CN114177415A

CN114177415A - Intelligent method and system for monitoring anesthesia target control of old people based on electroencephalogram signals

Info

Publication number: CN114177415A
Application number: CN202210030190.6A
Authority: CN
Inventors: 王天龙; 薛庆生; 杨建军; 崔德荣; 刘存明; 耿智隆; 埃里克·韦伯·詹森; 卞汉道
Original assignee: Shenzhen Yuanhai Hengxin Medical Technology Co ltd; Shenzhen City Weihaokang Medical Instrument Ltd
Current assignee: Shenzhen Yuanhai Hengxin Medical Technology Co ltd; Shenzhen City Weihaokang Medical Instrument Ltd
Priority date: 2022-01-12
Filing date: 2022-01-12
Publication date: 2022-03-15

Abstract

The invention provides an intelligent method and system for monitoring anesthesia target control of old people based on electroencephalogram signals, wherein the method comprises the following steps: acquiring the amount of anesthetic agent injected by a target old man at different target time points, and acquiring electroencephalogram signals of the target old man at different target time points in real time; determining consciousness indexes and injury indexes of the target old people under different dosages of anesthetics based on the electroencephalogram signals, and determining initial anesthesia unconsciousness critical points and sedation deep and shallow critical points of the target old people based on the consciousness indexes and the injury indexes; and determining the physiological parameters of the target old at the critical point, and integrating and recording the critical point, the dosage of the anesthetic corresponding to the critical point and the physiological parameters. By determining the consciousness activity intensity of the old under different doses of anesthetic, the critical point of deep and shallow sedation of the old can be conveniently and accurately found, so that the anesthetic dose can be conveniently adjusted to enable the patient to be in a good anesthetic state, the anesthetic efficiency is improved, the anesthetic level is enhanced, and the injury of the anesthetic to the patient is reduced.

Description

Intelligent method and system for monitoring anesthesia target control of old people based on electroencephalogram signals

Technical Field

The invention relates to the technical field of medicine research, in particular to an intelligent method and system for monitoring anesthesia target control of old people based on electroencephalogram signals.

Background

At present, anesthesia becomes an essential one-step operation in the operation process, and not only can the patient be stopped from knowing in the operation, but also the operation efficiency is improved;

however, currently, most of medical clinics predict the amount of anesthetic required by a patient according to the working experience of medical staff, and the current anesthetic state of the patient cannot be known in real time in the injection process, which easily causes more or less anesthetic, so that the anesthetic effect is greatly reduced, and the anesthetic state of the patient cannot be adjusted to the optimal anesthetic state in time according to the operation requirement;

therefore, the invention provides an intelligent method and system for monitoring anesthesia target control of the old based on electroencephalogram signals, which are used for determining the consciousness activity intensity of the old under different doses of anesthetic, so that the accurate finding of the critical point of the anesthesia depth and the anesthesia depth of the old is facilitated, the anesthetic dose can be conveniently adjusted according to the operation requirement, the patient is in a good anesthesia state, the anesthesia efficiency is improved, the anesthesia level is enhanced, the intraoperative awareness is avoided, and the injury of the anesthetic to the patient is reduced.

Disclosure of Invention

The invention provides an electroencephalogram signal monitoring-based elderly anesthesia target control intelligent method and system, which are used for determining the consciousness activity intensity of the elderly under different doses of anesthetics, so that the elderly can find the initial anesthesia unconsciousness critical point and the sedation depth and shallow critical point accurately, the anesthesia dose can be adjusted according to the operation requirement, a patient is in a good anesthesia state, the anesthesia efficiency is improved, the anesthesia level is enhanced, the intraoperative awareness is avoided, and the injury of anesthetics to the patient is reduced.

The invention provides an intelligent method for monitoring anesthesia target control of old people based on electroencephalogram signals, which comprises the following steps:

step 1: acquiring the doses of anesthetics injected by a target old man at different target time points, and acquiring electroencephalogram signals of the target old man at different target time points in real time;

step 2: determining consciousness index injury indexes of the target old people under different doses of anesthetics based on electroencephalogram signals, and determining initial anesthesia unconsciousness critical points and sedation depth and shallow critical points of the target old people based on the consciousness indexes and the injury indexes;

and step 3: and determining the brain physiological parameters of the target old at the initial anesthesia unconsciousness critical point and the sedation depth and shallow critical point, and performing integrated recording on the initial anesthesia unconsciousness critical point, the sedation depth and shallow critical point and the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters.

Preferably, the intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals, in the step 1, the dosage of the anesthetic injected by the target elderly at different target time points is obtained, and the method comprises the following steps:

acquiring initial time information of a target old man for receiving anesthetic injection, and determining the injection speed of a preset anesthetic injection pump, wherein the injection speed of the preset anesthetic injection pump is constant;

acquiring current time information, and determining the working time of the preset anesthetic injection pump based on the current time information and the initial time information of the target old people for receiving anesthetic injection;

and calculating the doses of the anesthetics which are injected by the target old people at different target time points based on the working time and the injection speed of a preset anesthetic injection pump.

Preferably, the intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals, which is based on the working time and the injection speed of a preset anesthetic injection pump, calculates the doses of anesthetics to be injected by the target elderly at different target time points, and comprises the following steps:

acquiring the doses of the anesthetics which are injected by the target old people at different target time points, and determining the remaining time length of the operation maintenance period of the target old people, wherein the doses of the anesthetics which are injected by the different target time points are obtained by accumulating the doses of the anesthetics which are received by the target old people based on time development;

acquiring the dose of the anesthetic injected into the body of the target old man at the current moment, and judging whether the current dose of the anesthetic in the body of the target old man can finish the remaining time length of the operation maintenance period or not based on a preset anesthesia maintenance method;

if yes, stopping injecting the anesthetic into the target old man body, and sending an early warning prompt to medical staff;

otherwise, continuing to inject anesthetic into the target old man, and monitoring the electroencephalogram signals of the target old man in real time.

Preferably, the intelligent method for monitoring the anesthesia target control of the old people based on electroencephalogram signals, in the step 1, the electroencephalogram signals of the target old people at different target time points are collected in real time, and the method comprises the following steps:

acquiring a signal acquisition instruction sent by a management terminal, and controlling a preset electroencephalogram signal acquisition device to open a signal acquisition channel based on the signal acquisition instruction;

monitoring the electroencephalogram signals of the target old people after receiving the anesthetic injection in real time based on a preset electroencephalogram electrode assembly, and transmitting the electroencephalogram signals to a preset electroencephalogram signal acquisition device based on the signal acquisition channel;

the preset electroencephalogram signal acquisition device performs clutter filtering processing and signal enhancement processing on the electroencephalogram signal, and performs analog-to-digital conversion on the processed electroencephalogram signal based on a preset method to obtain an electroencephalogram signal to be displayed;

and displaying the electroencephalogram signals to be displayed based on the preset electroencephalogram signal acquisition device, and acquiring the electroencephalogram signals of the target old at different target time points.

Preferably, an intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals, in step 1, the dosage of anesthetic injected by a target elderly at different target time points is obtained, and electroencephalogram signals of the target elderly at different target time points are collected in real time, and the method comprises the following steps:

acquiring doses of anesthetics injected by a target old man at different target time points and electroencephalograms corresponding to the different target time points, wherein the time intervals between the anesthetics injected and the electroencephalograms are consistent;

determining the corresponding relation between the dose of the anesthetic injected into the target old man body and the electroencephalogram signals based on the time interval, and marking the dose of the anesthetic at the same time point and the corresponding electroencephalogram signals based on the corresponding relation;

and generating a target report sheet by using the dosage of the anesthetic at the same time point and the corresponding electroencephalogram signal based on the marking result, and storing and recording the target report sheet.

Preferably, in step 2, a consciousness index and a damage index of the target elderly at different doses of anesthetics are determined based on the electroencephalogram signal, and an initial anesthesia unconsciousness critical point and a sedation depth and shallow critical point of the target elderly are determined based on the consciousness index, and the method includes the following steps:

acquiring electroencephalograms of the target old man at different target time points, and determining the average path length of the electroencephalograms at the different target time points based on a preset electroencephalogram processing method;

determining time series signal characteristics of the electroencephalogram signals under different target time points based on the average path length, and sequentially converting the electroencephalogram signals of different time domains into digital electroencephalogram signal sequences based on the time series signal characteristics;

determining crossing information points of digital electroencephalogram signal sequences of adjacent time domains, and determining voltage values corresponding to the crossing information points based on a preset processing method;

determining consciousness indexes and injury indexes of the target old people at different time points based on the voltage value;

acquiring the total number of consciousness indexes and injury indexes of the target old man at different time points, and simultaneously determining the width of a display area in a line graph to be displayed, wherein the width of the display area comprises the number of displayable data;

determining whether the width of the display area can display the consciousness indexes and the injury indexes at different time points at one time or not based on the corresponding relation between the width of the display area and the number of displayable data;

if not, grouping the consciousness indexes and the injury indexes at different time points to obtain N consciousness index groups to be displayed, determining drawing points of the consciousness indexes at different time points in the line graph to be displayed based on the time point sequence corresponding to the consciousness indexes, and respectively obtaining N consciousness indexes and injury index line graphs based on the drawing points;

otherwise, displaying the consciousness indexes at different time points at one time to obtain corresponding consciousness indexes and injury index line graphs;

determining the brain consciousness and brain energy activity intensity of the target old people at different target time points based on the consciousness index and injury index line graph, and determining the turning point of the brain consciousness and brain energy activity intensity of the target old people based on the brain consciousness and brain energy activity intensity, wherein the different target time points correspond to different dosages of anesthetic;

and determining the initial anesthesia unconsciousness critical point and the critical point of deep and shallow sedation of the target old based on the transition point of the brain consciousness and the brain energy activity intensity of the target old.

Preferably, in step 3, determining the brain physiological parameters of the target elderly at the initial anesthesia unconsciousness critical point and the sedation depth and superficial critical point, and performing integrated recording on the initial anesthesia unconsciousness critical point, the sedation depth and superficial critical point, and the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters, the method for monitoring the anesthesia target control of the elderly based on the electroencephalogram signal comprises the following steps:

acquiring an initial anesthesia unconsciousness critical point and a sedation depth and shallowness critical point of the target old man, and acquiring brain physiological parameters of the target old man based on the initial anesthesia unconsciousness critical point and the sedation depth and shallowness critical point, wherein the physiological parameters are at least two;

acquiring historical brain physiological parameter values, and determining fluctuation range values of various brain physiological parameters of a patient at an initial anesthesia unconsciousness critical point and a sedation depth and shallow critical point based on the historical brain physiological parameter values;

verifying the acquired brain physiological parameters of the target old man based on the fluctuation range value, and judging whether the brain physiological parameters of the target old man are in the fluctuation range value;

if not, judging that the acquired brain physiological parameters of the target old people are abnormal, and inputting the brain physiological parameters of the target old people into a preset physiological parameter calibration model for calibration, wherein the preset brain physiological parameter calibration model is obtained by training historical brain physiological parameter values, the preset brain physiological parameter calibration model comprises a plurality of modules for verifying body physiological parameters, and the modules are independent from each other;

otherwise, judging that the acquired brain physiological parameters of the target old people are not abnormal;

generating a recording report task based on the initial anesthesia unconsciousness critical point, the sedation depth and superficial critical point, the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters, and matching a target report template from a preset report template library based on the recording report task;

visually configuring the target report template, and determining the initial anesthesia unconsciousness critical point, the critical point of the sedation depth and the sedation depth, the dosage of the anesthetic corresponding to the critical point and the target position of the brain physiological parameter in the target report template based on the visual configuration;

filling the initial anesthesia unconsciousness critical point, the sedation depth and superficial critical point, the dosage of the anesthetic corresponding to the critical point and the brain physiological parameter into the target position in the target report template respectively based on the target position to obtain an anesthesia parameter recording report sheet;

and sending the anesthesia parameter recording report sheet to a management terminal, and storing the anesthesia parameter recording report sheet in a preset storage area to finish the integrated recording of the initial anesthesia unconsciousness critical point, the sedation depth and shallow critical point, the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters.

Preferably, the intelligent method for monitoring the anesthesia target control of the old based on the electroencephalogram signal to obtain the anesthesia parameter recording report sheet comprises the following steps:

acquiring a plurality of groups of anesthesia parameter record report sheets corresponding to different operations of the old, and classifying the anesthesia parameter record report sheets based on operation types to obtain a target classification result, wherein the number of the anesthesia parameter record report sheets corresponding to each operation type is at least two, and the operation types are at least two;

packing the anesthesia parameter record report sheet corresponding to each type of operation type based on the target classification result to obtain a target data packet;

respectively storing the target data packets to obtain an anesthesia parameter record report list reference library;

and creating index keywords in the storage address of the anesthesia parameter record report list reference library based on the target data packet corresponding to each type of operation, and sending the index keywords to the medical staff terminal.

Preferably, an intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals sends the index keywords to a medical staff terminal, and the method comprises the following steps:

acquiring operation data of the current old man, and determining a target operation type of the current old man operation based on the operation data;

determining a target index keyword based on the target operation type, and searching a target data packet corresponding to the target operation type in the anesthesia parameter record report list reference library based on the target index keyword;

determining a target anesthesia depth required by the current old man operation based on the current old man operation data, and matching the target anesthesia depth with each anesthesia parameter recorded in each anesthesia parameter recording report in a target data packet to obtain a target critical point;

determining the dosage of a target anesthetic corresponding to the target critical point, preparing and injecting the anesthetic required by the current old man based on the dosage of the target anesthetic, and ensuring that the current old man is anesthetized to the target anesthetic depth required by the operation.

Preferably, an intelligent system based on brain electrical signal monitoring old man's anesthesia target accuse includes:

the electroencephalogram signal acquisition module is used for acquiring the doses of the anesthetics injected by the target old people at different target time points and acquiring electroencephalogram signals of the target old people at different target time points in real time;

the analysis module is used for determining consciousness indexes of the target old people under different anesthetic doses based on the electroencephalogram signals and determining an initial anesthesia unconsciousness critical point and a deep and shallow sedation critical point of the target old people based on the consciousness indexes;

and the integrated recording module is used for determining the brain physiological parameters of the target old at the initial anesthesia unconsciousness critical point and the sedation depth and superficial critical point, and performing integrated recording on the initial anesthesia unconsciousness critical point, the sedation depth and superficial critical point and the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters.

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 anesthesia target control of the elderly based on electroencephalogram signals in the embodiment of the invention;

FIG. 2 is a flowchart of step 1 in an intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals in the embodiment of the invention;

fig. 3 is a structural diagram of an intelligent anesthesia target control system for monitoring elderly people based on electroencephalogram signals in the embodiment of the 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 intelligent method for monitoring anesthesia target control of the old based on electroencephalogram signals, which comprises the following steps of:

step 2: determining consciousness indexes of the target old people under different doses of anesthetics based on electroencephalogram signals, and determining initial anesthesia unconsciousness critical points and critical points of deep and shallow sedation of the target old people based on the consciousness indexes;

In this example, the target elderly refers to patients 61-80 years old.

In this embodiment, the target time point refers to the patient receiving a dose of anesthetic in vivo at different times during the operation, for example, 10 ml of anesthetic is injected in vivo after one hour of the operation, 20 ml of anesthetic is injected in vivo for two hours, etc.

In this embodiment, the consciousness index and the injury index are used to describe the brain consciousness and the brain energy kinetic strength, i.e. the degree of surgical awareness, of the target elderly with different doses of anesthetic.

In this embodiment, the initial anesthesia unconsciousness threshold and the threshold of deep and shallow sedation refer to the intersection of the trend curves of the target geriatric consciousness index and injury index.

In this embodiment, the physiological parameters refer to electrocardio, blood pressure, blood oxygen, and the like of the target elderly.

The beneficial effects of the above technical scheme are: through confirming old man's brain consciousness and brain energy activity intensity under different dose narcotics, be favorable to accurately finding old man's initial anesthesia patient unconsciousness critical point and the deep and shallow critical point of sedation to carry out the record, thereby be convenient for according to the operation needs, the fast adjustment anesthetic dose makes the patient be in good anesthesia state, improved anesthesia efficiency, strengthened the anesthesia level, stopped intraoperative knowledge, reduced the injury of narcotic to the patient.

Example 2:

on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring anesthesia target control of an elderly person based on electroencephalogram signals, as shown in fig. 2, in step 1, acquiring doses of anesthetics that a target elderly person receives injections at different target time points includes:

step 101: acquiring initial time information of a target old man for receiving anesthetic injection, and determining the injection speed of a preset anesthetic injection pump, wherein the injection speed of the preset anesthetic injection pump is constant;

step 102: acquiring current time information, and determining the working time of the preset anesthetic injection pump based on the current time information and the initial time information of the target old people for receiving anesthetic injection;

step 103: and calculating the doses of the anesthetics which are injected by the target old people at different target time points based on the working time and the injection speed of a preset anesthetic injection pump.

In this embodiment, the start time information refers to time information of receiving anesthesia when the target elderly are prepared before the operation, and may be, for example, 9: 00 receive anesthetic injections.

In this embodiment, the preset anesthetic injection pump is set in advance, and includes various injection pumps, such as a control sedation injection pump, a sufen injection pump, and the like.

In this embodiment, the current time information refers to the time information determined currently for determining the dosage of the anesthetic, and the target elderly people still receive the anesthetic injection at the current time.

The beneficial effects of the above technical scheme are: the injection time and the injection speed of the preset anesthetic injection pump are determined, so that the dosage of anesthetics at different time points is accurately calculated, the electroencephalogram signals of the aged after the anesthetics with different dosages are injected into the body of the target aged are convenient to determine, the accuracy of analyzing the anesthesia state of the target aged is improved, and convenience is provided for determining the dosage of the anesthetics at the critical points of deep anesthesia and shallow anesthesia.

Example 3:

on the basis of the foregoing embodiment 2, this embodiment provides an intelligent method for monitoring anesthesia target control of an elderly person based on electroencephalogram signals, where the method includes calculating, based on the operating time and an injection speed of a preset anesthetic injection pump, doses of anesthetics that the targeted elderly person receives injections at different target time points, and includes:

In this embodiment, the remaining time length of the operation maintenance period refers to the current remaining time length of the target elderly during the operation, for example, the whole operation requires 3 hours, the operation has been performed for two hours, and the remaining time length of the operation maintenance period is 1 hour.

In this embodiment, the dosage of the anesthetic injected into the target elderly person at the current time refers to the total amount of the anesthetic injected into the target elderly person from the beginning of the operation to the current time.

In this embodiment, the preset anesthesia maintenance method is set in advance, and may be, for example, prediction based on historical surgical anesthesia data.

The beneficial effects of the above technical scheme are: whether the dose of the anesthetic received by the current target old man is enough to complete the remaining operation task of the target old man or not is determined, so that the anesthetic can be stopped from being injected in time, the injury of the anesthetic to the body is reduced, and meanwhile, the anesthetic dose can be adjusted according to the operation requirement, so that the patient is in a good anesthetic state, and the anesthetic effect is improved.

Example 4:

on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring anesthesia target control of an elderly person based on electroencephalogram signals, and in step 1, acquiring electroencephalogram signals of the target elderly person at different target time points in real time includes:

In this embodiment, the preset electroencephalogram signal acquisition device is set in advance, and may be, for example, an electroencephalogram acquisition device in the existing medical field.

In this embodiment, the preset electroencephalogram electrode assembly refers to an assembly which is in contact with the scalp of the target elderly in the preset electroencephalogram signal acquisition device, and can accurately acquire the electroencephalogram signal of the target elderly through the cerebral cortex of the target elderly.

In this embodiment, clutter filtering processing and signal enhancement processing refer to the noise wave in the EEG of filtering, and carry out signal amplification with the EEG after the filtration, and medical personnel of being convenient for clearly look over the particular circumstances of target old man's EEG.

In this embodiment, the preset method is set in advance, and for example, the acquired electroencephalogram signals may be converted into corresponding digital signals by an analog-to-digital converter, so that the electroencephalogram signals are displayed.

The beneficial effects of the above technical scheme are: the electroencephalogram signals of the target old people are collected in real time by controlling the preset electroencephalogram signal collecting device, and the electroencephalogram signals of the target old people under different anesthetic agent doses can be accurately obtained, so that convenience is provided for accurately determining the initial anesthesia unconsciousness critical point and the sedation depth and shallow critical point of the target old people, and the anesthesia effect is improved.

Example 5:

on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring anesthesia target control of an elderly person based on electroencephalogram signals, and in step 1, the method includes the steps of obtaining doses of anesthetic injected by a target elderly person at different target time points, and acquiring electroencephalogram signals of the target elderly person at different target time points in real time, where the method includes:

In this embodiment, the fact that the time intervals between the anesthetic injected and the acquired electroencephalogram signal are consistent means that the acquired electroencephalogram signal is acquired in real time according to the amount of the anesthetic in the target elderly after the target elderly receive the anesthetic injection, for example, when the operation is performed for ten minutes, the volume of the anesthetic in the target elderly is 5 ml, and at this time, the electroencephalogram signal of the target elderly is acquired from the beginning of the anesthetic injection to the time of ten minutes.

In this embodiment, the correspondence relationship means that each time point corresponds to one electroencephalogram signal, and the time point may be one second, one minute, or the like.

In the embodiment, the marking refers to marking the dosage of the anesthetic and the electroencephalogram signal by adopting a uniform mark symbol at the same time point, so that the electroencephalogram signal condition of the target old people under different dosages of the anesthetic can be conveniently determined.

In the embodiment, the target report sheet refers to recording the dosage of the anesthetic and the corresponding electroencephalogram signals at the same time point, so that convenience is provided for analyzing the initial anesthesia unconsciousness critical point and the sedation depth and superficial critical point in the later period.

The beneficial effects of the above technical scheme are: by determining the electroencephalogram signals of the target old people under the anesthetics with different dosages at different time points, determining the corresponding relation between the electroencephalogram signals and the corresponding relation, and recording the corresponding relation between the electroencephalogram signals and the corresponding relation, convenience is provided for analyzing the initial anesthesia unconsciousness critical point and the sedation depth and shallow critical point of the target old people, the accuracy of the anesthesia depth and shallow critical point is improved, the anesthesia effect is enhanced, and the injury of the anesthetics to patients is reduced.

Example 6:

on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring anesthesia target control of an aged based on electroencephalogram signals, and in step 2, a consciousness index of the target aged at different dosages of anesthetics is determined based on electroencephalogram signals, and an initial anesthesia unconsciousness critical point and a critical point of deep and shallow sedation of the target aged are determined based on the consciousness index, including:

if not, grouping the consciousness indexes and the injury indexes at different time points to obtain N consciousness indexes and injury index groups to be displayed, determining drawing points of the consciousness indexes and the injury indexes at different time points in the line graph to be displayed based on the time point sequence corresponding to the consciousness indexes and the injury indexes, and respectively obtaining N consciousness indexes and injury index line graphs based on the drawing points;

determining the brain consciousness and brain energy activity intensity of the target old people at different target time points based on the consciousness index broken line graph, and determining the turning point of the brain consciousness and brain energy activity intensity of the target old people based on the brain consciousness and brain energy activity intensity, wherein the different target time points correspond to different dosages of anesthetic;

In this embodiment, the preset electroencephalogram signal processing method is set in advance, and for example, the average path length of the electroencephalogram signal may be determined by wavelet reconstruction, windowed horizontal-view complex network conversion, and complex network analysis.

In this embodiment, the average path length of the electroencephalogram signals refers to the distance from the electroencephalogram signals collected from the head of the target old person to the electroencephalogram signal display end, and is used for determining the sequence of transmitting the electroencephalogram signals to the display end.

In this embodiment, the time-series signal characteristics refer to the chronological order in which the brain wave signals are transmitted from the head of the target elderly to the brain wave display.

In this embodiment, the digital brain electrical signal sequence refers to converting the analog brain electrical signal collected from the head of the target old person into a digital signal that can be read and processed by a machine.

In this embodiment, the cross information point refers to a changed electroencephalogram signal part in the electroencephalogram signal of the target aged person at an adjacent time point.

In this embodiment, the preset processing method is set in advance, for example, conversion may be performed by a professional machine, for example, a brain wave machine may determine a voltage value corresponding to a brain electrical signal of a target elderly person in different situations.

In the embodiment, the consciousness index is used for measuring the wakefulness degree of the current brain of the target old man, the injury index is used for measuring the pain sensitivity degree of the current brain of the old man in the initial operation stage, and after the analgesia reaches the standard, the index can measure the wakefulness level of the current brain of the target old man.

In this embodiment, the one-time display means that consciousness indexes and injury indexes of current target elderly people at different time points are displayed in a unified line graph through the line graph.

In the embodiment, the drawing point refers to the positions of different consciousness indexes and injury indexes in the line graph, so that the position information of each consciousness index and injury index can be conveniently determined according to the value of each consciousness index and injury index, and the consciousness index and injury index can be displayed in detail through the line graph.

In this embodiment, the brain consciousness activity intensity refers to the degree of consciousness and the level of consciousness of the target elderly in different doses of anesthetic.

In this embodiment, the transition point of the brain consciousness and brain energy activity intensity refers to the point at which the brain consciousness and brain energy change from active to inactive.

In this embodiment, determining the target elderly initial anesthesia unconsciousness critical point and the critical point of deep and shallow sedation based on the turning point of the target elderly brain-conscious brain energy activity intensity includes:

the method comprises the following steps of obtaining the amount of an anesthetic agent injected by a target old man at a target time point, calculating a comprehensive evaluation value of a brain consciousness index and a damage index of the target old man at the target time point based on the amount of the anesthetic agent, and calculating the anesthetic efficiency of the anesthetic agent based on the comprehensive evaluation value of the brain consciousness index and the damage index, wherein the specific steps comprise:

calculating a brain consciousness index and injury index comprehensive evaluation value of the target old people according to the following formula:

wherein alpha represents a brain consciousness index and injury index comprehensive evaluation value of the target elderly; t represents the average change period of the electroencephalogram signal of the target elderly; beta represents the dose of anesthetic currently being injected by the target elderly; theta represents an anesthetic coefficient and has a value range of (0.8, 0.95); f represents the frequency value of the electroencephalogram signal when the target old people do not inject the anesthetic; f represents the frequency value of the electroencephalogram signal after the target old people receive the target dose of the anesthetic; v represents the speed value of the target old people absorbing the narcotics; t represents the total time length value of the target old people for absorbing the narcotic;

the anesthetic efficiency of the anesthetic at the target time point is calculated according to the following formula:

wherein eta represents the anesthesia efficiency of the anesthetic at the target time point, and the numeric area is (0, 1); mu represents an error factor, and the value range is (0.1, 0.15); k is a radical of₁A value representing a length of time it takes for the targeted elderly to receive an anesthetic injection to an initial anesthesia loss perception critical point and a critical point of deep and shallow sedation; k is a radical of₂Indicating unconsciousness threshold and deep sedation of the elderly from receiving anesthetic injection to initial anesthesiaAverage length of time values used for shallow critical points; alpha is alpha₁Representing the comprehensive evaluation value of the brain consciousness index and the injury index of the target old without injection of anesthetic, wherein the value is greater than alpha; h is₂A value representing the length of time the anesthetic is maintained after the injection of the anesthetic is stopped; h is₁The time length value which represents the time length value that the target old man needs to spend in the rest operation is less than h₂；

Comparing the anesthesia efficiency obtained by calculation with a preset anesthesia efficiency;

if the anesthesia efficiency is greater than or equal to the preset anesthesia efficiency, judging that the anesthetic is qualified to use;

otherwise, judging that the anesthetic is unqualified to use, and adjusting the injection speed of the anesthetic until the anesthetic efficiency is greater than or equal to the preset anesthetic efficiency.

The preset anesthesia efficiency is set in advance.

The brain consciousness index and the injury index are obtained by calculation according to the fluctuation frequency and the change degree of energy of the electroencephalogram signal of the target old after the target old receives the anesthetic injection.

The anesthetic coefficient refers to the paralysis degree of the anesthetic on the cranial nerves of the old after the target old receives the anesthetic injection, and the larger the value is, the faster the cranial nerves of the old are paralyzed.

The average time length value refers to an average value of time taken for a plurality of groups of old people to anaesthetize to a critical point, and operations performed by the plurality of groups of old people are consistent with those of a target old person.

The beneficial effects of the above technical scheme are: the acquired electroencephalogram signals are subjected to data conversion, so that values of various data of the electroencephalogram signals are accurately analyzed, the consciousness index of a target old man is judged in a voltage mode through the electroencephalogram signals, the active strength of the brain of the target old man is accurately confirmed, and finally the consciousness index and the injury index of the target old man at different time points are displayed by adopting a broken line graph.

Example 7:

on the basis of the foregoing embodiment 1, this embodiment provides an intelligent method for monitoring anesthesia target control of an elderly person based on electroencephalogram signals, and in step 3, determining physiological parameters of the target elderly person at the initial anesthesia unconsciousness critical point and the sedation depth and shallowness critical point, and performing integrated recording on the initial anesthesia unconsciousness critical point, the sedation depth and shallowness critical point, and the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters, including:

acquiring an initial anesthesia unconsciousness critical point and a sedation depth and superficial critical point of the target old man, and acquiring brain physiological parameters of the target old man based on the initial anesthesia unconsciousness critical point and the sedation depth and superficial critical point, wherein the brain physiological parameters are at least two;

if not, judging that the acquired brain physiological parameters of the target old people are abnormal, and inputting the brain physiological parameters of the target old people into a preset brain physiological parameter calibration model for calibration, wherein the preset brain physiological parameter calibration model is obtained by training historical brain physiological parameter values, the preset brain physiological parameter calibration model comprises a plurality of modules for verifying body physiological parameters, and the modules are independent from each other;

otherwise, judging that the acquired physiological parameters of the target old people are not abnormal;

In this embodiment, the brain physiological parameter may be a value of each physical sign of the target elderly at an initial anesthesia unconsciousness critical point and a sedation depth and shallowness critical point, for example, blood pressure, blood oxygen, and the like.

In this embodiment, the historical values of the brain physiological parameters refer to various physical parameters corresponding to the unconsciousness critical point and the sedation depth and the shallow critical point of the old who has performed the operation before at the initial anesthesia.

In this embodiment, the fluctuation range value of each brain physiological parameter refers to a value range of each brain physiological parameter under a normal condition when the elderly are at an initial anesthesia unconsciousness critical point and a sedation depth and shallow critical point.

In this embodiment, the preset brain physiological parameter calibration model is set in advance, and is used for calibrating the value of the abnormal brain physiological parameter.

In this embodiment, the recording report task refers to determining the number of items to be recorded, the amount of recording data corresponding to each recording item, and the like.

In this embodiment, the preset report template library is set in advance, and a plurality of report templates are stored in the preset report template library and used for recording surgical data to be recorded in the surgical procedure.

In this embodiment, the target report template refers to a report template suitable for recording an initial anesthesia unconsciousness critical point, a sedation depth critical point, a dosage of an anesthetic corresponding to the critical point, and the brain physiological parameter, and is one of a preset report template library.

In this embodiment, the visualization configuration refers to setting the length, width, height, and the like of each unit in the target report template and the position of each record item in the target report template.

In this embodiment, the target location refers to the location of each anesthesia parameter to be filled in the target report template.

In this embodiment, the preset storage area is set in advance, and is used for storing the finally generated report, and may be a hard disk or the like.

The beneficial effects of the above technical scheme are: by determining various physiological parameters of the target old people at the critical point and generating corresponding anesthesia parameter record reports for storage of the brain physiological parameters, the critical point and the anesthesia dosage corresponding to the critical point, various parameters of the anesthesia critical point are integrated and recorded, medical workers can conveniently and timely determine the corresponding anesthesia dosage according to different anesthesia depths required by the old people in the later operation process, the anesthesia effect is improved, and the anesthesia efficiency is also improved.

Example 8:

on the basis of the above embodiment 7, this embodiment provides an intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals, and an anesthesia parameter recording report is obtained, including:

In this embodiment, the target classification result refers to a result of finally classifying the anesthesia parameter record report by operation type, such as a cardiac operation type, a wound suture type, and the like.

In this embodiment, the target data packet refers to a data packet obtained by packing anesthesia parameter record report sheets corresponding to various types of surgeries.

In this embodiment, the reference library of the anesthesia parameter record report is composed of anesthesia parameter record reports corresponding to various operation types, and is intended to provide reference convenience for anesthesia in a later operation.

In this embodiment, the index keyword indicates that the medical staff can quickly find the anesthesia parameter record report corresponding to the corresponding operation type according to the index keyword, thereby improving the working efficiency.

The beneficial effects of the above technical scheme are: through the record of saving the anesthesia parameter record report list that corresponds each type operation, the later stage medical personnel of being convenient for when anaesthetizing the old man, in time according to the required anesthesia degree of depth of anaesthetizing the old man to the operation of reference data, improved the anesthesia level, strengthened anesthesia efficiency, reduce the injury of narcotic to the patient.

Example 9:

on the basis of the above embodiment 8, this embodiment provides an intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals, and sends the index keyword to a medical staff terminal, including:

In this embodiment, the current operation data of the elderly is different from the operation data of the elderly who have performed an operation at the current time, the target elderly is to determine the unconsciousness critical point and the critical point of deep and shallow sedation of the initial anesthetist, the critical points are obtained by analyzing a plurality of elderly through different operations, the target elderly are all fingers, and the current elderly is a special purpose.

In this embodiment, the target operation type refers to an operation type corresponding to a current geriatric operation pair.

In this embodiment, the target keyword refers to an index keyword corresponding to a current geriatric surgery type, and is one of a plurality of index keywords.

In this embodiment, the target data packet refers to a data packet corresponding to an anesthesia parameter record report corresponding to a current operation type of the elderly, and the anesthesia parameter record report included in the data packet is consistent with the current operation type of the elderly.

In this embodiment, the target anesthesia depth refers to a degree of need for anesthesia of the elderly determined according to the type of surgery of the elderly.

The beneficial effects of the above technical scheme are: by determining the operation type of the old and the needed anesthesia success, the dosage of the anesthetic needed by the old can be rapidly and accurately determined through the anesthesia parameter recording report sheet, the anesthesia efficiency and the anesthesia level are improved, and meanwhile, the injury caused by anesthesia is also reduced.

Example 10:

this embodiment provides an intelligent system of old man's anesthesia target accuse based on brain electrical signal monitoring, as shown in fig. 3, include:

and the integrated recording module is used for determining the physiological parameters of the target old people at the anesthesia depth and superficial critical points and performing integrated recording on the initial anesthesia unconsciousness critical point, the sedation depth and superficial critical point and the dosage of the anesthetic corresponding to the critical point and the brain physiological parameters.

The beneficial effects of the above technical scheme are: through confirming the consciousness activity intensity of old man under different dosage narcotics, be favorable to accurately finding old man's initial anesthesia unconsciousness critical point and the deep and shallow critical point of sedation to be convenient for according to the operation needs, the adjustment anesthetic dose makes the patient be in good anesthesia state, has improved anesthesia effect, has strengthened the anesthesia level, has stopped the intraoperative knowledge, reduces the injury of narcotic to the patient.

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

1. An intelligent method for monitoring anesthesia target control of the old based on electroencephalogram signals is characterized by comprising the following steps:

step 2: determining consciousness indexes and injury indexes of the target old people under different dosages of anesthetics based on electroencephalogram signals, and determining initial anesthesia unconsciousness critical points and sedation deep and shallow critical points of the target old people based on the consciousness indexes and the injury indexes;

and step 3: and determining physiological parameters of the target old people at the initial anesthesia unconsciousness critical point and the sedation depth and superficial critical point, and performing integrated recording on the initial anesthesia unconsciousness critical point, the sedation depth and superficial critical point and the dosage of the anesthetic corresponding to the critical point and the physiological parameters.

2. The electroencephalogram signal monitoring elderly anesthesia target control intelligent method based on claim 1, wherein in step 1, acquiring the doses of anesthetics injected by a target elderly at different target time points comprises:

3. The electroencephalogram signal monitoring elderly anesthesia target control intelligent method based on claim 2, wherein the step of calculating the doses of the anesthetics injected by the target elderly at different target time points based on the working time and the injection speed of a preset anesthetic injection pump comprises the following steps:

4. The intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals according to claim 1, wherein in step 1, electroencephalogram signals of the target elderly at different target time points are collected in real time, and the method comprises the following steps:

5. The intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals, according to claim 1, is characterized in that in step 1, the dosage of anesthetic injected by a target elderly at different target time points is obtained, and electroencephalogram signals of the target elderly at different target time points are collected in real time, and the method comprises the following steps:

6. The electroencephalogram signal-based monitoring elderly anesthesia target control intelligent method according to claim 1, wherein in step 2, consciousness indexes and injury indexes of the target elderly at different dosages of anesthetics are determined based on electroencephalogram signals, and initial anesthesia unconsciousness critical points and deep and shallow sedation critical points of the target elderly are determined based on the consciousness indexes and the injury indexes, and the method comprises the following steps:

if not, grouping the consciousness indexes and the injury indexes at different time points to obtain N consciousness index groups and injury index groups to be displayed, determining drawing points of the consciousness indexes and the injury indexes at different time points in the line graph to be displayed based on the time point sequence corresponding to the consciousness indexes and the injury indexes, and respectively obtaining N consciousness indexes and injury index line graphs based on the drawing points;

otherwise, displaying the consciousness indexes and the injury indexes at different time points at one time to obtain corresponding consciousness indexes and injury index line graphs;

7. The electroencephalogram signal-based monitoring elderly anesthesia target control intelligent method according to claim 1, wherein in step 3, the physiological parameters of the target elderly at the initial anesthesia unconsciousness critical point and the sedation deep and shallow critical point are determined, and the doses of the anesthetics corresponding to the unconsciousness critical point and the sedation deep and shallow critical point of the initial anesthesia patient and the critical point are integrated with the brain physiological parameters, and the method comprises the following steps:

if not, judging that the acquired brain physiological parameters of the target old people are abnormal, and inputting the brain physiological parameters of the target old people into a preset brain physiological parameter calibration model for calibration, wherein the preset brain physiological parameter calibration model is obtained by training historical brain physiological parameter values, the preset brain physiological parameter calibration model comprises a plurality of modules for verifying the body brain physiological parameters, and the modules are independent from each other;

8. The intelligent method for monitoring the anesthesia target control of the elderly based on electroencephalogram signals according to claim 7, wherein obtaining an anesthesia parameter recording report sheet comprises:

9. The intelligent method for monitoring anesthesia target control of the elderly based on electroencephalogram signals according to claim 8, wherein the index keyword is sent to a medical staff terminal, and the method comprises the following steps:

10. The utility model provides an intelligent system of old man's anesthesia target control based on brain electrical signal monitoring which characterized in that includes:

the analysis module is used for determining consciousness indexes and injuries of the target old people under different anesthetic doses based on the electroencephalogram signals, and determining initial anesthesia unconsciousness critical points and critical points of deep and shallow sedation of the target old people based on the consciousness indexes and the injury indexes;