Intelligent blood sampling robot system and method based on medical large model

Abstract

The invention relates to an intelligent blood sampling robot system and method based on a medical large model. According to the system, multiple technologies such as vein recognition, individualized blood sampling scheme making and real-time monitoring and adjusting are comprehensively applied, and the accuracy of the blood sampling process and the comfort level of a patient are improved. The system comprises a data acquisition module, a vein recognition module, an individualized blood sampling scheme making module, a blood sampling execution module and a real-time monitoring module. The data acquisition module is used for acquiring a vein image, health data and real-time physiological data of a patient; the vein recognition module analyzes vein image data through a large medical model and accurately positions a blood sampling position; the individualized blood sampling scheme making module makes an optimal blood sampling scheme by using a medical large model according to the health data of the patient; the blood sampling execution module controls the blood sampling robot to perform blood sampling operation according to a personalized scheme; the real-time monitoring module monitors the physiological reaction of a patient in the blood sampling process, data analysis is carried out through a medical large model, and the blood sampling strategy is adjusted.

Description

Technical Field

[0001] The present invention relates to the field of medical equipment technology, and in particular to an intelligent blood sampling robot system based on a medical large model and an application method thereof. The system combines the deep learning capabilities of the medical large model with a variety of advanced sensing technologies to achieve accurate identification and positioning of the patient's veins, formulation of personalized blood sampling plans, and real-time monitoring and adjustment of the blood sampling process, thereby improving the success rate of blood sampling and the comfort of patients. The system is suitable for scenarios such as hospitals and physical examination centers that require efficient and accurate blood sampling. Background Art

[0002] Blood collection is an essential operation in medical diagnosis and treatment, but the traditional manual blood collection method relies on the experience and skills of medical staff and has the following problems:

[0003] 1. Lack of accuracy: Due to large individual differences, the location and visibility of veins in different patients are different. Especially when the veins are not obvious or the vascular conditions are poor, the accuracy of blood collection is difficult to guarantee, which can easily lead to multiple punctures and increase the patient's pain and discomfort.

[0004] 2. Inefficiency: Manual blood collection takes a long time, especially when there are a large number of patients, which can easily lead to long waiting times and affect the efficiency of medical services.

[0005] 3. Strong reliance on skills: Manual blood collection requires high skills from the operator. Novice or inexperienced medical staff are prone to operating errors, which affects the quality of blood collection.

[0006] 4. Poor patient experience: Due to failed or repeated punctures, patients have a poor blood collection experience, which may cause fear and resistance to blood collection.

[0007] 5. There is a risk of cross infection.

[0008] With the development of artificial intelligence and robotics, intelligent medical equipment has shown great potential in improving the quality and efficiency of medical services. In particular, intelligent systems based on large medical models can perform high-precision vein recognition and personalized plan formulation based on a large amount of medical data through deep learning and multimodal data fusion technology, greatly improving the shortcomings of traditional blood collection methods.

[0009] At present, some intelligent blood collection robots have been launched, but most of these devices rely on a single sensor or simple image processing technology, and the accuracy of vein recognition and the intelligence level of the system still have a lot of room for improvement. At the same time, the lack of personalized blood collection plans and the ability to monitor and adjust in real time leads to insufficient flexibility and patient comfort during the blood collection process.

[0010] Therefore, an intelligent blood collection robot system and method based on a medical big model is proposed. By combining a variety of advanced sensing technologies and deep learning algorithms, high-precision vein recognition, personalized blood collection plan formulation and real-time monitoring and adjustment can be achieved, which has important practical application value and market prospects. Summary of the invention

[0011] In order to solve the above problems, the purpose of the present invention is to provide an intelligent blood sampling robot system and method based on a large medical model.

[0012] Step 1: Data collection: Use the data collection module to obtain the patient's venous images, health data and real-time physiological data; Step 2: Vein recognition: Analyze the vein image data through the vein recognition module to identify and locate the best blood collection position; Step 3: Individualized plan formulation: Generate a personalized blood collection plan based on the patient's health data using the individualized blood collection plan formulation module; Step 4: Blood collection execution: Control the blood collection robot to perform blood collection according to the personalized plan through the blood collection execution module; Step 5: Real-time monitoring and adjustment: During the blood collection process, the patient's physiological response is monitored through the real-time monitoring module, and the blood collection strategy is adjusted in real time.

[0013] Compared with the prior art, the present invention has the following beneficial effects:

[0014] 1. Improve the accuracy of blood collection: Through multimodal data fusion technology, combined with infrared sensors, ultrasonic sensors and image acquisition equipment, the medical big model can accurately identify and locate the patient's vein position, significantly improve the accuracy of blood collection, and reduce the probability of puncture failure.

[0015] 2. Personalized blood collection plan: The system can formulate a personalized blood collection plan based on the patient's health data and historical medical records, including optimized blood collection path and force control, to ensure the safety and effectiveness of the blood collection process and improve the patient's blood collection experience.

[0016] 3. Real-time monitoring and dynamic adjustment: During the blood collection process, the patient's physiological reactions (such as blood flow velocity, blood pressure, etc.) are monitored in real time, and the data is analyzed through the medical big model. The blood collection strategy is adjusted in real time to ensure the smooth progress of the blood collection process and further improve the success rate of blood collection.

[0017] 4. Improve work efficiency: The intelligent blood collection robot system reduces the dependence on the operator's experience and skills, can complete the blood collection operation in a shorter time, and improves the efficiency of medical services. It is particularly suitable for medical scenarios with a large number of patients and high work pressure.

[0018] 5. Reduce patient discomfort: Due to the improvement of blood collection accuracy and success rate, the number of punctures and the patient's pain are reduced, the patient's blood collection experience is improved, and the patient's fear and resistance to blood collection are alleviated.

[0019] 6. Equipment stability and reliability: The system has fault detection and self-repair functions. By analyzing the equipment operation data, it can predict possible failures and perform preventive maintenance in advance to ensure the stability and reliability of the equipment and reduce blood collection interruptions and operational errors caused by equipment failures.

[0020] 7. Improve medical quality: The intelligent blood collection robot system not only improves the standardization and consistency of blood collection operations, but also continuously optimizes blood collection plans through data analysis and machine learning, providing higher quality services for medical institutions.

[0021] 8. Wide applicability: The system is suitable for various medical institutions, including hospitals, physical examination centers, clinics, etc. It can work efficiently in different environments and conditions and has broad application prospects and market demand. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method.

[0024] Figure 2 It is a schematic diagram of the equipment for three-dimensional imaging, ultrasonic imaging and puncture mechanism of the method of the present invention.

[0025] Figure 3 Schematic diagram of automatic identification and positioning of blood vessels in ultrasound images. Implementation

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] See also Figure 1 As shown, the present invention provides an intelligent blood sampling robot system and method based on a medical large model, comprising:

[0028] Step 1: Data collection: Use the data collection module to obtain the patient's venous images, health data and real-time physiological data;

[0029] The data acquisition module is used to obtain the patient's venous imaging data, health data and real-time physiological data in order to provide necessary information support for the intelligent blood collection robot system. This module includes the following sub-modules: A1. Infrared sensor:

[0030] Purpose: To detect infrared images of the patient's veins, especially for patients whose veins are not obvious.

[0031] Function: Capture the distribution of subcutaneous veins through infrared imaging technology and provide clear images of veins.

[0032] A2. Ultrasonic sensor:

[0033] Purpose: To obtain ultrasound images of the patient's veins, especially for patients who need in-depth detection of vein depth and location.

[0034] Function: Generates real-time images of veins through ultrasonic imaging technology to help identify the location and depth of veins.

[0035] A3. 3D image acquisition equipment:

[0036] Purpose: To obtain visible light images of a patient's veins.

[0037] Function: Captures images of the patient's skin surface through a high-resolution camera to assist in vein identification and positioning.

[0038] A4. Health data collection:

[0039] Purpose: Collect historical medical records and health information of patients.

[0040] Function: By connecting with the hospital information system (HIS), electronic health record (EHR) and laboratory information management system (LIMS), it can obtain the patient's comprehensive health data, including past medical history, medication use record, allergy history, etc.

[0041] A5. Real-time physiological data collection:

[0042] Purpose: To monitor the patient's physiological parameters during blood collection.

[0043] Function: Monitor the patient's real-time physiological data such as blood pressure, heart rate, and blood oxygen saturation through sensors, and provide data support for real-time adjustment of blood collection strategies.

[0044] Step 2: Vein recognition: Analyze the vein image data through the vein recognition module to identify and locate the best blood collection position;

[0045] The vein recognition module is one of the core components of the intelligent blood collection robot system. It is used to analyze the collected vein image data and identify and locate the best blood collection position. The module combines advanced image processing technology and deep learning algorithms to achieve high-precision vein recognition and positioning.

[0046] B1. Data preprocessing: After acquiring the venous image data, preprocessing is performed to enhance the image quality, including image denoising, contrast enhancement, grayscale processing, etc.

[0047] B2. Multimodal data fusion: Infrared images, ultrasound images and visible light images are fused to generate comprehensive venous imaging data.

[0048] B3. Vein detection and segmentation: Use deep learning algorithms to perform vein detection and segmentation on the fused image data to generate a binary image of the vein.

[0049] B4. Vein feature extraction: Extract key features of veins from binary images, including morphological features and geometric features.

[0050] B5. Vein matching and blood collection point positioning: Based on the extracted vein features, a matching algorithm is used to perform vein matching and positioning to determine the best blood collection point.

[0051] B6. Dynamic adjustment and optimization: During the blood collection process, real-time physiological data is used to dynamically adjust and optimize the vein recognition results to ensure the accuracy and safety of the blood collection operation.

[0052] Step 3: Individualized plan formulation: Generate a personalized blood collection plan based on the patient's health data using the individualized blood collection plan formulation module; The individualized blood collection plan formulation module is used to generate a personalized blood collection plan based on the patient's health data using a medical big model. This module analyzes the patient's historical medical records, current health status, and real-time physiological data to formulate the optimal blood collection path and force control plan to ensure the safety and effectiveness of the blood collection process.

[0053] C1. Health data collection and analysis: Obtain the patient's historical health data, including past medical history, medication use records, allergy history, etc.

[0054] Data were obtained through hospital information systems (HIS), electronic health records (EHR), and laboratory information management systems (LIMS).

[0055] C2 cleans and integrates the data to form a comprehensive health profile of the patient.

[0056] Vein feature analysis: Based on the vein feature data provided by the vein recognition module, the morphology and status of the veins are analyzed.

[0057] Determine the depth, diameter, blood flow velocity and other parameters of the vein to provide a basis for the formulation of personalized plans.

[0058] C4. Personalized blood collection path planning: Combine vein characteristics and patient health data to develop a personalized blood collection path.

[0059] Utilize the path planning algorithm to generate the optimal blood collection path, avoid key areas, and reduce patient discomfort.

[0060] C5. Generation of force control scheme: Develop an appropriate blood sampling intensity control plan based on the patient's venous characteristics and real-time physiological data.

[0061] Determine the appropriate puncture force and needle insertion angle to ensure a smooth and safe blood collection process.

[0062] C6. Dynamic adjustment and optimization: During the blood collection process, the patient's physiological reactions are monitored in real time to obtain data such as blood pressure and blood flow rate.

[0063] Based on real-time data, the blood collection path and force control plan are dynamically adjusted to ensure the accuracy and safety of the blood collection operation.

[0064] Step 4: Blood collection execution: Control the blood collection robot to perform blood collection according to the personalized plan through the blood collection execution module; Nine-eye calibration motion control algorithm:

[0065] The blood collection execution module is responsible for controlling the intelligent blood collection robot to perform the actual blood collection operation according to the personalized blood collection plan. This module combines precise mechanical control technology and real-time feedback mechanism to ensure the efficiency, safety and patient comfort of the blood collection process.

[0066] The blood collection execution module is responsible for controlling the intelligent blood collection robot to perform the actual blood collection operation according to the personalized blood collection plan. This module combines precise mechanical control technology and real-time feedback mechanism to ensure the efficiency, safety and patient comfort of the blood collection process.

[0067] D1. Robotic arm initialization:

[0068] Start the robotic arm control system and perform self-check and calibration to ensure that all components are operating normally.

[0069] Set the initial position and operating parameters according to the personalized blood collection plan.

[0070] D2. Needle positioning and puncture:

[0071] According to the optimal blood collection position provided by the vein recognition module, the robotic arm is controlled to move the needle to the target position.

[0072] The needle angle and force are adjusted through the real-time feedback mechanism to ensure accurate vein puncture.

[0073] D3. Blood collection:

[0074] Control the blood collection device to automatically collect blood, and monitor the blood collection volume and flow rate in real time.

[0075] According to the patient's real-time physiological data (such as blood flow velocity, pressure, etc.), the blood collection parameters are dynamically adjusted to ensure a smooth and efficient blood collection process.

[0076] D4. Real-time feedback and adjustment:

[0077] During the blood collection process, sensors are used to monitor the blood collection operation in real time to obtain the puncture position, force and the patient's physiological response.

[0078] Based on the feedback data, the operating parameters of the robotic arm are dynamically adjusted to ensure that the blood collection process is safe and effective and reduce patient discomfort.

[0079] D5. Complete blood collection and withdrawal:

[0080] After blood collection is completed, the robotic arm is controlled to safely withdraw the needle and automatically disinfect and recycle it.

[0081] The collected blood samples are packaged and labeled to ensure the accuracy and sterility of the samples.

[0082] D6. Safety assurance and emergency response:

[0083] During the blood collection process, an emergency stop and automatic retraction mechanism are set to ensure that the operation can be stopped quickly in unexpected situations to protect the safety of patients.

[0084] Use aseptic operation procedures to prevent infection risks and ensure the safety and hygiene of the blood collection process.

[0085] Step 5: Real-time monitoring and adjustment: During the blood collection process, the patient's physiological response is monitored through the real-time monitoring module, and the blood collection strategy is adjusted in real time.

[0086] The real-time monitoring and adjustment module is a key part of the intelligent blood collection robot system. It is used to monitor the patient's physiological response during the blood collection process and dynamically adjust the blood collection strategy based on real-time data. This module combines sensor technology and the data analysis capabilities of medical big models to ensure the safety, effectiveness and comfort of the blood collection process.

[0087] E1. Initialization and monitoring startup:

[0088] Start the real-time monitoring module, initialize each sensor, and ensure the normal operation of the monitoring system.

[0089] Start real-time monitoring of the patient's blood pressure, heart rate, blood flow velocity, blood oxygen saturation and other physiological parameters.

[0090] E2.Data collection and transmission:

[0091] The patient's physiological data is continuously collected through sensors and transmitted to the central control system in real time.

[0092] Ensure the stability and low latency of data transmission and guarantee real-time performance.

[0093] E3. Real-time data analysis:

[0094] The central control system uses medical big models to analyze real-time data and detect changes and abnormalities in physiological parameters.

[0095] Based on the analysis results, determine whether the blood collection operation needs to be adjusted.

[0096] E4. Dynamic adjustment strategy generation:

[0097] When abnormal physiological reactions are detected or operation optimization is required, corresponding dynamic adjustment strategies are generated.

[0098] Adjustment strategies include modifying the needle angle, adjusting the puncture force, changing the blood collection speed, etc.

[0099] E5. Feedback control and execution:

[0100] The dynamic adjustment strategy is fed back to the robotic arm control system and the blood collection device to adjust the operating parameters in real time.

[0101] Through the closed-loop control mechanism, the rapid execution of adjustment strategies is ensured to maintain the smoothness and safety of the blood collection process.

[0102] E6. Continuous monitoring and optimization:

[0103] During the entire blood collection process, the patient's physiological parameters are continuously monitored, and the data is constantly analyzed and the blood collection operation is optimized.

[0104] Based on the patient's real-time physiological response, multiple dynamic adjustments are made to ensure the best blood collection effect.

[0105] E7.Exception handling and safety assurance:

[0106] If serious abnormal conditions are monitored (such as a sudden rise in the patient's blood pressure, abnormal heart rate, etc.), the emergency plan will be immediately activated and the blood collection operation will be suspended.

[0107] Notify medical staff to intervene and ensure patient safety.

Claims

1. An intelligent blood sampling robot system based on a medical large model, comprising: 1) Data acquisition module, used to collect patients’ venous imaging data, health data and real-time physiological data; 2) A vein recognition module, which analyzes the vein image data through a medical big model to identify and locate the best blood collection position; 3) A personalized blood collection plan formulation module, which formulates a personalized blood collection plan based on the patient's health data and using a medical big model; 4) A blood collection execution module, which controls the blood collection robot to perform the blood collection operation according to the personalized blood collection plan; 5) Real-time monitoring module: monitors the patient's physiological response during the blood collection process, analyzes data through medical big models, and adjusts the blood collection strategy in real time.

2. The system according to claim 1, wherein the data acquisition module comprises an infrared sensor, an ultrasonic sensor and an image acquisition device.

3. The system according to claim 1, wherein the vein recognition module processes the vein image data through a deep learning algorithm to improve the accuracy of vein recognition.

4. The system according to claim 1, wherein the individualized blood collection plan formulation module generates an optimized blood collection path and force control plan by analyzing the patient's historical medical data and real-time health data.

5. A system according to claim 1, wherein the real-time monitoring module uses sensor data, including blood flow velocity and blood pressure, to adjust the operating parameters of the blood collection robot in real time.

6. The system according to claim 1 further comprises a fault detection and self-repair module, which predicts possible faults and performs preventive maintenance by analyzing equipment operation data.

7. The system according to claim 1, wherein the medical big model is based on multimodal data fusion technology, integrating data from hospital information system (HIS), electronic health record (EHR) and laboratory information management system (LIMS).

8. An application method of an intelligent blood sampling robot system based on a medical large model, comprising the following steps: Step 1: Data collection: Use the data collection module to obtain the patient's venous images, health data and real-time physiological data ; Step 2: Vein recognition: Analyze vein image data through the vein recognition module to identify and locate the best blood collection position ; Step 3: Individualized plan formulation: Generate a personalized blood collection plan based on the patient's health data using the individualized blood collection plan formulation module; Step 4: Blood collection execution: The blood collection execution module controls the blood collection robot to perform blood collection operations according to the personalized plan. Nine-eye calibration motion control algorithm: ; Step 5: Real-time monitoring and adjustment: During the blood collection process, the patient's physiological response is monitored through the real-time monitoring module, and the blood collection strategy is adjusted in real time.

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