Bpm parameter adaptive artificial heart

Abstract

The application belongs to the technical field of electric digital data processing, and is an artificial heart, comprising an artificial heart bpm adaptive parameter auxiliary design method. The method is suitable for artificial heart bpm adaptive parameter adjustment by using computer aided design. The method uses digital data of blood oxygen concentration change amount within a certain time after patient movement, radial artery blood pressure and blood oxygen concentration change amount before and after movement to obtain expected blood oxygen drop speed and blood oxygen recovery difficulty after movement. Movements with similar blood oxygen recovery difficulty are classified into the same group. The artificial heart typical scaling of each movement in the group is determined. The high degree of the artificial heart typical scaling ratio of other movements is compared. The high degree, the artificial heart typical scaling ratio and the expected blood oxygen drop speed are used to correspondingly adjust the artificial heart scaling ratio after the current movement ends. The method effectively represents the decline of patient heart and lung function by the obtained abnormal degree, and improves patient comfort by correspondingly increasing the artificial heart scaling ratio.

Description

Technical Field

[0001] This invention relates to the field of electronic digital data processing technology, and specifically to an artificial heart with adaptive bpm parameters. Background Technology

[0002] When patients with implanted artificial hearts exercise, the artificial heart will increase its bpm (scale ratio) when it detects a decrease in the patient's blood oxygen concentration. This increases the patient's blood circulation speed to accelerate the removal of carbon dioxide from the blood and alleviate the low blood oxygen concentration.

[0003] However, the recovery of blood oxygen concentration after exercise is actually achieved through two factors: the blood circulation speed determined by the artificial heart and the efficiency of carbon dioxide removal from the lungs, i.e., the patient's cardiopulmonary function. Therefore, even if the same patient experiences the exact same exercise at different times, if their cardiopulmonary function differs or declines, the recovery rate of blood oxygen concentration during the exercise corresponding to the decline in cardiopulmonary function will be slower than before the decline. In this case, although the artificial heart will adaptively increase its scaling ratio to compensate for the slower recovery, the slow recovery has already occurred. Current technology cannot accurately detect the decline in cardiopulmonary function and quickly and effectively restore blood oxygen concentration, inevitably causing discomfort for the patient.

[0004] In other words, existing artificial hearts cannot effectively guarantee the comfort of patients who have received artificial hearts during daily use. Summary of the Invention

[0005] To address the problem that existing technologies cannot effectively guarantee the comfort of patients using implanted artificial hearts in daily life, this invention provides an artificial heart with adaptive bpm parameters, including a method for assisting in the design of artificial heart bpm adaptive parameters, comprising the following steps:

[0006] The decrease in blood oxygen concentration and radial artery blood pressure of patients were measured after the exercise process to determine the expected rate of decrease in blood oxygen concentration after the exercise process.

[0007] Based on the expected rate of decrease in blood oxygen concentration and the amount of decrease in blood oxygen concentration after the exercise process compared to before the exercise process, the difficulty of the patient's blood oxygen concentration recovery after the exercise process is determined.

[0008] Calculate the similarity between the motion record corresponding to the current motion process and the motion record corresponding to the historical motion process to obtain a set of motion record data consisting of the motion record corresponding to the current motion process and several motion records corresponding to the historical motion processes. The several motion records corresponding to the historical motion processes are motion records similar to the motion record corresponding to the current motion process.

[0009] Obtain the typical scaling ratio of the patient's artificial heart during the current exercise process and several historical exercise processes within the group. Within the group, calculate the degree to which the typical scaling ratio of the patient's artificial heart during the current exercise process is higher than the typical scaling ratio of the patient's artificial heart during several historical exercise processes. The typical scaling ratio of the artificial heart is the scaling ratio of the artificial heart after the blood oxygen concentration reaches a steady state during exercise.

[0010] Based on the degree of elevation, the typical scaling ratio of the artificial heart during the current exercise, and the expected rate of decrease in blood oxygen concentration after the current exercise, the affinity between the exercise record corresponding to the current exercise and the exercise records corresponding to the several historical exercise processes is determined. Based on the obtained affinity, the degree to which the scaling ratio of the artificial heart is adjusted from the automatic scaling ratio to the safe scaling ratio after the current exercise ends is determined. The safe scaling ratio is a scaling ratio designed by the physician that is greater than the automatic scaling ratio.

[0011] The beneficial effects of this invention are as follows:

[0012] This invention first determines the expected rate of decrease in blood oxygen concentration (Oxygen saturation) and the difficulty of Oxygen saturation recovery corresponding to different exercise records. Exercise records with similar difficulty are grouped together. Within each group, under the condition that the difficulty of Oxygen saturation recovery is the same, the degree to which the scaling ratio of the artificial heart in the stable state of Oxygen saturation is higher than that of the artificial heart in the stable state of Oxygen saturation in other exercise records is investigated. This degree of higher scaling ratio effectively characterizes the degree of decline in the patient's physical function, especially cardiopulmonary function, during the exercise corresponding to that exercise record. Subsequently, based on the obtained degree of higher scaling ratio, the scaling ratio of the artificial heart in the stable state of Oxygen saturation in that exercise record and the expected rate of decrease in Oxygen saturation in that exercise record are combined to determine the affinity between that exercise record and other exercise records in the group. Based on the degree of affinity, the scaling ratio of the artificial heart after the exercise process of that exercise record is determined. This invention effectively determines the degree of decline in a patient's physical function during a single exercise, and increases the scaling ratio of the artificial heart in the patient's post-exercise blood oxygen concentration recovery phase according to the degree of decline. It can quickly and accurately eliminate the decrease in blood oxygen concentration recovery speed caused by the decline in the patient's physical function, and improve the daily use comfort of patients with implanted artificial hearts.

[0013] Furthermore, the expected rate of decrease in blood oxygen concentration after the exercise process ends is:

[0014] ;

[0015] in, The expected rate of decrease in blood oxygen concentration after the i-th exercise phase. The mean radial artery blood pressure of the patient during a sampling period after the end of the i-th exercise process. This represents the maximum blood oxygen concentration of the patient within one sampling period after the end of the i-th exercise process. This represents the minimum blood oxygen concentration of the patient within a sampling period after the end of the i-th exercise process. This represents the maximum change in the patient's blood oxygen concentration within a sampling period after the end of the i-th exercise process.

[0016] Furthermore, the difficulty of restoring the patient's blood oxygen concentration after the exercise process is as follows:

[0017] ;

[0018] in, The difficulty of restoring the patient's blood oxygen concentration after the i-th exercise phase. This represents the minimum blood oxygen concentration of the patient within a sampling period after the end of the i-th exercise process. The average blood oxygen concentration of the patient during the sampling period before the start of the i-th exercise process.

[0019] Furthermore, the process of calculating the similarity between the motion record corresponding to the current motion process and the motion records corresponding to historical motion processes, to obtain a set of motion record data consisting of the motion record corresponding to the current motion process and several motion records corresponding to historical motion processes, is as follows:

[0020] Calculate the similarity of blood oxygen saturation recovery difficulty between any two exercise records:

[0021] ;

[0022] Where A and B represent any two motion records from all motion records, J A and J B These represent the difficulty of blood oxygen saturation recovery corresponding to these two exercise records; DTW is the dynamic time warping distance. This indicates the similarity in the difficulty of blood oxygen concentration recovery between any two exercise records. The range of values ​​is ;

[0023] Based on the similarity of blood oxygen concentration recovery difficulty between any two obtained exercise records, and the preset number of groups to be divided, k-means clustering is used to group exercise records with similar blood oxygen concentration recovery difficulty into the same group, resulting in a set number of exercise records with similar blood oxygen concentration recovery difficulty. After grouping, a set of exercise record data is obtained, consisting of the exercise record corresponding to the current exercise process and the exercise records corresponding to several historical exercise processes.

[0024] Furthermore, the calculation process for the degree of deviation is as follows:

[0025] ;

[0026] in, The degree to which the typical scaling ratio of the artificial heart is higher during the motion process corresponding to the i-th motion record in the group compared to the motion processes corresponding to other motion records in the group. This represents the typical scaling ratio of the artificial heart during the motion corresponding to the i-th motion record within the group. This represents the median typical scaling ratio of the artificial heart during the motion processes recorded in other motion logs within the group. The difference between the typical scaling ratio of the artificial heart in the i-th motion record within the group and the median of the typical scaling ratio of the artificial heart in other motion records within the group. If the difference is less than 0, the difference is set to 0.

[0027] Based on the calculation process of the degree of deviation corresponding to the i-th motion record, the degree of deviation of the patient's artificial heart typical scaling ratio during the current motion process compared with the patient's artificial heart typical scaling ratio during the aforementioned historical motion processes is calculated.

[0028] Furthermore, the process of determining, based on the obtained kinship, the degree to which the scaling ratio of the artificial heart is adjusted from the automatic scaling ratio to the safe scaling ratio after the current motion process ends is as follows:

[0029] Based on the degree of elevation (G), the expected rate of decrease in blood oxygen concentration (U), and the typical scaling ratio (V) of each motion record within a certain group, a feature vector is constructed for each motion record within that group. ;

[0030] Construct a hypothesis space to determine the affinity between the i-th motion record in the group and other motion records j in the group:

[0031] ;

[0032] ;

[0033] in, The affinity between the i-th motion record in the group and other motion records j in the group. Let K be the k-th distance neighborhood of the i-th motion record in the hypothesis space, and K be the number of other motion records closest to the i-th motion record when determining the k-th distance neighborhood of the i-th motion record in the hypothesis space. Let i be the feature vector of the i-th motion record. These are the feature vectors of other motion records within the group. as well as They are the feature vectors and The length of the mold, Let be the distance between the i-th motion record and other motion records in the group in the hypothetical space;

[0034] Calculate the scaling ratio of the artificial heart after the completion of the motion process corresponding to the i-th motion record within a certain group:

[0035] ;

[0036] in, The scaling ratio of the artificial heart after the completion of the motion process corresponding to the i-th motion record. Let be the affinity of the i-th motion record relative to other motion records within the group. The scaling ratio of the artificial heart automatically adjusted during the motion corresponding to the i-th motion record. The security scaling ratio;

[0037] Following the calculation process of the artificial heart scaling ratio after the end of the corresponding motion process of the i-th motion record, the artificial heart scaling ratio after the end of the current motion process is calculated. Attached Figure Description

[0038] Figure 1 This is a flowchart of the bpm adaptive parameter-assisted design method for artificial hearts according to the present invention. Detailed Implementation

[0039] The overall concept of this invention is as follows: First, using the acquired digital data on the maximum change in blood oxygen concentration within a certain period after the patient's exercise, the maximum change in blood oxygen concentration before and after exercise, and radial artery blood pressure after exercise, the expected rate of blood oxygen decline and the difficulty of blood oxygen recovery after exercise are determined. Exercise records with similar blood oxygen recovery difficulty are grouped into the same group. The scaling ratio of the artificial heart when blood oxygen concentration is stable during each exercise process within the group is obtained to determine the degree of deviation of the artificial heart's scaling ratio when blood oxygen concentration is stable during other exercise processes within the group. Based on the degree of deviation obtained for each exercise process, the scaling ratio of the artificial heart when blood oxygen concentration is stable, and the expected rate of blood oxygen concentration decline after the end of the exercise process, the affinity of the exercise process with other exercise processes within the group is determined. Based on the obtained affinity, the scaling ratio of the artificial heart after the end of the exercise process is adjusted from the automatic scaling ratio of the artificial heart to a safe scaling ratio higher than the automatic scaling ratio, eliminating the reduction in blood oxygen concentration recovery rate caused by the decline of the patient's cardiopulmonary function, and ensuring the comfort of patients with implanted artificial hearts during daily use.

[0040] The following detailed description, in conjunction with the accompanying drawings and embodiments, describes an artificial heart with adaptive bpm parameters according to the present invention, including a method for auxiliary design of artificial heart with adaptive bpm parameters.

[0041] Method Implementation Examples:

[0042] An embodiment of the bpm adaptive parameter-assisted design method for an artificial heart according to the present invention is as follows: Figure 1 As shown. The specific process is as follows:

[0043] 1. Detect the patient's blood oxygen concentration and radial artery blood pressure within a certain period after the end of the exercise process to determine the expected rate of decrease in the patient's blood oxygen concentration.

[0044] The rate at which a patient's blood oxygen concentration decreases due to exercise can be reflected in two ways: firstly, the amount of decrease in blood oxygen concentration within a certain period after exercise; and secondly, the higher radial artery blood pressure value resulting from exercise.

[0045] In this embodiment, the patient's blood oxygen concentration and radial artery blood pressure are continuously sampled at 1-second intervals and 1-minute sampling cycles. Of course, other sampling intervals and cycles can be set in other embodiments as needed.

[0046] Therefore, the expected rate of decrease in the patient's blood oxygen concentration (U) can be obtained based on changes in the patient's blood oxygen concentration and radial artery blood pressure. i :

[0047] ;

[0048] in, The expected rate of decrease in blood oxygen concentration after the i-th exercise phase. The mean radial artery blood pressure of the patient during a sampling period after the end of the i-th exercise process. This represents the maximum blood oxygen concentration of the patient within one sampling period after the end of the i-th exercise process. The minimum blood oxygen concentration of the patient within a sampling period after the end of the i-th exercise process, and the corresponding This represents the maximum change in the patient's blood oxygen concentration within a sampling period after the end of the i-th exercise process.

[0049] After exercise, a higher radial artery blood pressure corresponds to a higher equivalent myocardial oxygen consumption. Therefore, a higher radial artery blood pressure within a sampling period after exercise is expected to result in a faster decrease in blood oxygen concentration after exercise. Similarly, when... The larger the value, the greater the decrease in blood oxygen concentration within a sampling period after the end of the exercise process, and the greater the expected rate of decrease in blood oxygen concentration.

[0050] Based on the patient's minimum blood oxygen concentration within a certain period after the exercise process ends and the patient's average blood oxygen concentration before the exercise process, combined with the patient's expected rate of decrease in blood oxygen concentration after the exercise process, the difficulty of the patient's blood oxygen concentration recovery after the exercise process is determined.

[0051] ;

[0052] in, The difficulty of restoring the patient's blood oxygen concentration after the i-th exercise phase. This represents the minimum blood oxygen concentration of the patient within a sampling period after the end of the i-th exercise process. This represents the average blood oxygen concentration of the patient during the sampling period prior to the start of the i-th exercise process. The expected rate of decrease in blood oxygen concentration after the i-th exercise process.

[0053] In this embodiment, the average blood oxygen concentration of the patient within one sampling period before the start of the i-th exercise process is used as the average blood oxygen concentration of the patient before the exercise process. In other embodiments, the average blood oxygen concentration of the patient within multiple sampling periods before the start of the exercise process can also be used as the average blood oxygen concentration of the patient before the exercise process.

[0054] 3. Exercise records of the same patient with similar difficulty in restoring blood oxygen concentration were grouped into the same group, resulting in multiple groups of exercise records with similar difficulty in restoring blood oxygen concentration.

[0055] 1) Based on the difficulty of the patient's blood oxygen concentration recovery after the end of each exercise record, calculate the similarity of the difficulty of blood oxygen concentration recovery between any two exercise records.

[0056] The similarity of the difficulty of blood oxygen concentration recovery between any two exercise records is:

[0057] ;

[0058] Where A and B represent any two motion records from all motion records, J A and J B These represent the oxygen saturation recovery difficulty corresponding to the two exercise records; DTW is the dynamic time warping distance. The closer the recovery difficulties of the two oxygen saturation records are, the smaller the DTW value, and vice versa. The range of is [0,1]. Therefore, when the difficulty of restoring two blood oxygen concentrations is closer, The closer the value is to 1, the closer it is to 0.

[0059] 2) Based on the similarity of the difficulty of blood oxygen concentration recovery between any two obtained exercise records, k-means clustering is used to group the exercise records of the patient with similar difficulty of blood oxygen concentration recovery into a group.

[0060] First, based on the accuracy requirements of the adaptive bpm parameter adjustment for the artificial heart, the number of groups to be divided is set, and this number is denoted as k. Since the requirements for the adaptive bpm parameter adjustment of the artificial heart may vary in different scenarios or at different times, the number of groups can be set according to actual needs. It is easy to understand that the more groups set, the more detailed the classification of the difficulty of blood oxygen concentration recovery for all exercise recordings, and the higher the accuracy of the adaptive bpm parameter adjustment for the artificial heart.

[0061] The grouping method in this embodiment is implemented using the K-means clustering algorithm:

[0062] Specifically, based on the similarity of the difficulty of blood oxygen concentration recovery between any two motion records, the K-means clustering algorithm is used to classify all motion records of the patient as unlabeled samples, label all unlabeled sample data, and input them into a multi-selection multi-hidden-layer neural network for supervised training.

[0063] Based on the number of groups to be divided, the difficulty of blood oxygen concentration recovery in exercise records is divided into k levels, and different label values ​​are assigned to different levels of blood oxygen concentration recovery difficulty.

[0064] The clustering process is as follows: First, define k initial cluster centers, then assign each point to the nearest cluster center to form a cluster. If the number of points in a cluster exceeds 50% of the total number, then classify it into the remaining k-1 classes according to the distance, and recalculate the cluster center of each cluster. Repeat the previous step until the clusters do not change or the maximum number of iterations is reached.

[0065] At this point, all sports records were divided into k groups based on the difficulty of blood oxygen concentration recovery for each sports record.

[0066] 4. Obtain the artificial heart scaling ratio corresponding to the steady state of blood oxygen concentration during each exercise record within the group, and calculate the degree to which the artificial heart scaling ratio of the corresponding exercise record is higher than that of other exercise records based on the obtained artificial heart scaling ratios.

[0067] Because patients continuously consume oxygen during exercise, and in the early stages, they primarily rely on passive blood circulation, which is inefficient and insufficient to metabolize all the carbon dioxide produced, there is a drop in blood oxygen concentration during the initial phase of exercise. Once the blood oxygen concentration drops to a certain level, the artificial heart activates, initiating active blood circulation with the artificial heart's involvement. Due to the high efficiency of this active circulation after the artificial heart's intervention, after a period of time, the rate at which the patient produces and eliminates carbon dioxide reaches a balance, thus achieving a steady-state blood oxygen concentration.

[0068] However, in reality, although the difficulty of blood oxygen concentration recovery was roughly the same for each exercise record within the same group after grouping based on the difficulty of blood oxygen concentration recovery, the recovery of blood oxygen concentration is achieved through the combined efforts of two aspects: the blood circulation speed determined by the artificial heart and the patient's physical function, namely the efficiency of carbon dioxide removal from the lungs. Therefore, the patient's physical function, namely the efficiency of carbon dioxide removal from the lungs, may be different in different exercise records within the same group.

[0069] Since the scaling ratio of the artificial heart increases when the efficiency of carbon dioxide expulsion from the lungs decreases, the decrease in the efficiency of carbon dioxide expulsion from the lungs in a patient's exercise record can be characterized by the degree to which the scaling ratio of the artificial heart is higher in the corresponding exercise process compared to the corresponding exercise processes in other exercise records within the group.

[0070] ;

[0071] in, The degree to which the typical scaling ratio of the artificial heart is higher during the motion process corresponding to the i-th motion record in the group compared to the motion processes corresponding to other motion records in the group. This represents the typical scaling ratio of the artificial heart during the motion corresponding to the i-th motion record within the group. This represents the median typical scaling ratio of the artificial heart during the motion processes recorded in other motion logs within the group. The difference between the typical scaling ratio of the artificial heart in the i-th motion record within the group and the median of the typical scaling ratios of the artificial hearts in other motion records within the group is considered to be 0 if the difference is less than 0.

[0072] The so-called typical scaling ratio is the scaling ratio of the artificial heart after the blood oxygen concentration reaches a steady state during exercise.

[0073] The range of values ​​is [0,1), when The closer the value is to 1, the greater the degree to which the typical scaling ratio of the artificial heart corresponding to the i-th motion record is higher than that of the typical scaling ratio of the artificial heart corresponding to other motion records in the group, and vice versa.

[0074] 5. Based on the degree to which the typical scaling ratio of the artificial heart corresponding to a certain exercise record in the group is higher than that of the typical scaling ratio of the artificial heart corresponding to other exercise records in the group, the typical scaling ratio of the artificial heart corresponding to the exercise record, and the expected rate of decrease in blood oxygen concentration corresponding to the exercise record, determine the affinity between the exercise record and other exercise records in the group. Based on the obtained affinity, determine the scaling ratio of the artificial heart after the end of the exercise process in the exercise record.

[0075] Based on the degree of elevation, expected rate of decrease in blood oxygen concentration, and typical scaling ratio of each motion record within the group, a feature vector is constructed for each motion record. .

[0076] Calculate the feature vectors of all motion records within the group, construct the hypothesis space, and determine the affinity between the i-th motion record in the group and other motion records j in the group:

[0077] ;

[0078] ;

[0079] in, The affinity between the i-th motion record in the group and other motion records j in the group. Let K be the k-th distance neighborhood of the i-th motion record in the hypothesis space, and K be the number of other motion records closest to the i-th motion record when determining the k-th distance neighborhood of the i-th motion record in the hypothesis space. Let i be the feature vector of the i-th motion record. These are the feature vectors of other motion records within the group. as well as They are the feature vectors and The length of the mold, Let be the distance between the i-th motion record and other motion records in the group in the hypothetical space.

[0080] The range of affinity is [0,1]. The more similar the motion process corresponding to the i-th motion record is to the motion processes corresponding to other motion records j within the group, the higher the affinity obtained. The closer the value is to 1, the closer it is to 0.

[0081] By using the above-described process of calculating affinity, the affinity of the i-th motion record relative to other motion records within the group can be determined. And based on the obtained kinship Calculate the scaling ratio of the artificial heart after the completion of the motion process corresponding to the i-th motion record:

[0082] ;

[0083] in, The scaling ratio of the artificial heart after the completion of the motion process corresponding to the i-th motion record. Let be the affinity of the i-th motion record relative to other motion records within the group. The scaling ratio of the artificial heart automatically adjusted during the motion corresponding to the i-th motion record. The safe scaling ratio for an artificial heart designed for physicians is greater than the automatic scaling ratio of the artificial heart.

[0084] By following the process of determining the scaling ratio of the artificial heart after the end of the exercise corresponding to the i-th exercise record, the scaling ratio of the artificial heart after the end of the current exercise can be determined. This can accurately and effectively eliminate the defect of slow recovery of blood oxygen concentration caused by the decline in the patient's physical function during the recovery phase after the end of the current exercise, and improve the daily comfort of patients with implanted artificial hearts.

[0085] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An artificial heart, characterized by, The application discloses a bpm adaptive parameter auxiliary design method for artificial heart, which comprises the following steps: detecting the oxygen concentration drop of the patient after the exercise process, and the radial artery blood pressure of the patient, determining the expected oxygen concentration drop speed of the patient after the exercise process; determining the oxygen concentration recovery difficulty of the patient after the exercise process according to the expected oxygen concentration drop speed and the oxygen concentration drop of the patient after the exercise process compared with the oxygen concentration before the exercise process; calculating the similarity between the exercise record corresponding to the current exercise process and the exercise record corresponding to the historical exercise process, obtaining a group of exercise record data composed of the exercise record corresponding to the current exercise process and the exercise record corresponding to the historical exercise process, wherein the exercise record corresponding to the historical exercise process is similar to the exercise record corresponding to the current exercise process; obtaining the typical scaling ratio of the artificial heart of the patient in the current exercise process and the historical exercise process in the group, and calculating the high degree of the typical scaling ratio of the artificial heart of the patient in the current exercise process compared with the typical scaling ratio of the artificial heart of the patient in the historical exercise process in the group; the typical scaling ratio of the artificial heart is the scaling ratio of the artificial heart after the oxygen concentration reaches a steady state in the exercise process; determining the affinity between the exercise record corresponding to the current exercise process and the exercise record corresponding to the historical exercise process according to the high degree, the typical scaling ratio of the artificial heart in the current exercise process and the expected oxygen concentration drop speed after the current exercise process, and determining the degree of adjustment of the scaling ratio of the artificial heart from the automatic adjustment scaling ratio to the safety scaling ratio after the current exercise process, wherein the safety scaling ratio is the scaling ratio designed by the doctor and is greater than the automatic adjustment scaling ratio; the process of adjusting the scaling ratio of the artificial heart from the automatic adjustment scaling ratio to the safety scaling ratio after the current exercise process is as follows: According to the high degree G, the expected blood oxygen concentration drop speed U, and the typical scaling ratio V corresponding to each motion record in a certain group, a feature vector of each motion record in a certain group is constructed ; constructing a hypothesis space, and determining the affinity between the i-th exercise record in the group and other exercise records j in the group: ； ； wherein, is the affinity between the i-th motion record in the group and other motion records j in the group, is the k-th distance neighborhood of the i-th motion record in the hypothesis space, K is the number of other motion records taken into account when determining the k-th distance neighborhood of the i-th motion record in the hypothesis space, is the feature vector of the i-th motion record, is the feature vector of other motion records in the group, and is the length of the feature vector and respectively, is the distance between the i-th motion record and other motion records in the group in the hypothesis space; calculating the scaling ratio of the artificial heart after the exercise process corresponding to the i-th exercise record in the group: ； wherein, is a scaling ratio of the artificial heart at the end of the exercise process corresponding to the i-th exercise record, is a kinship of the i-th exercise record compared with other exercise records in the group, is an automatic adjustment scaling ratio of the artificial heart in the exercise process corresponding to the i-th exercise record, is the safety scaling ratio; calculating the scaling ratio of the artificial heart after the exercise process corresponding to the i-th exercise record according to the calculation process of the scaling ratio of the artificial heart.

2. The artificial heart of claim 1, comprising an artificial heart bpm adaptive parameter aided design method, characterized in that, the expected oxygen concentration drop speed after the exercise process is: ； wherein, is the expected blood oxygen concentration decrease rate of the patient after the end of the i-th exercise process, is the average radial artery blood pressure of the patient within one sampling period after the end of the i-th exercise process, is the maximum blood oxygen concentration of the patient within one sampling period after the end of the i-th exercise process, is the minimum blood oxygen concentration of the patient within one sampling period after the end of the i-th exercise process, is the maximum blood oxygen concentration change of the patient within one sampling period after the end of the i-th exercise process.

3. The artificial heart of claim 1, comprising an artificial heart bpm adaptive parameter aided design method, characterized in that, the oxygen concentration recovery difficulty of the patient after the exercise process is: ； wherein, is the difficulty of the patient's blood oxygen concentration recovery after the end of the i-th movement process, is the minimum value of the patient's blood oxygen concentration in a sampling period after the end of the i-th movement process, is the average value of the patient's blood oxygen concentration in a sampling period before the start of the i-th movement process.

4. The artificial heart of claim 1, comprising an artificial heart bpm adaptive parameter aided design method, characterized in that, the process of calculating the similarity between the exercise record corresponding to the current exercise process and the exercise record corresponding to the historical exercise process, and obtaining a group of exercise record data composed of the exercise record corresponding to the current exercise process and the exercise record corresponding to the historical exercise process is as follows: calculating the similarity of the oxygen concentration recovery difficulty between any two exercise records: calculating the similarity of the oxygen concentration recovery difficulty between any two exercise records: ； wherein A and B represent any two of all the motion records, J A and J B are the blood oxygen concentration recovery difficulties of the two motion records respectively; DTW is the dynamic time warping distance, represents the similarity of the blood oxygen concentration recovery difficulty between any two motion records, the value range of ; According to the similarity of the blood oxygen concentration recovery difficulty between any two obtained movement records, and the preset number of groups to be divided, the movement records with similar blood oxygen concentration recovery difficulty are classified into the same group by using k-means clustering, to obtain movement records with similar blood oxygen concentration recovery difficulty in the set number of groups, and after grouping, a group of movement record data composed of the movement record corresponding to the current movement process and the movement records corresponding to the historical movement processes is obtained.

5. The artificial heart of claim 1, comprising an artificial heart bpm adaptive parameter aided design method, characterized in that, The high degree calculation process is: ； wherein, a degree of overestimation of the typical scaling ratio of the artificial heart during the exercise corresponding to the i-th exercise record in the group compared to the typical scaling ratio of the artificial heart during the exercises corresponding to the other exercise records in the group, a typical scaling ratio of the artificial heart during the exercise corresponding to the i-th exercise record in the group, a median of the typical scaling ratios of the artificial heart during the exercises corresponding to the other exercise records in the group, a difference between the typical scaling ratio of the artificial heart during the exercise corresponding to the i-th exercise record in the group and the median of the typical scaling ratios of the artificial heart during the exercises corresponding to the other exercise records in the group, and if the difference is less than 0, the difference is set to 0. According to the calculation process of the high degree corresponding to the i th movement record, the high degree of the typical scaling ratio of the artificial heart of the patient in the current movement process compared with the typical scaling ratio of the artificial heart of the patient in the historical movement process is calculated.

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