Medical equipment data management system based on multiple platforms

Abstract

The invention discloses a medical equipment data management system based on multiple platforms, relates to the technical field of medical data management, and aims at further judging whether a shunt sequence with a nonlinear property to be judged can be converted into a linear property or not, and further distinguishing the shunt sequence based on a judgment result. According to the method, three different conversion modes can be selected based on the linear property of any shunting sequence to convert the shunting sequence, the cracking difficulty and tampering difficulty of medical extraction data are greatly increased, the conversion logic is adopted to replace a secret key encryption mode, the risk of secret key loss is avoided, the secret key management cost is saved, and the safety of the medical extraction data is improved. And even if the conversion logic is partially cracked, the complete data is difficult to calculate based on the three different conversion modes, so that the anti-cracking capability of the medical extraction data is ensured while the dependence on the secret key is eliminated, and the security of medical data transmission is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data management, and in particular to a medical equipment data management system based on multiple platforms. Background Art

[0002] Medical device data is a key component of medical information. This data not only reflects the various real-time parameters of medical equipment during operation, but also serves as an important carrier of comprehensive medical data of medical subjects.

[0003] In real-world medical scenarios, the phenomenon of patients traveling across regions for medical treatment is becoming increasingly common. When patients visit medical institutions in other regions, the examination data generated by medical devices used in different locations is extremely critical for the new doctor to fully understand the patient's condition, make accurate diagnoses, and make reasonable treatment decisions.

[0004] However, medical data involves patient privacy. Currently, when different medical institutions and related platforms share medical data of medical subjects, key encryption is generally used to ensure the security of data during transmission and storage.

[0005] However, this key-dependent encryption model not only requires frequent generation of public and private keys to meet the needs of different data transmission, storage scenarios, and security cycles, which greatly increases the complexity of key management, but also poses a risk of loss if the key is improperly stored, which will lead to serious leakage of patient privacy.

[0006] In order to solve the above problems, the present invention proposes a solution. Summary of the Invention

[0007] The purpose of the present invention is to provide a multi-platform medical equipment data management system in order to solve the problems raised in the above background technology.

[0008] The present invention provides a multi-platform medical device data management system, comprising:

[0009] A medical data storage terminal is used to extract medical data from the interactive confirmation information transmitted by the credit platform, wherein the interactive confirmation information includes identity information of several medical subjects, and the extracted medical data includes medical data of several medical subjects;

[0010] an interactive data splitting unit, configured to perform a pre-processing operation on the received extracted medical data to obtain first processed data of the extracted medical data, wherein the pre-processing operation is performed using a base converter to convert the base of the extracted medical data;

[0011] The interactive data splitting unit is further configured to perform a first pre-grouping operation on the first processed data to obtain a plurality of split sequences of the first processed data;

[0012] The interactive data shunting unit is also configured to, after obtaining a plurality of shunting sequences of the first processed data, perform shunting conversion on all shunting sequences obtained by performing the first pre-grouping operation on the first processed data according to a preset shunting conversion step to obtain shunting feedback data of the interactive confirmation information;

[0013] The interactive data sharing unit is configured to transmit the diversion feedback data of the interactive confirmation information to the credit platform corresponding to the transmission of the interactive confirmation information after receiving the diversion feedback data of the interactive confirmation information.

[0014] Furthermore, the medical data storage terminal stores the medical data of all medical subjects in the target hospital.

[0015] Furthermore, the character length of each shunt sequence obtained after the interactive data shunt unit performs the first pre-grouping operation is P1, and the calculation formula of P1 is P1=12+8×(n-1), where the value of n is 1, 2, 3, ..., ∞.

[0016] Furthermore, the steps of converting the shunt feedback data obtained by shunt conversion to obtain the interactive confirmation information are as follows:

[0017] Step 1: Mark all the shunt sequences of the first processed data as A1, A2, ..., Aa, where a≥1, from left to right according to their positions in the first processed data before the first pre-grouping operation is performed on each shunt sequence;

[0018] Step 2: Extract a root chain string, chain head strings C1, C2, ..., Cc, and chain head strings D1, D2, ..., Dd from the branch sequence A1 according to the preset branch extraction rules;

[0019] Step 3: Determine the linear properties of the diversion sequence A1. The linear properties include linear sequence and nonlinear sequence.

[0020] Step 4: Based on the determination in step 3 that the diversion sequence A1 is a linear sequence, first determine that the linear character of the diversion sequence A1 is 1, and then perform a linear transformation on the diversion sequence A1 using a preset linear transformation rule to obtain a diversion transformation sequence of the diversion sequence A1;

[0021] Step 5: Based on the determination in step 3 that the diversion sequence A1 is a nonlinear sequence, first determine that the nonlinear character of the diversion sequence A1 is 0, and then execute a preset nonlinear transformation rule to perform a nonlinear transformation on the diversion sequence A1 to obtain a diversion transformation sequence of the diversion sequence A1;

[0022] Step 6: Obtain the diversion conversion sequence of the diversion sequence A2, A3, ..., Aa in sequence according to steps 2 to 4, and then concatenate the diversion conversion sequence of the diversion sequence A1, A2, ..., Aa in the order of diversion sequence A1, A2, ..., Aa to obtain the diversion feedback data of the interactive confirmation information.

[0023] Compared with the existing technology, it has the following beneficial effects:

[0024] The present invention provides an interactive information acquisition unit to acquire corresponding medical extraction data in a medical data storage terminal according to interactive confirmation information transmitted by a credit platform, and provides an interactive data diversion unit to perform pre-processing on the extracted medical data and a first pre-grouping operation to perform binary conversion and grouping operations on the medical extraction data to obtain a plurality of diversion sequences, and then performs diversion conversion on each diversion sequence. During the diversion conversion process, a second pre-grouping operation is performed on the diversion sequence to obtain a plurality of chain arrays. Based on the difference between the decimal number of the chain head string and the root chain substring of each chain array being greater than the linear property of the diversion sequence, the diversion sequence is diverted and converted in different ways according to the judgment result. In this way, the diversion conversion process of each diversion sequence is made more orderly and standardized.

[0025] The present invention further determines whether a shunt sequence that is determined to have nonlinear properties can be converted to a linear property. Based on the determination result, the shunt sequence is further differentiated and processed. In this way, any shunt sequence can be converted using three different conversion methods based on its linear property. This greatly increases the difficulty of cracking and tampering of medical extraction data.

[0026] The present invention adopts conversion logic to replace the key encryption method for the acquired medical extraction data, avoiding the risk of key loss and saving the cost of key management. Even if the conversion logic is partially cracked, it is difficult to infer the complete data based on the three different conversion methods of the present invention. While getting rid of the dependence on keys, it also ensures the anti-cracking ability of the medical extraction data and ensures the security of medical data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0029] See also Figure 1 , the present application provides a multi-platform-based medical device data management system, including a medical data storage terminal and a multi-platform management terminal;

[0030] A medical data storage terminal is used to store the medical data of all medical subjects in the target hospital. In this application, medical subjects refer to the patient group receiving various medical services in the target hospital, including but not limited to patients who visit the target hospital for consultation, follow-up visits, and are hospitalized;

[0031] In this application, the sources of medical data collected from medical subjects include but are not limited to several medical devices used by the medical subjects in the target hospital and the electronic medical records of the medical subjects;

[0032] A multi-platform management terminal is used to manage the interaction of medical data between target hospitals and several credit platforms. The multi-platform management terminal includes an interaction information acquisition unit, an interaction data diversion unit, and an interaction data sharing unit.

[0033] After receiving the interaction confirmation information transmitted from the credit platform, the interaction information acquisition unit transmits the interaction confirmation information to the medical data storage terminal, wherein the interaction confirmation information includes identity information of several medical subjects, and the identity information in this application includes but is not limited to name, age, telephone number and ID number;

[0034] In this application, the credit platform refers to a platform that has been authenticated by the target hospital and authorized to interact with data, including but not limited to hospitals and medical institutions;

[0035] After receiving the transmitted interactive confirmation information, the medical data storage terminal extracts the medical data corresponding to the plurality of medical subjects from all the medical data of the medical subjects stored in the medical data storage terminal according to the identity information of the plurality of medical subjects contained therein;

[0036] The medical data storage terminal generates extracted medical data of the interactive confirmation information based on the extracted medical data of the plurality of medical subjects, and transmits the extracted medical data to the interactive data diversion unit;

[0037] After receiving the extracted medical data transmitted with the interactive confirmation information, the interactive data shunting unit first performs a pre-processing operation on the extracted medical data to obtain first processed data of the extracted medical data, wherein the pre-processing operation is performed using a base converter to convert the extracted medical data into a base.

[0038] In this application, the base converter used is a binary converter, and the extracted medical data is converted into binary data by using the binary converter;

[0039] Then, a first pre-grouping operation is performed on the first processed data to obtain a plurality of stream sequences of the first processed data. The character length of each stream sequence obtained after the first pre-grouping operation is P1, where P1 is calculated as P1=12+8×(n-1), where n can be 1, 2, 3, ..., ∞. In the present application, the value of P1 is preferably 12;

[0040] In the present application, the first pre-grouping operation is performed as follows: each P1 character in the first processed data is treated as a branch sequence from left to right, and a plurality of branch sequences can be obtained. During the execution process, if the number of remaining characters is less than P1, the remaining characters are temporarily stored as a fixed sequence;

[0041] After obtaining a plurality of shunt sequences of the first processed data, the interactive data shunt unit performs shunt conversion on all shunt sequences obtained by performing the first pre-grouping operation on the first processed data according to a preset shunt conversion step. The shunt conversion step is as follows:

[0042] Step 1: Mark all the shunt sequences of the first processed data as A1, A2, ..., Aa, where a≥1, from left to right according to their positions in the first processed data before the first pre-grouping operation is performed on each shunt sequence;

[0043] Step 2: Extract a root chain string, chain head strings C1, C2, ..., Cc, and chain head strings D1, D2, ..., Dd from the branch sequence A1 according to the preset branch extraction rules. The branch extraction rules are as follows:

[0044] SS11: performing a second pre-grouping operation on the split sequence A1 to obtain a plurality of chain arrays, wherein the character length of each chain array obtained after performing the second pre-grouping operation is 4;

[0045] In the present application, the second pre-grouping operation is performed as follows: from left to right, every four characters in the split sequence A1 are used as a chain array to obtain a plurality of chain arrays;

[0046] SS12: Label all the chain arrays of the branch sequence A1 as B1, B2, ..., Bb from left to right, according to the position of each chain array in the branch sequence A1 before the second pre-grouping operation, where b≥1;

[0047] SS13: From left to right, extract the first two characters in chain array B1 as the chain head string of chain array B1. Similarly, extract the first two characters from chain arrays B2, B3, ..., Bb in turn as the chain head strings of the corresponding chain arrays.

[0048] SS14: Chain array The chain head string of is used as the root chain string of the shunt sequence A1. According to the order of the chain array subscripts corresponding to the chain head string from small to large, the chain head strings of all chain arrays with subscripts less than (b+1) / 2 are marked as C1, C2, ..., Cc, c = (b+1) / 2-1. Similarly, according to the order of the chain array subscripts corresponding to the chain head string from small to large, the chain head strings of all chain arrays with subscripts greater than (b+1) / 2 are marked as D1, D2, ..., Dd, d = b-(b+1) / 2.

[0049] Step 3: Determine the linear properties of the diversion sequence A1. In this application, linear properties include linear sequence and nonlinear sequence. The determination process is as follows:

[0050] Substitute the decimal numbers of the chain head strings C1, C2, ..., Cc, D1, D2, ..., Dd and the decimal number of the root chain string of the shunt sequence A1 into the linear determination expression Ec±1=F1, where Ec represents each of the decimal numbers of the chain head strings C1, C2, ..., Cc, D1, D2, ..., Dd, and F1 is the decimal number of the root chain string of the shunt sequence A1;

[0051] If the decimal numbers of the chain head strings C1, C2, ..., Cc, D1, D2, ..., Dd and the decimal numbers of the root chain string of the branch sequence A1 are substituted into the linear determination expression in sequence, and the linear determination expression is satisfied, then the linear property of the branch sequence A1 is determined to be a linear sequence, otherwise it is a nonlinear sequence;

[0052] In the present application, when the decimal numbers of the chain head strings C1, C2, ..., Cc, D1, D2, ..., Dd and the decimal numbers of the root chain string of the shunt sequence A1 are sequentially substituted into the linear determination expression, if there is a decimal number of the chain head string and the decimal number of the root chain string of the shunt sequence A1 that makes the linear determination expression invalid when substituted into the linear determination expression, the process of substituting the decimal numbers of the remaining chain head strings into the linear determination expression is immediately stopped, and the linear property of the shunt sequence A1 is directly determined to be a nonlinear sequence;

[0053] Step 4: Based on the determination in step 3 that the diversion sequence A1 is a linear sequence, the linear character of the diversion sequence A1 is first determined to be 1, and then a preset linear conversion rule is executed to linearly convert the diversion sequence A1 to obtain a diversion conversion sequence of the diversion sequence A1. The linear conversion rule is as follows:

[0054] SS21: Determine the direction of conversion of the chain head string C1 to the root chain string based on the magnitude relationship between the decimal number of the chain head string C1 and the decimal number of the root chain string. In this application, the direction of conversion includes ascending and descending.

[0055] If the decimal number of the chain head string C1 is smaller than the decimal number of the root chain string, then the change direction of the chain head string C1 to the root chain string is determined to be ascending. In this case, character 1 is used as the characteristic character of the change direction of the chain head string C1 to the root chain string. Otherwise, character 0 is used as the characteristic character of the change direction of the chain head string C1 to the root chain string.

[0056] SS22: Concatenate the linear characters of the branch sequence A1, the characteristic characters in the direction of change of the chain head string C1 toward the root chain string, and all the strings remaining after the chain array B1 cuts out the chain head string C1 to obtain a linear conversion array of the chain array B1. In this application, the linear conversion array includes, from left to right, the linear characters, the characteristic characters, and all the strings remaining after the chain array cuts out the corresponding chain head string;

[0057] SS23: Get the chain array in sequence from SS21 to SS22 Bb linear transformation array;

[0058] SS24: Follow the chain array The order of the chain array Then, for the data after the splicing, the root chain string of the shunt sequence A1 is spliced to the rightmost end of the data to obtain the shunt conversion sequence of the shunt sequence A1;

[0059] Step 5: Based on the determination in step 3 that the diversion sequence A1 is a nonlinear sequence, the nonlinear character of the diversion sequence A1 is first determined to be 0, and then a preset nonlinear transformation rule is executed to perform a nonlinear transformation on the diversion sequence A1 to obtain a diversion transformation sequence of the diversion sequence A1. The nonlinear transformation rule is as follows:

[0060] SS31: Calculate the difference between the decimal number of the chain head string C1, C2, ..., Cc, D1, D2, ..., Dd and the decimal number of the root chain string in sequence, wherein the decimal number of the root chain string is always used as the subtrahend when calculating the difference;

[0061] SS32: If the total number of differences of 2 or -2 among all the differences is calculated to be b, it is determined that the linear property of the branch sequence A1 can be transformed from a nonlinear sequence to a linear sequence, and character 1 is determined to be a quasi-linear character of the branch sequence. The branch conversion sequence of the branch sequence A1 is obtained according to a preset quasi-transformation rule. The quasi-transformation rule is as follows:

[0062] SS321: Determine whether the decimal difference between the chain head string C1 and the root chain string is positive or negative. If the difference is positive, the quasi-linear change direction of the root chain string is determined to be ascending compared to the chain head string C1. In this case, character 1 is used as the character to be changed in the chain head string C1. Otherwise, the quasi-linear change direction of the root chain string is determined to be descending compared to the chain head string C1. Character 0 is used as the character to be changed in the chain head string C1. In this application, the quasi-linear change direction includes both ascending and descending changes.

[0063] SS322: Update the root chain string according to the quasi-linear change direction of the root chain string compared to the chain head string C1. Specifically, if the quasi-linear change direction is ascending, first perform a two-digit binary conversion on the decimal value of the root chain string plus 1, and then use the converted data as the new root chain string.

[0064] If the quasi-linear change direction is descending, first, the value obtained by subtracting 1 from the decimal number of the root chain string is converted to two binary digits, and then the converted data is used as the new root chain string;

[0065] SS323: At this time, according to SS21 to SS22, based on the size relationship between the decimal number of the chain head string C1 and the decimal number of the new root chain string, the change direction of the chain head string C1 to the root chain string is determined to obtain the characteristic character of the change direction of the chain head string C1 to the new root chain string;

[0066] SS324: Concatenate all remaining strings after extracting the corresponding chain head string from the chain array B1 according to the proposed changed character, the characteristic character, and the chain array B1 to obtain a linear transformation array of the chain array B1. After obtaining the linear transformation array of the chain array B1, restore the new root chain string to the original root chain string before the update.

[0067] SS325: Get the chain array in sequence from SS321 to SS32 The linear transformation array of each chain array is calculated, and the initial root chain string is updated and restored once in the process of calculating the linear transformation array of each chain array;

[0068] SS326: According to nonlinear characters, quasi-linear characters, root chain string and chain array of diversion sequence A1 The nonlinear characters, quasi-linear characters of the shunt sequence A1 and the root chain string of the chain array are separated in the order of The linear transformation arrays of the shunt sequence A1 are spliced to obtain the shunt transformation sequence;

[0069] SS33: If the total number of differences of 2 or -2 among all the obtained differences is not b, it is determined that the linear property of the branch sequence A1 cannot be converted from a nonlinear sequence to a linear sequence through transformation. In this case, character 0 is determined to be a quasi-linear character of the branch sequence. The branch sequence A1 is transformed according to a preset non-quasi-transformation rule to obtain a branch conversion sequence. The non-quasi-transformation rule is as follows:

[0070] SS331: Use the binary number of b as the non-intended record array of the branch sequence A1. In this application, the character length of the binary number of b is 8. If the character length of the binary number converted from b is less than 8, it is padded with the character 0;

[0071] SS332: Determine whether the decimal difference between the chain header string C1 and the root chain string is positive or negative. If the difference is positive, the nonlinear change direction of the chain header string C1 relative to the root chain string is determined to be positive. In this case, character 1 is used as the nonlinear change character of the chain header string C1. Otherwise, the nonlinear change direction of the chain header string C1 relative to the root chain string is determined to be negative. In this case, character 0 is used as the nonlinear change character of the chain header string C1. In this application, the nonlinear change direction includes positive and negative.

[0072] SS333: Using the two binary digits of the absolute value of the difference as a nonlinear combination of the chain array B1;

[0073] SS334: Concatenate the nonlinear changing characters, the nonlinear combination, and all the remaining strings after the chain array B1 cuts out the corresponding chain head string in this order to obtain a linear transformation array of the chain array B1;

[0074] SS335: Follow SS332 to SS334 to calculate and obtain the chain array The linear transformation array of ;

[0075] SS336: According to non-linear characters, quasi-linear characters, non-quasi-record arrays, chain arrays B1, The nonlinear character, quasi-linear character, non-quasi-record array, chain array are arranged in the order Splicing is performed to obtain a diversion conversion sequence of diversion sequence A1;

[0076] Step 6: Obtain the diversion conversion sequences of diversion sequences A2, A3, ..., Aa in sequence according to steps 2 to 4, and then concatenate the diversion conversion sequences of diversion sequences A1, A2, ..., Aa in the order of diversion sequences A1, A2, ..., Aa to obtain the diversion feedback data of the interactive confirmation information;

[0077] The interactive data shunting unit transmits the shunted feedback data of the interactive confirmation information to the interactive data sharing unit. In this application, if there is a temporarily stored fixed sequence, the fixed sequence is also transmitted to the interactive data sharing unit;

[0078] After receiving the diversion feedback data of the transmitted interaction confirmation information, the interactive data sharing unit transmits the diversion feedback data to the credit platform corresponding to the transmission of the interaction confirmation information. In this application, if the interactive data sharing unit receives the transmitted fixed sequence, the fixed sequence is asynchronously transmitted to the credit platform.

[0079] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0080] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A multi-platform medical equipment data management system, characterized in that: include: A medical data storage terminal is used to extract medical data from the interactive confirmation information transmitted by the credit platform, wherein the interactive confirmation information includes identity information of several medical subjects, and the extracted medical data includes medical data of several medical subjects; an interactive data splitting unit, configured to perform a pre-processing operation on the received extracted medical data to obtain first processed data of the extracted medical data, wherein the pre-processing operation is performed using a base converter to convert the base of the extracted medical data; The interactive data splitting unit is further configured to perform a first pre-grouping operation on the first processed data to obtain a plurality of split sequences of the first processed data; The interactive data shunting unit is also configured to, after obtaining a plurality of shunting sequences of the first processed data, perform shunting conversion on all shunting sequences obtained by performing the first pre-grouping operation on the first processed data according to a preset shunting conversion step to obtain shunting feedback data of the interactive confirmation information; The interactive data sharing unit is configured to transmit the diversion feedback data of the interactive confirmation information to the credit platform corresponding to the transmission of the interactive confirmation information after receiving the diversion feedback data of the interactive confirmation information.

2. A multi-platform medical device data management system according to claim 1, characterized in that: The medical data storage terminal stores the medical data of all medical objects in the target hospital.

3. The multi-platform medical device data management system according to claim 1, characterized in that: The character length of each shunt sequence obtained after the interactive data shunt unit performs the first pre-grouping operation is P1. The calculation formula of P1 is P1=12+8×(n-1), where n is 1, 2, 3, ..., ∞.

4. The multi-platform medical device data management system according to claim 1, characterized in that: The steps of converting the shunt feedback data obtained by shunt conversion to obtain the interactive confirmation information are as follows: Step 1: Mark all the shunt sequences of the first processed data as A1, A2, ..., Aa, where a≥1, from left to right according to their positions in the first processed data before the first pre-grouping operation is performed on each shunt sequence; Step 2: Extract a root chain string, chain head strings C1, C2, ..., Cc, and chain head strings D1, D2, ..., Dd from the branch sequence A1 according to the preset branch extraction rules; Step 3: Determine the linear properties of the diversion sequence A1. The linear properties include linear sequence and nonlinear sequence. Step 4: Based on the determination in step 3 that the diversion sequence A1 is a linear sequence, first determine that the linear character of the diversion sequence A1 is 1, and then perform a linear transformation on the diversion sequence A1 using a preset linear transformation rule to obtain a diversion transformation sequence of the diversion sequence A1; Step 5: Based on the determination in step 3 that the diversion sequence A1 is a nonlinear sequence, first determine that the nonlinear character of the diversion sequence A1 is 0, and then execute a preset nonlinear transformation rule to perform a nonlinear transformation on the diversion sequence A1 to obtain a diversion transformation sequence of the diversion sequence A1; Step 6: Obtain the diversion conversion sequence of the diversion sequence A2, A3, ..., Aa in sequence according to steps 2 to 4, and then concatenate the diversion conversion sequence of the diversion sequence A1, A2, ..., Aa in the order of diversion sequence A1, A2, ..., Aa to obtain the diversion feedback data of the interactive confirmation information.

5. The multi-platform medical device data management system according to claim 4, characterized in that: In step 2, the diversion extraction rules are as follows: SS11: performing a second pre-grouping operation on the split sequence A1 to obtain a plurality of chain arrays, wherein the character length of each chain array obtained after performing the second pre-grouping operation is 4; SS12: Label all the chain arrays of the branch sequence A1 as B1, B2, ..., Bb from left to right, according to the position of each chain array in the branch sequence A1 before the second pre-grouping operation, where b≥1; SS13: From left to right, extract the first two characters in chain array B1 as the chain head string of chain array B1. Similarly, extract the first two characters from chain arrays B2, B3, ..., Bb in turn as the chain head strings of the corresponding chain arrays. SS14: Chain array The chain head string is used as the root chain string of the diversion sequence A1. According to the order of the mark subscripts of the chain arrays corresponding to the chain head string from small to large, the chain head strings of all chain arrays with mark subscripts less than (b+1) / 2 are marked as C1, C2, ..., Cc, c = (b+1) / 2-1. Similarly, the chain head strings of all chain arrays with mark subscripts greater than (b+1) / 2 are marked as D1, D2, ..., Dd, d = b-(b+1) / 2.

6. The multi-platform medical device data management system according to claim 5, characterized in that: Step 4: The linear conversion rule of the diversion conversion sequence of the diversion sequence A1 is obtained as follows: SS21: Determine the direction and characteristic characters of the conversion of the chain head string C1 to the root chain string based on the magnitude relationship between the decimal number of the chain head string C1 and the decimal number of the root chain string. The direction of the conversion includes ascending and descending order. SS22: Concatenate the linear characters of the branch sequence A1, the characteristic characters in the direction of change of the chain head string C1 toward the root chain string, and all the remaining strings after the chain array B1 is cut out of the chain head string C1 to obtain a linear conversion array of the chain array B1; SS23: Follow SS21 to SS22 to get chain arrays B2, B3, ..., linear transformation array of Bb; SS24: According to the chain array B1, B2, ..., ..., Bb in the order of chain arrays B1, B2, ..., ..., Bb are spliced together, and then for the spliced data, the root chain string of the shunt sequence A1 is spliced to the rightmost end of the data to obtain the shunt conversion sequence of the shunt sequence A1.

7. The multi-platform medical device data management system according to claim 5, characterized in that: Step 5: The nonlinear conversion rule of the diversion conversion sequence of the diversion sequence A1 is obtained as follows: SS31: Calculate the difference between the decimal number of the chain head string C1, C2, ..., Cc, D1, D2, ..., Dd and the decimal number of the root chain string in sequence, wherein the decimal number of the root chain string is always used as the subtrahend when calculating the difference; SS32: If the total number of differences of 2 or -2 among all the differences is calculated to be b, then it is determined that the linear property of the diversion sequence A1 can be transformed from a nonlinear sequence to a linear sequence through transformation, and character 1 is determined to be a quasi-linear character of the diversion sequence. The diversion conversion sequence of the diversion sequence A1 is obtained according to a preset quasi-transformation rule; SS33: If the total number of differences of 2 or -2 among all the obtained differences is not b, it is determined that the linear property of the diversion sequence A1 cannot be converted from a nonlinear sequence to a linear sequence through transformation. At this time, the character 0 is determined to be the quasi-linear character of the diversion sequence, and the diversion conversion sequence of the diversion sequence A1 is obtained according to the preset non-quasi-transformation rule.

8. The multi-platform medical device data management system according to claim 6, characterized in that: In SS21, if the decimal number of the chain head string C1 is smaller than the decimal number of the root chain string, it is determined that the change direction of the chain head string C1 toward the root chain string is ascending. At this time, character 1 is used as the characteristic character of the change direction of the chain head string C1 toward the root chain string. Otherwise, character 0 is used as the characteristic character of the change direction of the chain head string C1 toward the root chain string.

9. The multi-platform medical device data management system according to claim 7, characterized in that: SS32, the pseudo-transformation rule of the diversion conversion sequence obtained by converting the diversion sequence A1 is as follows: SS321: Determine whether the decimal difference between the chain header string C1 and the root chain string is positive or negative. If the difference is positive, the quasi-linear change direction of the root chain string relative to the chain header string C1 is determined to be ascending. In this case, character 1 is used as the character to be changed in the chain header string C1. Otherwise, character 0 is used as the character to be changed in the chain header string C1. The quasi-linear change direction includes ascending and descending changes. SS322: Update the root chain string according to the quasi-linear change direction of the root chain string compared to the chain head string C1; SS323: At this time, according to SS21 to SS22, based on the size relationship between the decimal number of the chain head string C1 and the decimal number of the new root chain string, the change direction of the chain head string C1 to the root chain string is determined to obtain the characteristic character of the change direction of the chain head string C1 to the new root chain string; SS324: Concatenate all remaining strings after extracting the corresponding chain head string from the chain array B1 according to the proposed changed character, the characteristic character, and the chain array B1 to obtain a linear transformation array of the chain array B1. After obtaining the linear transformation array of the chain array B1, restore the new root chain string to the original root chain string before the update. SS325: Follow SS321 to SS32 to get chain arrays B2, B3, ..., ..., linear transformation array of Bb; SS326: According to nonlinear characters, quasi-linear characters, the root chain string of the diversion sequence A1, the chain arrays B1, B2, ..., ..., Bb, the nonlinear characters and quasi-linear characters of the shunt sequence A1 and the root chain string of the chain arrays B1, B2, ..., ..., and the linear transformation arrays of Bb are concatenated to obtain the shunt transformation sequence of the shunt sequence A1.

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