A nociceptive perception monitoring method based on short-time scatter plot

Abstract

The application discloses a kind of based on short time scatter diagram's nociceptive monitoring method, belong to biomedical signal processing technical field, to solve the problems of long existing HRV scatter diagram analysis window, poor real-time, low system integration, weak anti-interference ability, insufficient clinical practicability, including multimodal biosignal acquisition, central processing and main control, RR interval sequence preprocessing, short time scatter diagram construction and feature extraction, nociceptive real-time evaluation and man-machine interaction and communication six big core steps, short time RR interval sequence is constructed using 100 seconds sliding window, scatter diagram is drawn and extracts SD1, SD2 core characteristic parameter, completes autonomic nervous activity determination and nociceptive quantification grading monitoring, the application significantly improves monitoring real-time and accuracy, constructs whole-process closed-loop monitoring architecture, can be widely adapted to perioperative anesthesia monitoring and other clinical scenes, has important clinical application value.

Description

Technical Field

[0001] This invention relates to the field of biomedical signal processing technology, and more specifically, to a nociceptive monitoring method based on short-time scatter plots. Background Technology

[0002] Heart rate variability (HRV) analysis is an internationally recognized core method for non-invasive and objective evaluation of autonomic nervous system activity. By analyzing the dynamic changes between consecutive heartbeats, it can accurately reflect the tension balance between the sympathetic and parasympathetic nervous systems. When the human body is subjected to noxious stimuli, the central nervous system triggers an autonomic nervous stress response centered on sympathetic nerve excitation. This process is not under conscious control, therefore, HRV analysis can be used to achieve an objective quantitative evaluation of noxious perception.

[0003] Among the methods for analyzing heart rate variability (HRV), scatter plot analysis (also known as Poincaré plot) has the advantages of being intuitive, visual, and highly resistant to interference. It can directly present the nonlinear variation law of heart rate variability through the distribution characteristics of a two-dimensional graph. However, in current technologies, HRV scatter plot analysis is generally based on 24-hour Holter monitoring or at least 5 minutes of continuous ECG signals. The analysis window is too long, and the data processing latency is high, which cannot meet the real-time monitoring needs of autonomic nervous activity and nociceptive perception in perioperative, intensive care, and other scenarios.

[0004] In recent years, short-time HRV analysis has gradually become a research hotspot, but existing related technologies still have many shortcomings: Firstly, existing short-term HRV analysis methods are mostly based on single algorithms and lack an integrated hardware system that integrates signal acquisition, preprocessing, analysis and calculation, and result output. In clinical applications, multiple devices are required, resulting in low integration, cumbersome deployment, and poor anti-interference capabilities. Secondly, the existing short-term HRV monitoring system has a separate signal acquisition module and analysis module, resulting in high data transmission latency and making it impossible to achieve continuous real-time analysis using a sliding window approach. Third, existing short-time scatter plot analysis methods are not robust enough to abnormal ECG signals, lack a complete RR interval cleaning and quality control process, and are easily affected by factors such as noise and arrhythmia, resulting in insufficient accuracy of monitoring results. Fourth, the existing system cannot achieve a closed-loop process from signal acquisition to nociceptive perception grading assessment. The output results are only scatter plots and basic parameters, which cannot provide clinicians with an intuitive assessment of nociceptive perception status, thus limiting its clinical applicability.

[0005] Therefore, developing a monitoring method that integrates multi-module biosignal acquisition, enables real-time analysis of short-term scatter plots at the 100-second level, and has full-process closed-loop processing capabilities has significant clinical value and application prospects for preoperative assessment of perioperative patients, precise control of intraoperative anesthetic medication, surgical safety assurance, and quantitative evaluation of rapid postoperative recovery. Summary of the Invention

[0006] To overcome the above-mentioned deficiencies of the prior art, embodiments of the present invention provide a harm perception monitoring method based on short-time scatter plots.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A nociception monitoring method based on short-time scatter plots includes: Multimodal biosignal acquisition is used to acquire the raw electrocardiogram (ECG) signals of the subject, and to amplify, filter and convert the signals to digital, and output digital ECG signals to the central processing and main control module. The central processing and control unit is used to schedule the collaborative work of various modules, complete the reception, storage, processing and instruction distribution of ECG data; RR interval sequence preprocessing is used to identify R waves, calculate RR intervals, construct sliding window sequences and clean outliers from digital electrocardiogram signals, and output short RR interval sequences that pass quality control. The short-time scatter plot construction and feature extraction module is used to construct a 100-second short-time scatter plot based on the short-time RR interval sequence and extract the quantized feature parameters of the scatter plot; Real-time assessment of nociception is used to determine the state of autonomic nervous activity and to quantitatively grade the level of nociception based on extracted feature parameters, and to output monitoring results and early warning signals. Human-computer interaction and communication are used to realize the real-time display of monitoring data, user operation interaction, and data transmission.

[0008] Specifically, multimodal biosignal acquisition uses medical-grade Ag / AgCl surface electrodes to acquire raw electrocardiogram signals in standard lead II mode; It consists of a cascaded instrumentation amplifier circuit, a high-pass filter circuit, a low-pass filter circuit, and a power frequency notch filter circuit, and is used to amplify and denoise the raw electrocardiogram signal. It uses a 12-bit or higher ADC chip with an adjustable sampling rate of 250Hz~1000Hz to convert analog ECG signals into digital ECG signals.

[0009] Specifically, the RR interval sequence preprocessing uses the improved Pan-Tompkins algorithm to identify the R wave in the electrocardiogram signal and mark the time position of the R wave; Calculate the time interval between adjacent R waves to generate a continuous raw sequence of RR intervals; A fixed sliding window with a width of 100 seconds is used to slide and truncate the continuous RR interval sequence with a step size of 1 second to construct a short-time RR interval sequence that is updated in real time. The system employs a dual cleaning logic that combines physiological thresholds and statistical rules. First, it removes RR intervals outside the physiological threshold of 300ms to 2000ms. Then, it removes outliers using the quartile method and interpolates abnormal RR intervals to correct them, outputting a short-term RR interval sequence that meets quality control standards.

[0010] Specifically, the construction and feature extraction of the short-time scatter plot are performed by plotting scatter points in a two-dimensional rectangular coordinate system with the nth RR interval RRn in the short-time RR interval sequence as the x-axis and the (n+1)th RR interval RRn+1 as the y-axis, thus completing the construction of the 100-second short-time scatter plot. Extract the core feature parameters of the scatter plot, including the standard deviation of the minor axis SD1, the standard deviation of the major axis SD2, and the SD1 / SD2 ratio.

[0011] Specifically, real-time assessment of nociceptive function is based on the dynamic changes in SD1, SD2 and the SD1 / SD2 ratio to determine the tension state of the sympathetic and parasympathetic nervous systems in real time. The system presets clinical grading thresholds, classifying nociceptive states into four levels: 0, 1, 2, and 3. When a nociceptive state reaches level 2 or above, an audio-visual warning is automatically triggered.

[0012] Specifically, the formula for calculating SD1 is: ; The formula for calculating SD2 is: ; Var is the variance calculation function.

[0013] Specifically, determine the tension state of the sympathetic and parasympathetic nervous systems; Based on the dynamic changes of SD1, SD2 and the SD1 / SD2 ratio, the autonomic nervous activity state of the tested subject is determined in real time. When SD2 is higher than the preset threshold, SD1 is lower than the preset threshold, and the SD1 / SD2 ratio decreases to less than the set threshold ratio, it is determined to be sympathetic nerve excitation and parasympathetic nerve inhibition, corresponding to the autonomic nervous stress response triggered by noxious stimuli.

[0014] Specifically, the human-computer interaction includes an LCD touch module, a button module, and an audio-visual warning module, which are used for real-time display of monitoring data, user operation control, and warning prompts; The communication interface includes a network interface, a USB interface, and a wireless communication unit, which are used to realize the transmission of monitoring data, system firmware upgrades, and integration with the institute's information system.

[0015] The technical effects and advantages of this invention are as follows: This invention integrates functions such as biosignal acquisition, preprocessing, core computation, result output, and human-computer interaction to construct a closed-loop monitoring hardware architecture, solving the problems of separation of acquisition and analysis modules and cumbersome equipment deployment in existing technologies. The system adopts a medical-grade portable design and can be adapted to multiple application scenarios such as preoperative assessment, intraoperative bedside monitoring, and postoperative rehabilitation, making it highly clinically applicable. This invention adopts a sliding window analysis mode with a fixed width of 100 seconds and a step size of 1 second, which breaks through the limitation of the existing technology of analysis window of more than 5 minutes. It realizes the second-by-second update of monitoring results, can capture the instantaneous changes of autonomic nerve activity in real time, accurately reflect the stress response caused by noxious stimuli, and fully meet the needs of clinical scenarios with extremely high real-time requirements such as perioperative anesthesia monitoring. This invention establishes a dual RR interval quality control process based on physiological thresholds and statistical rules, which can effectively eliminate outliers caused by factors such as noise, arrhythmia, and baseline drift, ensuring the effectiveness of short-term scatter plot construction. At the same time, the signal acquisition uses multi-stage amplification and filtering circuits, which greatly improves the signal-to-noise ratio of weak ECG signals, ensuring the accuracy of the analysis results from the signal source. This invention not only enables real-time plotting and feature parameter extraction of short-term scatter plots, but also constructs a nociceptive perception grading assessment model based on clinical data. It can output quantitative nociceptive perception levels at different levels and includes an over-limit warning function, providing clinicians with intuitive and operable decision-making references rather than simply displaying graphics and parameters. This solves the problem of insufficient clinical applicability of existing technologies. Attached Figure Description

[0016] Figure 1 This is a flowchart of a harm perception monitoring method based on short-time scatter plots according to the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] like Figure 1 As shown, a harm perception monitoring method based on short-time scatter plots is as follows: Multimodal biosignal acquisition is used to acquire the raw electrocardiogram (ECG) signals of the subject, and to amplify, filter and convert the signals to digital, and output digital ECG signals to the central processing and main control. This includes bioelectric sensing, signal preprocessing, and high-precision analog-to-digital conversion; Bioelectric sensing: Medical-grade Ag / AgCl surface electrodes are used to attach to the chest surface of the subject to collect raw electrocardiogram (ECG) signals. The electrode configuration adopts the standard II lead method, which has the characteristics of high input impedance and low polarization voltage, and can effectively capture weak ECG signals in the millivolt range. Signal preprocessing: This consists of a cascaded instrumentation amplifier circuit, a high-pass filter circuit, a low-pass filter circuit, and a power frequency notch filter circuit. The instrumentation amplifier circuit uses a low-noise instrumentation amplifier to differentially amplify the raw ECG signal, with an adjustable amplification factor ranging from 500 to 1000 times. The high-pass filter circuit has a cutoff frequency of 0.05 Hz to filter out baseline drift interference. The low-pass filter circuit has a cutoff frequency of 100 Hz to filter out high-frequency electromyography interference. The power frequency notch filter circuit has a center frequency of 50 Hz to suppress power grid interference, ultimately outputting a preprocessed ECG signal with a high signal-to-noise ratio. High-precision analog-to-digital conversion: Using a 12-bit or higher high-precision ADC chip with an adjustable sampling rate of 250Hz~1000Hz, the pre-processed analog ECG signal is converted into a digital ECG signal and transmitted to the central processing and main control via the serial peripheral interface (SPI) to complete the entire signal acquisition process.

[0019] The central processing and control unit is used to schedule various collaborative tasks and complete the reception, storage, processing, and instruction distribution of ECG data. The STM32F103VCT6 microcontroller (MCU) is used as the main control chip. It has an integrated ARM Cortex-M3 core with a maximum operating frequency of 72MHz, providing ample computing resources and peripheral interfaces. It also has an embedded real-time operating system to schedule the working sequence of each component, complete the reception, storage, processing and instruction distribution of digital signals, and coordinate the synchronous operation of each component to ensure the real-time performance and stability of the system. It also has external high-capacity storage, including Flash memory and SRAM static random access memory. Flash memory is used to store system firmware, algorithm models and historical monitoring data, while SRAM is used for data caching during real-time calculations, ensuring fast read, write and processing of 100-second sliding window data.

[0020] RR interval sequence preprocessing is used to identify R waves, calculate RR intervals, construct sliding window sequences and clean outliers from digital electrocardiogram signals, and output short RR interval sequences that pass quality control. An improved Pan-Tompkins algorithm was used to locate the R-wave in digital electrocardiogram (ECG) signals. Through steps such as bandpass filtering, differentiation, squaring, and moving window integration, the characteristic peaks of the R-wave in the ECG signal were identified, and the time position of each R-wave was marked. Based on the marked R-wave time position, the time interval between two adjacent R waves, i.e. the RR interval, is calculated in milliseconds (ms), and a continuous raw sequence of RR intervals is generated. A fixed sliding window with a width of 100 seconds is used to slide and truncate the continuous RR interval sequence with a step size of 1 second to construct a short-time RR interval sequence that is updated in real time; the number of effective RR intervals in each sliding window is no less than 60 to ensure the effectiveness of the scatter plot construction. A dual cleaning logic based on physiological thresholds and statistical rules is set up. First, RR intervals exceeding the physiological threshold (300ms~2000ms) are removed. Then, outliers exceeding 1.5 times the interquartile range are removed using the quartile method. At the same time, abnormal RR intervals caused by premature beats and missed beats are corrected by interpolation. Finally, a short RR interval sequence with qualified quality control is output to avoid the interference of outliers on the scatter plot features.

[0021] Short-time scatter plot construction and feature extraction: This method is used to construct 100-second short-time scatter plots based on short-time RR interval sequences and extract the quantized feature parameters of the scatter plots. Based on the quality-controlled short-time RR interval series, the Poincaré plotting logic is adopted. The nth RR interval value RRn in the series is used as the x-axis, and the (n+1)th RR interval value RRn+1 is used as the y-axis. The corresponding scatter points are plotted in a two-dimensional rectangular coordinate system. All consecutive RR interval pairs in the series are traversed to complete the real-time plotting of the 100-second short-time scatter plot. The x-axis and y-axis ranges of the coordinate system are uniformly set to 300ms~2000ms to ensure the consistency and comparability of the scatter plot. For the constructed short-time scatter plot, quantized nonlinear feature parameters are extracted. The core parameters include the standard deviation of the scatter plot's minor axis (SD1), the standard deviation of the scatter plot's major axis (SD2), and the SD1 / SD2 ratio; where: The formula for calculating SD1 is: ; The formula for calculating SD2 is: ; Var is the variance calculation function; SD1 reflects instantaneous heart rate variability, corresponding to the tension level of the parasympathetic (vagus nerve); SD2 reflects long-term heart rate variability, corresponding to the tension level of the sympathetic nerve; the SD1 / SD2 ratio reflects the tension balance between the sympathetic and parasympathetic nerves.

[0022] Real-time assessment of nociception is used to determine the state of autonomic nervous activity and to quantitatively grade the level of nociception based on extracted feature parameters, and to output monitoring results and early warning signals. Based on the dynamic changes of SD1, SD2 and the SD1 / SD2 ratio, the autonomic nervous activity state of the tested subject is determined in real time. When SD2 is higher than the preset threshold, SD1 is lower than the preset threshold, and the SD1 / SD2 ratio decreases to less than the set threshold ratio, it is determined to be sympathetic nerve excitation and parasympathetic nerve inhibition, corresponding to the autonomic nervous stress response triggered by noxious stimuli. The system presets a threshold for grading nociception based on clinical data, classifying the nociception state of the tested subjects into four levels: Level 0 (no nociception, autonomic nervous system tension is balanced), Level 1 (mild nociception, mild sympathetic nervous system excitation), Level 2 (moderate nociception, moderate sympathetic nervous system excitation), and Level 3 (severe nociception, excessive sympathetic nervous system excitation), thereby achieving a quantitative grading output of nociception. When the level of nociception is detected to be 2 or above, an early warning is automatically triggered. The system outputs an audible and visual warning signal through human-computer interaction, providing real-time reference for clinicians in anesthesia administration and intervention procedures.

[0023] Human-computer interaction and communication are used to realize the real-time display of monitoring data, user operation interaction, and data transmission; It includes a medical-grade LCD touchscreen, buttons, and audible and visual alarms. The touchscreen displays real-time 100-second short-term scatter plot, SD1 / SD2 characteristic parameter curves, hazard perception level, real-time heart rate, and other monitoring data. It also allows users to set system parameters, control monitoring start / stop, and query historical data via the touchscreen. The buttons are physical backup operation interfaces that support emergency start / stop and rapid parameter adjustment. The audible and visual alarms provide warnings when hazard perception exceeds the limit. Communication interfaces include a network interface, a USB interface, and Bluetooth / WiFi wireless communication. The network interface supports system access to the hospital's local area network, enabling data exchange with the hospital's HIS / LIS system. The USB interface supports local data export, firmware upgrades, and external storage device connection. Wireless communication supports wireless data transmission with mobile monitoring devices, enabling remote monitoring.

[0024] The above formulas are all dimensionless calculations. Dimensionless calculations can be performed using various methods such as standardization, which will not be elaborated here. The formulas are derived from software simulations based on a large amount of collected data, and the preset parameters in the formulas can be set by those skilled in the art according to the actual situation.

[0025] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, ATA hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium can be a solid-state ATA hard disk.

[0026] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0027] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0028] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0029] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0030] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0031] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable ATA hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0032] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for monitoring nociception based on short-time scatter plots, characterized in that, include: Multimodal biosignal acquisition is used to acquire the raw electrocardiogram (ECG) signals of the subject, and to amplify, filter and convert the signals to digital, and output digital ECG signals to the central processing and main control module. The central processing and control unit is used to schedule the collaborative work of various modules, complete the reception, storage, processing and instruction distribution of ECG data; RR interval sequence preprocessing is used to identify R waves, calculate RR intervals, construct sliding window sequences and clean outliers from digital electrocardiogram signals, and output short RR interval sequences that pass quality control. The short-time scatter plot construction and feature extraction module is used to construct a 100-second short-time scatter plot based on the short-time RR interval sequence and extract the quantized feature parameters of the scatter plot; Real-time assessment of nociception is used to determine the state of autonomic nervous activity and to quantitatively grade the level of nociception based on extracted feature parameters, and to output monitoring results and early warning signals. Human-computer interaction and communication are used to realize the real-time display of monitoring data, user operation interaction, and data transmission.

2. The harm perception monitoring method based on short-time scatter plots according to claim 1, characterized in that: Multimodal biosignal acquisition uses medical-grade Ag / AgCl surface electrodes to acquire raw electrocardiogram signals in standard lead II mode; It consists of a cascaded instrumentation amplifier circuit, a high-pass filter circuit, a low-pass filter circuit, and a power frequency notch filter circuit, and is used to amplify and denoise the raw electrocardiogram signal. It uses a 12-bit or higher ADC chip with an adjustable sampling rate of 250Hz~1000Hz to convert analog ECG signals into digital ECG signals.

3. A harm perception monitoring method based on short-time scatter plots according to claim 2, characterized in that: The RR interval sequence preprocessing uses the improved Pan-Tompkins algorithm to identify the R wave in the electrocardiogram signal and mark the time position of the R wave; Calculate the time interval between adjacent R waves to generate a continuous raw sequence of RR intervals; A fixed sliding window with a width of 100 seconds is used to slide and truncate the continuous RR interval sequence with a step size of 1 second to construct a short-time RR interval sequence that is updated in real time. The system employs a dual cleaning logic that combines physiological thresholds and statistical rules. First, it removes RR intervals outside the physiological threshold of 300ms to 2000ms. Then, it removes outliers using the quartile method and interpolates abnormal RR intervals to correct them, outputting a short-term RR interval sequence that meets quality control standards.

4. A harm perception monitoring method based on short-time scatter plots according to claim 3, characterized in that: Short-time scatter plot construction and feature extraction: Using the nth RR interval RRn in the short-time RR interval sequence as the x-axis and the (n+1)th RR interval RRn+1 as the y-axis, scatter points are plotted in a two-dimensional rectangular coordinate system to complete the construction of a 100-second short-time scatter plot; Extract the core feature parameters of the scatter plot, including the standard deviation of the minor axis SD1, the standard deviation of the major axis SD2, and the SD1 / SD2 ratio.

5. A harm perception monitoring method based on short-time scatter plots according to claim 4, characterized in that: Real-time assessment of nociceptive function is based on the dynamic changes of SD1, SD2 and the SD1 / SD2 ratio to determine the tension state of the sympathetic and parasympathetic nervous systems in real time. Preset clinical grading thresholds to classify nociceptive states into four levels: level 0, level 1, level 2, and level 3; When the level of harm perception reaches level 2 or above, an audio-visual warning will be automatically triggered.

6. A harm perception monitoring method based on short-time scatter plots according to claim 4, characterized in that: The formula for calculating SD1 is: ; The formula for calculating SD2 is: ; Var is the variance calculation function.

7. A harm perception monitoring method based on short-time scatter plots according to claim 5, characterized in that: Determine the tension state of the sympathetic and parasympathetic nervous systems; Based on the dynamic changes of SD1, SD2 and the SD1 / SD2 ratio, the autonomic nervous activity state of the tested subject is determined in real time. When SD2 is higher than the preset threshold, SD1 is lower than the preset threshold, and the SD1 / SD2 ratio decreases to less than the set threshold ratio, it is determined to be sympathetic nerve excitation and parasympathetic nerve inhibition, corresponding to the autonomic nerve stress response triggered by noxious stimuli.

8. A harm perception monitoring method based on short-time scatter plots according to claim 1, characterized in that: Human-computer interaction includes an LCD touch module, a button module, and an audio-visual warning module, which are used for real-time display of monitoring data, user operation control, and warning prompts; The communication interface includes a network interface, a USB interface, and a wireless communication unit, which are used to realize the transmission of monitoring data, system firmware upgrades, and integration with the institute's information system.

Images