Rail transit risk personnel job suitability assessment method and device

Abstract

The application provides a rail transit risk personnel on-job ability evaluation method and device, the method comprises the following steps: collecting physiological signal data of the measured personnel in the resting stage and the task execution stage respectively, and aligning the physiological signal data with the task to obtain the aligned physiological signal parameters; extracting physiological characteristic parameters from the aligned physiological signal parameters, and calculating the change amplitude of the physiological characteristic parameters in the task execution stage relative to the resting stage; constructing a response index related to the task and the physiology according to the change amplitude and the fatigue accumulation rate of the measured personnel; and evaluating the on-job ability of the measured personnel according to the response index to obtain the on-job ability evaluation result. The method and device can represent the fatigue development trend and the change condition of the cognitive ability of the individual under the high-load task condition, and provide a basis for the on-job evaluation, shift management and safe operation of the rail transit risk personnel.

Description

Technical Field

[0001] This invention relates to the fields of rail transit operation safety, human factors engineering, and brain-computer interface technology, and particularly to a method and device for assessing the job suitability of personnel at risk in rail transit operations. Background Technology

[0002] The rail transit industry is characterized by high operational density, high safety levels, and high automation. Personnel in positions such as train dispatching, traffic control, signal monitoring, and driver operation need to maintain a high level of vigilance and continuous cognitive load during their work. To ensure operational safety, operating units typically conduct suitability assessments for relevant personnel before they start work or during shift scheduling.

[0003] In recent years, brain-computer interface (BCI) technology, by collecting and analyzing electroencephalogram (EEG) signals, can objectively reflect a person's cognitive load, attention level, and fatigue state, and has been researched and applied in fields such as driving safety monitoring and industrial operation status assessment. However, existing BCI technologies lack job suitability assessment schemes tailored to the characteristics of high-risk positions in rail transit, making it difficult to dynamically evaluate the fatigue development trend and changes in cognitive ability of personnel during actual task execution.

[0004] In related technologies, existing suitability testing schemes mainly rely on experience-based manual judgment, with managers assessing employees based on past performance, subjective descriptions, or simple observations; or they utilize questionnaires or psychological tests, scoring employees' states through a series of cognitive or psychological questions. Additionally, existing technologies introduce simple reaction time or attention tests in some scenarios to evaluate employees' short-term reaction abilities. These schemes, primarily based on subjective evaluation or static testing, fail to accurately reflect the physiological and cognitive states of employees under actual workload conditions, leading to a mismatch between employee capabilities and job characteristics, and posing potential safety hazards to rail transit operations. Summary of the Invention

[0005] This invention provides a method and apparatus for assessing the job suitability of personnel at risk in rail transit, which addresses the shortcomings of existing job suitability testing schemes that rely primarily on subjective evaluation or static testing, making it difficult to accurately reflect the physiological and cognitive state of personnel under actual workload conditions, resulting in a mismatch between personnel capabilities and job characteristics.

[0006] This invention provides a method for assessing the job suitability of personnel at risk in rail transit, comprising the following steps: Physiological signal data of the subjects were collected during the resting phase and the task execution phase, and the physiological signal data were aligned with the task to obtain the aligned physiological signal parameters. Physiological feature parameters are extracted from the aligned physiological signal parameters, and the variation amplitude of the physiological feature parameters in the task execution phase relative to the resting phase is calculated; a response index relating the task and physiology is constructed based on the variation amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of EEG signal power ratio parameters, heart rate parameters, and heart rate variability parameters, and the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject in the task execution phase; The job suitability of the tested personnel is assessed based on the response indicators to obtain the job suitability assessment results.

[0007] According to the present invention, a method for assessing the job suitability of personnel at risk in rail transit is provided, wherein the aligned physiological signal parameters include electroencephalogram (EEG) signal data. The extraction of physiological feature parameters from the aligned physiological signal parameters includes: The EEG signal data is subjected to bandpass filtering to obtain processed EEG signal data; the processed EEG signal data includes EEG data in the theta wave band and the beta wave band. The processed EEG signal data is divided into continuous time windows according to a preset window length, and the power of the theta wave and the power of the beta wave are calculated in each time window. The power ratio of the theta wave to the power of the beta wave within each time window is calculated, and the average value of the ratio within each time window is calculated to obtain the EEG signal power ratio parameter.

[0008] According to the present invention, a method for assessing the job suitability of personnel at risk in rail transit is provided, wherein the fatigue accumulation rate is obtained through the following steps: The power ratio change sequence of the EEG signal is determined based on the ratio of the power of the theta wave to the power of the beta wave corresponding to each time window; Outliers are removed from the EEG signal power ratio change sequence, and the least squares method is used to fit the sequence after outlier removal to obtain the fitted curve. The slope of the fitted curve is calculated to obtain the cumulative fatigue rate.

[0009] According to the present invention, a method for assessing the job suitability of personnel at risk in rail transit includes constructing a task-physiological correlation response index based on the change range and the cumulative fatigue rate of the tested personnel, comprising: The variation range of each physiological characteristic parameter and the corresponding weight of the fatigue accumulation rate are determined; wherein, the weight includes positive weight and negative weight, and the sum of the absolute values ​​of all weights is 1; The evaluation standard function is obtained by weighted summation of the change range, the fatigue accumulation rate and the corresponding weights, and then normalized to obtain a percentage value as the response index.

[0010] According to the present invention, a method for assessing the job suitability of personnel at risk in rail transit includes at least one of continuous monitoring tasks and incident handling tasks. Aligning the physiological signal data with the task to obtain aligned physiological signal parameters includes: In the event of the task starting, ending, or generating key interactive events, acquire task marker information; The task marker information and the corresponding timestamp are written into the physiological signal data to obtain the aligned physiological signal parameters.

[0011] According to the present invention, a method for assessing the job suitability of personnel at risk in rail transit includes, in which the job suitability of the tested personnel is assessed based on the response indicators to obtain a job suitability assessment result, comprising: If the response index is less than the first job suitability threshold, the job suitability assessment result is determined to be a recommended job suitability. If the response index is greater than or equal to the first job suitability threshold and less than the second job suitability threshold, the job suitability assessment result is determined to be a post-rest recommendation. If the response index is greater than or equal to the second job suitability threshold, the job suitability assessment result is determined to be a job transfer.

[0012] The present invention also provides a device for assessing the suitability of personnel at risk in rail transit, comprising: The signal acquisition module is used to acquire physiological signal data of the test subject during the resting phase and the task execution phase, and to align the physiological signal data with the task to obtain aligned physiological signal parameters. The indicator calculation module is used to extract physiological feature parameters from the aligned physiological signal parameters and calculate the change amplitude of the physiological feature parameters in the task execution phase relative to the resting phase; construct a response index of task-physiological correlation based on the change amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of EEG signal power ratio parameter, heart rate parameter, and heart rate variability parameter, and the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject in the task execution phase; The job suitability assessment module is used to assess the job suitability of the tested personnel based on the response indicators, and obtain the job suitability assessment results.

[0013] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described method for assessing the suitability of personnel at risk in rail transit.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for assessing the suitability of personnel at risk in rail transit.

[0015] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for assessing the suitability of personnel at risk in rail transit.

[0016] The present invention provides a method and apparatus for assessing the suitability of personnel in high-risk rail transit positions. By collecting physiological signal data of the tested personnel during the resting and task execution phases and aligning the physiological signal data with the task, it can accurately obtain the physiological response of the tested personnel under actual workload and reduce manual annotation errors. By extracting physiological characteristic parameters, calculating the magnitude of change, and combining them with the fatigue accumulation rate, a response index that correlates task and physiology can be constructed. This index can characterize the trend of increasing fatigue and the degree of cognitive decline in individuals under specific high-load tasks. Finally, the suitability of the tested personnel is assessed based on the response index, and the results can characterize the fatigue development trend and cognitive changes of individuals under high-load task conditions. This provides a basis for suitability assessment, scheduling management, and safe operation of personnel in high-risk rail transit positions, thereby improving the safety assurance capability of rail transit operations. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 This is one of the flowcharts of the method for assessing the suitability of personnel at risk in rail transit provided by the present invention.

[0019] Figure 2 This is a schematic diagram illustrating the time synchronization relationship between standardized work tasks and physiological signals provided by the present invention.

[0020] Figure 3 This is the second flowchart of the method for assessing the suitability of personnel at risk in rail transit provided by this invention.

[0021] Figure 4 This is one of the structural schematic diagrams of the rail transit risk personnel suitability assessment device provided by the present invention.

[0022] Figure 5 This is the second structural schematic diagram of the rail transit risk personnel suitability assessment device provided by the present invention.

[0023] Figure 6 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0025] The following is combined with Figures 1-5 This invention describes a method and apparatus for assessing the suitability of personnel for rail transit risk assessment.

[0026] Figure 1 This is one of the flowcharts illustrating the method for assessing the suitability of personnel for rail transit risk assessment provided by this invention, such as... Figure 1 As shown, the method includes the following steps: Step 110: Collect physiological signal data of the test subjects during the resting phase and the task execution phase, and align the physiological signal data with the task to obtain the aligned physiological signal parameters.

[0027] In this step, the personnel being tested can be those in high-risk positions with high operational density and high safety levels in the rail transit industry, such as train dispatchers, train operation commanders, or train drivers.

[0028] In this step, the resting phase refers to the baseline phase in which the test subject maintains a stable state without any operational load (e.g., for 2 minutes), while the task execution phase refers to the high-load phase in which the test subject performs standardized operational tasks (e.g., continuous monitoring tasks, incident handling tasks).

[0029] In this step, the physiological signal data includes, but is not limited to, multi-channel electroencephalogram (EEG) signals (mainly used to obtain potential changes in the forehead region) and continuous electrocardiogram (ECG) waveform signals acquired by the acquisition device. These physiological signal data are used to reflect the actual physiological and cognitive state of the subject.

[0030] In this embodiment, when a task starts, ends, or a key event is triggered, the system (the method execution entity) generates task marker information with a unified clock timestamp and synchronously writes the marker into the EEG and ECG data streams to obtain aligned physiological signal parameters.

[0031] In the pre-job testing scenario for rail transit dispatchers, the test subjects (such as dispatchers) wear EEG and ECG patches at a fixed workstation. The system first prompts the dispatcher to enter a 2-minute resting phase, automatically recording physiological data and marking "rest start / end" timestamps. Then, in the task execution phase, the system simulates a sudden "train operation conflict" on the ATS (Automatic Train Monitoring) interface and prompts the dispatcher to complete the "route manual processing" operation within a limited time. When the dispatcher performs the task, the system sends a trigger signal to the time synchronization unit, writing the corresponding timestamp and operation mark into the continuously collected EEG and ECG data stream to obtain aligned physiological signal parameters.

[0032] Step 120: Extract physiological feature parameters from the aligned physiological signal parameters and calculate the variation amplitude of physiological feature parameters during the task execution phase relative to the resting phase; construct a response index for the task-physiological correlation based on the variation amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of the following: EEG signal power ratio parameter, heart rate parameter, and heart rate variability parameter; the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject during the task execution phase.

[0033] In this step, the aligned physiological data can be filtered to remove artifacts and calculated in time windows to extract physiological characteristic parameters, such as EEG signal power ratio parameters, heart rate parameters, and heart rate variability parameters.

[0034] In this step, the relative increase or decrease of various physiological characteristic parameters between the task state and the resting state can be calculated to obtain the corresponding change range.

[0035] In this step, a change sequence is first constructed based on the power ratio of EEG signals in all time windows of the task phase. Then, a curve fitting algorithm is used to construct a curve based on the change sequence, and the slope of the curve trend is calculated, which is the fatigue accumulation rate. This parameter is used to characterize the speed at which the cognitive state of the test subject deteriorates over time under continuous high-pressure tasks.

[0036] In this embodiment, the above-mentioned change amplitude and fatigue accumulation rate are weighted according to the set positive and negative weights (such as assigning positive weights to changes in EEG and negative weights to decreases in ECG, ensuring that the absolute value of the sum of weights is 1), thereby constructing a response index that is related to the task and physiology. This index is used to reflect the degree of decline in the alertness level and fatigue trend of the test subjects.

[0037] In the aforementioned pre-job testing scenario for rail transit dispatchers, power frequency interference in the aligned physiological signal parameters can be filtered out first. The EEG signal is then windowed by t (e.g., t=3) seconds. Calculations confirm that when handling train operation conflict tasks, the dispatcher's physiological characteristic parameters (such as the EEG signal power ratio parameter, θ / β ratio) increase by 25% compared to the resting phase (i.e., the change amplitude is positive), the average heart rate decreases by 10%, and the heart rate variability decreases by 15%. Simultaneously, the system extracts and fits the θ / β ratio sequence of continuous time windows during the entire conflict handling task, calculating a straight line with a positive slope, indicating that the fatigue accumulation rate is increasing. At this point, the system substitutes the change amplitude of the above indicators and the fatigue accumulation rate into the evaluation standard function with preset weights. After normalization calculation, the task-related physiological response indicators are finally obtained, namely, the above-mentioned task-physiologically related response indicators.

[0038] Step 130: Assess the job suitability of the tested personnel based on the response indicators to obtain the job suitability assessment results.

[0039] In this step, the output response index value can be compared with the system's pre-set job suitability threshold range (such as the low fatigue threshold and high fatigue threshold determined based on a large number of sample engineering tests).

[0040] In this step, the job suitability assessment results can include job suitability (recommendation), job adjustment required (recommendation after rest), or job incompatibility (job transfer). These results are used to enable the operating unit to schedule shifts and provide risk warnings.

[0041] For example, after calculating the dispatcher's performance indicators, the system retrieves the preset job suitability threshold range from the backend: 0 to 40 points indicates no fatigue, 40 to 80 points indicates "moderate fatigue," and 80 to 100 points indicates fatigue. The system substitutes the dispatcher's comprehensive response indicator of 75 points into the range for comparison and determines that it falls within the 40-80 point range. At this point, the structured visual panel of the job suitability test program displays the dispatcher's fatigue assessment result as "moderate fatigue" and outputs the final job suitability assessment result, showing "Recommended for work after rest." Based on this conclusion, the scheduling manager slightly adjusts the dispatcher's originally scheduled early shift to a later shift.

[0042] The method for assessing the suitability of personnel in high-risk rail transit positions provided in this invention collects physiological signal data of the tested personnel during the resting and task execution phases, and aligns the physiological signal data with the task. This allows for accurate acquisition of the physiological responses of the tested personnel under actual workloads and reduces manual annotation errors. By extracting physiological characteristic parameters, calculating the magnitude of change, and combining this with the fatigue accumulation rate, a response index linking the task and physiology is constructed. This index can characterize the trend of increasing fatigue and the degree of cognitive decline in individuals under specific high-load tasks. Finally, the suitability of the tested personnel is assessed based on the response index, resulting in a suitability assessment result. This result can characterize the fatigue development trend and changes in cognitive ability of individuals under high-load task conditions, providing a basis for suitability assessment, scheduling management, and safe operation of personnel in high-risk rail transit positions, thereby improving the safety assurance capability of rail transit operations.

[0043] In some embodiments, the aligned physiological signal parameters include electroencephalogram (EEG) signal data; extracting physiological feature parameters from the aligned physiological signal parameters includes: performing bandpass filtering on the EEG signal data to obtain processed EEG signal data; the processed EEG signal data includes EEG data in the theta wave band and the beta wave band; dividing the processed EEG signal data into continuous time windows according to a preset window length, and calculating the power of the theta wave and the power of the beta wave in each time window; calculating the ratio of the power of the theta wave to the power of the beta wave in each time window, and calculating the average value of the ratio in each time window to obtain the EEG signal power ratio parameter.

[0044] In this embodiment, during the execution of standardized tasks, the EEG and ECG signals of the test subjects are collected simultaneously. The EEG signals are multi-channel EEG time-series signals, and the ECG signals are continuous ECG waveform signals. The collected EEG signals are preprocessed by artifact removal and filtering, and EEG frequency domain feature parameters are extracted within the corresponding task time period. The EEG frequency domain feature parameters include at least energy distribution parameters or frequency band energy ratio parameters of different frequency bands. Then, R-wave detection is performed on the collected ECG signals, and heart rate and heart rate variability-related feature parameters, i.e., physiological feature parameters, are extracted.

[0045] Specifically, the data acquisition and transmission module can acquire the corresponding aligned physiological signal parameters; the data acquisition and transmission module includes a fixed testing station, an EEG signal acquisition unit, an ECG signal acquisition unit, a time synchronization and task marking unit, and a data buffering and transmission unit.

[0046] In this embodiment, a fixed testing station limits the sitting height, head position, visual range, and operating area of ​​the test subject during the testing process. By fixing the seat height, display terminal position, and input device layout, the influence of body position changes, electromyographic interference, and line of sight deviation on EEG and ECG signals is reduced, thereby improving the repeatability of multiple test results.

[0047] In this embodiment, the EEG acquisition unit is used to acquire multi-channel EEG signals of the test subject during the performance of standardized work tasks. The EEG acquisition unit includes: A multi-channel electrode array is used to acquire potential changes in different brain regions (based on engineering needs, priority is given to acquiring EEG signals from the frontal region). Analog front-end amplification and filtering circuitry is used to amplify weak EEG signals and suppress power frequency interference; The analog-to-digital converter is used to convert analog EEG signals into digital signals.

[0048] The sampling frequency can be set in the range of 200–1000Hz to meet the requirements of frequency domain feature extraction (the highest frequency of the extracted signal should not exceed 50Hz; according to the Nyquist sampling theorem, the sampling rate should be above 100Hz, but here it is limited to above 200Hz to reserve a certain amount of redundancy).

[0049] In this embodiment, the ECG acquisition unit is used to acquire continuous ECG waveform signals of the subject. The ECG signals include at least R wave information (the peak position of the R wave in the QRS complex) for subsequent heart rate and heart rate variability analysis. The ECG acquisition method can be a chest lead or a patch lead to ensure signal stability under long-term task conditions.

[0050] In this embodiment, the time synchronization and task marking unit is used to achieve precise alignment between task events and physiological signal data, and its specific implementation includes: (1) When a standardized work task begins, ends, or a critical event is triggered, the task presentation module sends an event trigger signal to the time synchronization unit; (2) After receiving the event trigger signal, the time synchronization unit generates the corresponding task tag information and binds the task tag information with the timestamp generated by the unified system clock; (3) The task tag information with timestamps is synchronously written into the EEG signal data stream and the ECG signal data stream to form physiological signal data with task tags.

[0051] (4) In subsequent data processing, by parsing the task label information, the continuous physiological signals are automatically divided into multiple time windows according to the task stage, thereby realizing the accurate extraction of physiological responses corresponding to different standardized tasks and their sub-stages, avoiding errors caused by manual labeling or subjective division.

[0052] In this embodiment, the collected physiological signal data can be cached locally and transmitted to the data processing module via wired or wireless means. During transmission, a data verification mechanism can be used to ensure data integrity. This process can adopt real-time transmission (such as transmitting the current data every 2 seconds) or uniform transmission of data at each stage. The selection method should be determined in combination with the hardware cache size and transmission rate.

[0053] In one embodiment, the extraction of physiological characteristic parameters includes the following steps: (1) preprocessing the collected EEG and ECG signals, (2) extracting characteristic parameters, (3) calculating the power ratio parameter of the EEG signal, (4) calculating the amplitude parameter of the change in the power ratio of the EEG signal, (5) fatigue accumulation rate, (6) heart rate parameter, and (7) heart rate variability parameter.

[0054] In this embodiment, (1) includes: filtering the EEG signal using a 4th-order Butterworth bandpass filter with parameters of 1-30Hz to suppress DC drift and motion artifacts, and retaining the frequency band information of theta waves (4-8Hz), alpha waves (8-13Hz), and beta waves (13-30Hz) related to alertness and fatigue; R-wave detection and abnormal heartbeat removal of the ECG signal, wherein the R-wave detection can be performed using a peak detection algorithm.

[0055] In this embodiment, (2) includes: after preprocessing, extracting physiological feature parameters in different standardized task time periods, including but not limited to: EEG signal power ratio parameter, EEG signal power ratio change amplitude parameter, fatigue accumulation speed, heart rate parameter, and heart rate variability parameter.

[0056] In this embodiment, (3) includes: using the task phase Wave power and The average value of the ratio of wave power within each time window is used as the EEG signal power ratio parameter, denoted as . The calculation method is as follows: Assuming the raw data after preprocessing in the task phase is The sampling rate is assumed to be The frequency can be set to 250Hz. First, the data is windowed, with a window length of 3 seconds, for a total of K time windows. The number of data points in each window... For the k-th time window, its content is Then, a Hamming window is used instead of a rectangular window to achieve truncation, that is, the content of the k-th time window is: ; right Perform a Fast Fourier Transform to obtain the spectrum: ; Calculate the power spectral density (PSD) from the spectrum: ; Based on the frequency range of each EEG signal, the power spectral density can be integrated (approximately by summation) to obtain the power within each frequency range. The main signal frequency bands are shown in the table below: Table 1. Range and Explanation of EEG Characteristic Signals by Taking wave power as an example, the calculation formula is as follows: ; Averaging over all windows yields the following result. Average power The definition is as follows: ; Similarly, it can be calculated that Task Phase relative power The expression is as follows: .

[0057] In this embodiment, (4) includes: calculating a single window using the following formula. : ; Next, for all time windows of the task phase... By averaging, we can obtain the result. As shown below: .

[0058] In this embodiment, the fatigue accumulation rate is obtained through the following steps: determining the EEG signal power ratio change sequence based on the ratio of the power of the theta wave to the power of the beta wave corresponding to each time window; removing outliers from the EEG signal power ratio change sequence and using the least squares method to fit the sequence after removing outliers to obtain the fitted curve; calculating the slope of the fitted curve to obtain the fatigue accumulation rate.

[0059] Specifically, the above (5) includes: the time window within each phase of the computation task. The sequence of values ​​formed by these values ​​in the task phase is then fitted using the least squares method to obtain the fitted curve, which is specifically represented by the following formula: ; Where 'a' represents the slope of the curve, reflecting the rate of fatigue accumulation during the task phase. For constant terms, For the first k At that moment t .

[0060] It should be noted that although filtering has been performed, abnormal window data still needs to be removed. This embodiment can be achieved by setting... The threshold is used for initial filtering to exclude significant abnormal data before subsequent calculations are performed.

[0061] In this embodiment, (6) includes: obtaining an R-wave time series based on the ECG (electrocardiogram) data from the task phase using R-wave detection. Calculate the time difference between adjacent wave peaks. The unit is s: ; This embodiment also removes obvious outliers, such as those less than 0.3s or greater than 2s; this sequence is referred to as the NN interval. The average heart rate during the task phase... The average instantaneous heart rate is defined by the following formula: .

[0062] In this embodiment, (7) includes: heart rate variability parameters are measured using the standard deviation of the NN interval (SDNN). Taking the task phase as an example, the heart rate variability parameters... The definition is as follows: .

[0063] The method for assessing the suitability of personnel at risk in rail transit provided in this invention extracts specific frequency bands by bandpass filtering the aligned EEG signals, calculates the power ratio of theta waves and beta waves by slicing them according to time windows, and finally obtains the mean value to obtain the EEG signal power ratio parameter. This parameter is used to convert complex, noisy, and non-stationary raw EEG signals into response indicators that can objectively and stably characterize changes in cognitive load and attention control levels of personnel under specific tasks.

[0064] In some embodiments, a response index relating the task and physiology is constructed based on the magnitude of change and the cumulative fatigue rate of the test subject, including: determining the magnitude of change of each physiological characteristic parameter and the corresponding weight of the cumulative fatigue rate; wherein the weights include positive weights and negative weights, and the sum of the absolute values ​​of all weights is 1; weighted summing of the magnitude of change, the cumulative fatigue rate and the corresponding weights to obtain an evaluation standard function, and normalizing the evaluation standard function to obtain a percentage value as the response index.

[0065] In this embodiment, after the feature parameters are extracted, task-related analysis is performed on the physiological feature parameters based on the time window corresponding to the task marker. This is achieved by: normalizing and comparing the physiological feature parameters extracted during the task execution phase with the corresponding feature parameters of the subject in a resting state or under a low-load baseline task. Based on engineering experience, except for the fatigue accumulation rate, all the aforementioned feature parameters need to be measured by comparing the change in the task phase with the change in the resting phase. The trend of change in relevant parameters as fatigue increases is shown in Table 2 below. Table 2. Explanation of the changing trends of physiological characteristic parameters as fatigue levels increase. In this embodiment, for cases containing multiple standard tasks, the aforementioned index can be the average of multiple standard tasks; specifically, for the feature parameter X, which requires calculating the change in the task state compared to the resting state, the calculation method is expressed as follows: ; To ensure that all parameters change in the same direction as fatigue increases, different weights are assigned to each parameter, and the absolute value of the sum of the weights is ensured to be 1. The weights for reference are shown in Table 3 below: Table 3. Explanation of the variation range and weighting of physiological characteristic parameters In this embodiment, based on the aforementioned weights, a unified job suitability index evaluation standard function FI can be constructed, defined as the weighted sum of each evaluation index, thus obtaining the evaluation standard function, expressed as follows: ; Furthermore, to facilitate engineering applications, FI should be standardized, with the following reference formula: ; in, and The calibration can be completed by collecting data from a certain sample size of people in low and high fatigue states respectively; through the above calculation, the job suitability evaluation parameters are correlated with the degree of fatigue, and a normalized (0-100) index is used for quantitative evaluation, so that the job suitability assessment has objective physiological data support.

[0066] The method for assessing the job suitability of personnel at risk in rail transit provided in this invention assigns positive and negative weights based on the natural changing trends of characteristics, constructs an evaluation standard function through weighted summation, and then outputs a percentage-based numerical result through normalization. This method can convert complex physiological responses into a comparable comprehensive job suitability score, providing a reliable basis for subsequent assessment of the job suitability of personnel at risk in rail transit.

[0067] In some embodiments, the task includes at least one of continuous monitoring tasks and event handling tasks; aligning physiological signal data with the task to obtain aligned physiological signal parameters includes: acquiring task marker information at the start, end, and occurrence of key interaction events of the task; and writing the task marker information and the corresponding timestamp into the physiological signal data to obtain aligned physiological signal parameters.

[0068] In this embodiment, the above-mentioned tasks are standardized work tasks, including at least the following two categories: (1) Continuous monitoring tasks are used to simulate working conditions that require long-term vigilance, such as train operation monitoring and signal status monitoring. By continuously presenting multi-source operation information, the vigilance decay process is induced.

[0069] (2) Event handling tasks are used to simulate sudden operational anomalies, such as train delays, operational conflicts or equipment alarms. The test subjects are required to complete information judgment and decision-making operations within a limited time to induce a state of high cognitive load.

[0070] Taking event handling tasks as an example, this embodiment uses "handling train routes according to the train timetable" as an example. The triggering time for the above task is: handling it in a timely manner according to the train timetable. Users can choose from the following two options, depending on the train's specific situation: (a) Manual processing of the route; 1. Right-click the signal at the beginning of the route and select "Route Selection". 2. A route processing dialog box will pop up; select the route you wish to process. 3. After selecting "OK", the route will be successfully established.

[0071] (ii) When two or more trains are running in the same direction, an interlocking automatic route shall be arranged; 1. Right-click the signal at the beginning of the route and select "Set Interlocking Automatic Route"; 2. A dialog box will pop up automatically loading the station name and the name of the signal at the beginning of the route; 3. After selecting "OK", the interlocking automatic route is successfully established, and a green arrow will appear next to the signal.

[0072] In this embodiment, the system automatically records user operations and whether the final result meets the requirements, and stores the final operation rating in the cache. It can use a 3-level output, such as excellent, qualified, and unqualified. When the user's operation result is unqualified, the user should be prompted to retest, and the subtask data will not be used in subsequent evaluations.

[0073] In this embodiment, each standardized task is defined by system parameterization, and its standardized design includes at least: (1) event ID identifier; (2) maximum task duration; (3) set of correct operation logic; and (4) operation complexity level (a level manually evaluated based on the number of operation objects, number of interaction steps, etc.). In this embodiment, the parameters mentioned above are fixed in the system in the form of configuration files or parameter tables, and remain consistent across different test subjects and different test batches. This achieves consistency and reproducibility of standardized work task conditions through technical means rather than human experience. In addition, this embodiment also requires the addition of: time interval between tasks and number of standardized tasks for multiple tasks in the testing process.

[0074] Figure 2 This is a schematic diagram illustrating the time synchronization relationship between standardized work tasks and physiological signals provided by the present invention. Figure 2 In the illustrated embodiment, at the start of the task, the subject opens the suitability test program, and the system simultaneously begins a self-check, providing feedback on the user's device wearing status and electrode fit. The system also records the current fit status in a cache. When the electrodes fit well and the device is worn correctly, the self-check is considered passed, and the user is prompted to proceed to the task phase. The task is triggered by the user's click, and the system prompts the user to enter the resting task phase (e.g., the user needs to maintain a stable state for 2 minutes). During this period (i.e., the start and end of the resting task), the system collects the user's EEG and ECG signals, storing the raw and parsed data, and simultaneously providing start and end markers for data collection. After the resting task ends, audio and text prompts should be provided. The system will prompt the user to enter the standard task data collection phase. This task is still triggered by the user's click. The system will use a real ATS interface to simulate high-load interactive tasks that may be encountered on-site. According to the parameter settings, the system will randomly select a certain number of tasks from the task library that meet the preset conditions and load and display them. The user will complete the required operations according to the prompts (each standard task generally does not exceed 2 minutes, and the task interval is 30 seconds). The system should record the corresponding flags at the beginning and end of the standardized tasks to facilitate subsequent data processing. After all tasks are completed, the system will prompt that the task has ended and automatically perform data analysis. Based on the indicators of resting state and task state, the system will complete the job suitability assessment and output the job suitability test results.

[0075] The method for assessing the suitability of personnel at risk in rail transit provided in this invention sets up standardized tasks that include continuous monitoring and event handling, and obtains marker information and timestamps at the start and end of the tasks and key interaction nodes. These are then synchronously written into a continuous physiological signal data stream to obtain alignment parameters. This method can restore the real workload of rail transit and automatically bind abstract physiological electrical signals with specific business actions on the timeline, eliminating the human alignment error when slicing physiological data.

[0076] In some embodiments, the suitability of the tested personnel is assessed based on response indicators to obtain a suitability assessment result, including: if the response indicator is less than a first suitability threshold, the suitability assessment result is determined to be recommended for a suitable position; if the response indicator is greater than or equal to the first suitability threshold and less than a second suitability threshold, the suitability assessment result is determined to be recommended after rest; if the response indicator is greater than or equal to the second suitability threshold, the suitability assessment result is determined to be reassigned.

[0077] In this embodiment, different types of physiological response indicators are weighted and summed or linearly combined according to preset weights to obtain a comprehensive job suitability assessment score; or based on threshold mapping rules, each physiological response indicator is mapped to a discrete risk level and then jointly judged; or a discriminant model based on training samples is used to classify or regress the physiological response indicators.

[0078] In this embodiment, the comprehensive job suitability assessment score can be compared with a pre-set job suitability threshold range. Based on the comparison results, an assessment conclusion can be output indicating whether the candidate is suitable for the job, needs to adjust their position, or is unsuitable for the job, thereby forming a quantitative result that can directly support management decisions.

[0079] In this embodiment, the aforementioned threshold needs to be determined through engineering experiments based on sample data. It is assumed that the output results are categorized into three types: 1) no fatigue; 2) general fatigue; 3) fatigue. The following methods can be used... Two parameters ( The output results are simply separated as shown in Table 4 below: Table 4. Explanation of the Relationship between Response Indicators and Corresponding Job Suitability Recommendations In this embodiment, the above-mentioned job suitability assessment results may include the following: (1) job suitability assessment parameter values; (2) job suitability status classification results; and (3) physiological response change trends at different task stages.

[0080] In this embodiment, considering practical needs, the program's main interface can prioritize displaying... The system collects fatigue assessment results and job suitability recommendations, and retains detailed data such as original data, characteristic parameters, variation range, and final results for each task stage, for future algorithm optimization and review.

[0081] In this embodiment, the above-mentioned job suitability assessment results can be used in the following scenarios: (1) job suitability determination before starting work; (2) shift adjustment and job rotation decision-making; (3) long-term personnel status tracking and risk warning.

[0082] In this embodiment, the above-mentioned job suitability assessment results are visualized and used for application decisions in subsequent scenarios, which can realize the direct transformation of test results from testing to management decision support.

[0083] Figure 3 This is the second flowchart of the method for assessing the suitability of personnel for rail transit risk assessment provided by this invention. Figure 3 In the illustrated embodiment, during the task preparation phase, the subjects wear EEG and ECG acquisition devices and adjust their sitting posture and viewing distance; when the devices are in normal self-test mode, they enter the task execution phase, where they input login information and perform standardized tasks; during the result evaluation phase, the subjects' data is analyzed and relevant features are extracted, and evaluation indicators (i.e., the aforementioned response indicators) are output. After comparing with preset thresholds, the evaluation results (i.e., the corresponding job recommendation results) are output.

[0084] Figure 4 This is one of the structural schematic diagrams of the rail transit risk personnel suitability assessment device provided by the present invention. Figure 4 In the illustrated embodiment, the device includes a data acquisition module, a standardized task module, a data processing module, and a result presentation and application module. The data acquisition module includes a fixed testing station unit, an EEG signal acquisition unit, an ECG signal acquisition unit, a time synchronization and task marking unit, and a data caching and transmission unit. The standardized task module's task parameters include complexity, duration, number of occurrences, and maximum response time; its task types include continuous monitoring tasks and event handling tasks. The data processing module includes feature extraction and evaluation parameter calculation. Specifically, feature extraction includes extracting frequency band energy, frequency band energy ratio, heart rate, heart rate variability, and surprise state features. By comparing the extracted features, the rate of change, magnitude of change, and statistical differences are obtained. Through threshold mapping, supervised models, and weighted combination processing, the output result is a response index related to the task and physiology. The result presentation and application module displays and integrates evaluation results (such as job suitability assessment parameters, state classification results, and change trends) for application in scenarios such as job suitability judgment and adjustment, and risk warning.

[0085] The following describes the rail transit risk personnel suitability assessment device provided by the present invention. The rail transit risk personnel suitability assessment device described below can be referred to in correspondence with the rail transit risk personnel suitability assessment method described above.

[0086] Figure 5 This is the second structural schematic diagram of the rail transit risk personnel suitability assessment device provided by the present invention, as shown below. Figure 5 As shown, the rail transit risk personnel suitability assessment device includes: a signal acquisition module 510, an index calculation module 520, and a suitability assessment module 530.

[0087] The signal acquisition module 510 is used to acquire physiological signal data of the test subject during the resting phase and the task execution phase, and to align the physiological signal data with the task to obtain the aligned physiological signal parameters. The index calculation module 520 is used to extract physiological feature parameters from the aligned physiological signal parameters and calculate the change amplitude of the physiological feature parameters during the task execution phase relative to the resting phase; and construct a response index of task-physiological correlation based on the change amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of the following: EEG signal power ratio parameter, heart rate parameter, and heart rate variability parameter; the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject during the task execution phase. The job suitability assessment module 530 is used to assess the job suitability of the tested personnel based on response indicators and obtain job suitability assessment results.

[0088] The rail transit risk personnel suitability assessment device provided by this invention collects physiological signal data of the tested personnel during the resting and task execution phases, and aligns the physiological signal data with the task to accurately obtain the physiological response of the tested personnel under actual workload, reducing manual annotation errors. By extracting physiological characteristic parameters, calculating the magnitude of change, and combining them with the fatigue accumulation rate, a response index that correlates task and physiology is constructed, which can characterize the trend of increasing fatigue and the degree of cognitive decline in individuals under specific high-load tasks. Finally, the suitability of the tested personnel is assessed based on the response index, and the suitability assessment results can characterize the fatigue development trend and cognitive changes of individuals under high-load task conditions. This provides a basis for suitability assessment, scheduling management, and safe operation of personnel in high-risk rail transit positions, thereby improving the safety assurance capability of rail transit operations.

[0089] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communications bus 640, wherein the processor 610, the communications interface 620, and the memory 630 communicate with each other through the communications bus 640. The processor 610 can call logic instructions in the memory 630 to execute a method for assessing the suitability of personnel at risk in rail transit. This method includes: collecting physiological signal data of the test subject during the resting and task execution phases, aligning the physiological signal data with the task to obtain aligned physiological signal parameters; extracting physiological characteristic parameters from the aligned physiological signal parameters and calculating the magnitude of change of these parameters during the task execution phase relative to the resting phase; constructing a response index relating the task and physiology based on the magnitude of change and the test subject's cumulative fatigue rate; the physiological characteristic parameters include at least one of EEG signal power ratio parameters, heart rate parameters, and heart rate variability parameters, with the cumulative fatigue rate obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject during the task execution phase; and assessing the test subject's suitability based on the response index to obtain a suitability assessment result.

[0090] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part 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 the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0091] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the above-described method for assessing the suitability of personnel at risk in rail transit. The method includes: collecting physiological signal data of the test subject during a resting phase and a task execution phase, and aligning the physiological signal data with the task to obtain aligned physiological signal parameters; extracting physiological characteristic parameters from the aligned physiological signal parameters and calculating the variation amplitude of the physiological characteristic parameters during the task execution phase relative to the resting phase; constructing a response index relating the task and physiology based on the variation amplitude and the test subject's fatigue accumulation rate; the physiological characteristic parameters include at least one of an EEG signal power ratio parameter, a heart rate parameter, and a heart rate variability parameter, and the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject during the task execution phase; and assessing the test subject's suitability based on the response index to obtain a suitability assessment result.

[0092] In another aspect, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the rail transit risk personnel suitability assessment method provided by the above methods. The method includes: collecting physiological signal data of the test subject in the resting phase and the task execution phase, and aligning the physiological signal data with the task to obtain aligned physiological signal parameters; extracting physiological feature parameters from the aligned physiological signal parameters and calculating the change amplitude of the physiological feature parameters in the task execution phase relative to the resting phase; constructing a response index of task-physiological correlation based on the change amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of EEG signal power ratio parameter, heart rate parameter, and heart rate variability parameter, and the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject in the task execution phase; and assessing the suitability of the test subject based on the response index to obtain a suitability assessment result.

[0093] The device embodiments described above are merely illustrative. 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; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0094] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for assessing the job suitability of personnel at risk in rail transit, characterized in that, include: Physiological signal data of the subjects were collected during the resting phase and the task execution phase, and the physiological signal data were aligned with the task to obtain the aligned physiological signal parameters. Physiological feature parameters are extracted from the aligned physiological signal parameters, and the variation amplitude of the physiological feature parameters in the task execution phase relative to the resting phase is calculated; a response index relating the task and physiology is constructed based on the variation amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of EEG signal power ratio parameters, heart rate parameters, and heart rate variability parameters, and the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject in the task execution phase; The job suitability of the tested personnel is assessed based on the response indicators to obtain the job suitability assessment results.

2. The method for assessing the suitability of personnel for rail transit risk assessment according to claim 1, characterized in that, The aligned physiological signal parameters include electroencephalogram (EEG) signal data; The extraction of physiological feature parameters from the aligned physiological signal parameters includes: The EEG signal data is subjected to bandpass filtering to obtain processed EEG signal data; The processed EEG signal data includes EEG data in the theta wave band and the beta wave band; The processed EEG signal data is divided into continuous time windows according to a preset window length, and the power of the theta wave and the power of the beta wave are calculated in each time window. The power ratio of the theta wave to the power of the beta wave within each time window is calculated, and the average value of the ratio within each time window is calculated to obtain the EEG signal power ratio parameter.

3. The method for assessing the suitability of personnel for rail transit risk assessment according to claim 2, characterized in that, The fatigue accumulation rate is obtained through the following steps: The power ratio change sequence of the EEG signal is determined based on the ratio of the power of the theta wave to the power of the beta wave corresponding to each time window; Outliers are removed from the EEG signal power ratio change sequence, and the least squares method is used to fit the sequence after outlier removal to obtain the fitted curve. The slope of the fitted curve is calculated to obtain the cumulative fatigue rate.

4. The method for assessing the suitability of personnel for rail transit risk assessment according to claim 1, characterized in that, The construction of a task-physiological correlation response index based on the magnitude of change and the cumulative fatigue rate of the test subject includes: The variation range of each physiological characteristic parameter and the corresponding weight of the fatigue accumulation rate are determined; wherein, the weight includes positive weight and negative weight, and the sum of the absolute values ​​of all weights is 1; The evaluation standard function is obtained by weighted summation of the change range, the fatigue accumulation rate and the corresponding weights, and then normalized to obtain a percentage value as the response index.

5. The method for assessing the job suitability of personnel facing risks in rail transit according to claim 1, characterized in that, The tasks include at least one of continuous monitoring tasks and incident handling tasks; Aligning the physiological signal data with the task to obtain aligned physiological signal parameters includes: In the event of the task starting, ending, or generating key interactive events, acquire task marker information; The task marker information and the corresponding timestamp are written into the physiological signal data to obtain the aligned physiological signal parameters.

6. The method for assessing the job suitability of personnel facing risks in rail transit according to any one of claims 1-5, characterized in that, The process of assessing the job suitability of the tested personnel based on the response indicators to obtain job suitability assessment results includes: If the response index is less than the first job suitability threshold, the job suitability assessment result is determined to be a recommended job suitability. If the response index is greater than or equal to the first job suitability threshold and less than the second job suitability threshold, the job suitability assessment result is determined to be a post-rest recommendation. If the response index is greater than or equal to the second job suitability threshold, the job suitability assessment result is determined to be a job transfer.

7. A device for assessing the job suitability of personnel facing risks in rail transit, characterized in that, include: The signal acquisition module is used to acquire physiological signal data of the test subject during the resting phase and the task execution phase, and to align the physiological signal data with the task to obtain aligned physiological signal parameters. The indicator calculation module is used to extract physiological feature parameters from the aligned physiological signal parameters and calculate the change amplitude of the physiological feature parameters in the task execution phase relative to the resting phase; construct a response index of task-physiological correlation based on the change amplitude and the fatigue accumulation rate of the test subject; the physiological feature parameters include at least one of EEG signal power ratio parameter, heart rate parameter, and heart rate variability parameter, and the fatigue accumulation rate is obtained by fitting the EEG signal power ratio change sequence corresponding to the test subject in the task execution phase; The job suitability assessment module is used to assess the job suitability of the tested personnel based on the response indicators, and obtain the job suitability assessment results.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the method for assessing the suitability of personnel at risk in rail transit as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for assessing the suitability of personnel at risk in rail transit as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for assessing the suitability of personnel at risk in rail transit as described in any one of claims 1 to 6.

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