A data analysis and monitoring method and system for an external counterpulsation device

Abstract

The present invention provides a data analysis and monitoring method and system for an external anti-pulsation device, the method comprising: collecting a variety of cardiac-related data of a patient according to a preset cycle and collecting the working pressure data of the external anti-pulsation device in real time to establish working group data; processing the working group data in real time to obtain the real-time processing results, making real-time predictions of the patient's cardiac contraction, determining the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external anti-pulsation device, and thus controlling the inflation and deflation of the external anti-pulsation device. The present invention predicts the patient's cardiac contraction nodes and cardiac relaxation nodes to determine the inflation and deflation nodes during the patient's anti-pulsation period, thereby ensuring that the inflation and deflation time points of the external anti-pulsation airbag can be accurately determined in different anti-pulsation stages of the patient, and adaptively determines the inflation and deflation volumes of the airbag during the anti-pulsation process based on the patient's actual anti-pulsation monitoring data, thereby achieving personalized design of the inflation and deflation parameters during the anti-pulsation period.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis and monitoring, and in particular to a data analysis and monitoring method for an extracorporeal counterpulsation device. Background Art

[0002] EECP is a method of non-invasively applying external pressure to the lower body to alleviate and eliminate angina symptoms and improve hypoxia-ischemia in vital organs. It is also a medical device used to prevent and treat cardiovascular and cerebrovascular diseases. It involves inflating and pressurizing balloons wrapped around the limbs and buttocks during diastole, driving blood from the limb arteries back into the aorta, significantly increasing diastolic pressure, increasing blood flow to the heart, and reducing cardiac afterload. During systole, the balloons are rapidly deflated, relieving pressure and causing a decrease in systolic pressure in the aorta. This minimizes resistance during the ejection phase and accelerates blood flow to the distal end, achieving the EECP effect. The pressure applied to the limbs and buttocks by external counterpulsation must be coordinated with the contraction and relaxation of the heart in the cardiac cycle, that is, the inflation and deflation cycle of the airbag by the external counterpulsation device must track the contraction and relaxation cycle of the heart during the counterpulsation period. Therefore, the contraction and relaxation of the patient's heart need to be positioned during the counterpulsation period. However, since the patient has just stopped moving or is nervous at the early stage of the counterpulsation, the heart rate difference between the early stage of the counterpulsation and the middle and late stages of the counterpulsation increases. Traditional fixed positioning is prone to inaccurate positioning, resulting in poor treatment effect. At the same time, due to the difference in inflation space caused by individual body shape or the tightness of the airbag fixation, the limbs of different patients require different amounts of inflation. Therefore, the present invention proposes a data analysis and monitoring method and system for an external counterpulsation device. Summary of the Invention

[0003] The present invention provides a data analysis and monitoring method and system for an external counterpulsation device to solve the above problems.

[0004] The present invention provides a data analysis and monitoring method for an external counterpulsation device, comprising:

[0005] Step 1: Collect various cardiac data of the patient according to a preset cycle, and collect the working pressure data of the external counterpulsation device in real time to establish working group data, wherein the various cardiac data include electrocardiogram, blood oxygen, and heart rate;

[0006] Step 2: Process the workgroup data in real time to obtain real-time processing results. Based on the real-time processing results, make real-time predictions of the patient's cardiac contractions to determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external counterpulsation device.

[0007] Step 3: Based on the optimal inflation and deflation nodes and the optimal inflation and deflation volumes, control the inflation and deflation of the external counterpulsation device.

[0008] Preferably, in a data analysis and monitoring method for an external antipulsation device, step 1 comprises:

[0009] The built-in sensor of the external counterpulsation device collects working pressure data in real time and adds time tags to the collected working pressure data synchronously;

[0010] Based on an external wireless ECG monitoring device, it collects a variety of heart-related data and adds time tags to the collected data;

[0011] Based on the time tags, the corresponding relationships between the various heart-related data and the work pressure data are determined, and based on the corresponding relationships, the work group data is established.

[0012] Preferably, in a data analysis and monitoring method for an external antipulsation device, step 2 comprises:

[0013] Process various heart-related data in the working group data in real time according to data types to obtain the patient's real-time heart rate and real-time blood oxygen;

[0014] Based on the real-time heart rate and real-time blood oxygen, the patient's heart rate change curve and blood oxygen change curve are generated respectively and aligned and compared to obtain the correlation between the curve rate changes;

[0015] Obtain the latest blood oxygen value and update the blood oxygen change curve in real time to obtain the curvature change of the curve node corresponding to the latest blood oxygen value;

[0016] Predict the patient's heart rate changes based on the curvature change combined with the curve rate change correlation to obtain the predicted heart rate, perform ECG deduction based on the predicted heart rate, and predict the patient's next cardiac contraction node and next cardiac diastole node by combining the cardiac contraction ECG features and cardiac relaxation ECG features corresponding to the cardiac contraction node and cardiac relaxation node;

[0017] The next cardiac contraction node is used as the optimal deflation node, and the next cardiac diastole node is used as the optimal inflation node;

[0018] At the same time, based on the patient's blood pressure measurement value before treatment and referring to the standard range corresponding to the blood pressure, the patient's counter-beat adjustment amplitude is determined, and according to the changes in working pressure data and fluctuations in blood oxygen data, the current optimal inflation and deflation volume is determined within the counter-beat adjustment amplitude.

[0019] Preferably, in a data analysis and monitoring method for an external antipulsation device, determining the antipulsation adjustment amplitude of the patient based on the patient's blood pressure measurement value before treatment and referring to a standard range corresponding to the blood pressure includes:

[0020] Based on the standard range corresponding to the blood pressure, the systolic pressure and diastolic pressure of the blood pressure measurement value before treatment are determined to be the systolic pressure extreme difference and diastolic pressure extreme difference of the corresponding standard range;

[0021] Compare the systolic and diastolic pressure extreme differences to obtain the blood pressure extreme difference, and refer to the preset pressure reference table corresponding to the external counterpulsation device to determine the patient's corresponding maximum pressure tolerance;

[0022] Based on the patient's corresponding maximum pressure tolerance, the counter-pulsation adjustment amplitude is generated and stored.

[0023] Preferably, in a data analysis and monitoring method for an extracorporeal anti-pulsation device, the anti-pulsation adjustment amplitude is adjusted according to the working pressure data change and the blood oxygen data fluctuation to determine the current optimal inflation and deflation volume, including:

[0024] Generate a pressure data curve based on the working pressure data during the inflation and deflation process, mark the maximum pressure on the pressure data curve, and obtain the maximum inflation volume corresponding to the patient's maximum pressure, as well as the minimum inflation volume corresponding to the effective inflation node;

[0025] Based on the minimum inflation volume and the maximum inflation volume, the effective inflation range is obtained;

[0026] At the same time, based on historical blood oxygen data, the blood oxygen fluctuation range of patients undergoing anti-pulsation treatment is determined, and the blood oxygen fluctuation range is divided to obtain multiple blood oxygen levels;

[0027] The effective inflation range is reversely graded based on the blood oxygen level to obtain multiple sub-ranges. The upper limit value corresponding to each sub-range is used as the target inflation volume, and a corresponding relationship between blood oxygen and gas volume is established;

[0028] Obtain the patient's current blood oxygen value corresponding to the current cardiac systolic and diastolic cycle, and determine the optimal inflation volume based on the blood oxygen level corresponding to the current blood oxygen value and the blood oxygen-gas volume correspondence relationship;

[0029] At the same time, the optimal deflation volume is obtained based on the minimum inflation volume and the optimal inflation volume;

[0030] Wherein, when the current cardiac diastolic cycle is the initial counterbeat cycle, the optimal inflation volume is equal to the target inflation volume;

[0031] When the current cardiac systolic cycle is not the initial counter-beat cycle, the optimal inflation volume is equal to the difference between the target inflation volume and the minimum inflation volume.

[0032] Preferably, in a data analysis and monitoring method for an external counterpulsation device, step 3 includes determining the duration of the patient's cardiac diastolic cycle based on the patient's current heart rate;

[0033] Based on the time interval between the optimal charging and discharging nodes, the duration of the cardiac systolic and diastolic cycle is divided to determine the inflation and deflation durations respectively. With reference to the optimal charging and discharging volumes, the inflation and deflation speeds of the EVD are determined.

[0034] According to the inflation speed and the deflation speed, an inflation signal and a deflation signal are generated respectively. When the time reaches the optimal inflation node or the optimal deflation node, the external counterpulsation device is controlled to inflate or deflate.

[0035] Preferably, in a data analysis and monitoring method for an external anti-pulsation device, when the time reaches the optimal inflation and deflation node, controlling the external anti-pulsation device to inflate also includes:

[0036] Perform real-time recognition of the patient's electrocardiogram to determine whether the patient's actual cardiac diastolic point is consistent with the optimal inflation node. If so, the optimal inflation and deflation node prediction is considered normal.

[0037] If they are inconsistent, the prediction of the optimal inflation and deflation node is judged to be abnormal, and the pressure error between the actual diastolic point of the patient's heart and the optimal inflation node is obtained;

[0038] Based on the pressure error, the optimal deflation node corresponding to the current counter-pulsation cycle is corrected, and the actual deflation node is recorded.

[0039] Preferably, in a data analysis and monitoring method for an extracorporeal anti-pulsation device, determining the optimal inflation and deflation node for predicting abnormality includes:

[0040] When deflation starts in the current counter-beat cycle, a decompression error between an original optimal deflation node and an actual contraction point of the patient's heart is obtained;

[0041] Obtaining a decompression prediction error based on the decompression error and the actual duration corresponding to the current heartbeat;

[0042] Obtaining a pressure prediction error based on the pressure error and the actual duration corresponding to the current heartbeat;

[0043] Comparing the pressure application prediction error with the decompression prediction error, and calculating the predicted duration of the patient's next cardiac contraction and diastole based on the patient's current real-time heart rate;

[0044] When the pressure prediction error and the decompression prediction error are the same, the current error is determined to be a first-class error. The anti-beat node prediction error is obtained based on the pressure prediction error and the predicted duration of the next cardiac systole. Based on the anti-beat node prediction error, the prediction of the next cardiac diastole node after the next cardiac systole node is compensated.

[0045] When the pressure prediction error and the decompression prediction error are different, the current error is determined to be a second type error, and the next cardiac contraction node is compensated based on the decompression error, and the next cardiac diastole node is compensated based on the pressure error.

[0046] Preferably, in a data analysis and monitoring method for an external counterpulsation device, the process of controlling the external counterpulsation device to inflate further includes:

[0047] Based on judging whether the real-time heart rate reaches the predicted heart rate;

[0048] If the optimal inflation volume is not completed when the real-time heart rate reaches the predicted heart rate, or if the predicted heart rate is not reached after the optimal inflation volume is completed, the external counter-pump device is controlled to stop further inflation, and the current actual inflation volume is recorded, and the volume error between the current actual inflation volume and the current optimal inflation volume is calculated. Based on the volume error and the current optimal inflation volume, a personal tolerance error compensation value is calculated;

[0049] The individual tolerance error compensation value is stored and sent synchronously to step 2 to perform error correction on the calculation of the optimal inflation and deflation volume.

[0050] The present invention provides a data analysis and monitoring system for an external counterpulsation device, comprising:

[0051] A monitoring and acquisition module is used to collect various heart-related data of the patient according to a preset cycle, and to collect the working pressure data of the external counterpulsation device in real time to establish working group data, wherein the various heart-related data include electrocardiogram, blood oxygen, and heart rate;

[0052] An analysis and processing module is used to process the workgroup data in real time, obtain real-time processing results, and based on the real-time processing results, make real-time predictions of the patient's cardiac contractions and determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external counterpulsation device;

[0053] The inflation and deflation control module is used to control the inflation and deflation of the external counterpulsation device based on the optimal inflation and deflation nodes and the optimal inflation and deflation volumes.

[0054] Compared with the prior art, the present invention has at least the following advantages: first, the present invention collects various cardiac data of the patient according to a preset period, and collects the working pressure data of the external anti-pulsation device in real time to establish working group data; then, the working group data is processed in real time to obtain real-time processing results, and based on the real-time processing results, the patient's cardiac contraction is predicted in real time to determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external anti-pulsation device; finally, based on the optimal inflation and deflation nodes and optimal inflation and deflation volumes, the external anti-pulsation device is controlled to inflate and deflate. The present invention monitors the patient's heart rate, electrocardiogram, blood oxygen, and working pressure data, analyzes them, and predicts the patient's cardiac contraction nodes and cardiac diastole nodes to determine the inflation and deflation nodes during the patient's anti-pulsation period, thereby ensuring that the inflation and deflation time points of the external anti-pulsation balloon can be accurately determined at different stages of the patient's anti-pulsation. At the same time, the inflation and deflation volumes of the balloon during the anti-pulsation process can be adaptively determined based on the patient's actual anti-pulsation monitoring data, achieving personalized design of inflation and deflation parameters during the anti-pulsation period, ensuring that each inflation and deflation of the external anti-pulsation device is most consistent with the patient's current condition, thereby achieving the purpose of optimal anti-pulsation treatment effect.

[0055] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0056] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0058] Figure 1 A flow chart of a data analysis and monitoring method for an external counterpulsation device according to the present invention;

[0059] Figure 2 This is a flow chart of step 1 of a data analysis and monitoring method for an external counterpulsation device according to the present invention;

[0060] Figure 3 This is a flow chart of step 3 of a method for analyzing and monitoring data of an external counterpulsation device according to the present invention;

[0061] Figure 4 This is a schematic diagram of a data analysis and monitoring system for an external counterpulsation device of the present invention. DETAILED DESCRIPTION

[0062] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0063] Example 1:

[0064] The present invention provides a data analysis and monitoring method for an external antipulsation device, such as Figure 1 Shown, including:

[0065] Step 1: Collect various cardiac data of the patient according to a preset cycle, and collect the working pressure data of the external counterpulsation device in real time to establish working group data, wherein the various cardiac data include electrocardiogram, blood oxygen, and heart rate;

[0066] Step 2: Process the workgroup data in real time to obtain real-time processing results. Based on the real-time processing results, make real-time predictions of the patient's cardiac contractions to determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external counterpulsation device.

[0067] Step 3: Based on the optimal inflation and deflation nodes and the optimal inflation and deflation volumes, control the inflation and deflation of the external counterpulsation device.

[0068] In this embodiment, the various ECG data refer to the actual pressure values ​​of the airbag on the patient during the operation of the external counterpulsation device.

[0069] The beneficial effects of the above technical solution are as follows: the present invention first collects various cardiac-related data of the patient according to a preset cycle, and collects the working pressure data of the external anti-pulsation device in real time to establish working group data; then processes the working group data in real time to obtain real-time processing results, and based on the real-time processing results, predicts the patient's cardiac contraction in real time to determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external anti-pulsation device; finally, based on the optimal inflation and deflation nodes and optimal inflation and deflation volumes, controls the inflation and deflation of the external anti-pulsation device. The present invention monitors the patient's heart rate, electrocardiogram, blood oxygen, and working pressure data, analyzes them, and predicts the patient's cardiac contraction nodes and cardiac diastole nodes to determine the inflation and deflation nodes during the patient's anti-pulsation period, thereby ensuring that the inflation and deflation time points of the external anti-pulsation airbag can be accurately determined at different stages of the patient's anti-pulsation. At the same time, the inflation and deflation volumes of the airbag during the anti-pulsation process can be adaptively determined based on the patient's actual anti-pulsation monitoring data, realizing personalized design of the inflation and deflation parameters during the anti-pulsation period, ensuring that each inflation and deflation of the external anti-pulsation device is most consistent with the patient's current condition, thereby achieving the purpose of optimal anti-pulsation treatment effect.

[0070] Example 2:

[0071] On the basis of Example 1, step 1, as Figure 2 Shown, including:

[0072] Step 101: collecting working pressure data in real time based on the built-in sensor of the external counterpulsation device, and synchronously adding a time tag to the collected working pressure data;

[0073] Step 102: collecting a variety of heart-related data based on an external wireless ECG monitoring device, and synchronously adding time tags to the collected multiple heart-related data;

[0074] Step 103: Based on the time tags, determine the corresponding relationship between the various heart-related data and the working pressure data, and establish the working group data based on the corresponding relationship.

[0075] The beneficial effects of the above technical solution: The present invention collects the pressure of the airbag of the extracorporeal antipulsation device on the patient's limbs and buttocks and various heart-related data of the patient during the antipulsation period, and constructs working group data through time tags. While realizing the monitoring of the antipulsation process, it also completes the collation of multiple data at the same time, providing a basis for subsequent data analysis.

[0076] Example 3:

[0077] On the basis of Example 1, step 2 includes:

[0078] Process various heart-related data in the working group data in real time according to data types to obtain the patient's real-time heart rate and real-time blood oxygen;

[0079] Based on the real-time heart rate and real-time blood oxygen, the patient's heart rate change curve and blood oxygen change curve are generated respectively and aligned and compared to obtain the correlation between the curve rate changes;

[0080] Obtain the latest blood oxygen value and update the blood oxygen change curve in real time to obtain the curvature change of the curve node corresponding to the latest blood oxygen value;

[0081] Predict the patient's heart rate changes based on the curvature change combined with the curve rate change correlation to obtain the predicted heart rate, perform ECG deduction based on the predicted heart rate, and predict the patient's next cardiac contraction node and next cardiac diastole node by combining the cardiac contraction ECG features and cardiac relaxation ECG features corresponding to the cardiac contraction node and cardiac relaxation node;

[0082] The next cardiac contraction node is used as the optimal deflation node, and the next cardiac diastole node is used as the optimal inflation node;

[0083] At the same time, based on the patient's blood pressure measurement value before treatment and referring to the standard range corresponding to the blood pressure, the patient's counter-beat adjustment amplitude is determined, and according to the changes in working pressure data and fluctuations in blood oxygen data, the current optimal inflation and deflation volume is determined within the counter-beat adjustment amplitude.

[0084] In this embodiment, the standard range corresponding to blood pressure includes a diastolic pressure standard range (60-89 mmHg) and a systolic pressure standard range (90-139 mmHg).

[0085] In this embodiment, the counterpulsation adjustment amplitude refers to the range of values ​​of the pressure applied by the airbag of the external counterpulsation device to the patient, and the upper limit of the range does not exceed the maximum pressure that the airbag can apply.

[0086] In this embodiment, the antipulsation stage includes the early antipulsation stage and the middle and late antipulsation stage. The early antipulsation stage refers to the initial stage when the patient starts antipulsation treatment, generally referring to the first 3-5 minutes after the start of antipulsation treatment.

[0087] The beneficial effects of the above technical solution are as follows: The present invention generates a patient's blood oxygen change curve and heart rate change curve based on the patient's real-time heart rate during treatment and blood pressure measurement before treatment, aligns and compares them, obtains the curve rate change correlation, and characterizes the correlation between the patient's blood oxygen and heart rate with the curvature change correlation between the curves. The patient's next electrocardiogram is predicted and deduced based on the blood oxygen value, and the patient's next cardiac contraction node and next cardiac diastole node are thereby obtained to obtain the optimal inflation and deflation nodes. The patient's anti-beat adjustment amplitude is then determined based on the patient's blood pressure measurement before treatment in the current anti-beat stage, with reference to the standard range corresponding to the blood pressure. The current optimal inflation and deflation volume is determined within the anti-beat adjustment amplitude based on changes in working pressure data and fluctuations in blood oxygen data. The inflation and deflation parameters for each anti-beat inflation and deflation are predicted and determined based on the patient's real-time working group data during the anti-beat period. This helps adapt to the patient's heart rate differences in different anti-beat stages and also facilitates intelligent anti-beat adjustment based on actual treatment to achieve the optimal treatment effect.

[0088] Example 4:

[0089] On the basis of Example 3, based on the patient's blood pressure measurement value before treatment and referring to the standard range corresponding to the blood pressure, the patient's counterbeat adjustment amplitude is determined, including:

[0090] Based on the standard range corresponding to the blood pressure, the systolic pressure and diastolic pressure of the blood pressure measurement value before treatment are determined to be the systolic pressure extreme difference and diastolic pressure extreme difference of the corresponding standard range;

[0091] Compare the systolic and diastolic pressure extreme differences to obtain the blood pressure extreme difference, and refer to the preset pressure reference table corresponding to the external counterpulsation device to determine the patient's corresponding maximum pressure tolerance;

[0092] Based on the patient's corresponding maximum pressure tolerance, the counter-pulsation adjustment amplitude is generated and stored.

[0093] In this embodiment, the extreme systolic blood pressure difference refers to the smaller difference between the two differences between the systolic blood pressure and the upper and lower limits of the systolic blood pressure standard range.

[0094] The extreme difference of diastolic pressure refers to the smaller difference between the two differences between diastolic pressure and the upper and lower limits of the diastolic pressure standard range.

[0095] The extreme blood pressure difference refers to the smaller value between the extreme systolic pressure difference and the extreme diastolic pressure difference.

[0096] In this embodiment, the preset pressure reference table refers to the pressure tolerance levels corresponding to patients under different blood pressure health conditions, and the pressure ranges corresponding to each tolerance level, wherein the blood pressure health condition is determined by the blood pressure extreme difference value.

[0097] In this embodiment, the fixed period (fixed time length) is shorter than the initial stage of the counterpulsation.

[0098] The beneficial effects of the above technical solution: The present invention judges the systolic pressure and diastolic pressure of the blood pressure measurement values ​​before treatment and the systolic pressure extreme difference and diastolic pressure extreme difference of the standard range corresponding to the blood pressure based on the standard range; compares the systolic pressure extreme difference and the diastolic pressure extreme difference to obtain the blood pressure extreme difference, and determines the patient's corresponding maximum tolerance pressure with reference to the preset pressure reference table corresponding to the extracorporeal anti-pulsation device; based on the patient's corresponding maximum tolerance pressure, generates an anti-pulsation adjustment amplitude for storage, and determines the anti-pulsation adjustment amplitude according to the patient's own health condition, which is beneficial to avoid the probability of the patient experiencing discomfort during anti-pulsation, and improves the safety of anti-pulsation use while ensuring the anti-pulsation effect.

[0099] Example 5:

[0100] On the basis of Example 3, according to the change of working pressure data and the fluctuation of blood oxygen data, the amplitude of the counter-beat is adjusted to determine the current optimal inflation and deflation volume, including:

[0101] Generate a pressure data curve based on the working pressure data during the inflation and deflation process, mark the maximum pressure on the pressure data curve, and obtain the maximum inflation volume corresponding to the patient's maximum pressure and the minimum inflation volume corresponding to the effective inflation node;

[0102] Based on the minimum inflation volume and the maximum inflation volume, the effective inflation range is obtained;

[0103] At the same time, based on historical blood oxygen data, the blood oxygen floating range of patients undergoing anti-pulsation treatment is determined, and the blood oxygen floating range is divided to obtain multiple blood oxygen levels; based on historical blood oxygen data, the blood oxygen floating range of patients undergoing anti-pulsation treatment is determined;

[0104] The effective inflation range is reversely graded based on the blood oxygen level to obtain multiple sub-ranges. The upper limit value corresponding to each sub-range is used as the target inflation volume, and a corresponding relationship between blood oxygen and gas volume is established;

[0105] Obtain the patient's current blood oxygen value corresponding to the current cardiac diastolic cycle, and determine the optimal inflation volume based on the blood oxygen level corresponding to the current blood oxygen value and the blood oxygen-gas volume correspondence relationship;

[0106] At the same time, based on the minimum inflation volume and the optimal inflation volume, the optimal deflation volume is obtained;

[0107] Wherein, when the current cardiac diastolic cycle is the initial counterbeat cycle, the optimal inflation volume is equal to the target inflation volume;

[0108] When the current cardiac systolic and diastolic cycle is not the initial counter-beat cycle, the optimal inflation volume is equal to the difference between the target inflation volume and the minimum inflation volume.

[0109] In this embodiment, the effective inflation node refers to the inflation time point at which the pressure sensor senses and monitors the pressure.

[0110] In this embodiment, the effective inflation range refers to the optional range of inflation volume during the patient's counterpulsation process, with the upper limit being the maximum inflation volume and the lower limit being the minimum inflation volume.

[0111] In this embodiment, reverse classification means that the blood oxygen level is classified from large to small according to the blood oxygen value, and the effective inflation range is classified from small to large according to the inflation volume, and vice versa.

[0112] The blood oxygen-gas volume correspondence refers to a one-to-one correspondence between the blood oxygen level and the sub-range, and then a new correspondence is established between the blood oxygen level and the target inflation volume of the corresponding sub-range based on the changed correspondence.

[0113] In this embodiment, when the current cardiac diastolic cycle is the last counterbeat cycle, the optimal deflation volume is the total inflation volume in the airbag.

[0114] The beneficial effects of the above technical solution are as follows: the present invention generates a pressure data curve based on the working pressure data during the inflation and deflation process, marks the maximum pressure to be tolerated on the pressure data curve, obtains the maximum inflation volume corresponding to the patient's maximum pressure to be tolerated and the minimum inflation volume corresponding to the effective inflation node, and obtains the effective inflation range. Then, based on the historical blood oxygen data, the blood oxygen floating range of the patient undergoing counterpulsation treatment is determined, the blood oxygen floating range is divided to obtain multiple blood oxygen levels; and the effective inflation range is reversely graded based on the blood oxygen level to obtain multiple sub-ranges, and the upper limit value corresponding to each sub-range is used as the target inflation volume, and a blood oxygen-gas volume correspondence is established to obtain the current blood oxygen value corresponding to the patient's current cardiac diastolic cycle, and the optimal inflation volume is determined based on the blood oxygen level corresponding to the current blood oxygen value and the blood oxygen-gas volume correspondence; at the same time, the optimal deflation volume is obtained based on the minimum inflation volume and the optimal inflation volume. While determining the maximum inflatable volume during the patient's counterpulsation process, the remaining air volume in the airbag during deflation is also determined. This avoids wasting time during ineffective inflation (where the airbag's inflation volume is less than the minimum inflation volume), reducing energy consumption while ensuring the counterpulsation effect. The inflation and deflation volumes are determined based on the patient's real-time blood oxygen level to achieve the desired counterpulsation pressure change, effectively avoiding situations where excessive counterpulsation pressure causes patient discomfort or too low a pressure results in a counterpulsation effect.

[0115] Example 6:

[0116] On the basis of Example 1, step 3, as Figure 3 Shown, including

[0117] Determine the duration of the patient's cardiac systolic and diastolic cycle based on the patient's current heart rate;

[0118] Based on the time interval between the optimal charging and discharging nodes, the cardiac systolic and diastolic cycle is segmented to determine the inflation and deflation durations respectively. The inflation and deflation speeds of the EVD are determined with reference to the optimal charging and discharging volumes.

[0119] According to the inflation speed and the deflation speed, an inflation signal and a deflation signal are generated respectively. When the time reaches the optimal inflation node or the optimal deflation node, the external counterpulsation device is controlled to inflate or deflate.

[0120] In this embodiment, the cardiac systolic cycle is divided into two time periods, one for inflation and one for deflation. Each cardiac contraction is a cardiac systolic cycle, that is, a diastolic period and a systolic period constitute a cardiac systolic cycle.

[0121] The beneficial effects of the above technical solution are as follows: the present invention adaptively determines the inflation and deflation speeds of the external counterpulsation device according to the duration of the patient's cardiac systolic and diastolic cycle, and then generates an inflation signal and a deflation signal according to the inflation speed and the deflation speed, respectively. When the time reaches the optimal inflation node or the optimal deflation node, the external counterpulsation device is controlled to inflate or deflate, realizing intelligent control of the inflation and deflation of the airbag during the counterpulsation process.

[0122] Example 7:

[0123] Based on Example 6, when the time reaches the optimal inflation and deflation node, controlling the external counterpulsation device to inflate also includes:

[0124] Perform real-time recognition of the patient's electrocardiogram to determine whether the patient's actual cardiac diastolic point is consistent with the optimal inflation node. If so, the optimal inflation and deflation node prediction is considered normal.

[0125] If they are inconsistent, the prediction of the optimal inflation and deflation node is judged to be abnormal, and the pressure error between the actual diastolic point of the patient's heart and the optimal inflation node is obtained;

[0126] Based on the pressure error, the optimal deflation node corresponding to the current counter-pulsation cycle is corrected, and the actual deflation node is recorded.

[0127] In this embodiment, one inflation and deflation of the airbag constitutes one counterpulsation cycle.

[0128] In this embodiment, the pressure error refers to the time difference between the original optimal inflation node and the actual diastolic point. The pressure prediction error refers to the ratio of the pressure error to the actual duration corresponding to the current heartbeat.

[0129] The beneficial effects of the above technical solution are as follows: the present invention performs real-time detection of the prediction results of the optimal inflation and deflation nodes during the inflation process of the extracorporeal anti-pulsation device, and then corrects the optimal deflation nodes within the same anti-pulsation cycle based on the detection results, which is beneficial to improving the accuracy of anti-pulsation inflation and deflation within the same anti-pulsation cycle.

[0130] Example 8:

[0131] Based on Example 7, determining whether the optimal inflation and deflation node prediction is abnormal includes:

[0132] When deflation starts in the current counter-beat cycle, a decompression error between an original optimal deflation node and an actual contraction point of the patient's heart is obtained;

[0133] Obtaining a decompression prediction error based on the decompression error and the actual duration corresponding to the current heartbeat;

[0134] Obtaining a pressure prediction error based on the pressure error and the actual duration corresponding to the current heartbeat;

[0135] Comparing the pressure application prediction error with the decompression prediction error, and calculating the predicted duration of the patient's next cardiac contraction and diastole based on the patient's current real-time heart rate;

[0136] When the pressure prediction error and the decompression prediction error are the same, the current error is determined to be a first-class error. The anti-beat node prediction error is obtained based on the pressure prediction error and the predicted duration of the next cardiac systole. Based on the anti-beat node prediction error, the prediction of the next cardiac diastole node after the next cardiac systole node is compensated.

[0137] When the pressure prediction error and the decompression prediction error are different, the current error is determined to be a second type error, and the next cardiac contraction node is compensated based on the decompression error, and the next cardiac diastole node is compensated based on the pressure error.

[0138] In this embodiment, the decompression error refers to the time difference between the original optimal deflation point and the actual contraction point. The decompression prediction error refers to the ratio of the decompression error to the actual duration corresponding to the current heartbeat.

[0139] The beneficial effect of the above technical solution is that during the counter-beat period, the error value corresponding to the current charging and discharging node is used to continuously compensate for the error in the prediction of the next counter-beat node, making the prediction of the counter-beat charging and discharging node more and more accurate.

[0140] Example 9:

[0141] Based on Example 1, the process of controlling the inflation of the external counterpulsation device further includes:

[0142] Based on judging whether the real-time heart rate reaches the predicted heart rate;

[0143] If the optimal inflation volume is not completed when the real-time heart rate reaches the predicted heart rate, or if the predicted heart rate is not reached after the optimal inflation volume is completed, the external counter-pump device is controlled to stop further inflation, and the current actual inflation volume is recorded, and the volume error between the current actual inflation volume and the current optimal inflation volume is calculated. Based on the volume error and the current optimal inflation volume, a personal tolerance error compensation value is calculated;

[0144] The individual tolerance error compensation value is stored and sent synchronously to step 2 to perform error correction on the calculation of the optimal inflation and deflation volume.

[0145] In this embodiment, the personal tolerance error compensation value refers to the ratio of the air volume error and the current optimal inflation volume.

[0146] The beneficial effects of the above technical solution: The present invention determines the individual error compensation value based on the prediction error, digitizes the patient's individual vascular pressure tolerance, and then stores the individual error compensation value and synchronously sends step 2 to correct the error in the calculation of the optimal inflation and deflation volume, thereby enhancing the personalization of the inflation and deflation parameter settings during the patient's counterpulsation process, making the prediction of the optimal inflation and deflation parameters more accurate and improving the counterpulsation treatment effect.

[0147] Example 10:

[0148] The present invention provides a data analysis and monitoring system for an external antipulsation device, such as Figure 4 As shown, including:

[0149] A monitoring and acquisition module is used to collect various heart-related data of the patient according to a preset cycle, and to collect the working pressure data of the external counterpulsation device in real time to establish working group data, wherein the various heart-related data include electrocardiogram, blood oxygen, and heart rate;

[0150] An analysis and processing module is used to process the workgroup data in real time, obtain real-time processing results, and based on the real-time processing results, make real-time predictions of the patient's cardiac contractions and determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external counterpulsation device;

[0151] The inflation and deflation control module is used to control the inflation and deflation of the external counterpulsation device based on the optimal inflation and deflation nodes and the optimal inflation and deflation volumes.

[0152] The beneficial effects of the above technical solution: The present invention monitors the patient's heart rate, electrocardiogram, blood oxygen and working pressure data for analysis, predicts the patient's cardiac contraction node and cardiac relaxation node to determine the inflation and deflation nodes during the patient's counterpulsation period, thereby ensuring that the inflation and deflation time points of the external counterpulsation airbag can be accurately determined in different counterpulsation stages of the patient. At the same time, the inflation and deflation volumes of the airbag during the counterpulsation process can be adaptively determined based on the patient's actual counterpulsation monitoring data, realizing personalized design of the inflation and deflation parameters during the counterpulsation period, ensuring that each inflation and deflation of the external counterpulsation device is most in line with the patient's current state, so as to achieve the purpose of optimal counterpulsation treatment effect.

[0153] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A data analysis and monitoring method for an external antipulsation device, characterized in that: include: Step 1: Collect various cardiac data of the patient according to a preset cycle, and collect the working pressure data of the external counterpulsation device in real time to establish working group data, wherein the various cardiac data include electrocardiogram, blood oxygen, and heart rate; Step 2: Process the workgroup data in real time to obtain real-time processing results. Based on the real-time processing results, make real-time predictions of the patient's cardiac contractions to determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external counterpulsation device. Step 3: Based on the optimal inflation and deflation nodes and optimal inflation and deflation volumes, control the inflation and deflation of the external counterpulsation device; Wherein, step 2 includes: Process various heart-related data in the working group data in real time according to data types to obtain the patient's real-time heart rate and real-time blood oxygen; Based on the real-time heart rate and real-time blood oxygen, the patient's heart rate change curve and blood oxygen change curve are generated respectively and aligned and compared to obtain the correlation between the curve rate changes; Obtain the latest blood oxygen value and update the blood oxygen change curve in real time to obtain the curvature change of the curve node corresponding to the latest blood oxygen value; Predict the patient's heart rate changes based on the curvature change combined with the curve rate change correlation to obtain the predicted heart rate, perform ECG deduction based on the predicted heart rate, and predict the patient's next cardiac contraction node and next cardiac diastole node by combining the cardiac contraction ECG features and cardiac relaxation ECG features corresponding to the cardiac contraction node and cardiac relaxation node; The next cardiac contraction node is used as the optimal deflation node, and the next cardiac diastole node is used as the optimal inflation node; At the same time, based on the patient's blood pressure measurement value before treatment and referring to the standard range of blood pressure, the patient's anti-beat adjustment range is determined. According to the changes in working pressure data and the fluctuation of blood oxygen data, the current optimal inflation and deflation volume is determined within the anti-beat adjustment range. Among them, according to the changes in working pressure data and the fluctuation of blood oxygen data, the amplitude of the counter-beat is adjusted to determine the current optimal inflation and deflation volume, including: Generate a pressure data curve based on the working pressure data during the inflation and deflation process, mark the maximum pressure on the pressure data curve, and obtain the maximum inflation volume corresponding to the patient's maximum pressure, as well as the minimum inflation volume corresponding to the effective inflation node; Based on the minimum inflation volume and the maximum inflation volume, the effective inflation range is obtained; At the same time, based on historical blood oxygen data, the blood oxygen fluctuation range of patients undergoing anti-pulsation treatment is determined, and the blood oxygen fluctuation range is divided to obtain multiple blood oxygen levels; The effective inflation range is reversely graded based on the blood oxygen level to obtain multiple sub-ranges. The upper limit value corresponding to each sub-range is used as the target inflation volume, and a corresponding relationship between blood oxygen and gas volume is established; Obtain the patient's current blood oxygen value corresponding to the current cardiac systolic and diastolic cycle, and determine the optimal inflation volume based on the blood oxygen level corresponding to the current blood oxygen value and the blood oxygen-gas volume correspondence relationship; At the same time, the optimal deflation volume is obtained based on the minimum inflation volume and the optimal inflation volume; Wherein, when the current cardiac diastolic cycle is the initial counterbeat cycle, the optimal inflation volume is equal to the target inflation volume; When the current cardiac systolic cycle is not the initial counter-beat cycle, the optimal inflation volume is equal to the difference between the target inflation volume and the minimum inflation volume.

2. The data analysis and monitoring method of an external counterpulsation device according to claim 1, characterized in that: Step 1 includes: The built-in sensor of the external counterpulsation device collects working pressure data in real time and adds time tags to the collected working pressure data synchronously; Based on an external wireless ECG monitoring device, it collects a variety of heart-related data and adds time tags to the collected data; Based on the time tags, the corresponding relationships between the various heart-related data and the work pressure data are determined, and based on the corresponding relationships, the work group data is established.

3. The data analysis and monitoring method of an external counterpulsation device according to claim 1, characterized in that: Based on the patient's blood pressure measurement before treatment and referring to the standard range of blood pressure, the patient's counterpulsation adjustment range is determined, including: Based on the standard range corresponding to the blood pressure, the systolic pressure and diastolic pressure of the blood pressure measurement value before treatment are determined to be the systolic pressure extreme difference and diastolic pressure extreme difference of the corresponding standard range; Compare the systolic and diastolic pressure extreme differences to obtain the blood pressure extreme difference, and refer to the preset pressure reference table corresponding to the external counterpulsation device to determine the patient's corresponding maximum pressure tolerance; Based on the patient's corresponding maximum pressure tolerance, the counter-pulsation adjustment amplitude is generated and stored.

4. The data analysis and monitoring method of an external counterpulsation device according to claim 1, characterized in that: Step 3, including Determine the duration of the patient's cardiac systolic and diastolic cycle based on the patient's current heart rate; Based on the time interval between the optimal charging and discharging nodes, the duration of the cardiac systolic and diastolic cycle is divided to determine the inflation and deflation durations respectively. With reference to the optimal charging and discharging volumes, the inflation and deflation speeds of the EVD are determined. According to the inflation speed and the deflation speed, an inflation signal and a deflation signal are generated respectively. When the time reaches the optimal inflation node or the optimal deflation node, the external counterpulsation device is controlled to inflate or deflate.

5. The data analysis and monitoring method of an external counterpulsation device according to claim 4, characterized in that: When the time reaches the optimal inflation and deflation node, the external counterpulsation device is controlled to inflate, and the following also applies: Perform real-time recognition of the patient's electrocardiogram to determine whether the patient's actual cardiac diastolic point is consistent with the optimal inflation node. If so, the optimal inflation and deflation node prediction is considered normal. If they are inconsistent, the prediction of the optimal inflation and deflation node is judged to be abnormal, and the pressure error between the actual diastolic point of the patient's heart and the optimal inflation node is obtained; Based on the pressure error, the optimal deflation node corresponding to the current counter-pulsation cycle is corrected, and the actual deflation node is recorded.

6. The data analysis and monitoring method of an external counterpulsation device according to claim 5, characterized in that: When determining the optimal inflation and deflation node and predicting an abnormality, it includes: When deflation starts in the current counter-beat cycle, a decompression error between an original optimal deflation node and an actual contraction point of the patient's heart is obtained; Obtaining a decompression prediction error based on the decompression error and the actual duration corresponding to the current heartbeat; Obtaining a pressure prediction error based on the pressure error and the actual duration corresponding to the current heartbeat; Comparing the pressure application prediction error with the decompression prediction error, and calculating the predicted duration of the patient's next cardiac contraction and diastole based on the patient's current real-time heart rate; When the pressure prediction error and the decompression prediction error are the same, the current error is determined to be a first-class error. The anti-beat node prediction error is obtained based on the pressure prediction error and the predicted duration of the next cardiac systole. Based on the anti-beat node prediction error, the prediction of the next cardiac diastole node after the next cardiac systole node is compensated. When the pressure prediction error and the decompression prediction error are different, the current error is determined to be a second type error, and the next cardiac contraction node is compensated based on the decompression error, and the next cardiac diastole node is compensated based on the pressure error.

7. The data analysis and monitoring method of an external counterpulsation device according to claim 1, characterized in that: The process of controlling the inflation of the external counterpulsation device also includes: Based on judging whether the real-time heart rate reaches the predicted heart rate; If the optimal inflation volume is not completed when the real-time heart rate reaches the predicted heart rate, or if the predicted heart rate is not reached after the optimal inflation volume is completed, the external counter-pump device is controlled to stop further inflation, and the current actual inflation volume is recorded, and the volume error between the current actual inflation volume and the current optimal inflation volume is calculated. Based on the volume error and the current optimal inflation volume, a personal tolerance error compensation value is calculated; The individual tolerance error compensation value is stored and sent synchronously to step 2 to perform error correction on the calculation of the optimal inflation and deflation volume.

8. The data analysis and monitoring system for an external counterpulsation device according to claim 1, characterized in that: include: A monitoring and acquisition module is used to collect various heart-related data of the patient according to a preset cycle, and to collect the working pressure data of the external counterpulsation device in real time to establish working group data, wherein the various heart-related data include electrocardiogram, blood oxygen, and heart rate; An analysis and processing module is used to process the workgroup data in real time, obtain real-time processing results, and based on the real-time processing results, make real-time predictions of the patient's cardiac contractions and determine the optimal inflation and deflation nodes and optimal inflation and deflation volumes of the external counterpulsation device; The inflation and deflation control module is used to control the inflation and deflation of the external counterpulsation device based on the optimal inflation and deflation nodes and the optimal inflation and deflation volumes.

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