A remote medical data management system and method based on cloud platform

Abstract

The present invention discloses a remote medical data management system and method based on a cloud platform, belonging to the field of data management technology. The present invention comprises the following steps: updating medical data to a primary storage node and generating an update record of the primary storage node; the primary storage node initiating a data synchronization request to a secondary storage node and calculating the synchronization delay between the primary storage node and the secondary storage node; judging whether the synchronization delay between the primary storage node and the secondary storage node is abnormal and adjusting the synchronization frequency between the primary storage node and the secondary storage node; the primary storage node synchronizing the data to the secondary storage node and forming a synchronization record; judging whether the data is consistent, dividing the recovery priority of the secondary storage node and restoring the data of the secondary storage node; the present invention can judge and adjust the synchronization frequency between the primary storage node and the secondary storage node, avoid the problem of data inconsistency caused by abnormal delay, and improve the real-time, accuracy and integrity of medical data management.

Description

Technical Field

[0001] The present invention belongs to the field of data management technology, 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 significant progress in data storage, management and sharing. Distributed storage is a technology that stores data in a dispersed manner across multiple physical nodes. Cloud platforms use distributed storage to centrally manage and quickly access patient monitoring data, providing medical institutions with an efficient and flexible storage solution, enabling centralized management and rapid access to patients' historical medical records and real-time monitoring data.

[0003] However, as data volumes continue to grow, data synchronization issues are gradually emerging due to the distributed storage nodes used by cloud platforms. High synchronization latency can lead to untimely or incomplete data updates, which in turn causes data inconsistencies between different storage nodes. Failure to promptly discover and restore data from each storage node can easily lead to misdiagnosis of patients, impacting 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. Medical data is collected through medical devices and transmitted to the cloud platform. After receiving the medical data, the cloud platform updates the medical data to the primary storage node and generates an update record for the primary 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. Determine whether the synchronization delay between the primary storage node and the secondary storage node is abnormal based on the synchronization delay between the primary storage node and the secondary storage node; 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 anomaly warning, calculates the amount of data loss on the secondary storage node, divides the recovery priority of the secondary storage node, and recovers the data on the secondary storage node.

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

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

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

[0015] By acquiring and uploading medical data in real time, the timeliness of the data is ensured, and through centralized management through the main storage node, the efficiency of data management is improved.

[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; the primary storage node collects the sending time of the data synchronization request and the receiving time of the data synchronization request in the secondary storage node, and calculates the difference between the receiving time of the data synchronization request in the secondary storage node and the sending time 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. Collect the time points at which the secondary storage node processes the data synchronization request, and calculate 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 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 the impact 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 usage, disk usage and network usage of the secondary storage node at time point t are collected, using the formula: B 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 t, B1 t Indicates the CPU usage of the secondary storage node at time t, B2 t Indicates the disk usage of the secondary storage node at time 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 Indicates the maximum synchronization frequency allowed by the system, γ indicates the adjustment coefficient, Represents 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, thereby improving the overall system operation efficiency and reducing 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 data on the secondary storage node, it records the synchronization timestamp and synchronized data volume of the synchronized data on the secondary storage node. Each time the data on the secondary storage node is synchronized, the synchronization timestamp and synchronized data volume of the synchronized data on the secondary storage node are obtained, and a synchronization record for 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, select the update record with the largest update timestamp, and record it as the first record; select the synchronization record with the largest synchronization timestamp, and record it as the second record;

[0029] Compare the updated data volume of the first record with the synchronized data volume of the second record. If the updated data volume of the first record is equal to the synchronized data volume of the second record, the data between the primary storage node and the secondary storage node are consistent; if the updated data volume of the first record is not equal to the synchronized data volume 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 is inconsistent, a synchronization anomaly warning is issued, and 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 is calculated as the data loss amount of the secondary storage node corresponding to the second record; the secondary storage nodes with inconsistent data are obtained, the synchronization frequency between each secondary storage node and the primary storage node is obtained, and the data loss amount of each secondary storage node is calculated;

[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 i-th secondary storage node, D i represents the data loss of the ith secondary storage node, C i represents the synchronization frequency of the i-th secondary storage node, δ1 represents the loss weight coefficient, and δ2 represents the frequency weight coefficient;

[0032] Sort the secondary storage nodes by their recovery priority values ​​from largest to smallest, and number each secondary storage node according to the ranking, which serves as the recovery priority of each secondary storage node. 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 or heavy load of the secondary storage node is, and it should be restored first;

[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. 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 an acquisition 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 is consistent based on the update record and the synchronization record; 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 update data volume when the main storage node updates data, and generate an update record of the main storage node; the synchronization record unit is used to record the synchronization timestamp and synchronization data volume when the secondary storage node synchronizes 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 delivery time and request processing interval between the primary storage node and the secondary storage node, and obtain the synchronization delay based on the request delivery 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 based on 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 based on the load characteristics and synchronization delay status of the secondary storage node.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[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 judge 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 failure due to high load, thereby improving the system operation efficiency and stability. Moreover, the present invention can quickly locate and recover data at key nodes through data loss amount 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 This is a flow chart of a remote medical data management method based on a cloud platform according to the present invention;

[0051] Figure 2 It is a structural diagram of a cloud platform-based telemedicine data management system of the present invention. DETAILED DESCRIPTION

[0052] 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 a person of ordinary skill in the art without making any creative effort shall fall 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. Medical data is collected through medical devices and transmitted to the cloud platform. After receiving the medical data, the cloud platform updates the medical data to the primary storage node and generates an update record for the primary storage node.

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

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

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

[0059] By acquiring and uploading medical data in real time, the timeliness of the data is ensured, and through centralized management through the main storage node, the efficiency of data management is improved.

[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; the primary storage node collects the sending time of the data synchronization request and the receiving time of the data synchronization request in the secondary storage node, and calculates the difference between the receiving time of the data synchronization request in the secondary storage node and the sending time 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. Collect the time points at which the secondary storage node processes the data synchronization request, and calculate 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. Determine whether the synchronization delay between the primary storage node and the secondary storage node is abnormal based on the synchronization delay between the primary storage node and the secondary storage node; 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 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 the impact 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 usage, disk usage and network usage of the secondary storage node at time point t are collected, using the formula: B 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 t, B1 t Indicates the CPU usage of the secondary storage node at time t, B2 t Indicates the disk usage of the secondary storage node at time 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 Indicates the maximum synchronization frequency allowed by the system, γ indicates the adjustment coefficient, Represents 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 the 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 characteristics 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, and 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, thereby improving the overall system operation efficiency and reducing data inconsistencies caused by delay anomalies.

[0075] S4. The primary storage node synchronizes the data to the secondary storage node, forming a synchronization record. Based on the update record and the synchronization record, the node determines whether the data is consistent. If the data is inconsistent, the node issues a synchronization anomaly warning, calculates the amount of data lost on the secondary storage node, prioritizes the secondary storage node for recovery, and recovers the data on 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 data on the secondary storage node, it records the synchronization timestamp and synchronized data volume of the synchronized data on the secondary storage node. Each time the data on the secondary storage node is synchronized, the synchronization timestamp and synchronized data volume of the synchronized data on the secondary storage node are obtained, and a synchronization record for 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, select the update record with the largest update timestamp, and record it as the first record; select the synchronization record with the largest synchronization timestamp, and record it as the second record;

[0079] Compare the updated data volume of the first record with the synchronized data volume of the second record. If the updated data volume of the first record is equal to the synchronized data volume of the second record, the data between the primary storage node and the secondary storage node are consistent; if the updated data volume of the first record is not equal to the synchronized data volume 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 is inconsistent, a synchronization anomaly warning is issued, and 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 is calculated as the data loss amount of the secondary storage node corresponding to the second record; the secondary storage nodes with inconsistent data are obtained, the synchronization frequency between each secondary storage node and the primary storage node is obtained, and the data loss amount of each secondary storage node is calculated;

[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 i-th secondary storage node, D i represents the data loss of the ith secondary storage node, C i represents the synchronization frequency of the i-th secondary storage node, δ1 represents the loss weight coefficient, and δ2 represents the frequency weight coefficient;

[0082] Sort the secondary storage nodes by their recovery priority values ​​from largest to smallest, and number each secondary storage node according to the ranking, which serves as the recovery priority of each secondary storage node. 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 or heavy load of the secondary storage node is, and it should be restored first;

[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. 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 telemedicine data management system based on a cloud platform, the system includes an acquisition 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 is consistent based on the update record and the synchronization record; 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 update data volume when the main storage node updates data, and generate an update record of the main storage node; the synchronization record unit is used to record the synchronization timestamp and synchronization data volume when the secondary storage node synchronizes 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 delivery time and request processing interval between the primary storage node and the secondary storage node, and obtain the synchronization delay based on the request delivery 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 exception 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 to 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 based on 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 based on the load characteristics and synchronization delay status of the secondary storage node.

[0096] It should be noted that, in this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include," "comprise," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it will be apparent to those skilled in the art that the technical solutions described in the aforementioned embodiments may be modified, or some of the technical features therein may be replaced by equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A remote medical data management method based on a cloud platform, characterized by: The method comprises the following steps: S1. Medical data is collected through medical devices and transmitted to the cloud platform. After receiving the medical data, the cloud platform updates the medical data to the primary storage node and generates an update record for the primary 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. Determine whether the synchronization delay between the primary storage node and the secondary storage node is abnormal based on the synchronization delay between the primary storage node and the secondary storage node; 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; S3-1. Take the average value of all synchronization delays between the primary storage node and a 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 the impact 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 usage, disk usage and network usage of the secondary storage node at time point t are collected, using the formula: B 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 t, B1 t Indicates the CPU usage of the secondary storage node at time t, B2 t Indicates the disk usage of the secondary storage node at time 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 C=min{ , C max }, where C represents the synchronization frequency between the primary storage node and the secondary storage node, C max Indicates the maximum synchronization frequency allowed by the system, γ indicates the adjustment coefficient, Represents γ×T×B t ×C max Round up, min{ , C max } means taking γ×T×B t ×C max and C max The minimum value between 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 anomaly warning, calculates the amount of data loss on the secondary storage node, divides the recovery priority of the secondary storage node, and recovers the data on the secondary storage node.

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

3. The cloud platform-based remote medical data management method according to claim 2, characterized in that: The step S2 includes the following: S2-1. The primary storage node sends a data synchronization request to a secondary storage node; the primary storage node collects the sending time of the data synchronization request and the receiving time of the data synchronization request in the secondary storage node, and calculates the difference between the receiving time of the data synchronization request in the secondary storage node and the sending time 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. Collect the time points at which the secondary storage node processes the data synchronization request, and calculate 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 cloud platform-based telemedicine data management method according to claim 3, characterized in that: The step S4 includes the following: S4-1. When the primary storage node synchronizes data on the secondary storage node, it records the synchronization timestamp and synchronized data volume of the synchronized data on the secondary storage node. Each time the data on the secondary storage node is synchronized, the synchronization timestamp and synchronized data volume of the synchronized data on the secondary storage node are obtained, and a synchronization record for the secondary storage node is generated. S4-2. Filter the update records of the primary storage node and the synchronization records of a secondary storage node, and select the update record with the largest update timestamp, which is recorded 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 volume of the first record with the synchronized data volume of the second record. If the updated data volume of the first record is equal to the synchronized data volume of the second record, the data between the primary storage node and the secondary storage node are consistent; if the updated data volume of the first record is not equal to the synchronized data volume 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 is inconsistent, a synchronization anomaly warning is issued, and 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 is calculated as the data loss amount of the secondary storage node corresponding to the second record; the secondary storage nodes with inconsistent data are obtained, the synchronization frequency between each secondary storage node and the primary storage node is obtained, and the data loss amount of each secondary storage node is calculated; 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 i-th secondary storage node, D i represents the data loss of the ith secondary storage node, C i represents the synchronization frequency of the i-th secondary storage node, δ1 represents the loss weight coefficient, and δ2 represents the frequency weight coefficient; The secondary storage nodes are sorted from largest to smallest according to their recovery priority values, and the secondary storage nodes are numbered according to the sorting, which serves as the recovery priority of each secondary storage node. The data of each secondary storage node is restored in sequence.

5. A cloud-based telemedicine data management system, used to implement the cloud-based telemedicine data management method according to any one of claims 1 to 4, 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 is consistent based on the update record and the synchronization record; 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.

6. The cloud-based telemedicine data management system according to claim 5, characterized in that: The acquisition module includes a medical data unit, an update recording unit and a synchronization recording 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 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 synchronization data volume when the secondary storage node synchronizes the data, and generate a synchronization record of the secondary storage node.

7. The cloud-based telemedicine data management system according to claim 5, 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 delivery time and request processing interval between the primary storage node and the secondary storage node, and obtain the synchronization delay based on the request delivery 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.

8. The cloud-based telemedicine data management system according to claim 5, 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.

9. The cloud-based telemedicine data management system according to claim 5, 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 based on 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 based on the load characteristic value and synchronization delay status of the secondary storage node.

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