Self-adaptive postoperative vital sign data processing method and related equipment

Abstract

The embodiment of the invention provides a self-adaptive postoperative vital sign data processing method and related equipment, which can improve the accuracy of pain assessment and adjust the dosage in time. The method comprises the following steps: acquiring vital sign data, historical medication response and surgical wound level of a target user; the vital sign data, the historical medication response and the operation wound level are preprocessed; inputting the preprocessed vital sign data, the historical medication response and the operative wound level into an LSTM network to predict a pain index change slope of the target user in a future preset time period; determining regulation and control parameters corresponding to the target user according to the pain index change slope in the future preset time period and the current state of the target user; and carrying out output processing on the regulation and control parameters, so that a management user adjusts target usage metering corresponding to the target user based on the regulation and control parameters.

Description

Technical Field

[0001] This invention relates to the field of data processing, and in particular to an adaptive method and related equipment for processing postoperative vital signs data. Background Technology

[0002] Traditional methods often employ fixed-dose patient-controlled intravenous analgesia (PCIA) or patient-controlled epidural analgesia (PCEA), relying on the patient to actively trigger the dosing button. This approach cannot dynamically adjust drug infusion parameters based on real-time physiological indicators. For example, in one hospital's postoperative analgesia protocol, calculations were based solely on body weight, without considering differences in intraoperative stress responses.

[0003] The analgesic pump uses a preset background infusion rate (e.g., 2 ml / h) and lockout time (15 minutes), lacking closed-loop control based on dynamic adjustment of pain intensity. Studies show that traditional PCIA leads to inadequate analgesia or drug overdose in 23.6% of patients. While subjective scale adjustment schemes relying on visual analog scales (VAS) exist, patients with impaired consciousness cannot accurately express pain levels within 48 hours post-procedure. A clinical study showed that traditional methods result in 42% of nocturnal burst pain in elderly patients not being recognized in a timely manner. Summary of the Invention

[0004] This invention provides an adaptive postoperative vital sign data processing method and related equipment, which can consider multiple data aspects and assess the user's pain index without relying on subjective ratings, and generate corresponding adjustment parameters based on the assessment results to prompt the management user to adjust the dosage based on the adjustment parameters.

[0005] The first aspect of this invention provides an adaptive postoperative vital sign data processing method, comprising: Acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, the historical medication response, and the surgical trauma level are preprocessed; The preprocessed vital signs data, historical medication response, and surgical trauma level are input into an LSTM network to predict the slope of the target user's pain index change over a future preset period. The control parameters corresponding to the target user are determined based on the slope of the pain index change within the preset future time period and the current status of the target user. The control parameters are output and processed so that the management user can adjust the target usage measurement for the target user based on the control parameters.

[0006] In one possible design, the method further includes: When the target user is injected with the adjusted target dosage, the remaining dose corresponding to the target dosage is monitored in real time; When the remaining dose reaches a first threshold, a first prompt message is issued, which prompts the management user to change the dosage of the target.

[0007] In one possible design, the method further includes: Real-time monitoring of the target user's blood oxygen saturation; When the blood oxygen saturation is lower than the second threshold and the duration reaches the preset duration, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input.

[0008] In one possible design, the method further includes: When the slope of the pain index change reaches a preset condition, the current measurement parameters of the target user are adjusted, and a third prompt message is generated; The third prompt message is sent to the management terminal of the management user to prompt the management user to adjust the target usage rate corresponding to the target user according to the third prompt message.

[0009] In one possible design, the method further includes: Real-time monitoring of the target user's liver; When the target user has abnormal liver function, a target drug and a corresponding replacement drug are determined, wherein the target drug is the drug used by the target user that corresponds to the liver. The dosage of the replacement drug is determined based on the dosage conversion formula between the target drug and the replacement drug. A fourth prompt message is generated based on the dosage used, and the fourth prompt message is sent to the management terminal of the management user to prompt the management user to replace the target drug with the replacement drug according to the dosage used.

[0010] A second aspect of the present invention provides an adaptive postoperative vital sign data processing apparatus, comprising: The acquisition module is used to acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The preprocessing module is used to preprocess the vital signs data, the historical medication response, and the surgical trauma level. The prediction module is used to input the preprocessed vital sign data, the historical medication response and the surgical trauma level into the LSTM network to predict the slope of the pain index change of the target user in the future preset time period. The adjustment module is used to determine the control parameters corresponding to the target user based on the slope of the change in the pain index within the preset future time period and the current state of the target user. The output module is used to process the control parameters so that the management user can adjust the target usage measurement corresponding to the target user based on the control parameters.

[0011] In one possible design, the output module is further used for: When the target user is injected with the adjusted target dosage, the remaining dose corresponding to the target dosage is monitored in real time; When the remaining dose reaches a first threshold, a first prompt message is issued, which prompts the management user to change the dosage of the target.

[0012] In one possible design, the output module is further used for: Real-time monitoring of the target user's blood oxygen saturation; When the blood oxygen saturation is lower than the second threshold and the duration reaches the preset duration, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input.

[0013] In one possible design, the output module is further used for: When the slope of the pain index change reaches a preset condition, the current measurement parameters of the target user are adjusted, and a third prompt message is generated; The third prompt message is sent to the management terminal of the management user to prompt the management user to adjust the target usage rate corresponding to the target user according to the third prompt message.

[0014] In one possible design, the output module is further used for: Real-time monitoring of the target user's liver; When the target user has abnormal liver function, a target drug and a corresponding replacement drug are determined, wherein the target drug is the drug used by the target user that corresponds to the liver. The dosage of the replacement drug is determined based on the dosage conversion formula between the target drug and the replacement drug. A fourth prompt message is generated based on the dosage used, and the fourth prompt message is sent to the management terminal of the management user to prompt the management user to replace the target drug with the replacement drug according to the dosage used.

[0015] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the processor is configured to execute a computer management program stored in the memory to implement the steps of the adaptive postoperative vital sign data processing method as described in any of the preceding aspects.

[0016] A fourth aspect of the present invention provides a computer-readable storage medium having a computer management program stored thereon, which, when executed by a processor, implements the steps of adaptive postoperative vital sign data processing as described in any of the preceding aspects.

[0017] In summary, the embodiments provided by this invention involve acquiring the target user's vital signs data, historical medication responses, and surgical trauma levels. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, historical medication responses, and surgical trauma levels are preprocessed. These data are then input into an LSTM network to predict the slope of the target user's pain index change over a future preset time period. Based on the slope of the pain index change over the future preset time period and the target user's current state, the corresponding control parameters for the target user are determined. The control parameters are then output and processed so that the management user can adjust the target dosage for the target user based on these parameters. Therefore, multiple data points can be considered, and the user's pain index can be assessed without relying on subjective ratings. Based on the assessment results, corresponding adjustment parameters are generated to prompt the management user to adjust the dosage accordingly. Attached Figure Description

[0018] Figure 1 A flowchart illustrating the adaptive postoperative vital sign data processing method provided in this embodiment of the invention; Figure 2 A virtual structural diagram of the adaptive postoperative vital sign data processing device provided in an embodiment of the present invention; Figure 3 A schematic diagram of the hardware structure of the adaptive postoperative vital sign data processing device provided in an embodiment of the present invention; Figure 4 A schematic diagram of an embodiment of the electronic device provided in this invention; Figure 5 A schematic diagram illustrating an embodiment of a computer-readable storage medium provided in this invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] In the following description, specific embodiments of the invention will be illustrated with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be referred to several times as being performed by a computer, and computer execution as referred to herein includes operations by a computer processing unit representing electronic signals of data in a structured format. This operation transforms the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise alter the operation of the computer in a manner well known to those skilled in the art. The data structure maintained by the data is the physical location of the memory, which has specific characteristics defined by the data format. However, the principles of the invention described above are not intended to be limiting, and those skilled in the art will understand that many of the steps and operations described below can also be implemented in hardware.

[0021] The principles of this invention are applied using many other general-purpose or purpose-specific computing, communication environments, or configurations. Examples of well-known computing systems, environments, and configurations suitable for use with this invention include (but are not limited to) handheld phones, personal computers, servers, multiprocessor systems, microcomputer-based systems, mainframe computers, and distributed computing environments, including any of the aforementioned systems or devices.

[0022] The terms "first," "second," and "third," etc., used in this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion.

[0023] The adaptive postoperative vital signs data processing method provided by the present invention will be described from the perspective of the adaptive postoperative vital signs data processing device. The adaptive postoperative vital signs data processing device can be a server or a service unit in a server, and there is no specific limitation. For the sake of simplicity, the adaptive postoperative vital signs data processing device will be described as a server as an example.

[0024] Please see Figure 1 , Figure 1 A flowchart illustrating the adaptive postoperative vital sign data processing method provided by the present invention includes: 101. Obtain the target user's vital signs data, historical medication response, and surgical trauma level.

[0025] In this embodiment, the server can acquire the target user's vital signs data, historical medication response, and surgical trauma level. The target user is a user who has undergone surgery. The vital signs data includes the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. Specifically, the server collects pain-related physiological parameters in real time through IoT sensors and PCA recording units, such as skin conductance sensors and myocardiogram sensors, and transmits the collected physiological parameters to the server through high-speed wireless technology. It also collects the target user's historical medication response and surgical trauma level data simultaneously, thereby collecting comprehensive and objective physiological and psychological mixed indicators.

[0026] 102. Preprocess vital signs data, historical medication responses, and surgical trauma levels.

[0027] In this embodiment, after the server obtains the target user's vital signs data, historical medication responses, and surgical trauma level, it can perform preprocessing. This preprocessing includes, but is not limited to, noise removal, missing value imputation, and normalization. For example, after wavelet denoising of the raw electromyography signal, time-domain features (such as RMS value) and frequency-domain features (such as median frequency) are extracted. In addition, the server can use a sliding time window (window length 5 minutes, step size 30 seconds) to align and integrate all data within the window (heart rate variability, respiratory rate, electrodermal signal, and several processed features, etc.) to generate a unified state snapshot of the target user containing multi-dimensional information. This state snapshot is updated every 30 seconds and includes the calculated objective pain index, which is correlated and corrected with the subjective pain score input by the target user to finally obtain an objective current pain index for the target user.

[0028] 103. Input the preprocessed vital signs data, historical medication response and surgical trauma level into the LSTM network to predict the slope of the target user's pain index change in the future preset time period.

[0029] In this embodiment, the server can pre-train an LSTM model based on the historical vital sign data and historical pain trends of multiple postoperative users. That is, after receiving pre-processed vital sign data, historical medication responses, and surgical trauma levels, the server assigns different weights to different factors and makes a comprehensive judgment. Specifically: The current pain index (with a weight of 60%) is the most important direct basis for judgment; Historical medication response (weighted at 30%): The server determines the target user's response to the drug dosage up to the current moment based on their historical treatment data. If pain relief was not significant after the last dose, the dosage may be appropriately increased next time; if signs of side effects such as drowsiness occur, the dosage will be conservatively adjusted. Surgical trauma level (with a weight of 10%): Considering the different pain baseline levels of open-chest surgery and appendectomy, the server can adjust the baseline of medication dosage according to different surgical trauma levels.

[0030] The server then inputs the three factors mentioned above into the LSTM network and analyzes the time-series data of the target user's pain index to predict the slope of the pain index change over the next 30 minutes. If the slope is greater than 0.2, it means that the pain is intensifying. Instead of passively waiting for the pain to erupt, the server will proactively issue a corresponding prompt, alerting the administrator to initiate "preventive pressure boosting infusion" for the target user.

[0031] 104. Determine the control parameters corresponding to the target user based on the slope of the pain index change within a preset time period and the current status of the target user.

[0032] In this embodiment, after the server predicts the slope of the target user's pain index change over a future period using an LSTM network, it can determine the individualized control parameters corresponding to the target user through a generative decision engine based on the slope of the pain index change and the target user's current state. These individualized control parameters include the base infusion rate, single booster dose, and lockout interval, as exemplified below: Basal infusion rate (0.1-5.0 ml / h): The background rate of continuous slow drug administration.

[0033] Single booster dose (0.5-2.5 ml): An additional dose given when the target user actively presses the button or anticipates a burst of pain.

[0034] Lockout interval (5-30 minutes): For safety reasons, the server will be locked for a period of time after an additional dose is administered, preventing further doses from being administered.

[0035] It should be noted that this generative decision engine integrates adversarial networks (GANs) and deep Q-networks (DQNs). GANs are used to generate personalized drug metabolism models and predict changes in drug concentrations in different patients. DQNs learn and optimize dosage adjustment strategies by continuously interacting with the environment and outcomes (pain feedback).

[0036] 105. Output the control parameters so that management users can adjust the target usage metering for the target user based on the control parameters.

[0037] In this embodiment, after determining the adjustment parameters, the server can output these parameters so that the management user can adjust the target usage rate for the target user based on them. These adjustment parameters include, but are not limited to, the target user's ID, the parameters before adjustment, the adjustment range, and the parameters after adjustment. For example, the adjustment parameters can be directly displayed on a large screen or directly transmitted to the management user's mobile terminal to remind the management user to adjust the target user's usage rate accordingly.

[0038] It should be noted that when the target user is injected with the adjusted target dosage, the remaining dose corresponding to the target dosage is monitored in real time; when the remaining dose reaches the first threshold, a first prompt message is issued, which is used to prompt the management user to change the target dosage.

[0039] In one embodiment, the server also performs the following operations: Real-time monitoring of the target user's blood oxygen saturation; When the blood oxygen saturation is lower than the second threshold and the duration reaches the preset duration, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input.

[0040] In this embodiment, the server can also monitor the target user's blood oxygen saturation in real time and make a judgment on the monitored blood oxygen saturation. It can determine whether the real-time monitored blood oxygen saturation is lower than a second threshold (the second threshold is, for example, 92%, that is, when the blood oxygen saturation is lower than 92% and lasts for a period of time, the target user will be at risk of respiratory depression). When the blood oxygen saturation is lower than the second threshold, it can determine whether the duration of the target user's blood oxygen saturation being lower than the second threshold has reached a preset duration. If the preset duration has been reached, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input. The first backup input can be, for example, naloxone, and the specific input can be adjusted according to the actual situation of the target user.

[0041] In one embodiment, the server also performs the following operations: When the slope of the pain index change reaches the preset condition, the current measurement parameters of the target user are adjusted and a third prompt message is generated; The third prompt message is sent to the management terminal of the management user to prompt the management user to adjust the target usage meter for the target user according to the third prompt message.

[0042] In this embodiment, after monitoring the slope of the pain index change, the server can also perform a judgment to determine whether the slope of the pain index change meets a preset condition. The preset condition is, for example, that the slope of the pain index change is greater than 6. When it is determined that the slope of the pain index change is greater than 6, the server determines the target user's current measurement parameters, that is, the target user's current basic infusion rate and the specific value of the additional dose, and makes adjustments accordingly. For example, the basic infusion rate is adjusted from 0.5 ml / h to 2.0 ml / h, and the additional dose interval is adjusted from 20 minutes to 8 minutes. A corresponding third prompt message is generated to prompt the management user to adjust the target usage measurement for the target user.

[0043] In one embodiment, the server also performs the following operations: Real-time monitoring of the target user's liver; When the target user has abnormal liver function, a target drug and a corresponding replacement drug are determined, wherein the target drug is the drug used by the target user that corresponds to the liver. The dosage of the replacement drug is determined based on the dosage conversion formula between the target drug and the replacement drug. A fourth prompt message is generated based on the dosage used, and the fourth prompt message is sent to the management terminal of the management user to prompt the management user to replace the target drug with the replacement drug according to the dosage used.

[0044] In this embodiment, the server can construct a clinical knowledge graph, building a computer-understandable knowledge network from massive amounts of medical knowledge (clinical guidelines, drug contraindications) and providing decision-making knowledge. It can monitor the liver function of a target user in real time. When abnormal liver function is detected, the server determines the target user's current medication and, based on the constructed clinical knowledge graph, identifies the corresponding replacement drug, generating a dosage conversion formula. Finally, based on this formula, the server determines the dosage of the replacement drug, generates a fourth prompt message, and sends this message to the administrator's terminal, prompting the administrator to replace the target drug with the replacement drug according to the prescribed dosage. For example, when a patient's liver function is abnormal, the clinical knowledge graph determines the target user's specific situation, allowing the server to replace the currently used fentanyl with remifentanil, generating a dosage conversion formula (e.g., reducing the dosage by 40% when eGFR < 30), and then having the administrator make the change.

[0045] In summary, the embodiments provided by this invention acquire the target user's vital signs data, historical medication responses, and surgical trauma levels. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, historical medication responses, and surgical trauma levels are preprocessed. The preprocessed vital signs data, historical medication responses, and surgical trauma levels are input into an LSTM network to predict the slope of the target user's pain index change over a future preset time period. Based on the slope of the pain index change over the future preset time period and the target user's current state, the corresponding adjustment parameters for the target user are determined. The adjustment parameters are then output and processed so that the management user can adjust the target dosage for the target user based on the adjustment parameters. Therefore, this method considers multiple data aspects, assesses the user's pain index without relying on subjective ratings, and generates corresponding adjustment parameters based on the assessment results to prompt the management user to adjust the dosage accordingly.

[0046] The embodiments of the present invention have been described above from the perspective of the adaptive postoperative vital sign data processing method. The embodiments of the present invention will now be described below from the perspective of the adaptive postoperative vital sign data processing device.

[0047] Please see Figure 2 , Figure 2 A virtual structural diagram of an adaptive postoperative vital signs data processing device 200 according to an embodiment of the present invention. The adaptive postoperative vital signs data processing device 200 includes: The acquisition module 201 is used to acquire the target user's vital signs data, historical medication response and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability and respiratory rate. Preprocessing module 202 is used to preprocess the vital signs data, the historical medication response, and the surgical trauma level; Prediction module 203 is used to input the preprocessed vital sign data, the historical medication response and the surgical trauma level into the LSTM network to predict the slope of the pain index change of the target user in the future preset period. The adjustment module 204 is used to determine the control parameters corresponding to the target user based on the slope of the change in the pain index within the future preset time period and the current state of the target user; The output module 205 is used to output the control parameters so that the management user can adjust the target usage metering corresponding to the target user based on the control parameters.

[0048] In one possible design, the output module 205 is further used for: When the target user is injected with the adjusted target dosage, the remaining dose corresponding to the target dosage is monitored in real time; When the remaining dose reaches a first threshold, a first prompt message is issued, which prompts the management user to change the dosage of the target.

[0049] In one possible design, the output module 205 is further used for: Real-time monitoring of the target user's blood oxygen saturation; When the blood oxygen saturation is lower than the second threshold and the duration reaches the preset duration, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input.

[0050] In one possible design, the output module 205 is further used for: When the slope of the pain index change reaches a preset condition, the current measurement parameters of the target user are adjusted, and a third prompt message is generated; The third prompt message is sent to the management terminal of the management user to prompt the management user to adjust the target usage rate corresponding to the target user according to the third prompt message.

[0051] In one possible design, the output module 205 is further used for: Real-time monitoring of the target user's liver; When the target user has abnormal liver function, a target drug and a corresponding replacement drug are determined, wherein the target drug is the drug used by the target user that corresponds to the liver. The dosage of the replacement drug is determined based on the dosage conversion formula between the target drug and the replacement drug. A fourth prompt message is generated based on the dosage used, and the fourth prompt message is sent to the management terminal of the management user to prompt the management user to replace the target drug with the replacement drug according to the dosage used.

[0052] above Figure 2 The adaptive postoperative vital signs data processing device in this embodiment of the invention has been described from the perspective of modular functional entities. The following is a detailed description of the adaptive postoperative vital signs data processing device in this embodiment of the invention from the perspective of hardware processing. Please refer to Figure 300, which is a schematic diagram of an embodiment of the adaptive postoperative vital signs data processing device 300 in this invention. The adaptive postoperative vital signs data processing device 300 includes: Input device 301, output device 302, processor 303, and memory 304 (where the number of processors 303 can be one or more). Figure 3 (Taking a processor 303 as an example). In some embodiments of the present invention, the input device 301, the output device 302, the processor 303, and the memory 304 may be connected via a communication bus or other means, wherein... Figure 3 Take the China-Israel communication bus connection as an example.

[0053] Specifically, by calling the operation instructions stored in memory 304, processor 303 executes the following steps: Acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, the historical medication response, and the surgical trauma level are preprocessed; The preprocessed vital signs data, historical medication response, and surgical trauma level are input into an LSTM network to predict the slope of the target user's pain index change over a future preset period. The control parameters corresponding to the target user are determined based on the slope of the pain index change within the preset future time period and the current status of the target user. The control parameters are output and processed so that the management user can adjust the target usage measurement for the target user based on the control parameters.

[0054] By calling the operation instructions stored in memory 304, processor 303 is also used to execute... Figure 1 Any of the methods in the corresponding embodiments.

[0055] Please see Figure 4 , Figure 4 A schematic diagram of an embodiment of the electronic device provided in this invention.

[0056] like Figure 4 As shown, this embodiment of the invention provides an electronic device, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, it performs the following steps: Acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, the historical medication response, and the surgical trauma level are preprocessed; The preprocessed vital signs data, historical medication response, and surgical trauma level are input into an LSTM network to predict the slope of the target user's pain index change over a future preset period. The control parameters corresponding to the target user are determined based on the slope of the pain index change within the preset future time period and the current status of the target user. The control parameters are output and processed so that the management user can adjust the target usage measurement for the target user based on the control parameters.

[0057] In practical implementation, when the processor 420 executes the computer program 411, it can achieve... Figure 1 Any of the corresponding implementation methods in the embodiments.

[0058] Since the electronic device described in this embodiment is the device used by the computing device for implementing the mid-frequency unit excitation of an array antenna in this embodiment of the present invention, those skilled in the art can understand the specific implementation method and various variations of the electronic device in this embodiment based on the method described in this embodiment of the present invention. Therefore, how the electronic device implements the method in this embodiment of the present invention will not be described in detail here. Any device used by those skilled in the art to implement the method in this embodiment of the present invention is within the scope of protection of this invention.

[0059] Please refer to Figure 500, which is a schematic diagram of an embodiment of a computer-readable storage medium provided by an embodiment of the present invention.

[0060] As shown in Figure 500, this embodiment of the invention also provides a computer-readable storage medium 500, on which a computer program 511 is stored. When the computer program 511 is executed by a processor, it performs the following steps: Acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, the historical medication response, and the surgical trauma level are preprocessed; The preprocessed vital signs data, historical medication response, and surgical trauma level are input into an LSTM network to predict the slope of the target user's pain index change over a future preset period. The control parameters corresponding to the target user are determined based on the slope of the pain index change within the preset future time period and the current status of the target user. The control parameters are output and processed so that the management user can adjust the target usage measurement for the target user based on the control parameters.

[0061] In the specific implementation process, the computer program 511 is executed by the processor to achieve... Figure 1 Any of the corresponding implementation methods in the embodiments.

[0062] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0063] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0064] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0065] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0066] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0067] This invention also provides a computer program product comprising computer software instructions that, when executed on a processing device, cause the processing device to perform actions such as... Figure 1 The process in the corresponding embodiment.

[0068] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0069] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0070] In the embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0071] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0072] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0073] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0074] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for processing adaptive postoperative vital signs data, characterized in that, include: Acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The vital signs data, the historical medication response, and the surgical trauma level are preprocessed; The preprocessed vital signs data, historical medication response, and surgical trauma level are input into an LSTM network to predict the slope of the target user's pain index change over a future preset period. The control parameters corresponding to the target user are determined based on the slope of the pain index change within the preset future time period and the current status of the target user. The control parameters are output and processed so that the management user can adjust the target usage measurement for the target user based on the control parameters.

2. The method according to claim 1, characterized in that, The method further includes: When the target user is injected with the adjusted target dosage, the remaining dose corresponding to the target dosage is monitored in real time; When the remaining dose reaches a first threshold, a first prompt message is issued, which prompts the management user to change the dosage of the target.

3. The method according to claim 1, characterized in that, The method further includes: Real-time monitoring of the target user's blood oxygen saturation; When the blood oxygen saturation is lower than the second threshold and the duration reaches the preset duration, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input.

4. The method according to claim 1, characterized in that, The method further includes: When the slope of the pain index change reaches a preset condition, the current measurement parameters of the target user are adjusted, and a third prompt message is generated; The third prompt message is sent to the management terminal of the management user to prompt the management user to adjust the target usage rate corresponding to the target user according to the third prompt message.

5. The method according to claim 1, characterized in that, The method further includes: Real-time monitoring of the target user's liver; When the target user has abnormal liver function, a target drug and a corresponding replacement drug are determined, wherein the target drug is the drug used by the target user that corresponds to the liver. The dosage of the replacement drug is determined based on the dosage conversion formula between the target drug and the replacement drug. A fourth prompt message is generated based on the dosage used, and the fourth prompt message is sent to the management terminal of the management user to prompt the management user to replace the target drug with the replacement drug according to the dosage used.

6. An adaptive postoperative vital sign data processing device, characterized in that, include: The acquisition module is used to acquire the target user's vital signs data, historical medication response, and surgical trauma level. The vital signs data include the target user's sweat gland activity data, muscle tension, heart rate variability, and respiratory rate. The preprocessing module is used to preprocess the vital signs data, the historical medication response, and the surgical trauma level. The prediction module is used to input the preprocessed vital sign data, the historical medication response and the surgical trauma level into the LSTM network to predict the slope of the pain index change of the target user in the future preset time period. The adjustment module is used to determine the control parameters corresponding to the target user based on the slope of the change in the pain index within the preset future time period and the current state of the target user. The output module is used to process the control parameters so that the management user can adjust the target usage measurement corresponding to the target user based on the control parameters.

7. The apparatus according to claim 6, characterized in that, The output module is also used for: When the target user is injected with the adjusted target dosage, the remaining dose corresponding to the target dosage is monitored in real time; When the remaining dose reaches a first threshold, a first prompt message is issued, which prompts the management user to change the dosage of the target.

8. The apparatus according to claim 6, characterized in that, The output module is also used for: Real-time monitoring of the target user's blood oxygen saturation; When the blood oxygen saturation is lower than the second threshold and the duration reaches the preset duration, a second prompt message is issued. The second prompt message is used to prompt the management user to stop the original input and start the first backup input.

9. An electronic device, characterized in that, include: A memory and a processor, wherein the processor is configured to execute a computer management program stored in the memory to implement the steps of the adaptive postoperative vital signs data processing method as described in any one of claims 1 to 5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer management program, which, when executed by a processor, performs the steps of processing adaptive postoperative vital signs data as described in any one of claims 1 to 5.

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