Intelligent anesthesia system

Abstract

The invention provides an intelligent anesthesia system which is characterized in that a medical record collection module collects medical record data of a patient, and a scheme making module performs anesthesia risk prediction according to the medical record data and makes an initial anesthesia scheme; the monitoring and collecting module continuously collects anesthesia monitoring data in the anesthesia process; the analysis processing module analyzes the anesthesia monitoring data to obtain a real-time analysis result; the anesthesia adjusting module adjusts an anesthesia scheme based on the real-time analysis result, and sends the adjusted anesthesia scheme to the anesthesia device; the mechanical arm control module generates a mechanical arm auxiliary instruction based on the real-time analysis result and sends the mechanical arm auxiliary instruction to the mechanical arm device; when the anesthesia device receives the adjusted anesthesia scheme, the anesthesia device doses medicine to the patient according to the adjusted anesthesia scheme; and the mechanical arm device executes corresponding auxiliary operation after receiving the mechanical arm auxiliary instruction. Intelligentization and automation of the anesthesia process can be achieved, the accuracy of anesthetic medication is improved, and the risk caused by insufficient or excessive anesthetic is reduced.

Description

Technical Field

[0001] The present invention relates to the field of medical detection auxiliary technology, and in particular to an intelligent anesthesia system. Background Art

[0002] With the increasing incidence of digestive system diseases, the demand for painless gastroenteroscopy is rapidly increasing in clinical practice. In China, up to 100 million people undergo gastroenteroscopy each year. This figure not only reflects the public's growing emphasis on health examinations and early disease detection, but also reveals the tremendous pressure on existing medical resources.

[0003] Currently, the number of anesthesiologists and anesthesiologists falls far short of market demand, making it difficult for many hospitals to provide timely and effective painless gastroenteroscopy services. Furthermore, existing anesthesia technology also has significant deficiencies in accuracy. Typically, anesthesiologists rely on monitoring physiological indicators such as the patient's blood pressure, heart rate, and body movement response to determine whether additional anesthetic drugs are needed. However, this method is highly subjective and easily affected by various factors, resulting in inaccurate control of anesthesia depth.

[0004] When anesthesia is insufficient, the patient may struggle due to pain, which not only increases the difficulty of endoscopic operation, but may also lead to serious complications such as gastrointestinal perforation; on the contrary, if anesthesia is excessive, it will cause the risk of delayed awakening and even damage to important organs. Summary of the Invention

[0005] Based on the above problems, the present invention provides an intelligent anesthesia system, which aims to solve technical problems such as shortage of anesthesia personnel and insufficient accuracy of anesthesia technology in existing painless gastroenteroscopy diagnosis and treatment.

[0006] An intelligent anesthesia system includes a robotic arm device, a data processing device, and an anesthesia device; the data processing device includes:

[0007] Medical record collection module, used to collect patients' medical record data;

[0008] The plan formulation module is connected to the data acquisition module and is used to predict anesthesia risks and formulate an initial anesthesia plan based on medical record data;

[0009] A monitoring and collection module is used to continuously collect anesthesia monitoring data during anesthesia;

[0010] The analysis and processing module is connected to the monitoring and collection module to analyze the anesthesia monitoring data and obtain real-time analysis results;

[0011] An anesthesia adjustment module, connected to the analysis and processing module, is used to adjust the anesthesia plan based on the real-time analysis results and send the adjusted anesthesia plan to the anesthesia device;

[0012] The robotic arm control module is connected to the plan formulation module and the analysis and processing module respectively, and is used to generate robotic arm auxiliary instructions based on real-time analysis results and send them to the robotic arm device;

[0013] The anesthesia device is used to administer medication to the patient according to the adjusted anesthesia plan when the adjusted anesthesia plan is received;

[0014] The robot arm device performs the corresponding auxiliary operation after receiving the robot arm auxiliary instruction.

[0015] Furthermore, the robotic arm control module is also used to generate a venipuncture instruction during the pre-anesthesia preparation stage and send it to the robotic arm device;

[0016] The robotic arm device performs venipuncture on the patient after receiving the venipuncture instruction.

[0017] Furthermore, it also includes an alarm formation module, connected to the analysis and processing module, for generating an alarm message when an abnormality occurs in the real-time analysis result;

[0018] Intelligent anesthesia systems also include portable computing devices;

[0019] The portable computing device is wirelessly connected to the data processing device to display real-time analysis results and anesthesia adjustment plans, and to issue an alarm based on the alarm information.

[0020] Furthermore, the intelligent anesthesia system is applied to a gastroenteroscopy, and further comprises an image monitoring device connected to the data processing device, wherein the image monitoring device is used to obtain gastroenteroscopy images collected by the gastroenteroscopy device in real time and send the images to the data processing device;

[0021] The anesthesia monitoring data includes the gastroenteroscopic image.

[0022] Furthermore, the anesthesia phases during anesthesia include anesthesia induction phase, anesthesia maintenance phase, and anesthesia recovery phase;

[0023] The data processing module also includes a stage updating module, connected to the analysis processing module, for updating the anesthesia stage during the anesthesia process based on the real-time analysis results;

[0024] The anesthesia adjustment module is further connected to the stage update module, and is used to adjust the anesthesia plan in real time based on the real-time analysis results and the updated anesthesia stage, and send the adjusted anesthesia plan to the anesthesia device;

[0025] The robotic arm control module is connected to the stage update module and is used to generate robotic arm auxiliary instructions based on the real-time analysis results and the updated anesthesia stage and send them to the robotic arm device.

[0026] Furthermore, the anesthesia device includes an anesthesia machine and a drug delivery pump, the anesthesia plan includes a first anesthesia parameter and a second anesthesia parameter, the anesthesia adjustment module transmits the first anesthesia parameter to the anesthesia machine, and the anesthesia adjustment module transmits the second anesthesia parameter to the drug delivery pump;

[0027] The anesthesia machine controls the delivery of oxygen and a first anesthetic drug to the patient according to the first anesthesia parameter;

[0028] The drug delivery pump controls the infusion of the second anesthetic drug into the patient according to the second anesthesia parameter.

[0029] Furthermore, the second anesthetic drug includes a sedative, analgesic, and muscle relaxant.

[0030] Furthermore, the anesthesia machine is further configured to send anesthesia machine monitoring data to the data processing device;

[0031] Anesthesia monitoring data includes anesthesia machine monitoring data.

[0032] Furthermore, the anesthesia monitoring data includes the patient's vital signs monitoring data.

[0033] Furthermore, the intelligent anesthesia system also includes BIS monitoring equipment, ANI monitoring equipment, and TOF monitoring equipment;

[0034] The BIS monitoring device, the ANI monitoring device and the TOF monitoring device are respectively connected to the data processing device;

[0035] The BIS monitoring device collects the bispectral index during anesthesia;

[0036] The ANI monitoring device collects the noxious stimulus balance index during anesthesia;

[0037] The TOF monitoring device collects four trains of stimulation during anesthesia;

[0038] Vital sign monitoring data included the bispectral index, noxious stimulus balance index, and train-of-four stimulation.

[0039] The beneficial technical effect of the present invention is that: the present invention collects monitoring data during the anesthesia process based on a data processing device, thereby issuing an anesthesia plan to the anesthesia device. The anesthesia plan can be adjusted in real time according to the real-time data, thereby objectively judging whether additional anesthetic drugs are needed, realizing the intelligence and automation of the anesthesia process, improving the accuracy of anesthetic medication, and reducing the risks caused by insufficient or excessive anesthetic drugs. At the same time, the anesthesia system of the present invention is equipped with a robotic arm device, which controls the robotic arm device to assist the anesthesia personnel in operating during the anesthesia process. Anesthesia automation and robotic arm assistance reduce the dosage requirements of the anesthesia personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1and Figure 2 The present invention provides a module schematic diagram of an intelligent anesthesia system. DETAILED DESCRIPTION

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0042] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0043] The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0044] See also Figure 1-Figure 2 The present invention provides an intelligent anesthesia system, comprising a robotic arm device (3), a data processing device (1), and an anesthesia device (2); the data processing device (1) comprises:

[0045] A medical record collection module (101) is used to collect the patient's medical record data;

[0046] A plan formulation module (102), connected to the data acquisition module (101), is used to predict anesthesia risk based on medical record data and formulate an initial anesthesia plan;

[0047] A monitoring and collection module (103), configured to continuously collect anesthesia monitoring data during anesthesia;

[0048] An analysis and processing module (104), connected to the monitoring and collecting module (103), is used to analyze the anesthesia monitoring data to obtain real-time analysis results;

[0049] an anesthesia adjustment module (105), connected to the plan formulation module (102) and the analysis and processing module (104), for adjusting the anesthesia plan based on the real-time analysis results and sending the adjusted anesthesia plan to the anesthesia device (2);

[0050] A robotic arm control module (106), connected to the analysis and processing module (104), is used to generate a robotic arm auxiliary instruction based on the real-time analysis result and send it to the robotic arm device (3);

[0051] The anesthesia device (2) is used to administer medication to the patient according to the adjusted anesthesia plan when receiving the adjusted anesthesia plan;

[0052] The robot arm device (3) performs a corresponding auxiliary operation after receiving the robot arm auxiliary instruction.

[0053] Before officially entering the anesthesia process, a pre-anesthesia assessment is required. The anesthesia system of the present invention can collect the patient's medical record data through a universal medical record collection module (101). The patient's case data includes the patient's basic information, medical history, family medical history, hospital test and examination data, etc. Part of the data can be extracted through a voice conversation with the patient, for example, setting a voice device to be connected to a data processing device, and the data processing device obtains relevant case data from the voice device. The voice device can be a portable computing device.

[0054] Specifically, the patient's basic information includes name, identification information, age, height, weight, etc. Anesthesiologists or doctors can use voice devices to ask questions of the patient and obtain some information from the patient's medical records through conversation. Hospital test data such as blood pressure, blood test results, liver and kidney function, electrocardiogram, etc.

[0055] The plan making module (102) analyzes the patient's case data, predicts the anesthesia risk, and provides a preliminary anesthesia plan, which includes anesthetic drugs and drug dosages, etc. Different patients may be suitable for different anesthetic drugs and dosages.

[0056] The present invention collects monitoring data during the anesthesia process based on a data processing device, thereby issuing an anesthesia plan to the anesthesia device. The anesthesia plan can be adjusted in real time according to the real-time data, thereby objectively determining whether additional anesthetic drugs are needed, realizing the intelligence and automation of the anesthesia process, improving the accuracy of anesthetic medication, and reducing the risks caused by insufficient or excessive anesthetic drugs. At the same time, the anesthesia system of the present invention is equipped with a robotic arm device to control the robotic arm device to assist the anesthesia personnel in operating during the anesthesia process. Anesthesia automation and robotic arm assistance reduce the dosage requirements of the anesthesia personnel.

[0057] Furthermore, the robotic arm control module (106) is also used to generate a venipuncture instruction during the pre-anesthesia preparation phase and send it to the robotic arm device (3);

[0058] The robotic arm device (3) performs venipuncture on the patient after receiving the venipuncture instruction.

[0059] Before officially entering the anesthesia process, after completing the anesthesia plan, pre-anesthesia preparations need to be carried out, such as checking patient information, making some special preparations for special patients, and performing venipuncture on the patient. During the pre-anesthesia preparations, the system can issue instructions to the robotic arm device to make some auxiliary preparations, such as using the robotic arm device to perform venipuncture on the patient. The use of artificial intelligence to automatically perform manual puncture solves the problem of insufficient anesthesia personnel and busy operations. The robotic arm control module (106) can generate venipuncture instructions after receiving the puncture operation task set by the anesthesia personnel.

[0060] During the pre-anesthetic preparation process, the anesthesia staff also checks the patient information to ensure that the patient information is accurate and avoid the wrong use of drugs.

[0061] Furthermore, it also includes an alarm generation module (107), connected to the analysis and processing module (104), for generating an alarm message when an abnormality occurs in the real-time analysis result;

[0062] The intelligent anesthesia system also includes a portable computing device (4);

[0063] The portable computing device (4) is wirelessly connected to the data processing device (1) and is used to display real-time analysis results and anesthesia adjustment plans, and to issue an alarm according to the alarm information.

[0064] The anesthesia personnel carry a portable device, and once the patient or the equipment is detected to be abnormal during the anesthesia process, an alarm is immediately issued to reduce the occurrence of danger. Specifically, the portable computing device (4) can issue an alarm in the form of sound, or through an interface display, or through a combination of sound and display. Of course, other methods can also be used to issue an alarm so that the anesthesia personnel can be notified in a timely manner.

[0065] Furthermore, the intelligent anesthesia system is applied to a gastroenteroscopy and further comprises an image monitoring device (5) connected to the data processing device (1), wherein the image monitoring device (5) is used to obtain gastroenteroscopy images collected by a gastroenteroscopy device in real time and send the images to the data processing device;

[0066] The anesthesia monitoring data includes the gastroenteroscopic image.

[0067] In addition to being equipped with a robotic arm device to assist anesthesia personnel during anesthesia and to monitor and analyze the patient's anesthesia status in real time, the present invention is equipped with an image monitoring device (5) to further monitor the patient during anesthesia to avoid danger. The image of the gastrointestinal endoscope of the patient during anesthesia is used to assist in judging the patient's anesthesia status based on the gastrointestinal endoscope image. The information of the gastrointestinal endoscope diagnosis and treatment process can be monitored in detail, and the system can be controlled to stop drug administration in time.

[0068] Furthermore, the anesthesia phases during anesthesia include anesthesia induction phase, anesthesia maintenance phase, and anesthesia recovery phase;

[0069] The data processing module (1) further comprises a stage updating module (108), connected to the analysis processing module (104), for updating the anesthesia stage during the anesthesia process according to the real-time analysis result;

[0070] The anesthesia adjustment module (105) is further connected to the stage update module (108) and is used to adjust the anesthesia plan in real time based on the real-time analysis results and the updated anesthesia stage, and send the adjusted anesthesia plan to the anesthesia device (2);

[0071] The robot arm control module (106) is connected to the stage update module (108) and is used to generate a robot arm auxiliary instruction based on the real-time analysis result and the updated anesthesia stage and send it to the robot arm device (3).

[0072] Anesthesia induction is the first step in anesthesia. The goal of this phase is to transition the patient from a conscious state to an anesthetized state. During this process, the anesthesia provider will administer sedatives, analgesics, and muscle relaxants to render the patient unconscious and pain-free. Anesthesia induction can be performed via intravenous injection (with a pump) or inhaled anesthetic gas (with an anesthesia machine), depending on the patient's specific condition.

[0073] Once the patient is anesthetized, the next phase is anesthesia maintenance. During this phase, the patient is continuously given an appropriate amount of anesthetic drugs to maintain their depth of anesthesia, while their vital signs are monitored to ensure their safety. Anesthesia maintenance can be achieved through continuous infusion of intravenous anesthetic drugs or precise doses of inhaled anesthetic drugs provided by an anesthesia machine.

[0074] As the gastrointestinal endoscopy nears its end, during the anesthesia recovery phase, the anesthetic drug supply is reduced to gradually allow the patient to recover from anesthesia. During this phase, the anesthesiologist closely monitors the patient's respiration, heart rate, blood pressure, and other vital physiological parameters to ensure the patient can safely regain spontaneous breathing and consciousness.

[0075] During the anesthesia induction phase, the patient's vital signs are monitored in real time to determine whether the patient has entered a deep anesthesia state, so that the doctor can prepare for the next anesthesia maintenance phase and perform gastrointestinal endoscopy.

[0076] In combination with the image monitoring device (5) and the patient's vital sign data, the system automatically determines whether to enter the next anesthesia maintenance stage, generates a stage update reminder message and notifies the anesthesia personnel through a portable computing device so that the doctor can diagnose and treat. The anesthesia personnel can confirm the stage update after receiving the stage update reminder message, and the data processing module enters the next anesthesia maintenance stage to implement the anesthesia stage update when confirmed by the anesthesia personnel. The data processing module can also directly update the anesthesia stage and enter the anesthesia maintenance stage while generating a stage update reminder message to notify the anesthesia personnel.

[0077] During the anesthesia maintenance phase, the anesthesia adjustment module adjusts the anesthesia plan in real time based on the real-time analysis results and the updated anesthesia phase, so that the drug dosage conforms to the drug dosage during the anesthesia maintenance phase.

[0078] The image monitoring device (5) determines the gastrointestinal endoscopic information during the gastrointestinal endoscopic diagnosis and treatment process by analyzing the patient's environmental data, thereby determining whether to update the anesthesia stage to enter the next anesthesia recovery stage.

[0079] As an application example, a gastrointestinal endoscope sends real-time gastrointestinal images to the system. The analysis and processing module can use these images to assist in analyzing whether the anesthesia maintenance phase has concluded. It can also further analyze the patient's vital signs during this phase using the images. This includes monitoring the gastrointestinal endoscope images and other vital signs, enabling comprehensive patient monitoring to detect abnormalities, ensure patient safety during gastrointestinal endoscope procedures, and ensure accurate anesthetic medication delivery. Furthermore, the gastrointestinal endoscope images can be used to further analyze the completion of the gastrointestinal endoscope procedure, such as whether the gastrointestinal endoscope has been removed or whether the device is still capturing images in real time. The system automatically determines whether the next anesthesia recovery phase can be initiated and generates a phase update notification, which is then sent to the anesthesia staff via a portable computing device. Upon receiving the phase update notification, the anesthesia staff can confirm the phase update. Upon confirmation by the anesthesia staff, the data processing module advances to the next anesthesia recovery phase, implementing the anesthesia phase update. Alternatively, the data processing module can directly update the anesthesia phase and enter the anesthesia recovery phase, simultaneously generating a phase update notification to the anesthesia staff.

[0080] During the anesthesia recovery phase, the supply of anesthetic drugs is reduced or stopped based on real-time analysis results, and the patient is gradually revived.

[0081] Furthermore, the anesthesia device (2) includes an anesthesia machine and a drug delivery pump, the anesthesia plan includes a first anesthesia parameter and a second anesthesia parameter, the anesthesia adjustment module (105) transmits the first anesthesia parameter to the anesthesia machine, and the anesthesia adjustment module (105) transmits the second anesthesia parameter to the drug delivery pump;

[0082] The anesthesia machine controls the delivery of oxygen and a first anesthetic drug to the patient according to the first anesthesia parameter;

[0083] The drug delivery pump controls the infusion of the second anesthetic drug into the patient according to the second anesthesia parameter.

[0084] Anesthesia machines are primarily used to provide and control the delivery of anesthetic gases, typically for general anesthesia or deep sedation. They are capable of providing precise concentrations of oxygen, anesthetic gases (such as isoflurane, sevoflurane, etc.), and fresh gas flow.

[0085] The anesthesia machine and drug delivery pump automatically administer the drug, reducing the operating burden on the anesthesia personnel.

[0086] During the anesthesia process, the robotic arm control module (106) can generate some robotic arm auxiliary instructions such as mask connection, nasogastric tube intubation, etc., and the robotic arm device can help the anesthesia personnel put on the mask and tube of the anesthesia machine for the patient. More specifically, for example, the robotic arm device can grab the mask and tube and hand them to the anesthesia personnel.

[0087] Furthermore, the second anesthetic drug includes a sedative, analgesic, and muscle relaxant.

[0088] A drug delivery pump is primarily used to precisely control the rate and dosage of intravenous medications. These medications may include sedatives (such as propofol), analgesics (such as fentanyl), and other adjunctive medications such as muscle relaxants. Using a drug delivery pump allows for more precise regulation of the rate of drug delivery, thereby better controlling the depth of anesthesia and reducing the risk of side effects.

[0089] Furthermore, the anesthesia machine is further configured to send anesthesia machine monitoring data to the data processing device (1);

[0090] Anesthesia monitoring data includes anesthesia machine monitoring data.

[0091] Anesthesia machine monitoring data includes, for example, breathing circuit pressure, respiratory rate, tidal volume, inspired oxygen concentration, anesthetic gas concentration, etc.

[0092] Breathing circuit pressure: The breathing circuit is the channel through which the breathing gas in the anesthesia machine flows. The breathing circuit pressure refers to the pressure of the gas in the breathing circuit.

[0093] Respiratory rate refers to the number of breaths a patient takes per minute, and this parameter can be used to monitor the patient's breathing condition.

[0094] Tidal volume refers to the volume of air that a patient breathes into their lungs with each breath.

[0095] Inspired oxygen concentration refers to the concentration of oxygen in the gas inhaled by the patient.

[0096] Anesthetic gas concentration refers to the concentration of anesthetic agent in the anesthetic gas output by the anesthesia machine.

[0097] Furthermore, the anesthesia monitoring data includes the patient's vital signs monitoring data.

[0098] Vital sign monitoring data includes data monitored by monitors, such as body temperature, electrocardiogram, blood oxygen saturation, heart rate data, blood pressure data, etc.

[0099] Furthermore, the intelligent anesthesia system also includes a BIS monitoring device (6), an ANI monitoring device (7), and a TOF monitoring device (8);

[0100] The BIS monitoring device (6), the ANI monitoring device (7) and the TOF monitoring device (8) are respectively connected to the data processing device (1);

[0101] The BIS monitoring device (6) collects the bispectral index during anesthesia;

[0102] The ANI monitoring device (7) collects the noxious stimulus balance index during anesthesia;

[0103] The TOF monitoring device (8) collects four trains of stimulation during anesthesia;

[0104] Vital sign monitoring data included the bispectral index, noxious stimulus balance index, and train-of-four stimulation.

[0105] BIS (Bispectral Index) is a technique that quantifies a patient's level of consciousness by analyzing electroencephalogram (EEG) signals. BIS values can be used to guide anesthetic dosage adjustments, ensure the patient is at the appropriate depth of anesthesia, reduce the risk of intraoperative awareness, and facilitate faster postoperative recovery.

[0106] The Analgesia Nociception Index (ANI) is an indicator of the body's analgesic state, assessing autonomic nervous system activity based on the high-frequency components of heart rate variability (HRV). The ANI can help physicians better manage the use of analgesics during anesthesia, optimizing analgesic efficacy while avoiding side effects caused by overdose.

[0107] Train-of-four stimulation (TOF) is a commonly used method to monitor the degree of neuromuscular blockade. The TOF count (i.e., the number of responses) can be used to determine the degree of neuromuscular blockade and its recovery, which is crucial for ensuring safe extubation.

[0108] The system of the present invention realizes automation, intelligence, visualization and standardization of the anesthesia process.

[0109] The above are only preferred embodiments of the present invention and do not limit the implementation mode and protection scope of the present invention. For those skilled in the art, it should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the description and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent anesthesia system, characterized in that: It includes a robotic arm device, a data processing device, and an anesthesia device; the data processing device includes: Medical record collection module, used to collect patients' medical record data; A plan formulation module, connected to the data acquisition module, for predicting anesthesia risk based on the medical record data and formulating an initial anesthesia plan; A monitoring and collection module is used to continuously collect anesthesia monitoring data during anesthesia; An analysis and processing module, connected to the monitoring and collection module, for analyzing the anesthesia monitoring data to obtain real-time analysis results; an anesthesia adjustment module, connected to the plan formulation module and the analysis and processing module, respectively, for adjusting the anesthesia plan based on the real-time analysis result and sending the adjusted anesthesia plan to the anesthesia device; a robotic arm control module, connected to the analysis and processing module, configured to generate a robotic arm auxiliary instruction based on the real-time analysis result and send it to the robotic arm device; The anesthesia device is used to administer medication to the patient according to the adjusted anesthesia plan upon receiving the adjusted anesthesia plan; The robotic arm device performs a corresponding auxiliary operation after receiving the robotic arm auxiliary instruction.

2. The intelligent anesthesia system according to claim 1, characterized in that: The robotic arm control module is also used to generate a venipuncture instruction during the pre-anesthesia preparation stage and send it to the robotic arm device; The robotic arm device performs venipuncture on the patient after receiving the venipuncture instruction.

3. The intelligent anesthesia system according to claim 1, characterized in that: It also includes an alarm generation module, connected to the analysis and processing module, for generating an alarm message when an abnormal situation occurs in the real-time analysis result; The intelligent anesthesia system also includes a portable computing device; The portable computing device is wirelessly connected to the data processing apparatus, and is used to display the real-time analysis results and the anesthesia adjustment plan, and to generate an alarm according to the alarm information.

4. The intelligent anesthesia system according to claim 1, characterized in that: The intelligent anesthesia system is applied to a gastroenteroscopy, and further comprises an image monitoring device connected to the data processing device, wherein the image monitoring device is used to obtain gastroenteroscopy images collected by a gastroenteroscopy device in real time and send the images to the data processing device; The anesthesia monitoring data includes the gastroenteroscopic image.

5. The intelligent anesthesia system according to claim 3, characterized in that: The anesthesia stages in the anesthesia process include anesthesia induction stage, anesthesia maintenance stage and anesthesia recovery stage; The data processing module further includes a stage updating module connected to the analysis processing module, for updating the anesthesia stage during the anesthesia process according to the real-time analysis result; The anesthesia adjustment module is further connected to the stage updating module, and is configured to adjust the anesthesia plan in real time based on the real-time analysis result and the updated anesthesia stage, and send the adjusted anesthesia plan to the anesthesia device; The robotic arm control module is connected to the stage update module and is used to generate a robotic arm auxiliary instruction based on the real-time analysis result and the updated anesthesia stage and send it to the robotic arm device.

6. The intelligent anesthesia system according to claim 3, characterized in that: The anesthesia device includes an anesthesia machine and a drug delivery pump, the anesthesia plan includes a first anesthesia parameter and a second anesthesia parameter, the anesthesia adjustment module transmits the first anesthesia parameter to the anesthesia machine, and the anesthesia adjustment module transmits the second anesthesia parameter to the drug delivery pump; The anesthesia machine controls the delivery of oxygen and a first anesthetic drug to the patient according to the first anesthesia parameter; The drug delivery pump controls the infusion of a second anesthetic drug into the patient according to the second anesthesia parameter.

7. The intelligent anesthesia system according to claim 6, characterized in that: The second anesthetic drugs include sedatives, analgesics and muscle relaxants.

8. The intelligent anesthesia system according to claim 6, characterized in that: The anesthesia machine is further configured to send anesthesia machine monitoring data to the data processing device; The anesthesia monitoring data includes the anesthesia machine monitoring data.

9. The intelligent anesthesia system according to claim 1, characterized in that: The anesthesia monitoring data includes the patient's vital sign monitoring data.

10. The intelligent anesthesia system according to claim 9, characterized in that: The intelligent anesthesia system also includes a BIS monitoring device, an ANI monitoring device, and a TOF monitoring device; The BIS monitoring device, the ANI monitoring device and the TOF monitoring device are respectively connected to the data processing device; The BIS monitoring device collects bispectral index during anesthesia; The ANI monitoring device collects the noxious stimulus balance index during anesthesia; The TOF monitoring device collects four trains of stimulation during anesthesia; The vital sign monitoring data includes the bispectral index, the noxious stimulation balance index and the four trains of stimulation.

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