Remote medical data management system and method based on cloud platform

Abstract

The invention discloses a remote medical data management system and method based on a cloud platform, and belongs to the technical field of data management, and the method comprises the following steps: updating medical data to a main storage node, and generating an update record of the main storage node; the main storage node initiates a data synchronization request to the auxiliary storage node, and the synchronization delay between the main storage node and the auxiliary storage node is calculated; judging whether the synchronization delay between the main storage node and the auxiliary storage node is abnormal or not, and adjusting the synchronization frequency between the main storage node and the auxiliary storage node; the main storage node synchronizes the data to the auxiliary storage node to form a synchronous record; judging whether the data are consistent or not, dividing recovery priorities of the secondary storage nodes, and recovering the data of the secondary storage nodes; according to the method, the synchronization frequency between the main storage node and the auxiliary storage node can be judged and adjusted, the problem of data inconsistency caused by delay abnormity is avoided, and the real-time performance, the accuracy and the integrity of medical data management are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of data management, and specifically relates to a remote medical data management system and method based on a cloud platform. Background Art

[0002] With the continuous development of science and technology, especially the application of cloud platform technology, the medical industry has achieved remarkable progress in data storage, management and sharing. Distributed storage is a technology that stores data in multiple physical nodes. Cloud platforms use distributed storage to centrally manage and quickly access patients' monitoring data, providing medical institutions with efficient and flexible storage solutions, so that patients' historical medical records and real-time monitoring data can be centrally managed and quickly accessed.

[0003] However, as the amount of data continues to increase, the distributed storage nodes used by the cloud platform have gradually caused data synchronization problems. The synchronization delay is high during data synchronization, and data updates are not timely or complete, which in turn causes data inconsistency between different storage nodes. If the data of each storage node is not discovered and restored in time, it is easy to cause misdiagnosis of patients and affect their treatment.

[0004] Therefore, people are in urgent need of a cloud-based telemedicine data management system to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a remote medical data management system based on a cloud platform to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] A remote medical data management method based on a cloud platform, the method comprising the following steps:

[0008] S1. Collect medical data through medical equipment and transmit it to the cloud platform. After receiving the medical data, the cloud platform updates the medical data to the main storage node and generates an update record of the main storage node;

[0009] S2, the primary storage node initiates a data synchronization request to the secondary storage node, obtains the request transmission interval between the primary storage node and the secondary storage node, and the request processing interval of the secondary storage node, and calculates the synchronization delay between the primary storage node and the secondary storage node;

[0010] S3. According to the synchronization delay between the primary storage node and the secondary storage node, determine whether the synchronization delay between the primary storage node and the secondary storage node is abnormal; if the synchronization delay between the primary storage node and the secondary storage node is abnormal, adjust the synchronization frequency between the primary storage node and the secondary storage node;

[0011] S4. The primary storage node synchronizes the data to the secondary storage node to form a synchronization record; based on the update record and the synchronization record, it determines whether the data is consistent; if the data is inconsistent, it sends a synchronization abnormality warning, calculates the amount of data loss of the secondary storage node, divides the recovery priority of the secondary storage node, and recovers the data of the secondary storage node.

[0012] According to the above technical solution, step S1 includes the following:

[0013] S1-1. Set up medical equipment, monitor the user through the medical equipment, and obtain the medical data of the user; the medical equipment transmits the collected medical data to the cloud platform, and the cloud platform updates the medical data to the main storage node after receiving the medical data transmitted by the medical equipment;

[0014] S1-2. When updating the data in the main storage node, record the update timestamp and update data volume of the updated data in the main storage node; each time the data in the main storage node is updated, obtain the update timestamp and update data volume of the updated data in the main storage node, and generate an update record of the main storage node;

[0015] The timeliness of the data is ensured by real-time acquisition and uploading of medical data, and data management efficiency is improved through centralized management through the main storage node.

[0016] According to the above technical solution, step S2 includes the following:

[0017] S2-1, the primary storage node sends a data synchronization request to a secondary storage node; collects the sending time point of the data synchronization request in the primary storage node and the receiving time point of the data synchronization request in the secondary storage node, and calculates the difference between the receiving time point of the data synchronization request in the secondary storage node and the sending time point of the data synchronization request in the primary storage node as the request transmission time between the primary storage node and the secondary storage node;

[0018] S2-2, collecting the time point at which the secondary storage node processes the data synchronization request, and calculating the difference between the time point at which the secondary storage node processes the data synchronization request and the time point at which the secondary storage node receives the data synchronization request as the request processing interval of the secondary storage node;

[0019] S2-3. Calculate the sum of the request transmission time between the primary storage node and the secondary storage node and the request processing interval of the secondary storage node as the synchronization delay between the primary storage node and the secondary storage node.

[0020] According to the above technical solution, step S3 includes the following:

[0021] S3-1, take the average value of all synchronization delays between the primary storage node and a certain secondary storage node, recorded as A1; take the standard deviation of all synchronization delays between the primary storage node and the secondary storage node, recorded as A2;

[0022] If the synchronization delay between the primary storage node and the secondary storage node is greater than A1+α×A2, the delay between the primary storage node and the secondary storage node is abnormal, and a synchronization abnormality warning is sent, where α represents an influencing parameter;

[0023] S3-2, the time point when the secondary storage node processes the corresponding data synchronization request is recorded as time point t, and the CPU utilization rate, disk utilization rate and network utilization rate of the secondary storage node at time point t are collected, and the formula is used: t =β1×B1 t +β2×B2 t +β3×B3 t , calculate the load characteristics of the secondary storage node at time point t, where B t represents the load characteristics of the secondary storage node at time point t, B1 t Indicates the CPU usage of the secondary storage node at time point t, B2 t Indicates the disk usage of the secondary storage node at time point t, B3 t represents the network utilization of the secondary storage node at time point t, β1 represents the CPU weight coefficient, β2 represents the disk weight coefficient, and β3 represents the network weight coefficient;

[0024] The value of the request processing interval of the synchronization request corresponding to the data processed by the secondary storage node is recorded as T; the synchronization frequency between the primary storage node and the secondary storage node is adjusted to C max}, where C represents the synchronization frequency between the primary storage node and the secondary storage node, C max represents the maximum synchronization frequency allowed by the system, γ represents the adjustment coefficient, Represents the pair γ×T×B t ×C max Round upwards, Indicates taking γ×T×B t ×C max and C max The minimum value between

[0025] Through synchronization delay monitoring, network, hardware or system problems can be quickly discovered; the synchronization frequency can be dynamically adjusted to avoid performance degradation or system failure caused by high load, improve the overall operation efficiency of the system, and reduce data inconsistencies caused by delay anomalies.

[0026] According to the above technical solution, step S4 includes the following:

[0027] S4-1, when the primary storage node synchronizes the data in the secondary storage node, it records the synchronization timestamp and the amount of synchronized data in the secondary storage node after synchronization, and each time the data in the secondary storage node is synchronized, the synchronization timestamp and the amount of synchronized data in the secondary storage node after synchronization are obtained, and a synchronization record of the secondary storage node is generated;

[0028] S4-2, filter the update record of the primary storage node and the synchronization record of a secondary storage node, filter out the update record with the largest update timestamp, and record it as the first record; filter out the synchronization record with the largest synchronization timestamp, and record it as the second record;

[0029] Compare the updated data amount of the first record with the synchronized data amount of the second record. If the updated data amount of the first record is equal to the synchronized data amount of the second record, the data between the primary storage node and the secondary storage node are consistent; if the updated data amount of the first record is not equal to the synchronized data amount of the second record, the data between the primary storage node and the secondary storage node are inconsistent;

[0030] S4-3. If the data between the primary storage node and the secondary storage node are inconsistent, send a synchronization abnormality warning, calculate the ratio of the updated data volume of the first record minus the synchronized data volume of the second record to the updated data volume of the first record, and use this as the data loss volume of the secondary storage node corresponding to the second record; obtain the secondary storage nodes with inconsistent data, obtain the synchronization frequency between each secondary storage node and the primary storage node, and calculate the data loss volume of each secondary storage node;

[0031] Using the formula: E i =δ1×D i +δ2×(1-C i / C max ), calculate the recovery priority value of each secondary storage node, where E i represents the recovery priority value of the ith secondary storage node, D i represents the data loss of the ith secondary storage node, C i represents the synchronization frequency of the ith secondary storage node, δ1 represents the loss weight coefficient, and δ2 represents the frequency weight coefficient;

[0032] The secondary storage nodes are sorted from large to small according to the recovery priority value, and the secondary storage nodes are numbered according to the sorting as the recovery priority of each secondary storage node, and the data of each secondary storage node is restored in sequence;

[0033] The lower the synchronization frequency or the higher the data loss, the more serious the abnormality of the secondary storage node or the heavier the load, and the priority should be given to recovery;

[0034] The higher the synchronization frequency or the lower the data loss, the less abnormal the secondary storage node is or the lighter the load is, and the priority can be appropriately lowered;

[0035] Quickly locate nodes with inconsistent data, reduce the impact of data loss on the system, prioritize restoring key nodes based on the amount of data loss, improve data recovery efficiency, ensure the eventual consistency of data between primary and secondary storage nodes, and meet the high reliability requirements of telemedicine data.

[0036] A remote medical data management system based on a cloud platform, the system includes a collection module, a calculation module, a data evaluation module and a decision module;

[0037] The acquisition module is used to collect the patient's medical data through medical equipment and store the data in the database of the cloud platform; the calculation module is used to calculate the synchronization delay of the data between the primary storage node and the secondary storage node, the load characteristics of the secondary storage node and the synchronization frequency adjustment value; the data evaluation module is used to evaluate the consistency of the data between the primary storage node and the secondary storage node, and determine whether the data between the primary storage node and the secondary storage node are consistent based on the update records and synchronization records; the decision module is used to optimize the synchronization frequency according to the load status of the secondary storage node, and divide the recovery priority of the secondary storage node in combination with the data loss amount of the secondary storage node, and recover the data of the secondary storage node.

[0038] According to the above technical solution, the acquisition module includes a medical data unit, an update recording unit and a synchronization recording unit;

[0039] The medical data unit is used to collect medical data of users through medical equipment, including physiological data, vital sign data and medical imaging data, and store them in the database of the cloud platform; the update record unit is used to record the update timestamp and the update data volume when the main storage node updates the data, and generate an update record of the main storage node; the synchronization record unit is used to record the synchronization timestamp and the synchronization data volume when the secondary storage node synchronizes the data, and generate a synchronization record of the secondary storage node.

[0040] According to the above technical solution, the calculation module includes a synchronization delay calculation unit and a load characteristic calculation unit;

[0041] The synchronization delay calculation unit is used to calculate the request transmission time and request processing interval between the primary storage node and the secondary storage node, and obtain the synchronization delay based on the request transmission time and request processing interval; the load characteristic calculation unit is used to calculate the load characteristics of the secondary storage node based on the CPU utilization, disk utilization and network utilization of the secondary storage node.

[0042] According to the above technical solution, the data evaluation module includes a data verification unit and an abnormality recording unit;

[0043] The data verification unit is used to compare the update record of the primary storage node with the synchronization record of the secondary storage node, and evaluate the consistency status of the data between the primary storage node and the secondary storage node;

[0044] The abnormality recording unit is used to record the data loss amount and abnormal status of the secondary storage node when data inconsistency is found.

[0045] According to the above technical solution, the decision module includes a recovery decision unit and a synchronization frequency optimization unit;

[0046] The recovery decision unit is used to generate a recovery priority according to the amount of data loss and synchronization frequency of the secondary storage node, and to perform data recovery operations in sequence; the synchronization frequency optimization unit is used to adjust the synchronization frequency between the primary storage node and the secondary storage node according to the load characteristics and synchronization delay status of the secondary storage node.

[0047] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0048] The present invention collects data in real time and combines it with a cloud platform to dynamically manage and evaluate the consistency of medical data. It can intelligently determine and adjust the synchronization frequency between the main storage node and the secondary storage node, thereby avoiding data inconsistency problems caused by delay anomalies and improving the real-time and accuracy of medical data management. At the same time, the present invention calculates the load characteristics of the secondary storage node and dynamically optimizes the system synchronization strategy to avoid performance degradation or failures caused by high load, thereby improving the operating efficiency and stability of the system. Moreover, the present invention can quickly locate and restore data at key nodes through data loss assessment and recovery priority division, reduce the impact of data loss on medical decision-making, and effectively ensure the high reliability of the telemedicine system. In addition, the present invention optimizes the storage and maintenance mechanism of the cloud platform, reduces the problem of excessive or delayed maintenance of the system, effectively reduces operating costs, and at the same time ensures the integrity and security of medical data, meeting the needs of telemedicine data management in high concurrency and big data scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] 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:

[0050] Figure 1 It is a flow chart of a remote medical data management method based on a cloud platform of the present invention;

[0051] Figure 2 It is a structural schematic diagram of a remote medical data management system based on a cloud platform of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 technical visitors in this field without creative work are within the scope of protection of the present invention.

[0053] See also Figure 1 , the present invention provides a technical solution:

[0054] A remote medical data management method based on a cloud platform, the method comprising the following steps:

[0055] S1. Collect medical data through medical equipment and transmit it to the cloud platform. After receiving the medical data, the cloud platform updates the medical data to the main storage node and generates an update record of the main storage node;

[0056] According to the above technical solution, step S1 includes the following:

[0057] S1-1. Set up medical equipment, monitor the user through the medical equipment, and obtain the medical data of the user; the medical equipment transmits the collected medical data to the cloud platform, and the cloud platform updates the medical data to the main storage node after receiving the medical data transmitted by the medical equipment;

[0058] S1-2. When updating the data in the main storage node, record the update timestamp and update data volume of the updated data in the main storage node; each time the data in the main storage node is updated, obtain the update timestamp and update data volume of the updated data in the main storage node, and generate an update record of the main storage node;

[0059] The timeliness of the data is ensured by real-time acquisition and uploading of medical data, and data management efficiency is improved through centralized management through the main storage node.

[0060] S2, the primary storage node initiates a data synchronization request to the secondary storage node, obtains the request transmission interval between the primary storage node and the secondary storage node, and the request processing interval of the secondary storage node, and calculates the synchronization delay between the primary storage node and the secondary storage node;

[0061] According to the above technical solution, step S2 includes the following:

[0062] S2-1, the primary storage node sends a data synchronization request to a secondary storage node; collects the sending time point of the data synchronization request in the primary storage node and the receiving time point of the data synchronization request in the secondary storage node, and calculates the difference between the receiving time point of the data synchronization request in the secondary storage node and the sending time point of the data synchronization request in the primary storage node as the request transmission time between the primary storage node and the secondary storage node;

[0063] S2-2, collecting the time point at which the secondary storage node processes the data synchronization request, and calculating the difference between the time point at which the secondary storage node processes the data synchronization request and the time point at which the secondary storage node receives the data synchronization request as the request processing interval of the secondary storage node;

[0064] S2-3. Calculate the sum of the request transmission time between the primary storage node and the secondary storage node and the request processing interval of the secondary storage node as the synchronization delay between the primary storage node and the secondary storage node.

[0065] S3. According to the synchronization delay between the primary storage node and the secondary storage node, determine whether the synchronization delay between the primary storage node and the secondary storage node is abnormal; if the synchronization delay between the primary storage node and the secondary storage node is abnormal, adjust the synchronization frequency between the primary storage node and the secondary storage node;

[0066] According to the above technical solution, step S3 includes the following:

[0067] S3-1, take the average value of all synchronization delays between the primary storage node and a certain secondary storage node, recorded as A1; take the standard deviation of all synchronization delays between the primary storage node and the secondary storage node, recorded as A2;

[0068] If the synchronization delay between the primary storage node and the secondary storage node is greater than A1+α×A2, the delay between the primary storage node and the secondary storage node is abnormal, and a synchronization abnormality warning is sent, where α represents an influencing parameter;

[0069] S3-2, the time point when the secondary storage node processes the corresponding data synchronization request is recorded as time point t, and the CPU utilization rate, disk utilization rate and network utilization rate of the secondary storage node at time point t are collected, and the formula is used: t =β1×B1 t +β2×B2 t +β3×B3 t , calculate the load characteristics of the secondary storage node at time point t, where B t represents the load characteristics of the secondary storage node at time point t, B1 t Indicates the CPU usage of the secondary storage node at time point t, B2 t Indicates the disk usage of the secondary storage node at time point t, B3t represents the network utilization of the secondary storage node at time point t, β1 represents the CPU weight coefficient, β2 represents the disk weight coefficient, and β3 represents the network weight coefficient;

[0070] The value of the request processing interval of the synchronization request corresponding to the data processed by the secondary storage node is recorded as T; the synchronization frequency between the primary storage node and the secondary storage node is adjusted to C max}, where C represents the synchronization frequency between the primary storage node and the secondary storage node, C max represents the maximum synchronization frequency allowed by the system, γ represents the adjustment coefficient, Represents the pair γ×T×B t ×C max Round upwards, Indicates taking γ×T×B t ×C max and C max The minimum value between

[0071] For example:

[0072] At time point t, the secondary storage node needs to process a data synchronization request. At this time, the system resource usage of the secondary storage node at time point t is collected, and the CPU usage rate B1 t =0.75, disk usage B2 t =0.6 and network utilization rate B3 t =0.5, using the formula: B t =β1×B1 t +β2×B2 t +β3×B3 t , where the CPU weight coefficient β1 = 0.5, the disk weight coefficient β2 = 0.3, and the network weight coefficient β3 = 0.2. Calculate the load characteristic B of the secondary storage node at time point t t =0.655;

[0073] The request processing interval T of the secondary storage node processing data corresponding to the synchronization request is 1, and the maximum synchronization frequency allowed by the system is C max =10, adjustment coefficient γ = 0.8, the synchronization frequency between the primary storage node and the secondary storage node is adjusted to C max =10}=6;

[0074] Through synchronization delay monitoring, network, hardware or system problems can be quickly discovered; the synchronization frequency can be dynamically adjusted to avoid performance degradation or system failure caused by high load, improve the overall operation efficiency of the system, and reduce data inconsistencies caused by delay anomalies.

[0075] S4. The primary storage node synchronizes the data to the secondary storage node to form a synchronization record; based on the update record and the synchronization record, it determines whether the data is consistent; if the data is inconsistent, it sends a synchronization abnormality warning, calculates the data loss amount of the secondary storage node, divides the recovery priority of the secondary storage node, and recovers the data of the secondary storage node;

[0076] According to the above technical solution, step S4 includes the following:

[0077] S4-1, when the primary storage node synchronizes the data in the secondary storage node, it records the synchronization timestamp and the amount of synchronized data in the secondary storage node after synchronization, and each time the data in the secondary storage node is synchronized, the synchronization timestamp and the amount of synchronized data in the secondary storage node after synchronization are obtained, and a synchronization record of the secondary storage node is generated;

[0078] S4-2, filter the update record of the primary storage node and the synchronization record of a secondary storage node, filter out the update record with the largest update timestamp, and record it as the first record; filter out the synchronization record with the largest synchronization timestamp, and record it as the second record;

[0079] Compare the updated data amount of the first record with the synchronized data amount of the second record. If the updated data amount of the first record is equal to the synchronized data amount of the second record, the data between the primary storage node and the secondary storage node are consistent; if the updated data amount of the first record is not equal to the synchronized data amount of the second record, the data between the primary storage node and the secondary storage node are inconsistent;

[0080] S4-3. If the data between the primary storage node and the secondary storage node are inconsistent, send a synchronization abnormality warning, calculate the ratio of the updated data volume of the first record minus the synchronized data volume of the second record to the updated data volume of the first record, and use this as the data loss volume of the secondary storage node corresponding to the second record; obtain the secondary storage nodes with inconsistent data, obtain the synchronization frequency between each secondary storage node and the primary storage node, and calculate the data loss volume of each secondary storage node;

[0081] Using the formula: E i =δ1×D i +δ2×(1-C i / C max ), calculate the recovery priority value of each secondary storage node, where E i represents the recovery priority value of the ith secondary storage node, D i represents the data loss of the ith secondary storage node, C i represents the synchronization frequency of the ith secondary storage node, δ1 represents the loss weight coefficient, and δ2 represents the frequency weight coefficient;

[0082] The secondary storage nodes are sorted from large to small according to the recovery priority value, and the secondary storage nodes are numbered according to the sorting as the recovery priority of each secondary storage node, and the data of each secondary storage node is restored in sequence;

[0083] The lower the synchronization frequency or the higher the data loss, the more serious the abnormality of the secondary storage node or the heavier the load, and the priority should be given to recovery;

[0084] The higher the synchronization frequency or the lower the data loss, the less abnormal the secondary storage node is or the lighter the load is, and the priority can be appropriately lowered;

[0085] Quickly locate nodes with inconsistent data, reduce the impact of data loss on the system, prioritize restoring key nodes based on the amount of data loss, improve data recovery efficiency, ensure the eventual consistency of data between primary and secondary storage nodes, and meet the high reliability requirements of telemedicine data.

[0086] See also Figure 2 , a remote medical data management system based on a cloud platform, the system includes a collection module, a calculation module, a data evaluation module and a decision module;

[0087] The acquisition module is used to collect the patient's medical data through medical equipment and store the data in the database of the cloud platform; the calculation module is used to calculate the synchronization delay of the data between the primary storage node and the secondary storage node, the load characteristics of the secondary storage node and the synchronization frequency adjustment value; the data evaluation module is used to evaluate the consistency of the data between the primary storage node and the secondary storage node, and determine whether the data between the primary storage node and the secondary storage node are consistent based on the update records and synchronization records; the decision module is used to optimize the synchronization frequency according to the load status of the secondary storage node, and divide the recovery priority of the secondary storage node in combination with the data loss amount of the secondary storage node, and recover the data of the secondary storage node.

[0088] According to the above technical solution, the acquisition module includes a medical data unit, an update recording unit and a synchronization recording unit;

[0089] The medical data unit is used to collect medical data of users through medical equipment, including physiological data, vital sign data and medical imaging data, and store them in the database of the cloud platform; the update record unit is used to record the update timestamp and the update data volume when the main storage node updates the data, and generate an update record of the main storage node; the synchronization record unit is used to record the synchronization timestamp and the synchronization data volume when the secondary storage node synchronizes the data, and generate a synchronization record of the secondary storage node.

[0090] According to the above technical solution, the calculation module includes a synchronization delay calculation unit and a load characteristic calculation unit;

[0091] The synchronization delay calculation unit is used to calculate the request transmission time and request processing interval between the primary storage node and the secondary storage node, and obtain the synchronization delay based on the request transmission time and request processing interval; the load characteristic calculation unit is used to calculate the load characteristics of the secondary storage node based on the CPU utilization, disk utilization and network utilization of the secondary storage node.

[0092] According to the above technical solution, the data evaluation module includes a data verification unit and an abnormality recording unit; the data verification unit is used to compare the update record of the primary storage node with the synchronization record of the secondary storage node, and evaluate the consistency status of the data between the primary storage node and the secondary storage node;

[0093] The abnormality recording unit is used to record the data loss amount and abnormal status of the secondary storage node when data inconsistency is found.

[0094] According to the above technical solution, the decision module includes a recovery decision unit and a synchronization frequency optimization unit;

[0095] The recovery decision unit is used to generate a recovery priority according to the amount of data loss and synchronization frequency of the secondary storage node, and to perform data recovery operations in sequence; the synchronization frequency optimization unit is used to adjust the synchronization frequency between the primary storage node and the secondary storage node according to the load characteristics and synchronization delay status of the secondary storage node.

[0096] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, for technical visitors in the field, it is still possible to modify the technical solutions recorded in the aforementioned embodiments, or to replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A remote medical data management method based on a cloud platform, characterized in that: The method comprises the following steps: S1. Collect medical data through medical equipment and transmit it to the cloud platform. After receiving the medical data, the cloud platform updates the medical data to the main storage node and generates an update record of the main storage node; S2, the primary storage node initiates a data synchronization request to the secondary storage node, obtains the request transmission interval between the primary storage node and the secondary storage node, and the request processing interval of the secondary storage node, and calculates the synchronization delay between the primary storage node and the secondary storage node; S3. According to the synchronization delay between the primary storage node and the secondary storage node, determine whether the synchronization delay between the primary storage node and the secondary storage node is abnormal; if the synchronization delay between the primary storage node and the secondary storage node is abnormal, adjust the synchronization frequency between the primary storage node and the secondary storage node; S4. The primary storage node synchronizes the data to the secondary storage node to form a synchronization record; based on the update record and the synchronization record, it determines whether the data is consistent; if the data is inconsistent, it sends a synchronization abnormality warning, calculates the amount of data loss of the secondary storage node, divides the recovery priority of the secondary storage node, and recovers the data of the secondary storage node.

2. The remote medical data management method based on a cloud platform according to claim 1, characterized in that: The step S1 comprises the following: S1-1. Set up medical equipment, monitor the user through the medical equipment, and obtain the medical data of the user; the medical equipment transmits the collected medical data to the cloud platform, and the cloud platform updates the medical data to the main storage node after receiving the medical data transmitted by the medical equipment; S1-2, when updating the data in the primary storage node, record the update timestamp and update data volume of the updated data in the primary storage node; Each time the data in the main storage node is updated, the update timestamp and update data volume of the updated data in the main storage node are obtained, and an update record of the main storage node is generated.

3. A remote medical data management method based on a cloud platform according to claim 2, characterized in that: The step S2 comprises the following: S2-1, the primary storage node sends a data synchronization request to a secondary storage node; collects the sending time point of the data synchronization request in the primary storage node and the receiving time point of the data synchronization request in the secondary storage node, and calculates the difference between the receiving time point of the data synchronization request in the secondary storage node and the sending time point of the data synchronization request in the primary storage node as the request transmission time between the primary storage node and the secondary storage node; S2-2, collecting the time point at which the secondary storage node processes the data synchronization request, and calculating the difference between the time point at which the secondary storage node processes the data synchronization request and the time point at which the secondary storage node receives the data synchronization request as the request processing interval of the secondary storage node; S2-3. Calculate the sum of the request transmission time between the primary storage node and the secondary storage node and the request processing interval of the secondary storage node as the synchronization delay between the primary storage node and the secondary storage node.

4. The remote medical data management method based on a cloud platform according to claim 3, characterized in that: The step S3 includes the following: S3-1, take the average value of all synchronization delays between the primary storage node and a certain secondary storage node, recorded as A1; take the standard deviation of all synchronization delays between the primary storage node and the secondary storage node, recorded as A2; If the synchronization delay between the primary storage node and the secondary storage node is greater than A1+α×A2, the delay between the primary storage node and the secondary storage node is abnormal, and a synchronization abnormality warning is sent, where α represents an influencing parameter; S3-2, the time point when the secondary storage node processes the corresponding data synchronization request is recorded as time point t, and the CPU utilization rate, disk utilization rate and network utilization rate of the secondary storage node at time point t are collected, and the formula is used: t =β1×B1 t +β2×B2 t +β3×B3 t , calculate the load characteristics of the secondary storage node at time point t, where B t represents the load characteristics of the secondary storage node at time point t, B1 t Indicates the CPU usage of the secondary storage node at time point t, B2 t Indicates the disk usage of the secondary storage node at time point t, B3 t represents the network utilization of the secondary storage node at time point t, β1 represents the CPU weight coefficient, β2 represents the disk weight coefficient, and β3 represents the network weight coefficient; The value of the request processing interval of the synchronization request corresponding to the data processed by the secondary storage node is recorded as T; the synchronization frequency between the primary storage node and the secondary storage node is adjusted to Where C represents the synchronization frequency between the primary storage node and the secondary storage node, C max represents the maximum synchronization frequency allowed by the system, γ represents the adjustment coefficient, Represents the pair γ×T×B t ×C max Round upwards, Indicates taking γ×T×B t ×C max and C max The minimum value between .

5. A remote medical data management method based on a cloud platform according to claim 4, characterized in that: The step S4 comprises the following: S4-1, when the primary storage node synchronizes the data in the secondary storage node, it records the synchronization timestamp and the amount of synchronized data in the secondary storage node after synchronization, and each time the data in the secondary storage node is synchronized, the synchronization timestamp and the amount of synchronized data in the secondary storage node after synchronization are obtained, and a synchronization record of the secondary storage node is generated; S4-2, filter the update record of the primary storage node and the synchronization record of a secondary storage node, filter out the update record with the largest update timestamp, and record it as the first record; Filter out the synchronization record with the largest synchronization timestamp and record it as the second record; Compare the updated data amount of the first record with the synchronized data amount of the second record. If the updated data amount of the first record is equal to the synchronized data amount of the second record, the data between the primary storage node and the secondary storage node are consistent; if the updated data amount of the first record is not equal to the synchronized data amount of the second record, the data between the primary storage node and the secondary storage node are inconsistent; S4-3. If the data between the primary storage node and the secondary storage node are inconsistent, send a synchronization abnormality warning, calculate the ratio of the updated data volume of the first record minus the synchronized data volume of the second record to the updated data volume of the first record, and use this as the data loss volume of the secondary storage node corresponding to the second record; obtain the secondary storage nodes with inconsistent data, obtain the synchronization frequency between each secondary storage node and the primary storage node, and calculate the data loss volume of each secondary storage node; Using the formula: E i =δ1×D i +δ2×(1-C i / C max ), calculate the recovery priority value of each secondary storage node, where E i represents the recovery priority value of the ith secondary storage node, D i represents the data loss of the ith secondary storage node, C i represents the synchronization frequency of the ith secondary storage node, δ1 represents the loss weight coefficient, and δ2 represents the frequency weight coefficient; The secondary storage nodes are sorted from large to small according to their recovery priority values, and the secondary storage nodes are numbered according to the sorting as the recovery priority of each secondary storage node, and the data of each secondary storage node is restored in sequence.

6. A cloud-based telemedicine data management system, used to implement a cloud-based telemedicine data management method according to any one of claims 1 to 5, characterized in that: The system includes an acquisition module, a calculation module, a data evaluation module and a decision-making module; The acquisition module is used to collect the patient's medical data through medical equipment and store the data in the database of the cloud platform; the calculation module is used to calculate the synchronization delay of the data between the primary storage node and the secondary storage node, the load characteristics of the secondary storage node and the synchronization frequency adjustment value; the data evaluation module is used to evaluate the consistency of the data between the primary storage node and the secondary storage node, and determine whether the data between the primary storage node and the secondary storage node are consistent based on the update records and synchronization records; the decision module is used to optimize the synchronization frequency according to the load status of the secondary storage node, and divide the recovery priority of the secondary storage node in combination with the data loss amount of the secondary storage node, and recover the data of the secondary storage node.

7. A cloud platform-based remote medical data management system according to claim 6, characterized in that: The acquisition module includes a medical data unit, an update record unit and a synchronization record unit; The medical data unit is used to collect medical data of users through medical equipment, including physiological data, vital sign data and medical imaging data, and store them in the database of the cloud platform; the update record unit is used to record the update timestamp and the update data volume when the main storage node updates the data, and generate an update record of the main storage node; the synchronization record unit is used to record the synchronization timestamp and the synchronization data volume when the secondary storage node synchronizes the data, and generate a synchronization record of the secondary storage node.

8. The cloud platform-based remote medical data management system according to claim 6, characterized in that: The calculation module includes a synchronization delay calculation unit and a load characteristic calculation unit; The synchronization delay calculation unit is used to calculate the request transmission time and request processing interval between the primary storage node and the secondary storage node, and obtain the synchronization delay based on the request transmission time and request processing interval; the load characteristic calculation unit is used to calculate the load characteristics of the secondary storage node based on the CPU utilization, disk utilization and network utilization of the secondary storage node.

9. A cloud platform-based remote medical data management system according to claim 6, characterized in that: The data evaluation module includes a data verification unit and an abnormality recording unit; The data verification unit is used to compare the update record of the primary storage node with the synchronization record of the secondary storage node, and evaluate the consistency status of the data between the primary storage node and the secondary storage node; The abnormality recording unit is used to record the data loss amount and abnormal status of the secondary storage node when data inconsistency is found.

10. A cloud platform-based remote medical data management system according to claim 6, characterized in that: The decision module includes a recovery decision unit and a synchronization frequency optimization unit; The recovery decision unit is used to generate a recovery priority according to the amount of data loss and synchronization frequency of the secondary storage node, and to perform data recovery operations in sequence; the synchronization frequency optimization unit is used to adjust the synchronization frequency between the primary storage node and the secondary storage node according to the load characteristic value and synchronization delay status of the secondary storage node.

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