Methods for displaying monitoring information, alarm methods for abnormal EEG readings, and monitoring systems.

Abstract

A monitoring system, an alarm method for abnormal electroencephalogram (EEG), and a method for displaying monitoring information are disclosed. The monitoring system includes a display (40) and a processor (50). The processor (50) is used to acquire first monitoring data of the patient's EEG parameters during a first monitoring period, and second monitoring data of the patient during a second monitoring period, including at least one other monitoring parameter besides the EEG parameters. The first and second monitoring periods at least partially overlap. Based on the first monitoring data, an amplitude-integrated EEG (1) for the first monitoring period is generated. Based on the second monitoring data, a trend chart of at least one other monitoring parameter is generated. The display (40) is controlled to simultaneously display the amplitude-integrated EEG (1) and the trend chart. In this monitoring system, the user can more accurately and quickly compare the amplitude-integrated EEG (1) with the trend charts of other monitoring parameters, thereby improving the accuracy of the assessment of the patient's physical condition.

Description

Technical Field

[0001] This invention relates to the field of medical devices, specifically to a method for displaying monitoring information, an alarm method for abnormal electroencephalogram (EEG) data, and a monitoring system. Background Technology

[0002] Currently, the monitoring process for EEG using a monitoring system (e.g., a monitor) involves nurses monitoring the EEG display in real-time (or continuously) to assess the patient's condition. Amplitude integrated EEG (AEEG) is obtained by compressing the EEG, which can quickly present historical (e.g., daily) changes in EEG signals. When abnormalities are found on the AEEG (e.g., gaps), doctors need to further review the original EEG for final confirmation. The problem with this process is that relying solely on AEEG to assess a patient's condition has a high false-positive rate and insufficient accuracy. False positives can be caused by distortion during EEG compression or interference during signal acquisition. Currently, there is a lack of reliable and comprehensive monitoring systems / display devices (bedside monitors and central stations), display methods, or display interfaces to assist healthcare professionals in diagnosing patient conditions based on EEG signals. Invention Overview

[0004] Technical issues

[0005] Solution to the problem

[0006] Technical solutions

[0007] According to a first aspect, one embodiment provides a monitoring system, including:

[0008] monitor;

[0009] Processor, used for:

[0010] Acquire first monitoring data of the patient's electroencephalogram (EEG) parameters during a first monitoring period, and acquire second monitoring data of the patient's at least one other monitoring parameter besides the EEG parameters during a second monitoring period, wherein the first monitoring period and the second monitoring period at least partially overlap.

[0011] An amplitude integrated EEG for the first monitoring period is generated based on the first monitoring data, and a trend chart of the at least one other monitoring parameter is generated based on the second monitoring data.

[0012] The display is controlled to simultaneously show the amplitude-integrated EEG and the trend graph.

[0013] According to a second aspect, one embodiment provides a monitoring system, including:

[0014] monitor;

[0015] Processor, used for:

[0016] Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period;

[0017] An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data;

[0018] Control the display to show the amplitude-integrated electroencephalogram;

[0019] Based on the user's selection instruction for the reference time point or reference time period input of the amplitude integrated EEG, a third monitoring period is determined, which includes the reference time point or reference time period selected by the user, and the third monitoring period is included in the first monitoring period;

[0020] Based on the first monitoring data corresponding to the third monitoring period, generate the EEG parameter waveform for the third monitoring period;

[0021] The display is controlled to show the EEG parameter waveforms while simultaneously displaying the amplitude-integrated EEG.

[0022] According to a third aspect, one embodiment provides a monitoring system, including:

[0023] monitor;

[0024] Processor, used for:

[0025] Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters;

[0026] An amplitude-integrated electroencephalogram (EEG) was obtained based on the first monitoring data;

[0027] Obtain the abnormal moments of the amplitude-integrated EEG;

[0028] Obtain second monitoring data for at least one monitoring parameter of the patient other than EEG parameters;

[0029] Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated;

[0030] Obtain the change characteristics on the trend graph at the abnormal moment;

[0031] Based on the changing characteristics on the trend graph, determine whether an abnormal EEG event has occurred;

[0032] If an abnormal EEG event occurs, the display is controlled to show alarm information associated with the abnormal EEG event.

[0033] According to the fourth aspect, one embodiment provides a monitoring system, including:

[0034] monitor;

[0035] Processor, used for:

[0036] Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters;

[0037] An amplitude-integrated electroencephalogram (EEG) is generated based on the first monitoring data;

[0038] Acquire physiological data of at least one other physiological parameter of the patient in addition to monitoring parameters, wherein the monitoring parameters include the electroencephalogram (EEG) parameters;

[0039] Based on the physiological data, generate a trend graph for at least one other physiological parameter;

[0040] The display is controlled to simultaneously show the amplitude-integrated EEG and the trend graph.

[0041] According to a fifth aspect, one embodiment provides a monitoring system, including:

[0042] monitor;

[0043] Processor, used for:

[0044] Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters;

[0045] Real-time EEG waveforms are obtained based on the first monitoring data;

[0046] Obtain second monitoring data for at least one monitoring parameter of the patient other than EEG parameters;

[0047] Based on the second monitoring data, generate a real-time waveform diagram of at least one other monitoring parameter;

[0048] The display is controlled to simultaneously show the real-time EEG parameter waveform and the real-time waveform diagram.

[0049] According to a sixth aspect, one embodiment provides a method for displaying monitoring information, including:

[0050] Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period;

[0051] Acquire second monitoring data of at least one monitoring parameter other than EEG parameters during the second monitoring period, wherein the first monitoring period and the second monitoring period at least partially overlap.

[0052] An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data;

[0053] Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated;

[0054] Simultaneously displaying the amplitude-integrated EEG and the trend graph.

[0055] According to the seventh aspect, one embodiment provides a method for displaying monitoring information, including:

[0056] Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period;

[0057] An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data;

[0058] Displaying the amplitude-integrated electroencephalogram;

[0059] Based on the user's selection instruction for the reference time point or reference time period input of the amplitude integrated EEG, a third monitoring period is determined, which includes the reference time point or reference time period selected by the user, and the third monitoring period is included in the first monitoring period;

[0060] Based on the first monitoring data corresponding to the third monitoring period, generate the EEG parameter waveform for the third monitoring period;

[0061] The waveforms of the EEG parameters are displayed simultaneously with the amplitude-integrated EEG.

[0062] According to the eighth aspect, one embodiment provides an alarm method for abnormal brainwaves, comprising:

[0063] Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters;

[0064] An amplitude-integrated electroencephalogram (EEG) was obtained based on the first monitoring data;

[0065] Obtain the abnormal moments of the amplitude-integrated EEG;

[0066] Obtain second monitoring data for at least one monitoring parameter of the patient other than EEG parameters;

[0067] Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated;

[0068] Obtain the change characteristics on the trend graph at the abnormal moment;

[0069] Based on the changing characteristics on the trend graph, determine whether an abnormal EEG event has occurred;

[0070] If an abnormal EEG event occurs, an alarm message associated with the abnormal EEG event will be displayed.

[0071] According to the ninth aspect, one embodiment provides a method for displaying monitoring information, including:

[0072] Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters;

[0073] An amplitude-integrated electroencephalogram (EEG) is generated based on the first monitoring data;

[0074] Acquire physiological data of at least one other physiological parameter of the patient in addition to monitoring parameters, wherein the monitoring parameters include the electroencephalogram (EEG) parameters;

[0075] Based on the physiological data, generate a trend graph for at least one other physiological parameter;

[0076] Simultaneously displaying the amplitude-integrated EEG and the trend graph.

[0077] According to a tenth aspect, one embodiment provides a method for displaying monitoring information, including:

[0078] Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters;

[0079] Real-time EEG waveforms are obtained based on the first monitoring data;

[0080] Obtain second monitoring data for at least one monitoring parameter of the patient other than EEG parameters;

[0081] Based on the second monitoring data, generate a real-time waveform diagram of at least one other monitoring parameter;

[0082] Simultaneously display the real-time EEG parameter waveform and the real-time waveform diagram.

[0083] According to the eleventh aspect, one embodiment provides a monitoring system, including:

[0084] Memory, used to store programs;

[0085] A processor for implementing the method described in any one of the sixth to tenth aspects by executing a program stored in the memory.

[0086] According to the twelfth aspect, one embodiment provides a computer-readable storage medium storing a program that can be executed by a processor to implement the method of any one of the sixth to tenth aspects.

[0087] Beneficial effects of the invention

[0088] Beneficial effects

[0089] According to the above embodiments, the amplitude integrated EEG of the first monitoring period and the trend chart of at least one other monitoring parameter of the second monitoring period are displayed simultaneously. The first and second monitoring periods overlap at least partially. Therefore, when the amplitude integrated EEG is abnormal at a certain moment or time period during the overlapping period, the changes of other monitoring parameters at the same moment can always be found in the trend chart of at least one other monitoring parameter. Thus, by combining the amplitude integrated EEG and other monitoring parameters, the false positive rate of the test results is reduced and the accuracy of the test is improved.

[0090] Brief description of the accompanying drawings Attached Figure Description

[0091] Figure 1 This is a schematic diagram of the composition structure of a monitoring system according to one embodiment;

[0092] Figure 2 This is a schematic diagram of the monitoring information display interface in the first embodiment;

[0093] Figure 3 This is a schematic diagram of the monitoring information display interface in the second embodiment;

[0094] Figure 4 This is a schematic diagram of the monitoring information display interface in the third embodiment;

[0095] Figure 5 This is a schematic diagram of the monitoring information display interface in the fourth embodiment;

[0096] Figure 6 This is a schematic diagram of the monitoring information display interface in the fifth embodiment;

[0097] Figure 7 This is a schematic diagram of the monitoring information display interface in the sixth embodiment;

[0098] Figure 8 A flowchart illustrating a method for displaying monitoring information according to one embodiment;

[0099] Figure 9 A flowchart illustrating a method for displaying monitoring information according to another embodiment;

[0100] Figure 10 A flowchart illustrating a method for displaying monitoring information according to yet another embodiment;

[0101] Figure 11 This is a flowchart of an alarm identification method based on monitoring information according to one embodiment;

[0102] 1. Amplitude-integrated electroencephalography (EEG);

[0103] 2a. Heart rate trend chart;

[0104] 2b. Blood oxygenation trend graph;

[0105] 3. EEG parameter waveforms;

[0106] 4a. Heart rate waveform;

[0107] 4b. Blood oxygen waveform;

[0108] 5. Real-time EEG parameter waveforms;

[0109] 6a. Real-time heart rate waveform;

[0110] 6b. Real-time blood oxygen waveform;

[0111] 10. Input device;

[0112] 20. Data acquisition device;

[0113] 30. Memory;

[0114] 40. Monitor;

[0115] 50. Processor.

[0116] x, First display area;

[0117] y, Second display area;

[0118] z, Third display area;

[0119] m, physiological information display area;

[0120] n. Display sub-windows;

[0121] e. Marker line.

[0122] Invention Embodiments

[0123] Embodiments of the present invention

[0124] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0125] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0126] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0127] Current monitoring interfaces typically display real-time EEG waveforms and corresponding amplitude-integrated EEG (AIE) graphs. If an EEG signal is abnormal, it appears fleeting on the real-time waveform to the user, but is "retained" on the AIE graph. Therefore, AIE is a crucial indicator of EEG abnormalities. In clinical practice, medical staff usually refer to other monitoring parameters to determine EEG abnormalities. However, these other parameters are generally on different monitoring devices, and medical staff need to expend considerable effort comparing the AIE graph with other monitoring parameter trend graphs. The improvement of this invention lies in minimizing the effort required for medical staff to make comparisons, providing users with the necessary information in a more intuitive and effective manner.

[0128] Please refer to Figure 1 The present invention provides a monitoring system, including an input device 10, a data acquisition device 20, a memory 30, a display 40, and a processor 50.

[0129] The input device 10 is configured to receive input from a user (typically an operator), such as one or more of a mouse, keyboard, touchscreen, trackball, and joystick, to receive user-inputted commands. The user can perform input operations through the input device 10.

[0130] The display 40 is configured to output information, such as visual information. The display 40 can be a simple display or a touchscreen display. Therefore, the display 40 and the input device 10 form a human-machine interface for the monitoring system, capable of both receiving user input and displaying visual information.

[0131] The data acquisition device 20 is used to acquire monitoring data. For example, it can be used to acquire first monitoring data of the patient's electroencephalogram (EEG) parameters and second monitoring data of at least one other monitoring parameter besides the EEG parameters. In this document, the first monitoring data refers to the monitoring data of the EEG parameters, and the second monitoring data refers to the monitoring data of the other monitoring parameters besides the EEG parameters. The monitoring system of the present invention can be any of a patient monitor, a local central station, a remote central station, a cloud service system, or a mobile terminal, and the corresponding data acquisition device 20 can acquire monitoring data in different ways. For example, if the monitoring system is a patient monitor, the data acquisition device 20 can be a sensor. The sensor is used to monitor the patient's monitoring parameters and obtain monitoring data of the monitoring parameters. In addition to EEG parameters, the types of monitoring parameters include one or more of the following: brain oxygen, heart rate, respiration, non-invasive blood pressure, blood oxygen saturation, pulse, body temperature, blood glucose, invasive blood pressure, end-tidal carbon dioxide, respiratory mechanics, anesthetic gas, cardiac output, and bispectral index of EEG. For example, if the monitoring system can be a local central station, a remote central station, a cloud service system, or a mobile terminal, then the data acquisition device 20 is a communication device or communication interface or other communication module used to communicate with the monitor and obtain the aforementioned monitoring data from the monitor.

[0132] The memory 30 is used to temporarily store or store the first monitoring data and the second monitoring data. Simultaneously, intermediate values ​​and calculation results from secondary processing such as calculations and comparisons of the monitoring data can also be temporarily stored or stored in the memory 30. The memory 30 can be implemented using any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0133] Processor 50 can be configured to integrate the amplitude of EEG during a first monitoring period based on the acquired first monitoring data. Figure 1 (aEEG, amplitude integrated electroencephalography), and also generate a trend graph of at least one other monitoring parameter based on the second monitoring data during the second monitoring period.

[0134] The first monitoring period can be the default time period of the monitoring system, or it can be set based on user input. For example, the user can input any two of the three parameters of the first monitoring period: start time, duration, and end time, and then obtain a specific time period as the first monitoring period.

[0135] The aforementioned second monitoring period is based on the first monitoring period, or rather, it changes accordingly with the changes in the first monitoring period. The first and second monitoring periods must meet the following condition: they must overlap, meaning there must be at least some overlap. If this condition is met, the second monitoring period can be a default time period, for example, the second monitoring period can default to having the same start and end times as the first monitoring period. Alternatively, it can be set by user input, such as setting the midpoint of the first monitoring period as the start point of the second monitoring period.

[0136] The aforementioned trend chart is also known as a progression chart, running chart, chain chart, trend graph, etc. A trend chart can be used to reflect the relationship between one or more variables and time, that is, the trend of the changes in one or more variables over time. For example, a trend chart can use time as the horizontal axis and the variable to be observed as the vertical axis to observe the trend and / or deviation of the variable's changes. The horizontal axis time can be seconds, minutes, hours, days, months, years, etc., and each time point should be continuous. The observed variable on the vertical axis can be an absolute quantity / absolute value, average value, incidence rate, etc. In this paper, trend charts for monitoring parameters other than EEG parameters can be used to reflect the trend of a monitoring parameter changing over time. For example, the parameter value of the monitoring parameter changes continuously over time. This parameter value can be an absolute value collected at a certain sampling rate, or an average value collected and calculated at a certain sampling rate over various fixed time periods. Therefore, for monitoring parameters, the "variable" in the trend chart is usually the parameter value of the monitoring parameter. Furthermore, regarding the format of the trend graph, it only needs to reflect the changing trend of the monitoring parameters. Therefore, the trend graph can be one of the following: a line graph, histogram, bar graph, box plot, scatter plot, or line graph, or various combinations of these. In this embodiment, the trend graphs of monitoring parameters other than EEG parameters are illustrated using a line graph as an example, and the overall illustration uses heart rate and blood oxygen as examples.

[0137] Please refer to Figure 2 Amplitude-integrated EEG data were obtained during the first monitoring period. Figure 1 and heart rate trends during the second monitoring period Figure 2 a and blood oxygen trends Figure 2 After b, the processor 50 can control the first display area x on the display 40 to simultaneously display the amplitude-integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b.

[0138] If the patient's amplitude is integrated with EEG Figure 1 If an abnormality occurs, and this abnormality happens within the overlapping period of the first and second monitoring periods, then medical staff can directly observe the heart rate trend. Figure 2 a and / or blood oxygen trend Figure 2 b. Changes in amplitude at corresponding moments or time periods, combined with heart rate and / or blood oxygenation, to comprehensively assess the patient's condition. For example, when amplitude is integrated with EEG... Figure 1 If a suspected electrical discharge pattern is observed, and respiratory monitoring (RESP) is simultaneously found to have stopped, it may be considered that the child has experienced an apnea (AOP) event due to the presence of the electrical discharge.

[0139] Amplitude integrated EEG Figure 1 Combined analysis with trend charts of other monitoring parameters can reduce the false positive rate. For healthcare workers, it also eliminates the need to search for relevant parameters on other devices, saving time and effort.

[0140] To facilitate quick location of information by medical staff, the processor 50 can integrate EEG data based on amplitude. Figure 1 Using timelines to generate heart rate trends Figure 2 a and blood oxygen trends Figure 2 b's time axis enables amplitude integration of EEG Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b. The time interval represented by each unit on the time axis of the three is the same. The time interval represented by each unit can be variable or preset. For example, the preset time interval can be a specific time interval / time scale / walking speed determined according to medical guidelines, industry standards, etc. Figure 2 The illustrated embodiment integrates EEG data based on amplitude. Figure 1 Using timelines to generate heart rate trends Figure 2 a and blood oxygen trends Figure 2 The display interface following timeline b hides the individual timelines. Intuitively, medical staff are observing the integrated EEG amplitude. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 At time b, by moving the gaze the same distance along the respective time axes of the three timeframes, one can observe the amplitude integration EEG at the same moment or time period. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 Changes on b.

[0141] Amplitude integrated EEG Figure 1 It is obtained by compressing the primary monitoring data, heart rate trend. Figure 2a and blood oxygen trends Figure 2 The generation method of b also differs from existing trend chart generation methods, essentially "compressing" existing trend charts. Existing trend charts record the values ​​of various parameters based on a set "window time," while this application integrates EEG data based on amplitude. Figure 1 The sampling and recording of other monitoring parameters were automatically adjusted, resulting in the aforementioned heart rate trend. Figure 2 a and blood oxygen trends Figure 2 b maintained integration with amplitude in EEG Figure 1 Synchronous compression. In other words, this example not only provides the integration of the amplitude from the first monitoring period into the EEG... Figure 1 Furthermore, the scheme of jointly presenting trend graphs of other monitoring parameters during the second monitoring period provides a further explanation of how to organically and rationally combine the two to facilitate the integration of amplitude into EEG data. Figure 1 The purpose is to compare and contrast the trend charts with those of other monitoring parameters.

[0142] In some embodiments, the amplitude can also be integrated into the EEG within the first display area x. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 b. Displaying them side-by-side (e.g., three arranged vertically or horizontally; this embodiment uses a vertical arrangement as an example). After side-by-side display, if lines are drawn connecting the same moments on the timeline of each graph, then those lines will be parallel to each other. This makes observation easier for medical staff, allowing them to focus more on information analysis. For example, as... Figure 2 The image shown is an example of amplitude-integrated EEG. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 b. Side-by-side display method (two amplitudes integrated EEG) Figure 1 This is because there are two EEG measurement channels, similar to using two sensors to simultaneously measure two signals. In this method, the first and second monitoring periods are exactly the same (the start and end times are identical). From the user's perspective, this is reflected in the amplitude integration of EEG. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 The window time (total duration displayed on monitor 40) for b is the same, both being 3 hours. Meanwhile, the amplitude-integrated EEG... Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 b. The three are displayed side by side, which is both compact and in line with human eye habits.

[0143] In addition, amplitude-integrated EEG Figure 1 Heart rate trend Figure 2a and blood oxygen trends Figure 2 b can also share a common timeline to facilitate comparison among the three.

[0144] Similarly, to facilitate amplitude integration of EEG Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 Based on the reference and comparison of b, the processor 50 can control the display 40 to mark the amplitude of the integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b. A portion at the same time or within a time period. For example, it can be marked using boxes, arrows, marker lines, symbols, text, etc. Figure 2 In the middle, amplitude integration of EEG Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 Not only are the three data points (b, b, and c) displayed side-by-side, but the line connecting their respective timelines at the same point in time is a vertical marker line (e). This marker line (e) can be used as a marker to integrate the amplitude of the EEG data. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b intersects.

[0145] The aforementioned markers are dynamic markers, capable of responding to the user's initial input command and altering the amplitude of the integrated EEG signal. Figure 1 The position above, when the amplitude is integrated with the EEG Figure 1 Heart rate trend after the marker position is changed Figure 2 a and blood oxygen trends Figure 2 The position of the marker on 'b' also changes synchronously to maintain the consistency of the time or time period pointed to by the marker. For example, in Figure 2 In the process, users can move the marker line e using the mouse to control the cursor, thereby simultaneously changing the marker line e and the amplitude integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b is the location where they intersect. Other operations on the marker include, but are not limited to, gesture input commands or manually dragging or clicking the marker when the display is a touchscreen.

[0146] By integrating EEG amplitudes at the same moment or within the same time period Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b is marked, even if the heart rate trend Figure 2 a and blood oxygen trends Figure 2 b's timeline integrates EEG without amplitude dependence Figure 1 With the generation of the timeline, users can quickly and accurately locate heart rate trends. Figure 2 a and blood oxygen trends Figure 2 The part to refer to on b.

[0147] In addition to referring to trend charts of other monitoring parameters, amplitude-integrated EEG Figure 1 It can also be compared with EEG waveform 3, which is used as a comparison reference for EEG waveform 3 and amplitude integrated EEG. Figure 1 The signals originate from the same source, meaning that the initial monitoring data of the patient, after compression and other processing, generates an amplitude-integrated EEG. Figure 1 The first monitoring data, without compression, can generate the raw EEG parameter waveform 3. The following section discusses the amplitude-integrated EEG... Figure 1 Based on this, the explanation will refer to the waveform of EEG parameters 3.

[0148] The monitoring system is first based on the user's integrated EEG amplitude. Figure 1 The input command selects either a reference time point or a reference time period, specifying which time period the user wants to view the EEG waveform parameters. Taking the user selecting a reference time point as an example, the user can select the amplitude-integrated EEG waveform using a mouse or other peripheral device (e.g., double-clicking or long-term hovering). Figure 1 Coordinates or amplitude integration of EEG on the time axis Figure 1 A reference time point is selected at a specific location. Then, the third monitoring period is determined based on the selected reference time point. The relationship between the third monitoring period and the selected reference time point is as follows: the third monitoring period must include the selected reference time point. This is because after the monitoring system obtains the third monitoring period, it generates EEG parameter waveform 3 based on the first monitoring data acquired within the third monitoring period. The user can integrate the EEG parameter waveform 3 with the amplitude for a period before and / or after the selected reference time point into the EEG data. Figure 1 A comparison is performed. For example, if the length of the third monitoring period is preset to 30 seconds, after selecting a reference time point, the system will automatically use 15 seconds before and after the selected reference time point (30 seconds in total) as the third monitoring period. Alternatively, the selected reference time point can be used as the start or end time point of the third monitoring period. Of course, the length of the third monitoring period can be variable, provided it includes a reference time point. For example, if the initial user-set length of the third monitoring period is 10 seconds, the length can be extended during the comparison process to obtain more information about the EEG parameter waveform 3. The EEG parameter waveform 3 of the third monitoring period is compared with the amplitude integrated EEG. Figure 1 In essence, it is uncompressed "raw data." Users can "retrieve" the "raw data" of a specific point in time or time period according to their needs and integrate it with the amplitude of the EEG. Figure 1 Comparative analysis can be performed, for example, when a user discovers that the amplitude of the integrated EEG data is within a certain time point or time period. Figure 1If abnormalities are found, the corresponding EEG parameter waveform 3 can be reviewed to obtain more information. Therefore, the above-mentioned amplitude-integrated EEG... Figure 1 The scheme of simultaneously displaying EEG parameter waveforms after selecting a reference time point or reference time period has important clinical value.

[0149] Integrating amplitude into EEG Figure 1 There are many ways to compare and reference the EEG parameters waveform 3 of the third monitoring period mentioned above. Two examples are given below.

[0150] Method 1

[0151] like Figure 3 Or as shown in Figure 4, simultaneously displaying amplitude-integrated EEG Figure 1 The vital information display area m displays the EEG parameter waveform 3 for the currently determined third monitoring period. Figure 3 The third monitoring period is from 5:00 PM to 5:15 PM. The vital signs display area m can be an integrated EEG display on monitor 40. Figure 1 In addition to a pre-defined fixed area. In some embodiments, when the user is not in the amplitude-integrated EEG... Figure 1 When a reference time point or reference time period is selected, the life information display area m can display various real-time monitoring data of the current patient's monitoring parameters (including first monitoring data and / or second monitoring data), or it can display real-time EEG parameter waveforms 3, etc., to provide medical staff with more patient information.

[0152] Method 2

[0153] like Figure 5 As shown, the monitoring system responds to the user's integrated EEG amplitude. Figure 1 The input command to select a reference time point or reference time period will bring up a sub-window n displaying further EEG parameter waveform 3. For example, when the user clicks the amplitude integrated EEG... Figure 1 When a certain position is reached on the screen, this sub-window n will pop up. This sub-window n is at least partially superimposed on the amplitude-integrated EEG. Figure 1 The upper or lower amplitude integrated EEG Figure 1 They are displayed independently of each other. Partial overlay refers to the fact that the displayed sub-window n can partially obscure the amplitude of the integrated EEG as a floating window. Figure 1 The blank area, or, in Figure 5 The amplitude-integrated EEG data was partially obscured, with a portion of the data being located far from the selected reference time point or reference time period. Figure 1 (Does not affect amplitude integration of EEG) Figure 1 (Comparison with EEG parameter waveform 3). There are also more ways to display them independently, including but not limited to displaying sub-window n and amplitude-integrated EEG. Figure 1Display side-by-side, for example, displaying sub-window n with amplitude-integrated EEG. Figure 1 At least one boundary of each element is adjacent to the other and they are either vertically or horizontally side-by-side; the display sub-window n is integrated with the amplitude EEG. Figure 1 Display in different regions, for example, where the boundaries of the two are not adjacent or they are separated; display sub-window n with amplitude-integrated EEG. Figure 1 The display alternates between floating elements in response to user selections, for example, when the user moves the mouse to the amplitude integration EEG. Figure 1 When it is above, the amplitude is integrated with the EEG. Figure 1 The cursor hovers above and partially obscures the display sub-window n. When the user moves the cursor to the EEG parameter waveform 3 within the display sub-window n, the display sub-window n hovers above the amplitude integrated EEG waveform. Figure 1 The upper part of the amplitude is blocked and the EEG is integrated. Figure 1 This method can reduce the amplitude of EEG integration Figure 1 It displays the area occupied by the child window n, while highlighting the information the user wants to view.

[0154] Based on the EEG parameter waveform 3 from the third monitoring period, waveforms of other monitoring parameters from the fourth monitoring period can be further displayed. Similar to the third monitoring period, the fourth monitoring period can integrate EEG data based on user-defined amplitude parameters. Figure 1 The input is determined by the selection command of the reference time point or reference time period. For example, the user can select the amplitude-integrated EEG using a peripheral device such as a mouse (e.g., by double-clicking or long-term hovering). Figure 1 Coordinates or amplitude integration of EEG on the time axis Figure 1 A reference time point is selected at a certain location. Then, the fourth monitoring period is determined based on the selected reference time point. The relationship between the fourth monitoring period and the selected reference time point is that the fourth monitoring period must include the selected reference time point. After determining the fourth monitoring period, the processor 50 generates a waveform of at least one other monitoring parameter based on the second monitoring data acquired during the fourth monitoring period. In the following explanation, heart rate and blood oxygen saturation are used as examples of other monitoring parameters during the fourth monitoring period. Blood oxygen waveform during the fourth monitoring period. Figure 4 b and heart rate waveform Figure 4 The purpose of 'a' is to compare it with the EEG parameter waveform 3 during the third monitoring period, and to jointly evaluate the amplitude integration of EEG. Figure 1 Does the abnormality in the waveform represent the patient's actual condition? While the waveform's time span is relatively short, it better reflects changes in other monitoring parameters around the user-selected reference time point or time period, helping medical staff to more accurately interpret the amplitude-integrated EEG. Figure 1Abnormal situations are assessed. For example, the total length of the fourth monitoring period is 30 seconds, including the 15 seconds before and after the user-selected reference time point. It should be noted that since the fourth monitoring period is based on the user-selected reference time point, its length is not directly related to the length of the third monitoring period. It is sufficient that the waveforms of other monitoring parameters during the fourth monitoring period adequately illustrate the changes in these parameters at the selected time point. Similar to the display method of EEG parameter waveform 3, the heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b can also be displayed within a pre-defined display area, or a pop-up window can be set up for display. Of course, the heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b can be like Figure 4 As shown, along with the EEG parameter waveform 3, it is displayed in the vital information display area m, or as... Figure 5 As shown, the EEG parameter waveform 3 is displayed in the sub-window n.

[0155] In some embodiments, the EEG waveform 3 and the heart rate waveform Figure 4 a and blood oxygen waveform Figure 4 b. The display comparison method of the three can refer to the amplitude integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b) The display comparison method of the three is processed. Specifically, the processor 50 can generate a heart rate waveform based on the time axis of the EEG parameter waveform 3. Figure 4 a and blood oxygen waveform Figure 4 The time axis of b makes the EEG parameter waveform 3 and heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b) On the time axis of all three, each unit of measurement represents the same duration. Intuitively, this means that medical staff are observing the EEG waveform, heart rate waveform, and other parameters. Figure 4 a. Blood oxygen waveform Figure 4 b) By moving the gaze equidistantly along the respective time axes of the three parameters (3) and heart rate waveform, one can observe the EEG waveform at the same moment or time interval. Figure 4 a. Blood oxygen waveform Figure 4 Changes on b. In addition, EEG waveform 3 and heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b can also share a common timeline to facilitate comparison among the three.

[0156] In some embodiments, the EEG waveform 3 and heart rate waveform can be used. Figure 4 a. Blood oxygen waveform Figure 4b. Displaying them side-by-side (e.g., vertically or horizontally arranged; in this embodiment, vertical arrangement is used as an example). After side-by-side display, if lines are drawn connecting the same moments on the time axis of each graph, the lines will be parallel to each other. This makes observation easier for medical staff, allowing them to focus more on information analysis. Furthermore, simultaneously displaying the waveforms of the aforementioned EEG parameters 3 with waveforms of other monitoring parameters also has significant clinical implications. From the user's perspective, amplitude integration of EEG can be observed first. Figure 1 Then, by using the time point of interest or that is considered abnormal as a reference time point, the EEG parameters and other monitoring parameters around the reference time point can be reviewed. This helps medical staff make a more accurate judgment on the patient's condition, and subsequently, targeted medication or treatment methods can be selected. For example, when a patient experiences abnormal discharges, the EEG data can be integrated within a 40-degree range on the same monitor. Figure 1 Heart rate waveform Figure 4 a. Blood oxygen waveform Figure 4 b) and respiratory rate waveform diagrams are used to better determine whether the patient's abnormal discharge is caused by asphyxiation or asphyxiation is caused by abnormal discharge (the treatment directions for these two situations are completely different), and appropriate treatment is carried out accordingly.

[0157] Similarly, to facilitate the display of EEG waveform 3 and heart rate waveform... Figure 4 a. Blood oxygen waveform Figure 4 Based on the reference and comparison of b, the processor 50 can control the display 40 to mark the EEG parameter waveform 3 and the heart rate waveform respectively. Figure 4 a. Blood oxygen waveform Figure 4 b. A portion at the same time or within a time period. For example, it can be marked using boxes, arrows, marker lines, symbols, text, etc. Figure 4 or Figure 5 In the middle, the EEG waveform 3 and the heart rate waveform Figure 4 a. Blood oxygen waveform Figure 4 Not only are the three waveforms (b, 3, and 4) displayed side-by-side, but the line connecting their respective time axes at the same point in time is a vertical marker line (e). This marker line (e) can be used as a marker to correlate with the EEG waveform (3), heart rate waveform, and other parameters. Figure 4 a. Blood oxygen waveform Figure 4 b intersects.

[0158] The aforementioned marker is a dynamic marker, capable of responding to a second user input command and changing its position on the EEG waveform 3. When the marker position on the EEG waveform 3 changes, the heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 The position of the marker on 'b' also changes accordingly to maintain consistency in the time or time period it points to. For example, in Figure 4In the process, users can move the marker line e using the mouse cursor, thereby simultaneously changing the relationship between marker line e and the EEG waveform 3 and heart rate waveform. Figure 4 a. Blood oxygen waveform Figure 4 b is the location where they intersect. Other operations on the marker include, but are not limited to, gesture input commands or manually dragging or clicking the marker when the display is a touchscreen.

[0159] In some embodiments, the monitoring system may also jointly present real-time EEG parameter waveform 5 and real-time waveforms of at least one other monitoring parameter (hereinafter, blood oxygen and heart rate are examples). Specifically, while acquiring the patient's first monitoring data, the processor 50 may generate and display the real-time EEG parameter waveform 5 on the display 40; while acquiring the patient's heart rate and blood oxygen monitoring data, the processor 50 may generate and display the real-time heart rate waveform on the display 40. Figure 6 a and real-time blood oxygen waveform Figure 6 b. Real-time EEG waveform, 5. Real-time heart rate waveform Figure 6 a and real-time blood oxygen waveform Figure 6 b Simultaneously, users can observe the changes in real-time EEG parameters (waveform 5) and real-time blood oxygen waveform at the same moment. Figure 6 b and real-time heart rate waveform Figure 6 The change of 'a'.

[0160] like Figure 6 As shown, the real-time EEG parameter waveform 5 and the real-time heart rate waveform are displayed. Figure 6 a and real-time blood oxygen waveform Figure 6 b. During the simultaneous display, the real-time heart rate waveform can be shown. Figure 6 a's paper feed speed and real-time blood oxygen waveform Figure 6 The paper feed speed of b is adjusted to match the paper feed speed of the real-time EEG parameter waveform 5. For example, if the paper feed speed of the real-time EEG parameter waveform 5 is 6 cm / h, it means that any point on the real-time EEG parameter waveform 5 will travel 6 cm on the display screen after one hour. Thus, a real-time heart rate waveform with a paper feed speed of 6 cm / h is generated. Figure 6 a and real-time blood oxygen waveform Figure 6 b.

[0161] By real-time heart rate waveform Figure 6 a and real-time blood oxygen waveform Figure 6 The paper feed speed of b is adjusted to match the paper feed speed of the real-time EEG parameter waveform 5, so that the real-time heart rate waveform... Figure 6 a. Real-time blood oxygen waveform Figure 6 b and the real-time EEG parameter waveform 5 remain relatively stationary, allowing users to easily compare the changes in the three waveforms at the same time. In other embodiments, the real-time EEG parameter waveform 5 and the real-time heart rate waveform... Figure 6a and real-time blood oxygen waveform Figure 6 The paper feed speed of b can also be inconsistent. For example, the display 40 shows the real-time EEG parameter waveform 5 from the current time to 10 seconds before the current time, and the real-time heart rate waveform from the current time to 20 seconds before the current time. Figure 6 a and real-time blood oxygen waveform Figure 6 b, and real-time heart rate waveform Figure 6 a's paper feed speed and real-time blood oxygen waveform Figure 6 The paper feed speed of b is twice that of the real-time EEG parameter waveform 5.

[0162] As can be seen from the above, the display 40 in this application can show the user at least: amplitude-integrated EEG data from the first monitoring period. Figure 1 The trend graphs of other monitoring parameters in the second monitoring period, the waveforms of EEG parameters in the third monitoring period (3), the waveforms of other monitoring parameters in the fourth monitoring period (5), the real-time EEG waveforms, and the real-time waveforms of other monitoring parameters, can be combined in two main ways. In the first type of combination, the amplitude integrated EEG data from the first monitoring period... Figure 1 It can be displayed simultaneously with at least one of the following for comparison: trend graphs of other monitoring parameters in the second monitoring period, EEG parameter waveform 3 in the third monitoring period, and waveform graphs of other monitoring parameters in the fourth monitoring period. In the second type of combination, real-time EEG parameter waveform 5 and real-time waveform graphs of other monitoring parameters are displayed simultaneously. The first and second types of combinations can also be displayed simultaneously. Furthermore, the time axis of the trend graphs of other monitoring parameters can be integrated with the EEG waveforms based on amplitude. Figure 1 The timeline is generated, thereby compressing the trend plots of other monitoring parameters into an EEG integrated with amplitude. Figure 1 Synchronous display facilitates comparison and reference. The time axis of the waveform of other monitoring parameters can be generated based on the time axis of EEG parameter waveform 3, which also facilitates comparison and reference.

[0163] like Figure 7 The diagram shows an interface where the first and second types of combinations are displayed simultaneously in one embodiment. The display interface is divided into a first display area x, a second display area y, and a third display area z, and the amplitude-integrated EEG data for the first monitoring period is shown. Figure 1 At the point where the first display area x and the second display area y overlap, the first display area x also displays trend graphs of other monitoring parameters for the second monitoring period, while the second display area y also includes a vital information display area m, in which the EEG parameter waveform 3 for the third monitoring period and the waveform graphs of other monitoring parameters for the fourth monitoring period are displayed, and the third display area z displays the real-time EEG parameter waveform 5 and the real-time waveform graphs of other monitoring parameters.

[0164] Figure 7The illustrated embodiment is an example where all information is concentrated on the display interface. In other embodiments, the figures may also pop up or hide based on user operation commands.

[0165] In some embodiments, the monitoring system further identifies and alarms for abnormal EEG events based on the acquired first monitoring data and second monitoring data. These abnormal EEG events may include, but are not limited to, symptoms that cause abnormal EEG signals in patients, such as epilepsy, seizures, suspected seizures, and burst inhibition. Specifically, the processor 50 can integrate EEG data based on amplitude. Figure 1 Amplitude integration EEG Figure 1 Abnormal moments in the data, for example, could be amplitude-integrated EEG data. Figure 1 The appearance of a "gap" in the data may be due to amplitude integration of EEG. Figure 1 The processor 50 identifies moments when the amplitude of changes rapidly increases. Since the monitoring system acquires both the first and second monitoring data simultaneously, upon receiving this abnormal moment, the processor 50 can obtain the change characteristics of at least one other monitoring parameter on the trend graph at that moment. These change characteristics can be obtained by calculating parameters such as the first and second derivatives of the trend graph. If these change characteristics correspond to the changes that would occur in the trend graph during an abnormal EEG event, then the processor 50 identifies the occurrence of an abnormal EEG event. In other words, the processor 50 can automatically integrate EEG data based on amplitude. Figure 1 Following an initial assessment and further confirmation through trend charts of other monitoring parameters, if both the initial assessment and further confirmation indicate the occurrence of an abnormal EEG event, the display 40 can be controlled to show alarm information associated with that event. For example, an alarm notification can be issued to the user by displaying graphic text (an alarm string displayed in real-time in the alarm area at the top of the display 40 interface).

[0166] The aforementioned monitoring system can automatically identify abnormal EEG events and output corresponding alarm information to a certain extent, thereby greatly reducing the workload of medical staff.

[0167] After displaying an alarm message, medical staff typically take certain measures or methods to treat the patient, such as medication. If the monitoring system only alarms when an EEG abnormality occurs, it is insufficient to assist medical staff in completing the entire patient monitoring process. Therefore, in some embodiments, the monitoring system can acquire the first moment representing the patient's treatment and / or medication administration. This first moment can be acquired manually by the user, for example, after medication or medical device treatment, the medical staff manually input the treatment or medication time. Alternatively, it can be acquired by recording the status of the medical device when the monitoring system is connected to it. For example, if the monitoring system is connected to an infusion pump, after the infusion pump completes the injection treatment for the user, it sends a message indicating that the injection operation is complete to the monitoring system. The monitoring system can use the moment it receives this message as the first moment. After acquiring the first moment, the processor 50 then acquires the alarm load within a first preset time period before the first moment and the alarm load within a second preset time period after the first moment. The first and second preset time periods are of the same or approximately the same length. The alarm load is used to characterize the severity of the patient's EEG abnormality. The alarm load may include, but is not limited to, the number of alarms within the preset time period and / or the total alarm duration corresponding to the same type of EEG abnormality. For example, the number of alarms can be recorded within 5 hours before and 5 hours after the first moment. If the number of alarms decreases significantly within the last 5 hours, it can prove that the treatment is effective, and the degree of decrease in the number of alarms can further assess the effectiveness of the treatment. In some embodiments, the alarm load can be quantitatively integrated with the amplitude of the EEG in the form of a load map. Figure 1 The presentation can be combined, for example, the load chart is a statistical histogram, where each bar in the histogram represents the total alarm duration corresponding to a type of abnormal EEG event, and the same type of abnormal EEG event has two corresponding bars, which are used to represent the total duration of a period of time before the treatment time and a period of time after the treatment time, respectively.

[0168] By introducing alarm load and integrating amplitude into EEG Figure 1 When presented in conjunction with a load chart, users can intuitively understand the patient's physical condition before and after treatment or medication, thereby formulating subsequent strategies.

[0169] In the above embodiments, the acquisition times of the monitoring data for EEG parameters and other types of monitoring data overlap. That is, at least during a monitoring period, both the first monitoring data for EEG parameters and the second monitoring data for at least one other monitoring parameter are acquired. However, in some embodiments, the acquisition times of the first monitoring data for EEG parameters and the physiological data for certain non-monitoring physiological parameters may differ. For example, in some embodiments, the monitoring system is communicatively connected to an ultrasound device. The ultrasound device is used to obtain changes in cerebral blood flow using ultrasound technology, then generates a cerebral blood flow map based on these changes, and finally integrates the cerebral blood flow map and amplitude data into the EEG data. Figure 1 A joint comparison is performed. During this process, the physiological data and the initial monitoring data of the electroencephalogram (EEG) parameters acquired by the ultrasound equipment can be obtained in different time periods.

[0170] The aforementioned monitoring system can be used in conjunction with other monitoring devices to perform overall analysis and judgment of the acquired monitoring parameters.

[0171] Please refer to Figure 8 The present invention also provides a method for displaying monitoring information, comprising the following steps:

[0172] Step 100: Obtain the first monitoring data of the patient's EEG parameters during the first monitoring period.

[0173] For example, impedance detection can be used to obtain the first monitoring data of EEG parameters. The aforementioned first monitoring period can be the default time period of the monitoring system, or it can be set based on user input. For example, the user can input any two of the three parameters of the first monitoring period: the start time, duration, and end time, and a specific time period can be obtained as the first monitoring period.

[0174] Step 200: Obtain second monitoring data for the patient during the second monitoring period, excluding EEG parameters, for at least one other monitoring parameter.

[0175] In addition to EEG parameters, monitoring parameters can include one or more of the following: brain oxygenation, heart rate, respiration, non-invasive blood pressure, blood oxygen saturation, pulse, body temperature, blood glucose, invasive blood pressure, end-tidal carbon dioxide, respiratory mechanics, anesthetic gases, cardiac output, and bispectral index. This embodiment primarily uses blood oxygenation and heart rate as examples for illustration.

[0176] The aforementioned second monitoring period is based on the first monitoring period, or rather, it changes accordingly with the changes in the first monitoring period. The first and second monitoring periods must meet the following condition: they must overlap, meaning there must be at least some overlap. If this condition is met, the second monitoring period can be a default time period, for example, the second monitoring period can default to having the same start and end times as the first monitoring period. Alternatively, it can be set by user input, such as setting the midpoint of the first monitoring period as the start point of the second monitoring period.

[0177] Step 300: Generate amplitude-integrated EEG data for the first monitoring period based on the first monitoring data. Figure 1 .

[0178] Step 400: Based on the second monitoring data, generate a trend chart for at least one other monitoring parameter during the second monitoring period.

[0179] The aforementioned trend chart is also known as a progression chart, running chart, chain chart, trend graph, etc. A trend chart can be used to reflect the relationship between one or more variables and time, that is, the trend of the changes in one or more variables over time. For example, a trend chart can use time as the horizontal axis and the variable to be observed as the vertical axis to observe the trend and / or deviation of the variable's changes. The horizontal axis time can be seconds, minutes, hours, days, months, years, etc., and each time point should be continuous. The observed variable on the vertical axis can be an absolute quantity / absolute value, average value, incidence rate, etc. In this paper, the trend chart of a monitoring parameter can be used to reflect the trend of a monitoring parameter changing over time. For example, the parameter value of the monitoring parameter changes continuously over time. This parameter value can be an absolute value collected at a certain sampling rate, or an average value collected and calculated at a certain sampling rate over various fixed time periods. Therefore, for a monitoring parameter, the "variable" in its trend chart is usually the parameter value of that monitoring parameter. Furthermore, regarding the format of the trend chart, as long as it reflects the changing trend of the monitored parameters, it can be any one of the following: line graph, histogram, bar chart, box plot, scatter plot, or line graph; or it can be various combinations of line graphs, histograms, bar charts, box plots, scatter plots, and line graphs. In this embodiment, the trend chart of the monitored parameters is illustrated using a line graph as an example.

[0180] Step 500: Simultaneously display amplitude-integrated EEG Figure 1 And a trend graph of at least one other monitoring parameter.

[0181] Figure 2 EEG amplitude integration Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b is the interface simultaneously displayed within the first display area x. If the patient's amplitude is integrated with the EEG... Figure 1If an abnormality occurs, and this abnormality happens within the overlapping period of the first and second monitoring periods, then medical staff can directly observe the heart rate trend. Figure 2 a and / or blood oxygen trend Figure 2 b. Changes in amplitude at corresponding moments or time periods, combined with heart rate and / or blood oxygenation, to comprehensively assess the patient's condition. For example, when amplitude is integrated with EEG... Figure 1 If a suspected electrical discharge pattern is observed, and respiratory monitoring (RESP) is simultaneously found to have stopped, it may be considered that the child has experienced an apnea (AOP) event due to the presence of the electrical discharge.

[0182] Amplitude integrated EEG Figure 1 Combined analysis with trend charts of other monitoring parameters can reduce the false positive rate. For healthcare workers, it also eliminates the need to search for relevant parameters on other devices, saving time and effort.

[0183] In some embodiments, to facilitate medical staff in quickly locating the information they wish to view, the method further includes the following steps:

[0184] Step 510: Obtain amplitude-integrated EEG Figure 1 The first unit on the first timeline represents the duration. This unit can be the smallest grid cell on the timeline, or a user-defined unit.

[0185] Step 520: Integrate EEG based on amplitude Figure 1 The duration represented by the first unit on the first time axis is used to obtain the second time axis of the trend chart to be generated.

[0186] The purpose of this step is to adjust the duration represented by the second unit scale of the second time axis of the trend chart to match the amplitude of the EEG. Figure 1 The duration represented by each unit of time on the first time axis is the same.

[0187] Step 530: Generate a trend chart for at least one monitoring parameter based on the second monitoring data and the time axis of the trend chart.

[0188] Please continue to refer to Figure 2 The image shows an integrated EEG based on amplitude. Figure 1 Generate heart rate trend using the first timeline Figure 2 a and blood oxygen trends Figure 2 The display interface following the second timeline of b contains hidden individual timelines. Intuitively, medical staff observe the integrated amplitude EEG. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 At time b, by moving the gaze the same distance along the respective time axes of the three timeframes, one can observe the amplitude integration EEG at the same moment or time period. Figure 1 Heart rate trend Figure 2a and blood oxygen trends Figure 2 Changes on b.

[0189] Amplitude integrated EEG Figure 1 It is obtained by compressing the primary monitoring data, heart rate trend. Figure 2 a and blood oxygen trends Figure 2 The generation method of b also differs from existing trend chart generation methods, essentially "compressing" existing trend charts. Existing trend charts record the values ​​of various parameters based on a set "window time," while this application integrates EEG data based on amplitude. Figure 1 The sampling and recording of monitoring parameters were automatically adjusted to reflect the aforementioned heart rate trend. Figure 2 a and blood oxygen trends Figure 2 b maintained integration with amplitude in EEG Figure 1 Synchronous compression. In other words, this example not only provides the integration of the amplitude from the first monitoring period into the EEG... Figure 1 The scheme of jointly presenting trend graphs of monitoring parameters during the second monitoring period further provides a method for organically and rationally combining the two to facilitate the integration of amplitude into EEG data. Figure 1 The purpose is to compare and contrast the trend charts of monitoring parameters.

[0190] In some embodiments, after the trend graphs of the monitoring parameters are also synchronously "compressed," the amplitude can also be integrated into the EEG within the first display area x. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 b. Displaying them side-by-side (e.g., three arranged vertically or horizontally; this embodiment uses a vertical arrangement as an example). After side-by-side display, if lines are drawn connecting the same moments on the timeline of each graph, then those lines will be parallel to each other. This makes observation easier for medical staff, allowing them to focus more on information analysis. For example, as... Figure 2 The image shown is an example of amplitude-integrated EEG. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 b. Side-by-side display method (two amplitudes integrated EEG) Figure 1 This is because there are two EEG measurement channels, similar to using two sensors to simultaneously measure two signals. In this method, the first and second monitoring periods are exactly the same (the start and end times are identical). From the user's perspective, this is reflected in the amplitude integration of EEG. Figure 1 Heart rate trend Figure 2 a. Blood oxygenation trend Figure 2 The window time (total display duration) for b is the same, both being 3 hours. However, the amplitude-integrated EEG... Figure 1 Heart rate trend Figure 2a. Blood oxygenation trend Figure 2 b. The three are displayed side by side, which is both compact and in line with human eye habits.

[0191] In addition, amplitude-integrated EEG Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b can also share a common timeline to facilitate comparison among the three.

[0192] Similarly, to facilitate amplitude integration of EEG Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 The reference and comparison of b can also be used to separately label the amplitude of the integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b. A portion at the same time or within a time period. For example, it can be marked using boxes, arrows, marker lines, symbols, text, etc. Figure 2 In the middle, amplitude integration of EEG Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 Not only are the three data points (b, b, and c) displayed side-by-side, but the line connecting their respective timelines at the same point in time is a vertical marker line (e). This marker line (e) can be used as a marker to integrate the amplitude of the EEG data. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b intersects.

[0193] The aforementioned markers are dynamic markers, capable of responding to the user's initial input command and altering the amplitude of the integrated EEG signal. Figure 1 The position above, when the amplitude is integrated with the EEG Figure 1 Heart rate trend after the marker position is changed Figure 2 a and blood oxygen trends Figure 2 The position of the marker on 'b' also changes synchronously to maintain the consistency of the time or time period pointed to by the marker. For example, in Figure 2 In the process, users can move the marker line e using the mouse to control the cursor, thereby simultaneously changing the marker line e and the amplitude integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 The location where b intersects. Other operations on the marker include, but are not limited to, gesture input commands, manual dragging, or clicking the marker.

[0194] By integrating EEG amplitudes at the same moment or within the same time period Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b is marked, even if the heart rate trend Figure 2a and blood oxygen trends Figure 2 b's timeline integrates EEG without amplitude dependence Figure 1 With the generation of the timeline, users can quickly and accurately locate heart rate trends. Figure 2 a and blood oxygen trends Figure 2 The part to refer to on b.

[0195] In addition to referring to the trend chart of monitoring parameters, amplitude integration EEG Figure 1 It can also be compared with EEG waveform 3, which is used as a comparison reference for EEG waveform 3 and amplitude integrated EEG. Figure 1 The signals originate from the same source, meaning that the initial monitoring data of the patient, after compression and other processing, generates an amplitude-integrated EEG. Figure 1 The initial monitoring data, without compression, can generate raw EEG waveforms. For details, please refer to... Figure 9 After step 100, the following may be included:

[0196] Step 200-1: Generate amplitude-integrated EEG data for the first monitoring period based on the first monitoring data. Figure 1 .

[0197] This step can be the same as step 300.

[0198] Step 300-1: Integrate EEG based on user-defined amplitude. Figure 1 The input is a selection instruction for a reference time point or reference time period, and the third monitoring period of the reference time point or reference time period is included within the first monitoring period.

[0199] Taking the selection of a reference time point as an example, the user can select the amplitude-integrated EEG using peripherals such as a mouse (e.g., by double-clicking or hovering for a long time). Figure 1 Coordinates or amplitude integration of EEG on the time axis Figure 1 A reference time point is selected at a certain location. Then, the third monitoring period is determined based on the selected reference time point. The relationship between the third monitoring period and the selected reference time point is as follows: the third monitoring period must include the selected reference time point.

[0200] For example, if the length of the third monitoring period is preset to 30 seconds, after a reference time point is selected, the system will automatically use 15 seconds before and after the selected reference time point (30 seconds in total) as the third monitoring period. Alternatively, the selected reference time point can be used as the start or end time point of the third monitoring period. Of course, the length of the third monitoring period can be variable, provided that the conditions of including the reference time point are met. For example, if the initial user sets the length of the third monitoring period to 10 seconds, the length of the third monitoring period can be extended during the comparison process to obtain more information about the EEG parameter waveform 3.

[0201] Step 400-1: Integrate the EEG parameters waveform 3 and amplitude from the third monitoring period into the EEG data. Figure 1 Displayed simultaneously.

[0202] Integrating amplitude into EEG Figure 1 There are many ways to compare and reference the EEG parameters waveform 3 of the third monitoring period mentioned above. Two examples are given below.

[0203] Method 1

[0204] like Figure 3 Or as shown in Figure 4, simultaneously displaying amplitude-integrated EEG Figure 1 The vital information display area m displays the EEG parameter waveform 3 for the currently determined third monitoring period. Figure 3 The third monitoring period is from 5:00 PM to 5:15 PM. The vital signs display area m can be an amplitude-integrated EEG reading. Figure 1 In addition to a pre-defined fixed area. In some embodiments, when the user is not in the amplitude-integrated EEG... Figure 1 When a reference time point or reference time period is selected, the life information display area m can display various real-time monitoring data of the current patient's monitoring parameters (including first monitoring data and / or second monitoring data), or it can display real-time EEG parameter waveforms 3, etc., to provide medical staff with more patient information.

[0205] Method 2

[0206] like Figure 5 As shown, the monitoring system responds to the user's integrated EEG amplitude. Figure 1 The input command to select a reference time point or reference time period will bring up a sub-window n displaying further EEG parameter waveform 3. For example, when the user clicks the amplitude integrated EEG... Figure 1 When a certain position is reached on the screen, this sub-window n will pop up. This sub-window n is at least partially superimposed on the amplitude-integrated EEG. Figure 1 The upper or lower amplitude integrated EEG Figure 1 They are displayed independently of each other. Partial overlay refers to the fact that the displayed sub-window n can partially obscure the amplitude of the integrated EEG as a floating window. Figure 1 The blank area, or, in Figure 5 The amplitude-integrated EEG data was partially obscured, with a portion of the data being located far from the selected reference time point or reference time period. Figure 1 (Does not affect amplitude integration of EEG) Figure 1 (Comparison with EEG parameter waveform 3). There are also more ways to display them independently, including but not limited to displaying sub-window n and amplitude-integrated EEG. Figure 1 Display side-by-side, for example, displaying sub-window n with amplitude-integrated EEG. Figure 1At least one boundary of each element is adjacent to the other and they are either vertically or horizontally side-by-side; the display sub-window n is integrated with the amplitude EEG. Figure 1 Display in different regions, for example, where the boundaries of the two are not adjacent or they are separated; display sub-window n with amplitude-integrated EEG. Figure 1 The display alternates between floating elements in response to user selections, for example, when the user moves the mouse to the amplitude integration EEG. Figure 1 When it is above, the amplitude is integrated with the EEG. Figure 1 The cursor hovers above and partially obscures the display sub-window n. When the user moves the cursor to the EEG parameter waveform 3 within the display sub-window n, the display sub-window n hovers above the amplitude integrated EEG waveform. Figure 1 The upper part of the amplitude is blocked and the EEG is integrated. Figure 1 This method can reduce the amplitude of EEG integration Figure 1 It displays the area occupied by the child window n, while highlighting the information the user wants to view.

[0207] In some embodiments, the steps further include:

[0208] Step 500-1: Obtain second monitoring data for the patient during the second monitoring period, excluding EEG parameters, for at least one other monitoring parameter.

[0209] This step can be the same as step 200. It should be noted that there is no sequential restriction between steps 500-1 and steps 100-1 to 400-1.

[0210] Step 600-1: Based on the user's selection instruction for the reference time point or reference time period input for the amplitude integrated EEG, determine the fourth monitoring period including the reference time point or reference time period selected by the user.

[0211] The method for determining the fourth monitoring period is basically the same as that for the third monitoring period, so it will not be elaborated here. The relationship between the fourth monitoring period and the selected reference time point is that the fourth monitoring period should include the selected reference time point.

[0212] Step 700-1: Simultaneously display the waveform of EEG parameter 3 and the waveform of at least one monitoring parameter.

[0213] The following explanation uses heart rate and blood oxygen saturation as examples of monitoring parameters during the fourth monitoring period. Blood oxygen waveform during the fourth monitoring period. Figure 4 b and heart rate waveform Figure 4 The purpose of 'a' is to compare it with the EEG parameter waveform 3 during the third monitoring period, and to jointly evaluate the amplitude integration of EEG. Figure 1 Does the abnormality in the waveform represent the patient's actual condition? While the waveform's time span is relatively short, it better reflects changes in monitoring parameters near the user-selected reference time point or segment, helping medical staff to more accurately interpret the amplitude-integrated EEG. Figure 1 Abnormal situations are assessed. For example, the total length of the fourth monitoring period is 30 seconds, including the 15 seconds before and after the user-selected reference time point. It should be noted that since the fourth monitoring period is based on the user-selected reference time point, its length is not directly related to the length of the third monitoring period. The only requirement is that the waveform of the monitoring parameters in the fourth monitoring period sufficiently illustrates the changes in the monitoring parameters at the selected reference time point. Similar to the display method of EEG parameter waveform 3, the heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b can also be displayed within a pre-defined display area, or a pop-up window can be set up for display. Of course, the heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b can be like Figure 3 Or as shown in Figure 4, it is displayed together with the EEG parameter waveform 3 in the vital information display area m, or as shown in Figure 4. Figure 5 As shown, the EEG parameter waveform 3 is displayed in the sub-window n.

[0214] In some embodiments, the EEG waveform 3 and the heart rate waveform Figure 4 a and blood oxygen waveform Figure 4 b. The display comparison method of the three can refer to the amplitude integrated EEG. Figure 1 Heart rate trend Figure 2 a and blood oxygen trends Figure 2 b) The display comparison method of the three is processed. Specifically, the heart rate waveform can be generated based on the time axis of the EEG parameter waveform 3. Figure 4 a and blood oxygen waveform Figure 4 The time axis of b makes the EEG parameter waveform 3 and heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b) On the time axis of all three, each unit of measurement represents the same duration. Intuitively, this means that medical staff are observing the EEG waveform, heart rate waveform, and other parameters. Figure 4 a. Blood oxygen waveform Figure 4 b) By moving the gaze equidistantly along the respective time axes of the three parameters (3) and heart rate waveform, one can observe the EEG waveform at the same moment or time interval. Figure 4 a. Blood oxygen waveform Figure 4 Changes on b. In addition, EEG waveform 3 and heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 b can also share a common timeline to facilitate comparison among the three.

[0215] In some embodiments, the EEG waveform 3 and heart rate waveform can be used. Figure 4 a. Blood oxygen waveform Figure 4b. Display side by side (e.g., the three are arranged vertically or horizontally, in this embodiment, the three are arranged vertically). After the side by side display, if the same time on the time axis of each graph is connected by a line, then the lines will be parallel to each other. This makes it easier for medical staff to observe and helps them to focus more on the analysis of information.

[0216] Similarly, to facilitate the display of EEG waveform 3 and heart rate waveform... Figure 4 a. Blood oxygen waveform Figure 4 The reference and comparison for b can be used to label the EEG parameter waveform 3 and the heart rate waveform respectively. Figure 4 a. Blood oxygen waveform Figure 4 b. A portion at the same time or within a time period. For example, it can be marked using boxes, arrows, marker lines, symbols, text, etc. Figure 4 or Figure 5 In the middle, the EEG waveform 3 and the heart rate waveform Figure 4 a. Blood oxygen waveform Figure 4 Not only are the three waveforms (b, 3, and 4) displayed side-by-side, but the line connecting their respective time axes at the same point in time is a vertical marker line (e). This marker line (e) can be used as a marker to correlate with the EEG waveform (3), heart rate waveform, and other parameters. Figure 4 a. Blood oxygen waveform Figure 4 b intersects.

[0217] The aforementioned marker is a dynamic marker, capable of responding to a second user input command and changing its position on the EEG waveform 3. When the marker position on the EEG waveform 3 changes, the heart rate waveform... Figure 4 a and blood oxygen waveform Figure 4 The position of the marker on 'b' also changes accordingly to maintain consistency in the time or time period it points to. For example, in Figure 4 In the process, users can move the marker line e using the mouse cursor, thereby simultaneously changing the relationship between marker line e and the EEG waveform 3 and heart rate waveform. Figure 4 a. Blood oxygen waveform Figure 4 The location where b intersects. Other operations on the marker include, but are not limited to, gesture input commands, manual dragging, or clicking the marker.

[0218] In some embodiments, such as Figure 10 As shown, after steps 100 and 200, the following may also be included:

[0219] Step 300-2: Generate real-time EEG parameter waveforms based on the first monitoring data of EEG parameters.

[0220] Step 400-2: Generate a real-time waveform diagram of at least one other monitoring parameter based on the second monitoring data.

[0221] Step 500-2: Simultaneously display the real-time EEG parameter waveform 5 and the real-time waveform diagrams of other monitoring parameters.

[0222] Taking heart rate and blood oxygen as monitoring parameters as an example, users can observe the changes in real-time EEG waveform 5 and real-time blood oxygen waveform at the same time. Figure 6 b and real-time heart rate waveform Figure 6 The change of 'a'.

[0223] like Figure 6 As shown, the real-time EEG parameter waveform 5 and the real-time heart rate waveform are displayed. Figure 6 a and real-time blood oxygen waveform Figure 6 b. During the simultaneous display, the real-time heart rate waveform can be shown. Figure 6 a's paper feed speed and real-time blood oxygen waveform Figure 6 The paper feed speed of b is adjusted to match the paper feed speed of the real-time EEG parameter waveform 5. For example, if the paper feed speed of the real-time EEG parameter waveform 5 is 6 cm / h, it means that any point on the real-time EEG parameter waveform 5 will travel 6 cm on the display screen after one hour. Thus, a real-time heart rate waveform with a paper feed speed of 6 cm / h is generated. Figure 6 a and real-time blood oxygen waveform Figure 6 b.

[0224] By real-time heart rate waveform Figure 6 a and real-time blood oxygen waveform Figure 6 The paper feed speed of b is adjusted to match the paper feed speed of the real-time EEG parameter waveform 5, so that the real-time heart rate waveform... Figure 6 a. Real-time blood oxygen waveform Figure 6 b and the real-time EEG parameter waveform 5 remain relatively stationary, allowing users to easily compare the changes in the three waveforms at the same time. In other embodiments, the real-time EEG parameter waveform 5 and the real-time heart rate waveform... Figure 6 a and real-time blood oxygen waveform Figure 6 The paper feed speed of b can also be inconsistent. For example, displaying real-time EEG parameter waveforms from the current time to 10 seconds prior to the current time, or displaying real-time heart rate waveforms from the current time to 20 seconds prior to the current time. Figure 6 a and real-time blood oxygen waveform Figure 6 b, and real-time heart rate waveform Figure 6 a's paper feed speed and real-time blood oxygen waveform Figure 6 The paper feed speed of b is twice that of the real-time EEG parameter waveform 5.

[0225] As can be seen from the above, what can be shown to the user can at least include: amplitude-integrated EEG data from the first monitoring period. Figure 1The trend graphs of monitoring parameters in the second monitoring period, the waveforms of EEG parameters in the third monitoring period, the waveforms of monitoring parameters in the fourth monitoring period, the real-time EEG waveforms, and the real-time waveforms of monitoring parameters can be combined in two main ways. In the first type of combination, the amplitude integrated EEG data from the first monitoring period... Figure 1 It can be displayed simultaneously with at least one of the following for comparison: the trend graph of monitoring parameters in the second monitoring period, the waveform of EEG parameters in the third monitoring period (3), and the waveform of monitoring parameters in the fourth monitoring period. In the second type of combination, the real-time EEG waveform (5) and the real-time waveform of monitoring parameters are displayed simultaneously. The first and second types of combinations can also be displayed simultaneously. Furthermore, the time axis of the monitoring parameter trend graph can be integrated with the EEG waveform based on amplitude. Figure 1 The timeline is generated, thereby compressing the trend graph of the monitoring parameters into an EEG integrated with amplitude. Figure 1 Synchronous display facilitates comparison and reference. The time axis of the waveform of the monitoring parameters can be generated based on the time axis of the EEG parameter waveform 3, which also facilitates comparison and reference.

[0226] like Figure 7 The diagram shows an interface where the first and second types of combinations are displayed simultaneously in one embodiment. The display interface is divided into a first display area x, a second display area y, and a third display area z, and the amplitude-integrated EEG data for the first monitoring period is shown. Figure 1 At the point where the first display area x and the second display area y overlap, the first display area x also displays a trend graph of the monitoring parameters for the second monitoring period, while the second display area y also includes a vital information display area m, in which the EEG parameter waveform 3 for the third monitoring period and the real-time waveform graph of the monitoring parameters for the fourth monitoring period are displayed, and the third display area z displays the real-time EEG parameter waveform 5 and the real-time waveform graph of the monitoring parameters.

[0227] Figure 7 The illustrated embodiment is an example where all information is concentrated on the display interface. In other embodiments, the figures may also pop up or hide based on user operation commands.

[0228] In some embodiments, such as Figure 11 As shown, step 400 is followed by:

[0229] Step 500-3: Obtain amplitude-integrated EEG Figure 1 An unusual moment.

[0230] For example, this abnormal moment could be an amplitude-integrated EEG. Figure 1 The appearance of a "gap" in the data may be due to amplitude integration of EEG. Figure 1 The moment when the magnitude of change increases rapidly.

[0231] Step 600-3: Obtain the change characteristics of at least one other monitoring parameter on the trend graph at the time of the anomaly. These change characteristics can be obtained by calculating parameters such as the first derivative and second derivative of the trend graph.

[0232] Step 700-3: Based on the change characteristics on the trend graph of at least one other monitoring parameter, determine whether an abnormal EEG event has occurred. If an abnormal EEG event has occurred, proceed to step 800-3; otherwise, continue to step 500-3.

[0233] If the amplitude is integrated with EEG Figure 1 If, at an abnormal moment, the trend graph of the monitoring parameters changes accordingly, then it can be determined that an abnormal EEG event has occurred.

[0234] Step 800-3: Display alarm information associated with abnormal EEG events.

[0235] The above methods can automatically identify abnormal EEG events and output corresponding alarm information to a certain extent, thereby greatly reducing the workload of medical staff.

[0236] After issuing an alarm, medical staff typically take certain measures or methods to treat the patient, such as medication. If the monitoring system only alarms when an abnormal EEG occurs, it is insufficient to assist medical staff in the entire process of monitoring the patient. Therefore, in some embodiments, such as... Figure 11 As shown, it also includes:

[0237] Step 900-3: Obtain the first moment used to characterize the treatment and / or medication administered to the patient.

[0238] The first moment can be obtained manually by the user, such as when a patient is treated with medication or a medical device, the medical staff manually enters the treatment or medication time. Alternatively, it can be obtained by the monitoring system recording the status of the medical device when it is connected to the medical device. For example, when the monitoring system is connected to the infusion pump, after the infusion pump completes the injection treatment for the user, it sends a message to the monitoring system that the injection operation is complete. The monitoring system can use the moment when it receives this message as the first moment.

[0239] Step 1000-3: Obtain the alarm load within the first preset time period before the first moment.

[0240] Step 1100-3: Obtain the alarm load within the second preset time period after the first moment.

[0241] The first preset time period and the second preset time period are of the same or approximately the same length. The alarm load is used to characterize the severity of the patient's abnormal EEG events. The alarm load may include, but is not limited to, the number of alarms within the preset time period and / or the total alarm duration corresponding to the same type of abnormal EEG events.

[0242] Step 1200-3: Compare the alarm load within the first preset time period and the second preset time period to obtain comparison information used to characterize the treatment effect.

[0243] Taking alarm load as the alarm count as an example, the number of alarms in the first 5 hours and the last 5 hours can be recorded. If the number of alarms in the last 5 hours decreases significantly, it can prove that the treatment is effective. The degree of decrease in the number of alarms can further assess the effectiveness of the treatment.

[0244] Step 1300-3: Output comparison information to provide feedback on treatment effectiveness.

[0245] The comparison information can be presented in the form of text, images, tables, or videos. In some embodiments, the alarm load can be quantitatively integrated with the amplitude of the EEG in the form of a load chart. Figure 1 The presentation is combined; for example, the load chart is a statistical histogram. Each bar in the histogram represents the total alarm duration corresponding to a type of EEG abnormality. Furthermore, the same type of EEG abnormality has two corresponding bars, which respectively represent the total duration of the time before and after treatment. Users can intuitively see the changes in alarm load before and after treatment through this load chart.

[0246] The above embodiments can simultaneously display at least one of the following: amplitude-integrated EEG and monitoring parameter trend graphs, EEG near the desired time point or time period, and waveform graphs of monitoring parameters. This allows for a more accurate assessment of the patient's brain condition. Furthermore, it can automatically identify and trigger alarms for abnormal EEG events, significantly assisting users in clinical practice. Moreover, the monitoring system can be used in conjunction with other devices to provide more assessment options for clinical practice. For example, it can acquire physiological data of at least one other physiological parameter besides monitoring parameters, such as using ultrasound equipment to obtain physiological data. A trend graph can then be generated based on this physiological data, and finally, the amplitude-integrated EEG... Figure 1 The trend chart is displayed simultaneously. During this process, the physiological data and initial monitoring data of EEG parameters acquired by the ultrasound equipment can be obtained in different time periods.

[0247] Those skilled in the art will understand that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in a server, another computer, disk, optical disk, flash drive, or external hard drive, etc., and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be achieved.

[0248] The above examples illustrate the present invention and are only intended to aid in understanding the invention, not to limit it. Those skilled in the art can make variations to the specific embodiments described above based on the spirit of the invention.

Claims

1. A monitoring system, characterized in that, include: monitor; Processor, used for: Acquire first monitoring data of the patient's electroencephalogram (EEG) parameters during a first monitoring period, and acquire second monitoring data of the patient's at least one other monitoring parameter besides the EEG parameters during a second monitoring period, wherein the first monitoring period and the second monitoring period at least partially overlap. An amplitude integrated EEG for the first monitoring period is generated based on the first monitoring data, and a trend chart of the at least one other monitoring parameter is generated based on the second monitoring data. The display is controlled to simultaneously display the amplitude integrated EEG and the trend graphs of other monitoring parameters; wherein the time axis of the trend graph of the other monitoring parameters is generated according to the time axis of the amplitude integrated EEG, so as to compress the trend graph of the other monitoring parameters to be displayed synchronously with the amplitude integrated EEG.

2. The monitoring system as described in claim 1, characterized in that, The step of generating a trend chart for the at least one other monitoring parameter based on the second monitoring data includes: The processor acquires the duration represented by the first unit scale on the first time axis of the amplitude-integrated electroencephalogram; The processor determines the second time axis of the trend graph to be generated based on the duration represented by the first unit scale on the first time axis of the amplitude integrated EEG, wherein the duration represented by the second unit scale on the second time axis of the trend graph is the same as the duration represented by the first unit scale on the first time axis of the amplitude integrated EEG. The processor generates a trend chart for the at least one other monitoring parameter based on the second monitoring data and the second time axis of the trend chart.

3. The monitoring system as described in claim 1 or 2, characterized in that, The processor is also used for: The display is controlled to mark portions of the amplitude-integrated EEG and the trend graph at the same moment or within a time period, respectively. Upon receiving the first operation command input by the user, the system controls the display to synchronously change the position of the amplitude integrated EEG marker and the position of the trend graph marker.

4. The monitoring system as described in claim 1, characterized in that, The processor is also used for: Based on the user's selection instruction for the reference time point or reference time period input of the amplitude integrated EEG, a third monitoring period is determined, which includes the reference time point or reference time period selected by the user, and the third monitoring period is included in the first monitoring period; Based on the first monitoring data corresponding to the third monitoring period, generate the EEG parameter waveform for the third monitoring period; The display is controlled to show the EEG parameter waveforms of the third monitoring period.

5. The monitoring system as described in claim 4, characterized in that, The control of the display to show the EEG parameter waveforms of the third monitoring period includes: The processor controls the display to simultaneously show the amplitude-integrated EEG and the physiological information display area, and displays the EEG parameter waveforms of the third monitoring period within the physiological information display area; or In response to the user's input selection command, the processor controls the display to pop up a sub-window that further displays the EEG parameter waveforms. The sub-window is at least partially superimposed on the amplitude integrated EEG, or displayed independently of the amplitude integrated EEG.

6. The monitoring system as described in claim 4 or 5, characterized in that, The processor is also used for: Based on the selection instruction input by the user, a fourth monitoring period is determined, which includes the reference time point or reference time period, and the fourth monitoring period is included within the second monitoring period; Based on the second monitoring data corresponding to the fourth monitoring period, generate a waveform diagram of the at least one other monitoring parameter; The display is controlled to simultaneously display the waveforms of the EEG parameters and the waveforms of at least one other monitoring parameter.

7. The monitoring system as described in claim 6, characterized in that, The step of generating a waveform diagram of the at least one other monitoring parameter based on the second monitoring data corresponding to the fourth monitoring period includes: The processor acquires the duration represented by the third unit scale on the third time axis of the EEG parameter waveform; The processor determines the fourth time axis of the waveform to be generated based on the duration represented by the third unit scale on the third time axis of the EEG parameter waveform, wherein the duration represented by the fourth unit scale on the fourth time axis of the waveform is the same as the duration represented by the third unit scale on the third time axis of the EEG parameter waveform. The waveform is generated based on the second monitoring data corresponding to the fourth monitoring period and the fourth time axis of the waveform.

8. The monitoring system as described in claim 6, characterized in that, The processor is also used for: The display is controlled to mark the EEG parameter waveform and a portion of the waveform at the same moment or within a time period, respectively. When a second operation command is received from the user, the display is controlled to synchronously change the position of the waveform markers for the EEG parameters and the position of the waveform markers.

9. The monitoring system as described in claim 1, characterized in that, The processor is also used for: Obtain the abnormal moments of the amplitude-integrated EEG; Obtain the change characteristics on the trend graph at the abnormal moment; Based on the changing characteristics on the trend graph, determine whether an abnormal EEG event has occurred; If an abnormal EEG event occurs, the display is controlled to show alarm information associated with the abnormal EEG event.

10. The monitoring system as described in claim 9, characterized in that, After displaying the alarm information, the processor is further configured to: Acquire the first moment used to characterize the treatment and / or medication administered to the patient; Obtain the alarm load within the first preset time period before the first moment; Obtain the alarm load within a second preset time period after the first moment; The alarm load is the number of alarms corresponding to the same type of abnormal EEG events and / or the total alarm duration corresponding to the same type of abnormal EEG events. The alarm load within the first preset time period and the second preset time period are compared to obtain comparison information used to characterize the treatment effect. The comparison information is output to provide feedback on the treatment effect.

11. The monitoring system as described in claim 1, characterized in that, The trend graphs of the at least one other monitoring parameter include at least one of the following: heart rate trend graph, pulse rate trend graph, blood oxygen trend graph, non-invasive blood pressure trend graph, invasive blood pressure trend graph, respiration trend graph, body temperature trend graph, stroke volume trend graph, cardiac output trend graph, blood glucose trend graph, brain oxygenation trend graph, and urine output trend graph.

12. The monitoring system as described in claim 1, characterized in that, It also includes a data acquisition device for acquiring first monitoring data of the patient's electroencephalogram (EEG) parameters and second monitoring data of at least one other monitoring parameter besides the EEG parameters.

13. The monitoring system as described in claim 12, characterized in that, The acquisition device is a signal sensor or a communication module used to acquire data from a remote device.

14. The monitoring system as described in claim 1, characterized in that, The monitoring system includes at least one of a monitor, a local central station, a remote central station, a cloud service system, and a mobile terminal.

15. The monitoring system as described in claim 1, characterized in that, The monitoring parameters, in addition to EEG parameters, include at least one of the following: heart rate, blood oxygen, pulse, body temperature, brain oxygen, blood glucose, and blood pressure.

16. A monitoring system, characterized in that, include: monitor; Processor, used for: Acquire the first monitoring data of the patient's EEG parameters during the first monitoring period, and acquire the second monitoring data of the patient's at least one other monitoring parameter besides the EEG parameters during the second monitoring period; An amplitude integrated EEG for the first monitoring period is generated based on the first monitoring data, and a trend chart of the at least one other monitoring parameter is generated based on the second monitoring data. The display is controlled to show the trend graphs of the amplitude integrated EEG and other monitoring parameters; wherein the time axis of the trend graphs of the other monitoring parameters is generated according to the time axis of the amplitude integrated EEG, so as to compress the trend graphs of the other monitoring parameters to be displayed synchronously with the amplitude integrated EEG; Based on the user's selection instruction for the reference time point or reference time period input of the amplitude integrated EEG, a third monitoring period is determined, which includes the reference time point or reference time period selected by the user, and the third monitoring period is included in the first monitoring period; Based on the first monitoring data corresponding to the third monitoring period, generate the EEG parameter waveform for the third monitoring period; The display is controlled to show the EEG parameter waveforms while simultaneously displaying the amplitude-integrated EEG.

17. The monitoring system as described in claim 16, characterized in that, The control of the display to show the EEG parameter waveforms of the third monitoring period includes: The processor controls the display to simultaneously show the amplitude-integrated EEG and the physiological information display area, and displays the EEG parameter waveforms of the third monitoring period within the physiological information display area; or In response to the user's input selection command, the processor controls the display to pop up a sub-window that further displays the EEG parameter waveforms. The sub-window is at least partially superimposed on the amplitude integrated EEG, or displayed independently of the amplitude integrated EEG.

18. The monitoring system as described in claim 16 or 17, characterized in that, The processor is also used for: Based on the selection instruction input by the user, a fourth monitoring period is determined, which includes the reference time point or reference time period, and the fourth monitoring period is included within the second monitoring period; Based on the second monitoring data corresponding to the fourth monitoring period, generate a waveform diagram of the at least one other monitoring parameter; The display is controlled to simultaneously show the EEG parameter waveform and the waveform diagram.

19. The monitoring system as described in claim 18, characterized in that, The step of generating a waveform diagram of the at least one other monitoring parameter based on the second monitoring data corresponding to the fourth monitoring period includes: The processor acquires the duration represented by the third unit scale on the third time axis of the EEG parameter waveform; The processor determines the fourth time axis of the waveform to be generated based on the duration represented by the third unit scale on the third time axis of the EEG parameter waveform, wherein the duration represented by the fourth unit scale on the fourth time axis of the waveform is the same as the duration represented by the third unit scale on the third time axis of the EEG parameter waveform. The waveform is generated based on the second monitoring data corresponding to the fourth monitoring period and the fourth time axis of the waveform.

20. The monitoring system as described in claim 18, characterized in that, The processor is also used for: The display is controlled to mark the EEG parameter waveform and a portion of the waveform at the same moment or within a time period, respectively. When a second operation command is received from the user, the display is controlled to synchronously change the position of the waveform markers for the EEG parameters and the position of the waveform markers.

21. The monitoring system as described in claim 16, characterized in that, It also includes a data acquisition device for acquiring first monitoring data of the patient's electroencephalogram (EEG) parameters and second monitoring data of at least one other monitoring parameter besides the EEG parameters.

22. The monitoring system as described in claim 21, characterized in that, The acquisition device is a signal sensor or a communication module used to acquire data from a remote device.

23. The monitoring system as described in claim 16, characterized in that, The monitoring system includes at least one of a monitor, a local central station, a remote central station, a cloud service system, and a mobile terminal.

24. The monitoring system as described in claim 16, characterized in that, The monitoring parameters, in addition to EEG parameters, include at least one of the following: heart rate, blood oxygen, pulse, body temperature, brain oxygen, blood glucose, and blood pressure.

25. A monitoring system, characterized in that, include: monitor; Processor, used for: Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters; An amplitude-integrated electroencephalogram (EEG) is generated based on the first monitoring data; Acquire physiological data of at least one other physiological parameter of the patient in addition to monitoring parameters, wherein the monitoring parameters include the electroencephalogram (EEG) parameters; Based on the physiological data, generate a trend graph for at least one other physiological parameter; The display is controlled to simultaneously display the amplitude-integrated EEG and trend graphs of the other physiological parameters; wherein the time axis of the trend graph of the other physiological parameters is generated according to the time axis of the amplitude-integrated EEG, so as to compress the trend graph of the other physiological parameters to be displayed synchronously with the amplitude-integrated EEG.

26. The monitoring system as described in claim 25, characterized in that, In addition to the monitoring parameters, at least one other physiological parameter includes cerebral blood flow parameters obtained by ultrasound equipment.

27. The monitoring system as described in claim 25, characterized in that, It also includes a data acquisition device for acquiring first monitoring data of the patient's electroencephalogram (EEG) parameters and second monitoring data of at least one other monitoring parameter besides the EEG parameters.

28. The monitoring system as described in claim 27, characterized in that, The acquisition device is a signal sensor or a communication module used to acquire data from a remote device.

29. The monitoring system as described in claim 25, characterized in that, The monitoring system includes at least one of a monitor, a local central station, a remote central station, a cloud service system, and a mobile terminal.

30. The monitoring system as described in claim 27, characterized in that, The monitoring parameters, in addition to EEG parameters, include at least one of the following: heart rate, blood oxygen, pulse, body temperature, brain oxygen, blood glucose, and blood pressure.

31. A monitoring system, characterized in that, include: monitor; Processor, used for: Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period; An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data, and real-time EEG parameter waveforms are also obtained. Acquire second monitoring data of at least one monitoring parameter other than EEG parameters during the second monitoring period; the first monitoring period and the second monitoring period at least partially overlap. Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated, and a real-time waveform chart of the at least one other monitoring parameter is also generated; The display is controlled to simultaneously display the trend graphs of the amplitude integrated EEG and the other monitoring parameters, as well as the real-time waveforms of the EEG parameters and the real-time waveforms of the other monitoring parameters; wherein the time axis of the trend graph of the other monitoring parameters is generated according to the time axis of the amplitude integrated EEG, so as to compress the trend graph of the other monitoring parameters to be displayed synchronously with the amplitude integrated EEG.

32. The monitoring system as described in claim 31, characterized in that, Based on the second monitoring data, a real-time waveform diagram of the at least one other monitoring parameter is generated, including: The paper feed speed of the real-time EEG parameter waveform is obtained, and the paper feed speed is used to characterize the moving speed of the real-time EEG parameter waveform. The paper feed speed of the real-time EEG parameter waveform is used as the paper feed speed of the real-time waveform diagram to be generated. The real-time waveform is generated based on the second monitoring data and the paper feed speed of the real-time waveform.

33. The monitoring system as described in claim 31, characterized in that, It also includes a data acquisition device for acquiring first monitoring data of the patient's electroencephalogram (EEG) parameters and second monitoring data of at least one other monitoring parameter besides the EEG parameters.

34. The monitoring system as described in claim 33, characterized in that, The acquisition device is a signal sensor or a communication module used to acquire data from a remote device.

35. The monitoring system as described in claim 31, characterized in that, The monitoring system includes at least one of a monitor, a local central station, a remote central station, a cloud service system, and a mobile terminal.

36. The monitoring system as described in claim 31, characterized in that, The monitoring parameters, in addition to EEG parameters, include at least one of the following: heart rate, blood oxygen, pulse, body temperature, brain oxygen, blood glucose, and blood pressure.

37. A method for displaying monitoring information, characterized in that, include: Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period; Acquire second monitoring data of at least one monitoring parameter other than EEG parameters during the second monitoring period, wherein the first monitoring period and the second monitoring period at least partially overlap. An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data; Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated; Simultaneously displaying the trend graphs of the amplitude integrated EEG and the other monitoring parameters; wherein, the time axis of the trend graph of the other monitoring parameters is generated according to the time axis of the amplitude integrated EEG, so as to compress the trend graph of the other monitoring parameters to be displayed synchronously with the amplitude integrated EEG.

38. A method for displaying monitoring information, characterized in that, include: Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period; Acquire secondary monitoring data of at least one monitoring parameter other than EEG parameters during the second monitoring period; An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data; Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated; The trend graphs of the amplitude-integrated EEG and the other monitoring parameters are displayed; wherein the time axis of the trend graphs of the other monitoring parameters is generated based on the time axis of the amplitude-integrated EEG, so as to compress the trend graphs of the other monitoring parameters to be displayed synchronously with the amplitude-integrated EEG; Based on the user's selection instruction for the reference time point or reference time period input of the amplitude integrated EEG, a third monitoring period is determined, which includes the reference time point or reference time period selected by the user, and the third monitoring period is included in the first monitoring period; Based on the first monitoring data corresponding to the third monitoring period, generate the EEG parameter waveform for the third monitoring period; The waveforms of the EEG parameters are displayed simultaneously with the amplitude-integrated EEG.

39. A method for displaying monitoring information, characterized in that, include: Acquire the patient's initial monitoring data of electroencephalogram (EEG) parameters; An amplitude-integrated electroencephalogram (EEG) is generated based on the first monitoring data; Acquire physiological data of at least one other physiological parameter of the patient in addition to monitoring parameters, wherein the monitoring parameters include the electroencephalogram (EEG) parameters; Based on the physiological data, generate a trend graph for at least one other physiological parameter; Simultaneously displaying the trend graphs of the amplitude-integrated EEG and the other physiological parameters; wherein, the time axis of the trend graphs of the other physiological parameters is generated based on the time axis of the amplitude-integrated EEG, so as to compress the trend graphs of the other physiological parameters to be displayed synchronously with the amplitude-integrated EEG.

40. A method for displaying monitoring information, characterized in that, include: Acquire the first monitoring data of the patient's electroencephalogram (EEG) parameters during the first monitoring period; An amplitude-integrated electroencephalogram (EEG) for the first monitoring period is generated based on the first monitoring data, and real-time EEG parameter waveforms are also obtained. Acquire second monitoring data of at least one monitoring parameter other than EEG parameters during the second monitoring period; the first monitoring period and the second monitoring period at least partially overlap. Based on the second monitoring data, a trend chart of the at least one other monitoring parameter is generated, and a real-time waveform chart of the at least one other monitoring parameter is also generated; Simultaneously displaying the trend graphs of the amplitude integrated EEG and the other monitoring parameters, and simultaneously displaying the real-time EEG waveforms and the real-time waveforms of the other monitoring parameters; wherein, the time axis of the trend graph of the other monitoring parameters is generated according to the time axis of the amplitude integrated EEG, so as to compress the trend graph of the other monitoring parameters to be displayed synchronously with the amplitude integrated EEG.

41. A monitoring system, characterized in that, include: Memory, used to store programs; A processor for implementing the method as described in any one of claims 37-40 by executing a program stored in the memory.

42. A computer-readable storage medium, characterized in that, The medium stores a program that can be executed by a processor to implement the method as described in any one of claims 37-40.

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