CN115316957A - Perioperative anesthesia depth monitoring system based on multi-parameter indexes - Google Patents
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Abstract
The invention discloses a perioperative anesthesia depth monitoring system based on multi-parameter indexes, which comprises a multi-parameter acquisition module, a processing module, a comparison module and a storage module, wherein the multi-parameter acquisition module acquires multiple items of characteristic data of a patient, the characteristic data is transmitted to the processing module for processing and then transmitted to the comparison module, the comparison module compares the non-anesthesia characteristic data with the anesthesia characteristic data, calculates the current anesthesia depth, and finally stores the characteristic data processed by the processing module through the storage module. The monitoring system disclosed by the invention has the advantages that the monitoring system is used for carrying out multi-parameter acquisition on the patient, and calculating the anesthesia depth after comparing the preoperative non-anesthesia characteristic data and the anesthesia characteristic data of the patient in the anesthesia process, so that the monitoring precision of the system on the anesthesia depth is high, and the problem that the patient feels pain during the perioperative period due to the fact that the patient is injured by too large anesthesia depth or the patient feels pain due to too small anesthesia depth is solved.
Description
Technical Field
The invention relates to the technical field of monitoring systems, in particular to a perioperative anesthesia depth monitoring system based on multi-parameter indexes.
Background
In current clinical practice, most of clinical anesthesia states are the results of comprehensive effects of various medicines, including consciousness loss, forgetting, pain easing, muscle relaxation, body movement inhibition, and cardiovascular and endocrine system reaction to surgical stimulation, so that effective anesthesia monitoring is of great importance, anesthesia depth assessment is the most subjective and most controversial topic in the field of anesthesia, sedation can enhance analgesia, analgesia can also enhance sedation, both can enhance the effect of muscle relaxation, otherwise, muscle relaxation can also affect the effects of sedation and analgesia to a certain extent, comprehensive analysis and judgment can be performed clinically according to the performances of blood pressure, heart rate, respiration amplitude and rhythm, muscle relaxation degree and the like in a patient operation, and ideal anesthesia depth is important for ensuring that the patient has no pain sense and unconscious activity in the operation, hemodynamics is stable, and recovery after operation is perfect and has no intraoperative knowledge, but the judgment of anesthesia depth is influenced by too many factors, so that the anesthesia depth judgment by various means is of great importance in clinical work.
The Chinese patent with application number of 202110559528.2 discloses an anesthesia depth monitoring system, which comprises a microprocessor, an electroencephalogram signal acquisition module, an electroencephalogram signal processing module, a data storage module, a power management module, an external power supply module, a built-in battery module, a network interface, a USB interface, an LCD display module and a touch screen module, and relates to the technical field of software identification algorithm, signal processing and filtering. The anesthesia depth monitoring system can realize the high-quality acquisition of electroencephalogram signals, performs anti-interference processing in the signal transmission process, performs filtering through a filter based on characteristics of the electroencephalogram signals, reduces the influence of external interference on the system, and meets the high-quality requirement of the electroencephalogram signals, thereby providing stable and high-quality electroencephalogram signal data and higher acquisition precision for a micro-processing system, reducing the deviation caused by system calculation, and can realize the addition of a common-mode inductor in a differential acquisition circuit by utilizing the characteristic of common-mode inductor to suppress common-mode noise.
Disclosure of Invention
The invention aims to provide a perioperative anesthesia depth monitoring system based on multi-parameter indexes so as to solve the defects in the background technology.
In order to achieve the above purpose, the invention provides the following technical scheme: the perioperative anesthesia depth monitoring system based on the multi-parameter indexes comprises a multi-parameter acquisition module, a processing module, a comparison module and a storage module;
the multi-parameter acquisition module acquires a plurality of characteristic data of a patient, the characteristic data are transmitted to the comparison module after being transmitted to the processing module for processing, the comparison module compares the non-anesthesia characteristic data with the anesthesia characteristic data, calculates the current anesthesia depth, and finally stores the characteristic data processed by the processing module through the storage module.
Preferably, the plurality of feature data include electroencephalogram feature data, cerebral blood oxygen feature data, and pupil feature data.
Preferably, the multi-parameter acquisition module acquires non-anesthesia characteristic data of the patient in a waking state as first characteristic data, and the multi-parameter acquisition module acquires anesthesia characteristic data of the patient in an anesthesia state as second characteristic data.
Preferably, the multi-parameter acquisition module comprises an electroencephalogram acquisition unit, a brain blood oxygen acquisition unit and a pupil image acquisition unit, the electroencephalogram acquisition unit is used for acquiring electroencephalogram signals of the patient, the brain blood oxygen acquisition unit is used for acquiring brain blood oxygen data of the patient, and the pupil image acquisition unit is used for acquiring pupil image data of the patient.
Preferably, the difference signal is input by the electroencephalogram acquisition unit, is subjected to first-stage amplification, second-stage amplification, 200Hz low-pass filtering and finally three-stage amplification and 50Hz power frequency notch filtering, and the calculation formula is as follows:
in the formula, W G Representing the filter cut-off frequency, C 1 Representing a filter capacitance of 1, C 2 Representing a filter capacitance of 2, R 1 Representing a filter resistance of 1,R 2 Representing the filter resistance 2.
Preferably, the brain blood oxygen collecting unit is used for collecting the forehead brain blood oxygen signals of a patient receiving general anesthesia in a waking state and an anesthesia state.
Preferably, the brain blood oxygen collecting unit comprises the following collecting steps:
collecting cerebral blood oxygen data of a patient;
filtering the cerebral blood oxygen signal;
the ROC curve of each signal is drawn by using the sensitivity and the specificity to obtain the AUC value of each signal, and a target signal is determined;
and determining a sample entropy monitoring threshold value by comparing the you' n indexes.
Preferably, the pupil image acquisition unit includes an ultrasonic monitoring device, and the ultrasonic monitoring device includes a head-mounted part and two miniature ultrasonic probes, and two miniature ultrasonic probes are symmetrically arranged in head-mounted part both sides, and a miniature ultrasonic probe's position corresponds an eye, and miniature ultrasonic probe laminating face obtains pupil ultrasonic image through the ultrasonic wave.
Preferably, the monitoring of the pupil image acquisition unit includes the following steps:
wearing an ultrasound monitoring device for a patient;
applying a shading paste on the eyelid of the patient, wherein the shading paste positions an ultrasonic monitoring device;
the miniature ultrasonic probe transmits and receives ultrasonic waves, monitors the left eye and the right eye and acquires pupil ultrasonic images;
the ultrasonic imaging system comprises an ultrasonic host, a miniature ultrasonic probe, a display, a pupil diameter real-time numerical value display, a binocular pupil diameter average value display, a change trend chart data information display and a pupil diameter real-time numerical value display.
Preferably, the processing module comprises an electroencephalogram signal processing unit, a cerebral blood oxygen data processing unit and a pupil image data processing unit, the electroencephalogram signal processing unit is used for processing electroencephalograms acquired by the electroencephalogram acquisition unit, the cerebral blood oxygen data processing unit is used for processing cerebral blood oxygen data acquired by the cerebral blood oxygen acquisition unit, and the pupil image data processing unit is used for processing pupil image data acquired by the pupil image acquisition unit.
In the technical scheme, the invention provides the following technical effects and advantages:
1. according to the invention, a plurality of characteristic data of a patient are acquired through a multi-parameter acquisition module, the characteristic data are processed through a processing module, and then the non-anesthesia characteristic data and the anesthesia characteristic data are compared through a comparison module, so that the current anesthesia depth is calculated.
2. According to the invention, through high-quality acquisition of the electroencephalogram signals, anti-interference processing is carried out in the signal transmission process, and filtering is carried out through a filter based on characteristics of the electroencephalogram signals, so that the influence of external interference on the system is reduced, the high-quality requirement of the electroencephalogram signals is met, stable and high-quality electroencephalogram signal data and higher acquisition precision are provided for a micro-processing system, the deviation caused by system calculation is reduced, and the high-frequency high-energy conducted disturbance can be well inhibited by adding the common-mode inductor into the differential acquisition circuit by utilizing the characteristic that the common-mode inductor inhibits common-mode noise.
Drawings
In order to more clearly illustrate the embodiments of the present application or technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
FIG. 1 is a block diagram of the system of the present invention.
FIG. 2 is a block diagram of the monitoring system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1, the perioperative anesthesia depth monitoring system based on multi-parameter index of the present embodiment includes a multi-parameter acquisition module, a processing module, a comparison module and a storage module;
wherein,
a multi-parameter acquisition module: the system is used for collecting electroencephalogram characteristic data, cerebral blood oxygen characteristic data and pupil characteristic data of a patient;
the multi-parameter acquisition module acquires non-anesthesia characteristic data of a patient in a waking state and then acquires anesthesia characteristic data of the patient in an anesthesia state.
A processing module: the method is used for processing the electroencephalogram characteristic data, the cerebral blood oxygen characteristic data and the pupil characteristic data of the patient.
A comparison module: the device is used for comparing the non-anesthesia characteristic data with the anesthesia characteristic data so as to calculate the current anesthesia depth;
a storage module: the system is used for storing the characteristic data processed by the processing module, the monitoring system collects multiple parameters of the patient, and in the anesthesia process, the anesthesia depth is calculated after comparing the preoperative non-anesthesia characteristic data and the anesthesia characteristic data of the patient, the monitoring precision of the system on the anesthesia depth is high, and the problem that the patient feels pain in the perioperative period due to the fact that the anesthesia depth is too large and the patient is injured or the anesthesia depth is too small is avoided.
Example 2
The multi-parameter acquisition module comprises an electroencephalogram acquisition unit, a brain blood oxygen acquisition unit and a pupil image acquisition unit, the electroencephalogram acquisition unit is used for acquiring electroencephalogram signals of a patient, the brain blood oxygen acquisition unit is used for acquiring brain blood oxygen data of the patient, and the pupil image acquisition unit is used for acquiring pupil image data of the patient.
Wherein,
(1) The electroencephalogram acquisition unit inputs a differential signal, after primary amplification processing, secondary amplification and 200Hz low-pass filtering are carried out, and then tertiary amplification and 50Hz power frequency notch filtering are carried out to filter out the high-frequency part of the electroencephalogram signal; after three-stage amplification, the amplification factor is 10000 times, and the calculation is carried out according to the following formula:
in the formula, W G Representing the cut-off frequency of the filter, C 1 Representing a filter capacitance of 1, C 2 Representing a filter capacitance of 2, R 1 Representing a filter resistance of 1,R 2 Representing the filter resistance 2.
In the embodiment of the invention, brain wave signals are collected and transmitted by a lead system, enter a preamplifier for amplification processing, then are sent to a low-pass filter for filtering, then are sent to a secondary amplifier for secondary amplification processing, and after analog signals are secondarily amplified, the intervals among signals with different frequencies are expanded.
Wherein,
the frequency of the delta wave signal is 0.5-4Hz;
the frequency of the theta wave signal is 4-8Hz;
the frequency of the alpha wave signal is 8-13Hz;
the frequency of the beta wave signal is 13-30Hz;
the frequency of the gamma wave signal is more than 30Hz;
the signal intensity is weak, the signal is not enough for analog-to-digital conversion, the signal needs to be sent into a three-level amplifier for amplification, the signal is sent into a microcontroller for analog-to-digital conversion, fast Fourier transform and signal processing system operation are carried out in the microcontroller, and a sedation/consciousness index (IoC 1), an analgesia/pain index (IoC 2), an outbreak suppression ratio (BS), an electromyographic index (EMG), signal Quality (SQI) and impedance value parameters of electrodes are finally obtained, and a fast Fourier theory operating system analyzes four different frequency band energy parameters of an original electroencephalogram signal spectrum:
energy ratio of delta wave E θ ＝ln(E 0.5-4Hz /E 0-47Hz )；
Energy ratio of theta wave E θ ＝ln(E 4-8Hz /E 0-47Hz )；
Energy ratio of alpha wave E a ＝ln(E 8-13Hz /E 0-47Hz )；
Energy ratio of beta wave E a ＝ln(E 13-30Hz /E 0-47Hz )；
The Fuzzy model is accessed into four same-frequency-band energy parameters, the analgesia/pain index (IoC 2) is preliminarily calculated, the explosion suppression ratio (BS) of an output system is corrected, and the output Fuzzy of the Fuzzy model is corrected output The formula for the calculation of the analgesia/pain index (IoC 2) is as follows:
analgesia/pain index (IoC 2) = max (0, 1-BS/30). Times Fuzzy output +min(1，BS/30)×(41-0.41BS)
The cut-off frequency is set to be low, on one hand, high-frequency clutter is filtered, on the other hand, noise is suppressed, then the noise is sent to a single chip microcomputer AD for digital-to-analog conversion, the AD range is 0-3.3V, and after the time sampling and the filtering processing of the single chip microcomputer, the noise is input to an algorithm model for calculation.
The electroencephalogram signals are collected in high quality, anti-interference processing is carried out in the signal transmission process, filtering is carried out through a filter based on characteristics of the electroencephalogram signals, the influence of external interference on a system is reduced, the high-quality requirement of the electroencephalogram signals is met, stable and high-quality electroencephalogram signal data and higher collection precision are provided for a micro-processing system, the deviation caused by system calculation is reduced, and high-frequency and high-energy conduction disturbance can be well restrained by adding a common-mode inductor into a differential collection circuit by utilizing the characteristic that the common-mode inductor restrains common-mode noise.
(2) The brain blood oxygen acquisition unit is used for acquiring the left and right forehead brain blood oxygen signals of a patient receiving general anesthesia in an awake state and an anesthesia state.
The brain blood oxygen acquisition unit comprises the following acquisition steps:
the NIRS multi-parameter recorder is adopted, the acquisition equipment of the near infrared signals consists of the recorder and two probes, each probe comprises a light source and two receivers at a near end and a far end, the two receivers are respectively 2cm and 3cm away from the light source and respectively attached to the left side and the right side of the forehead of a patient, the distance between the forehead and the upper part of the eyebrow center is 1cm, the sampling frequency is 10Hz, the near infrared light sources with double wavelengths of 735nm and 850nm are selected for respectively acquiring Hb and HbO 2 The concentration variation signal of (2).
The obtained cerebral blood oxygen signal is filtered, on one hand, the filtering is hopeful to remove high-frequency noise in data, on the other hand, the cerebral blood oxygen signal belongs to a low-frequency signal, and a frequency band reflecting cerebral nerve information in the cerebral blood oxygen signal is selected, so the filtering frequency band selected in the embodiment is a frequency band of 0.01-0.4 Hz.
And (3) plotting an ROC curve of each signal by using the sensitivity and the specificity, then obtaining an AUC value of each signal, and determining a target signal.
The sample entropy monitoring threshold is determined by comparing the you ' n indexes, the optimal threshold is determined by comparing the sizes of the you ' n indexes (sensitivity + specificity-1), and the larger the you ' n index is, the more accurate the judgment of the positive data and the negative data is, namely, the better the distinguishing effect under the threshold is.
(3) Pupil image acquisition unit includes ultrasonic monitoring device, and ultrasonic monitoring device includes wear-type installed part and two miniature ultrasonic probe, and two miniature ultrasonic probe symmetrical arrangement are in wear-type installed part both sides, and a miniature ultrasonic probe's position corresponds an eye, and miniature ultrasonic probe laminating face obtains pupil ultrasonic image through the ultrasonic wave.
The monitoring of the pupil image acquisition unit comprises the following steps:
wearing an ultrasonic monitoring device on a patient, wherein the positions of two miniature ultrasonic probes respectively correspond to the left eye and the right eye, and adjusting the miniature ultrasonic probes to be attached to the face;
applying a shading paste on the eyelid of the patient, wherein the shading paste positions an ultrasonic monitoring device;
the miniature ultrasonic probe transmits and receives ultrasonic waves, monitors the left eye and the right eye and acquires pupil ultrasonic images;
the pupil ultrasonic image acquired by the miniature ultrasonic probe is transmitted to the ultrasonic host, the ultrasonic host processes the pupil ultrasonic image and displays data information such as the pupil image, a pupil diameter real-time numerical value, a binocular pupil diameter average value, a variation trend chart and the like through the display.
The transmission mode of the pupil ultrasonic image comprises Bluetooth, wireless and wired modes, and data transmission can be carried out in various modes.
Example 3
The processing module comprises an electroencephalogram signal processing unit, a cerebral blood oxygen data processing unit and a pupil image data processing unit, the electroencephalogram signal processing unit is used for processing electroencephalograms acquired by the electroencephalogram acquisition unit, the cerebral blood oxygen data processing unit is used for processing cerebral blood oxygen data acquired by the cerebral blood oxygen acquisition unit, and the pupil image data processing unit is used for processing pupil image data acquired by the pupil image acquisition unit.
Wherein,
(1) The electroencephalogram signal processing unit: the electroencephalogram acquisition unit inputs acquired electroencephalogram signals into the electroencephalogram signal processing unit through a special electroencephalogram sensor, the electroencephalogram signals are amplified through a preamplifier, then sent into a low-pass filter for filtering, then sent into a secondary amplifier for second amplification, after analog signals are amplified for the second time, intervals among signals with different frequencies are enlarged, due to the fact that signal intensity is weak, analog-to-digital conversion is not enough, the signals need to be sent into a third-level amplifier for amplification, finally sent into a microcontroller for analog-to-digital conversion, and fast Fourier transform and signal processing system operation are conducted inside the microcontroller, and finally a sedation/consciousness index (IoC 1), an analgesia/pain index (IoC 2), an outbreak suppression ratio (BS), an electromyogram index (EMG), signal Quality (SQI) and impedance value parameters of electrodes are obtained.
(2) A brain blood oxygen data processing unit: the system is used for calculating sample entropy of the brain blood oxygen data acquired by the brain blood oxygen acquisition unit under two states of waking and anaesthesia, determining the length of the brain blood oxygen signal, and then forming a multi-dimensional vector; according to the similarity tolerance, determining the average similarity function of the signal in the dimension and the higher dimension, and then obtaining the sample entropy of the signal.
(3) Pupil image data processing means: the ultrasonic pupil imaging system comprises a display and an ultrasonic host, wherein pupil ultrasonic images acquired by a miniature ultrasonic probe are transmitted to the ultrasonic host, the ultrasonic host processes the pupil ultrasonic images, and the data information such as the pupil images, real-time pupil diameter numerical values, pupil diameter average values of two eyes, pupil diameter variation trend graphs and the like are displayed through the display.
Example 4
Referring to fig. 2, the software architecture of the system includes a UI layer, a service layer, and a BSP layer;
wherein,
the main tasks of the service layer are communication protocol analysis, data forwarding, storage, alarm system management, system timer management and the like, and in the layer, the data flow is processed by a data manager serving as a control center to analyze and distribute the data flow, and is pushed to a UI layer for refreshing and the like;
the UI layer is mainly related to a user interface, and is used for refreshing a trend graph and a waveform of a channel display area, displaying parameter values of a parameter area, a module function dialog box and a parameter setting menu.
The BSP layer is used to monitor network communications of the device.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. The procedures or functions according to the embodiments of the present application are wholly or partially generated when the computer instructions or the computer program are loaded or executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, data center, etc., that contains one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
It should be understood that the term "and/or" herein is only one kind of association relationship describing the association object, and means that there may be three kinds of relationships, for example, a and/or B, and may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. In addition, the "/" in this document generally indicates that the former and latter associated objects are in an "or" relationship, but may also indicate an "and/or" relationship, and may be understood with particular reference to the former and latter contexts.
In the present application, "at least one" means one or more, "a plurality" means two or more. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of the singular or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims. .
Claims (10)
1. Perioperative anesthesia depth monitoring system based on multi-parameter index, its characterized in that: the device comprises a multi-parameter acquisition module, a processing module, a comparison module and a storage module;
the multi-parameter acquisition module acquires a plurality of characteristic data of a patient, the characteristic data are transmitted to the comparison module after being transmitted to the processing module for processing, the comparison module compares the non-anesthesia characteristic data with the anesthesia characteristic data, calculates the current anesthesia depth, and finally stores the characteristic data processed by the processing module through the storage module.
2. The perioperative anesthesia depth monitoring system based on multi-parameter index as claimed in claim 1, characterized in that: the characteristic data comprises electroencephalogram characteristic data, cerebral blood oxygen characteristic data and pupil characteristic data.
3. The perioperative anesthesia depth monitoring system based on multi-parameter index as claimed in claim 2, characterized in that: the multi-parameter acquisition module acquires non-anesthesia characteristic data of a patient in a waking state as first characteristic data, and acquires anesthesia characteristic data of the patient in an anesthesia state as second characteristic data.
4. The perioperative anesthesia depth monitoring system based on multi-parameter index as claimed in claim 1, characterized in that: the multi-parameter acquisition module comprises an electroencephalogram acquisition unit, a cerebral blood oxygen acquisition unit and a pupil image acquisition unit, the electroencephalogram acquisition unit is used for acquiring electroencephalogram signals of a patient, the cerebral blood oxygen acquisition unit is used for acquiring cerebral blood oxygen data of the patient, and the pupil image acquisition unit is used for acquiring pupil image data of the patient.
5. The perioperative anesthesia depth monitoring system based on multi-parameter index as claimed in claim 4, characterized in that: the electroencephalogram acquisition unit inputs a differential signal, the differential signal is subjected to primary amplification processing, secondary amplification and 200Hz low-pass filtering, and finally three-stage amplification and 50Hz power frequency notch filtering, and the calculation formula is as follows:
in the formula, W G Representing the cut-off frequency of the filter, C 1 Representing a filter capacitance of 1, C 2 Representing a filter capacitance of 2, R 1 Representing a filter resistance of 1,R 2 Representing the filter resistance 2.
6. The perioperative anesthesia depth monitoring system based on multi-parameter index of claim 5, characterized in that: the brain blood oxygen collecting unit is used for collecting the forehead brain blood oxygen signals of a patient receiving general anesthesia in a waking state and an anesthesia state.
7. The perioperative anesthesia depth monitoring system based on multi-parameter index of claim 6, characterized in that: the brain blood oxygen collecting unit comprises the following collecting steps:
collecting cerebral blood oxygen data of a patient;
filtering the cerebral blood oxygen signal;
drawing an ROC curve of each signal by using the sensitivity and the specificity to obtain an AUC value of each signal and determine a target signal;
and determining a sample entropy monitoring threshold value by comparing the ewing indexes.
8. The perioperative anesthesia depth monitoring system based on multi-parameter index of claim 7, wherein: pupil image acquisition unit includes ultrasonic monitoring device, and ultrasonic monitoring device includes wear-type installed part and two miniature ultrasonic probe, and two miniature ultrasonic probe symmetrical arrangement are in wear-type installed part both sides, and a miniature ultrasonic probe's position corresponds an eye, and miniature ultrasonic probe laminating face obtains pupil ultrasound image through the ultrasonic wave.
9. The perioperative anesthesia depth monitoring system based on multi-parameter index of claim 8, characterized in that: the monitoring of the pupil image acquisition unit comprises the following steps:
wearing an ultrasound monitoring device for a patient;
applying a shading paste on the eyelid of the patient, wherein the shading paste positions an ultrasonic monitoring device;
the miniature ultrasonic probe transmits and receives ultrasonic waves, monitors the left eye and the right eye and acquires pupil ultrasonic images;
the ultrasonic imaging system comprises an ultrasonic host, a miniature ultrasonic probe, a display, a pupil diameter real-time numerical value display, a binocular pupil diameter average value display, a change trend chart data information display and a pupil diameter real-time numerical value display.
10. The perioperative anesthesia depth monitoring system based on multi-parameter indices of any of claims 1-9, wherein: the processing module comprises an electroencephalogram signal processing unit, a cerebral blood oxygen data processing unit and a pupil image data processing unit, the electroencephalogram signal processing unit is used for processing electroencephalograms acquired by the electroencephalogram acquisition unit, the cerebral blood oxygen data processing unit is used for processing cerebral blood oxygen data acquired by the cerebral blood oxygen acquisition unit, and the pupil image data processing unit is used for processing pupil image data acquired by the pupil image acquisition unit.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115813352A (en) * | 2023-02-23 | 2023-03-21 | 昌乐县人民医院 | Pupil monitoring and evaluating system for general anesthesia patient |
| CN117814760A (en) * | 2024-03-04 | 2024-04-05 | 江西杰联医疗设备有限公司 | Anesthesia depth detection device based on multiple indexes and electronic equipment |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115813352A (en) * | 2023-02-23 | 2023-03-21 | 昌乐县人民医院 | Pupil monitoring and evaluating system for general anesthesia patient |
| CN117814760A (en) * | 2024-03-04 | 2024-04-05 | 江西杰联医疗设备有限公司 | Anesthesia depth detection device based on multiple indexes and electronic equipment |
| CN117814760B (en) * | 2024-03-04 | 2024-05-17 | 江西杰联医疗设备有限公司 | Anesthesia depth detection device based on multiple indexes and electronic equipment |
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