CN114177414A - Intelligent adult anesthesia target control method and system based on electroencephalogram signal monitoring - Google Patents
Intelligent adult anesthesia target control method and system based on electroencephalogram signal monitoring Download PDFInfo
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Abstract
The invention provides an adult anesthesia target control intelligent method and system based on electroencephalogram signal monitoring, wherein the method comprises the following steps: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol; injecting the target anesthetic into a target adult based on a preset injection pump, and acquiring an electroencephalogram signal of the target adult in real time; and determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, and controlling the injection speed of a preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth to finish intelligent target control on adult anesthesia. By collecting the brain wave signals of the target adult in real time, the current sedation depth and analgesia depth of the target adult can be known conveniently in real time according to the brain waves, so that the accuracy of adjustment of an injection pump and an anesthetic is improved, the anesthetic effect is improved, and the injury caused by anesthesia is reduced.
Description
Technical Field
The invention relates to the technical field of anesthesia, in particular to an adult anesthesia target control intelligent method and system based on electroencephalogram signal monitoring.
Background
At present, anesthetic is essential for a patient in an operation process, and usually dose, speed and the like of anesthetic injection are manually controlled, so that on one hand, the most suitable anesthetic dose is difficult to be accurately matched for the patient, and on the other hand, after the anesthetic is injected, the injection speed and the injection dose of the anesthetic cannot be changed in real time according to the physical sign state of the patient, so that the patient cannot be completely prevented from knowing or preventing the anesthesia too deeply in the operation, and meanwhile, the anesthesia effect or the injury caused by the anesthesia too deeply is greatly reduced;
therefore, the invention provides an adult anesthesia target control intelligent method and system based on electroencephalogram signal monitoring, which are used for analyzing the operation type of a target adult, ensuring that an anesthetic used by the target adult is accurate enough, and simultaneously collecting brain waves of the target adult in real time during injection, so that the current sedation depth and analgesia depth of the target adult can be known in real time according to the brain waves, the accuracy of adjustment of an injection pump and the anesthetic is improved, the anesthesia effect is improved, and the injury caused by anesthesia is reduced.
Disclosure of Invention
The invention provides an adult anesthesia target control intelligent method and system based on electroencephalogram signal monitoring, which are used for analyzing the operation type of a target adult, ensuring that an anesthetic used by the target adult is accurate enough, simultaneously collecting the electroencephalogram signal of the target adult in real time during injection, facilitating the real-time understanding of the current sedation depth and analgesia depth of the target adult according to the electroencephalogram, improving the accuracy of adjustment of an injection pump and the anesthetic, improving the anesthesia effect and reducing the injury caused by anesthesia.
The invention provides an adult anesthesia target control intelligent method based on electroencephalogram signal monitoring, which comprises the following steps:
step 1: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol;
step 2: injecting the target anesthetic into a target adult based on a preset injection pump, and acquiring an electroencephalogram signal of the target adult in real time;
and step 3: and determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, and controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth to finish intelligent target control on adult anesthesia.
Preferably, in step 1, an adult anesthesia target control intelligent method based on electroencephalogram signal monitoring is used for determining an anesthesia scheme for a target adult based on the operation type of the target adult, and the method comprises the following steps:
acquiring diagnostic data of a target adult and determining attribute information of the diagnostic data;
matching a target operation type consistent with the attribute information from a preset operation type library based on the attribute information, and determining the complexity of the target operation type based on the attribute information of the diagnosis data;
and determining an anesthesia scheme required when the target operation type is carried out on the target adult based on the complexity, wherein the anesthesia scheme comprises a whole vein anesthesia and a static suction compound anesthesia.
Preferably, in step 1, the method for intelligently monitoring adult anesthesia target control based on electroencephalogram signals, wherein the step of determining the target anesthetic required by the target adult anesthesia based on the anesthesia scheme comprises the following steps:
acquiring an anesthesia scheme of the target adult, and determining a target anesthetic class corresponding to the operation type of the target adult based on the anesthesia scheme, wherein each anesthetic class comprises a plurality of anesthetics;
acquiring the allergy history of the target adult, and screening the anesthetic contained in the category of the target anesthetic based on the allergy history to obtain the target anesthetic, wherein the allergy history comprises the allergy condition of the target adult to the anesthetic.
Preferably, the method for monitoring adult anesthesia target control intellectualization based on electroencephalogram signals screens the anesthetic contained in the target anesthetic category based on the allergy history to obtain the target anesthetic, and comprises the following steps:
acquiring categories of anesthetic agents to be selected, which are obtained by screening anesthetic agents contained in the categories of the target anesthetic agents based on the allergy history, wherein the categories of the anesthetic agents to be selected are at least one;
extracting the medicament attribute information of the to-be-selected anesthetic type, and simultaneously acquiring the operation type of the target adult;
and performing anesthesia effect evaluation on the to-be-selected anesthetic type based on the operation type and the medicament attribute information, and selecting an optimal anesthetic type from the to-be-selected anesthetic type as a target anesthetic required in the target adult operation process based on an evaluation result.
Preferably, the intelligent adult anesthesia target control method based on electroencephalogram signal monitoring comprises the following steps of 1: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol, comprising:
constructing a time estimation model, acquiring the operation type of a target adult, and acquiring medical record data of the target adult;
acquiring a historical operation type and corresponding operation data, and determining the complexity of the historical operation, the average time consumption of the historical operation and the time increase of the operation emergency based on the historical operation type and the corresponding operation data;
determining training parameters of the time estimation model based on the complexity, the average time consumption of the historical operation and the operation emergency condition in a time adding manner, and training 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 estimated time consumption corresponding to the operation type;
determining a quantity of priming drug for the target anesthetic agent based on the estimated elapsed time.
Preferably, in step 2, the method for monitoring adult anesthesia target control based on electroencephalogram signals comprises the steps of injecting the target anesthetic into a target adult based on a preset injection pump, and collecting the electroencephalogram signals of the target adult in real time, wherein the steps comprise:
acquiring vital sign information of a target adult, and transmitting the vital sign information to a management terminal for analysis and processing to obtain an injection speed required by the target adult in the operation process;
controlling the preset injection pump to inject the target anesthetic into the target adult based on the injection speed, simultaneously determining a target acquisition area on the scalp of the target adult, and acquiring an electroencephalogram signal of the target adult in the target acquisition area based on a preset electroencephalogram signal acquisition probe;
dividing the electroencephalogram signal into M sections of sub-electroencephalogram signals, and marking each section of sub-electroencephalogram signal;
determining the frequency fluctuation range value and the brain energy fluctuation range of the target adult electroencephalogram signal in each section of sub-electroencephalogram signals based on the marking result, comparing the frequency fluctuation range value and the brain energy fluctuation range of the target adult electroencephalogram signal with the frequency fluctuation range value and the preset brain energy fluctuation range value of a preset standard electroencephalogram signal, and determining an interference electroencephalogram signal of which the frequency fluctuation range value in each section of sub-electroencephalogram signals is not within the frequency fluctuation range value and the brain energy fluctuation range value of the preset standard electroencephalogram signal;
filtering the interference electroencephalogram signal to obtain a sub-electroencephalogram signal to be amplified, and fusing the sub-electroencephalogram signal to be amplified based on a marking result to obtain an electroencephalogram signal to be amplified;
common-mode interference elimination is carried out on the electroencephalogram signals of the target adults based on a preset method to obtain electroencephalogram common-mode signals;
carrying out differential amplification on the electroencephalogram signal to be amplified and the electroencephalogram common-mode signal to obtain an electroencephalogram amplified signal of the target adult;
acquiring a data format requirement of a preset electroencephalogram signal display device for an electroencephalogram signal to be displayed, and performing data format conversion on the electroencephalogram amplified signal based on the data format requirement to obtain a target electroencephalogram signal;
and transmitting the target electroencephalogram signal to the preset electroencephalogram signal display equipment for displaying, and completing acquisition of the electroencephalogram signal of the target adult.
Preferably, the intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals transmits the target electroencephalogram signals to the preset electroencephalogram signal display equipment for display, and completes acquisition of the electroencephalogram signals of the target adults, and comprises the following steps:
acquiring a target electroencephalogram signal of the target adult, and acquiring identity information of the target adult and an injected target anesthetic;
determining the number of items to be recorded based on the target electroencephalogram signals, the identity information and the injected target anesthetic, and matching a target report template from a preset recording template library based on the items to be recorded;
filling specific recording data corresponding to a to-be-recorded item to a target position in the target report template respectively to generate an electroencephalogram signal recording report sheet of a target adult, wherein the to-be-recorded item comprises a target electroencephalogram signal, identity information of the target adult, an injected target anesthetic and time for injecting the target anesthetic, and the target electroencephalogram signal, the injected target anesthetic and the time for injecting the target anesthetic correspond to the identity information of the target adult one by one respectively;
and transmitting the electroencephalogram signal recording report sheet to a preset storage area for storage, and completing the recording of the target electroencephalogram signal.
Preferably, in step 3, the method for monitoring adult anesthesia target control based on electroencephalogram signals determines the sedation depth and analgesia depth of the target adult based on the electroencephalogram signals, and controls the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and analgesia depth, and includes:
acquiring an electroencephalogram signal of a target adult, and determining a state time sequence corresponding to the electroencephalogram signal after the target adult receives the target anesthetic, wherein the electroencephalogram signal corresponds to the state time sequence;
decomposing the electroencephalogram signal based on a preset signal decomposition method to obtain the frequency and the power of the electroencephalogram signal at different state time points, and determining the heartbeat information and the breathing information of the target adult at different state time points based on the frequency and the power of the electroencephalogram signal;
establishing an anesthesia evaluation model, and inputting heart rate information and respiratory information of the target adult at different state time points into the anesthesia evaluation model to obtain consciousness indexes and nociceptive sensitivity indexes of the target adult at different state time points;
acquiring a preset comparison table, and searching the sedation depth and the analgesia depth of the target adult at different state time points in the preset comparison table based on the consciousness index and the nociception sensitivity index;
comparing the sedation depth and the analgesia depth of the target adult at different state time points with a preset sedation depth and a preset analgesia depth respectively;
if the sedation depth or the analgesia depth is smaller than the preset sedation depth or the preset analgesia depth, judging that the anesthesia of the target adult is unqualified, and adjusting the injection speed of a current preset injection pump and the injection amount of a target anesthetic based on the sedation depth and the analgesia depth;
otherwise, judging that the anesthesia of the target adult is qualified, and monitoring the sedation depth and analgesia depth of the target adult in the next time period in real time until the current operation is completed.
Preferably, the method for monitoring adult anesthesia target control intelligence based on electroencephalogram signals, which adjusts the injection speed of a current preset injection pump and the injection amount of a target anesthetic based on the sedation depth and the analgesia depth, comprises the following steps:
when the anesthesia of the target adult is judged to be unqualified, an alarm signal is sent to a management terminal;
meanwhile, obtaining the analgesia depth and the sedation depth of the target adult, and calculating target difference values between the analgesia depth and the sedation depth and between a preset analgesia depth and a preset sedation depth;
determining a correction value for the injection speed of the preset injection pump and an adjustment value for the injection amount of the target anesthetic agent based on the target difference value;
and adjusting the injection speed of a preset injection pump and the injection amount of the target anesthetic on the basis of the corrected value of the injection speed and the adjustment value of the injection amount.
Preferably, an adult anesthesia target control intelligent system based on electroencephalogram signal monitoring comprises:
an anesthetic agent type determination module for determining an anesthesia scheme for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia scheme;
the electroencephalogram signal acquisition module is used for injecting the target anesthetic into a target adult based on a preset injection pump and acquiring electroencephalogram signals of the target adult in real time;
and the anesthesia target control module is used for determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth, and completing intelligent target control on adult anesthesia.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flowchart of an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals in the embodiment of the invention;
FIG. 2 is a flowchart of step 1 in an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals in the embodiment of the present invention;
fig. 3 is a structural diagram of an adult anesthesia target control intelligent system based on electroencephalogram signal monitoring in the embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
the embodiment provides an adult anesthesia target control intelligent method based on electroencephalogram signal monitoring, as shown in fig. 1, the method comprises the following steps:
step 1: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol;
step 2: injecting the target anesthetic into a target adult based on a preset injection pump, and acquiring an electroencephalogram signal of the target adult in real time;
and step 3: and determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, and controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth to finish intelligent target control on adult anesthesia.
In this embodiment, the target adult may be a patient 14-60 years old.
In this embodiment, the anesthesia protocol is tailored to the type of surgery and the complexity of the surgery for different targeted adults, and may vary from patient to patient.
In this embodiment, the target anesthetic refers to an anesthetic determined according to the type of operation of the target adult, for example, general anesthesia or local anesthesia is determined according to the complexity of the operation, and the anesthetic used may be lidocaine, bupivacaine, tetracaine, ropivacaine, and the like.
In this embodiment, the preset injection pump is set in advance, and may be a sedation injection pump, a shufen injection pump, a resifen injection pump, a muscle relaxation injection pump, a pressure increasing drug injection pump, a pressure decreasing drug injection pump, or the like.
In this embodiment, the sedation and analgesia depths are used to represent the current mood swings and awareness of pain perception of the target adult, respectively.
The beneficial effects of the above technical scheme are: the operation type of the target adult is analyzed, so that the anesthetic used by the target adult is accurate enough, and meanwhile, the brain waves of the target adult are collected in real time during injection, the current sedation depth and analgesia depth of the target adult can be known in real time according to the brain waves, the accuracy of adjustment of an injection pump and the anesthetic is improved, the anesthetic effect is improved, and the injury caused by anesthesia is reduced.
Example 2:
on the basis of the above embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals, as shown in fig. 2, in step 1, determining an anesthesia scheme for a target adult based on a surgical type of the target adult, including:
step 101: acquiring diagnostic data of a target adult and determining attribute information of the diagnostic data;
step 102: matching a target operation type consistent with the attribute information from a preset operation type library based on the attribute information, and determining the complexity of the target operation type based on the attribute information of the diagnosis data;
step 103: and determining an anesthesia scheme required when the target operation type is carried out on the target adult based on the complexity, wherein the anesthesia scheme comprises a whole vein anesthesia and a static suction compound anesthesia.
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.
In this embodiment, the attribute information may be a final diagnosis result of the target adult, values of various index parameters of the body, and the like.
In this embodiment, the preset operation type library is set in advance, and operation types corresponding to a plurality of disease conditions are stored in the preset operation type library.
In this embodiment, the target operation type refers to an operation type suitable for a target adult, and is one of a library of preset operation types.
The beneficial effects of the above technical scheme are: the accurate judgment of the operation type of the target adult is realized by acquiring the diagnosis data of the target adult, so that the accurate formulation of the anesthesia scheme of the target adult is realized according to the operation type, the accuracy of the anesthesia of the target adult is improved, and the typhoid caused by the anesthesia is reduced.
Example 3:
on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals, and in step 1, determining a target anesthetic required for anesthesia of the target adult based on the anesthesia scheme includes:
acquiring an anesthesia scheme of the target adult, and determining a target anesthetic class corresponding to the operation type of the target adult based on the anesthesia scheme, wherein each anesthetic class comprises a plurality of anesthetics;
acquiring the allergy history of the target adult, and screening the anesthetic contained in the category of the target anesthetic based on the allergy history to obtain the target anesthetic, wherein the allergy history comprises the allergy condition of the target adult to the anesthetic.
In this embodiment, the target anesthetic type is whether general anesthesia or local anesthesia is collected by a target adult, and the types of anesthetic used for the two are different.
In this example, the allergy history refers to the allergy profile of the target adult to various drugs, where the target adult is characterized by its allergy profile to the drug component of the anesthetic agent.
In this embodiment, the target anesthetic is obtained by removing an allergic anesthetic from anesthetics included in a category corresponding to a target adult operation type, and may be one or a plurality of types.
The beneficial effects of the above technical scheme are: the anesthesia agent required by the target adult in the operation process is accurately confirmed according to the anesthesia scheme of the target adult, so that the optimal anesthesia treatment of the target adult is facilitated, and the safety of the anesthesia treatment is improved.
Example 4:
on the basis of the above embodiment 3, this embodiment provides an adult anesthesia target control intelligent method based on electroencephalogram signal monitoring, and the method includes the steps of screening anesthetic agents contained in the target anesthetic agent category based on the allergy history to obtain a target anesthetic agent, including:
acquiring categories of anesthetic agents to be selected, which are obtained by screening anesthetic agents contained in the categories of the target anesthetic agents based on the allergy history, wherein the categories of the anesthetic agents to be selected are at least one;
extracting the medicament attribute information of the to-be-selected anesthetic type, and simultaneously acquiring the operation type of the target adult;
and performing anesthesia effect evaluation on the to-be-selected anesthetic type based on the operation type and the medicament attribute information, and selecting an optimal anesthetic type from the to-be-selected anesthetic type as a target anesthetic required in the target adult operation process based on an evaluation result.
In this embodiment, the anesthetic type to be selected refers to an anesthetic obtained by removing an anesthetic that is allergic to a target adult from a target anesthetic type.
In this embodiment, the drug attribute information may be a composition of the drug, a length of action time of the drug, and the like.
In this embodiment, the evaluation of anesthetic effect refers to a comprehensive evaluation of the effect of each anesthetic agent based on the length of time of anesthesia, the amount of anesthetic agent used, and the like.
In this embodiment, the optimal anesthetic agent type is the anesthetic agent with the best anesthetic effect of the anesthetic agent type to be selected.
The beneficial effects of the above technical scheme are: by screening the types of the anesthetic, the target adult is ensured to use the corresponding anesthetic, the anesthetic effect is improved, and the injury caused by anesthesia is reduced.
Example 5:
on the basis of the embodiment 1, the embodiment provides an intelligent adult anesthesia target control method based on electroencephalogram signal monitoring, and the method comprises the following steps: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol, comprising:
constructing a time estimation model, acquiring the operation type of a target adult, and acquiring medical record data of the target adult;
acquiring a historical operation type and corresponding operation data, and determining the complexity of the historical operation, the average time consumption of the historical operation and the time increase of the operation emergency based on the historical operation type and the corresponding operation data;
determining training parameters of the time estimation model based on the complexity, the average time consumption of the historical operation and the operation emergency condition in a time adding manner, and training 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 estimated time consumption corresponding to the operation type;
determining a quantity of priming drug for the target anesthetic agent based on the estimated elapsed time.
In this embodiment, the medical record data may be a diagnosis certificate or the like prescribed by a doctor according to the symptom expression of the target adult.
In this embodiment, the historical surgical type and the corresponding surgical data refer to various types of operated surgeries and various surgical index data recorded in the surgical process, which are known in advance.
In this embodiment, the training parameters are used to train the time estimation model, determine various factors affecting the operation time, and thus, accurately train the time estimation model and ensure accurate estimation time.
In this embodiment, the target time estimation model refers to a time estimation model obtained after training a built time estimation model.
In this embodiment, the estimated elapsed time refers to a length of time that the target adult may spend performing the current operation.
In this embodiment, the prepared dose refers to a dose of anesthetic prepared in advance according to a time that may be required for a targeted adult surgery.
In this embodiment, inputting the operation type of the target adult and the medical record data into the target time estimation model to obtain the estimated time consumption corresponding to the operation type includes:
obtaining the wound shape of a target adult, and placing the wound shape in a preset two-dimensional coordinate system to obtain a wound curve function;
calculating a time length value required for completing the current operation of the target adult based on the wound curve function, and calculating the preparation dosage of the target anesthetic based on the time length value, wherein the specific steps comprise:
calculating a length of time required to complete the current operation of the target adult according to the following formula:
wherein T represents a length of time value required to complete the current procedure for the target adult; alpha represents the difficulty coefficient of the current operation of the target adult, and the value range is (0.6, 0.9); a represents the starting point value of the wound shape of the target adult in the preset two-dimensional coordinate system; b represents an end point value of the wound shape of the target adult in the preset two-dimensional coordinate system; k represents an upper boundary curve of the wound shape of the target adult in the preset two-dimensional coordinate system; f (k) an upper bound curve function representing the shape of the wound of the target adult in the preset two-dimensional coordinate system; g represents a lower boundary curve of the wound shape of the target adult in the preset two-dimensional coordinate system; f (G) a lower boundary curve function representing the shape of the wound of the target adult in the preset two-dimensional coordinate system; v represents a velocity value of a healthcare worker treating the target adult wound; s represents the length value of time-adding required by the medical staff when an emergency happens in the operation process;
calculating the preparation drug amount of the target anesthetic according to the following formula:
wherein M represents a prepared drug amount for the target anesthetic; mu represents an error factor, and the value range is (0.05, 0.15); p represents the working power value of the preset injection pump; f represents the thrust of the preset injection pump to the target anesthetic agent; z represents the resistance of the target adult to the target anesthetic; t represents a length of time value required to complete the current operation of the target adult; h represents the surplus preparation amount of the medical staff for the target anesthetic;
and sending the calculated preparation dosage to a medical staff terminal, reminding medical staff to prepare the target anesthetic according to the preparation dosage, and completing preparation of the preoperative anesthetic of the target adult human hand.
The difficulty coefficient indicates that the greater the difficulty coefficient of the operation on the target adult, the more complicated the operation month of the target adult.
The surplus preparation amount is an amount of the target anesthetic to be prepared more after the surgical requirement of the target adult is satisfied.
The preset two-dimensional coordinate system is set in advance and is used for providing convenience for determining the wound area of the target adult.
The above formula
The calculation is the injection rate of the preset syringe pump in ml/s.
The length of time required for medical staff to take an emergency during the operation is determined in advance, for example, five minutes or ten minutes, to prevent the medical staff from taking time to deal with other situations during the operation, based on the calculation of the theoretical length of time.
The beneficial effects of the above technical scheme are: by constructing the time pre-estimation model, the operation time pre-estimation is realized according to the operation type and the medical record data of the target adult, so that the sufficient anesthetic dosage can be prepared in advance, the accuracy of adjusting an injection pump and anesthetic is improved, and the anesthetic effect is improved.
Example 6:
on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals, and in step 2, the method includes injecting the target anesthetic agent into a target adult based on a preset injection pump, and acquiring electroencephalogram signals of the target adult in real time, where the method includes:
acquiring vital sign information of a target adult, and transmitting the vital sign information to a management terminal for analysis and processing to obtain an injection speed required by the target adult in the operation process;
controlling the preset injection pump to inject the target anesthetic into the target adult based on the injection speed, simultaneously determining a target acquisition area on the scalp of the target adult, and acquiring an electroencephalogram signal of the target adult in the target acquisition area based on a preset electroencephalogram signal acquisition probe;
dividing the electroencephalogram signal into M sections of sub-electroencephalogram signals, and marking each section of sub-electroencephalogram signal;
determining the frequency fluctuation range value and the brain energy fluctuation range of the target adult electroencephalogram signal in each section of sub-electroencephalogram signals based on the marking result, comparing the frequency fluctuation range value and the brain energy fluctuation range of the target adult electroencephalogram signal with the frequency fluctuation range value and the preset brain energy fluctuation range value of a preset standard electroencephalogram signal, and determining interference electroencephalograms in which the frequency fluctuation range value in each section of sub-electroencephalogram signals is not within the preset standard electroencephalogram signal frequency fluctuation range value and the preset brain energy fluctuation range value;
filtering the interference electroencephalogram signal to obtain a sub-electroencephalogram signal to be amplified, and fusing the sub-electroencephalogram signal to be amplified based on a marking result to obtain an electroencephalogram signal to be amplified;
common-mode interference elimination is carried out on the electroencephalogram signals of the target adults based on a preset method to obtain electroencephalogram common-mode signals;
carrying out differential amplification on the electroencephalogram signal to be amplified and the electroencephalogram common-mode signal to obtain an electroencephalogram amplified signal of the target adult;
acquiring a data format requirement of a preset electroencephalogram signal display device for an electroencephalogram signal to be displayed, and performing data format conversion on the electroencephalogram amplified signal based on the data format requirement to obtain a target electroencephalogram signal;
and transmitting the target electroencephalogram signal to the preset electroencephalogram signal display equipment for displaying, and completing acquisition of the electroencephalogram signal of the target adult.
In this embodiment, the vital sign information refers to various physical indicators of the target adult before the operation, and may be, for example, a blood pressure value, a blood glucose value, a heart rate value, and the like.
In this embodiment, the transmitting of the vital sign information to the management terminal for analysis may be to determine an injection speed of the anesthetic according to a current physical quality of the target adult, for example, if each item of the vital sign information is normal, a standard anesthetic injection speed is adopted, otherwise, the anesthetic injection speed is reduced.
In this embodiment, the preset injection pump is set in advance, and may be a sedation injection pump, a shufen injection pump, a resifen injection pump, or the like.
In this embodiment, the target acquisition area refers to a scalp area corresponding to the acquisition of electroencephalogram signals for the target adult.
In the embodiment, the preset electroencephalogram signal acquisition probe is set in advance, is a common medical device and is used for collecting electroencephalograms of patients.
In this embodiment, the sub-electroencephalogram signal refers to an electroencephalogram signal obtained by dividing an acquired original electroencephalogram signal into a plurality of small segments, and is a part of the original electroencephalogram signal, so as to perform filtering processing on an interference signal in the electroencephalogram signal.
In the embodiment, the preset standard electroencephalogram signal frequency fluctuation range value is known in advance through training and is used for representing the normal frequency range value of the electroencephalogram of the patient without interference of other external factors after the anesthetic is injected.
In this embodiment, the interfering electroencephalogram signal refers to a part of electroencephalogram signals in the electroencephalogram signals, the frequency of which is not within the fluctuation range of the preset quasi-electroencephalogram signal frequency, and both too low and too high frequencies are interfering electroencephalogram signals.
In this embodiment, the preset method is set in advance, and may be performed by a professional machine.
In this embodiment, the common mode interference cancellation refers to cancellation of a noise signal in an original signal.
In this embodiment, the preset electroencephalogram signal display device is set in advance, and may be, for example, an electroencephalogram display.
In this embodiment, the preset brain energy fluctuation range value is set in advance, and can be adjusted according to actual conditions.
The beneficial effects of the above technical scheme are: the method has the advantages that the vital sign information of the target adult is analyzed, so that the target adult is ensured to be injected with the anesthetic at a proper injection speed, meanwhile, the electroencephalogram signal of the target adult is collected in real time in the injection process, the collected electroencephalogram signal is processed, and the electroencephalogram signal provided for medical personnel is ensured to be accurate enough, so that the accurate analysis on the sedation depth and analgesia depth of the target adult is improved, the anesthesia effect is improved, and medical accidents are reduced.
Example 7:
on the basis of the foregoing embodiment 6, this embodiment provides an adult anesthesia target control intelligent method based on electroencephalogram signal monitoring, which is characterized in that the target electroencephalogram signal is transmitted to the preset electroencephalogram signal display device for display, and the acquisition of the electroencephalogram signal of the target adult is completed, including:
acquiring a target electroencephalogram signal of the target adult, and acquiring identity information of the target adult and an injected target anesthetic;
determining the number of items to be recorded based on the target electroencephalogram signals, the identity information and the injected target anesthetic, and matching a target report template from a preset recording template library based on the items to be recorded;
filling specific recording data corresponding to a to-be-recorded item to a target position in the target report template respectively to generate an electroencephalogram signal recording report sheet of a target adult, wherein the to-be-recorded item comprises a target electroencephalogram signal, identity information of the target adult, an injected target anesthetic and time for injecting the target anesthetic, and the target electroencephalogram signal, the injected target anesthetic and the time for injecting the target anesthetic correspond to the identity information of the target adult one by one respectively;
and transmitting the electroencephalogram signal recording report sheet to a preset storage area for storage, and completing the recording of the target electroencephalogram signal.
In this embodiment, the identification information of the target adult includes the name, age, and the like of the target adult.
In this embodiment, the item to be recorded refers to information to be recorded in the recording report template, and may be, for example, target identity information, an identification number, a surgical time, and the like.
In this embodiment, the preset record template library is set in advance, and a plurality of data record reports are stored therein.
In this embodiment, the target report template refers to a record report template suitable for recording current target adult operation information, and is one of a preset record half-height template library.
In this embodiment, the target position refers to a corresponding recording position of the item to be recorded in the target report template.
In this embodiment, the preset storage area is set in advance, and may be a hard disk, for example.
The beneficial effects of the above technical scheme are: by determining the items to be recorded by the target adult in the operation process, the electroencephalogram signal of the target adult and the corresponding identity information are accurately recorded, the electroencephalogram signal of the target adult can be reserved, meanwhile, medical staff can check the anesthesia condition of the target adult conveniently, the anesthesia effect is improved, and the effectiveness of anesthesia target control is also enhanced.
Example 8:
on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals, and in step 3, the method includes determining a sedation depth and an analgesia depth of the target adult based on the electroencephalogram signals, and controlling an injection speed of the preset injection pump and an injection amount of the target anesthetic based on the sedation depth and the analgesia depth, and includes:
acquiring an electroencephalogram signal of a target adult, and determining a state time sequence corresponding to the electroencephalogram signal after the target adult receives the target anesthetic, wherein the electroencephalogram signal corresponds to the state time sequence;
decomposing the electroencephalogram signal based on a preset signal decomposition method to obtain the frequency and the power of the electroencephalogram signal at different state time points, and determining the heartbeat information and the breathing information of the target adult at different state time points based on the frequency and the power of the electroencephalogram signal;
establishing an anesthesia evaluation model, and inputting heartbeat information and respiratory information of the target adult at different state time points into the anesthesia evaluation model to obtain cardiopulmonary indexes and nociceptive sensitivity indexes of the target adult at different state time points;
acquiring a preset comparison table, and searching the sedation depth and analgesia depth of the target adult at different state time points in the preset comparison table based on the cardiopulmonary index and the nociceptive sensitivity index;
comparing the sedation depth and the analgesia depth of the target adult at different state time points with a preset sedation depth and a preset analgesia depth respectively;
if the sedation depth or the analgesia depth is smaller than the preset sedation depth or the preset analgesia depth, judging that the anesthesia of the target adult is unqualified, and adjusting the injection speed of a current preset injection pump and the injection amount of a target anesthetic based on the sedation depth and the analgesia depth;
otherwise, judging that the anesthesia of the target adult is qualified, and monitoring the sedation depth and analgesia depth of the target adult in the next time period in real time until the current operation is completed.
In this embodiment, the state time series refers to the change of the target adult vital signs over time after receiving the anesthetic injection.
In this embodiment, the preset signal decomposition method is set in advance, and may be to decompose the electroencephalogram signal into a plurality of electroencephalogram signal segments.
In this example, the cardiopulmonary index is used to describe the depth of sedation in a target adult after receiving an injection of an anesthetic agent.
In this embodiment, the nociceptive sensitivity index is used to describe the depth of analgesia that a target adult receives after injection of an anesthetic.
In this embodiment, the preset comparison table is set in advance and is used for recording the sedation depth and analgesia depth corresponding to different consciousness indexes and nociceptive sensitivity indexes.
In this embodiment, the preset sedation depth and the preset analgesia depth are set in advance, and are used for measuring whether the current sedation depth and analgesia depth of the target adult meet the surgical requirements or not, and are obtained through multiple training, and the usage amount of different anesthetic agents corresponds to different sedation depths and analgesia depths.
In this embodiment, the next time period may be the sedation depth and analgesia depth of the target adult in the next ten minutes, which may be modified according to actual conditions.
In this embodiment, the heart rate information and the breathing information of the target adult at different state time points are determined based on the frequency and the power of the electroencephalogram signal, and the heart rate information and the breathing information of the target adult at the current time can be obtained by analyzing the frequency and the power of the electroencephalogram signal through a professional machine.
The beneficial effects of the above technical scheme are: the sedation depth and analgesia depth of the target adult are analyzed according to the electroencephalogram signals, so that the sedation and analgesia of the target adult at different time points can be accurately grasped, the current injection speed and injection amount can be timely adjusted according to the analgesia depth and the sedation depth, the anesthesia effect is improved, the accuracy of adjustment of an injection pump and an anesthetic is improved, and the injury caused by anesthesia is reduced.
Example 9:
on the basis of the above embodiment 8, this embodiment provides an intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals, and the adjusting of the injection speed of the current preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth includes:
when the anesthesia of the target adult is judged to be unqualified, an alarm signal is sent to a management terminal;
meanwhile, obtaining the analgesia depth and the sedation depth of the target adult, and calculating target difference values between the analgesia depth and the sedation depth and between a preset analgesia depth and a preset sedation depth;
determining a correction value for the injection speed of the preset injection pump and an adjustment value for the injection amount of the target anesthetic agent based on the target difference value;
and adjusting the injection speed of a preset injection pump and the injection amount of the target anesthetic on the basis of the corrected value of the injection speed and the adjustment value of the injection amount.
In this embodiment, the target difference refers to a difference between the analgesia depth and the preset sedation depth and a difference between the sedation depth and the preset sedation depth, and the injection speed of the preset injection pump and the injection amount of the target anesthetic need to be adjusted if one of the analgesia depth and the preset sedation depth is not satisfied.
In this embodiment, the determination of the correction value of the injection speed of the preset injection pump and the adjustment value of the injection amount of the target anesthetic based on the target difference may be performed by searching a corresponding reference table according to the difference, where the reference table is data obtained through multiple surgical training, and a corresponding relationship between the injection speed and the anesthetic amount corresponding to different differences is recorded.
The beneficial effects of the above technical scheme are: the injection speed and the target anesthetic dosage are accurately adjusted by determining the specific adjustment values of the preset injection speed of the injection pump and the target anesthetic dosage, so that the anesthetic effect is improved, the accuracy of adjustment of the injection pump and the anesthetic dosage is improved, and the injury caused by anesthesia is reduced.
Example 10:
the embodiment provides an adult anesthesia target control intelligent system based on electroencephalogram signal monitoring, as shown in fig. 3, includes:
an anesthetic agent type determination module for determining an anesthesia scheme for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia scheme;
the electroencephalogram signal acquisition module is used for injecting the target anesthetic into a target adult based on a preset injection pump and acquiring electroencephalogram signals of the target adult in real time;
and the anesthesia target control module is used for determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth, and completing intelligent target control on adult anesthesia.
The beneficial effects of the above technical scheme are: the operation type of the target adult is analyzed, so that the anesthetic used by the target adult is accurate enough, and meanwhile, the brain waves of the target adult are collected in real time during injection, the current sedation depth and analgesia depth of the target adult can be known conveniently in real time according to the brain waves, the accuracy of adjustment of an injection pump and the anesthetic is improved, the anesthetic effect is improved, and the injury caused by anesthesia is reduced.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such 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 such modifications and variations.
Claims (10)
1. An adult anesthesia target control intelligent method based on electroencephalogram signal monitoring is characterized by comprising the following steps:
step 1: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol;
step 2: injecting the target anesthetic into a target adult based on a preset injection pump, and acquiring an electroencephalogram signal of the target adult in real time;
and step 3: and determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, and controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth to finish intelligent target control on adult anesthesia.
2. The intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals as claimed in claim 1, wherein in step 1, determining an anesthesia scheme for a target adult based on the operation type of the target adult comprises:
acquiring diagnostic data of a target adult and determining attribute information of the diagnostic data;
matching a target operation type consistent with the attribute information from a preset operation type library based on the attribute information, and determining the complexity of the target operation type based on the attribute information of the diagnosis data;
and determining an anesthesia scheme required when the target operation type is carried out on the target adult based on the complexity, wherein the anesthesia scheme comprises a whole vein anesthesia and a static suction compound anesthesia.
3. The electroencephalogram signal-based monitoring adult anesthesia target control intelligent method as claimed in claim 1, wherein in step 1, the determination of the target anesthetic agent required for the anesthesia of the target adult based on the anesthesia scheme comprises:
acquiring an anesthesia scheme of the target adult, and determining a target anesthetic class corresponding to the operation type of the target adult based on the anesthesia scheme, wherein each anesthetic class comprises a plurality of anesthetics;
acquiring the allergy history of the target adult, and screening the anesthetic contained in the category of the target anesthetic based on the allergy history to obtain the target anesthetic, wherein the allergy history comprises the allergy condition of the target adult to the anesthetic.
4. The electroencephalogram signal monitoring adult anesthesia target control intelligent method based on claim 3, wherein the target anesthetic is obtained by screening anesthetic agents contained in the target anesthetic category based on the allergy history, and the method comprises the following steps:
acquiring categories of anesthetic agents to be selected, which are obtained by screening anesthetic agents contained in the categories of the target anesthetic agents based on the allergy history, wherein the categories of the anesthetic agents to be selected are at least one;
extracting the medicament attribute information of the to-be-selected anesthetic type, and simultaneously acquiring the operation type of the target adult;
and performing anesthesia effect evaluation on the to-be-selected anesthetic type based on the operation type and the medicament attribute information, and selecting an optimal anesthetic type from the to-be-selected anesthetic type as a target anesthetic required in the target adult operation process based on an evaluation result.
5. The intelligent adult anesthesia target control method based on electroencephalogram signal monitoring as claimed in claim 1, characterized in that the step 1: determining an anesthesia protocol for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia protocol, comprising:
constructing a time estimation model, acquiring the operation type of a target adult, and acquiring medical record data of the target adult;
acquiring a historical operation type and corresponding operation data, and determining the complexity of the historical operation, the average time consumption of the historical operation and the time increase of the operation emergency based on the historical operation type and the corresponding operation data;
determining training parameters of the time estimation model based on the complexity, the average time consumption of the historical operation and the operation emergency condition in a time adding manner, and training 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 estimated time consumption corresponding to the operation type;
determining a quantity of priming drug for the target anesthetic agent based on the estimated elapsed time.
6. The intelligent method for monitoring the adult anesthesia target control based on the electroencephalogram signal as claimed in claim 1, wherein in the step 2, the target anesthetic agent is injected to the target adult based on a preset injection pump, and the electroencephalogram signal of the target adult is collected in real time, and the method comprises the following steps:
acquiring vital sign information of a target adult, and transmitting the vital sign information to a management terminal for analysis and processing to obtain an injection speed required by the target adult in the operation process;
controlling the preset injection pump to inject the target anesthetic into the target adult based on the injection speed, simultaneously determining a target acquisition area on the scalp of the target adult, and acquiring an electroencephalogram signal of the target adult in the target acquisition area based on a preset electroencephalogram signal acquisition probe;
dividing the electroencephalogram signal into M sections of sub-electroencephalogram signals, and marking each section of sub-electroencephalogram signal;
determining the frequency fluctuation range value and the brain energy fluctuation range of the target adult electroencephalogram signal in each section of sub-electroencephalogram signals based on the marking result, comparing the frequency fluctuation range value and the brain energy fluctuation range of the target adult electroencephalogram signal with the frequency fluctuation range value and the preset brain energy fluctuation range value of a preset standard electroencephalogram signal, and determining interference electroencephalograms in which the frequency fluctuation range value in each section of sub-electroencephalogram signals is not within the preset standard electroencephalogram signal frequency fluctuation range value and the preset brain energy fluctuation range value;
filtering the interference electroencephalogram signal to obtain a sub-electroencephalogram signal to be amplified, and fusing the sub-electroencephalogram signal to be amplified based on a marking result to obtain an electroencephalogram signal to be amplified;
common-mode interference elimination is carried out on the electroencephalogram signals of the target adults based on a preset method to obtain electroencephalogram common-mode signals;
carrying out differential amplification on the electroencephalogram signal to be amplified and the electroencephalogram common-mode signal to obtain an electroencephalogram amplified signal of the target adult;
acquiring a data format requirement of a preset electroencephalogram signal display device for an electroencephalogram signal to be displayed, and performing data format conversion on the electroencephalogram amplified signal based on the data format requirement to obtain a target electroencephalogram signal;
and transmitting the target electroencephalogram signal to the preset electroencephalogram signal display equipment for displaying, and completing acquisition of the electroencephalogram signal of the target adult.
7. The intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals, as claimed in claim 6, is characterized in that the target electroencephalogram signals are transmitted to the preset electroencephalogram signal display equipment for display, and the acquisition of the electroencephalogram signals of the target adult is completed, and comprises:
acquiring a target electroencephalogram signal of the target adult, and acquiring identity information of the target adult and an injected target anesthetic;
determining the number of items to be recorded based on the target electroencephalogram signals, the identity information and the injected target anesthetic, and matching a target report template from a preset recording template library based on the items to be recorded;
filling specific recording data corresponding to a to-be-recorded item to a target position in the target report template respectively to generate an electroencephalogram signal recording report sheet of a target adult, wherein the to-be-recorded item comprises a target electroencephalogram signal, identity information of the target adult, an injected target anesthetic and time for injecting the target anesthetic, and the target electroencephalogram signal, the injected target anesthetic and the time for injecting the target anesthetic correspond to the identity information of the target adult one by one respectively;
and transmitting the electroencephalogram signal recording report sheet to a preset storage area for storage, and completing the recording of the target electroencephalogram signal.
8. The electroencephalogram signal-based monitoring adult anesthesia target control intelligent method according to claim 1, wherein in step 3, the sedation depth and the analgesia depth of the target adult are determined based on the electroencephalogram signal, 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 the analgesia depth, and the method comprises the following steps:
acquiring an electroencephalogram signal of a target adult, and determining a state time sequence corresponding to the electroencephalogram signal after the target adult receives the target anesthetic, wherein the electroencephalogram signal corresponds to the state time sequence;
decomposing the electroencephalogram signal based on a preset signal decomposition method to obtain the frequency and the power of the electroencephalogram signal at different state time points, and determining the heartbeat information and the breathing information of the target adult at different state time points based on the frequency and the power of the electroencephalogram signal;
establishing an anesthesia evaluation model, and inputting heartbeat information and respiratory information of the target adult at different state time points into the anesthesia evaluation model to obtain consciousness indexes and nociceptive sensitivity indexes of the target adult at different state time points;
acquiring a preset comparison table, and searching the sedation depth and the analgesia depth of the target adult at different state time points in the preset comparison table based on the consciousness index and the nociception sensitivity index;
comparing the sedation depth and the analgesia depth of the target adult at different state time points with a preset sedation depth and a preset analgesia depth respectively;
if the sedation depth or the analgesia depth is smaller than the preset sedation depth or the preset analgesia depth, judging that the anesthesia of the target adult is unqualified, and adjusting the injection speed of a current preset injection pump and the injection amount of a target anesthetic based on the sedation depth and the analgesia depth;
otherwise, judging that the anesthesia of the target adult is qualified, and monitoring the sedation depth and analgesia depth of the target adult in the next time period in real time until the current operation is completed.
9. The intelligent method for monitoring adult anesthesia target control based on electroencephalogram signals of claim 8, wherein adjusting the injection speed of the current preset injection pump and the injection amount of the target anesthetic agent based on the sedation depth and analgesia depth comprises:
when the anesthesia of the target adult is judged to be unqualified, an alarm signal is sent to a management terminal;
meanwhile, obtaining the analgesia depth and the sedation depth of the target adult, and calculating target difference values between the analgesia depth and the sedation depth and between a preset analgesia depth and a preset sedation depth;
determining a correction value for the injection speed of the preset injection pump and an adjustment value for the injection amount of the target anesthetic agent based on the target difference value;
and adjusting the injection speed of a preset injection pump and the injection amount of the target anesthetic on the basis of the corrected value of the injection speed and the adjustment value of the injection amount.
10. The utility model provides an adult anesthesia target control intelligent system based on brain electrical signal monitoring which characterized in that includes:
an anesthetic agent type determination module for determining an anesthesia scheme for a target adult based on a surgical type of the target adult and determining a target anesthetic agent required for anesthesia of the target adult based on the anesthesia scheme;
the electroencephalogram signal acquisition module is used for injecting the target anesthetic into a target adult based on a preset injection pump and acquiring electroencephalogram signals of the target adult in real time;
and the anesthesia target control module is used for determining the sedation depth and the analgesia depth of the target adult based on the electroencephalogram signals, controlling the injection speed of the preset injection pump and the injection amount of the target anesthetic based on the sedation depth and the analgesia depth, and completing intelligent target control on adult anesthesia.
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| CN116617492B (en) * | 2023-05-22 | 2024-05-07 | 深圳市威浩康医疗器械有限公司 | Target control intelligent system for anesthesia by gastrointestinal endoscopy |
| CN117838063A (en) * | 2024-03-04 | 2024-04-09 | 江西杰联医疗设备有限公司 | Physiological information early warning processing system and electronic equipment under anesthesia scene |
| CN117838063B (en) * | 2024-03-04 | 2024-05-24 | 江西杰联医疗设备有限公司 | Physiological information early warning processing system and electronic equipment under anesthesia scene |
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