An intelligent method and system for target control of adult anesthesia based on EEG signal monitoring

Abstract

The present invention provides an intelligent method and system for target control of adult anesthesia based on EEG signal monitoring, and the method includes: determining the anesthesia scheme for the target adult based on the type of surgery of the target adult, and determining the target anesthetic agent required for the anesthesia of the target adult based on the anesthesia scheme; injecting the target anesthetic agent into the target adult based on a preset injection pump, and collecting the EEG signal of the target adult in real time; determining the sedation depth and analgesia depth of the target adult based on the EEG signal, and controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic agent based on the sedation depth and analgesia depth, so as to complete the intelligent target control of adult anesthesia. By collecting the EEG signal of the target adult in real time, it is convenient to understand the current sedation depth and analgesia depth of the target adult according to the EEG in real time, thereby improving the accuracy of adjusting the injection pump and the anesthetic agent, improving the anesthesia effect, and reducing the damage caused by anesthesia.

Description

Technical Field

[0001] The present invention relates to the field of anesthesia technology, and in particular to an intelligent method and system for adult anesthesia target control based on electroencephalogram signal monitoring. Background Art

[0002] At present, anesthetics are indispensable for patients during surgery. The dosage and speed of anesthetic injection are usually controlled manually. On the one hand, it is difficult to accurately match the most suitable anesthetic dosage for the patient. On the other hand, after the anesthetic is injected, the injection speed and dosage of the anesthetic cannot be changed in real time according to the patient's physical condition. This makes it difficult to prevent the patient from knowing during the operation or prevent excessive anesthesia. At the same time, the anesthetic effect is greatly reduced or the harm caused by excessive anesthesia is caused.

[0003] Therefore, the present invention provides an intelligent method and system for target control of adult anesthesia based on EEG signal monitoring, which is used to analyze the type of surgery for the target adult to ensure that the anesthetic used for the target adult is accurate enough, and at the same time, the brain waves of the target adult are collected in real time during injection, so as to understand the current sedation depth and analgesia depth of the target adult in real time based on the brain waves, thereby improving the accuracy of adjustment of the injection pump and anesthetic agents, improving the anesthetic effect, and reducing the damage caused by anesthesia. Summary of the invention

[0004] The present invention provides an intelligent method and system for adult anesthesia target control based on EEG signal monitoring, which is used to analyze the type of surgery of the target adult to ensure that the anesthetic used for the target adult is sufficiently accurate, and at the same time, the EEG signal of the target adult is collected in real time during injection, so as to understand the current sedation depth and analgesia depth of the target adult in real time according to the EEG, thereby improving the accuracy of adjusting the injection pump and the anesthetic, improving the anesthetic effect, and reducing the damage caused by anesthesia.

[0005] The present invention provides an intelligent method for monitoring adult anesthesia target control based on EEG signals, comprising:

[0006] Step 1: determining an anesthesia regimen for the target adult based on the type of surgery for the target adult, and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia regimen;

[0007] Step 2: injecting the target anesthetic agent into the target adult based on a preset injection pump, and collecting the EEG signal of the target adult in real time;

[0008] Step 3: Determine the sedation depth and analgesia depth of the target adult based on the EEG signal, and control the injection speed of the preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth to complete intelligent target control of adult anesthesia.

[0009] Preferably, an intelligent method for target control of adult anesthesia based on EEG signal monitoring, in step 1, determining an anesthesia plan for the target adult based on the type of surgery of the target adult, comprises:

[0010] Acquiring diagnostic data of a target adult and determining attribute information of the diagnostic data;

[0011] Matching a target surgery type consistent with the attribute information from a preset surgery type library based on the attribute information, and determining the complexity of the target surgery type based on the attribute information of the diagnosis data;

[0012] The anesthesia scheme required for performing the target surgery type on the target adult is determined based on the complexity, wherein the anesthesia scheme includes total intravenous anesthesia and combined intravenous-inhalation anesthesia.

[0013] Preferably, an intelligent method for target control of adult anesthesia based on EEG signal monitoring, in step 1, determining the target anesthetic agent required for anesthesia of the target adult based on the anesthesia scheme, comprises:

[0014] Acquire an anesthesia plan for the target adult, and determine a target anesthetic agent category corresponding to the surgical type of the target adult based on the anesthesia plan, wherein each anesthetic agent category includes multiple anesthetic agents;

[0015] The allergy history of the target adult is obtained, and the anesthetic drugs included in the target anesthetic drug category are screened based on the allergy history to obtain the target anesthetic drug, wherein the allergy history includes the allergy of the target adult to the anesthetic drug.

[0016] Preferably, an intelligent method for adult anesthesia target control based on EEG signal monitoring, screening the anesthetic agents contained in the target anesthetic agent category based on the allergy history to obtain the target anesthetic agent, includes:

[0017] Obtaining the types of anesthetic agents to be selected after screening the anesthetic agents included in the target anesthetic agent category based on the allergy history, wherein the type of anesthetic agents to be selected is at least one;

[0018] Extracting the drug attribute information of the type of anesthetic drug to be selected, and obtaining the target adult surgery type;

[0019] The anesthetic effect of the anesthetic agent type to be selected is evaluated based on the operation type and the agent attribute information, and based on the evaluation result, the optimal anesthetic agent type is selected from the anesthetic agent types to be selected as the target anesthetic agent required during the target adult surgery.

[0020] Preferably, an intelligent method for target control of adult anesthesia based on EEG signal monitoring, step 1: determining an anesthesia scheme for the target adult based on the type of surgery of the target adult, and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia scheme, comprising:

[0021] A time estimation model is constructed, and the type of surgery of the target adult is obtained, and medical record data of the target adult is obtained;

[0022] Obtaining historical surgery types and corresponding surgery data, and determining the complexity of historical surgeries, average duration of historical surgeries, and overtime due to surgical emergencies based on the historical surgery types and corresponding surgery data;

[0023] Determine the training parameters of the time estimation model based on the complexity, the average duration of historical surgeries, and the added time of surgical emergencies, and train the time estimation model based on the training parameters to obtain a target time estimation model;

[0024] Inputting the operation type of the target adult and the medical record data into the target time estimation model to obtain the estimated time corresponding to the operation type;

[0025] A prepared dosage of the target anesthetic agent is determined based on the estimated time.

[0026] Preferably, an intelligent method for monitoring adult anesthesia target control based on EEG signals, in step 2, injecting the target anesthetic agent into the target adult based on a preset injection pump, and collecting the EEG signals of the target adult in real time, including:

[0027] Obtaining vital sign information of the target adult, and transmitting the vital sign information to the management terminal for analysis and processing, to obtain the injection speed required by the target adult during the operation;

[0028] Controlling the preset injection pump to inject the target anesthetic agent into the target adult based on the injection speed, and at the same time, determining a target acquisition area on the scalp of the target adult, and acquiring the EEG signal of the target adult in the target acquisition area based on a preset EEG signal acquisition probe;

[0029] Dividing the EEG signal into M segments of EEG signals, and marking each segment of EEG signals;

[0030] Determine the frequency fluctuation range value and brain energy fluctuation range of the target adult EEG signal in each segment of the sub-EEG signal based on the marking result, and compare the frequency fluctuation range value and brain energy fluctuation range of the target adult EEG signal with the preset standard EEG signal frequency fluctuation range value and preset brain energy fluctuation range value, to determine the interfering EEG signal whose frequency fluctuation range value in each segment of the sub-EEG signal is not within the preset standard EEG signal frequency fluctuation range value and brain energy fluctuation range value;

[0031] The interfering EEG signals are filtered out to obtain sub-EEG signals to be amplified, and the sub-EEG signals to be amplified are fused based on the labeling results to obtain the EEG signals to be amplified;

[0032] Eliminating common-mode interference of the target adult's EEG signal based on a preset method to obtain an EEG common-mode signal;

[0033] Performing differential amplification on the EEG signal to be amplified and the EEG common mode signal to obtain an EEG amplified signal of the target adult;

[0034] Obtaining a data format requirement of a preset EEG signal display device for an EEG signal to be displayed, and converting the data format of the amplified EEG signal based on the data format requirement to obtain a target EEG signal;

[0035] The target EEG signal is transmitted to the preset EEG signal display device for display, thereby completing the collection of the EEG signal of the target adult.

[0036] Preferably, an intelligent method for monitoring adult anesthesia target control based on EEG signals, transmitting the target EEG signals to the preset EEG signal display device for display, completing the collection of the EEG signals of the target adult, includes:

[0037] Acquire a target EEG signal of the target adult, and simultaneously acquire identity information of the target adult and a target anesthetic agent to be injected;

[0038] Determining the number of items to be recorded based on the target EEG signal, the identity information, and the injected target anesthetic agent, and matching a target report template from a preset record template library based on the items to be recorded;

[0039] Filling the specific recording data corresponding to the items to be recorded into the target positions in the target report template respectively, and generating an EEG signal recording report sheet of the target adult, wherein the items to be recorded include the target EEG signal, the identity information of the target adult, the target anesthetic agent injected, and the time of injection of the target anesthetic agent, and the target EEG signal, the target anesthetic agent injected, and the time of injection of the target anesthetic agent correspond to the identity information of the target adult one by one;

[0040] The EEG signal recording report is transmitted to a preset storage area for storage, thereby completing the recording of the target EEG signal.

[0041] Preferably, an intelligent method for monitoring adult anesthesia target control based on EEG signals, in step 3, the sedation depth and analgesia depth of the target adult are determined based on the EEG signals, and the injection speed of the preset injection pump and the injection amount of the target anesthetic agent are controlled based on the sedation depth and analgesia depth, including:

[0042] Acquire an EEG signal of a target adult, and determine a state time series corresponding to the EEG signal after the target adult receives the target anesthetic, wherein the EEG signal corresponds to the state time series;

[0043] Decomposing the EEG signal based on a preset signal decomposition method to obtain the frequency and power of the EEG signal at different state time points, and determining the heartbeat information and breathing information of the target adult at different state time points based on the frequency and power of the EEG signal;

[0044] Constructing an anesthesia assessment model, and inputting the heart rate information and respiration information of the target adult at different state time points into the anesthesia assessment model to obtain the consciousness index and noxious stimulus sensitivity index of the target adult at different state time points;

[0045] Obtaining a preset comparison table, and searching the preset comparison table for the sedation depth and analgesia depth of the target adult at different state time points based on the consciousness index and the noxious stimulus sensitivity index;

[0046] Comparing the sedation depth and analgesia depth of the target adult at different state time points with the preset sedation depth and the preset analgesia depth respectively;

[0047] If the sedation depth or the analgesia depth is less than the preset sedation depth or the preset analgesia depth, the anesthesia of the target adult is determined to be unqualified, and the injection speed of the current preset injection pump and the injection volume of the target anesthetic agent are adjusted based on the sedation depth and the analgesia depth;

[0048] Otherwise, the anesthesia of the target adult is determined to be qualified, and the sedation depth and analgesia depth of the target adult in the next time period are monitored in real time until the current operation is completed.

[0049] Preferably, an intelligent method for target control of adult anesthesia based on EEG signal monitoring adjusts the injection speed of the current preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth, including:

[0050] When it is determined that the anesthesia of the target adult is unqualified, sending an alarm signal to the management terminal;

[0051] At the same time, the analgesia depth and the sedation depth of the target adult are obtained, and the target difference between the analgesia depth and the sedation depth and the preset analgesia depth and the preset sedation depth is calculated;

[0052] determining a correction value for the injection speed of the preset injection pump and an adjustment value for the injection volume of the target anesthetic agent based on the target difference;

[0053] The injection speed of the preset injection pump and the injection volume of the target anesthetic agent are adjusted based on the correction value of the injection speed and the adjustment value of the injection volume.

[0054] Preferably, an intelligent system for monitoring adult anesthesia target control based on EEG signals comprises:

[0055] An anesthetic agent type determination module is used to determine an anesthesia plan for the target adult based on the type of surgery of the target adult, and determine a target anesthetic agent required for anesthesia of the target adult based on the anesthesia plan;

[0056] An electroencephalogram signal acquisition module, used for injecting the target anesthetic agent into the target adult based on a preset injection pump, and acquiring the electroencephalogram signal of the target adult in real time;

[0057] The anesthesia target control module is used to determine the sedation depth and analgesia depth of the target adult based on the EEG signal, and control the injection speed of the preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth, thereby completing intelligent target control of adult anesthesia.

[0058] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0059] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0061] Figure 1 This is a flow chart of an intelligent method for monitoring adult anesthesia target control based on EEG signals in an embodiment of the present invention;

[0062] Figure 2This is a flowchart of step 1 in an intelligent method for monitoring adult anesthesia target control based on EEG signals in an embodiment of the present invention;

[0063] Figure 3 The present invention is a structural diagram of an intelligent target control system for monitoring adult anesthesia based on EEG signals in an embodiment of the present invention. DETAILED DESCRIPTION

[0064] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0065] Embodiment 1:

[0066] This embodiment provides an intelligent method for monitoring adult anesthesia target control based on EEG signals. Figure 1 As shown, including:

[0067] Step 1: determining an anesthesia regimen for the target adult based on the type of surgery for the target adult, and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia regimen;

[0068] Step 2: injecting the target anesthetic agent into the target adult based on a preset injection pump, and collecting the EEG signal of the target adult in real time;

[0069] Step 3: Determine the sedation depth and analgesia depth of the target adult based on the EEG signal, and control the injection speed of the preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth to complete intelligent target control of adult anesthesia.

[0070] In this embodiment, the target adult may be a patient aged 14-60 years.

[0071] In this embodiment, the anesthesia plan is formulated based on the type of surgery and the complexity of the surgery for different target adults, and the anesthesia plan between different patients may be different.

[0072] In this embodiment, the target anesthetic agent refers to the anesthetic agent corresponding to the type of surgery for the target adult, for example, general anesthesia or local anesthesia is determined according to the complexity of the surgery. The anesthetic drugs used may include lidocaine, bupivacaine, tetracaine, ropivacaine, etc.

[0073] In this embodiment, the preset injection pump is set in advance, for example, it can be a sedative injection pump, a sufen injection pump, a ruifen injection pump, a muscle relaxant injection pump, a pressor injection pump, a hypotensive injection pump, etc.

[0074] In this embodiment, the sedation depth and the analgesia depth are used to represent the current emotional fluctuations and awareness of pain of the target adult, respectively.

[0075] The beneficial effects of the above technical solution are: by analyzing the type of surgery for the target adult, ensuring that the anesthetic used for the target adult is accurate enough, and at the same time, collecting the target adult's brain waves in real time during injection, it is convenient to understand the target adult's current sedation depth and analgesia depth based on the brain waves in real time, thereby improving the accuracy of adjusting the injection pump and anesthetic drugs, improving the anesthetic effect, and reducing the damage caused by anesthesia.

[0076] Embodiment 2:

[0077] Based on the above embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on EEG signals, such as Figure 2 As shown, in step 1, an anesthetic regimen for the target adult is determined based on the type of surgery of the target adult, including:

[0078] Step 101: Acquire diagnostic data of a target adult and determine attribute information of the diagnostic data;

[0079] Step 102: matching a target surgery type consistent with the attribute information from a preset surgery type library based on the attribute information, and determining the complexity of the target surgery type based on the attribute information of the diagnosis data;

[0080] Step 103: Determine the anesthesia scheme required for performing the target surgery type on the target adult based on the complexity, wherein the anesthesia scheme includes total intravenous anesthesia and combined intravenous-inhalation anesthesia.

[0081] In this embodiment, the diagnosis data refers to the diagnosis result of the target adult by the medical staff or the examination data of the target adult by the instrument.

[0082] In this embodiment, the attribute information may be the final diagnosis result of the target adult and the values ​​of various physical index parameters.

[0083] In this embodiment, the preset surgery type library is set in advance, and surgery types corresponding to various diseases are stored internally.

[0084] In this embodiment, the target surgery type refers to a surgery type suitable for the target adult, which is one of the preset surgery type libraries.

[0085] The beneficial effect of the above technical solution is: by obtaining the diagnostic data of the target adult, the type of surgery for the target adult can be accurately judged, so that the anesthesia plan for the target adult can be accurately formulated according to the type of surgery, thereby improving the accuracy of anesthesia for the target adult and reducing the risk of anesthesia-related injuries.

[0086] Embodiment 3:

[0087] On the basis of the above-mentioned embodiment 1, this embodiment provides an intelligent method for target control of adult anesthesia based on EEG signal monitoring. In step 1, the target anesthetic agent required for anesthesia of the target adult is determined based on the anesthesia scheme, including:

[0088] Acquire an anesthesia plan for the target adult, and determine a target anesthetic agent category corresponding to the surgical type of the target adult based on the anesthesia plan, wherein each anesthetic agent category includes multiple anesthetic agents;

[0089] The allergy history of the target adult is obtained, and the anesthetic drugs included in the target anesthetic drug category are screened based on the allergy history to obtain the target anesthetic drug, wherein the allergy history includes the allergy of the target adult to the anesthetic drug.

[0090] In this embodiment, the target anesthetic agent category refers to whether the target adult is used for general anesthesia or local anesthesia, and there is a difference in the types of anesthetic agents used in the two.

[0091] In this embodiment, the allergy history refers to the target adult's allergies to various drugs, and here refers to the target adult's allergies to drug components in anesthetic agents.

[0092] In this embodiment, the target anesthetic agent refers to the anesthetic agent obtained by eliminating allergic anesthetic agents from the anesthetic agents included in the category corresponding to the target adult surgery type, and can be one or more.

[0093] The beneficial effect of the above technical solution is: by accurately confirming the anesthetic agents required by the target adult during the operation according to the anesthesia plan of the target adult, it is beneficial to provide the target adult with optimal anesthesia treatment and improve the safety of the anesthesia treatment.

[0094] Embodiment 4:

[0095] On the basis of the above-mentioned embodiment 3, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on EEG signals, wherein the anesthetic agents contained in the target anesthetic agent category are screened based on the allergy history to obtain the target anesthetic agent, including:

[0096] Obtaining the types of anesthetic agents to be selected after screening the anesthetic agents included in the target anesthetic agent category based on the allergy history, wherein the type of anesthetic agents to be selected is at least one;

[0097] Extracting the drug attribute information of the type of anesthetic drug to be selected, and obtaining the target adult surgery type;

[0098] The anesthetic effect of the anesthetic agent type to be selected is evaluated based on the operation type and the agent attribute information, and based on the evaluation result, the optimal anesthetic agent type is selected from the anesthetic agent types to be selected as the target anesthetic agent required during the target adult surgery.

[0099] In this embodiment, the type of anesthetic agent to be selected refers to the anesthetic agent obtained by eliminating the anesthetic agent to which the target adult is allergic from the target anesthetic agent category.

[0100] In this embodiment, the drug attribute information may be the composition of the drug, the duration of action of the drug, etc.

[0101] In this embodiment, the anesthetic effect evaluation refers to a comprehensive evaluation of the effect of each anesthetic agent based on the duration of anesthesia, the amount of anesthetic agent used, and the like.

[0102] In this embodiment, the optimal anesthetic agent type refers to the anesthetic agent with the best anesthetic effect among the anesthetic agents to be selected.

[0103] The beneficial effect of the above technical solution is: by screening the types of anesthetic agents, it is ensured that the corresponding anesthetics are used for the target adults, thereby improving the anesthetic effect and reducing the damage caused by anesthesia.

[0104] Embodiment 5:

[0105] Based on the above-mentioned embodiment 1, this embodiment provides an intelligent method for target control of adult anesthesia based on EEG signal monitoring, step 1: determining an anesthesia scheme for the target adult based on the type of surgery of the target adult, and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia scheme, including:

[0106] A time estimation model is constructed, and the type of surgery of the target adult is obtained, and medical record data of the target adult is obtained;

[0107] Obtaining historical surgery types and corresponding surgery data, and determining the complexity of historical surgeries, average duration of historical surgeries, and overtime due to surgical emergencies based on the historical surgery types and corresponding surgery data;

[0108] Determine the training parameters of the time estimation model based on the complexity, the average duration of historical surgeries, and the added time of surgical emergencies, and train the time estimation model based on the training parameters to obtain a target time estimation model;

[0109] Inputting the operation type of the target adult and the medical record data into the target time estimation model to obtain the estimated time corresponding to the operation type;

[0110] A prepared dosage of the target anesthetic agent is determined based on the estimated time.

[0111] In this embodiment, the medical record data may be a diagnosis certificate issued by a doctor based on the symptoms of the target adult.

[0112] In this embodiment, the historical surgery types and the corresponding surgery data refer to various types of surgeries that have been performed and various surgical indicator data recorded during the surgery, which are already known in advance.

[0113] In this embodiment, the training parameters are used to train the time estimation model, determine the various factors that affect the operation time, and accurately train the time estimation model to ensure the accuracy of the estimated time.

[0114] In this embodiment, the target time estimation model refers to a time estimation model obtained after training the construction time estimation model.

[0115] In this embodiment, the estimated time refers to the length of time that the target adult may spend when performing the current operation.

[0116] In this embodiment, the prepared amount refers to the amount of anesthetic prepared in advance according to the time that may be required for the target adult surgery.

[0117] In this embodiment, the operation type of the target adult and the medical record data are input into the target time estimation model to obtain the estimated time consumption corresponding to the operation type, including:

[0118] Acquire the wound shape of the target adult, and place the wound shape in a preset two-dimensional coordinate system to obtain the wound curve function;

[0119] The time length value required to complete the current surgery of the target adult is calculated based on the wound curve function, and the preparation dosage of the target anesthetic agent is calculated based on the time length value. The specific steps include:

[0120] The time required to complete the current surgery for the target adult is calculated according to the following formula:

[0121] ;

[0122] in, A value indicating the length of time required to complete the current surgery of the target adult; represents the difficulty coefficient of the current surgery for the target adult, and the value range is (0.6, 0.9); Indicates the starting point value of the target adult's wound shape in the preset two-dimensional coordinate system; Indicates the endpoint value of the target adult's wound shape in the preset two-dimensional coordinate system; An upper boundary curve representing the wound shape of the target adult in the preset two-dimensional coordinate system; An upper boundary curve function representing the target adult's wound shape in the preset two-dimensional coordinate system; A lower boundary curve representing the target adult's wound shape in the preset two-dimensional coordinate system; A lower boundary curve function representing the target adult's wound shape in the preset two-dimensional coordinate system; Indicates the speed value of medical personnel treating the wound of the target adult; It indicates the length of extra time required by medical staff in case of emergencies during surgery;

[0123] The preparation dosage of the target anesthetic agent is calculated according to the following formula:

[0124] ;

[0125] in, indicating a prepared dosage of the target anesthetic agent; Represents the error factor, and its value range is (0.05, 0.15); Indicates the working power value of the preset injection pump; Indicates the thrust of the preset injection pump on the target anesthetic agent; represents the target adult's resistance to the target anesthetic agent; Indicates the time length required to complete the current operation of the target adult; Indicates the surplus amount of target anesthetic agents prepared by medical staff;

[0126] The calculated prepared drug dosage is sent to the medical staff terminal, and the medical staff is reminded to prepare the target anesthetic agent according to the prepared drug dosage, thereby completing the preparation of the target adult preoperative anesthetic agent.

[0127] The above-mentioned difficulty coefficient refers to the difficulty of performing surgery on the target adult. The larger the difficulty coefficient is, the more complicated the surgery on the target adult is.

[0128] The above-mentioned surplus preparation amount refers to the amount of target anesthetic agent prepared in excess after meeting the surgical needs of target adults.

[0129] The above-mentioned preset two-dimensional coordinate system is set in advance to facilitate the determination of the target adult wound area.

[0130] The above formula The calculated result is the injection speed of the preset injection pump, and its dimension is milliliters per second.

[0131] The overtime length required for medical staff to deal with emergencies during the operation refers to the time spent on preventing medical staff from having to deal with other situations during the operation, based on the calculated theoretical time length. It can be set in advance, for example, five minutes, ten minutes, etc.

[0132] The beneficial effect of the above technical solution is: by constructing a time estimation model, the surgery time can be estimated according to the surgery type and medical record data of the target adult, so as to facilitate the preparation of sufficient anesthetic drugs in advance, improve the accuracy of adjusting the injection pump and anesthetic drugs, and improve the anesthesia effect.

[0133] Embodiment 6:

[0134] Based on the above-mentioned embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on EEG signals. In step 2, the target anesthetic agent is injected into the target adult based on a preset injection pump, and the EEG signal of the target adult is collected in real time, including:

[0135] Obtaining vital sign information of the target adult, and transmitting the vital sign information to the management terminal for analysis and processing, to obtain the injection speed required by the target adult during the operation;

[0136] Controlling the preset injection pump to inject the target anesthetic agent into the target adult based on the injection speed, and at the same time, determining a target acquisition area on the scalp of the target adult, and acquiring the EEG signal of the target adult in the target acquisition area based on a preset EEG signal acquisition probe;

[0137] Dividing the EEG signal into M segments of sub-EEG signals, and marking each segment of sub-EEG signals;

[0138] Determine the frequency fluctuation range value and brain energy fluctuation range of the target adult EEG signal in each segment of the sub-EEG signal based on the marking result, and compare the frequency fluctuation range value and brain energy fluctuation range of the target adult EEG signal with the preset standard EEG signal frequency fluctuation range value and the preset brain energy fluctuation range value, to determine the interfering EEG signal whose frequency fluctuation range value in each segment of the sub-EEG signal is not within the preset standard EEG signal frequency fluctuation range value and the preset brain energy fluctuation range value;

[0139] The interfering EEG signals are filtered out to obtain sub-EEG signals to be amplified, and the sub-EEG signals to be amplified are fused based on the labeling results to obtain the EEG signals to be amplified;

[0140] Eliminating common-mode interference of the target adult's EEG signal based on a preset method to obtain an EEG common-mode signal;

[0141] Performing differential amplification on the EEG signal to be amplified and the EEG common mode signal to obtain an EEG amplified signal of the target adult;

[0142] Obtaining a data format requirement of a preset EEG signal display device for an EEG signal to be displayed, and converting the data format of the amplified EEG signal based on the data format requirement to obtain a target EEG signal;

[0143] The target EEG signal is transmitted to the preset EEG signal display device for display, thereby completing the collection of the EEG signal of the target adult.

[0144] In this embodiment, the vital sign information refers to various physical indicators of the target adult before the operation, such as blood pressure value, blood sugar value, heart rate value, etc.

[0145] In this embodiment, the vital sign information is transmitted to the management terminal for analysis and processing to determine the injection speed of the anesthetic according to the current physical fitness of the target adult. For example, if the vital sign information is normal, the standard anesthetic injection speed is used, otherwise the anesthetic injection speed is reduced.

[0146] In this embodiment, the preset injection pump is set in advance, and may be a sedation injection pump, a Shufen injection pump, a Ruifen injection pump, or the like.

[0147] In this embodiment, the target acquisition area refers to the scalp area corresponding to the EEG signal acquisition of the target adult.

[0148] In this embodiment, the preset EEG signal acquisition probe is set in advance and is a commonly used medical device for collecting EEG signals of patients.

[0149] In this embodiment, the sub-EEG signal refers to an EEG signal obtained by dividing the collected original EEG signal into multiple small segments, which is a part of the original EEG signal and is used to filter the interference signal in the EEG signal.

[0150] In this embodiment, the preset standard EEG signal frequency fluctuation range value is known in advance through training, and is used to represent the normal frequency range value of the patient's EEG wave without interference from other external factors after injection of anesthetics.

[0151] In this embodiment, the interfering EEG signal refers to a portion of the EEG signal whose frequency is not within the preset standard EEG signal frequency fluctuation range. A frequency that is too low or too high is an interfering EEG signal.

[0152] In this embodiment, the preset method is set in advance and can be performed by a professional machine.

[0153] In this embodiment, common mode interference elimination refers to eliminating the noise signal in the original signal.

[0154] In this embodiment, the preset EEG signal display device is set in advance, for example, it may be an EEG display.

[0155] In this embodiment, the preset brain energy fluctuation range value is set in advance and can be adjusted according to actual conditions.

[0156] The beneficial effects of the above technical solution are: by analyzing the vital signs information of the target adult, it is ensured that the target adult is injected with anesthetics at an appropriate injection speed. At the same time, the EEG signals of the target adult are collected in real time during the injection process, and the collected EEG signals are processed to ensure that the EEG signals provided to medical staff are accurate enough, thereby improving the accurate analysis of the sedation depth and analgesia depth of the target adult, improving the anesthesia effect, and reducing the occurrence of medical accidents.

[0157] Embodiment 7:

[0158] On the basis of the above-mentioned embodiment 6, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on EEG signals, characterized in that the target EEG signal is transmitted to the preset EEG signal display device for display, and the EEG signal of the target adult is collected, including:

[0159] Acquire a target EEG signal of the target adult, and simultaneously acquire identity information of the target adult and a target anesthetic agent to be injected;

[0160] Determining the number of items to be recorded based on the target EEG signal, the identity information, and the injected target anesthetic agent, and matching a target report template from a preset record template library based on the items to be recorded;

[0161] Filling the specific recording data corresponding to the items to be recorded into the target positions in the target report template respectively, and generating an EEG signal recording report sheet of the target adult, wherein the items to be recorded include the target EEG signal, the identity information of the target adult, the target anesthetic agent injected, and the time of injection of the target anesthetic agent, and the target EEG signal, the target anesthetic agent injected, and the time of injection of the target anesthetic agent correspond to the identity information of the target adult one by one;

[0162] The EEG signal recording report is transmitted to a preset storage area for storage, thereby completing the recording of the target EEG signal.

[0163] In this embodiment, the identity information of the target adult includes the name, age, etc. of the target adult.

[0164] In this embodiment, the items to be recorded refer to the information to be recorded in the record report template, such as the target's identity information, ID number, operation time, etc.

[0165] In this embodiment, the preset record template library is pre-set and stores a variety of data record reports.

[0166] In this embodiment, the target report template refers to a record report template suitable for recording the current target adult surgery information, and is one of the preset record half-height template libraries.

[0167] In this embodiment, the target position refers to the recording position corresponding to the item to be recorded in the target report template.

[0168] In this embodiment, the preset storage area is set in advance, and may be, for example, a hard disk.

[0169] The beneficial effect of the above technical solution is: by determining the items that need to be recorded during the operation of the target adult, the EEG signals of the target adult and the corresponding identity information can be accurately recorded, ensuring that the EEG signals of the target adult can be retained. At the same time, it is also convenient for medical staff to check the anesthesia status of the target adult in time, thereby improving the anesthesia effect and enhancing the effectiveness of anesthesia target control.

[0170] Embodiment 8:

[0171] On the basis of the above-mentioned embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on EEG signals. In step 3, the sedation depth and analgesia depth of the target adult are determined based on the EEG signals, and the injection speed of the preset injection pump and the injection amount of the target anesthetic agent are controlled based on the sedation depth and analgesia depth, including:

[0172] Acquire an EEG signal of a target adult, and determine a state time series corresponding to the EEG signal after the target adult receives the target anesthetic, wherein the EEG signal corresponds to the state time series;

[0173] Decomposing the EEG signal based on a preset signal decomposition method to obtain the frequency and power of the EEG signal at different state time points, and determining the heartbeat information and breathing information of the target adult at different state time points based on the frequency and power of the EEG signal;

[0174] Constructing an anesthesia assessment model, and inputting the heartbeat information and respiratory information of the target adult at different state time points into the anesthesia assessment model to obtain the cardiopulmonary index and noxious stimulus sensitivity index of the target adult at different state time points;

[0175] Obtaining a preset comparison table, and searching the preset comparison table for the sedation depth and analgesia depth of the target adult at different state time points based on the cardiopulmonary index and the noxious stimulus sensitivity index;

[0176] Comparing the sedation depth and analgesia depth of the target adult at different state time points with the preset sedation depth and the preset analgesia depth respectively;

[0177] If the sedation depth or the analgesia depth is less than the preset sedation depth or the preset analgesia depth, the anesthesia of the target adult is determined to be unqualified, and the injection speed of the current preset injection pump and the injection volume of the target anesthetic agent are adjusted based on the sedation depth and the analgesia depth;

[0178] Otherwise, the anesthesia of the target adult is determined to be qualified, and the sedation depth and analgesia depth of the target adult in the next time period are monitored in real time until the current operation is completed.

[0179] In this embodiment, the state time series refers to the changes in the target adult's vital signs over time after the target adult receives an anesthetic injection.

[0180] In this embodiment, the preset signal decomposition method is set in advance, and may be to decompose the EEG signal into multiple EEG signal segments.

[0181] In this embodiment, the cardiopulmonary index is used to describe the sedation depth of the target adult after the target adult receives an anesthetic injection.

[0182] In this embodiment, the noxious stimulus sensitivity index is used to describe the depth of analgesia of the target adult after the target adult receives an anesthetic injection.

[0183] In this embodiment, the preset comparison table is set in advance and is used to record the sedation depth and analgesia depth corresponding to different consciousness indexes and noxious stimulus sensitivity indexes.

[0184] In this embodiment, the preset sedation depth and the preset analgesia depth are set in advance and are used to measure whether the current sedation depth and analgesia depth of the target adult meet the surgical requirements. They are obtained through multiple trainings, and the usage of different anesthetic agents corresponds to different sedation depths and analgesia depths.

[0185] In this embodiment, the next time period may be the sedation depth and analgesia depth of the target adult in the next ten minutes, and this time period may be modified according to actual conditions.

[0186] In this embodiment, determining the heart rate information and breathing information of the target adult at different state time points based on the frequency and power of the EEG signal can be performed by analyzing the frequency and power of the EEG signal with a professional machine to obtain the heart rate information and breathing information of the target adult at the current moment.

[0187] The beneficial effect of the above technical solution is: by analyzing the sedation depth and analgesia depth of the target adult based on EEG signals, it is ensured that the sedation and analgesia conditions of the target adult at different time points are accurately grasped, so as to achieve timely adjustment of the current injection speed and injection volume according to the analgesia depth and sedation depth, thereby improving the anesthesia effect, and at the same time improving the accuracy of the adjustment of the injection pump and anesthetic agents, reducing the damage caused by anesthesia.

[0188] Embodiment 9:

[0189] Based on the above-mentioned Example 8, this embodiment provides an intelligent method for target control of adult anesthesia based on EEG signal monitoring, which adjusts the injection speed of the current preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth, including:

[0190] When it is determined that the anesthesia of the target adult is unqualified, sending an alarm signal to the management terminal;

[0191] At the same time, the analgesia depth and the sedation depth of the target adult are obtained, and the target difference between the analgesia depth and the sedation depth and the preset analgesia depth and the preset sedation depth is calculated;

[0192] determining a correction value for the injection speed of the preset injection pump and an adjustment value for the injection volume of the target anesthetic agent based on the target difference;

[0193] The injection speed of the preset injection pump and the injection volume of the target anesthetic agent are adjusted based on the correction value of the injection speed and the adjustment value of the injection volume.

[0194] In this embodiment, the target difference refers to the difference between the analgesia depth and the preset sedation depth, and the difference between the sedation depth and the preset sedation depth. If either of the two is not satisfied, the injection speed of the preset injection pump and the injection volume of the target anesthetic agent need to be adjusted.

[0195] In this embodiment, the correction value of the injection speed of the preset injection pump and the adjustment value of the injection amount of the target anesthetic agent determined based on the target difference can be corrected by searching the corresponding reference table according to the difference, wherein the reference table is data obtained through multiple surgical trainings, which records the corresponding relationship between the injection speed and the anesthetic dose corresponding to different differences.

[0196] The beneficial effect of the above technical solution is: by determining the specific adjustment values ​​of the preset injection pump injection speed and the target anesthetic dose, the injection speed and the target anesthetic dose are accurately adjusted, thereby improving the anesthesia effect, while also improving the accuracy of the adjustment of the injection pump and anesthetic agents, thereby reducing the damage caused by anesthesia.

[0197] Embodiment 10:

[0198] This embodiment provides an intelligent system for monitoring adult anesthesia target control based on EEG signals. Figure 3 As shown, including:

[0199] An anesthetic agent type determination module is used to determine an anesthesia plan for the target adult based on the type of surgery of the target adult, and determine a target anesthetic agent required for anesthesia of the target adult based on the anesthesia plan;

[0200] An electroencephalogram signal acquisition module, used for injecting the target anesthetic agent into the target adult based on a preset injection pump, and acquiring the electroencephalogram signal of the target adult in real time;

[0201] The anesthesia target control module is used to determine the sedation depth and analgesia depth of the target adult based on the EEG signal, and control the injection speed of the preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth, thereby completing intelligent target control of adult anesthesia.

[0202] The beneficial effects of the above technical solution are: by analyzing the type of surgery for the target adult, ensuring that the anesthetic used for the target adult is accurate enough, and at the same time, collecting the target adult's brain waves in real time during injection, it is convenient to understand the target adult's current sedation depth and analgesia depth based on the brain waves in real time, thereby improving the accuracy of adjusting the injection pump and anesthetic drugs, improving the anesthesia effect, and reducing the damage caused by anesthesia.

[0203] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent system for monitoring adult anesthesia target control based on EEG signals, characterized in that: include: An anesthetic agent type determination module is used to determine an anesthesia plan for the target adult based on the type of surgery of the target adult, and determine a target anesthetic agent required for anesthesia of the target adult based on the anesthesia plan; An electroencephalogram signal acquisition module, used for injecting the target anesthetic agent into the target adult based on a preset injection pump, and acquiring the electroencephalogram signal of the target adult in real time; An anesthesia target control module, used to determine the sedation depth and analgesia depth of the target adult based on the EEG signal, and control the injection speed of the preset injection pump and the injection volume of the target anesthetic agent based on the sedation depth and analgesia depth, so as to complete the intelligent target control of adult anesthesia; Among them, the EEG signal acquisition module includes: Obtaining vital sign information of the target adult, and transmitting the vital sign information to the management terminal for analysis and processing, to obtain the injection speed required by the target adult during the operation; Controlling the preset injection pump to inject the target anesthetic agent into the target adult based on the injection speed, and at the same time, determining a target acquisition area on the scalp of the target adult, and acquiring the EEG signal of the target adult in the target acquisition area based on a preset EEG signal acquisition probe; Dividing the EEG signal into M segments of sub-EEG signals, and marking each segment of sub-EEG signals; Determine the frequency fluctuation range value and brain energy fluctuation range of the target adult EEG signal in each segment of the sub-EEG signal based on the marking result, and compare the frequency fluctuation range value and brain energy fluctuation range of the target adult EEG signal with the preset standard EEG signal frequency fluctuation range value and preset brain energy fluctuation range value, to determine the interfering EEG signal whose frequency fluctuation range value in each segment of the sub-EEG signal is not within the preset standard EEG signal frequency fluctuation range value; The interfering EEG signals are filtered out to obtain sub-EEG signals to be amplified, and the sub-EEG signals to be amplified are fused based on the labeling results to obtain the EEG signals to be amplified; Eliminating common-mode interference of the target adult's EEG signal based on a preset method to obtain an EEG common-mode signal; Performing differential amplification on the EEG signal to be amplified and the EEG common mode signal to obtain an EEG amplified signal of the target adult; Obtaining a data format requirement of a preset EEG signal display device for an EEG signal to be displayed, and converting the data format of the amplified EEG signal based on the data format requirement to obtain a target EEG signal; Transmitting the target EEG signal to the preset EEG signal display device for display, thereby completing the collection of the EEG signal of the target adult; Among them, the anesthetic agent type determination module includes: A time estimation model is constructed, and the type of surgery of the target adult is obtained, and medical record data of the target adult is obtained; Obtaining historical surgery types and corresponding surgery data, and determining the complexity of historical surgeries, average duration of historical surgeries, and overtime due to surgical emergencies based on the historical surgery types and corresponding surgery data; Determine the training parameters of the time estimation model based on the complexity, the average duration of historical surgeries, and the added time of surgical emergencies, and train the time estimation model based on the training parameters to obtain a target time estimation model; Inputting the operation type of the target adult and the medical record data into the target time estimation model to obtain the estimated time corresponding to the operation type; determining a prepared dosage of the target anesthetic agent based on the estimated time consumption; The operation type of the target adult and the medical record data are input into the target time estimation model to obtain the estimated time corresponding to the operation type, including: Acquire the wound shape of the target adult, and place the wound shape in a preset two-dimensional coordinate system to obtain a wound curve function; The time length value required to complete the current surgery of the target adult is calculated based on the wound curve function, and the preparation dosage of the target anesthetic agent is calculated based on the time length value. The specific steps include: The time required to complete the current surgery for the target adult is calculated according to the following formula: ； in, Indicates the time length required to complete the current operation of the target adult; represents the difficulty coefficient of the current surgery for the target adult, and the value range is (0.6, 0.9); Indicates the starting point value of the target adult's wound shape in the preset two-dimensional coordinate system; Indicates the endpoint value of the target adult's wound shape in the preset two-dimensional coordinate system; An upper boundary curve representing the wound shape of the target adult in the preset two-dimensional coordinate system; An upper boundary curve function representing the target adult's wound shape in the preset two-dimensional coordinate system; A lower boundary curve representing the target adult's wound shape in the preset two-dimensional coordinate system; A lower boundary curve function representing the target adult's wound shape in the preset two-dimensional coordinate system; Indicates the speed value of medical personnel treating the wound of the target adult; It indicates the length of extra time required by medical staff in case of emergencies during surgery; The preparation dosage of the target anesthetic agent is calculated according to the following formula: ； in, indicating a prepared dosage of the target anesthetic agent; Represents the error factor, and its value range is (0.05, 0.15); Indicates the working power value of the preset injection pump; Indicates the thrust of the preset injection pump on the target anesthetic agent; represents the target adult's resistance to the target anesthetic agent; Indicates the time length required to complete the current operation of the target adult; Indicates the surplus amount of target anesthetic agents prepared by medical staff; The calculated prepared drug dosage is sent to the medical staff terminal, and the medical staff is reminded to prepare the target anesthetic agent according to the prepared drug dosage, thereby completing the preparation of the target adult preoperative anesthetic agent.

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