Isolation chamber post task embedded stressor devices, systems, and methods

Abstract

This invention discloses an isolation-enclosed chamber-based stress-inducing device, system, and method embedded in a job-specific task. The device includes: an isolation chamber constructed according to the structure of a task cabin; an environmental simulation device installed inside the isolation chamber to simulate corresponding hazardous environments based on virtual emergency events; a physiological signal acquisition device installed inside the isolation chamber to collect physiological signals from the subject in real time; a central control console equipped with a job-specific emergency triggering system to simulate virtual emergency events and induce stress responses in the subject; the central control console also receives physiological signals from the subject collected by the physiological signal acquisition device for stress induction and assessment; and a VR headset to provide a VR environment for the subject. This invention can simulate isolation-enclosed environments and long-range mission scenarios with high fidelity in a laboratory environment. By coupling VR technology with job-specific emergency tasks, it enables the testing of mild, moderate, and severe stress emotions in the subject. The method is controllable and repeatable.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of human factors engineering and virtual reality technology, and in particular relates to a VR-based three-level stress induction system and method for job-specific embedded tasks in an isolated closed cabin. Background Technology

[0002] Personnel who perform long-term missions in isolated and confined environments such as submarines, spacecraft, and polar research stations are prone to stress when faced with sudden emergencies, affecting operational safety and mission effectiveness. Existing stress-inducing tasks are disconnected from real-world work situations, lack environmental elements, and cannot quantitatively control stress levels. Currently, commonly used stress-inducing methods in laboratories mostly use static emotional stimuli (such as pictures and videos) or simplified game tasks, lacking connection to real-world work situations and failing to reflect the unique visual, auditory, social, and information transmission characteristics of isolated and confined environments. This results in low ecological validity and an inability to quantify and repeatedly induce mild, moderate, and severe stress states. Summary of the Invention

[0003] To address the aforementioned issues, this invention proposes an isolation-enclosed cabin-based stress-inducing device, system, and method that can realistically simulate isolation-enclosed environments and long-range mission scenarios in a laboratory setting. By coupling VR technology with job-related hazardous tasks, it enables the testing of subjects' mild, moderate, and severe stress emotions. This method is controllable and can be repeatedly induced.

[0004] The objective of this invention is achieved through the following technical solution: a stress-inducing device embedded in a closed-cell work area, comprising: The sealed isolation chamber was constructed according to the structure of the mission compartment.

[0005] The environmental simulation equipment is installed inside a sealed isolation chamber to simulate corresponding dangerous environments based on virtual emergency events.

[0006] The physiological signal acquisition device is installed inside a sealed chamber to collect the physiological signals of the subjects in real time.

[0007] The central control unit is equipped with a job-related hazard triggering system that simulates virtual hazard events to induce stress responses in the subjects. The central control unit also receives physiological signals from the subjects collected by physiological signal acquisition equipment for stress induction and assessment.

[0008] VR headsets provide participants with a VR environment.

[0009] The environmental simulation equipment, physiological signal acquisition equipment, central control console, and VR headset are connected via wired or wireless means.

[0010] Preferably, the interior of the sealed isolation chamber is configured as follows: Warm-colored LED lighting is installed on the cabin ceiling; Portholes are located directly in front of and to the side of enclosed, isolated compartments; The cabin is equipped with an operating console and a human-machine interface.

[0011] Preferably, the environmental simulation equipment includes: Lighting simulation device, audio simulation device, and information delay simulation device.

[0012] Preferably, the physiological signal acquisition device includes: Wristband-type physiological data collection device.

[0013] In addition to providing a stress-inducing device embedded in a closed-cell work area, this invention further provides a stress-inducing system embedded in a closed-cell work area for controlling the aforementioned device. This system includes: The VR environment building module is used to construct virtual environments with characteristics such as monotonous lighting, information delay, and social isolation. The task and hazard integration module embeds typical hazard events into the virtual task process and sets multi-level parameter groups for each type of hazard; The physiological monitoring and feedback control module collects the physiological signals of the subjects in real time and dynamically adjusts the risk parameters through a PID controller to keep the subjects' stress level stable within the target range.

[0014] Preferably, the isolation-sealed cabin job task embedded stress induction system also includes an experiment reproduction module, which records and stores experimental parameters and physiological data, and generates standardized scripts that can be replayed with one click.

[0015] Preferably, the task and emergency integration module embeds four typical emergency events into the virtual task process, including damage control, fire alarm, depth drop and rudder jamming, with each type of emergency having three levels of parameter groups: light, medium and heavy.

[0016] The present invention also provides a method for inducing embedded stress in isolated closed-cell work positions using the above-mentioned equipment, the method comprising the following steps: Step 1: The subject enters the sealed isolation chamber and performs routine job operations. Step 2: The central control console triggers the corresponding emergency event based on the preset or real-time selected emergency type; Step 3: The physiological signal acquisition device collects physiological data in real time, and dynamically adjusts the intensity and duration of the emergency through a closed-loop controller; Step 4: After the experiment, save the scene parameters and adjustment records as a script file.

[0017] Preferably, in step 2, a risk-stress level mapping is set up. Based on the preset or real-time selected risk type and target stress level, a corresponding risk event is triggered. The stress level includes three levels: mild, moderate, and severe. The specific values ​​of the three levels of triggering parameter groups are established by collecting the subjective stress scores and physiological indicators of the subjects under different parameter combinations of risk situations to establish a mapping relationship.

[0018] Preferably, in step 3, the closed-loop controller is a PID controller with a control cycle of no more than 1 second and a system closed-loop delay of less than 200 milliseconds.

[0019] The beneficial effects of this invention are as follows: As can be seen from the above scheme, the stress-inducing device, system, and method embedded in a closed-loop isolation chamber, provided by this invention, constructs a VR digital twin closed-loop environment, embeds real-world hazardous tasks, and combines physiological feedback closed-loop control technology to achieve controllable and repeatable induction of mild, moderate, and severe stress emotions, and supports one-click scripted reproduction of the experimental process. This invention is applicable to research on personnel stress capacity training and assessment in closed-loop environments such as aerospace, submarines, and polar regions.

[0020] This invention achieves stress induction that integrates a highly ecologically effective isolated and enclosed environment with job tasks; it also enables the quantification and repeated induction of mild, moderate, and severe stress emotions.

[0021] The device provided by this invention supports full parameter recording and one-click reproduction of the experimental process, ensuring experimental repeatability and data comparability, and has real-time physiological feedback and safety protection mechanisms to ensure the safety of the subjects. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the hardware composition of the stress-inducing device embedded in the job position of the isolated closed chamber in an embodiment of the present invention; Figure 2 This is a schematic diagram of the internal environment of the VR digital twin cabin in an embodiment of the present invention; Figure 3 This is a schematic diagram of the closed-loop control process for physiological signals in an embodiment of the present invention; Figure 4 This is a schematic diagram of experimental parameter recording and script generation in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions in this embodiment 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.

[0024] The present invention provides a stress-inducing device embedded in a closed-cell isolation work area, comprising: The sealed isolation chamber was constructed according to the structure of the mission compartment.

[0025] The environmental simulation equipment is installed inside a sealed isolation chamber to simulate corresponding dangerous environments based on virtual emergency events.

[0026] The physiological signal acquisition device is installed inside a sealed chamber to collect the physiological signals of the subjects in real time.

[0027] The central control unit is equipped with a job-related hazard triggering system that simulates virtual hazard events to induce stress responses in the subjects. The central control unit also receives physiological signals from the subjects collected by physiological signal acquisition equipment for stress induction and assessment.

[0028] VR headsets provide participants with a VR environment.

[0029] The environmental simulation equipment, physiological signal acquisition equipment, central control console, and VR headset are connected via wired or wireless means.

[0030] like Figures 1 to 2As shown, in a specific embodiment of the present invention, the hardware configuration of the isolation-enclosed cabin task-embedded stress-inducing device is as follows: including: a host (central control console), a VR headset, physiological signal acquisition equipment, and environmental simulation equipment (lighting, audio, and information delay simulation devices). The devices are connected via wired or wireless means to ensure data synchronization and low-latency control. The interior of the isolation cabin is equipped with: warm yellow LED lighting at the top of the cabin, with a color temperature of 1800K; portholes located at the front and sides of the isolation cabin, displaying black or static starry sky images on the outside, and a communication interruption icon with an exclamation mark on the portholes; an operating console and human-machine interface are provided inside the cabin, which can be configured as a ship, submarine, or spacecraft operating panel, including buttons, instrument panels, and displays, depending on the actual situation. The human-machine interface uses a communication panel displaying crew portraits, all in gray. The overall color scheme of the isolation cabin is dark and monotonous, emphasizing the sense of confinement and isolation. In this embodiment, the environmental simulation equipment includes: a lighting simulation device using a monochrome LED ceiling light with a color temperature of 1800K and PWM dimming; an audio simulation device that is level two with 45dB white noise output; and an information delay simulation device using an OLED porthole screen with a "communication interruption" icon and a 3s delay. The physiological signal acquisition equipment includes: a wristband-type physiological data acquisition device that collects real-time PPG heart rate sensor sampling rate (100Hz) and GSR skin conductance sensor sampling rate (4Hz). The VR headset uses a Meta Quest 3 with a ≥90Hz refresh rate. In this embodiment, the VR headset communicates with the host via HDMI / DisplayPort. The wristband-type physiological data acquisition device connects to the host via Bluetooth. The environmental simulation unit connects to the host via an RS485 bus. The host has a console / script management interface, including a monitor icon and a one-click reproduction button.

[0031] In addition to providing an isolation-sealed cabin task-embedded stress-inducing device, the present invention further provides an isolation-sealed cabin task-embedded stress-inducing system for controlling the above-mentioned device, the system comprising: The VR environment building module is used to construct virtual environments with characteristics such as monotonous lighting, information delay, and social isolation. The task and hazard integration module is used to embed four typical hazard events into the virtual task process: damage control, fire alarm, depth drop, and rudder jamming. Each hazard has three levels of parameter groups: light, medium, and heavy. The physiological monitoring and feedback control module is used to collect physiological signals such as heart rate, heart rate variability and skin conductivity of the subjects in real time, and dynamically adjust the danger parameters through the PID controller to keep the stress level of the subjects stable within the target level range. The experiment reproduction module is used to record and store experimental parameters and physiological data, and generate standardized scripts that can be replayed with one click, ensuring the consistency of multiple experiments on the same subject.

[0032] In one specific embodiment of the present invention, a VR-based three-level stress-inducing system for isolated and enclosed environments includes: The VR environment building module is used to generate and present virtual reality scenes that simulate isolated and enclosed environments. The environment simulation includes monotonous visual lighting, setting information delays, and social isolation elements. The task and hazard integration module stores task sequences bound to the standard operating procedures of the job, and can embed multiple preset hazard events, including damage control, fire alarm, depth drop, and rudder jamming, into the task sequences; the hazard events are configured with three levels of triggering parameter groups: light, medium, and heavy. The parameter groups include at least the event duration, the intensity of the fault manifestation, and the degree of information incompleteness. The physiological monitoring and feedback control module is used to collect the subjects' heart rate, heart rate variability and skin conductivity physiological signals in real time, and dynamically adjust the induction parameter group of the current dangerous event through a closed-loop controller based on the deviation between the physiological signals and the target stress level. The experiment reproduction module is used to record and store the scene configuration parameters, the sequence of triggered dangerous events and their corresponding dynamically adjusted parameters during the experiment, and generate a script file that can be executed repeatedly.

[0033] In this embodiment, the specific values ​​of the mild, moderate, and severe induced parameter groups are determined through pre-experiment calibration. The pre-experiment establishes a mapping relationship by collecting the subjective stress scores and physiological indicators of subjects under different parameter combinations of dangerous situations. The closed-loop controller is a PID controller with a control cycle of no more than 1 second and a system closed-loop delay of less than 200 milliseconds. The script file is stored in a structured data format, including a timeline, event type, stress level, event parameters, and environmental configuration information. In the VR environment construction module, monotonous visual lighting is simulated using a lighting with a color temperature of 1800K±100K, and the information delay is 3.0 seconds±0.2 seconds for the simulated information interface response delay. Social isolation elements include graying out social avatars in the virtual communication interface and playing background white noise. The physiological monitoring and feedback control module also includes a safety protection unit. When the subject's heart rate is detected to exceed the safety threshold calculated based on age, the current dangerous event is forcibly terminated and the subject enters a resting scenario. In the task and dangerous situation integration module, the binding relationship between dangerous events and job standard operating procedure steps is stored in the database, supporting queries and calls based on task steps or event types.

[0034] The present invention also provides a method for inducing embedded stress in isolated closed-cell work positions using the above-mentioned equipment, the method comprising the following steps: Step 1: The subject enters a sealed isolation chamber and performs routine job operations. Step 2: The system triggers the selected type and initial level of hazard events according to preset parameters or through the task and hazard integration module, thereby triggering the corresponding hazard events; Step 3: Collect physiological signals in real time through the physiological monitoring and feedback control module, and dynamically adjust the danger parameters to make the stress response of the subject approach and stabilize within the target level range; Step 4: After the experiment, save the complete experimental parameter script through the experiment reproduction module; Step 5: When a repeat experiment is required, load the script file to reproduce the exact same experimental scenario and event process with one click.

[0035] In this embodiment, the target stress level is defined by a threshold for changes in physiological indicators, which is calibrated and verified using pre-experimental data. Before loading the script file for reproduction, the system verifies the integrity of the script file; if the verification fails, loading is refused. Before each experiment, the system automatically performs hardware and software self-checks to ensure that the VR rendering frame rate, physiological sensor connection status, and controller initialization parameters meet preset standards. The program implementing this embodiment uses differential privacy technology with added noise when storing the subject's physiological data; the program is packaged as a containerized image, supporting rapid deployment and operation on various computing platforms that meet hardware requirements. The program implementing this embodiment includes a data storage interface for generating immutable evidence records from key log information of each experiment.

[0036] In one embodiment of the present invention, in step 2, a hazard-stress level mapping is set up for four types of job-related hazardous events (damage control, fire alarm, deep fall, and rudder jamming). Based on a preset or real-time selected hazard type and target stress level, a corresponding hazardous event is triggered. The stress level includes three levels: mild, moderate, and severe. The specific values ​​of the induced parameter groups for the mild, moderate, and severe levels are established by collecting the subjective stress scores and physiological indicators of subjects under different parameter combinations of hazardous events to establish a mapping relationship. In this embodiment, the standardized construction method of the mild, moderate, and severe stress level parameter mapping table includes the following steps: Step 2.1, Multi-dimensional hazard scenario prototype parameter design: For each type of emergency event, three quantifiable adjustment dimensions are defined, and initial parameter levels are set to generate a series of testable scenario prototypes: Step 2.1.1, Define Duration: Define the time from when the hazard is triggered until it can be resolved or escalated. Initial settings are: mild 3-8 seconds, moderate 8-15 seconds, severe 15-25 seconds.

[0037] Step 2.1.2: Set Fault Intensity: The severity of the fault presented in the VR environment through multimodal feedback is normalized to a scale of 0.0 to 1.0. For example, for "fire alarm", it can be represented by the speed of flame spread, smoke concentration and alarm sound intensity; for "depth drop", it can be represented by the amplitude of instrument pointer swing and cabin vibration feedback.

[0038] Step 2.1.3: Set the information missing rate: This refers to the percentage of missing or incorrect key information (such as instrument readings, command feedback, and situation map) required to complete emergency response, expressed as a percentage. For example, set 20% (minor missing, some minor information is unclear), 50% (moderate missing, key information is delayed or partially incorrect), and 80% (severe missing, information is seriously confused or interrupted).

[0039] Step 2.2, Standardized Pre-experiment and Synchronous Data Acquisition: Step 2.2.1, Subject Recruitment and Training: Recruit no fewer than 30 subjects with relevant backgrounds or who have undergone standardized training to familiarize them with the VR environment and basic operating procedures.

[0040] Step 2.2.2, Experimental Procedure Design: In the VR system, prototype scenarios with different parameter combinations (covering different levels of the three dimensions mentioned above) are randomly presented for each type of hazard. The scenarios are embedded in the regular job task sequence to ensure ecological validity.

[0041] Step 2.2.3, Multimodal Data Synchronous Acquisition: Subjective data: After each trial, participants were immediately asked to use a 9-point Likert scale for immediate stress self-assessment (1 = completely relaxed, 9 = extremely stressed), and the NASA-TLX scale was used to assess task load.

[0042] Physiological data: A synchronization scheme based on laboratory fluidized bed protocol or hardware TTL pulses is employed to ensure that VR event markers are aligned with physiological data timestamps. The following physiological signals are acquired in real time: 4-channel PPG signal: used to calculate heart rate and heart rate variability. Skin conductance signal: used to calculate skin conductance level and response frequency.

[0043] Step 2.3, Data Analysis and Level Threshold Calibration: Step 2.3.1, Data Preprocessing and Feature Extraction: The physiological signals of each trial segment are filtered and feature extracted. The core features include: the rate of change of heart rate relative to the baseline, the time-domain index of heart rate variability, and the average amplitude of skin conductance response.

[0044] Step 2.3.2, Unsupervised Clustering Preliminary Classification: The K-means clustering algorithm is used to cluster the physiological feature vectors of all trials, with a preset number of clusters of 3. This step aims to initially classify the trials into three categories based on the objective patterns of physiological responses.

[0045] Step 2.3.3: Establish the subjective-objective mapping relationship: Calculate the median self-rated subjective stress scores for all trials in each cluster.

[0046] Based on the median subjective ratings of the three clusters, from low to high, they were labeled as "mild", "moderate", and "severe" stress categories, respectively.

[0047] Step 2.3.4: Supervised Model Construction and Threshold Determination: Using the labeled data as the training set, a classification model is trained using linear discriminant analysis (LDA). This model can optimally distinguish three stress levels based on physiological characteristics. By analyzing the discriminant function and feature weights of the LDA model, the key physiological indicators used to differentiate the stress levels and their decision boundary values ​​are determined. For example, specific thresholds for "heart rate variability" between mild-moderate and moderate-severe stress levels (e.g., +8%, +15%) are determined.

[0048] Step 2.3.5, Scenario Parameter Backtracking Calibration: For each labeled stress level, backtrack and analyze the scenario parameters (duration, fault intensity, information loss rate) used in all trials that induced the response at that level. Take the mode or median of these parameter values ​​as the recommended parameter set for this type of hazard at that level.

[0049] Step 2.4, Generation and storage of structured mapping tables: The above calibration results are organized into a structured mapping table. Each entry corresponds to a (hazard type, stress level) combination, including: (1) Scene parameters: duration after calibration, fault intensity, and information loss rate.

[0050] (2) Physiological threshold reference range: the typical range of key physiological indicators (such as heart rate change rate) corresponding to this level.

[0051] (3) Subjective rating reference range: the typical range of subjective self-rating for this level.

[0052] This mapping table is stored in the system database in a structured format such as JSON or XML, and is called by the task and hazard integration module.

[0053] Step 2.5, Mapping Table Verification and Iteration: The constructed mapping table is validated using the following quantitative metrics to form a closed-loop optimization: (1) Validation of the success rate of induction: The mapping table was used to conduct induction experiments on new subjects. The success rate was calculated based on the standard that "both subjective scores and physiological indicators fall within the target range". The target is ≥85%.

[0054] (2) Accuracy verification of grading: Using reserved test data, calculate the accuracy of the stress level predicted by the LDA model based on physiological signals and the level based on subjective rating (gold standard) and the Kappa coefficient, with a target Kappa>0.6.

[0055] (3) Reproducibility verification: The experiment was reproduced using the same script after a period of time for the same subject, and the intraclass correlation coefficient of the core physiological indicators was calculated. The target ICC was >0.75.

[0056] (4) Ecological validity verification: The similarity between the sense of task immersion and the real job situation was assessed through post-event questionnaires and interviews.

[0057] If the above verification metrics fail to meet the target, return to step 2.1, adjust the prototype parameters of the emergency scenario, and re-execute the subsequent steps until the mapping table performance meets the requirements. The mapping table constructed above will be stored in the system database for use by the task and emergency integration module.

[0058] In this embodiment, the mapping table between the four types of job-related hazards and the three levels of stress parameters (light, medium, and severe) is shown in Table 1: Table 1. Mapping Table of Job Hazards and Stress Parameters for Light, Medium, and Severe Levels

[0059] Note: The parameter set was determined through pre-experiment calibration and is used to initialize emergency events.

[0060] like Figure 3 As shown, in one embodiment of the present invention, in step 3, the closed-loop controller is a PID controller with a control cycle of no more than 1 second and a system closed-loop delay of less than 200 milliseconds. In this embodiment, the closed-loop control process based on physiological feedback dynamically adjusts the parameters of the virtual emergency event by real-time monitoring of the subject's core physiological indicators to achieve precise and stable control of the stress level.

[0061] In this embodiment, the control objective and system architecture are defined as follows: Controlled quantity: The intensity of the subject's stress response, quantified as the overall deviation of physiological signals.

[0062] Key feedback indicator: Normalized heart rate variability. This is the core control signal, calculated as follows: ΔHR norm(t) = (HR current(t) – HR baseline ) / HR baseline * 100% Among them, HR baseline ΔHR is the mean heart rate during the resting or stable task period before the experiment. norm(t) For normalized heart rate variability, HRcurrent(t) This represents the current rate of change in heart rate.

[0063] Auxiliary monitoring indicators: skin conductance level, heart rate variability (SDNN). Used for verifying control effectiveness and safety monitoring.

[0064] 1. Control parameters (adjustment parameters): The adjustable parameter combination for the current emergency event, including: (1) Fault intensity factor (FI): range [0.0, 1.0], 0.0 corresponds to no fault performance, and 1.0 corresponds to the preset maximum visual, auditory and force feedback intensity.

[0065] (2) Information Interference Rate (IR): Range [0%, 100%], refers to the proportion of interface information that is blurry, jittery, erroneous or delayed.

[0066] (3) Sound pressure level (SL): range [0.0, 1.0], 0.0 corresponds to silence or background sound, 1.0 corresponds to the preset maximum alarm volume and harshness.

[0067] 2. Control target range: Set ΔHR based on the target stress level (mild, moderate, severe). norm The target scope. For example: Mild: ΔHR norm The target is +5% to +15%. Moderate: ΔHR norm The target is +15% to +30%. Severe: ΔHR norm The target is >+30%. In this embodiment, the closed-loop control process is specifically as follows: The control process is executed cyclically at a fixed period (e.g., Tc = 0.5 seconds), and the total system latency (from physiological signal acquisition to VR scene update) is strictly less than 200 milliseconds. The specific steps are as follows: Step 3.1: Signal Acquisition and Preprocessing At the start of each control cycle, the system reads the latest preprocessed heart rate value and calculates the current ΔHR. norm(t) .

[0068] Step 3.2, Error Calculation Calculate the error e(t) between the current physiological feedback and the target value: e(t) = ΔHR normtarget - ΔHR norm(t) Among them, ΔHR normtarget The target value for the normalized rate of change of heart rate is the midpoint of the target interval (e.g., 22.5% for moderate stress).

[0069] Step 3.3: PID controller calculates the adjustment amount. Using a digital PID controller, the required "stimulus regulation factor" K(t) is calculated: K(t) = Kp * e(t) + Ki * ∫e(t)dt + Kd * [de(t) / dt] Proportional term (Kp): Rapid response error. For example, Kp=0.05 means that for a 1% deviation in heart rate, the stimulus intensity will be adjusted by 0.05 accordingly.

[0070] Integral term (Ki): Eliminates steady-state error. For example, Ki = 0.005 is used to accumulate persistent deviations.

[0071] Differential term (Kd): Suppresses overshoot and predicts trends. For example, Kd=0.01, which reduces stimulation in advance when the heart rate rises rapidly.

[0072] Output limiting: K(t) is limited to [0.3, 1.5] to prevent over-adjustment.

[0073] Step 3.4: Dynamic Mapping and Updating of Hazard Parameters The adjustment factor K(t) is mapped to a specific adjustable parameter of the current risk situation. A weighted synchronous adjustment strategy is adopted: FI actual =FI initial * K(t) IR actual = min(100%, IR initial * K(t)) SL actual =SL initial * K(t) Wherein, FI represents the fault intensity factor: range [0.0, 1.0], where 0.0 corresponds to no fault performance, and 1.0 corresponds to the preset maximum visual, auditory, and tactile feedback intensity. IR represents the information interference rate: range [0%, 100%], referring to the proportion of blurred, jittery, erroneous, or delayed interface information. SL represents the sound pressure level: range [0.0, 1.0], where 0.0 corresponds to silence or background noise, and 1.0 corresponds to the preset maximum alarm volume and harshness. FI initial (Initial Fault Strength Factor), IR initial (Initial Information Disturbance Rate) and SL initial (Initial sound pressure level) is the initial parameter corresponding to the target level, retrieved from the mapping table. The system immediately sets FI... actual (Real-time Fault Intensity Factor), IR actual (Real-time information interference rate), SL actual(Real-time sound pressure level) is sent to the VR rendering engine to update the scene.

[0074] Step 3.5, Security Monitoring and Over-Limit Handling (Parallel Independent Processes) While the closed-loop control is operating, an independent safety protection unit continuously monitors the raw heart rate value. Once the heart rate is detected to exceed a safety threshold calculated based on age (e.g., HR), the unit will take action. max = 220 - age), or if the skin conductance spikes above the preset safety threshold within any consecutive 3 seconds, then immediately: 1. Force overwrite the PID output and set K(t) to 0.

[0075] 2. The current dangerous situation is terminated, and the VR scene switches to a relaxing "safe rest pod".

[0076] 3. Record the security event and issue an alert in the console.

[0077] Step 3.6: Recording and Iteration Within each control cycle, the system records the timestamp t and ΔHR. norm(t) The data includes e(t), K(t), and the updated risk parameters. These data are used to generate experimental scripts and can be used for subsequent optimization of PID parameters.

[0078] In one embodiment of the present invention, after the experiment, the system automatically packages the scene parameters, the sequence of dangerous events, physiological regulation records, etc. into a structured script file (such as JSON format), which supports one-click reproduction of the entire experiment process and ensures that the experimental results of the same subject or different subjects are comparable under the same parameters.

[0079] The effectiveness of this invention was verified using the following methods: 1. Validation of the success rate of induction: Determine whether the target stress level has been successfully induced through subjective scales and physiological indicators; 2. Validation of grading accuracy: Machine learning methods are used to classify physiological signals and assess their consistency with subjective grading. 3. Repeatability verification: The same subject repeats the same script experiment at different times, and the coefficient of variation of physiological indicators is calculated; Immersion Verification: An immersion questionnaire was used to assess the realism of the virtual environment and the sense of task engagement. Specific verification results are as follows: Figure 4 As shown.

[0080] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A stress-inducing device embedded in a closed-cell isolation work area, characterized in that: The device includes: The sealed isolation chamber was constructed according to the structure of the mission compartment. The environmental simulation equipment is installed inside a sealed isolation chamber to simulate corresponding hazardous environments based on virtual hazardous events. The physiological signal acquisition device is installed inside a sealed chamber to collect the physiological signals of the subjects in real time; The central control unit is equipped with a job-related hazard triggering system that simulates virtual hazard events to induce stress responses in the subjects. The central control unit also receives physiological signals from the subjects collected by physiological signal acquisition equipment for stress induction and assessment. VR headsets provide a VR environment for test subjects; The environmental simulation equipment, physiological signal acquisition equipment, central control console, and VR headset are connected via wired or wireless means.

2. The stress-inducing device embedded in a closed-cell isolation chamber as described in claim 1, characterized in that: The interior of the sealed isolation chamber is configured as follows: Warm-colored LED lighting is installed on the cabin ceiling; Portholes are located directly in front of and to the side of enclosed, isolated compartments; The cabin is equipped with an operating console and a human-machine interface.

3. The stress-inducing device embedded in a closed-cell isolation chamber as described in claim 1, characterized in that: The environmental simulation equipment includes: Lighting simulation device, audio simulation device, and information delay simulation device.

4. The stress-inducing device embedded in a closed-cell isolation chamber as described in claim 1, characterized in that: The physiological signal acquisition device includes: Wristband-type physiological data collection device.

5. A stress-inducing system embedded in a closed-cell isolation work area, characterized in that: The system is used to control the isolated closed chamber job-embedded stress induction device according to any one of claims 1-4, the system comprising: The VR environment building module is used to construct virtual environments with characteristics such as monotonous lighting, information delay, and social isolation. The task and hazard integration module embeds typical hazard events into the virtual task process and sets multi-level parameter groups for each type of hazard. The physiological monitoring and feedback control module collects the subject's physiological signals in real time and dynamically adjusts the danger parameters through a PID controller to stabilize the subject's stress level within the target range. Based on a closed-loop control process of physiological feedback, the physiological monitoring and feedback control module dynamically adjusts the parameters of the virtual danger event by monitoring the subject's core physiological indicators in real time to achieve precise and stable control of the stress level.

6. The isolated closed-cell task-embedded stress induction system as described in claim 5, characterized in that: The isolated closed chamber job task embedded stress induction system also includes an experiment reproduction module, which records and stores experimental parameters and physiological data, and generates standardized scripts that can be replayed with one click.

7. The isolated closed-cell task-embedded stress-inducing system as described in claim 6, characterized in that: The task and hazard integration module embeds four typical hazard events into the virtual task process, including damage control, fire alarm, depth drop, and rudder jamming. Each hazard has three levels of parameter groups: light, medium, and heavy.

8. A method for inducing embedded stress in a closed-cell isolation work environment, characterized in that: Using the device according to any one of claims 1-4, operate according to the following steps: Step 1: The subject enters the sealed isolation chamber and performs routine job operations. Step 2: The central control console triggers the corresponding emergency event based on the preset or real-time selected emergency type; Step 3: The physiological signal acquisition device collects physiological data in real time, and dynamically adjusts the intensity and duration of the emergency through a closed-loop controller; Step 4: After the experiment, save the scene parameters and adjustment records as a script file.

9. The method for inducing embedded stress in a closed-cell isolation work environment as described in claim 8, characterized in that: In step 2, a risk-stress level mapping is set up. Based on the preset or real-time selected risk type and target stress level, the corresponding risk event is triggered. The stress level includes three levels: mild, moderate, and severe. The specific values ​​of the three levels of triggering parameter groups are established by collecting the subjective stress scores and physiological indicators of the subjects under different parameter combinations of risk situations to establish a mapping relationship.

10. The method for inducing embedded stress in a closed-cell isolation work environment as described in claim 9, characterized in that: In step 3, the closed-loop controller is a PID controller with a control cycle of no more than 1 second and a system closed-loop delay of less than 200 milliseconds.

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