Intelligent monitoring and analysis method for cardiology compression hemostasis device

Abstract

The present invention discloses an intelligent monitoring and analysis method for a cardiology compression hemostasis device, belonging to the technical field of medical devices. The present invention is applied to a compression hemostasis device, wherein the compression hemostasis device is provided with an airbag, a motion sensor, and a pressure sensing unit, wherein the pressure sensing unit is provided on the bottom surface of the compression hemostasis device. By acquiring compression state data and initial state data of the compression hemostasis device at the current moment, and acquiring vital sign data, the compression state data includes: a first pressure image acquired by the pressure sensing unit and first motion data acquired by the motion sensor; determining compression change information based on the compression state data and the initial state data; and determining monitoring results based on the compression change information and the vital sign data, the convenience of using the compression hemostasis device is improved.

Description

Technical Field

[0001] The present invention relates to the field of medical devices, and in particular to an intelligent monitoring and analysis method for a cardiology compression hemostasis device. Background Art

[0002] In cardiology, puncture operations are required during various surgical procedures. For example, digital subtraction angiography commonly requires puncture at the radial artery or femoral artery. Currently, the limb on the surgical side generally needs to be immobilized for more than 12 hours after surgery, and a pressurized hemostatic device is used to press the puncture point to achieve compression hemostasis. In order to avoid pressure injuries to the skin, the patient needs to be turned over every 2 hours. Among them, it is generally necessary to keep the head, shoulders, waist, and legs in the same straight line and turn them in the same direction to avoid arbitrary twisting and bending of the limb at the puncture point, which may cause the pressurized hemostatic device to fall off and move. Therefore, medical staff are required to accompany and monitor at all times during this process. It can be seen that the pressing hemostatic device requires monitoring by medical staff and is less convenient to use.

[0003] The above content is only used to assist in understanding the technical solution of the present invention and does not constitute an admission that the above content is prior art. Summary of the Invention

[0004] The main purpose of the present invention is to provide an intelligent monitoring and analysis method for a cardiology compression hemostasis device, aiming to improve the convenience of using the compression hemostasis device. To achieve the above purpose, the present invention provides an intelligent monitoring and analysis method for a cardiology compression hemostasis device, which is applied to the compression hemostasis device, wherein the compression hemostasis device is provided with an airbag, a motion sensor, and a pressure sensing unit, and the pressure sensing unit is provided on the bottom surface of the compression hemostasis device. The intelligent monitoring and analysis method for the cardiology compression hemostasis device includes the following steps:

[0005] Acquiring pressing state data and initial state data of the pressing hemostasis device at a current moment, and acquiring vital sign data, wherein the pressing state data includes: a first pressure image acquired by the pressure sensing unit and first motion data acquired by the motion sensor;

[0006] determining pressing change information according to the pressing state data and the initial state data;

[0007] A monitoring result is determined based on the compression change information and the vital sign data.

[0008] Optionally, the step of determining the pressure change information according to the pressure state data and the initial state data includes:

[0009] determining a plurality of target data according to the pressing state data and the initial state data;

[0010] generating a first target vector according to a plurality of target data;

[0011] The compression change information is determined based on matching the first target vector in a compression hemostasis state vector library.

[0012] Optionally, the initial state data includes a preset pressure image and preset motion data corresponding to the initial state of the pressing hemostasis device, and the step of determining a plurality of target data based on the pressing state data and the initial state data includes:

[0013] Calculating an average pressure difference, an offset distance, and an offset direction of a central pressure zone according to the first pressure image and a preset pressure image;

[0014] determining steering data according to the first motion data and the preset motion data;

[0015] The average pressure difference, the offset distance, the offset direction, and the steering data are respectively used as the target data to obtain a plurality of target data.

[0016] Optionally, after the step of determining the pressure change information according to the pressure state data and the initial state data, the method further includes:

[0017] When the pressure change information includes tag information of the changed state, the initial state data is updated according to the pressure state data.

[0018] Optionally, there are multiple pieces of compression change information, and the step of determining the monitoring result according to the compression change information and the vital sign data includes:

[0019] When the compression change information belongs to a normal compression state and the vital sign data does not have an abnormality, determining that the monitoring result is that the patient is in a normal state;

[0020] When the compression change information belongs to an abnormal compression state, or when the vital sign data is abnormal, it is determined that the monitoring result is that the patient state is abnormal.

[0021] Optionally, the step of determining a monitoring result according to the pressure change information and the vital sign data includes:

[0022] Extracting fluctuation characteristic data of the vital sign data, and determining the abnormal change moment of the vital sign data according to the fluctuation characteristic data;

[0023] The abnormal change moment is matched with the pressure change information, and the monitoring result is determined according to the matching result.

[0024] Optionally, there are multiple pieces of pressure change information, each piece of pressure change information corresponds to a data collection time, and the step of matching the abnormal change moment with the pressure change information and determining the monitoring result according to the matching result includes:

[0025] When there is a data collection time that is the same as the abnormal change moment, and the compression change information corresponding to the abnormal change moment belongs to an abnormal compression state, it is determined that the monitoring result is an abnormal synchronization between compression for hemostasis and the patient state.

[0026] Optionally, the step of acquiring vital sign data includes:

[0027] Obtain blood oxygen saturation data and heart rate data collected by the pulse oximeter;

[0028] Acquiring arterial pressure data collected by a non-invasive arterial blood pressure monitoring device;

[0029] The blood oxygen saturation data, the heart beats per minute and the arterial pressure data are used as the vital sign data.

[0030] In addition, to achieve the above-mentioned purpose, the present invention also provides a compression hemostasis device, which includes: a memory, a processor, and an intelligent monitoring and analysis program for a cardiology compression hemostasis device stored on the memory and runnable on the processor. The intelligent monitoring and analysis program for a cardiology compression hemostasis device is configured to implement the steps of the intelligent monitoring and analysis method for a cardiology compression hemostasis device described in any one of the above items.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also provides a storage medium, on which is stored an intelligent monitoring and analysis program for a cardiology compression hemostasis device. When the intelligent monitoring and analysis program for a cardiology compression hemostasis device is executed by a processor, the steps of the intelligent monitoring and analysis method for a cardiology compression hemostasis device described in any one of the above items are implemented.

[0032] The present invention proposes an intelligent monitoring and analysis method for a compression hemostatic device for cardiology. The method obtains the compression state data and initial state data of the compression hemostatic device at the current moment, and obtains vital signs data, and determines the compression change information based on the compression state data and the initial state data. Compared with the traditional method that requires medical staff to look after the patient while paying attention to whether the compression hemostatic device is worn correctly, and monitoring whether the patient's turning over in bed causes abnormalities in the compression hemostatic device, the method can intelligently monitor the state of the compression hemostatic device without the need for personnel to directly monitor it, and determine the monitoring results in combination with the compression change information and the vital signs data, thereby achieving accurate monitoring of the puncture site of the postoperative patient, reducing the difficulty of monitoring while improving the accuracy of monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Schematic diagram of the structure of the compression hemostasis device in the hardware operating environment involved in the embodiment of the present invention;

[0034] Figure 2 This is a flow chart of a first embodiment of the intelligent monitoring and analysis method for a cardiology compression hemostasis device according to the present invention;

[0035] Figure 3 2 is a flow chart of a second embodiment of the intelligent monitoring and analysis method for a cardiology compression hemostasis device according to the present invention.

[0036] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0037] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a compression hemostasis device in the hardware operating environment involved in an embodiment of the present invention.

[0039] like Figure 1 As shown, the compression hemostasis device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, an interactive device 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The interactive device 1003 may include a display and an input unit, such as a keyboard. Optionally, the interactive device 1003 may also be connected to the communication bus via a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a wireless fidelity (WI-FI) interface). The memory 1005 may be a high-speed random access memory (RAM) or a stable non-volatile memory (NVM), such as a disk drive. The memory 1005 may also be a storage device independent of the processor 1001.

[0040] Furthermore, the compression hemostasis device may also include an airbag, a pressure plate, a gasket, an inflatable component, a motion sensor, and a pressure sensing unit. Furthermore, a securing strap may be provided to secure the compression hemostasis device to the patient's puncture site. Furthermore, vital sign data monitored by other devices is acquired via network interface 1004. This is because other vital sign data must be collected by devices that comply with the medical device specifications to ensure data accuracy.

[0041] Furthermore, in order to display the monitoring results, the display screen can display the monitoring results and label information of the current change status.

[0042] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation to the compression hemostasis device, and the device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0043] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a data storage module, a network communication module, a user interface module, and an intelligent monitoring and analysis program for a cardiology compression hemostasis device.

[0044] exist Figure 1 In the pressing hemostasis device shown, the network interface 1004 is mainly used for data communication with other devices; the interactive device 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the pressing hemostasis device of the present invention can be set in the pressing hemostasis device, and the pressing hemostasis device calls the intelligent monitoring and analysis program for the cardiology pressing hemostasis device stored in the memory 1005 through the processor 1001, and executes the intelligent monitoring and analysis method for the cardiology pressing hemostasis device provided in the embodiment of the present invention.

[0045] The embodiment of the present invention provides an intelligent monitoring and analysis method for a cardiology compression hemostasis device, referring to Figure 2 , Figure 2 This is a flow chart of a first embodiment of an intelligent monitoring and analysis method for a cardiology compression hemostasis device according to the present invention. This embodiment is applied to a compression hemostasis device equipped with an airbag, a motion sensor, and a pressure sensing unit, the pressure sensing unit being disposed on the bottom surface of the compression hemostasis device. The intelligent monitoring and analysis method for a cardiology compression hemostasis device includes the following steps:

[0046] Step S1, obtaining pressing state data and initial state data of the pressing hemostasis device at a current moment, and obtaining vital sign data, wherein the pressing state data includes: a first pressure image collected by the pressure sensing unit and first motion data collected by the motion sensor;

[0047] In this embodiment, the pressure sensing unit is provided in the pressing hemostasis device and can detect the pressure of the pressing hemostasis device on the setting position. Preferably, the pressure sensing unit here is a body pressure mapping system (BPMS), which can accurately measure the pressure data of each position of the contact surface, thereby forming the first pressure image data. The pressing state data here is the data collected at the current moment. The initial state data here is the data of the same type as the pressing state data recorded before the current moment. Preferably, the initial state data here can be the pressure image and motion data collected by medical staff for the first time after the patient wears the pressing hemostasis device. The vital signs data here may include: arterial pressure data, blood oxygen saturation data, heart rate per minute, etc.

[0048] Step S2, determining pressing change information according to the pressing state data and the initial state data;

[0049] The pressure change information of the hemostatic device can be determined based on the pressure state data and the initial state data. It should be noted that when pressing the puncture point, the pressure gradually decreases with the duration of the pressing. Generally, different pressing time intervals can be set, and different pressing pressures correspond to different pressing time intervals. In addition, the pressure change information here reflects not only normal changes in the pressure state, but also abnormal changes in the pressure state caused by falling off or tilting. By identifying whether this positive pressure change is normal, it is determined whether the pressure change information belongs to a normal pressing state.

[0050] Step S3, determining a monitoring result based on the pressure change information and the vital sign data;

[0051] Optionally, a data correlation analysis is performed based on the pressure change information and the vital signs data to determine whether the fluctuation of the vital signs data is related to the pressure change information, and whether the pressure change information causes the fluctuation of the vital signs data is determined based on the correlation data, thereby monitoring whether the pressing hemostasis device is in a normal operating state.

[0052] In this embodiment, the pressing state data and initial state data of the pressing hemostatic device at the current moment are obtained, and the vital signs data are obtained, and the pressing change information is determined according to the pressing state data and the initial state data; compared with the traditional method that requires medical staff to look after the patient while paying attention to whether the pressing hemostatic device is worn correctly, and monitoring whether the patient's turning over in bed and other behaviors cause abnormalities in the pressing hemostatic device, the state of the pressing hemostatic device can be monitored intelligently and without the need for personnel to directly monitor, and the monitoring results can be determined in combination with the pressing change information and the vital signs data, thereby achieving accurate monitoring of the puncture site of the postoperative patient, reducing the difficulty of monitoring and improving the convenience of use while improving the accuracy of monitoring.

[0053] Further, based on the first embodiment, a second embodiment of the intelligent monitoring and analysis method for a cardiology compression hemostasis device of the present invention is proposed. In this embodiment, referring to Figure 3 The step of determining the pressure change information according to the pressure state data and the initial state data includes:

[0054] Step S21, determining a plurality of target data according to the pressing state data and the initial state data;

[0055] In this embodiment, the target data is specifically extracted from the feature data of the first pressure image. Alternatively, the feature data of the first motion data is extracted or the first operation data is directly used as the target data. Alternatively, the target data is obtained by taking the difference between the pressing state data and the initial state data.

[0056] Step S22, generating a first target vector according to the plurality of target data;

[0057] Specifically, the target data is used as elements of a vector in a preset order, thereby obtaining the first target vector. The first target vector here is a vector used to describe the state of the pressing hemostasis device.

[0058] Step S23: determining the compression change information based on matching the first target vector in the compression hemostasis state vector library.

[0059] The compression hemostasis state vector library here includes multiple vectors with the same dimension as the first target vector. It should be noted that the vectors in the compression hemostasis state vector library can correspond to one or more identifiers and are obtained based on the data collected from the patient during the use of the compression hemostasis device recorded before the current moment. In order to ensure that it matches the first target vector, it is necessary to limit the generation method of the vectors in the compression hemostasis state vector library to the same generation method as the first target vector. Specifically, the cosine similarity between the vectors in the compression hemostasis state vector library and the first target vector is calculated respectively, and the compression hemostasis state vector library is sorted according to the size of the cosine similarity, and the vector with the highest cosine similarity is selected as the matching result, and the associated identifier corresponding to the vector with the highest cosine similarity is used as the compression change information.

[0060] In this embodiment, multiple target data are determined by the compression state data and the initial state data, and the compression change information is determined by matching the first target vector in the compression hemostasis state vector library, so that the existing target data can be analyzed to determine the operation status of the compression hemostasis device represented by the current type of data, thereby replacing medical staff to identify whether the compression hemostasis device is falling off, displaced, tilted, etc., thereby effectively saving the required medical monitoring resources.

[0061] Furthermore, the initial state data includes a preset pressure image and preset motion data corresponding to the initial state of the pressing hemostasis device, and the step of determining a plurality of target data based on the pressing state data and the initial state data includes:

[0062] Calculating an average pressure difference, an offset distance, and an offset direction of a central pressure zone according to the first pressure image and a preset pressure image;

[0063] Specifically, a first average pressure of the first pressure image and a second average pressure of the preset pressure image are calculated, and the difference between the first average pressure and the second average pressure is used as the average pressure difference. Here, the central pressure area refers to the second area in the preset pressure image where the pressure is greater than the preset pressure, and the first area in the first pressure image where the pressure is greater than the preset pressure. The offset distance and offset direction are determined based on the center coordinates of the first area and the center coordinates of the second area.

[0064] determining steering data according to the first motion data and the preset motion data;

[0065] Specifically, by measuring the downward rotation angle in three-dimensional space, the current turning data relative to the preset motion data can be determined, thereby reflecting the movement of the compression hemostasis device specifically following the movement of the patient.

[0066] The average pressure difference, the offset distance, the offset direction, and the steering data are respectively used as the target data to obtain a plurality of target data.

[0067] In this embodiment, the average pressure difference, the offset distance and the offset direction of the central pressure zone are calculated based on the first pressure image and the preset pressure image; the steering data is determined based on the first motion data and the preset motion data, and the data of the pressing hemostasis device during the wearing process can be accurately monitored, thereby ensuring the accuracy of subsequent identification of the operating status.

[0068] Furthermore, based on the first or second embodiment, a third embodiment of the present invention is provided for an intelligent monitoring and analysis method for a cardiology compression hemostasis device. In this embodiment, the amount of compression change information is multiple, and the step of determining the monitoring result based on the compression change information and the vital sign data includes:

[0069] When the compression change information belongs to a normal compression state and the vital sign data does not have an abnormality, determining that the monitoring result is that the patient is in a normal state;

[0070] When the compression change information belongs to an abnormal compression state, or when the vital sign data is abnormal, it is determined that the monitoring result is that the patient state is abnormal.

[0071] In this embodiment, the pressure change information includes multiple labels, and the labels here may include: normal pressure state or abnormal pressure state. In addition, the labels here may also include: static, swinging, rotation, misalignment, pressure reduction, pressure increase, etc. The pressure change information here is composed of multiple labels, and the above labels can be sent to the corresponding display device, and the display device displays the labels of each compression hemostasis device and the monitoring results. Generally speaking, abnormal arterial pressure data refers to systolic pressure outside the range of 90-139 mmHg, diastolic pressure outside the range of 60-89 mmHg, and blood oxygen saturation below 95%. In some embodiments, when there are large blood pressure fluctuations, it can also be regarded as an abnormality in the vital signs data. For example: if the systolic pressure fluctuates by more than 30 mmHg or the diastolic pressure fluctuates by more than 20 mmHg within one hour, it is regarded as an abnormality in the vital signs data.

[0072] Furthermore, after the step of determining the pressing change information according to the pressing state data and the initial state data, the method further includes:

[0073] When the pressure change information includes tag information of the changed state, the initial state data is updated according to the pressure state data.

[0074] When the pressure change information includes a change state tag, it is determined that there is a significant change between the current pressure state data and the initial state data, and therefore the current pressure state data is used as the new initial state data. If the change state tag does not exist, this means that there is no significant change between the current pressure state data and the initial state data, and therefore, there is no need to update the initial state data.

[0075] In this embodiment, by updating the initial state data, the accuracy of the corresponding pressure change information at each moment can be improved.

[0076] Furthermore, based on the above embodiments, a fourth embodiment of the present invention is provided for an intelligent monitoring and analysis method for a cardiology compression hemostasis device. In this embodiment, the step of determining the monitoring result based on the compression change information and the vital sign data includes:

[0077] Extracting fluctuation characteristic data of the vital sign data, and determining the abnormal change moment of the vital sign data according to the fluctuation characteristic data;

[0078] The abnormal change moment is matched with the pressure change information, and the monitoring result is determined according to the matching result.

[0079] The fluctuation characteristic data here may be: calculating the fluctuation amplitude of the vital sign data, and determining the time corresponding to when the fluctuation amplitude is greater than a preset amplitude as the abnormal change moment.

[0080] In some embodiments, blood pressure fluctuation characteristics, heart rate fluctuation characteristics, blood oxygen saturation fluctuation characteristics, etc. are obtained. Generally, the noise in the signal is first removed and the data is segmented into multiple time periods. The segmented data is then Fourier transformed to extract frequency domain features. The frequency domain features corresponding to each time period are compared. When a frequency appears in one time period that does not exist in the data of other time periods, it is determined that an abnormal change moment occurred within that period.

[0081] Furthermore, there are multiple pieces of pressure change information, each piece of pressure change information corresponds to a data collection time, and the step of matching the abnormal change moment with the pressure change information and determining the monitoring result based on the matching result includes:

[0082] When there is a data collection time that is the same as the abnormal change moment, and the compression change information corresponding to the abnormal change moment belongs to an abnormal compression state, it is determined that the monitoring result is an abnormal synchronization between compression for hemostasis and the patient state.

[0083] It should be noted that postoperative patients often experience respiratory and cardiovascular abnormalities due to anesthesia, which often present similar vital sign abnormalities as abnormalities in the hemostatic device. Therefore, in this embodiment, by comparing the data collection time with the moment of the abnormal change, the cause of the vital sign abnormality can be effectively distinguished, thus preventing medical staff from being unable to effectively determine the cause of the patient's vital sign abnormality.

[0084] Furthermore, the step of obtaining vital sign data includes:

[0085] Obtain blood oxygen saturation data and heart rate data collected by the pulse oximeter;

[0086] Acquiring arterial pressure data collected by a non-invasive arterial blood pressure monitoring device;

[0087] The blood oxygen saturation data, the heart beats per minute and the arterial pressure data are used as the vital sign data.

[0088] In other embodiments, due to the different actual conditions of each patient, other vital sign data may also be used, such as body temperature data, exhaled carbon dioxide data, brain oxygen saturation data, etc. The above vital sign data can effectively monitor the patient's health and the operation of the device.

[0089] In addition, an embodiment of the present invention also proposes a compression hemostasis device, characterized in that the compression hemostasis device includes: a memory, a processor, and an intelligent monitoring and analysis program for a cardiology compression hemostasis device stored on the memory and runnable on the processor, and the intelligent monitoring and analysis program for a cardiology compression hemostasis device is configured to implement the steps of any of the above-mentioned intelligent monitoring and analysis methods for a cardiology compression hemostasis device.

[0090] In addition, an embodiment of the present invention also proposes a storage medium, on which is stored an intelligent monitoring and analysis program for a cardiology compression hemostasis device. When the intelligent monitoring and analysis program for a cardiology compression hemostasis device is executed by a processor, the steps of the intelligent monitoring and analysis method for a cardiology compression hemostasis device described in any one of the above items are implemented.

[0091] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0092] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0093] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0094] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An intelligent monitoring and analysis method for a cardiology compression hemostasis device, characterized in that: The method is applied to a compression hemostasis device, wherein the compression hemostasis device is provided with an airbag, a motion sensor, and a pressure sensing unit, wherein the pressure sensing unit is provided on the bottom surface of the compression hemostasis device. The method comprises the following steps: Acquiring pressing state data and initial state data of the pressing hemostasis device at a current moment, and acquiring vital sign data, wherein the pressing state data includes: a first pressure image acquired by the pressure sensing unit and first motion data acquired by the motion sensor; determining pressing change information according to the pressing state data and the initial state data; Determining a monitoring result according to the compression change information and the vital sign data; The step of determining the pressure change information according to the pressure state data and the initial state data comprises: determining a plurality of target data according to the pressing state data and the initial state data; generating a first target vector according to a plurality of target data; determining the compression change information based on matching the first target vector in a compression hemostasis state vector library; The initial state data includes a preset pressure image and preset motion data corresponding to the initial state of the pressing hemostasis device, and the step of determining a plurality of target data based on the pressing state data and the initial state data includes: Calculating an average pressure difference, an offset distance, and an offset direction of a central pressure zone according to the first pressure image and a preset pressure image; determining steering data according to the first motion data and the preset motion data; The average pressure difference, the offset distance, the offset direction, and the steering data are respectively used as the target data to obtain a plurality of target data.

2. The intelligent monitoring and analysis method for a cardiology compression hemostasis device according to claim 1, characterized in that: After the step of determining the pressing change information according to the pressing state data and the initial state data, the method further includes: When the pressure change information includes tag information of the changed state, the initial state data is updated according to the pressure state data.

3. The intelligent monitoring and analysis method for a cardiology compression hemostasis device according to claim 1, characterized in that: There are multiple pieces of compression change information, and the step of determining the monitoring result based on the compression change information and the vital sign data includes: When the compression change information belongs to a normal compression state and the vital sign data does not have an abnormality, determining that the monitoring result is that the patient is in a normal state; When the compression change information belongs to an abnormal compression state, or when the vital sign data is abnormal, it is determined that the monitoring result is that the patient state is abnormal.

4. The intelligent monitoring and analysis method for a cardiology compression hemostasis device according to claim 1, characterized in that: The step of determining the monitoring result according to the pressure change information and the vital sign data includes: Extracting fluctuation characteristic data of the vital sign data, and determining the abnormal change moment of the vital sign data according to the fluctuation characteristic data; The abnormal change moment is matched with the pressure change information, and the monitoring result is determined according to the matching result.

5. The intelligent monitoring and analysis method for a cardiology compression hemostasis device according to claim 4, characterized in that: There are multiple pieces of pressure change information, each piece of pressure change information corresponds to a data collection time, and the steps of matching the abnormal change time with the pressure change information and determining the monitoring result according to the matching result include: When there is a data collection time that is the same as the abnormal change moment, and the compression change information corresponding to the abnormal change moment belongs to an abnormal compression state, it is determined that the monitoring result is an abnormal synchronization between compression for hemostasis and the patient state.

6. The intelligent monitoring and analysis method for a cardiology compression hemostasis device according to any one of claims 1 to 5, characterized in that: The step of obtaining vital sign data comprises: Obtain blood oxygen saturation data and heart rate data collected by the pulse oximeter; Acquiring arterial pressure data collected by a non-invasive arterial blood pressure monitoring device; The blood oxygen saturation data, the heart beats per minute and the arterial pressure data are used as the vital sign data.

7. A compression hemostasis device, characterized in that: The compression hemostasis device includes: a memory, a processor, and an intelligent monitoring and analysis program for a cardiology compression hemostasis device stored in the memory and runnable on the processor. The intelligent monitoring and analysis program for a cardiology compression hemostasis device is configured to implement the steps of the intelligent monitoring and analysis method for a cardiology compression hemostasis device as described in any one of claims 1 to 6.

8. A storage medium, characterized in that: The storage medium stores an intelligent monitoring and analysis program for a cardiology compression hemostasis device. When the intelligent monitoring and analysis program for a cardiology compression hemostasis device is executed by a processor, the steps of the intelligent monitoring and analysis method for a cardiology compression hemostasis device as described in any one of claims 1 to 6 are implemented.

Images