Automatic calibration method, cardiac output monitoring method, device and monitoring device

Abstract

The present application relates to the technical field of medical equipment, in particular to an automatic calibration method, a cardiac output monitoring method, a device and a monitoring device, the method comprising: acquiring a pulse wave signal of a target monitoring object; extracting at least one signal feature of the pulse wave signal; and determining a target correction factor based on the at least one signal feature. The signal feature is determined by using the pulse wave signal of the target monitoring object, and in the calibration process, the at least one signal feature is combined for processing, so that the target correction factor is automatically calibrated, thereby improving the reliability of the monitoring result.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, specifically to automatic calibration methods, cardiac output monitoring methods, devices, and monitoring equipment. Background Technology

[0002] Currently, minimally invasive pulse contour cardiac output monitoring (Picco) technology is the mainstream product in the field of hemodynamic monitoring, enjoying high clinical and market acceptance. However, clinical research and literature reports have revealed that products using this technology cannot replace clinical "gold standards" such as pulmonary artery catheters. Moreover, in hemodynamically unstable conditions, it is easily affected by various factors, and the aforementioned methods cannot effectively solve problems such as low accuracy and correlation, resulting in poor performance.

[0003] In actual clinical applications, medical staff can only determine the timing of automatic recalibration based on personal experience and the recommendations in the product manual, in order to recalibrate the system's correction factor and improve the reliability of monitoring. Specifically, the collected pulse signal is processed using the calibration factor to obtain the measured value of cardiac output. If the calibration factor is unreliable, the obtained measured value of cardiac output will also be unreliable. However, since the pulse signal of each monitored subject is different, determining recalibration based solely on the manual's recommendations will result in significant deviations, leading to low reliability of the monitoring results. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide an automatic calibration method, a method for monitoring cardiac output, an apparatus, and a monitoring device to solve the problem of low reliability of monitoring results caused by the timing of recalibration.

[0005] According to a first aspect, embodiments of the present invention provide an automatic calibration method applied in a monitoring device, the method comprising:

[0006] Acquire the pulse wave signal of the target monitored object;

[0007] Extract at least one signal feature from the pulse wave signal;

[0008] The target correction factor is determined based on the at least one signal feature.

[0009] The automatic calibration method provided in this invention uses the pulse wave signal of the target monitored object to determine signal characteristics, and during the calibration process, it combines at least one signal characteristic for processing to achieve automatic calibration of the target calibration factor, thereby improving the reliability of the monitoring results.

[0010] In conjunction with the first aspect, in the first embodiment of the first aspect, determining the target correction factor based on the at least one signal feature includes:

[0011] The confidence level of the current correction factor is determined based on the at least one signal feature;

[0012] When the confidence level of the current correction factor does not meet the preset conditions, the calibration timing of the current correction factor is determined in order to determine the target correction factor.

[0013] The automatic calibration method provided in this embodiment of the invention determines the calibration timing of the current correction factor by judging the reliability of the current correction factor during the calibration timing process, and automatically calibrates the current correction factor, thereby improving the accuracy of the calibration timing of the current correction factor.

[0014] In conjunction with the first embodiment of the first aspect, in the second embodiment of the first aspect, determining the reliability of the current correction factor of the monitoring device based on the at least one signal feature includes:

[0015] Based on the at least one signal feature, calculate the reliability value corresponding to each of the signal features;

[0016] The reliability of the current correction factor is determined based on the relationship between the reliability value of each of the signal features and the first threshold.

[0017] The automatic calibration method provided in this embodiment of the invention calculates the corresponding reliability value of each feature, and then compares it with the first threshold to determine the reliability of the current correction factor. The reliability determination takes into account all signal features, which ensures the accuracy of the reliability of the current correction factor.

[0018] In conjunction with the second embodiment of the first aspect, in the third embodiment of the first aspect, determining the reliability of the current correction factor based on the relationship between the reliability value of each of the signal features and the first threshold includes:

[0019] The correlation between the various signal features is determined using each of the signal features;

[0020] Based on the correlation, each of the signal features is filtered to determine the target signal features;

[0021] The reliability of the current correction factor is determined based on the relationship between the reliability value of the target signal feature and the first threshold.

[0022] The automatic calibration method provided in this invention filters features by determining the correlation between various features, which can reduce the amount of data processing and improve the accuracy of the calculated reliability on the other hand.

[0023] In conjunction with the third embodiment of the first aspect, in the fourth embodiment of the first aspect, determining the reliability of the current correction factor based on the relationship between the reliability value of the target signal feature and the first threshold includes:

[0024] Obtain the weights of the target signal features;

[0025] The reliability value of the target signal feature is corrected based on the weight of the target signal feature to obtain the corrected reliability value.

[0026] The confidence level of the current correction factor is determined by counting the number of modified confidence values ​​of all the target signal features that are greater than the first threshold.

[0027] The automatic calibration method provided in this invention corrects the reliability value of target signal features by using the weights of each target signal feature to distinguish the influence of each feature on the monitoring results, thereby further ensuring the accuracy of the reliability.

[0028] In conjunction with the first embodiment of the first aspect, in the fifth embodiment of the first aspect, determining the calibration timing of the current correction factor when the confidence level of the current correction factor does not meet the preset conditions, in order to determine the target correction factor, includes:

[0029] When the confidence level of the current correction factor is less than the second threshold, the current moment is determined as the calibration time for the current correction factor, and the current correction factor is automatically calibrated to determine the target correction factor.

[0030] The automatic calibration method provided in this embodiment of the invention directly performs automatic calibration when it is determined that the current correction factor needs to be calibrated, thus ensuring the real-time nature of the calibration.

[0031] In conjunction with the first embodiment of the first aspect, in the sixth embodiment of the first aspect, determining the calibration timing of the current correction factor when the confidence level of the current correction factor does not meet the preset conditions, in order to determine the target correction factor, includes:

[0032] When the confidence level of the current correction factor is less than the second threshold, the current moment is determined as the calibration time for the current correction factor.

[0033] The monitoring interface of the monitoring device displays calibration reminder information;

[0034] In response to the selection result of the calibration reminder information;

[0035] When the selection result is confirmed calibration, the current correction factor is automatically calibrated to determine the target correction factor.

[0036] The automatic calibration method provided in this invention displays a calibration reminder when it is determined that the current correction factor needs calibration, so as to remind the user to confirm. This can avoid erroneous calibration operations caused by measurement errors and further improve the accuracy of monitoring results.

[0037] In conjunction with the sixth embodiment of the first aspect, in the seventh embodiment of the first aspect, the step of determining the calibration timing of the current correction factor when the confidence level of the current correction factor does not meet the preset conditions, so as to determine the target correction factor, further includes:

[0038] When the selection result is no calibration, the current correction factor is determined to be the target correction factor.

[0039] According to a second aspect, embodiments of the present invention also provide a method for monitoring cardiac output, comprising:

[0040] Acquire the pulse wave signal of the target monitored object;

[0041] Extract at least one signal feature from the pulse wave signal;

[0042] The target correction factor is determined based on the at least one signal feature;

[0043] The current cardiac output of the target monitored object is corrected based on the target correction factor to determine the target monitoring result.

[0044] The cardiac output monitoring method provided in this invention uses the pulse wave signal of the target monitored object to determine signal characteristics, and processes it in combination with at least one signal characteristic to determine a target calibration factor, and uses the target calibration factor to correct the current cardiac output, thereby improving the reliability of the target monitoring results.

[0045] In conjunction with the second aspect, in the first embodiment of the second aspect, the monitoring interface includes a pulse wave signal display area, a monitoring result display area, and a calibration reminder area, and the method further includes:

[0046] The pulse wave signal is displayed in the pulse wave signal display area, the monitoring result is displayed in the monitoring result display area, and the calibration reminder information is displayed in the calibration reminder area.

[0047] The cardiac output monitoring method provided in this embodiment of the invention simultaneously displays pulse wave signals, monitoring results, and calibration reminder information on the monitoring interface, so that users can intuitively understand the status of the target monitored object and make accurate calibration choices.

[0048] According to a third aspect, embodiments of the present invention also provide an automatic calibration device, comprising:

[0049] The first acquisition module is used to acquire the pulse wave signal of the target monitored object;

[0050] The first extraction module is used to extract at least one signal feature of the pulse wave signal;

[0051] The first determining module is used to determine the target correction factor based on the at least one signal feature.

[0052] According to a fourth aspect, embodiments of the present invention also provide a cardiac output monitoring device, comprising:

[0053] The second acquisition module is used to acquire the pulse wave signal of the target monitored object;

[0054] The second extraction module is used to extract at least one signal feature of the pulse wave signal;

[0055] The second determining module is used to determine the target correction factor based on the at least one signal feature;

[0056] The correction module is used to correct the current cardiac output of the target monitored object based on the target correction factor, and to determine the target monitoring result.

[0057] According to a fifth aspect, an embodiment of the present invention provides a monitoring device, including: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the automatic calibration method described in the first aspect or any embodiment of the first aspect.

[0058] According to a sixth aspect, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing the computer to perform the automatic calibration method described in the first aspect or any embodiment of the first aspect.

[0059] It should be noted that the corresponding beneficial effects of the automatic calibration device, cardiac output monitoring device, monitoring equipment, and computationally readable storage medium provided in the embodiments of the present invention can be found in the corresponding effects of the automatic calibration method and cardiac output monitoring method described above, and will not be repeated here. Attached Figure Description

[0060] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0061] Figure 1 This is a flowchart of an automatic calibration method according to an embodiment of the present invention;

[0062] Figure 2 This is a flowchart of an automatic calibration method according to an embodiment of the present invention;

[0063] Figure 3 This is a flowchart of a cardiac output monitoring method according to an embodiment of the present invention;

[0064] Figure 4 This is a schematic diagram of the monitoring interface according to an embodiment of the present invention;

[0065] Figure 5 This is a block diagram of a module for monitoring cardiac output according to an embodiment of the present invention;

[0066] Figure 6 This is a structural block diagram of an automatic calibration device according to an embodiment of the present invention;

[0067] Figure 7 This is a structural block diagram of a cardiac output monitoring device according to an embodiment of the present invention;

[0068] Figure 8 This is a schematic diagram of the hardware structure of the monitoring device provided in an embodiment of the present invention. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] The automatic calibration method provided in this invention determines the blood flow state of the target monitored object by analyzing its pulse wave signal. When a change in blood flow state is detected, it indicates that the correction factor of the monitoring device needs to be adjusted. Therefore, in this method, a change in blood flow state is the timing for automatic calibration.

[0071] The change in blood flow state is determined by analyzing the characteristics of the pulse wave signal. Specifically, regarding the automatic calibration of the correction factor, since the monitoring device is used to monitor the cardiac output of the target subject, and cardiac output monitoring is related to the correction factor, a change in blood flow state will correspondingly change the cardiac output. If the correction factor is not corrected at this time, it will lead to a large error between the measured cardiac output and the actual cardiac output. The specific method for measuring cardiac output is not limited in this embodiment of the invention; it can be set according to actual needs.

[0072] It should be noted that monitoring devices may have built-in standard values ​​for correction factors. When the monitoring device determines that the correction factor needs to be corrected, it determines a target correction factor, which can be understood as a correction coefficient relative to the standard value. For monitoring devices that do not have built-in standard values ​​for correction factors, the target correction factor in this embodiment of the invention is the correction factor used to determine cardiac output, and not the aforementioned correction coefficient.

[0073] According to embodiments of the present invention, an automatic calibration method and a cardiac output monitoring method are provided. It should be noted that the steps shown in the flowcharts in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0074] This embodiment provides an automatic calibration method that can be used in monitoring equipment. Figure 1 This is a flowchart of an automatic calibration method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0075] S11, acquire the pulse wave signal of the target monitored object.

[0076] The pulse wave signal of the target monitored object can be a photoelectric pulse wave, a pressure pulse wave, an arterial pressure wave, or other pulse wave waveforms, measured by the monitoring device, or measured by other devices and then sent to the monitoring device. There is no limitation on the source of the pulse wave signal. In this embodiment, the monitoring device can be a bedside monitoring device or a central station, etc. When the monitoring device is a central station, it is connected to each bedside monitoring device to receive the pulse wave signals measured by each device. After analyzing the signals, the central station determines whether the blood flow state of the target monitored object corresponding to that bedside monitoring device has changed. If a change in blood flow state is detected, it indicates that the correction factor of the bedside monitoring device needs to be corrected. In this case, the central station can directly determine the corrected correction factor and send it to the bedside monitoring device; alternatively, the central station can send a correction reminder to the bedside monitoring device, allowing the user to determine whether correction of the correction factor is needed, etc. There are no limitations on the specific application scenario; the specific settings can be configured according to actual needs.

[0077] S12, extract at least one signal feature of the pulse wave signal.

[0078] The monitoring equipment analyzes the pulse wave signal and extracts at least one signal feature. The extracted feature can be blood pressure characteristics such as pulse pressure, systolic / diastolic pressure, or diastolic pressure, or hemodynamic characteristics reflecting vascular adaptability. These features can be numerical values ​​or waveform features such as area and slope. There are no restrictions on which features(s) are specifically used. It should be noted that the feature value is not limited to a single numerical value; it can also be a feature vector, etc. The dimension of the feature vector is not limited here.

[0079] When a monitoring device extracts at least one signal feature from a pulse wave signal, it can perform image analysis on the pulse wave signal to extract the corresponding signal feature; or it can use a feature extraction network to extract the corresponding signal feature, etc.

[0080] S13, determine the target correction factor based on at least one signal feature.

[0081] As mentioned above, monitoring equipment can have built-in standard values ​​for correction factors. Corresponding to each standard value, target feature values ​​for each characteristic are set. By comparing the signal characteristics with the target feature values, the target correction factor can be determined.

[0082] For monitoring equipment, there may be no built-in standard value. In this case, the monitoring equipment compares the current signal characteristics with the historical signal characteristics corresponding to the last time the correction factor was determined, and thus determines the target correction factor.

[0083] The specifics of this step will be described in detail below.

[0084] The automatic calibration method provided in this embodiment uses the pulse wave signal of the target monitored object to determine the signal characteristics, and during the calibration process, it combines at least one signal characteristic for processing to realize the automatic calibration of the target calibration factor, thereby improving the reliability of the monitoring results.

[0085] This embodiment provides an automatic calibration method that can be used in monitoring equipment. Figure 2 This is a flowchart of an automatic calibration method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0086] S21, acquire the pulse wave signal of the target monitored object.

[0087] Please see details Figure 1 S11 of the illustrated embodiment will not be described again here.

[0088] S22, extract at least one signal feature of the pulse wave signal.

[0089] Please see details Figure 1 S12 of the illustrated embodiment will not be described again here.

[0090] S23, determine the target correction factor based on at least one signal feature.

[0091] Specifically, S23 above includes:

[0092] S231, determine the confidence level of the current correction factor based on at least one signal feature.

[0093] The monitoring device can be configured with target feature values ​​for each characteristic, which are used to characterize changes in blood flow status. Based on this, after obtaining at least one signal feature, the monitoring device compares each signal feature with its corresponding target feature value, determines the similarity between the two, and uses this similarity as the confidence level of the current correction factor to determine whether the blood flow status of the target patient has changed.

[0094] Alternatively, the monitoring device can be configured with preset confidence levels. The monitoring device uses at least one signal feature to calculate the confidence level of its current correction factor. Specifically, for each signal feature, the confidence level of that feature is calculated separately to obtain the confidence level of the current correction factor. The principle behind calculating the confidence level of a feature is to score the current correction factor based on each signal feature. If the feature value is close to the target signal feature value, the score of the current correction factor is low; conversely, it is high.

[0095] The specifics of this step will be described in detail below.

[0096] S232, when the confidence level of the current correction factor does not meet the preset conditions, determine the calibration timing of the current correction factor in order to determine the target correction factor.

[0097] After determining the confidence level of the current correction factor, the confidence level is compared with the preset conditions. If the preset conditions are not met, it means that the current correction factor needs to be calibrated, that is, the timing of calibration is determined; if the preset conditions are met, it means that the current correction factor does not need to be calibrated.

[0098] Once the monitoring equipment determines when it is time to calibrate the current correction factor, it can directly calibrate the current correction factor; alternatively, it can provide a calibration reminder so that the user can determine whether the current correction factor needs to be calibrated.

[0099] When the current correction factor is calibrated, the monitoring device uses the calibrated correction factor to determine the monitoring result; when the current correction factor is not calibrated, the monitoring device continues to use the current correction factor to determine the monitoring result.

[0100] The automatic calibration method provided in this embodiment uses the pulse wave signal of the target monitored object to determine the calibration timing of the current correction factor, and in the calibration judgment process, it combines at least one signal feature for processing to achieve timely and accurate calibration of the current calibration factor.

[0101] As an optional implementation of this embodiment, S231 above may include:

[0102] (1) Calculate the reliability value corresponding to each feature based on at least one signal feature.

[0103] For example, if all the signal features extracted in S22 above form an M*N feature matrix, then the obtained reliability value is an M*N reliability value. That is, each feature corresponds to a reliability value of the same dimension.

[0104] The reliability value can be calculated using the corresponding formula based on the feature value; or, as mentioned above, by comparing each signal feature with the target signal feature value and using the comparison result as the corresponding reliability value, and so on.

[0105] (2) Determine the credibility of the current correction factor based on the relationship between the credibility value of each feature and the first threshold.

[0106] Specifically, the reliability value of all features is an M*N matrix, which is called the reliability matrix. Each element in this M*N reliability matrix is ​​compared with a first threshold, and the number of elements greater than the first threshold is counted, which is taken as the reliability of the current correction factor. For example, if the reliability matrix is ​​a 3*4 matrix, and the number of elements greater than the first threshold is found to be 3, then the reliability of the current correction factor is determined to be 3.

[0107] In some optional embodiments of this example, step (2) of S231 above may include:

[0108] (2.1) Use the characteristics of each signal to determine the correlation between the characteristics.

[0109] (2.2) Based on the correlation, each feature is screened to determine the target signal features.

[0110] (2.3) Determine the reliability of the current correction factor based on the relationship between the reliability value of the target signal feature and the first threshold.

[0111] Before calculating the confidence level of the current correction factor, the monitoring device performs correlation analysis on the various signal features extracted in S22, excluding features with low correlation. For example, if four signal features are extracted in S22, and one feature is excluded through correlation analysis, then three target signal features are identified. These three target signal features are then used to calculate the corresponding confidence values ​​to determine the confidence level of the current correction factor.

[0112] By determining the correlation between various features and filtering them, we can reduce the amount of data processing and improve the accuracy of the calculated reliability.

[0113] As an optional implementation of this embodiment, step 2.3) in step (2) of S231 above may include:

[0114] 2.3.1) Obtain the weights of the target signal features.

[0115] 2.3.2) Based on the weights of the target signal features, the reliability value of the target signal features is corrected to obtain the corrected reliability value.

[0116] 2.3.3) Count the number of modified confidence values ​​of all target signal features that are greater than the first threshold to determine the confidence of the current correction factor.

[0117] During blood flow state analysis, different blood flow states have varying effects on different features. Specifically, for features with minor impact, the changes in their feature values ​​are not significant; for features with significant impact, the changes in their feature values ​​are more pronounced. Therefore, by adjusting the weights of each target signal feature, the analysis error caused by these effects can be reduced.

[0118] Specifically, the monitoring device acquires the weights corresponding to each target signal feature, uses these weights to correct the reliability value corresponding to the target signal feature, and obtains the corrected reliability value. Then, the corrected reliability value is compared with a first threshold, and the number of values ​​greater than the first threshold is counted to determine the reliability of the current correction factor.

[0119] Since different features have varying impacts on monitoring results, the reliability values ​​of target signal features are corrected using the weights of each feature to differentiate their influence on the monitoring results and further ensure the accuracy of reliability. By calculating the reliability value for each feature separately and then comparing it sequentially with a first threshold, the reliability of the current correction factor is determined. The determination of reliability incorporates all signal features, ensuring the accuracy of the obtained reliability of the current correction factor.

[0120] In some optional embodiments of this example, S232 may include: when the confidence level of the current correction factor is less than the second threshold, determining the current time as the calibration time for the current correction factor, and determining the target correction factor.

[0121] The preset condition is that the value is less than a second threshold. After determining the reliability of the current correction factor, the monitoring device compares it with the preset condition. If the reliability of the current correction factor is less than the second threshold, the current moment is determined as the calibration time for the current correction factor, and the current correction factor is automatically calibrated.

[0122] In some optional embodiments of this example, S232 may further include:

[0123] (1) When the confidence level of the current correction factor is less than the second threshold, determine the current time as the calibration time for the current correction factor.

[0124] (2) Display calibration reminder information on the monitoring interface of the monitoring equipment.

[0125] (3) In response to the selection result of calibration reminder information.

[0126] (4) When the selected result is to confirm calibration, the current correction factor is automatically calibrated to determine the target correction factor.

[0127] When the monitoring equipment determines that the current correction factor needs to be corrected, it displays a calibration reminder on the monitoring interface to alert the user. The user makes a selection on the monitoring interface, and the monitoring equipment confirms the selection. If the selection is "Confirm Calibration," the monitoring equipment automatically calibrates the current correction factor to determine the target correction factor. By automatically calibrating the current correction factor as soon as it is determined that calibration is needed, real-time calibration is ensured.

[0128] Alternatively, if the selection result is no calibration, determine that the current calibration factor does not need calibration and determine the current calibration factor as the target calibration factor.

[0129] When it is determined that the current correction factor needs calibration, a calibration reminder message is displayed to prompt the user to confirm, thereby avoiding miscalibration operations caused by measurement errors and further improving the accuracy of monitoring results.

[0130] As an optional implementation of this embodiment, the monitoring interface includes a pulse wave signal display area, a monitoring result display area, and a calibration reminder area. The monitoring method may further include: displaying a pulse wave signal in the pulse wave signal display area, displaying information based on the monitoring results in the monitoring result display area, and displaying calibration reminder information in the calibration reminder area.

[0131] like Figure 4 As shown, the monitoring interface of this monitoring device includes three areas: a pulse wave signal display area, a monitoring result display area, and a calibration reminder area. Specifically, during normal monitoring, only the pulse wave signal display area and the monitoring result display area can be displayed on the interface; when it is determined that the current correction factor needs to be corrected, the calibration reminder area is then displayed. Of course, the specific layout of the pulse wave signal display area, monitoring result display area, and calibration reminder area is not limited to... Figure 4 As shown, the specific settings can be customized according to actual needs. When it is determined that the current correction factor needs to be corrected, a calibration reminder message will be displayed in the calibration reminder area.

[0132] The monitoring interface simultaneously displays pulse wave signals, monitoring results, and calibration reminders, enabling users to intuitively understand the status of the target monitored object and make accurate calibration choices.

[0133] To better explain the cardiac output monitoring method described in the embodiments of the present invention, such as Figure 5 As shown, it is described in detail from the perspective of software modules. These software modules include: a pulse wave measurement module, a feature calculation and selection module, a reliability value calculation module, a system feedback response module, a pulse contour cardiac output monitoring module, a CCO interface display module, a recalibration reminder module, and an internal system calibration module.

[0134] Specifically, the pulse wave measurement module is used to measure the pulse wave signal of the target patient, such as pulse wave (PPG) or arterial pressure wave (ABP), etc.

[0135] The feature calculation and selection module is used for preprocessing, feature calculation, and feature selection of pulse waves.

[0136] The reliability value calculation module is used to calculate the reliability of the current correction factor and compare it with preset conditions to determine whether the reliability is lower than the second threshold: if yes, the current correction factor is unreliable and needs to be recalibrated to change the blood flow state; if no, the current correction factor is reliable and does not need to be recalibrated.

[0137] System feedback response module: There are two response methods. For systems that require external operation for recalibration, a recalibration interface reminder module is set up. For systems that do not require external operation for recalibration, an internal system calibration module is set up to calculate the system correction factor.

[0138] Pulse contour cardiac output monitoring module: mainly used to calculate continuous cardiac output.

[0139] CO Interface Display Module: This module connects to the pulse contour cardiac output monitoring module and displays the calculation results.

[0140] As a specific application example of this embodiment, the method calculates the reliability based on the feature values ​​of waveforms such as pulse wave and ABP. The reliability is highly correlated with the calibration factor. When the reliability is lower than a second threshold, the reliability of the calibration factor for the blood flow monitoring system decreases, indicating that the hemodynamic state of the target monitored object has changed. This information is then fed back to the CCO monitoring system and medical personnel, enabling the CCO monitoring system to automatically recalibrate. To avoid the randomness of single feature values, this embodiment proposes a method for calculating reliability using multiple feature values. A reliability score matrix is ​​obtained through multiple feature values, and then the reliability is determined based on its relationship with the first threshold.

[0141] In this embodiment, a method for determining the hemodynamic state of the target monitored object using pulse wave signals and realizing the automatic recalibration of the continuous CO monitoring system is described. This method can determine the optimal automatic recalibration time based on the individual condition of the target monitored object, thereby saving human resources as much as possible while ensuring system performance.

[0142] This embodiment also provides an automatic calibration device and a cardiac output monitoring device, which are used to implement the above embodiments and preferred embodiments, and will not be repeated as described previously. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0143] This embodiment provides an automatic calibration device, such as... Figure 6 As shown, it includes:

[0144] The first acquisition module 41 is used to acquire the pulse wave signal of the target monitored object;

[0145] The first extraction module 42 is used to extract at least one signal feature of the pulse wave signal;

[0146] The first determining module 43 is used to determine the target correction factor based on the at least one signal feature.

[0147] This embodiment provides a cardiac output monitoring device, such as... Figure 7 As shown, it includes:

[0148] The second acquisition module 51 is used to acquire the pulse wave signal of the target monitored object;

[0149] The second extraction module 52 is used to extract at least one signal feature of the pulse wave signal;

[0150] The second determining module 53 is used to determine the target correction factor based on the at least one signal feature;

[0151] The correction module 54 is used to correct the current cardiac output of the target monitored object based on the target correction factor, and determine the target monitoring result.

[0152] In this embodiment, the automatic calibration device and the cardiac output monitoring device are presented in the form of functional units. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0153] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0154] This invention also provides a monitoring device having the above-described features. Figure 6 The automatic calibration device shown, or the above-mentioned Figure 7 The device shown is for monitoring cardiac output.

[0155] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of a monitoring device provided in an optional embodiment of the present invention, such as... Figure 8 As shown, the monitoring device may include: at least one processor 61, such as a CPU (Central Processing Unit), at least one communication interface 63, a memory 64, and at least one communication bus 62. The communication bus 62 is used to enable communication between these components. The communication interface 63 may include a display screen or a keyboard; optionally, the communication interface 63 may also include a standard wired interface or a wireless interface. The memory 64 may be high-speed RAM (Random Access Memory) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 64 may also be at least one storage device located remotely from the aforementioned processor 61. The processor 61 may be combined with... Figure 6 or Figure 7 The described apparatus has an application program stored in memory 64, and the processor 61 calls the program code stored in memory 64 to perform any of the above method steps.

[0156] The communication bus 62 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus 62 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0157] The memory 64 may include volatile memory, such as random-access memory (RAM); the memory may also include non-volatile memory, such as flash memory, hard disk drive (HDD) or solid-state drive (SSD); the memory 64 may also include a combination of the above types of memory.

[0158] The processor 61 can be a central processing unit (CPU), a network processor (NP), or a combination of CPU and NP.

[0159] The processor 61 may further include a hardware chip. This hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0160] Optionally, memory 64 is also used to store program instructions. Processor 61 can invoke program instructions to implement the automatic calibration method or cardiac output monitoring method as shown in any embodiment of this application.

[0161] This invention also provides a non-transitory computer storage medium storing computer-executable instructions that can execute the automatic calibration method or the cardiac output monitoring method in any of the above-described method embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0162] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. An automatic calibration method, characterized in that, include: Acquire the pulse wave signal of the target monitored object; Extract at least one signal feature from the pulse wave signal; The target calibration factor is determined based on the at least one signal feature; Wherein, determining the target calibration factor based on the at least one signal feature includes: The confidence level of the current calibration factor is determined based on the at least one signal feature. When the reliability of the current calibration factor does not meet the preset conditions, the calibration timing of the current calibration factor is determined in order to determine the target calibration factor.

2. The method according to claim 1, characterized in that, Determining the confidence level of the current calibration factor based on the at least one signal feature includes: Based on the at least one signal feature, calculate the reliability value corresponding to each of the signal features; The reliability of the current calibration factor is determined based on the relationship between the reliability value of each of the signal features and the first threshold.

3. The method according to claim 2, characterized in that, Determining the reliability of the current calibration factor based on the relationship between the reliability value of each of the signal features and the first threshold includes: The correlation between the various signal features is determined using each of the signal features; Based on the correlation, each of the signal features is filtered to determine the target signal features; The reliability of the current calibration factor is determined based on the relationship between the reliability value of the target signal feature and the first threshold.

4. The method according to claim 3, characterized in that, Determining the reliability of the current calibration factor based on the relationship between the reliability value of the target signal features and the first threshold includes: Obtain the weights of the target signal features; The reliability value of the target signal feature is corrected based on the weight of the target signal feature to obtain the corrected reliability value. The confidence level of the current calibration factor is determined by counting the number of modified confidence values ​​of all the target signal features that are greater than the first threshold.

5. The method according to claim 1, characterized in that, When the reliability of the current calibration factor does not meet the preset conditions, determining the calibration timing of the current calibration factor to determine the target calibration factor includes: When the confidence level of the current calibration factor is less than the second threshold, the current moment is determined as the calibration time for the current calibration factor, and the current calibration factor is automatically calibrated to determine the target calibration factor.

6. The method according to claim 1, characterized in that, When the reliability of the current calibration factor does not meet the preset conditions, determining the calibration timing of the current calibration factor to determine the target calibration factor includes: When the confidence level of the current calibration factor is less than the second threshold, the current moment is determined as the calibration time for the current calibration factor. The monitoring interface of the monitoring device displays calibration reminder information; In response to the selection result of the calibration reminder information; When the selection result is "confirm calibration", the current calibration factor is automatically calibrated to determine the target calibration factor.

7. The method according to claim 6, characterized in that, The step of determining the calibration timing of the current calibration factor when the reliability of the current calibration factor does not meet the preset conditions, in order to determine the target calibration factor, further includes: When the selection result is no calibration, the current calibration factor is determined to be the target calibration factor.

8. A method for monitoring cardiac output, characterized in that, include: Acquire the pulse wave signal of the target monitored object; Extract at least one signal feature from the pulse wave signal; The target calibration factor is determined based on the at least one signal feature; The current cardiac output of the target monitored object is corrected based on the target calibration factor to determine the target monitoring result; Determining the target calibration factor based on the at least one signal feature includes: The confidence level of the current calibration factor is determined based on the at least one signal feature. When the reliability of the current calibration factor does not meet the preset conditions, the calibration timing of the current calibration factor is determined in order to determine the target calibration factor.

9. The method according to claim 8, characterized in that, The monitoring interface includes a pulse wave signal display area, a monitoring result display area, and a calibration reminder area. The method also includes: The pulse wave signal is displayed in the pulse wave signal display area, the monitoring result is displayed in the monitoring result display area, and the calibration reminder information is displayed in the calibration reminder area.

10. An automatic calibration device, characterized in that, include: The first acquisition module is used to acquire the pulse wave signal of the target monitored object; The first extraction module is used to extract at least one signal feature of the pulse wave signal; The first determining module is used to determine the target calibration factor based on the at least one signal feature; Wherein, determining the target calibration factor based on the at least one signal feature includes: The confidence level of the current calibration factor is determined based on the at least one signal feature. When the reliability of the current calibration factor does not meet the preset conditions, the calibration timing of the current calibration factor is determined in order to determine the target calibration factor.

11. A cardiac output monitoring device, characterized in that, include: The second acquisition module is used to acquire the pulse wave signal of the target monitored object; The second extraction module is used to extract at least one signal feature of the pulse wave signal, and the at least one signal feature is used to determine the calibration timing of the current calibration factor. The second determining module is used to determine a target calibration factor based on the at least one signal feature, wherein the target calibration factor is obtained by calibrating the current calibration factor when the calibration timing is met; The calibration module is used to correct the current cardiac output of the target monitored object based on the target calibration factor, and to determine the target monitoring result.

12. A monitoring device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the automatic calibration method of any one of claims 1-7, or the cardiac output monitoring method of claim 8 or 9.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the automatic calibration method according to any one of claims 1-7, or the cardiac output monitoring method according to claim 8 or 9.

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