Data processing method and system for digital operating room

Abstract

The invention relates to the technical field of medical information, in particular to a data processing method and system for a digital operating room, and the method comprises the following steps: obtaining operation plan information, decomposing an operation process into a plurality of links, classifying various operating room data collected in real time according to the operation links, and generating an operation data classification result. According to the method, the operation process is divided into a plurality of links, accurate classification of operating room data, dynamic assessment of operation risks in combination with physiological data and timely sending of early warning prompts to medical staff are achieved, and the bandwidth allocation priority is dynamically adjusted by analyzing the bandwidth requirement of each data stream in different operation links, so that the operation efficiency is improved. The data transmission efficiency in the operation process is improved, the storage priority of the data is adjusted according to the storage and reading behaviors of the data, optimized utilization of storage resources is achieved, the access permission of the data is dynamically adjusted by means of the timeliness of the data, and accurate management and safety control over the access permission of the data are achieved.

Description

Technical Field

[0001] The present invention relates to the field of medical information technology, and particularly to a data processing method and system for a digital operating room. Background Art

[0002] The field of medical information technology includes the collection, storage, management, and analysis of medical data, aiming to improve the efficiency, safety, and intelligence level of medical services. The core contents include electronic medical record systems, medical Internet of Things, artificial intelligence-assisted diagnosis, medical image processing, surgical navigation systems, and telemedicine. By means of data fusion, intelligent analysis, and visualization technologies, medical processes are optimized to make medical data more operable and valuable, covering aspects such as hospital information system integration, intelligent management of operating rooms, patient physiological monitoring, medical image enhancement, and medical decision-making support, focusing on improving the accuracy, reliability, and resource utilization rate of medical services.

[0003] Among them, the data processing method for a digital operating room refers to the efficient collection, storage, and processing of multiple data sources during the surgical process to support surgical operations and medical decisions. The method covers the collection of physiological data, surgical instrument data, and image data, adopts multi-modal data synchronization technology to ensure the time consistency of data, and combines Internet of Things sensing devices to reduce manual input errors. In terms of data storage and management, a distributed cloud storage architecture is used in combination with edge computing technology to optimize data access speed, and a blockchain mechanism is adopted to ensure data integrity. In the data processing link, abnormal detection algorithms are used for physiological parameters to analyze the intraoperative state of patients, and deep learning models are used to predict intraoperative emergencies. For image data processing, augmented reality or mixed reality technologies are adopted to overlay preoperative images with real-time surgical images to assist doctors in performing precise surgical operations. The network data sharing module realizes the docking of surgical data with the electronic medical record system and the hospital information system through high-speed network protocols, supporting remote expert consultations and surgical live broadcasts for surgical guidance and postoperative analysis.

[0004] In the traditional operating room data processing method, the data classification during the operation mostly relies on manual or static rule setting, resulting in insufficient data classification accuracy. It is unable to dynamically adjust the priority of the data stream according to the real-time surgical steps. In terms of data processing, it relies on preset anomaly detection algorithms and deep learning models for risk prediction, and it is difficult to cope with the sudden dynamic changes during the operation. In terms of data storage management, there is insufficient intelligence in the management of cache storage priority, and it is unable to dynamically adjust the storage priority of different data streams, resulting in key data being occupied by low-priority data during peak periods. In terms of data permission management, fixed permission rules and manual adjustment of permission levels are adopted, lacking a dynamic permission allocation mechanism for data timeliness and medical staff role types, resulting in the inability to obtain important data in a timely manner or an increase in data security risks in case of emergencies. Therefore, the existing technology is difficult to ensure the real-time, accurate, and secure data processing when facing complex surgical scenarios, which restricts the intelligent and efficient development of medical services. Summary of the Invention

[0005] In order to solve the technical problems existing in the prior art, an embodiment of the present invention provides a data processing method and system for a digital operating room. The technical solution is as follows:

[0006] In order to achieve the above object, the present invention adopts the following technical solution. A data processing method for a digital operating room includes the following steps:

[0007] S1: Obtain surgical plan information, decompose the surgical process into multiple links, and classify various operating room data collected in real time according to the surgical links to generate a surgical data classification result;

[0008] S2: Invoke the surgical data classification result, obtain the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data, calculate the physiological parameter change rate and trend direction, evaluate the surgical risk in real time and send a warning prompt to medical staff to generate a dynamic risk warning result;

[0009] S3: Invoke the dynamic risk warning result, combine with the classified operating room data, calculate the bandwidth requirements of each data stream in multiple surgical links, and adjust the bandwidth allocation priority to generate a real-time traffic allocation result;

[0010] S4: Based on the real-time traffic allocation result, according to the real-time update rate information of various data, combine the write delay, bandwidth occupancy ratio, and criticality weight to store the operating room data into multiple cache partitions to generate a data storage record;

[0011] S5: Call the data storage record, adjust the access rights of the data according to the timeliness of each type of operating room data in the database, and adjust the user permission level according to the type of medical staff to generate an access right management result.

[0012] As a further solution of the present invention, the surgical data classification result is specifically a surgical process decomposition record, an operating room data acquisition record, and a multi-link data set. The dynamic risk warning result includes a physiological parameter change rate, a risk trend direction, and a warning prompt message. The real-time traffic allocation result is specifically a data stream bandwidth priority, a data sampling frequency adjustment value, and an image data traffic allocation ratio. The data storage record includes a cache partition priority, a data write delay, and a bandwidth occupancy ratio. The access right management result is specifically a user permission level, data access timeliness, and a data right adjustment record.

[0013] As a further solution of the present invention, the steps of obtaining surgical plan information, decomposing the surgical process into multiple links, and classifying various operating room data collected in real time according to the surgical links to generate a surgical data classification result are specifically as follows:

[0014] S101: Obtain surgical plan information, decompose the surgical process into multiple links, including an incision stage, an operation stage, and a suture stage, to generate a surgical process decomposition result;

[0015] S102: Call the surgical process decomposition result, collect image data, surgical instrument operation data, and patient physiological parameters in the operating room data in real time, and synchronously record the link information and time stamp of each type of data to generate an operating room data set;

[0016] S103: Call the operating room data set, classify each type of operating room data according to the surgical link, and record the update rate of each type of data to generate a surgical data classification result.

[0017] As a further solution of the present invention, the steps of calling the surgical data classification result, obtaining the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data, calculating the physiological parameter change rate and trend direction, and real-time evaluating the surgical risk and sending a warning prompt to medical staff to generate a dynamic risk warning result are specifically as follows:

[0018] S201: Call the surgical data classification result, obtain the heart rate, blood pressure, blood oxygen, and respiratory rate in the patient's physiological data, detect the short-term change rate and cumulative change amplitude of each type of physiological data, and calculate the change rate of the physiological parameter to obtain a physiological data change characteristic value;

[0019] S202: Invoke the eigenvalue of the physiological data change, calculate the change rate of the physiological parameters according to the change rates and cumulative change amplitudes of heart rate, blood pressure, blood oxygen, and respiratory rate, identify the trend direction of the change rate, and establish the change trend information;

[0020] S203: Invoke the change trend information, calculate the surgical risk score in real time according to the change rate and trend direction of the physiological parameters, evaluate the risk level, and send a warning prompt message to medical staff to generate a dynamic risk warning result.

[0021] As a further solution of the present invention, the steps of invoking the dynamic risk warning result, combining the classified operating room data, calculating the bandwidth requirements of each data stream in multiple surgical procedures, and adjusting the bandwidth allocation priority to generate a real-time traffic allocation result are specifically as follows:

[0022] S301: Invoke the dynamic risk warning result, combine the classified operating room data, and calculate the bandwidth requirement values of each data in multiple surgical procedures according to the data volume, data transmission rate, and data stream occupancy ratio of each data in multiple surgical procedures to generate a data bandwidth requirement result;

[0023] S302: Invoke the data bandwidth requirement result, calculate the priority of each data stream in multiple surgical procedures according to the bandwidth requirement of each data to generate a bandwidth priority adjustment value;

[0024] S303: Invoke the bandwidth priority adjustment value, adjust the bandwidth allocation parameters of each surgical procedure according to the transmission priority of each data to generate a real-time traffic allocation result.

[0025] As a further solution of the present invention, the specific formula for calculating the bandwidth requirement value of each data in multiple procedures is:

[0026]

[0027] Calculate the bandwidth requirement value;

[0028] Among them, B p is the bandwidth requirement value of the p-th data in the surgical procedure, D pq is the data volume of the p-th data in the q-th surgical procedure, R pq is the data transmission rate of the p-th data in the q-th surgical procedure, S p is the actual data stream occupancy ratio of the p-th data, T p is the target data stream occupancy ratio of the p-th data, N is the total number of surgical procedures, p represents the serial number of the data type, and q represents the serial number of the surgical procedure.

[0029] As a further solution of the present invention, based on the real-time traffic allocation result, according to the real-time update rate information of various data, combined with the write latency, bandwidth occupancy ratio, and criticality weight, the step of storing the operating room data into multiple cache partitions and generating a data storage record is specifically as follows:

[0030] S401: Obtain the real-time traffic allocation result, and according to the real-time update rates of the image data, surgical instrument operation data, and patient physiological parameters in the operating room data, identify the update frequency, data stream change rate, and data transmission stability of each type of data, and obtain the real-time data update rate value;

[0031] S402: Invoke the real-time data update rate value, and according to the write latency, bandwidth occupancy ratio, and criticality weight of each type of data, calculate the storage priority coefficient of each data type to obtain a cache priority adjustment result;

[0032] S403: Invoke the cache priority adjustment result, and according to the storage priority of each type of data, store the operating room data into multiple cache partitions to generate a data storage record.

[0033] As a further solution of the present invention, the specific formula for calculating the storage priority coefficient of each data type is:

[0034]

[0035] Calculate the storage priority coefficient to obtain a cache priority adjustment result;

[0036] Among them, C represents the storage priority coefficient, W represents the criticality weight, B represents the bandwidth occupancy ratio, L represents the write latency, U a represents the a-th data update rate, μ U represents the average value of the data update rate, A represents the number of data updates, and a is the serial number of the data update.

[0037] As a further solution of the present invention, the step of invoking the data storage record, adjusting the access permission of the data according to the timeliness of each operating room data in the database, and adjusting the user permission level according to the type of medical staff to generate an access permission management result is specifically as follows:

[0038] S501: Invoke the data storage record, obtain the timeliness, data type, and storage location of each operating room data in the database, and adjust the access permission level required for the data according to the timeliness of the surgical data to obtain data permission level information;

[0039] S502: Invoke the data permission level information, and assign an access permission level to the medical staff according to the role type information of the medical staff to obtain user permission information;

[0040] S503: Invoke the user permission information, and based on the user's access request, adjust the access status of the data by comparing in real time the access permission levels required by the user and the operating room data, and generate an access permission management result.

[0041] On the other hand, a data processing system for a digital operating room is provided. This system is applied to the data processing method of a digital operating room and includes:

[0042] The real-time data classification module decomposes the surgical process into multiple links based on the surgical plan information, collects real-time image data, surgical instrument operation data, and patient physiological parameters, and classifies each type of data according to the link to generate a surgical data classification result;

[0043] The risk warning calculation module obtains the short-term change rate, cumulative change amplitude, and cross-signal correlation of multiple physiological data based on the surgical data classification result, calculates the change rate and trend direction of the physiological data, evaluates the surgical risk and sends a prompt message, and generates a dynamic risk warning result;

[0044] The data flow regulation module obtains the data volume of each data flow in multiple surgical links based on the dynamic risk warning result and combines it with the operating room data classification result, calculates the bandwidth requirements of each data flow, adjusts the bandwidth allocation priority of the data flow, and generates a real-time traffic allocation result;

[0045] The data partition storage module obtains the real-time update rate, write delay, bandwidth occupancy ratio, and criticality weight of each data type based on the real-time traffic allocation result, evaluates the storage priority of the data flow according to the update frequency, write delay value, and cache priority of the data, and stores the data in multiple cache partitions to generate a data storage record;

[0046] The access permission management module calculates and adjusts the access permission level of the data based on the data storage record according to the timeliness of each operating room data in the database, and assigns permission levels to medical staff in combination with the role type to generate an access permission management result.

[0047] The beneficial effects brought by the technical solution provided in the embodiments of the present invention at least include:

[0048] By decomposing the surgical process into multiple steps, precise classification of operating room data is achieved. Combining physiological data to dynamically evaluate surgical risks and sending early warning prompts to medical staff in a timely manner. By analyzing the bandwidth requirements of each data stream in different surgical steps, the bandwidth allocation priority is dynamically adjusted to improve the data transmission efficiency during the surgery. Adjusting the storage priority of data according to its storage and retrieval behavior to achieve optimal utilization of storage resources. Utilizing the timeliness of data to dynamically adjust data access permissions, achieving precise management and security control of data access permissions. Brief Description of the Drawings

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0050] Figure 1 It is a schematic diagram of the working process of the present invention;

[0051] Figure 2 It is a detailed flowchart of S1 of the present invention;

[0052] Figure 3 It is a detailed flowchart of S2 of the present invention;

[0053] Figure 4 It is a detailed flowchart of S3 of the present invention;

[0054] Figure 5 It is a detailed flowchart of S4 of the present invention;

[0055] Figure 6 It is a detailed flowchart of S5 of the present invention;

[0056] Figure 7 It is a system flowchart of the present invention. Detailed Embodiments

[0057] The following will describe the technical solutions in the present invention in conjunction with the drawings.

[0058] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "example" in the present invention should not be construed as more preferred or more advantageous than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either of the two can be selected.

[0059] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same. "Of", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same.

[0060] In the embodiments of the present invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, their intended meanings are the same.

[0061] To make the technical problems, technical solutions, and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0062] Please refer to Figure 1 , the present invention provides a technical solution, a data processing method for a digital operating room, including the following steps:

[0063] S1: Obtain surgical plan information, decompose the surgical process into multiple links, and classify various types of operating room data collected in real time according to the surgical links to generate a surgical data classification result;

[0064] S2: Call the surgical data classification result, obtain the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data, calculate the physiological parameter change rate and trend direction, evaluate the surgical risk in real time and send a warning prompt to medical staff to generate a dynamic risk warning result;

[0065] S3: Call the dynamic risk warning result, combine the classified operating room data, calculate the bandwidth requirements for each data stream in multiple surgical links, and adjust the bandwidth allocation priority to generate a real-time traffic allocation result;

[0066] S4: Based on the real-time traffic allocation result, according to the real-time update rate information of various data, combine the write delay, bandwidth occupancy ratio, and criticality weight, and store the operating room data into multiple cache partitions to generate a data storage record;

[0067] S5: Call the data storage record, adjust the access rights of the data according to the timeliness of each operating room data in the database, and adjust the user permission level according to the type of medical staff to generate an access permission management result.

[0068] The specific results of the surgical data classification are the surgical process decomposition record, the operating room data collection record, and the multi-link data set. The dynamic risk warning results include the physiological parameter change rate, the risk trend direction, and the warning prompt information. The real-time traffic allocation results are specifically the data stream bandwidth priority, the data sampling frequency adjustment value, and the imaging data traffic allocation ratio. The data storage record includes the cache partition priority, the data write delay, and the bandwidth occupancy ratio. The access permission management results are specifically the user permission level, the data access timeliness, and the data permission adjustment record.

[0069] Please refer to Figure 2 , obtain the surgical plan information, decompose the surgical process into multiple links, and classify various types of operating room data collected in real time according to the surgical links. The specific steps for generating the surgical data classification results are as follows:

[0070] S101: Obtain the surgical plan information, decompose the surgical process into multiple links, including the incision stage, the operation stage, and the suture stage, and generate the surgical process decomposition result;

[0071] Obtain the surgical plan information, decompose the surgical process into multiple links, including the incision stage, the operation stage, and the suture stage. According to the surgical type, surgical steps, and expected duration in the surgical plan information, decompose the surgery into specific operation links. For example, for laparoscopic surgery, the surgical process is divided into the incision stage, the operation stage, and the suture stage. Each link sets specific operation times according to the surgical steps. For example, the incision stage is expected to be 10 minutes, the operation stage is 30 minutes, and the suture stage is 20 minutes. During the decomposition process, bind each surgical link to the corresponding surgical instruments, imaging devices, and monitoring devices, and set the activation status of each device in a specific link. For example, activate the imaging device and cutting instrument in the incision stage, activate the laparoscope and monitoring instrument in the operation stage, and activate the suture device and imaging device in the suture stage. By associating the device status with the surgical process, realize the automatic switching of the device status. According to the time preset of each surgical link, the system compares the expected time of each link with the actual operation time. For example, in the incision stage, when the system monitors that the imaging device is turned on for more than 10 minutes, it automatically determines that the incision stage is delayed, automatically adjusts the remaining time to the operation stage, and updates the surgical progress information, and calculates the time difference value of the surgical link:

[0072] ΔT = T a - T e ;

[0073] Among them, ΔT is the time difference value of the surgical link (minutes), T a is the actual operation time (minutes), and T e is the expected operation time (minutes).

[0074] Assume that the expected operation time for the incision stage is 10 minutes, and the actual operation time is 15 minutes. Then the time difference value is calculated as follows:

[0075] ΔT = 15 - 10 = 5;

[0076] The time difference value is 5 minutes, indicating that the incision stage exceeded the time limit by 5 minutes. The system adjusted the 5 - minute delay to the next operation stage to obtain the surgical process decomposition result.

[0077] S102: Invoke the surgical process decomposition result, and collect in real - time the image data, surgical instrument operation data, and patient physiological parameters in the operating room data. Synchronously record the link information and time stamp of each type of data to generate an operating room data set;

[0078] Invoke the surgical process decomposition result, and collect in real - time the image data, surgical instrument operation data, and patient physiological parameters in the operating room data. Synchronously record the link information and time stamp of each type of data. When collecting image data, use the imaging device to collect the video stream of the surgical area at a rate of 30 frames per second. Bind each frame of the image to the current surgical link (such as the incision stage, operation stage, suture stage), and record the time stamp of image collection. For example, the time stamps of the image frames in the incision stage are from T1 to T3000 (the time interval between each frame is 0.033 seconds). For the surgical instrument operation data, through the sensor connected to the surgical instrument, collect the movement trajectory, usage frequency, and force data of the instrument. For example, during the operation stage, it is monitored that the movement trajectory of the scalpel in the XYZ - axis coordinate system is from (10, 15, 20) to (30, 25, 40), record the usage frequency as 5 times per minute, and the force as 10 Newtons. When collecting patient physiological parameters, use the physiological monitoring device to obtain data such as heart rate, blood pressure, and blood oxygen in real - time. For example, record the heart rate as 80 beats per minute, the blood pressure as 120 / 80 mmHg, and the blood oxygen as 98%. Synchronously record the surgical link and time stamp when all data is collected, and calculate the total amount of collected image data. The formula is as follows:

[0079] N’ = f × t;

[0080] Where, N’ is the total number of collected image data frames (frames), f is the imaging device collection frame rate (frames / second), and t is the surgical link duration (seconds).

[0081] Assume that the imaging device collection frame rate is 30 frames per second, and the duration of the incision stage is 10 minutes (600 seconds). Then the total amount of image data is:

[0082] N’ = 30 × 600 = 18000;

[0083] The total amount of image data collected in the incision stage is 18000 frames. Synchronously record the surgical link and time stamp when all data is collected to obtain the operating room data set.

[0084] S103: Invoke the operating room dataset, classify each type of operating room data according to the surgical procedures, record the update rate of each type of data, and generate the surgical data classification result.

[0085] Invoke the operating room dataset, classify each type of operating room data according to the surgical procedures, record the update rate of each type of data, match the data with the corresponding surgical procedures (incision stage, operation stage, suture stage) based on the image data, surgical instrument operation data, and patient physiological parameters in the operating room dataset. During the classification process, compare the timestamp of the image data with the time period of the surgical procedure. For example, the image data within the incision stage (T1 to T3000) is classified as incision data, and the image data in the operation stage (T3001 to T6000) is classified as operation data. For the surgical instrument operation data, judge by the operation frequency and the task requirements of the surgical procedure. For example, the usage frequency of the scalpel in the operation stage is 5 times per minute, while the operation frequency of the suture device is monitored to be 3 times per minute in the suture stage. Classify the operation data in different stages into the corresponding datasets. For the patient physiological parameters, classify the heart rate, blood pressure, and blood oxygen data according to the surgical procedure through the timestamp recorded by the physiological monitoring device. For example, the heart rate data recorded in the incision stage is 75 to 80 beats per minute, the blood pressure is 115 / 75 to 120 / 80 mmHg, and the blood oxygen is 97% to 98%. During the classification process, the system simultaneously calculates the update rate of each type of data, and the formula is as follows:

[0086]

[0087] where R is the data update rate (times / second or frames / second), N is the total amount of data (times or frames), and t is the data acquisition time (seconds).

[0088] Assume that 150 operations of the surgical instrument operation data are collected in the operation stage, and the duration of the operation stage is 30 minutes (1800 seconds). Then the update rate of the operation data is:

[0089]

[0090] The update rate of the surgical instrument operation data is 0.083 times / second (about 5 times per minute). Record all the data classification results together with the update rate to generate the surgical data classification result.

[0091] Please refer to Figure 3 , the steps of invoking the surgical data classification result, obtaining the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data, calculating the change rate and trend direction of physiological parameters, and real-time evaluating the surgical risk and sending a warning prompt to medical staff to generate the dynamic risk warning result are specifically as follows:

[0092] S201: Invoke the classified result of the surgical data to obtain the heart rate, blood pressure, blood oxygen, and respiratory rate in the patient's physiological data. Detect the short-term change rate and cumulative change amplitude of each physiological data, calculate the change rate of the physiological parameters, and obtain the change characteristic value of the physiological data.

[0093] Invoke the classified result of the surgical data to obtain the heart rate, blood pressure, blood oxygen, and respiratory rate in the patient's physiological data. Real-time collect the numerical changes of each physiological parameter through a physiological monitoring device, record the time stamp and value of each collection. For example, the heart rate data is updated every minute during the operation, and the collected data sequence is [80, 82, 85, 87] times / minute. Calculate the short-term change rate for each data sequence. The short-term change rate is obtained by calculating the ratio of the change amount between two adjacent collections to the time difference. The formula is as follows:

[0094]

[0095] Where, V is the short-term change rate (unit / second), ΔS is the data change amount (unit), ΔT is the time interval (second). For example, between the heart rate data [80, 82], the time interval is 60 seconds, then the change rate is:

[0096]

[0097] The short-term change rate is 0.033 times / second. After recording the change rates of all data, further calculate the cumulative change amplitude. The cumulative change amplitude is the difference between the current value and the initial value. For example, if the heart rate increases from 80 times / minute to 87 times / minute, then the cumulative change amplitude is:

[0098] ΔS = 87 - 80 = 7;

[0099] The cumulative change amplitude is 7 times / minute. Similarly calculate for blood pressure, blood oxygen, and respiratory rate. The system records the change rates and cumulative change amplitudes of all data, calculates the change rate of each physiological parameter. The change rate is obtained through weighted calculation of the short-term change rate and the cumulative change amplitude. The weighting coefficients are set according to the importance of each physiological parameter. For example, the heart rate weight is 0.4, the blood pressure weight is 0.3, the blood oxygen weight is 0.2, and the respiratory rate weight is 0.1. The change rate calculation formula is:

[0100] C = w1V1 + w2V2 + w3V3 + w4V4;

[0101] Among them, C is the physiological parameter change rate, w1, w2, w3, w4 are the weights of heart rate, blood pressure, blood oxygen, and respiratory rate respectively, and V1, V2, V3, V4 are the corresponding short-term change rates. For example, the heart rate change rate is 0.033 beats per second, the blood pressure change rate is 0.01 mmHg per second, the blood oxygen change rate is 0.001%, and the respiratory rate change rate is 0.002 breaths per second. Then the change rate is calculated as follows:

[0102] C = 0.4×0.033 + 0.3×0.01 + 0.2×0.001 + 0.1×0.002 = 0.015;

[0103] The change rate is 0.015, and the physiological data change characteristic value is obtained.

[0104] S202: Call the physiological data change characteristic value, calculate the change rate of the physiological parameter according to the change rate and cumulative change amplitude of the heart rate, blood pressure, blood oxygen, and respiratory rate, identify the trend direction of the change rate, and establish the change trend information;

[0105] Call the physiological data change characteristic value, calculate the change rate of the physiological parameter according to the change rate and cumulative change amplitude of the heart rate, blood pressure, blood oxygen, and respiratory rate, identify the trend direction of the change rate. During the change rate calculation process, judge the trend direction according to the magnitude of the change rate values at two consecutive moments. For example, the change rate at the previous moment is 0.015, and the change rate at the next moment is 0.02. By comparing the change rate values, it is judged that the change rate shows an upward trend. The trend direction is realized by calculating the increment of the change rate. The calculation formula is as follows:

[0106] D = C t - C t；1 ;

[0107] Among them, D is the change rate increment, C t is the current change rate, and C t；1 is the change rate at the previous moment. For example, the current change rate is 0.02, and the previous moment is 0.015. Then the increment is:

[0108] D = 0.02 - 0.015 = 0.005;

[0109] When the increment is 0.005 and the increment is greater than 0, it is judged as an upward trend; when it is less than 0, it is judged as a downward trend; when it is equal to 0, it is judged as a stable trend. After obtaining the trend direction, associate the change rate of the physiological parameter with the trend direction to establish the change trend information.

[0110] S203: Call the change trend information, calculate the surgical risk score in real time according to the change rate and trend direction of the physiological parameter, evaluate the risk level, and send a warning prompt message to medical staff to generate a dynamic risk warning result;

[0111] Call the change trend information, calculate the surgical risk score in real time according to the change rate and trend direction of physiological parameters, evaluate the risk level, and send warning messages to medical staff. During the calculation of the surgical risk score, different risk coefficients are assigned according to the change rate and trend direction of each physiological parameter. For example, the risk coefficient of heart rate change rate is 1.5, blood pressure is 1.2, blood oxygen is 1.8, and respiratory rate is 1.1. The risk score is calculated by multiplying the change rate by the risk coefficient. The calculation formula is as follows:

[0112]

[0113] Among them, S is the surgical risk score, C i is the change rate of the i-th physiological parameter, k i is the corresponding risk coefficient, and n is the number of types of physiological parameters. For example, if the heart rate change rate is 0.02 and the risk coefficient is 1.5, the risk score calculation is as follows:

[0114] S = 0.02 × 1.5 + 0.01 × 1.2 + 0.001 × 1.8 + 0.002 × 1.1 = 0.036;

[0115] The risk score is 0.036. The risk level is divided according to the size of the risk score. For example, a score lower than 0.02 is a low risk, 0.02 to 0.05 is a medium risk, and greater than 0.05 is a high risk. When the risk level reaches medium risk and above, the system sends a warning message to medical staff through the alarm device in the operating room to generate a dynamic risk warning result.

[0116] Please refer to Figure 4 , call the dynamic risk warning result, combine the classified operating room data, calculate the bandwidth requirements of each data stream in multiple surgical procedures, and adjust the bandwidth allocation priority to generate the real-time traffic allocation result. The specific steps are as follows:

[0117] S301: Call the dynamic risk warning result, combine the classified operating room data, and calculate the bandwidth requirement value of each data in multiple surgical procedures according to the data volume, data transmission rate, and data stream occupancy ratio of each data in multiple surgical procedures to generate a data bandwidth requirement result;

[0118] The specific formula for calculating the bandwidth requirement value of each data in multiple procedures is:

[0119]

[0120] Calculate the bandwidth requirement value;

[0121] Among them, B p is the bandwidth requirement value of the p-th data in the surgical procedure, Dpq is the data volume of the p-th type of data in the q-th surgical procedure, R pq is the data transmission rate of the p-th type of data in the q-th surgical procedure, S p is the actual data stream occupancy ratio of the p-th type of data, T p is the target data stream occupancy ratio of the p-th type of data. N is the total number of surgical procedures, p represents the serial number of the data type, and q represents the serial number of the surgical procedure.

[0122] Formula:

[0123]

[0124] Detailed explanation of the formula and the derivation process of formula calculation:

[0125] This formula is used to calculate the bandwidth requirement value of each type of data in multiple surgical procedures, and the obtained result is used to dynamically adjust the real-time traffic allocation of surgical data;

[0126] Meaning and setting values of parameters:

[0127] B p is the bandwidth requirement value of the p-th type of data in the surgical procedure, unit: MB / s, representing the actual bandwidth requirements of different types of data during the surgical process, such as imaging data, surgical instrument operation data, and patient physiological parameter data;

[0128] D pq is the data volume of the p-th type of data in the q-th surgical procedure, unit: MB. Assume the imaging data volume is 500 MB, the surgical instrument operation data volume is 300 MB, and the patient physiological parameter data volume is 100 MB;

[0129] R pq is the data transmission rate of the p-th type of data in the q-th surgical procedure, unit: MB / s. The imaging data transmission rate is 20 MB / s, the surgical instrument operation data is 10 MB / s, and the patient physiological parameter data is 5 MB / s;

[0130] S p is the actual data stream occupancy ratio of the p-th type of data, unit: %, the imaging data is 30%, the surgical instrument operation data is 20%, and the patient physiological parameter data is 10%;

[0131] T p is the target data stream occupancy ratio of the p-th type of data, unit: %, the imaging data target is 25%, the surgical instrument operation data target is 15%, and the patient physiological parameter data target is 10%;

[0132] N is the total number of surgical procedures, assume it is 3, such as the incision stage, the operation stage, and the suture stage;

[0133] Substitute the parameters into the formula for calculation:

[0134] Calculation of the bandwidth requirement value of the image data:

[0135]

[0136] Calculation of the bandwidth requirement value of the surgical instrument operation data:

[0137]

[0138] Calculation of the bandwidth requirement value of the patient's physiological parameter data:

[0139]

[0140] The bandwidth requirement of the image data is 505 MB / s, the bandwidth requirement of the surgical instrument operation data is 305 MB / s, and the bandwidth requirement of the patient's physiological parameter data is 100 MB / s. The bandwidth requirement value is used to dynamically adjust the data flow priority in the surgical procedure in the subsequent steps to generate the data bandwidth requirement result.

[0141] S302: Invoke the data bandwidth requirement result, and calculate the priority of each data flow in multiple surgical procedures according to the bandwidth requirement of each type of data to generate a bandwidth priority adjustment value;

[0142] Invoke the data bandwidth requirement result, calculate the priority of each data flow in multiple surgical procedures according to the bandwidth requirement of each type of data, obtain the bandwidth requirement values of the image data, surgical instrument operation data, and patient's physiological parameter data in the surgical procedure, and assign priorities to each data flow according to the three main procedures of incision, operation, and suture in the surgical process. The priority is calculated based on the bandwidth requirement value and the importance weight of the data type. The weights are set as 0.5 for image data, 0.3 for surgical instrument operation data, and 0.2 for patient's physiological parameter data. The priority calculation formula is as follows:

[0143] P = W × B;

[0144] Among them, P is the priority of the data flow, W is the weight of the data type, and B is the bandwidth requirement value. For example, if the weight of the image data is 0.5 and the bandwidth requirement value is 0.15 MB / s, then the priority of the image data is:

[0145] P = 0.5 × 0.15 = 0.075;

[0146] The priority is 0.075. By calculating the surgical instrument operation data and the patient's physiological parameter data in the same way, the bandwidth priority values of each type of data in each surgical procedure are obtained, and a bandwidth priority adjustment value is generated.

[0147] S303: Invoke the bandwidth priority adjustment value, and adjust the bandwidth allocation parameters for each surgical procedure according to the transmission priority of each type of data to generate a real-time traffic allocation result;

[0148] Invoke the bandwidth priority adjustment value, and adjust the bandwidth allocation parameters for each surgical procedure according to the transmission priority of each type of data. Obtain the priority values of image data, surgical instrument operation data, and patient physiological parameter data in the three surgical procedures of incision, operation, and suture. Calculate the bandwidth allocation ratio of each data stream in the surgical procedure. The bandwidth allocation ratio is calculated through the priority value and the total bandwidth of the surgical procedure. The total bandwidth of the surgical procedure is 500MB / s. The bandwidth allocation ratio calculation formula is as follows:

[0149] R = P × T;

[0150] Where, R is the bandwidth allocation ratio (MB / s), P is the priority of the data stream, and T is the total bandwidth of the surgical procedure. For example, if the priority of the image data is 0.075 and the total bandwidth is 500MB / s, then the bandwidth allocation ratio is:

[0151] R = 0.075 × 500 = 37.5;

[0152] The bandwidth allocation ratio is 37.5MB / s. Calculate it in the same way for the surgical instrument operation data and patient physiological parameter data. Apply the bandwidth allocation ratio to the network resource allocation in the operating room, and dynamically adjust the network bandwidth allocation parameters according to the actual bandwidth requirements of each surgical procedure to generate a real-time traffic allocation result.

[0153] Please refer to Figure 5 , based on the real-time traffic allocation result, according to the real-time update rate information of multiple types of data, combined with the write delay, bandwidth occupancy ratio, and criticality weight, the steps of storing the operating room data into multiple cache partitions to generate a data storage record are specifically as follows:

[0154] S401: Obtain the real-time traffic allocation result, and identify the update frequency, data stream change rate, and data transmission stability of each type of data according to the real-time update rates of the image data, surgical instrument operation data, and patient physiological parameters in the operating room data to obtain the data real-time update rate value;

[0155] Obtain the real-time traffic allocation result. According to the real-time update rates of the image data, surgical instrument operation data, and patient physiological parameters in the operating room data, first obtain the frame rate and transmission rate of the image data. For example, if the frame rate of the image data is 30 frames per second and the amount of data per frame is 500 KB, then the data update rate is 30×500 KB = 15000 KB / s. For the surgical instrument operation data, assume the operation frequency is 50 times per second and the amount of data per operation is 20 KB, then the real-time update rate of the operation data is 50×20 KB = 1000 KB / s. For the patient physiological parameter data, for example, the heart rate data is updated 10 times per second and the amount of data per update is 5 KB, then the real-time update rate of the physiological data is 10×5 KB = 50 KB / s. Calculate the update frequency, data stream change rate, and data transmission stability of each type of data based on these data. The data update frequency is the number of updates per unit time of the data. The data stream change rate is the change speed of the data volume. The data transmission stability is calculated by the fluctuation amplitude of the data traffic. The formula for calculating the data transmission stability is as follows:

[0156]

[0157] where S is the data transmission stability, σ d is the standard deviation of the data traffic, and μ d is the average value of the data traffic. For example, the traffic of the image data within 10 seconds is 14.5, 15, 15.2, 14.8, 15.1, 15, 14.9, 15.3, 14.7, 15 MB / s respectively. The average value is 15 MB / s and the standard deviation is 0.2 MB / s. Then the transmission stability of the image data is:

[0158]

[0159] After calculating the update frequency, change rate, and transmission stability of the image data, surgical instrument operation data, and patient physiological parameter data respectively, compare and judge these data to obtain the real-time update rate value of each type of data, and generate the real-time update rate value of the data.

[0160] S402: Call the real-time update rate value of the data, and calculate the storage priority coefficient of each type of data according to the write delay, bandwidth occupancy ratio, and criticality weight of each type of data to obtain the cache priority adjustment result;

[0161] The specific formula for calculating the storage priority coefficient of each type of data is:

[0162]

[0163] Calculate the storage priority coefficient to obtain the cache priority adjustment result;

[0164] Among them, C represents the storage priority coefficient, W represents the criticality weight, B represents the bandwidth occupancy ratio, L represents the write latency, U a represents the data update rate at the a-th time, μ U represents the average value of the data update rate, A represents the number of data updates, and a is the sequence number of the data update.

[0165] Formula:

[0166]

[0167] Detailed explanation of the formula and the derivation process of the formula calculation:

[0168] The formula is used to calculate the storage priority coefficient of the operating room data, and the result is used to determine the storage priority of the data in the cache partition to optimize the data access efficiency;

[0169] Meaning and setting values of parameters:

[0170] W is the criticality weight, assumed to be 0.8, which reflects the influence degree of this data on decision-making during the operation;

[0171] B is the bandwidth occupancy ratio, assumed to be 40 (MB / s), which represents the occupancy rate of the current data stream in the total bandwidth;

[0172] L is the write latency, assumed to be 0.5 (seconds);

[0173] U a is the data update rate at the a-th time, and the set values are 35, 42, 38, 40, 44 (MB / s);

[0174] μ U is the average value of the data update rate,

[0175] A is the number of data updates, assumed to be 5, which represents the total number of data updates during the data acquisition period.

[0176] Substitute the parameters into the formula for calculation:

[0177]

[0178] C = 0.8·80 + 1.62 = 64 + 1.62 = 65.62;

[0179] The storage priority coefficient is 65.62, indicating that this data has a high storage priority during the operation and is suitable for being allocated to the high-priority cache partition to improve the data reading and writing speeds during the operation and ensure the real-time performance and stability of the key data.

[0180] S403: Call the cache priority adjustment result, and store the operating room data into multiple cache partitions according to the storage priority of each type of data, generating a data storage record;

[0181] Call the cache priority adjustment result, and store the operating room data into multiple cache partitions according to the storage priority of each type of data. First, assuming that the cache partitions are divided into a high-priority cache area (write speed: 500MB / s), a medium-priority cache area (write speed: 300MB / s), and a low-priority cache area (write speed: 100MB / s) according to the storage priority coefficients of image data, surgical instrument operation data, and patient physiological parameter data, preferentially allocate the data with a higher priority coefficient to the high-priority cache area. For example, the storage priority coefficient of image data is 15, the priority coefficient of surgical instrument operation data is 10, and the priority coefficient of physiological parameter data is 5. Allocate the image data to the high-priority cache area, the surgical instrument operation data to the medium-priority cache area, and the physiological parameter data to the low-priority cache area. Dynamically adjust the cache partitions during the data allocation process, re-evaluate the cache requirements of the data according to the update frequency and change rate of the data, and adjust the storage priority of the cache partitions in real time, generating a data storage record.

[0182] Please refer to Figure 6 , the steps of calling the data storage record, adjusting the access rights of the data according to the timeliness of each type of operating room data in the database, and adjusting the user privilege level according to the type of medical staff, and generating an access right management result are specifically as follows:

[0183] S501: Call the data storage record, obtain the timeliness, data type, and storage location of each type of operating room data in the database, and adjust the access right level required for the data according to the timeliness of the surgical data, obtaining data privilege level information;

[0184] Call the data storage record, obtain the timeliness, data type, and storage location of each type of operating room data in the database. First, extract the storage records of image data, surgical instrument operation data, and patient physiological parameter data from the database. The timeliness of image data is set to be valid within 24 hours, the timeliness of surgical instrument operation data is within 1 week, and the timeliness of patient physiological parameter data is within 1 month. Obtain the data type, where the image data is video data, the surgical instrument operation data is log data, and the patient physiological parameter data is real-time monitoring data. The storage locations are cache area A, cache area B, and cache area C respectively. Adjust the access right level of the data according to the data timeliness, and set the privilege level thresholds for different timeliness data. For example, the data privilege level within 24 hours is 1, the data privilege level within 1 week is 2, the data privilege level within 1 month is 3, and the data privilege level exceeding 1 month is 4. The formula for calculating the data privilege level is as follows:

[0185] P d = T d ·W d ;

[0186] Wherein, P d is the data permission level, T d is the data timeliness (in days), W d is the data type weight (0.5 for image data, 0.3 for operation data, 0.2 for physiological parameter data). For example, if the timeliness of image data is 1 day, the data type is video data, and the weight is 0.5, then the permission level of the image data is:

[0187] P d = 1·0.5 = 0.5;

[0188] Similarly, calculate the permission levels of surgical instrument operation data and patient physiological parameter data, screen out the data with the highest permission level, call the permission level information of each data, and by comparing the permission level values of each data, assign the data permission levels from 1 to 4 in sequence to obtain the data permission level information.

[0189] S502: Call the data permission level information, and according to the role type information of the medical staff, assign an access permission level to the medical staff to obtain user permission information;

[0190] Call the data permission level information, and according to the role type information of the medical staff, assign an access permission level to the medical staff. First, obtain the role information of the medical staff, such as the surgeon in charge, surgical assistant, anesthesiologist, nurse, and equipment maintenance personnel, and set the permission level thresholds for different roles. For example, the permission level of the surgeon in charge is 1, the surgical assistant is 2, the anesthesiologist is 2, the nurse is 3, and the equipment maintenance personnel is 4. Calculate the access permission level of the medical staff according to the role type information, and set the permission level calculation formula as follows:

[0191] P u = R u + S u ;

[0192] Wherein, P u is the user permission level, R u is the role type weight (0.5 for the surgeon in charge, 0.3 for the surgical assistant, 0.3 for the anesthesiologist, 0.2 for the nurse, 0.1 for the equipment maintenance personnel), S u is the role priority (1 for the surgeon in charge, 2 for the surgical assistant, 2 for the anesthesiologist, 3 for the nurse, 4 for the equipment maintenance personnel). For example, if the role type weight of the surgeon in charge is 0.5 and the role priority is 1, then the permission level of the surgeon in charge is:

[0193] P u = 0.5 + 1 = 1.5;

[0194] Similarly, calculate the permission levels of other medical staff. By comparing the user permission level and the data permission level, allocate user permission information to obtain user permission information.

[0195] S503: Invoke the user permission information. According to the user's access request, by comparing the access permission levels required by the user and the operating room data in real time, adjust the access status of the data to generate an access permission management result;

[0196] Invoke the user permission information. According to the user's access request, by comparing the access permission levels required by the user and the operating room data in real time. First, receive the access requests of medical staff. For example, the surgeon requests access to imaging data, the nurse requests access to patient physiological parameter data, and the equipment maintenance staff requests access to surgical instrument operation data. According to the permission levels of the imaging data, operation data, and physiological parameter data (for example, the imaging data is 1, the operation data is 2, and the physiological parameter data is 3), compare with the permission levels of the medical staff. For example, the permission level of the surgeon is 1 and can access the imaging data. The permission level of the nurse is 3, and the permission level of the physiological parameter data is 3, so the nurse can access the physiological parameter data. The permission level of the equipment maintenance staff is 4, and the permission level of the surgical instrument operation data is 2, so the equipment maintenance staff cannot access the operation data. By setting access permission rules, adjust the access status of the data in real time, push the data that allows access to the terminal of the medical staff, and prohibit access and record logs for the data that does not meet the permission level to generate an access permission management result.

[0197] Please refer to Figure 7 , a data processing system for a digital operating room. The data processing system for a digital operating room is used to execute the above-mentioned data processing method for a digital operating room. The system includes:

[0198] The real-time data classification module decomposes the surgical process into multiple links based on the surgical plan information, collects imaging data, surgical instrument operation data, and patient physiological parameters in real time, and classifies each type of data according to the link to generate a surgical data classification result;

[0199] The risk warning calculation module obtains the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data based on the surgical data classification result, calculates the change rate and trend direction of the physiological data, evaluates the surgical risk and sends a prompt message to generate a dynamic risk warning result;

[0200] Based on the dynamic risk warning result and combined with the operating room data classification result, the data traffic regulation module obtains the data volume of each data stream in multiple surgical procedures, calculates the bandwidth requirements of each data stream, adjusts the bandwidth allocation priority of the data stream, and generates a real-time traffic allocation result;

[0201] Based on the real-time traffic allocation result, the data partition storage module obtains the real-time update rate, write latency, bandwidth occupancy ratio, and criticality weight of each data type, evaluates the storage priority of the data stream according to the update frequency, write latency value, and cache priority of the data, and stores the data in multiple cache partitions to generate a data storage record;

[0202] Based on the data storage record, the access permission management module calculates and adjusts the access permission level of the data according to the timeliness of each operating room data in the database, and assigns permission levels to medical staff in combination with the role type to generate an access permission management result.

[0203] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other arbitrary combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0204] It should be understood that the term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Among them, A and B can be singular or plural. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context.

[0205] In the present invention, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or a similar expression means any combination of these items, including any combination of single item(s) or plural item(s). For example, at least one of a, b, or c may represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c may be single or plural.

[0206] It should be understood that in various embodiments of the present invention, the magnitudes of the sequence numbers of the above - mentioned processes do not imply the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0207] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0208] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the devices, apparatuses, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0209] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in an electrical, mechanical, or other form.

[0210] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0211] In addition, in each embodiment of the present invention, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0212] If the above-mentioned function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0213] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A data processing method for a digital operating room, characterized in that: The method comprises: Obtain surgical plan information, decompose the surgical process into multiple links, and classify various operating room data collected in real time according to the surgical links to generate surgical data classification results; Call the surgical data classification results, obtain the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data, calculate the change rate and trend direction of physiological parameters, evaluate the surgical risks in real time, send early warning prompts to medical personnel, and generate dynamic risk early warning results; The dynamic risk warning result is called, combined with the classified operating room data, to calculate the bandwidth requirements of each data flow in multiple surgical links, and the bandwidth allocation priority is adjusted to generate a real-time traffic allocation result; Based on the real-time traffic distribution result, according to the real-time update rate information of multiple data, combined with write latency, bandwidth occupancy ratio, and criticality weight, the operating room data is stored in multiple cache partitions to generate data storage records; The data storage record is called, and the access rights to the data are adjusted according to the timeliness of each operating room data in the database, and the user authority level is adjusted according to the type of medical staff to generate access rights management results.

2. The data processing method for a digital operating room according to claim 1, characterized in that: The surgical data classification results specifically include surgical process decomposition records, operating room data collection records, and multi-link data sets; the dynamic risk warning results include physiological parameter change rates, risk trend directions, and warning prompt information; the real-time traffic allocation results specifically include data stream bandwidth priority, data sampling frequency adjustment value, and image data traffic allocation ratio; the data storage records include cache partition priority, data write delay, and bandwidth occupancy ratio; the access permission management results specifically include user permission levels, data access timeliness, and data permission adjustment records.

3. The data processing method for a digital operating room according to claim 1, characterized in that: Obtain surgical plan information, decompose the surgical process into multiple links, and classify the various operating room data collected in real time according to the surgical links. The specific steps for generating surgical data classification results are as follows: Obtain surgical plan information, decompose the surgical process into multiple stages, including the incision stage, operation stage, and suturing stage, and generate surgical process decomposition results; The surgical process decomposition result is called to collect the image data, surgical instrument operation data, and patient physiological parameters in the operating room data in real time, and the link information and timestamp of each data are synchronously recorded to generate an operating room data set; The operating room data set is called, each type of operating room data is classified according to the surgical link, and the update rate of each type of data is recorded to generate a surgical data classification result.

4. The data processing method for a digital operating room according to claim 1, characterized in that: The steps of calling the surgical data classification results, obtaining the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data, calculating the change rate and trend direction of physiological parameters, assessing surgical risks in real time and sending early warning prompts to medical personnel, and generating dynamic risk early warning results are as follows: Calling the surgical data classification result, obtaining the heart rate, blood pressure, blood oxygen, and respiratory rate in the patient's physiological data, detecting the short-term change rate and cumulative change amplitude of each physiological data, calculating the change rate of the physiological parameter, and obtaining the physiological data change characteristic value; Calling the physiological data change characteristic value, calculating the change rate of the physiological parameters according to the change rate and cumulative change amplitude of the heart rate, blood pressure, blood oxygen, and respiratory rate, identifying the change rate trend direction, and establishing the change trend information; The change trend information is called, and the surgical risk score is calculated in real time according to the change rate and trend direction of the physiological parameters, the risk level is evaluated, and early warning information is sent to medical personnel to generate dynamic risk warning results.

5. The data processing method for a digital operating room according to claim 1, characterized in that: The steps of calling the dynamic risk warning result, combining the classified operating room data, calculating the bandwidth requirements of each data flow in multiple surgical links, and adjusting the bandwidth allocation priority to generate the real-time traffic allocation result are as follows: The dynamic risk warning result is called, combined with the classified operating room data, and according to the data volume, data transmission rate, and data flow occupancy ratio of each data in multiple surgical links, the bandwidth requirement value of each data in multiple links is calculated to generate a data bandwidth requirement result; Calling the data bandwidth requirement result, calculating the priority of each data flow in multiple surgical links according to the bandwidth requirement of each data, and generating a bandwidth priority adjustment value; The bandwidth priority adjustment value is called, and the bandwidth allocation parameters of each surgical link are adjusted according to the transmission priority of each data to generate a real-time traffic allocation result.

6. The data processing method for a digital operating room according to claim 5, characterized in that: The specific formula for calculating the bandwidth requirement value of each data in multiple links is: Calculate bandwidth requirement value; Among them, B p is the bandwidth requirement of the p-th data in the surgical process, D pq is the amount of data of the pth type of data in the qth surgical session, R pq is the data transmission rate of the p-th data in the q-th surgical session, S p is the actual data flow occupancy ratio of the pth data, T p is the target data flow occupancy ratio of the pth type of data, N is the total number of surgical steps, p represents the sequence number of the data type, and q represents the sequence number of the surgical step.

7. The data processing method for a digital operating room according to claim 1, characterized in that: Based on the real-time traffic distribution result, according to the real-time update rate information of multiple data, combined with write delay, bandwidth occupancy ratio, and critical weight, the operating room data is stored in multiple cache partitions, and the steps of generating data storage records are specifically as follows: Obtain the real-time traffic distribution result, and identify the update frequency, data flow change rate, and data transmission stability of each type of data according to the real-time update rate of the image data, surgical instrument operation data, and patient physiological parameters in the operating room data, and obtain the real-time update rate value of the data; The real-time update rate value of the data is called, and according to the write delay, bandwidth occupancy ratio, and criticality weight of each data type, the storage priority coefficient of each data type is calculated to obtain a cache priority adjustment result; The cache priority adjustment result is called, and the operating room data is stored in multiple cache partitions according to the storage priority of each data to generate a data storage record.

8. The data processing method for a digital operating room according to claim 7, characterized in that: The specific formula for calculating the storage priority coefficient of each data type is: Calculate the storage priority coefficient and obtain the cache priority adjustment result; Among them, C represents the storage priority coefficient, W represents the criticality weight, B represents the bandwidth usage ratio, L represents the write latency, and U represents the storage priority coefficient. a represents the ath data update rate, μ U Represents the average value of the data update rate, A represents the number of data updates, and a is the sequence number of the data update.

9. The data processing method for a digital operating room according to claim 1, characterized in that: The steps of calling the data storage record, adjusting the access rights to the data according to the timeliness of each operating room data in the database, and adjusting the user authority level according to the type of medical staff, and generating the access rights management result are as follows: Call the data storage record to obtain the timeliness, data type, and storage location of each operating room data in the database, adjust the access permission level required for the data according to the timeliness of the surgical data, and obtain data permission level information; Calling the data permission level information, assigning access permission levels to medical personnel according to the role type information of the medical personnel, and obtaining user permission information; The user authority information is called, and according to the user's access request, the access status of the data is adjusted by comparing the access authority level required by the user and the operating room data in real time to generate an access authority management result.

10. A data processing system for a digital operating room, characterized in that: According to the data processing method of a digital operating room according to any one of claims 1 to 9, the system comprises: The real-time data classification module decomposes the surgical process into multiple links based on the surgical plan information, collects image data, surgical instrument operation data, and patient physiological parameters in real time, and classifies each type of data according to the link to generate surgical data classification results; The risk warning calculation module obtains the short-term change rate, cumulative change amplitude, and cross-signal correlation of various physiological data based on the surgical data classification results, calculates the change rate and trend direction of the physiological data, evaluates the surgical risk and sends prompt information, and generates dynamic risk warning results; The data flow control module obtains the data volume of each data flow in multiple surgical links based on the dynamic risk warning results and the operating room data classification results, calculates the bandwidth requirements of each data flow, adjusts the bandwidth allocation priority of the data flow, and generates real-time flow allocation results; The data partition storage module obtains the real-time update rate, write delay, bandwidth occupancy ratio, and criticality weight of each data type based on the real-time traffic allocation result, evaluates the storage priority of the data stream according to the data update frequency, write delay value, and cache priority, and stores the data in multiple cache partitions to generate data storage records; The access rights management module calculates and adjusts the access rights level of the data based on the data storage records and the timeliness of each operating room data in the database, assigns the access rights level to the medical staff in combination with the role type, and generates the access rights management results.

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