Intelligent ambulatory blood pressure regulation and control system based on infusion monitoring and control method of intelligent ambulatory blood pressure regulation and control system

Abstract

The invention provides an intelligent ambulatory blood pressure regulation and control system based on infusion monitoring and a control method thereof.The intelligent ambulatory blood pressure regulation and control system comprises infusion equipment which is configured to control the infusion speed of medicine and automatically adjust the infusion speed according to received real-time blood pressure data and a regulation and control strategy; the monitoring equipment is configured to monitor physiological data of a user in real time; the intelligent terminal is configured to automatically identify the activity level of the user; the image acquisition device is configured to monitor position information of a user in real time; the infusion monitoring system comprises an artificial regulation and control strategy and an AI regulation and control strategy, analysis is conducted according to the physiological data, the user state information and the user position information which are collected in real time, working parameters of infusion equipment are automatically adjusted according to the preset regulation and control strategy, and therefore intelligent dynamic regulation and control over the blood pressure of the user are achieved. According to the intelligent blood pressure regulation and control system, intelligent, unmanned and high-precision real-time regulation and control of the blood pressure are achieved by constructing the self-adaptive and multi-mode cooperative intelligent blood pressure regulation and control system, and a more accurate and personalized treatment scheme is provided for a user.

Description

Technical Field

[0001] The present invention relates to the field of medical monitoring technology, and in particular to an intelligent dynamic blood pressure control system based on infusion monitoring and a method thereof. Background Art

[0002] In current medical practice, blood pressure management is a key link in the treatment of many diseases and plays a vital role in the treatment of patients with chronic diseases such as hypertension and cardiovascular disease. Stable control of blood pressure can not only effectively prevent the occurrence of complications, but also significantly improve the quality of life of patients. However, traditional blood pressure management methods have many limitations.

[0003] Traditionally, blood pressure management mainly relies on medical staff to manually measure and record patients' blood pressure values ​​regularly. This measurement method is not only time-consuming and labor-intensive, but also greatly affected by human factors, such as measurement time and the technical level of the measurer, which may lead to inaccurate measurement results. Subsequently, medical staff need to adjust the patient's treatment plan based on these measurement results, including the type of drug, dosage, and infusion rate. This adjustment method based on manual measurement and human judgment is difficult to achieve real-time and accurate control of blood pressure, which often leads to poor treatment effects and may even cause adverse reactions.

[0004] With the continuous advancement of medical technology, non-invasive blood pressure monitoring technology, telemedicine systems, automated control technology and artificial intelligence have been widely used in the medical field, providing possibilities for automated and intelligent blood pressure management. The emergence of monitoring equipment such as monitors and smart bracelets makes it possible to monitor patients' blood pressure in real time, and medical staff can obtain patients' blood pressure data anytime and anywhere. At the same time, the development of infusion pump technology also provides strong support for the precise infusion of drugs, and the infusion speed can be adjusted in real time according to the actual needs of patients.

[0005] However, despite the great potential of these technologies in blood pressure management, most existing blood pressure management systems are still decentralized. The lack of effective data interaction and collaborative working mechanisms between monitoring devices, infusion pumps, and medical information systems makes it difficult to achieve real-time transmission and analysis of blood pressure data, as well as automated and intelligent regulation based on data. This not only limits the efficiency and accuracy of blood pressure management, but also affects the improvement of patient treatment outcomes.

[0006] Therefore, there is an urgent need for a system that can integrate various blood pressure monitoring devices, infusion pumps and medical information systems. Summary of the invention

[0007] In view of the shortcomings of the prior art, the present invention provides an intelligent dynamic blood pressure control system based on infusion monitoring and a method thereof. The system and method introduce AI algorithms and standardized communication protocols to construct an adaptive, multi-modal collaborative intelligent blood pressure control system, thereby realizing intelligent, unmanned, high-precision real-time control of blood pressure, providing patients with chronic diseases with more accurate and personalized treatment plans, thereby improving the quality of life of patients and preventing the occurrence of complications.

[0008] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0009] An intelligent dynamic blood pressure control system based on infusion monitoring, comprising:

[0010] an infusion device configured to control the infusion rate of the drug and to exchange data with the infusion monitoring system via a wireless communication protocol so as to automatically adjust the infusion rate according to the received real-time blood pressure data and the regulation strategy;

[0011] A monitoring device configured to monitor the user's physiological data in real time and send the monitored physiological data to the infusion monitoring system via a wireless communication protocol;

[0012] an intelligent terminal having a built-in sensor configured to automatically identify the activity level of a user and transmit the user's status information to the infusion monitoring system via wireless communication;

[0013] An image acquisition device configured to monitor the user's position information in real time and upload the monitoring data to the infusion monitoring system to determine the user's status;

[0014] The infusion monitoring system has a built-in blood pressure control strategy configuration module, which includes manual control strategies and AI control strategies. It analyzes the real-time collected physiological data, user status information and user location information, and automatically adjusts the working parameters of the infusion device according to the preset control strategy to achieve intelligent dynamic control of the user's blood pressure.

[0015] According to an intelligent dynamic blood pressure control system based on infusion monitoring provided by the present invention, the manual control strategy provides a user interface, allowing medical staff to perform specific configuration of the blood pressure control strategy through the interface;

[0016] Setting the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit of blood pressure, and the growth rate π value of drug infusion and the upper and lower limits of drug speed through the user interface;

[0017] The manual control strategy also includes an authorization setting function, which allows medical personnel to choose whether to authorize the device to automatically adjust the infusion rate according to the preset control strategy;

[0018] When authorization is set, the blood pressure rate control strategy configured by the medical staff will be used to automatically adjust the infusion rate to maintain the blood pressure within the set range when changes in the user's blood pressure are monitored.

[0019] According to an intelligent dynamic blood pressure control system based on infusion monitoring provided by the present invention, the AI ​​control strategy includes:

[0020] It is integrated with an AI intelligent analysis module, which is used to automatically generate the initial values ​​of the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value and drug speed upper and lower limits of blood pressure according to the user's initial physiological parameters;

[0021] The AI ​​intelligent analysis module receives and processes the user's physiological parameter data, historical blood pressure data, and environmental factor data in real time, performs continuous in-depth learning on the user's blood pressure data, and dynamically optimizes and adjusts the user's systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and drug speed upper and lower limits.

[0022] The AI ​​intelligent analysis module also has the ability to dynamically adjust the blood pressure speed control strategy according to the user's real-time status changes to ensure the accuracy and effectiveness of blood pressure control.

[0023] According to an intelligent dynamic blood pressure control system based on infusion monitoring provided by the present invention, the implementation method of the AI ​​control strategy specifically includes:

[0024] The AI ​​intelligent analysis module automatically generates the initial values ​​of the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and upper and lower limits of the drug speed according to the user's initial physiological parameters, and conducts continuous in-depth learning of the user's blood pressure data in combination with the user's real-time status, historical data, and environmental factors;

[0025] When the drug infusion begins, the blood pressure data from the monitoring device and the user status information of the smart terminal are collected regularly. Based on the current user's physiological parameters, medication type, and activity status, the optimized π value is obtained through the reinforcement learning strategy.

[0026] According to the optimized π value, the corresponding infusion speed adjustment amount is calculated through the preset blood pressure speed control logic, and the adjustment amount is converted into a specific control instruction and sent to the infusion device to realize automatic adjustment of the infusion speed; wherein, by continuously monitoring the user's blood pressure data and status information, a closed-loop control system is formed to realize dynamic control of blood pressure.

[0027] According to the intelligent dynamic blood pressure control system based on infusion monitoring provided by the present invention, it is determined whether the current user's blood pressure value exceeds the set systolic pressure upper limit, diastolic pressure upper limit or is lower than the systolic pressure lower limit, diastolic pressure lower limit;

[0028] If the current blood pressure value exceeds or falls below the set limit, a preliminary infusion rate adjustment is calculated based on the degree of excess or fall, the drug speed increase π value, and the upper and lower limits of the drug speed;

[0029] Combined with the user status information from the smart terminal, the preliminary infusion speed adjustment amount is corrected to obtain a final infusion speed adjustment amount that is more in line with the user's actual condition;

[0030] The final infusion speed adjustment amount is converted into a specific control instruction and sent to the infusion device to adjust the infusion speed in real time to ensure that the user's blood pressure is maintained within the set range.

[0031] According to an intelligent dynamic blood pressure control system based on infusion monitoring provided by the present invention, the blood pressure speed control strategy includes:

[0032] The user's blood pressure data and status information are sampled at regular intervals to first determine whether the user is in a state of strenuous exercise;

[0033] If the user is in a state of intense exercise, the blood pressure speed control strategy will not be triggered and the current infusion speed will remain unchanged;

[0034] If the user is not in a state of strenuous exercise, the current blood pressure data is compared with the blood pressure value sampled last time, and the speed is adjusted according to the type of blood pressure medicine currently used by the infusion device. The specific adjustment rules are as follows:

[0035] When users take blood pressure medication:

[0036] If the user's current blood pressure is still higher than the previous blood pressure and exceeds the preset high pressure upper limit, the control speed is equal to the current speed multiplied by (1+π value), and the control speed shall not exceed the maximum speed of medication;

[0037] If the user's current blood pressure has dropped compared to the previous blood pressure and exceeds the preset high pressure warning value, the control speed is equal to the current speed multiplied by (1-π value), and the control speed shall not exceed the maximum speed of medication;

[0038] If the user’s blood pressure remains within the normal range for 60 consecutive minutes, the infusion is suspended;

[0039] When users take vasopressors:

[0040] If the user's current blood pressure is still lower than the previous blood pressure and exceeds the preset low pressure limit, the control speed is equal to the current speed multiplied by (1+π value), and the control speed shall not exceed the maximum speed of medication;

[0041] If the user's current blood pressure has increased compared to the previous blood pressure but has not reached the normal range or is still below a certain safety threshold of the low pressure lower limit, the control speed is equal to the current speed multiplied by (1-π value), and the control speed shall not exceed the maximum speed of medication;

[0042] If the user’s blood pressure remains within the normal range for 60 consecutive minutes, the infusion is suspended;

[0043] The value of π is a configurable parameter, and its default value is 10%.

[0044] An intelligent dynamic blood pressure control method based on infusion monitoring, which adopts the above-mentioned intelligent dynamic blood pressure control system based on infusion monitoring to perform dynamic blood pressure control, and includes the following steps:

[0045] Monitor the user's blood pressure data in real time through monitoring equipment, monitor the user's activity level through smart terminals, and monitor the user's location information through image acquisition devices;

[0046] The above data is uploaded to the infusion monitoring system; the infusion monitoring system is equipped with a wireless network receiving function, which is used to receive multi-source data from infusion equipment, monitoring equipment, intelligent terminals and image acquisition devices in real time; after receiving the raw data, the infusion monitoring system performs a preliminary screening of the raw data according to a preset custom device communication protocol to remove invalid data or redundant data; the infusion monitoring system verifies the data after the preliminary screening using a data verification algorithm in the custom device communication protocol;

[0047] The infusion monitoring system analyzes the real-time collected data according to the preset manual control strategy or AI control strategy, and automatically adjusts the working parameters of the infusion equipment according to the analysis results to achieve dynamic control of blood pressure.

[0048] According to an intelligent dynamic blood pressure control method based on infusion monitoring provided by the present invention, after determining that the user is not in a state of strenuous exercise, it is further determined whether the user's real-time blood pressure data exceeds a preset blood pressure alarm threshold;

[0049] If the user's real-time blood pressure data exceeds the preset blood pressure upper limit alarm threshold, the speed control logic is triggered, and the adjustment amount for reducing the infusion speed is automatically calculated according to the preset control parameters and control logic;

[0050] If the user's real-time blood pressure data is lower than the preset lower blood pressure alarm threshold, the speed control logic will also be triggered, and the adjustment amount for increasing the infusion speed will be automatically calculated based on the preset control parameters and control logic;

[0051] Generate a control instruction corresponding to the calculated infusion speed adjustment amount, and send the control instruction to the infusion device to adjust the infusion speed to a suitable level.

[0052] According to an intelligent dynamic blood pressure control method based on infusion monitoring provided by the present invention, the infusion monitoring system converts the control speed into communication data according to the calculated control speed and the customized device communication protocol, and sends the communication data to the infusion device through the WI-FI wireless network;

[0053] After receiving the communication data sent by the infusion monitoring system, the infusion device verifies and analyzes the data according to the device communication protocol to confirm the validity of the control instruction;

[0054] The infusion device automatically adjusts its infusion speed according to the analyzed control instructions, thereby realizing dynamic control of the user's blood pressure. During the control process, the infusion monitoring system continuously monitors the changes in the user's blood pressure and adjusts the infusion speed as needed to ensure that the user's blood pressure is stable within the preset safety range.

[0055] When the user's blood pressure exceeds the preset safety range, or the user is in a dangerous position, the infusion monitoring system triggers the alarm mechanism to promptly alert medical staff to the user's condition.

[0056] According to an intelligent dynamic blood pressure control method based on infusion monitoring provided by the present invention, an environmental model for reinforcement learning is constructed according to the user's physiological parameters, medication type and activity status;

[0057] In the environment model, a state space is defined to map the user's physiological parameters, medication status, and activity status into state representations in reinforcement learning;

[0058] Define an action space and use possible medication adjustments as actions in reinforcement learning;

[0059] Define the reward function and set the reward mechanism according to the treatment goal to reflect the impact of different actions on the treatment effect;

[0060] Use policy π to represent the probability distribution of choosing an action in a given state;

[0061] Collect sample data, including states, actions, and rewards, by interacting with the environment;

[0062] Using the collected sample data, the reinforcement learning algorithm is used to optimize the strategy π. During the optimization process, according to the strategy improvement theorem, the strategy π is iteratively updated so that it can select the action with the maximum expected reward in the current state.

[0063] According to the optimized strategy π, a personalized dosage adjustment plan is generated in combination with the current user's physiological parameters, medication type, and activity status;

[0064] Conduct strategy evaluation on the generated dose adjustment scheme, verify its effectiveness through simulation or actual application, and further optimize and adjust the strategy π based on the evaluation results;

[0065] The method for obtaining the optimized strategy π value through the reinforcement learning strategy specifically includes the following steps:

[0066] State representation: Encoding the user’s physiological parameters, medication status, and activity status into a state vector in reinforcement learning;

[0067] Action selection: Based on the current state, use strategy π to select the action with the maximum expected reward, i.e., the dosage adjustment plan;

[0068] Reward calculation: According to the treatment goal, the reward value obtained after performing the action is calculated to evaluate the effect of the action;

[0069] Strategy update: Based on the reward value and state transition probability, a reinforcement learning algorithm is used to update the parameters of the strategy π to maximize the long-term expected reward.

[0070] It can be seen that compared with the prior art, the present invention achieves dynamic and precise control of blood pressure through a specific system architecture and components, advanced data processing and analysis algorithms, automatic control strategies and closed-loop control mechanisms, as well as real-time monitoring of the patient's motion status and AI functional modules. The following are the beneficial effects of the present invention:

[0071] The system architecture and components (infusion pump, monitor, smart bracelet, camera and infusion monitoring system) of the present invention realize the comprehensive and real-time collection of patient blood pressure, status information and environmental data through specific connection methods and data interaction mechanisms. This collaborative working mechanism greatly improves the accuracy and reliability of blood pressure data and provides a solid foundation for subsequent blood pressure management.

[0072] The control algorithm and data processing module used in the system of the present invention can efficiently process and analyze blood pressure data, patient status information and camera data. The accuracy and real-time performance of data analysis are ensured through algorithm logic, parameter setting and dynamic π value optimization algorithm, which helps to more accurately judge the patient's blood pressure condition and provide a scientific basis for blood pressure regulation.

[0073] The present invention automatically adjusts the infusion speed based on the data analysis results, thereby realizing dynamic regulation of blood pressure. This closed-loop control mechanism can flexibly adjust the infusion strategy according to the patient's real-time blood pressure and status information, thereby ensuring stable control of blood pressure within the target range. This not only improves the effect of blood pressure management, but also reduces the frequency and error of manual intervention.

[0074] The present invention can monitor the patient's state of rest, light activity, intense exercise, etc. in real time through image acquisition and intelligent terminals, so that the blood pressure control strategy can be dynamically adjusted according to the patient's exercise state, improving the adaptability and flexibility of blood pressure management. No matter what state the patient is in, the system can ensure stable control of blood pressure.

[0075] The system of the present invention integrates an intelligent analysis module based on AI algorithms such as DeepSeek, which can perform in-depth learning on the patient's blood pressure data and predict the trend of blood pressure changes, so that the system can adjust the infusion rate in advance and effectively prevent abnormal fluctuations in blood pressure. This not only improves the predictability of blood pressure management, but also further improves the accuracy and effectiveness of blood pressure regulation.

[0076] The blood pressure management system of the present invention realizes automated and intelligent blood pressure management, greatly reducing the burden on medical staff. At the same time, the ease of use and convenience of the system also enhance the user experience of patients, allowing patients to participate more actively in blood pressure management.

[0077] In summary, the blood pressure management system and method integrating intelligent monitoring and automatic control proposed in the present invention realize dynamic and precise control of blood pressure through advanced system architecture, data processing algorithm, automatic control strategy, motion status monitoring technology and AI functional module, which not only improves the accuracy and safety of blood pressure management, but also improves medical efficiency and patient experience.

[0078] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 It is a schematic diagram of an embodiment of an intelligent dynamic blood pressure control system based on infusion monitoring of the present invention.

[0080] Figure 2 It is a flow chart of an embodiment of an intelligent dynamic blood pressure control method based on infusion monitoring of the present invention. DETAILED DESCRIPTION

[0081] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0082] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0083] See also Figure 1 This embodiment provides an intelligent dynamic blood pressure control system based on infusion monitoring, including:

[0084] an infusion device configured to control the infusion rate of the drug and to exchange data with the infusion monitoring system via a wireless communication protocol so as to automatically adjust the infusion rate according to the received real-time blood pressure data and the regulation strategy;

[0085] A monitoring device configured to monitor the user's physiological data in real time and send the monitored physiological data to the infusion monitoring system via a wireless communication protocol;

[0086] an intelligent terminal having a built-in sensor configured to automatically identify the activity level of a user and transmit the user's status information to the infusion monitoring system via wireless communication;

[0087] An image acquisition device configured to monitor the user's position information in real time and upload the monitoring data to the infusion monitoring system to determine the user's status;

[0088] The infusion monitoring system has a built-in blood pressure control strategy configuration module, which includes manual control strategies and AI control strategies. It analyzes the real-time collected physiological data, user status information and user location information, and automatically adjusts the working parameters of the infusion device according to the preset control strategy to achieve intelligent dynamic control of the user's blood pressure.

[0089] Among them, the infusion equipment of this embodiment includes but is not limited to an infusion pump, which is mainly responsible for accurately controlling the infusion speed of the drug to ensure that the drug enters the patient's body safely and accurately at a predetermined speed and dosage; it interacts with the infusion monitoring system through a wireless communication protocol and reports the infusion pump information to the system for monitoring; under the control of the infusion monitoring system, the infusion pump can automatically adjust the infusion speed according to real-time blood pressure data and control strategies to achieve dynamic control of blood pressure.

[0090] Among them, the monitoring equipment of this embodiment includes but is not limited to a monitor, which is used to measure multiple physiological parameters of the patient, such as heart rate, respiration, blood pressure, etc., and interacts with the infusion monitoring system through a wireless communication protocol to report the patient's blood pressure data to the system.

[0091] The smart terminal of this embodiment includes but is not limited to a smart bracelet, which automatically identifies the patient's activity level (such as stillness, light activity, and vigorous exercise) through a built-in sensor. The smart bracelet exchanges data with the infusion monitoring system through wireless communication and reports the patient's status information (activity level).

[0092] The image acquisition device of this embodiment includes but is not limited to a camera, which is used to monitor the position of the patient on the bed in real time. After the camera uploads the data to the system, the system promptly determines whether the patient is in a dangerous position or has fallen out of bed, etc., and issues an early warning in a timely manner.

[0093] In this embodiment, the infusion monitoring system provides a user interface through a manual control strategy, allowing medical personnel to perform specific configuration of the blood pressure control strategy through the interface.

[0094] The systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit of blood pressure, as well as the growth rate π value of drug infusion and the upper and lower limits of drug speed are set through the user interface.

[0095] The manual control strategy also includes an authorization setting function, which allows medical personnel to choose whether to authorize the device to automatically adjust the infusion rate according to the preset control strategy.

[0096] When authorization is set, the blood pressure rate control strategy configured by the medical staff will be used to automatically adjust the infusion rate to maintain the blood pressure within the set range when changes in the user's blood pressure are monitored.

[0097] Specifically, the implementation of the manual control strategy includes the following steps:

[0098] First, medical staff set the basic values ​​of the blood pressure control strategy through the user interface of the infusion monitoring system, including the drug growth rate π value and the upper and lower limits of the drug speed.

[0099] Then, when the patient starts using pressor and antihypertensive drugs through an infusion pump device, the system regularly collects blood pressure data from the monitor and patient status information from the smart bracelet. The system calculates the appropriate infusion speed adjustment amount based on the current blood pressure status and medication type (antihypertensive or pressor) through the "blood pressure speed control logic".

[0100] The system then converts the calculated infusion speed adjustment amount into specific control instructions and sends them to the infusion pump to achieve automatic adjustment of the infusion speed.

[0101] Finally, through continuous monitoring, analysis and adjustment, a closed-loop control system is formed to achieve dynamic regulation of blood pressure.

[0102] In this embodiment, the AI ​​control strategy includes:

[0103] It is integrated with an AI intelligent analysis module, which is used to automatically generate the initial values ​​of the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value and upper and lower limits of drug speed according to the user's initial physiological parameters.

[0104] The AI ​​intelligent analysis module receives and processes the user's physiological parameter data, historical blood pressure data, and environmental factor data in real time, conducts continuous in-depth learning of the user's blood pressure data, and dynamically optimizes and adjusts the user's systolic blood pressure upper limit, diastolic blood pressure upper limit, systolic blood pressure lower limit, diastolic blood pressure lower limit, growth rate π value, and drug speed upper and lower limits.

[0105] The AI ​​intelligent analysis module also has the ability to dynamically adjust the blood pressure speed control strategy according to the user's real-time status changes to ensure the accuracy and effectiveness of blood pressure control.

[0106] Specifically, the implementation methods of AI control strategy include:

[0107] The AI ​​intelligent analysis module automatically generates the initial values ​​of the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and upper and lower limits of drug speed based on the user's initial physiological parameters. It also conducts continuous in-depth learning of the user's blood pressure data in combination with the user's real-time status, historical data, and environmental factors, and dynamically optimizes the patient's growth rate π value and upper and lower limits of drug speed.

[0108] When the patient starts to use infusion drugs (such as blood pressure-increasing and antihypertensive drugs) through the infusion device, the blood pressure data from the monitoring device and the user status information of the smart terminal are collected at regular intervals, and the optimized π value is obtained through the reinforcement learning strategy based on the current user's physiological parameters, medication type (antihypertensive or pressor drugs) and activity status.

[0109] According to the optimized π value, the corresponding infusion speed adjustment amount is calculated through the preset blood pressure speed control logic, and the adjustment amount is converted into a specific control instruction and sent to the infusion device to realize automatic adjustment of the infusion speed; wherein, by continuously monitoring the user's blood pressure data and status information, a closed-loop control system is formed to realize dynamic control of blood pressure.

[0110] In this embodiment, it is determined whether the current user's blood pressure value exceeds the set systolic upper limit, diastolic upper limit or is lower than the systolic lower limit, diastolic lower limit;

[0111] If the current blood pressure value exceeds or falls below the set limit, a preliminary infusion rate adjustment is calculated based on the degree of excess or fall, the drug speed increase π value, and the upper and lower limits of the drug speed;

[0112] Combined with the user status information from the smart terminal, the preliminary infusion speed adjustment amount is corrected to obtain a final infusion speed adjustment amount that is more in line with the user's actual condition;

[0113] Among them, the final infusion speed adjustment amount is converted into specific control instructions and sent to the infusion device to adjust the infusion speed in real time to ensure that the user's blood pressure is maintained within the set range.

[0114] Specifically, the infusion monitoring system of this embodiment is responsible for integrating devices such as infusion pumps, monitors, smart bracelets, and cameras to achieve data interaction and collaborative work between the devices, and specifically includes the following functions:

[0115] Speed ​​setting: The system has a built-in blood pressure control strategy configuration module, which provides two control strategies, including manual control strategy and AI control strategy:

[0116] Manual control strategy: Provide medical staff with blood pressure control strategy configuration, including setting the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, upper and lower limits of drug speed, and setting whether to authorize the device to automatically adjust the speed.

[0117] AI control strategy: The intelligent analysis module integrates AI algorithms (such as DeepSeek, etc.), which can automatically generate the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and initial values ​​of the upper and lower limits of drug speed according to the patient's physiological parameters. It can also combine the patient's real-time status, historical data and environmental factors to conduct continuous in-depth learning of the patient's blood pressure data, dynamically optimize the patient's systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and upper and lower limits of drug speed, and can set whether to authorize AI to automatically control the device speed.

[0118] Data analysis and regulation: The system's built-in control algorithm and data processing module can analyze the real-time collected blood pressure data, patient status information and camera data, and automatically adjust the working parameters of the infusion pump according to the preset control strategy to achieve dynamic control of blood pressure.

[0119] Blood pressure rate control strategy:

[0120] The user's blood pressure data and status information are sampled once at a certain time interval (5 minutes) to first determine whether the user is in a state of strenuous exercise.

[0121] If the user is in a state of strenuous exercise, the blood pressure speed control strategy will not be triggered and the current infusion speed will remain unchanged.

[0122] If the user is not in a state of strenuous exercise, the current blood pressure data is compared with the blood pressure value sampled last time, and the speed is adjusted according to the type of blood pressure medicine currently used by the infusion device. The specific adjustment rules are as follows:

[0123] When users take blood pressure medication:

[0124] If the user's current blood pressure is still higher than the previous blood pressure and exceeds the preset high pressure upper limit, the control speed is equal to the current speed multiplied by (1+π value), and the control speed shall not exceed the maximum speed of medication;

[0125] If the user's current blood pressure has dropped compared to the previous blood pressure and exceeds the preset high pressure warning value, the control speed is equal to the current speed multiplied by (1-π value), and the control speed shall not exceed the maximum speed of medication;

[0126] If the user’s blood pressure remains within the normal range for 60 consecutive minutes, the infusion is suspended;

[0127] When users take vasopressors:

[0128] If the user's current blood pressure is still lower than the previous blood pressure and exceeds the preset low pressure limit, the control speed is equal to the current speed multiplied by (1+π value), and the control speed shall not exceed the maximum speed of medication;

[0129] If the user's current blood pressure has increased compared to the previous blood pressure but has not reached the normal range or is still below a certain safety threshold of the low pressure lower limit, the control speed is equal to the current speed multiplied by (1-π value), and the control speed shall not exceed the maximum speed of medication;

[0130] If the user’s blood pressure remains within the normal range for 60 consecutive minutes, the infusion is suspended;

[0131] The π value is a configurable parameter, and its default value is 10%. The system provides a configuration interface to allow medical personnel to adjust the π value according to the patient's specific conditions and clinical needs.

[0132] An embodiment of an intelligent dynamic blood pressure control method based on infusion monitoring

[0133] like Figure 2 As shown, this embodiment provides an intelligent dynamic blood pressure control method based on infusion monitoring. The method uses the above-mentioned intelligent dynamic blood pressure control system based on infusion monitoring to perform dynamic blood pressure control, and includes the following steps:

[0134] Monitor the user's blood pressure data in real time through monitoring equipment, monitor the user's activity level through smart terminals, and monitor the user's location information through image acquisition devices;

[0135] The above data is uploaded to the infusion monitoring system; the infusion monitoring system is equipped with a wireless network receiving function, which is used to receive multi-source data from infusion equipment, monitoring equipment, intelligent terminals and image acquisition devices in real time; after receiving the raw data, the infusion monitoring system performs a preliminary screening of the raw data according to a preset custom device communication protocol to remove invalid data or redundant data; the infusion monitoring system verifies the data after the preliminary screening using a data verification algorithm in the custom device communication protocol;

[0136] The infusion monitoring system analyzes the real-time collected data according to the preset manual control strategy or AI control strategy, and automatically adjusts the working parameters of the infusion equipment according to the analysis results to achieve dynamic control of blood pressure.

[0137] In this embodiment, a system initialization and parameter setting step is also included:

[0138] Equipment installation and connection: First, install the infusion pump, monitor, and smart bracelet device according to the system requirements, and connect them to the infusion monitoring system wirelessly to ensure unimpeded data communication between the devices.

[0139] Parameter setting: On the speed control interface of the infusion monitoring system, medical staff set the blood pressure alarm threshold, upper and lower limits of drug infusion speed, and the speed increase value π according to the patient's specific situation and doctor's advice, or the AI ​​algorithm automatically generates initial values ​​such as the blood pressure alarm threshold, upper and lower limits of drug infusion speed, and speed increase value π, and sets key parameters such as whether to authorize. These parameters will serve as the basis for subsequent analysis and regulation of the system.

[0140] After determining that the user is not in a state of strenuous exercise, further determining whether the user's real-time blood pressure data exceeds a preset blood pressure alarm threshold;

[0141] If the user's real-time blood pressure data exceeds the preset blood pressure upper limit alarm threshold, the speed control logic is triggered, and the adjustment amount for reducing the infusion speed is automatically calculated according to the preset control parameters and control logic;

[0142] If the user's real-time blood pressure data is lower than the preset lower blood pressure alarm threshold, the speed control logic will also be triggered, and the adjustment amount for increasing the infusion speed will be automatically calculated based on the preset control parameters and control logic;

[0143] Generate a control instruction corresponding to the calculated infusion speed adjustment amount, and send the control instruction to the infusion device to adjust the infusion speed to a suitable level.

[0144] For example, if the upper alarm threshold of blood pressure is 150, when the blood pressure value collected by the system exceeds 150, the speed control logic will be automatically triggered.

[0145] For example, if the lower limit alarm threshold of blood pressure is 110, when the blood pressure value collected by the system is lower than 110, the speed control logic will be automatically triggered.

[0146] In this embodiment, the infusion monitoring system converts the control speed into communication data according to the calculated control speed and the customized device communication protocol, and sends the communication data to the infusion device through the WI-FI wireless network;

[0147] After receiving the communication data sent by the infusion monitoring system, the infusion device verifies and analyzes the data according to the device communication protocol to confirm the validity of the control instruction;

[0148] The infusion device automatically adjusts its infusion speed according to the analyzed control instructions, thereby realizing dynamic control of the user's blood pressure. During the control process, the infusion monitoring system continuously monitors the changes in the user's blood pressure and adjusts the infusion speed as needed to ensure that the user's blood pressure is stable within the preset safety range.

[0149] When the user's blood pressure exceeds the preset safety range, or the user is in a dangerous position, the infusion monitoring system triggers an alarm mechanism to promptly remind medical staff to pay attention to the user's condition through sound, light or interface prompts. At the same time, the system will also record every adjustment operation, the patient's blood pressure changes and camera monitoring data in detail to provide data support for clinical decision-making.

[0150] In this embodiment, the infusion monitoring system receives data from the infusion pump, monitor, smart bracelet and camera in real time, and performs preliminary processing, such as data filtering, cleaning, and verification, to ensure the accuracy and reliability of the data. The above collected data is automatically triggered by the reinforcement learning control strategy according to the current blood pressure value, predicted blood pressure value, medication type, patient physiological parameters, and patient activity level, and the π value is optimized to adapt to individual differences.

[0151] Specifically, according to the user's physiological parameters, medication type and activity status, an environmental model for reinforcement learning is constructed, including the following steps:

[0152] In the environment model, a state space is defined to map the user's physiological parameters, medication status, and activity status into state representations in reinforcement learning;

[0153] Define an action space and use possible medication adjustments as actions in reinforcement learning;

[0154] Define the reward function and set the reward mechanism according to the treatment goal to reflect the impact of different actions on the treatment effect;

[0155] Use policy π to represent the probability distribution of choosing an action in a given state;

[0156] Collect sample data, including states, actions, and rewards, by interacting with the environment;

[0157] Using the collected sample data, the reinforcement learning algorithm is used to optimize the strategy π. During the optimization process, according to the strategy improvement theorem, the strategy π is iteratively updated so that it can select the action with the maximum expected reward in the current state.

[0158] According to the optimized strategy π, a personalized dosage adjustment plan is generated in combination with the current user's physiological parameters, medication type, and activity status;

[0159] Conduct strategy evaluation on the generated dose adjustment scheme, verify its effectiveness through simulation or actual application, and further optimize and adjust the strategy π based on the evaluation results;

[0160] The method for obtaining the optimized strategy π value through the reinforcement learning strategy specifically includes the following steps:

[0161] State representation: Encoding the user’s physiological parameters, medication status, and activity status into a state vector in reinforcement learning;

[0162] Action selection: Based on the current state, use strategy π to select the action with the maximum expected reward, i.e., the dosage adjustment plan;

[0163] Reward calculation: According to the treatment goal, the reward value obtained after performing the action is calculated to evaluate the effect of the action;

[0164] Strategy update: Based on the reward value and state transition probability, a reinforcement learning algorithm is used to update the parameters of the strategy π to maximize the long-term expected reward.

[0165] In summary, the blood pressure management system and method integrating intelligent monitoring and automatic control proposed in the present invention realize dynamic and precise control of blood pressure through advanced system architecture, data processing algorithm, automatic control strategy, motion status monitoring technology and AI functional module, which not only improves the accuracy and safety of blood pressure management, but also improves medical efficiency and patient experience.

[0166] Furthermore, the dynamic blood pressure monitoring system of the present invention is composed of core components such as an infusion pump, a monitor, a smart bracelet, a camera, and an infusion monitoring system. Any system based on this system architecture that replaces or adds components with the same or similar functions to achieve dynamic blood pressure monitoring and regulation falls within the scope of protection of the present invention.

[0167] Furthermore, the present invention performs infusion detection and non-invasive continuous blood pressure monitoring through infusion pumps, smart bracelets, monitors, cameras and other devices, and transmits data to the infusion monitoring system. Any system that uses similar or equivalent data acquisition technology (such as wired monitoring, multi-parameter monitoring, etc.) and transmission methods (such as Bluetooth, Wi-Fi, wired connection, etc.) to achieve real-time and accurate blood pressure data transmission is deemed to fall within the scope of protection of the present invention.

[0168] Furthermore, the control algorithms and data processing modules in the system used to process and analyze blood pressure data, patient status information and camera data, including their algorithm logic, parameter settings and optimization methods, etc., are important technical secrets and competitive advantages of the present invention and need to be protected.

[0169] Furthermore, the present invention automatically adjusts the working parameters of the infusion pump through the infusion monitoring system to achieve dynamic regulation of blood pressure and trigger an alarm mechanism when necessary. Any system based on similar principles that automatically or semi-automatically adjusts treatment parameters to achieve stable blood pressure control and has an alarm function is covered within the scope of protection of the present invention.

[0170] Furthermore, through devices such as cameras and smart bracelets, the patient's state of rest, light activity, and intense exercise can be monitored in real time, and the blood pressure control strategy can be adjusted according to this state information. This technical point not only improves the accuracy and safety of blood pressure management, but is also one of the important features that distinguishes this invention from other similar products, and therefore needs to be protected.

[0171] Furthermore, the present invention provides an intuitive and easy-to-use user interface, which is convenient for medical staff to set parameters, view data and system status. Any technical solution that improves or optimizes the user interface design and enhances the user interaction experience, as long as its technical essence is consistent with the present invention, shall fall within the protection scope of the present invention.

[0172] The protection scope of the present invention is broad, covering all aspects of the dynamic blood pressure monitoring system and its equivalent replacement or change. Any improvement or innovation made by any person skilled in the art within the technical scope disclosed by the present invention, based on the technical solution and inventive concept of the present invention, shall be protected by the present invention as long as its technical essence is consistent with the present invention and can achieve similar or better technical effects.

[0173] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0174] The above-mentioned embodiments are only preferred embodiments of the present invention and cannot be used to limit the scope of protection of the present invention. Any non-substantial changes and substitutions made by technicians in this field on the basis of the present invention shall fall within the scope of protection required by the present invention.

Claims

1. An intelligent dynamic blood pressure control system based on infusion monitoring, characterized in that: include: an infusion device configured to control the infusion rate of the drug and to exchange data with the infusion monitoring system via a wireless communication protocol so as to automatically adjust the infusion rate according to the received real-time blood pressure data and the regulation strategy; A monitoring device configured to monitor the user's physiological data in real time and send the monitored physiological data to the infusion monitoring system via a wireless communication protocol; an intelligent terminal having a built-in sensor configured to automatically identify the activity level of a user and transmit the user's status information to the infusion monitoring system via wireless communication; An image acquisition device configured to monitor the user's position information in real time and upload the monitoring data to the infusion monitoring system to determine the user's status; The infusion monitoring system has a built-in blood pressure control strategy configuration module, which includes manual control strategies and AI control strategies. It analyzes the real-time collected physiological data, user status information and user location information, and automatically adjusts the working parameters of the infusion device according to the preset control strategy to achieve intelligent dynamic control of the user's blood pressure.

2. The system according to claim 1, characterized in that: The manual control strategy provides a user interface, allowing medical personnel to configure the blood pressure control strategy through the interface; Setting the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit of blood pressure, and the growth rate π value of drug infusion and the upper and lower limits of drug speed through the user interface; The manual control strategy also includes an authorization setting function, which allows medical personnel to choose whether to authorize the device to automatically adjust the infusion rate according to the preset control strategy; When authorization is set, the blood pressure rate control strategy configured by the medical staff will be used to automatically adjust the infusion rate to maintain the blood pressure within the set range when changes in the user's blood pressure are monitored.

3. The system according to claim 1, characterized in that The AI ​​control strategy includes: It is integrated with an AI intelligent analysis module, which is used to automatically generate the initial values ​​of the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value and drug speed upper and lower limits of blood pressure according to the user's initial physiological parameters; The AI ​​intelligent analysis module receives and processes the user's physiological parameter data, historical blood pressure data, and environmental factor data in real time, performs continuous in-depth learning on the user's blood pressure data, and dynamically optimizes and adjusts the user's systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and drug speed upper and lower limits. The AI ​​intelligent analysis module also has the ability to dynamically adjust the blood pressure speed control strategy according to the user's real-time status changes to ensure the accuracy and effectiveness of blood pressure control.

4. The system according to claim 1, characterized in that The implementation of the AI ​​control strategy specifically includes: The AI ​​intelligent analysis module automatically generates the initial values ​​of the systolic upper limit, diastolic upper limit, systolic lower limit, diastolic lower limit, growth rate π value, and upper and lower limits of the drug speed according to the user's initial physiological parameters, and conducts continuous in-depth learning of the user's blood pressure data in combination with the user's real-time status, historical data, and environmental factors; When the drug infusion begins, the blood pressure data from the monitoring device and the user status information of the smart terminal are collected regularly. Based on the current user's physiological parameters, medication type, and activity status, the optimized π value is obtained through the reinforcement learning strategy. According to the optimized π value, the corresponding infusion speed adjustment amount is calculated through the preset blood pressure speed control logic, and the adjustment amount is converted into a specific control instruction and sent to the infusion device to realize automatic adjustment of the infusion speed; wherein, by continuously monitoring the user's blood pressure data and status information, a closed-loop control system is formed to realize dynamic control of blood pressure.

5. The system according to claim 1, characterized in that: Determine whether the current user's blood pressure value exceeds the set systolic upper limit, diastolic upper limit or is lower than the systolic lower limit, diastolic lower limit; If the current blood pressure value exceeds or falls below the set limit, a preliminary infusion rate adjustment is calculated based on the degree of excess or fall, the drug speed increase π value, and the upper and lower limits of the drug speed; Combined with the user status information from the smart terminal, the preliminary infusion speed adjustment amount is corrected to obtain a final infusion speed adjustment amount that is more in line with the user's actual condition; The final infusion speed adjustment amount is converted into a specific control instruction and sent to the infusion device to adjust the infusion speed in real time to ensure that the user's blood pressure is maintained within the set range.

6. The system according to claim 4, characterized in that The blood pressure velocity regulation strategy includes: The user's blood pressure data and status information are sampled at regular intervals to first determine whether the user is in a state of strenuous exercise; If the user is in a state of intense exercise, the blood pressure speed control strategy will not be triggered and the current infusion speed will remain unchanged; If the user is not in a state of strenuous exercise, the current blood pressure data is compared with the blood pressure value sampled last time, and the speed is adjusted according to the type of blood pressure medicine currently used by the infusion device. The specific adjustment rules are as follows: When users take blood pressure medication: If the user's current blood pressure is still higher than the previous blood pressure and exceeds the preset high pressure upper limit, the control speed is equal to the current speed multiplied by (1+π value), and the control speed shall not exceed the maximum speed of medication; If the user's current blood pressure has dropped compared to the previous blood pressure and exceeds the preset high pressure warning value, the control speed is equal to the current speed multiplied by (1-π value), and the control speed shall not exceed the maximum speed of medication; If the user’s blood pressure remains within the normal range for 60 consecutive minutes, the infusion is suspended; When users take vasopressors: If the user's current blood pressure is still lower than the previous blood pressure and exceeds the preset low pressure limit, the control speed is equal to the current speed multiplied by (1+π value), and the control speed shall not exceed the maximum speed of medication; If the user's current blood pressure has increased compared to the previous blood pressure but has not reached the normal range or is still below a certain safety threshold of the low pressure lower limit, the control speed is equal to the current speed multiplied by (1-π value), and the control speed shall not exceed the maximum speed of medication; If the user’s blood pressure remains within the normal range for 60 consecutive minutes, the infusion is suspended; The value of π is a configurable parameter, and its default value is 10%.

7. An intelligent dynamic blood pressure control method based on infusion monitoring, characterized in that: The method is to use an intelligent dynamic blood pressure control system based on infusion monitoring as described in any one of claims 1 to 6 to perform dynamic blood pressure control, and comprises the following steps: Monitor the user's blood pressure data in real time through monitoring equipment, monitor the user's activity level through smart terminals, and monitor the user's location information through image acquisition devices; The above data is uploaded to the infusion monitoring system; the infusion monitoring system is equipped with a wireless network receiving function, which is used to receive multi-source data from infusion equipment, monitoring equipment, intelligent terminals and image acquisition devices in real time; after receiving the raw data, the infusion monitoring system performs a preliminary screening of the raw data according to a preset custom device communication protocol to remove invalid data or redundant data; the infusion monitoring system verifies the data after the preliminary screening using a data verification algorithm in the custom device communication protocol; The infusion monitoring system analyzes the real-time collected data according to the preset manual control strategy or AI control strategy, and automatically adjusts the working parameters of the infusion equipment according to the analysis results to achieve dynamic control of blood pressure.

8. The method according to claim 7, characterized in that: After determining that the user is not in a state of strenuous exercise, further determining whether the user's real-time blood pressure data exceeds a preset blood pressure alarm threshold; If the user's real-time blood pressure data exceeds the preset blood pressure upper limit alarm threshold, the speed control logic is triggered, and the adjustment amount for reducing the infusion speed is automatically calculated according to the preset control parameters and control logic; If the user's real-time blood pressure data is lower than the preset lower blood pressure alarm threshold, the speed control logic will also be triggered, and the adjustment amount for increasing the infusion speed will be automatically calculated based on the preset control parameters and control logic; Generate a control instruction corresponding to the calculated infusion speed adjustment amount, and send the control instruction to the infusion device to adjust the infusion speed to a suitable level.

9. The method according to claim 7, characterized in that: The infusion monitoring system converts the control speed into communication data according to the calculated control speed and the customized device communication protocol, and sends the communication data to the infusion device through the WI-FI wireless network; After receiving the communication data sent by the infusion monitoring system, the infusion device verifies and analyzes the data according to the device communication protocol to confirm the validity of the control instruction; The infusion device automatically adjusts its infusion speed according to the analyzed control instructions, thereby achieving dynamic control of the user's blood pressure; During the regulation process, the infusion monitoring system continuously monitors the user's blood pressure changes and adjusts the infusion rate as needed to ensure that the user's blood pressure is stable within the preset safety range; When the user's blood pressure exceeds the preset safety range, or the user is in a dangerous position, the infusion monitoring system triggers the alarm mechanism to promptly alert medical staff to the user's condition.

10. The method according to claim 7 or 8, characterized in that: Build an environmental model for reinforcement learning based on the user's physiological parameters, medication type, and activity status; In the environment model, a state space is defined to map the user's physiological parameters, medication status, and activity status into state representations in reinforcement learning; Define an action space and use possible medication adjustments as actions in reinforcement learning; Define the reward function and set the reward mechanism according to the treatment goal to reflect the impact of different actions on the treatment effect; Use policy π to represent the probability distribution of choosing an action in a given state; Collect sample data, including states, actions, and rewards, by interacting with the environment; Using the collected sample data, the reinforcement learning algorithm is used to optimize the strategy π. During the optimization process, according to the strategy improvement theorem, the strategy π is iteratively updated so that it can select the action with the maximum expected reward in the current state. According to the optimized strategy π, a personalized dosage adjustment plan is generated in combination with the current user's physiological parameters, medication type, and activity status; Conduct a strategy evaluation on the generated dose adjustment scheme, verify its effectiveness through simulation or actual application, and further optimize and adjust the strategy π based on the evaluation results.

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