that will result in more accurate measurements of SV and CO by the SC or AMC system. Additionally, the performance of competing solutions varies with the patient population. Therefore, having a solution that performs stably across various patient populations or demographics is crucial. Thus, a solution that detects and prevents inaccurate results during HDM measurements will contribute to this goal.

[0004] Current SC measurements take approximately 90 seconds. Any hemodynamic instability occurring during this measurement time will result in inaccuracies in the measured SV and CO. Instability can occur, for example, in heart rate (HR), respiratory rate / breathing rate (RR / BR), tidal volume (TV), or blood pressure (BP). Any hemodynamic instability occurring during this measurement time affects the accuracy of the resulting SV and CO measurement results, which can thus lead to inadequate medical assessment, diagnosis, and / or medical treatment. Therefore, it is important to appropriately handle such instabilities for intermittent SC measurements. For the inference of hemodynamic parameters and notification to the clinician, for example, if the accuracy of the SV and CO parameters may be in question, the instability needs to be considered based on the detection of such instability.

[0005] The most common complications caused by hemodynamic instability during or after surgery in patients are myocardial injury (MINS) and acute kidney injury (AKI). There is sufficient evidence to demonstrate a significant association between the degree and duration of intraoperative and postoperative hypotension and MINS and AKI. In addition, hypotension is the most common cause of hemodynamic instability in critically ill patients. Although anesthesia-related deaths are rare, deaths within 30 days after surgery are still surprisingly common. Therefore, it is important to measure the patient's blood pressure frequently, accurately, and reliably during and after surgery, where the SC system plays an important role. Therefore, making the measurements provided by the SC system more reliable is a key objective to be achieved.

[0006] US2006 / 155207A1 discloses a system and method for detecting incomplete reciprocation, including evaluating data of a time series representing at least one component of a parameter, detecting a first change in the data, detecting a second change in the data, and detecting incomplete reciprocation.

[0007] EP1742155 A2 discloses the determination of a clinical state of an object, including applying a corresponding adaptive transformation to at least one measurement signal obtained from the object and forming a diagnostic index that depends on the transformed measurement signal(s) and serves as a measure of the clinical state of the object.

[0008] WO2017 / 100188A2 discloses methods and devices for determining a patient's hemodynamic state by using venous return or trend observations of system perturbations over time.

[0009] US2015 / 265218A1 discloses methods and devices for non-invasively and continuously controlling the measurement of parameters in a fluid system, including arterial blood pressure within a living object, during conditions of degraded or lost hemodynamic signals.

[0010] By comparing the described system with some aspects of the present disclosure, the limitations and disadvantages of conventional and traditional methods will become apparent to those of ordinary skill in the art, as set forth in the remainder of this application and with reference to the accompanying drawings. Summary of the Invention

[0011] As described above, accurately and reliably measuring an object's hemodynamic parameters using a hemodynamic measurement system is currently challenging. The claimed solution rooted in computer technology overcomes problems that arise in the field of computer technology, particularly when detecting and correcting hemodynamic instability in hemodynamic measurements.

[0012] In the claimed solution of the present disclosure, a system is provided that includes a memory and a processing system communicatively coupled to the memory. The processing system is configured to receive first measurement data corresponding to one or more hemodynamic parameters from a hemodynamic measurement system. The hemodynamic measurement system is a non-invasive blood pressure (NIBP) measurement system. The NIBP measurement system includes an NIBP algorithm and uses tissue pressure (TP) signals and / or patient demographic data to make measurements. The one or more hemodynamic parameters may include, but are not limited to: stroke volume (SV), cardiac output (CO), heart rate (HR), respiratory rate (RR), respiratory depth, tidal volume (TV), and blood pressure (BP).

[0013] The processing system is further configured to derive one or more hemodynamic parameters based on second measurement data. The second measurement data may include, but are not limited to, electrocardiogram (ECG) data, bioimpedance data, pulse oximetry data, photoplethysmography (PPG) data, ventilator data, electroencephalogram (EEG) data, tissue pressure (TP) waveforms, and PPG waveforms. The second measurement data may correspond to a second measurement before, during, or after the hemodynamic measurement that provided the first measurement data.

[0014] According to aspects of the present disclosure, the processing system is configured to derive at least one of the following: heart rate from the ECG data; pulse rate from the TP or PPG waveforms; respiratory rate or breathing rate from the ECG, bioimpedance, PPG, or ventilator data; a measure of tidal volume (TV) or respiratory depth from the ECG, bioimpedance, PPG, or ventilator data; a change in blood pressure based on a change in pulse arrival time (PAT), which is measurable between the R peak in the ECG signal and the cardiac pulse in the PPG, bioimpedance, or TP signal; and a change in the bispectral index (BIS) based on the power distribution of the Fourier transform of the EEG signal.

[0015] The processing system is configured to determine a hemodynamic instability parameter based on at least one of the following: i) calculating the difference between the first measurement data and the second measurement data, and ii) characteristics derived from the second measurement data. The characteristics include changes in the one or more hemodynamic parameters derived from the second measurement data.

[0016] The processing system is further configured to determine whether the hemodynamic instability parameter exceeds a predefined limit. In the case where it is determined that the hemodynamic instability parameter exceeds the predefined limit, the processing system is configured to correct the first measurement data in the hemodynamic measurement system.

[0017] According to an aspect of the present disclosure, the system is configured to report the hemodynamic instability to a user.

[0018] According to another aspect of the present disclosure, the system is configured to abort and restart a measurement process based on the determined hemodynamic instability.

[0019] According to yet another aspect of the present disclosure, the system may be configured to: receive first raw measurement data corresponding to one or more first raw hemodynamic parameters from a hemodynamic measurement system, and derive one or more subsequent second hemodynamic parameters based on subsequent second raw measurement data. Additionally, the system may be configured according to this aspect to: determine a hemodynamic instability parameter based on at least one of the following: i) calculating a difference between the first raw measurement data and the subsequent second raw measurement data, and ii) a characteristic derived from the subsequent second measurement data; determine whether the hemodynamic instability parameter exceeds a predefined limit; and retrospectively correct the first raw measurement data in the hemodynamic measurement system in the case where it is determined that the hemodynamic instability parameter exceeds the predefined limit.

[0020] A main object of the present disclosure is to detect hemodynamic instability before, during, or after a measurement process, which further allows (1) interrupting and restarting the measurement (interrupting only in the case of detection before and during the measurement process), or (2) reporting the hemodynamic instability, or (3) correcting the measurement result for a given observed instability, or (4) avoiding false alarms.

[0021] Another object of the present disclosure is to make the measurements provided by the hemodynamic measurement system more reliable.

[0022] To effectively address the problem of hemodynamic instability occurring during the measurement time, the solution of the present disclosure provides an improved method, wherein the system automatically notifies a clinician of the occurrence of hemodynamic instability, such that the clinician may decide not to use the SV and CO measurement results with suspect accuracy. According to another aspect of the present disclosure, the system automatically corrects the inferred parameters where applicable.

[0023] Furthermore, the solution of the present disclosure overcomes the drawbacks of current SC system designs by detecting hemodynamic instability occurring before, during, and after the hemodynamic measurement process. Information regarding the hemodynamic instability is used to evaluate the accuracy of the measurements carried out. If the information indicates the occurrence of hemodynamic instability, the measurement is considered inaccurate, and the clinician is made aware of this to prevent them from drawing clinical conclusions from inaccurate measurements. This further prevents drawing false conclusions on a patient monitor and triggering false alarms.

[0024] In addition, the solution of the present disclosure provides an improved method that can partially correct hemodynamic instabilities occurring before, during, and after the measurement process, thereby improving the accuracy and reliability of measured HDM parameters such as SV and CO.

[0025] It should be understood that all combinations of the foregoing concepts and additional concepts discussed in more detail below (assuming such concepts are not mutually contradictory) are considered to be part of the subject matter disclosed herein. In particular, all combinations of the claimed subject matter appearing at the end of the present disclosure are contemplated to be part of the subject matter disclosed herein. It should also be understood that terms explicitly employed herein that may also appear in any incorporated-by-reference disclosure should be accorded a meaning most consistent with the particular concepts disclosed herein.

[0026] These and other aspects of the various embodiments will be apparent and elucidated with reference to the embodiments described below. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The various advantages of the embodiments will become apparent to those skilled in the art by reading the following specification and the appended claims, and by referring to the following drawings, in which:

[0028] Figure 1 is a general block diagram illustrating an implementation of the system and / or method described herein according to an exemplary embodiment of the present disclosure.

[0029] Figure 2 is a diagram illustrating a hemodynamic instability detection and correction system according to an exemplary embodiment of the present disclosure.

[0030] Figure 3 is a flowchart illustrating a method for detecting hemodynamic instabilities occurring in an object and correcting hemodynamic measurement data according to an exemplary embodiment of the present disclosure.

[0031] Figure 4 is a block diagram illustrating an example computer program product according to an exemplary embodiment of the present disclosure.

[0032] Figure 5 is a diagram illustrating an example of a system for detecting hemodynamic instabilities occurring in an object and correcting hemodynamic measurement data according to an exemplary embodiment of the present disclosure.

[0033] Figure 6 is a diagram illustrating a semiconductor device according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0034] As will be described in more detail below, in some embodiments discussed herein, a system and method are provided to detect hemodynamic instability occurring in an object and to correct hemodynamic measurement data.

[0035] Figure 1 is a general block diagram illustrating an embodiment of the system and / or method described herein according to an exemplary embodiment of the present disclosure. Referring Figure 1 to, a system 100 is shown, which includes a hemodynamic measurement system 102, a measurement control unit 104, a hemodynamic instability detection and correction system 106, an algorithm 108, input parameters, including a tissue pressure (TP) signal 110, additional measurement result inputs 112 (measurement results 112A - 112N), and patient demographic data 114, hemodynamic (HDM) parameters 116, and a hemodynamic instability output 118.

[0036] The hemodynamic measurement system 102 includes non-invasive hemodynamic monitoring techniques and may also include suitable logic, interfaces, and / or code that can be configured to measure HDM parameters, which may include, but are not limited to, stroke volume (SV) and cardiac output (CO). The hemodynamic measurement system 102 is a shell cuff (SC) system or an advanced monitoring cuff (AMC) system. The shell cuff is a technique for measuring blood pressure via a rigid cuff. More background information on this cuff can be found in the patent literature: EP2953528B1.

[0037] The hemodynamic instability detection and correction system 106 may include suitable logic, interfaces, and / or code that can be configured to detect hemodynamic instability occurring in an object and to correct hemodynamic measurement data.

[0038] According to an embodiment, the SC system uses the TP signal 110 and patient demographic data 114 to perform its measurements. Based on additional measurement inputs 112 that may include, but are not limited to Figure 1 electrocardiogram (ECG) data, bioimpedance data, pulse oximetry data (photoplethysmography (PPG) data), ventilator data, and electroencephalogram (EEG) data (indicated by measurement results 112A…measurement results 112N) among others, the occurrence of hemodynamic instability can be detected shortly before, during, and shortly after the measurement process.

[0039] The presence of ECG, bioimpedance, PPG, ventilator, and EEG data provides the following information throughout the measurement:

[0040] Heart rate (HR, from ECG) or pulse rate (PR, from tissue pressure (TP) or PPG waveform);

[0041] The respiratory rate (BR) or breathing rate (RR) can be obtained from ECG, bioimpedance, PPG, or ventilator data;

[0042] The tidal volume (TV) or a measure of the depth of breathing can be obtained from ECG, bioimpedance, PPG, or ventilator data;

[0043] The change in blood pressure can be determined, for example, based on the change in the pulse arrival time (PAT), which is measured between the R peak in the ECG signal and the cardiac pulse in the PPG, bioimpedance, or TP signal.

[0044] The change in the bispectral index (BIS) based on the power distribution of the Fourier transform of the EEG signal, which has been shown to be related to the change in hemodynamic parameters.

[0045] According to an embodiment, any significant change in the measurement of HR (or PR), RR / BR, TV, BP, or an EEG-derived parameter (such as BIS) can be considered a sign of hemodynamic instability. If hemodynamic instability is detected:

[0046] This information can be reported to the user as the hemodynamic instability output 118, so that the user can consider this when evaluating the results.

[0047] This information can be used in the cuff algorithm 108 to correct the effect of hemodynamic instability and output the corrected HDM parameter 116.

[0048] The cuff measurement control unit 104 can use this information to abort and restart the measurement process.

[0049] According to another embodiment, the additional measurements proposed above for evaluating hemodynamic instability can also be used with a traditional inflatable cuff for non-invasive blood pressure (NIBP) measurement. That is, before, during, and after the traditional NIBP measurement process, additional measurements can be used to detect the occurrence of hemodynamic instability. If hemodynamic instability is detected:

[0050] This information can be reported to the user as the hemodynamic instability output 118, so that the user can consider this when evaluating the results.

[0051] This information can be used by the NIBP algorithm 108 to correct the effect of hemodynamic instability and output the corrected HDM parameter 116.

[0052] The NIBP measurement control unit 104 can use this information to abort and restart the measurement process.

[0053] Figure 2FIG. is a diagram illustrating a hemodynamic instability detection and correction system according to an exemplary embodiment of the present disclosure. Referring to Figure 2 , a hemodynamic instability detection and correction system 106 is shown, which includes a memory 202, a processing system 204, an input component 206, a communication unit 208, an export component 210, a detection component 212, a correction component 214, and an output component 216.

[0054] The memory 202 may include, but is not limited to, one or more memory devices, persistent storage devices, computer-readable storage media, random access memory (RAM), and cache memory. Generally, the memory 202 may include any suitable volatile or non-volatile computer-readable storage media. The memory 202 may include suitable logic and / or interfaces, which may be configured to store instructions (e.g., computer-readable program code) that may implement various aspects of the present disclosure.

[0055] The memory 202 is communicatively coupled to the input component 206, the processing system 204, and the output component 216.

[0056] The processing system 204 may include suitable logic, interfaces, and / or code, which may be configured to run instructions stored in the memory 202 to implement various functions of the hemodynamic instability detection and correction system 106 according to various aspects of the present disclosure. The processing system 204 may also be configured to communicate with various modules of the hemodynamic instability detection and correction system 106 via the communication unit 208.

[0057] The communication unit 208 may be configured to transfer data between modules, engines, databases, memories, and other components of the hemodynamic instability detection and correction system 106 for performing the functions discussed herein. The communication unit 208 may include one or more communication types and utilize various communication methods for communication within the hemodynamic instability detection and correction system 106.

[0058] The input component 206 may include suitable logic, interfaces, and / or code, which may be configured to receive first measurement data corresponding to one or more hemodynamic parameters from a hemodynamic measurement system 102. The hemodynamic measurement system 102 is a non-invasive blood pressure (NIBP) measurement system. The NIBP measurement system includes a NIBP algorithm (algorithm 108) and uses a tissue pressure (TP) signal 110 and / or patient demographic data 114 for measurement. One or more hemodynamic parameters may include, but are not limited to: stroke volume (SV), cardiac output (CO), heart rate (HR), respiratory rate (RR), respiratory depth, tidal volume (TV), and blood pressure (BP).

[0059] The derivation component 210 may include suitable logic, interfaces, and / or code that may be configured to derive one or more hemodynamic parameters based on the second measurement data. The second measurement data may include, but is not limited to, electrocardiogram (ECG) data, bioimpedance data, pulse oximetry data, photoplethysmography (PPG) data, ventilator data, electroencephalogram (EEG) data, tissue pressure (TP) waveforms, and PPG waveforms.

[0060] According to aspects of the present disclosure, the derivation component 210 is configured to derive at least one of the following: heart rate from ECG data; pulse rate from TP or PPG waveforms; respiratory rate or breathing rate from ECG, bioimpedance, PPG, or ventilator data; tidal volume (TV) or measure of respiratory depth from ECG, bioimpedance, PPG, or ventilator data; change in blood pressure according to a change in pulse arrival time (PAT), the pulse arrival time being measurable between the R peak in the ECG signal and the cardiac pulse in the PPG, bioimpedance, or TP signal; and change in the bispectral index (BIS) based on the power distribution of the Fourier transform of the EEG signal.

[0061] The detection component 212 may include suitable logic, interfaces, and / or code that may be configured to determine a hemodynamic instability parameter based on at least one of the following: i) calculating the difference between the first measurement data and the second measurement data, and ii) a characteristic derived from the second measurement data. The characteristic includes a change in one or more hemodynamic parameters derived from the second measurement data.

[0062] The detection component 212 is further configured to determine whether the hemodynamic instability parameter exceeds a predefined limit.

[0063] The correction component 214 may include suitable logic, interfaces, and / or code that may be configured to correct the first measurement data in the hemodynamic measurement system based on an input received from the detection component 212 that the hemodynamic instability parameter exceeds the predefined limit.

[0064] The output component 216 may include suitable logic, interfaces, and / or code that may be configured to report hemodynamic instability to a user.

[0065] In addition, the hemodynamic instability detection and correction system 106 is configured to abort and restart the measurement process based on the determined hemodynamic instability.

[0066] According to an embodiment, detection, assessment, and reporting of the presence of hemodynamic instability during a shell cuff measurement process are described.

[0067] A shell-type cuff system can use additional measurement results (Measurement Results 112A…Measurement Results 112N) to evaluate hemodynamic instability during measurement. Additional inputs such as, but not limited to, ECG, bioimpedance, and pulse oximetry data (photoplethysmography (PPG) data) can be used to determine whether the patient's heart rate, respiratory rate, respiratory depth, and blood pressure are stable throughout the measurement. PPG data can be obtained from various body parts, such as peripherally at the finger, foot, or earlobe, or more centrally at the auricle, nasal septum, concha, or forehead.

[0068] The presence of ECG, bioimpedance, and PPG data provides the following information throughout the measurement:

[0069] By evaluating the inter-beat variation of the R-peaks in the ECG signal or the cardiac pulses in the TP or PPG signal, it is possible to assess whether the heart rate / pulse rate is stable throughout the measurement or whether arrhythmia has occurred.

[0070] By comparing the PR determined from the TP signal with the PR obtained from the PPG signal or the HR obtained from the ECG signal, the reliability of the TP signal can be evaluated. If the difference between the PR from the TP signal and the PR from the PPG signal or the HR from the ECG signal exceeds a predefined limit, i.e., if |PR TP -PR PPG | > PR lim or |PR TP -HR ECG | >

[0071] PR lim , then this can also be used as an indication that the SC measurement may be unreliable.

[0072] The respiratory cycle can be evaluated by analyzing the ECG, bioimpedance, and / or PPG signals. By evaluating the variation in the duration of individual respiratory cycles, it is possible to assess whether the respiratory rate is stable during the measurement. By evaluating the amplitude of individual respiratory cycles, a measure of the depth of individual respiratory cycles can be obtained, from which it is possible to determine whether the respiratory depth has become stable during the measurement.

[0073] By measuring the pulse arrival time (PAT) between, for example, the R-peaks in the ECG signal and the individual cardiac pulses in the TP or PPG signal obtained from, for example, a central location (such as, but not limited to, the alae nasi, nasal septum, forehead, or concha) or a peripheral location (such as the finger, earlobe, or foot), an alternative measure of blood pressure change can be obtained. If the PAT remains stable throughout the measurement, i.e., if the variation of the PAT throughout the measurement remains below a predefined threshold, it can be assumed that the blood pressure has remained stable during the measurement.

[0074] If instability is detected before or during the measurement of any of the HR / PR, RR, respiratory depth, or blood pressure / PAT parameters explained above, the instability will be reported to the user so that the user is aware of these instabilities when evaluating the HDM results provided by the shell cuff.

[0075] In the above embodiments, traditional NIBP measurements can be used instead of the shell cuff system.

[0076] According to another embodiment, the detection, evaluation, and reporting of the presence of hemodynamic instability during shell cuff measurements based on ventilator data are described.

[0077] Consider additional relevant background factors that can affect the patient's hemodynamic stability and thus can affect shell cuff measurements. For example, if the patient is on mechanical ventilation, the ventilator can measure whether the patient is following the ventilation rate and depth imposed by the ventilator, or whether the patient is deviating from the imposed ventilation rate or depth. Alternatively, if the patient is breathing spontaneously and only requires ventilator support, the ventilator can continuously measure the patient's spontaneous breathing rate and depth. Thus, in such a scenario, (1) the shell cuff system can use ventilator signals such as airway pressure and flow to detect any irregularities in the patient's respiratory rate or depth, or (2) the shell cuff system can use the ventilation rate and depth parameters measured by the ventilator to detect any irregularities in the patient's respiratory rate or depth. Also in such a scenario, respiratory information can be collected before, during, and after the SC measurement process to detect any instability in the respiratory / ventilation rate or depth.

[0078] If instability is detected before or during the measurement of the respiratory rate or depth, such instability will be reported to the user so that the user is aware of these instabilities when evaluating the HDM results provided by the shell cuff.

[0079] In the above embodiments, traditional NIBP measurements can be used instead of the shell cuff system.

[0080] According to yet another embodiment, the detection, evaluation, and reporting of the presence of hemodynamic instability during shell cuff measurements based on electroencephalogram (EEG) measurements are described.

[0081] The above parameters are directly related to cardiac function and activity (ECG, bioimpedance or pulse oximetry), but may also be affected by other body functions (such as the respiratory system in the case of pulse oximetry) or environmental conditions (such as ambient temperature, as sweating will affect bioimpedance). Thus, combinations of different effects may have an impact on blood pressure and other hemodynamic parameters of the vascular system that are directly dependent on each other. However, it is beneficial to have an additional physiological parameter (and measurement result) that is not directly related to human hemodynamics and is thus a more independent parameter for assessing possible hemodynamic instabilities during cuff measurements.

[0082] Electroencephalogram (EEG) measurements can be used to identify changes in hemodynamic parameters. Among them, the bispectral index (BIS, which is based on the power distribution of the Fourier transform of the EEG signal) is compared with the measurement results of heart rate (HR) and mean arterial blood pressure (MAP).

[0083] Thus, in another embodiment, it is proposed to use electroencephalogram (EEG) measurements to evaluate possible hemodynamic instabilities during SC measurements. The required EEG electrodes can be directly connected to the patient monitor to which the cuff is connected, or to a separate EEG scanner that can communicate with the SC-PM (cuff-patient monitor) or can be monitored by the operator.

[0084] If an instability is detected before or during the measurement process in an EEG-derived parameter such as BIS, this will be reported to the user, so that the user is aware of these instabilities when evaluating the HDM results provided by the cuff.

[0085] In this embodiment, traditional NIBP measurements can be used instead of the cuff system.

[0086] According to yet another embodiment, an automatic action of a system is disclosed. This includes automatically stopping and restarting the measurement in case of detected hemodynamic instability.

[0087] If a hemodynamic instability is detected in any of the mentioned parameters during the measurement process, the system can also automatically abort and restart the measurement process by providing the instability detection to the measurement control unit 104. Alternatively, the measurement control unit 104 can abort the measurement upon receiving a detection of hemodynamic instability and then request user input to restart the measurement.

[0088] According to another embodiment, the detected hemodynamic instability is corrected. In the case where hemodynamic instability is detected, the results of the cuff measurements can be corrected. For example, these corrections can be made during the measurement process or retrospectively after the complete measurement cycle of the cuff system has been completed. Various hemodynamic instabilities can be detected and corrected:

[0089] In the case where arrhythmias (such as missed beats or premature beats) are detected from the ECG, PPG, or TP waveforms, these beats can be corrected in the TP waveform by the following operation: interpolating adjacent normal beats in the TP waveform to correct for the missed beats or premature beats. This then allows the cuff algorithm 108 to be further run to determine the SV, CO, and other HDM parameters. Since this correction requires normal adjacent beats, the correction for missed or premature beats can only be made when the number of missed beats or premature beats is limited within the recorded duration. In this case, traditional NIBP measurements can be used instead of the cuff system, and then the cuff pressure signal is corrected.

[0090] The cuff determines the mean arterial pressure (MAP) as the clamping pressure associated with the occurrence of the maximum oscillation. The systolic and diastolic blood pressures are also determined relative to the occurrence of the maximum oscillation.

[0091] If the blood pressure increases during the measurement process, the maximum value of the envelope will shift to the right. Therefore, the mean pressure, systolic pressure, and diastolic pressure are overestimated. If the blood pressure decreases during the measurement process, the envelope will start to decay faster. Therefore, the mean pressure, systolic pressure, and diastolic pressure will be underestimated. Since these pressures are used to determine the SV and CO, this will also affect the resulting SV and CO. The SV estimated by the cuff and thus the CO are inversely correlated with the mean arterial pressure (MAP). Therefore, if the MAP is overestimated, this will result in an underestimation of the SV and CO, and if the MAP is underestimated, this will result in an overestimation of the SV and CO.

[0092] By utilizing the measured pulse arrival time (PAT), it can be determined whether the blood pressure is stable during the measurement process, or whether the blood pressure is increasing or decreasing during the measurement process. By determining the difference in PAT during the measurement process as ΔPAT = PAT 结束 - PAT 开始 , it is possible to distinguish the following cases:

[0093] If the PAT is stable throughout the measurement process, i.e., ΔPAT = 0 or ΔPAT is below a predefined threshold |ΔPAT| < ΔPAT lim , then this confirms that the blood pressure remains stable during the measurement process, and the resulting SV and CO will be accurate and can be trusted.

[0094] If PAT increases during the measurement process, i.e., ΔPAT > 0 or ΔPAT > ΔPAT lim , this indicates that the blood pressure decreases during the measurement process, and the mean pressure and systolic pressure are underestimated, and SV and CO are overestimated.

[0095] If PAT decreases during the measurement process, i.e., ΔPAT < 0 or ΔPAT < ΔPAT lim , this indicates that the blood pressure increases during the measurement process, and the mean pressure and systolic pressure are overestimated, and SV and CO are underestimated.

[0096] By taking advantage of the change in PAT during the measurement process, as indicated by ΔPAT, the SV and CO measurement results can be corrected for the resulting change in blood pressure in, for example, the following manner:

[0097] SV 校正 = SV - α corr ΔPAT,

[0098] CO 校正 = PR × SV 校正

[0099] where α corr is a positive correction factor.

[0100] In the case where the correction is being applied by algorithm 108, this is also reported to the user to make the user aware of the correction, so that these can be taken into account in the evaluation of the results.

[0101] In this case, the measured NIBP parameters can also be corrected taking into account the measured ΔPAT. That is, the correction of the systolic blood pressure, mean blood pressure, or diastolic blood pressure can be considered as:

[0102] BP 校正 = BP + β corr ΔPAT

[0103] where BP represents any one of the systolic blood pressure, mean pressure, or diastolic blood pressure, and β corr is a positive correction factor. In the context of the correction of the BP parameters, a shell cuff system or a conventional NIBP measurement system can be used.

[0104] According to yet another embodiment, an assessment of hemodynamic stability is described prior to starting the measurement to recommend the most suitable measurement mode of the shell cuff system.

[0105] Additional measurement data such as ECG, bioimpedance, pulse oximetry / PPG, ventilator, and EEG data are used to evaluate the hemodynamic stability of a patient before measurement. In the case where measurement is initiated using a cuff system, if the additional measurement indicates that the patient is hemodynamically unstable, the following actions can be taken:

[0106] In one embodiment, the cuff system can recommend not initiating a full measurement because the patient is hemodynamically unstable.

[0107] In another embodiment, the cuff system has a fast measurement mode in addition to the full measurement mode and can recommend switching to the fast measurement mode suitable for use during hemodynamic instability. For example, the cuff system can have a fast measurement mode that supports only a limited number of parameters, which can be measured with the required accuracy within a time period shorter than 90 s. That is, compared with the full measurement mode, the fast measurement mode measures a reduced number of parameters, where the full measurement mode requires a measurement time of about 90 s.

[0108] The method and solution of this embodiment can also be extended to traditional inflated cuff NIBP measurement, where the possibility of measuring a reduced set of parameters with the required accuracy within a shortened time period can also be provided.

[0109] Figure 3 is a flowchart illustrating a method for detecting hemodynamic instability occurring in an object and correcting hemodynamic measurement data according to an exemplary embodiment of the present disclosure. Refer to Figure 3 , a flowchart of a method 300 for detecting hemodynamic instability occurring in an object and correcting hemodynamic measurement data is shown.

[0110] At 302, first measurement data corresponding to one or more hemodynamic parameters is received from a hemodynamic measurement system. The input component 206 is configured to receive the first measurement data corresponding to one or more hemodynamic parameters from the hemodynamic measurement system 102. The one or more hemodynamic parameters can include but are not limited to: stroke volume (SV), cardiac output (CO), heart rate (HR), respiratory rate (RR), respiratory depth, tidal volume (TV), and blood pressure (BP).

[0111] At 304, one or more hemodynamic parameters are derived based on one or more second measurement data. The derivation component 210 is configured to derive one or more hemodynamic parameters based on the second measurement data. The second measurement data may include, but is not limited to: electrocardiogram (ECG) data, bioimpedance data, pulse oximetry data, photoplethysmography (PPG) data, ventilator data, electroencephalogram (EEG) data, tissue pressure (TP) waveform, and PPG waveform.

[0112] At 306, a hemodynamic instability parameter is determined based on at least one of the following: i) calculating a difference between the first measurement data and the second measurement data, and ii) a characteristic derived from the second measurement data. The detection component 212 is configured to determine a hemodynamic instability parameter based on at least one of the following: i) calculating a difference between the first measurement data and the second measurement data, and ii) a characteristic derived from the second measurement data. The characteristic includes a change in one or more hemodynamic parameters derived from the second measurement data.

[0113] At 308, it is determined whether the hemodynamic instability parameter exceeds a predefined limit. The detection component 212 is configured to determine whether the hemodynamic instability parameter exceeds a predefined limit.

[0114] At 310, in the case where it is determined that the hemodynamic instability parameter exceeds the predefined limit, the first measurement data in the hemodynamic measurement system is corrected. The correction component 214 is configured to correct the first measurement data in the hemodynamic measurement system based on receiving an input from the detection component 212 that the hemodynamic instability parameter exceeds the predefined limit.

[0115] Many different ways of performing the above method are possible, as will be apparent to those skilled in the art. For example, the steps may be performed in the order shown, but the order of the steps may vary, or some steps may be performed in parallel. Additionally, other method steps may be inserted between the steps. The inserted steps may represent a refinement of the method such as described herein, or may be unrelated to the method. For example, some steps may be performed at least partially in parallel. Additionally, a given step may not be fully completed before the next step begins.

[0116] Embodiments of the method can be implemented using software that includes instructions for causing a processor system to execute method 300. The software can include only those steps taken by a particular sub-entity of the system. The software can be stored in a suitable storage medium, such as a hard disk, floppy disk, memory, optical disk, etc. The software can be sent as a signal along a wire or wirelessly or using a data network (e.g., the Internet). The software can be available for download and / or used remotely on a server. The method can be implemented using a bitstream arranged to configure programmable logic (e.g., a field programmable gate array (FPGA)).

[0117] It should be understood that the presently disclosed subject matter also extends to computer programs suitable for putting the presently disclosed subject matter into practice, particularly computer programs on or in a carrier. The program can take the form of source code, object code, code intermediate between source and object code, such as in a partially compiled form, or any other form suitable for implementing embodiments of the method. Embodiments involving a computer program product include computer-executable instructions corresponding to each of the processing steps in at least one of the methods set forth. These instructions can be subdivided into subroutines and / or stored in one or more files that can be statically or dynamically linked. Another embodiment involving a computer program product includes computer-executable instructions corresponding to each of the devices, units, and / or parts in at least one of the systems and / or products set forth.

[0118] Figure 4 is a block diagram illustrating an example computer program product in accordance with an exemplary embodiment of the present disclosure. Referring Figure 4 , there is shown a computer program product 400 that includes a machine-readable storage device 402, which may also include logic 404. In some implementations, the machine-readable memory 402 can be implemented as a non-transitory machine-readable memory. In some implementations, the logic 404 can be implemented as machine-readable instructions, such as software. In an embodiment, when executed, the logic 404 implements one or more aspects of method 300( Figure 3 ), and / or implements system 100( Figure 1 ) that has been discussed.

[0119] Figure 5 is a diagram illustrating an example of a system for detecting hemodynamic instability occurring in an object and correcting hemodynamic measurement data in accordance with an exemplary embodiment of the present disclosure. Referring Figure 5 , in the example shown, the system 500 can include a processor 502 and a memory 504 communicatively coupled to the processor 502. The memory 504 can include logic 506 as an instruction set. In some implementations, the logic 506 can be implemented as software. In an embodiment, when executed by the processor 502, the logic 506 implements method 300(Figure 3 ) one or more aspects, and / or implement the system 100 that has been discussed Figure 1 ).

[0120] In some embodiments, the processor 502 may include a general controller, a dedicated controller, a storage controller, a storage manager, a memory controller, a microcontroller, a general-purpose processor, a dedicated processor, a central processing unit (CPU), etc. and / or combinations thereof.

[0121] In addition, embodiments may include distributed processing, component / object distributed processing, parallel processing, etc. and / or combinations thereof. For example, virtual computer system processing may implement one or more of the methods or functions described herein, and the processor 502 described herein may be used to support such virtual processing.

[0122] In some examples, the memory 504 is an example of a computer-readable storage medium. For example, the memory 504 may be any memory accessible to the processor 502, including but not limited to RAM memory, registers, and register files, etc. and / or combinations thereof. References to "computer memory" or "memory" should be interpreted as potentially multiple memories. The memory may, for example, be multiple memories within the same computer system. The memory may also be multiple memories distributed among multiple computer systems or computing devices.

[0123] Figure 6 is a diagram illustrating a semiconductor device according to an exemplary embodiment of the present disclosure. The illustrated semiconductor device 600 (e.g., a chip and / or a package) includes one or more substrates 602 (e.g., silicon, sapphire, or gallium arsenide) and logic 604 (e.g., configurable logic and / or fixed-function hardware logic) coupled to the (one or more) substrates 602. In an embodiment, the logic 604 implements method 300 Figure 3 ) one or more aspects, and / or implement the system 100 that has been discussed Figure 1 ).

[0124] In some embodiments, the logic 604 may include a transistor array and / or other integrated circuit / IC components. For example, the configurable logic and / or fixed-function hardware logic implementation of the logic 604 may include configurable logic, such as a programmable logic array (PLA), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), or fixed-functional logic hardware using circuit technologies (e.g., application-specific integrated circuit (ASIC), complementary metal-oxide semiconductor (CMOS), or transistor-transistor logic (TTL) technology, etc. and / or combinations thereof).

[0125] All definitions as defined and used in this document shall be understood to govern over dictionary definitions, definitions in incorporated by reference documents, and / or ordinary meanings of the defined terms.

[0126] The subject matter described herein is sometimes illustrated with different components contained within or connected to different other components. It should be understood that such depicted architectures are merely exemplary, and that many other architectures that actually achieve the same functionality can be implemented. In a conceptual sense, any arrangement of components that achieves the same functionality is effectively "associated" such that the desired functionality is achieved. Thus, any two components that are combined in this document to achieve a particular functionality can be regarded as "associated" with each other such that the desired functionality is achieved, regardless of the architecture or intermediate components. The term "coupled" can be used herein to refer to any type of direct or indirect relationship between the components being discussed, and can apply to electrical, mechanical, fluid, optical, electromagnetic, electromechanical, or other connections. Similarly, any two components so associated can also be regarded as "operably connected" or "operably coupled" to each other to achieve the desired functionality, and any two components that can be so associated can also be regarded as "operably couplable" to each other to achieve the desired functionality. Specific examples of operably couplable include, but are not limited to, components that physically mate and / or physically interact.

[0127] In the claims and the foregoing specification, the terms "first", "second", etc. can be used herein solely for convenience of discussion and do not have a particular temporal or chronological significance, unless otherwise indicated.

[0128] In the claims and the foregoing specification, all transitional phrases such as "comprising", "including", "carrying", "having", "containing", "involving", "holding", "with", etc. shall be understood to be open-ended, i.e., meaning including but not limited to. Only the transitional phrases "consisting of" and "consisting essentially of" shall be closed or semi-closed transitional phrases, respectively.

[0129] As used in this document in the specification and claims, the words "a" and "an" shall be understood to mean "at least one", unless expressly indicated to the contrary.

[0130] As used herein, the term "or" or "and / or" is inclusive rather than exclusive, unless expressly stated otherwise or the context otherwise indicates. Thus, in this document, "A or B" means "A, B, or both", unless expressly stated otherwise or the context otherwise indicates. Additionally, "and" is both conjunctive and disjunctive, unless expressly stated otherwise or the context otherwise indicates. Thus, in this document, "A and B" means "A and B, jointly or severally", unless expressly stated otherwise or the context otherwise indicates.

[0131] As used herein in the specification and claims, the phrase "at least one" in reference to a list of one or more elements should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including every element specifically listed in the list of elements and at least one of each element, and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally exist in addition to those specifically identified within the list of elements to which the phrase "at least one" refers, whether related or unrelated to those specifically identified.

[0132] As used in this application and the claims, a list of items joined by the term "one or more of..." can mean any combination of the listed items. For example, the phrase "one or more of A, B, or C" can mean A; B; C; A and B; A and C; B and C; or A, B, and C.

[0133] As described in more detail above, one or more processors, other units, etc. and / or combinations thereof can implement the functions of several of the items recited in the claims.

[0134] As described in more detail above, a computer program can be stored / distributed on a suitable medium, such as an optical storage medium or a solid-state medium provided with or as part of other hardware, but the computer program can also be distributed in other forms, such as via the Internet or other wired or wireless telecommunication systems.

[0135] It should also be understood that, unless explicitly stated to the contrary, in any method discussed herein that includes more than one step or action, the order of the steps or actions of the method is not necessarily limited to the order in which the steps or actions of the method are recited. Additionally, such a method can include additional or alternative steps or actions. As used in the claims, although specific measures are recited in mutually distinct dependent claims, this does not indicate that combinations of these measures cannot be used advantageously.

[0136] Those skilled in the art will recognize from the foregoing description that the broad techniques of the embodiments of the present disclosure can be implemented in various forms. Accordingly, although the embodiments of the present disclosure have been described in connection with specific examples of the present disclosure, the true scope of the embodiments of the present disclosure should not be so limited, as other modifications will become apparent to those skilled in the art upon study of the drawings, the specification, and the appended claims.

Claims

1. A system for detecting hemodynamic instability occurring in an object and correcting hemodynamic measurement data, the system comprising: a memory; a processing system communicatively coupled to the memory, wherein the processing system is configured to: receive first measurement data corresponding to one or more hemodynamic parameters from a hemodynamic measurement system; derive one or more hemodynamic parameters based on second measurement data; determine a hemodynamic instability parameter based on at least one of: i) calculating a difference between the first measurement data and the second measurement data, and ii) a characteristic derived from the second measurement data; determine whether the hemodynamic instability parameter exceeds a predefined limit; and correct the first measurement data in the hemodynamic measurement system in the case where it is determined that the hemodynamic instability parameter exceeds the predefined limit.

2. The system according to claim 1, wherein, the hemodynamic measurement system is a non-invasive blood pressure (NIBP) measurement system, wherein the NIBP measurement system includes a NIBP algorithm.

3. The system according to claim 2, wherein, the NIBP measurement system uses at least one of a tissue pressure (TP) signal and patient demographic data for measurement.

4. The system according to claim 1, wherein, the one or more hemodynamic parameters include at least one of: stroke volume (SV), cardiac output (CO), heart rate (HR), respiratory rate (RR), respiratory depth, tidal volume (TV), and blood pressure (BP).

5. The system according to claim 1, wherein, the second measurement data includes at least one of: electrocardiogram (ECG) data, bioimpedance data, pulse oximetry data, photoplethysmography (PPG) data, ventilator data, electroencephalogram (EEG) data, tissue pressure (TP) waveform, and PPG waveform.

6. The system according to claim 1, wherein, the characteristic includes a change in the one or more hemodynamic parameters derived from the second measurement data.

7. The system according to claim 1, wherein, the processing system is configured to derive at least one of: heart rate from ECG data; pulse rate from TP or PPG waveform; respiratory rate or breathing rate from ECG, bioimpedance, PPG, or ventilator data; a measure of tidal volume (TV) or respiratory depth from ECG, bioimpedance, PPG, or ventilator data; blood pressure change based on a change in pulse arrival time (PAT), the pulse arrival time being measurable between the R peak in the ECG signal and the cardiac pulse in the PPG, bioimpedance, or TP signal; and a change in bispectral index (BIS), the bispectral index being based on the power distribution of the Fourier transform of the EEG signal.

8. The system according to claim 1, wherein, the system is configured to report the hemodynamic instability to a user.

9. The system according to claim 1, wherein, the system is configured to abort and restart a measurement process based on the determined hemodynamic instability.

10. A computer-implemented method for detecting hemodynamic instability occurring in an object and correcting hemodynamic measurement data, the method comprising: receiving first measurement data corresponding to one or more hemodynamic parameters from a hemodynamic measurement system; deriving one or more hemodynamic parameters based on second measurement data; determining a hemodynamic instability parameter based on at least one of: i) calculating a difference between the first measurement data and the second measurement data, and ii) a characteristic derived from the second measurement data; determining whether the hemodynamic instability parameter exceeds a predefined limit; and correcting the first measurement data in the hemodynamic measurement system in the case where it is determined that the hemodynamic instability parameter exceeds the predefined limit.

11. The computer-implemented method according to claim 10, wherein, the one or more hemodynamic parameters include at least one of: stroke volume (SV), cardiac output (CO), heart rate (HR), respiratory rate (RR), respiratory depth, tidal volume (TV), and blood pressure (BP).

12. The computer-implemented method according to claim 10, wherein, the second measurement data includes at least one of: electrocardiogram (ECG) data, bioimpedance data, pulse oximetry data, photoplethysmography (PPG) data, ventilator data, electroencephalogram (EEG) data, tissue pressure (TP) waveform, and PPG waveform.

13. The computer-implemented method according to claim 10, wherein, the characteristic includes a change in the one or more hemodynamic parameters derived from the second measurement data.

14. The computer-implemented method according to claim 10, wherein, deriving the one or more hemodynamic parameters based on the second measurement data includes deriving at least one of: heart rate from ECG data; pulse rate from TP or PPG waveform; respiratory rate or respiratory frequency from ECG, bioimpedance, PPG, or ventilator data; a measure of tidal volume (TV) or respiratory depth from ECG, bioimpedance, PPG, or ventilator data; blood pressure change based on a change in pulse arrival time (PAT), which can be measured between the R peak in the ECG signal and the cardiac pulse in the PPG, bioimpedance, or TP signal; and a change in bispectral index (BIS), which is based on the power distribution of the Fourier transform of the EEG signal.

15. A computer program product for detecting hemodynamic instability occurring in an object and correcting hemodynamic measurement data, the computer program product comprising at least one non-transitory computer-readable storage medium and computer-executable program code for performing the method according to claims 10-14.

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