A highland environment personnel function damage risk active early warning visualization system

Abstract

The application discloses a plateau environment personnel function damage risk active early warning visualization system, and particularly relates to the technical field of health monitoring and safety early warning, and comprises a multi-modal data acquisition module, an edge data processing and alignment module, a hysteresis loop state space construction module, a function damage risk assessment module and a three-dimensional situation visualization early warning terminal; through collecting environment, motion load and physiological parameters, time-space synchronous alignment and denoising are carried out to generate effective hypoxia work index; orthogonal mapping force channels and biochemical channel characteristics are dynamically constructed to generate physiological response hysteresis loop state space; based on the hysteresis loop topological characteristics, the centroid drift vector amplitude, the coupling coherence coefficient and the comprehensive health risk index are calculated to execute graded early warning; the terminal superimposes the trajectory on the three-dimensional digital terrain map, renders the risk ripples and links the top pop-up hysteresis loop topological distortion trajectory; the application realizes active and accurate early warning of plateau operation damage risk.

Description

Technical Field

[0001] This invention relates to the field of health monitoring and safety early warning technology, and more specifically, to a proactive early warning visualization system for the risk of functional impairment in people in high-altitude environments. Background Technology

[0002] The complex terrain, high altitude, low pressure, low oxygen, and extreme cold of plateau regions pose a serious threat to the health and lives of workers. Those exposed to or prolonged exposure to high-altitude environments are highly susceptible to altitude sickness, high-altitude pulmonary edema, and high-altitude cerebral edema, among other forms of altitude-related functional impairment. Therefore, real-time monitoring and proactive early warning of health risks for workers operating at high altitudes are core technical means to ensure safety and reduce non-combat attrition in plateau operations.

[0003] However, existing high-altitude health monitoring and early warning methods have many shortcomings in practical applications. Traditional monitoring equipment mostly adopts a fixed threshold "over-limit alarm" mode. Due to the significant individual differences and delayed physiological compensation effects of high-altitude hypoxia injury, this "one-size-fits-all" delayed alarm often only triggers when organic lesions have already occurred in the body, failing to provide an early warning window. Although existing technologies can simultaneously collect environmental parameters and physiological indicators, they are mostly isolated monitoring of single indicators or simple linear weighting. Under complex multi-stress conditions of "heat load-hypoxia-physical labor," the multimodal data of the cardiovascular and respiratory systems exhibit nonlinear and asymmetric physical delays. Existing systems cannot effectively quantify the intrinsic biophysical mechanisms of the body's evolution from "cooperative compensation" to "desynchronized compensation," leading to easy confusion between high-load fatigue and compensatory function failure, resulting in high false alarm and false negative rates. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a proactive early warning visualization system for the risk of functional impairment in personnel in high-altitude environments, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a proactive early warning and visualization system for personnel functional impairment risk in high-altitude environments, comprising a multimodal data acquisition module, an edge data processing and alignment module, a hysteresis loop state space construction module, a functional impairment risk assessment module, and a three-dimensional situation visualization and early warning terminal;

[0006] The multimodal data acquisition module is used to acquire real-time field environmental data, exercise load data, and physiological characteristic signals of workers in high-altitude environments.

[0007] The edge data processing and alignment module is connected to the multimodal data acquisition module and is used to perform spatiotemporal synchronization alignment and noise reduction on the acquired multimodal data, and calculate the effective hypoxia work index based on the aligned data.

[0008] The hysteresis loop state space construction module is used to extract force channel features that characterize the compensatory driving force of the cardiovascular system of workers, as well as biochemical channel features that characterize tissue oxygenation and metabolic state; the force channel features and the biochemical channel features are respectively used as orthogonal control axes and mapped to a two-dimensional state space, and physiological response hysteresis loops are dynamically generated over time.

[0009] The functional damage risk assessment module is used to extract the topological geometric features of the physiological response hysteresis loop in real time, calculate the centroid drift vector amplitude and coupling coherence coefficient of the physiological response hysteresis loop relative to the individual's resting baseline state, and construct a comprehensive health risk index in combination with the effective hypoxia work index, so as to calculate and characterize the biophysical damage risk of the body from the collaborative compensation stage to the desynchronization compensation stage in real time.

[0010] The three-dimensional situation visualization and early warning terminal is connected to the functional damage risk assessment module. It is used to dynamically map the comprehensive health risk index and the topological distortion state of the physiological response hysteresis loop into hierarchical early warning visual elements, and to present the situation perception in an integrated manner on the three-dimensional geographic information platform.

[0011] Preferably, as a preferred embodiment of the active early warning visualization system for personnel functional impairment risk in high-altitude environments described in this invention, it includes the multimodal data acquisition module, which includes an environmental sensor unit, a wearable physiological monitoring unit, and a motion inertial navigation unit;

[0012] The environmental sensor unit is integrated into the housing of a portable terminal worn by the operator and is used to collect environmental parameters including altitude, atmospheric pressure, temperature and oxygen partial pressure; wherein, the environmental sensor unit includes a piezoresistive digital meteorological pressure sensor as a barometer, a semiconductor digital temperature sensor and an electrochemical oxygen sensor.

[0013] The wearable physiological monitoring unit is attached to the skin surface of the worker in the form of a skin patch to collect physiological parameters including heart rate, blood oxygen saturation, respiratory rate, body temperature, and sweat electrolyte concentration. The wearable physiological monitoring unit includes a multi-wavelength photoplethysmography (PPG) sensor group, a patch-type negative temperature coefficient thermistor array, and a flexible microfluidic sweat collection chip deployed on the worker's body. The flexible microfluidic sweat collection chip has a built-in ion-selective electrode.

[0014] The motion inertial navigation unit is rigidly fixed at the center of gravity of the worker's torso and is used to collect acceleration and three-dimensional trajectory data characterizing physical load; wherein, the motion inertial navigation unit includes a three-axis accelerometer, a three-axis gyroscope, and a dual-mode positioning chip of Global Positioning System and Beidou Satellite Navigation System integrated in a microelectromechanical system;

[0015] It should be specifically noted that, during operation, the multimodal data acquisition module is triggered by a unified clock source to implement a synchronization control mechanism. The data acquired by the environmental sensor unit, wearable physiological monitoring unit, and motion inertial navigation unit within the same sampling period are encapsulated in the local microcontroller unit as multimodal sensing data frames with the same source timestamp. The multimodal sensing data frames are synchronously transmitted to the backend edge data processing and alignment module through a low-power wireless communication network.

[0016] Preferably, as a preferred embodiment of the active early warning visualization system for personnel functional impairment risk in high-altitude environments according to the present invention, it includes the edge data processing and alignment module, specifically including the following:

[0017] Extract the same source timestamps from each received raw data stream, use a preset time step as the standard time grid, and use cubic spline interpolation to reconstruct and align physiological data, exercise load data and environmental data on the time axis;

[0018] Using the triaxial acceleration signal output by the motion inertial navigation unit as a reference noise source, an adaptive filter is used to filter out motion artifacts in the photoplethysmography pulse wave signal and the respiratory signal; and a wavelet packet transform algorithm is used to smooth and denoise the environmental air pressure and altitude data.

[0019] Within a set time window, the elevation gradient is calculated by taking the first derivative of the aligned dynamic elevation; the measured local oxygen partial pressure is obtained and its deficit ratio relative to the standard sea level oxygen partial pressure is calculated; the elevation gradient and the deficit ratio are integrated and summed to construct the environmental exposure accumulation factor.

[0020] The denoised triaxial acceleration signal is integrally shaped over a full wave to calculate the dynamic motion energy value. The effective hypoxia work index is calculated using a nonlinear exponential coupling formula. The effective hypoxia work index is equal to the dynamic motion energy value multiplied by the power of the base of the natural logarithm, where the exponent of the power is the product of a preset plateau environment sensitivity coefficient and the environmental exposure accumulation factor.

[0021] Preferably, as a preferred embodiment of the active early warning visualization system for personnel functional impairment risk in high-altitude environments according to the present invention, it includes the hysteresis loop state space construction module, specifically including the following:

[0022] The input physiological signals are windowed to extract force channel features and biochemical channel features. The force channel features include heart rate variability and blood pressure variability. The heart rate variability includes the root mean square value and standard deviation of the difference between adjacent heartbeats, while the blood pressure variability is extracted based on a pulse wave transit time estimation algorithm. The biochemical channel features include the rate of change of blood oxygen saturation, the trend of respiratory rate evolution, and the variability of sweat electrolytes. The rate of change of blood oxygen saturation is calculated based on first-order difference, the trend of respiratory rate evolution is extracted based on polynomial fitting, and the variability of sweat electrolytes is obtained by calculating the variance of sweat sodium and potassium ion concentrations.

[0023] The baseline values ​​of resting heart rate variability and resting blood oxygen saturation of the workers in a completely quiet state are obtained. The range normalization algorithm is used to convert the force channel features and the biochemical channel features extracted in real time into dimensionless standardized relative scalars with numerical ranges limited to zero and one.

[0024] Using the dimensionless force channel features as the x-axis and the dimensionless biochemical channel features as the y-axis, an orthogonal two-dimensional geometric state space is constructed.

[0025] Within a preset rolling monitoring window, aligned horizontal and vertical coordinate data points are continuously projected onto a point set trajectory in a two-dimensional geometric state space. As time evolves, the projected point set is connected to generate a closed dynamic physiological response hysteresis loop.

[0026] Preferably, as a preferred embodiment of the active early warning visualization system for personnel functional impairment risk in high-altitude environments according to the present invention, it includes the functional impairment risk assessment module, specifically including the following:

[0027] Morphological features are extracted from the physiological response hysteresis loop generated within the current rolling monitoring window. The topological geometric features include the hysteresis loop area, eccentricity, and geometric centroid coordinates. The hysteresis loop area is obtained by performing Green's formula discrete integral on the two-dimensional region enclosed by the hysteresis loop closed curve. The eccentricity is obtained by calculating the ratio of the focal length to the major axis length of the optimal circumscribed ellipse of the hysteresis loop trajectory. The geometric centroid coordinates are obtained by performing first-order geometric moments on the set of all orthogonal projection points of the hysteresis loop trajectory.

[0028] After extracting the above topological features, the degree of deviation and co-degeneration of the organism's physiological state is quantified, specifically including:

[0029] Calculate the centroid drift vector amplitude: Obtain the reference centroid coordinates of the reference hysteresis loop established under the worker's resting state, calculate the Euclidean distance between the geometric centroid coordinates of the hysteresis loop in the current time window and the reference centroid coordinates. The Euclidean distance is obtained by adding the square of the difference between the current geometric centroid abscissa and the reference centroid abscissa, plus the square of the difference between the current geometric centroid ordinate and the reference centroid ordinate, and then taking the square root of the sum.

[0030] Calculate the coupling coherence coefficient: Using the cross-spectral density algorithm, perform frequency domain correlation analysis on the original force channel signal and biochemical channel signal that construct the physiological response hysteresis loop to obtain the coupling coherence coefficient;

[0031] A comprehensive health risk index is calculated using a nonlinear weighted coupling formula. The comprehensive health risk index is equal to the product of the effective hypoxia work index and the magnitude of the centroid drift vector, divided by the coupling coherence coefficient. The comprehensive health risk index is then calculated based on the nonlinear weighted coupling formula, using the effective hypoxia work index. The comprehensive health risk index is equal to the product of the effective hypoxia work index and the magnitude of the centroid drift vector, divided by the coupling coherence coefficient.

[0032] The calculated comprehensive health risk index, the centroid drift vector amplitude, and the coupling coherence coefficient are compared in real time with a preset multivariate safety threshold matrix. The following graded early warning judgments are then executed, and corresponding instructions and visual driving signals are output:

[0033] Attention-level warning: When the area of ​​the hysteresis loop shows an increasing trend, the amplitude of the centroid drift vector is less than a preset first threshold, and the coupling coherence coefficient is higher than a preset safety boundary, an attention-level warning is triggered, and a command to restrict physical activity and a yellow visual drive signal are output.

[0034] Warning-level alert: When the magnitude of the centroid drift vector is greater than a preset first threshold and the coupling coherence coefficient shows a downward trend within a continuous preset period, a warning-level alert is triggered, and an instruction to stop the current operation and immediately inhale oxygen is output, as well as an orange visual drive signal.

[0035] Danger warning: When the trajectory of the physiological response hysteresis loop is not closed, the geometric centroid coordinates accelerate and drift, and the coupling coherence coefficient falls below the preset limit of step loss threshold, a danger warning is triggered, and emergency evacuation and medical rescue instructions are output, as well as a red visual flashing drive signal.

[0036] Preferably, as a preferred embodiment of the active early warning and visualization system for personnel functional impairment risk in high-altitude environments according to the present invention, it includes the three-dimensional situation visualization and early warning terminal, specifically including the following:

[0037] Run a 3D geographic information platform built on geographic information system and digital twin engine, load high-precision digital elevation model data and satellite remote sensing image data to generate 3D digital topographic map; receive 3D spatial absolute trajectory data output by motion inertial navigation unit, generate virtual entity labels representing workers on the geographic coordinates of 3D digital topographic map, and generate the movement trajectory line of workers on the surface of 3D digital topographic map through real-time coordinate updates.

[0038] Based on the graded early warning logic output by the functional impairment risk assessment module and the corresponding visual driving signal, the virtual entity label and movement trajectory line are dynamically rendered:

[0039] When the operator's warning status is at the attention level, respond to the yellow drive signal and render the virtual entity label in yellow;

[0040] When the warning status is at the alert level, respond to the orange drive signal and render the virtual entity label in orange;

[0041] When the warning status is at the danger level, respond to the red drive signal, render the virtual entity label as bright red and perform visual flashing at a preset frequency;

[0042] When the operator triggers the warning level or the danger level warning, a risk ripple aura that dynamically spreads outward on a three-dimensional digital terrain map is rendered with the operator's current geographical coordinates as the geometric center. The diffusion radius of the risk ripple aura is proportional to the centroid drift vector amplitude output in real time by the functional damage risk assessment module.

[0043] When an operator triggers the warning level alert or the hazard level alert, the following interactive steps are also performed:

[0044] The interface interrupts the response and forcibly pops up a secondary monitoring window in the sidebar of the command screen. It dynamically draws the dynamic trajectory of the topological distortion of the two-dimensional physiological response hysteresis loop of the operator. In conjunction with the two-dimensional physiological response hysteresis loop, a discrete digital stream containing the instantaneous value of the rate of decline of blood oxygen saturation, the scalar value of the increase of sweat sodium ion concentration, and the percentage of the proportion of environmental oxygen partial pressure deficit is displayed in a dynamic one-dimensional time series data matrix below the two-dimensional physiological response hysteresis loop.

[0045] On the other hand, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements the functional modules of a proactive early warning visualization system for personnel functional impairment risk in high-altitude environments as described above.

[0046] On the other hand, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements a proactive early warning visualization system for the risk of functional impairment of personnel in high-altitude environments as described above.

[0047] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0048] This invention achieves strict synchronous acquisition of environmental parameters, physiological signals, and exercise load through a multimodal data acquisition module. Combined with spatiotemporal alignment and denoising processing by an edge data processing and alignment module, it effectively improves data quality and usability. The hysteresis loop state space construction module maps force channel and biochemical channel features into a two-dimensional physiological response hysteresis loop. The functional damage risk assessment module extracts the centroid drift vector amplitude and coupling coherence coefficient of the loop to construct a comprehensive health risk index, which can accurately quantify the early biophysical signals of the body's evolution from "cooperative compensation" to "desynchronized compensation". Compared with the traditional fixed threshold alarm mode, it can identify the failure window of the compensation function several hours in advance, significantly reducing the false alarm rate and missed alarm rate. At the same time, the three-dimensional situation visualization early warning terminal uses a geographic information platform as a carrier to realize the integrated presentation of hierarchical early warning and risk heat map, providing an intuitive and accurate means of safety situation cognition for command and decision-making in plateau operations. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0050] Figure 1 This is a flowchart of a method for a proactive early warning visualization system for the risk of functional impairment in personnel in high-altitude environments, as described in this invention. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0052] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0053] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0054] Example 1

[0055] This embodiment provides, for example Figure 1 The system shown is a proactive early warning visualization system for personnel functional impairment risk in high-altitude environments, which specifically includes a multimodal data acquisition module, an edge data processing and alignment module, a hysteresis loop state space construction module, a functional impairment risk assessment module, and a three-dimensional situation visualization early warning terminal.

[0056] The multimodal data acquisition module is used to acquire real-time field environmental data, exercise load data, and physiological characteristic signals of workers in high-altitude environments.

[0057] The edge data processing and alignment module is connected to the multimodal data acquisition module and is used to perform spatiotemporal synchronization alignment and noise reduction on the acquired multimodal data, and calculate the effective hypoxia work index based on the aligned data.

[0058] The hysteresis loop state space construction module is used to extract force channel features that characterize the compensatory driving force of the cardiovascular system of workers, as well as biochemical channel features that characterize tissue oxygenation and metabolic state; the force channel features and the biochemical channel features are respectively used as orthogonal control axes and mapped to a two-dimensional state space, and physiological response hysteresis loops are dynamically generated over time.

[0059] The functional damage risk assessment module is used to extract the topological geometric features of the physiological response hysteresis loop in real time, calculate the centroid drift vector amplitude and coupling coherence coefficient of the physiological response hysteresis loop relative to the individual's resting baseline state, and construct a comprehensive health risk index in combination with the effective hypoxia work index, so as to calculate and characterize the biophysical damage risk of the body from the collaborative compensation stage to the desynchronization compensation stage in real time.

[0060] The three-dimensional situation visualization and early warning terminal is connected to the functional damage risk assessment module. It is used to dynamically map the comprehensive health risk index and the topological distortion state of the physiological response hysteresis loop into hierarchical early warning visual elements, and to present the situation perception in an integrated manner on the three-dimensional geographic information platform.

[0061] In this embodiment, the multimodal data acquisition module needs to be specifically described. This module includes an environmental sensor unit, a wearable physiological monitoring unit, and a motion inertial navigation unit, and is used to acquire real-time on-site environmental data, exercise load data, and physiological characteristic signals of workers in high-altitude environments. Specifically, it includes the following:

[0062] The environmental sensor unit is used to collect environmental parameters including altitude, atmospheric pressure, temperature, and oxygen partial pressure. The environmental sensor unit is integrated into the housing of a portable terminal worn by the operator and is in direct contact with the outside air. Specifically, atmospheric pressure and altitude monitoring uses a high-precision piezoresistive digital meteorological pressure sensor as a barometer. By measuring the current absolute atmospheric pressure and based on the mapping formula between standard atmospheric pressure and altitude, the dynamic altitude of the operator is calculated in real time. Temperature monitoring uses a semiconductor digital temperature sensor to acquire the current external temperature of the plateau environment in real time, providing a benchmark for subsequent physiological parameters to compensate for vasoconstriction under cold stress. Oxygen partial pressure monitoring uses a miniature electrochemical oxygen sensor to extract the local oxygen partial pressure in the air in real time. By co-calibrating oxygen partial pressure with dynamic altitude, the actual intensity of hypoxia exposure caused by sudden meteorological changes is accurately characterized, eliminating misjudgments of environmental hypoxia caused by a single altitude indicator.

[0063] The wearable physiological monitoring unit is used to collect physiological parameters including heart rate, blood oxygen saturation, respiratory rate, body temperature, and sweat electrolyte concentration. The wearable physiological monitoring unit is a multi-site skin patch that adheres tightly to the subject's skin surface. Heart rate and blood oxygen saturation monitoring utilizes a PPG sensor array deployed on the wrist, ear, and forehead. It calculates the real-time heart rate and pulse oxygen saturation of the worker at high frequency using the light intensity attenuation rate during the reflection of red and infrared light. The PPG sensor array refers to a multi-wavelength photoplethysmography (PPG) sensor array. Respiratory rate monitoring is achieved by extracting P… The respiratory modulation baseline drift characteristics and low-frequency fluctuations in the interval between beats of the PG sensor group output signal are used to invert and calculate the real-time respiratory rate of the worker; body temperature monitoring uses a patch-type high-precision negative temperature coefficient thermistor array to dynamically monitor the core torso temperature and peripheral skin temperature of the worker; sweat electrolyte concentration monitoring uses a flexible microfluidic sweat collection chip attached to the inner forearm and back of the worker. The chip has built-in ion-selective electrodes. When the worker sweats due to high-load work, the sweat is introduced into the microchannel through capillary force to measure the sodium ion concentration, potassium ion concentration and lactic acid level in the sweat in real time.

[0064] The motion inertial navigation unit is used to collect acceleration and three-dimensional trajectory data characterizing physical load. The motion inertial navigation unit is rigidly fixed at the center of gravity of the worker's torso. Acceleration monitoring uses a three-axis accelerometer and a three-axis gyroscope integrated in a microelectromechanical system to acquire the worker's linear acceleration and angular velocity in three-dimensional space in real time at a sampling frequency of not less than 100Hz. By performing time-domain integration and frequency-domain energy spectrum analysis on the linear acceleration, the individual's motion energy consumption value within the current time window is calculated in real time, serving as the core feature for quantitatively characterizing the intensity of physical load. Three-dimensional trajectory monitoring uses a dual-mode positioning chip of GPS and Beidou satellite navigation systems, combined with a pedestrian dead reckoning inertial navigation algorithm, to output the worker's three-dimensional absolute trajectory data in the plateau terrain, including longitude, latitude, and relative ground altitude.

[0065] It should be specifically noted that, during operation, the multimodal data acquisition module is triggered by a unified clock source to implement a synchronization control mechanism. The data acquired by the environmental sensor unit, wearable physiological monitoring unit, and motion inertial navigation unit within the same sampling period are encapsulated in the local microcontroller unit into multimodal sensing data frames with the same source timestamp. The multimodal sensing data frames are synchronously transmitted to the backend edge data processing and alignment module through a low-power wireless communication network, realizing the coordinated perception of "environmental stress - physical load - physiological compensation" in a three-in-one manner at the hardware front end.

[0066] In this embodiment, the edge data processing and alignment module is specifically described. This module is connected to the multimodal data acquisition module and is used to perform spatiotemporal synchronization alignment and noise reduction on the acquired multimodal data. Based on the aligned data, it calculates the effective hypoxic work index, specifically including the following:

[0067] The received raw data stream is aligned and denoised. The same source timestamps in each data stream are extracted. A preset time step of 1 second is used as the standard time network. Cubic spline interpolation is used to reconstruct and align physiological data, exercise load data and environmental data at the location on the time axis to ensure that the environmental stress at the same moment can accurately correspond to the physiological response and physical load of the human body.

[0068] In this embodiment, the module uses the triaxial acceleration signal output by the motion inertial navigation unit as a reference noise source, and uses an adaptive filter to dynamically filter out motion artifacts in the PPG signal and breathing signal; and uses a wavelet packet transform algorithm to smooth and denoise the environmental air pressure and altitude data, and removes instantaneous air pressure change noise caused by body swaying and local wind speed.

[0069] After data alignment and denoising, the environmental exposure accumulation factor is calculated based on the real-time elevation gradient and current oxygen partial pressure. The specific calculation method is as follows:

[0070] Real-time altitude gradient calculation: Within a set time window, the first derivative of the aligned dynamic altitude is calculated to determine the current person's altitude gradient.

[0071] Quantification of hypoxia stress intensity: Obtain the current measured local oxygen partial pressure and calculate its deficit ratio relative to the standard sea level oxygen partial pressure to quantify absolute hypoxia stress;

[0072] Construction of cumulative factor: The cumulative environmental exposure factor is constructed by integrating and summing the altitude gradient and the oxygen partial pressure deficit ratio. The cumulative environmental exposure factor can not only reflect the severity of hypoxia at present, but also effectively characterize the cumulative effect of acute exposure stress at high altitude due to the large altitude gradient and the body's inability to adapt.

[0073] The environmental exposure accumulation factor is nonlinearly coupled with physical load characterized by acceleration to generate an effective hypoxia work index that characterizes the total actual compensatory input of an individual under the current environmental load. The specific coupling mechanism is as follows:

[0074] Quantification of physical load: The denoised triaxial acceleration signal is integrally shaped over the whole wave to calculate the dynamic motion energy value that represents the current intensity of physical exertion of the human body.

[0075] Nonlinear coupling calculation: The effective hypoxia work index is calculated using a nonlinear exponential coupling formula. The effective hypoxia work index is equal to the dynamic motion energy value multiplied by the power of the base of the natural logarithm, where the exponent of the power is the product of the preset plateau environment sensitivity coefficient and the environmental exposure accumulation factor.

[0076] The effective hypoxia work index generated by the above nonlinear coupling integrates the external physical pressure of hypoxia in the environment with the internal work done by the body's autonomous movement into a unified metric, which accurately represents the total actual compensatory input that an individual makes to maintain life activities and work capacity under the current specific spatiotemporal environmental load.

[0077] In this embodiment, the hysteresis loop state space construction module is specifically described. This module extracts force channel features characterizing the compensatory driving force of the cardiovascular system in workers, as well as biochemical channel features characterizing tissue oxygenation and metabolic states. The force channel features and biochemical channel features are then mapped onto a two-dimensional state space as orthogonal control axes, dynamically generating a physiological response hysteresis loop over time. Specifically, this includes the following:

[0078] The input denoised physiological signal is processed in parallel through windowing to decouple and extract independent force channel features and biochemical channel features, including:

[0079] The force channel features include heart rate variability indicators and blood pressure variability indicators; by performing beat-by-beat time-domain analysis on continuous photoplethysmography pulse wave signals, heart rate variability indicators representing the intensity of autonomic cardiovascular regulation are calculated, including the root mean square value and standard deviation of the difference between adjacent heartbeats; combined with the pulse wave conduction time estimation algorithm, blood pressure variability indicators are continuously extracted.

[0080] The biochemical channel features include the rate of change of blood oxygen saturation, the trend of respiratory rate evolution, and the variability of sweat electrolytes. The rate of change of blood oxygen saturation is obtained by first-order difference calculation of real-time blood oxygen saturation within a set time window; the trend of respiratory rate evolution is extracted by polynomial fitting of respiratory rate; and the variance of sweat sodium and potassium ion concentrations output by microfluidic sensors is calculated to obtain the variability of sweat electrolytes. The biochemical channel features directly reflect the actual hypoxia and metabolic damage state of the body's tissue cells from the dimensions of peripheral metabolism, gas exchange, and tissue oxygenation.

[0081] Perform dimensionless normalization processing before mapping:

[0082] Physiological baseline values ​​of workers in a completely quiet state are obtained, including baseline values ​​of resting heart rate variability and resting blood oxygen saturation. The range normalization algorithm is used to convert the real-time extracted force channel features and biochemical channel features into dimensionless standardized relative scalars with numerical ranges limited to zero and one, so as to eliminate the influence of dimensional differences on spatial geometric topology.

[0083] After completing the dimensionless feature processing, the hysteresis loop state space construction module uses the dimensionless force channel features as the x-axis and the dimensionless biochemical channel features as the y-axis to construct an orthogonal two-dimensional geometric state space, specifically including:

[0084] Dynamic time window continuous projection: Within each preset rolling monitoring time window, the aligned horizontal and vertical coordinate data points are continuously projected onto the two-dimensional geometric state space to depict the trajectory of the point set.

[0085] Temporal evolution and memory effect quantification: As workers dynamically operate and time evolves in the high-altitude low-oxygen environment, the above-mentioned projection point set is plotted in the state space to draw a closed dynamic hysteresis curve that records the body's response delay and system memory effect, generating a physiological response hysteresis loop.

[0086] In this embodiment, the functional impairment risk assessment module is specifically described. This module is used to extract the topological geometric features of the physiological response hysteresis loop in real time, calculate the centroid drift vector amplitude and coupling coherence coefficient of the physiological response hysteresis loop relative to the individual's resting baseline state, and construct a comprehensive health risk index by combining it with the effective hypoxia work index. This index is used to calculate and characterize the biophysical impairment risk of the body transitioning from a coordinated compensation stage to a desynchronized compensation stage in real time. Specifically, it includes the following:

[0087] By calling the geometric topology analysis algorithm, the morphological features of the physiological response hysteresis loop generated within the current rolling monitoring window are extracted. The topological geometric features specifically include the hysteresis loop area, eccentricity, and geometric centroid coordinates.

[0088] The hysteresis loop area is calculated by performing Green's formula discrete integration on the two-dimensional pixel region enclosed by the hysteresis loop closed curve within the time window to obtain the absolute area of ​​the hysteresis loop. The size of the hysteresis loop area directly reflects the degree of time delay and compensatory energy loss between the body's cardiovascular regulation and peripheral oxygenation response.

[0089] The eccentricity is obtained by fitting the optimal circumscribed ellipse of the hysteresis loop trajectory, calculating the ratio of the focal length to the major axis length of the ellipse, and is used to characterize the nonlinear distortion direction of the dual-channel response.

[0090] The geometric centroid coordinates are calculated by performing a first-order geometric moment calculation on the set of all orthogonal projection points that make up the current hysteresis loop trajectory, in order to determine the two-dimensional geometric centroid coordinates of the hysteresis loop within the current time window.

[0091] After extracting the above topological features, the degree of deviation and co-degeneration of the organism's physiological state is quantified, specifically including:

[0092] Calculation of centroid drift vector amplitude: Obtain the two-dimensional reference centroid coordinates of the reference hysteresis loop established by the subject in a completely quiet state. The centroid drift vector amplitude is obtained by calculating the Euclidean distance between the geometric centroid coordinates of the hysteresis loop in the current time window and the reference centroid coordinates. The specific calculation method is as follows: Take the square root of the sum of the square difference between the current geometric centroid abscissa and the reference centroid abscissa, the square difference between the current geometric centroid ordinate and the reference centroid ordinate, and the square root of the sum to obtain the centroid drift vector amplitude, which is used to quantitatively characterize the current overall compensatory load intensity of the body.

[0093] Calculation of coupling coherence coefficient: By using the cross-spectral density algorithm, frequency domain correlation analysis is performed on the original force channel signal and biochemical channel signal that construct the hysteresis loop, and the degree of synergy between the two under the current stress state is calculated to obtain the coupling coherence coefficient, which is used to quantitatively characterize the degree of synergy between the subject's cardiopulmonary system and autonomic nervous system.

[0094] The obtained centroid drift vector amplitude, coupling coherence coefficient, and effective hypoxia work index are dynamically weighted and coupled to construct a comprehensive health risk index. The specific construction method is as follows:

[0095] The comprehensive health risk index is equal to the product of the effective hypoxia work index and the center of mass drift vector amplitude, divided by the coupling coherence coefficient. When the external environmental load and the effective hypoxia work index increase, and the center of mass drift vector amplitude of the body increases, while the coupling coherence coefficient decreases, the comprehensive health risk index will show a non-linear and drastic amplification, which can extremely sensitively quantify the intrinsic damage risk of the body evolving from "inter-system collaborative compensation" to "desynchronized compensation".

[0096] The calculated comprehensive health risk index, centroid drift vector amplitude, and coupling coherence coefficient are compared in real time with a preset multivariate safety threshold matrix. The following graded early warning logic is executed, and the early warning results are driven by specific color coding on the backend display terminal:

[0097] Attention-level warning: When calculations show that the hysteresis loop area is expanding, the centroid drift vector amplitude is less than the preset first threshold, and the coupling coherence coefficient is higher than the preset safety boundary, the body is determined to be in the "cooperative compensation period", triggering an attention-level warning, outputting a command to restrict physical activity, and presenting it in the system as a yellow visual element;

[0098] Warning level alert: When the centroid drift vector amplitude is greater than the preset first threshold and the coupling coherence coefficient shows a trend of decreasing within a continuous preset period, the body is determined to be on the "edge of decompensation", triggering a warning level alert, outputting the command to stop the current operation and immediately inhale oxygen, and presenting it in the system with an orange visual element;

[0099] Danger Level Warning: When the hysteresis loop trajectory becomes disordered and cannot be closed, the centroid accelerates and drifts, and the coupling coherence coefficient falls below the preset limit of out-of-synchronization threshold, it is determined that the body has entered the acute injury prodromal window period of multi-system "loss of synchronization compensation", triggering the highest level danger level warning, outputting emergency evacuation and medical rescue instructions, and displaying them in the system as flashing red visual elements.

[0100] In this embodiment, the three-dimensional situation visualization and early warning terminal is specifically described. This terminal is connected to the functional impairment risk assessment module and is used to dynamically map the comprehensive health risk index and the topological distortion state of the physiological response hysteresis loop into hierarchical early warning visual elements, and to present them in an integrated situational awareness manner on a three-dimensional geographic information platform. Specifically, this includes the following:

[0101] The three-dimensional situation visualization and early warning terminal has a built-in three-dimensional geographic information platform based on a geographic information system and a digital twin engine. This platform loads high-precision digital elevation model data and satellite remote sensing image data of the work area, seamlessly reconstructing a three-dimensional digital topographic map containing elevation variations, terrain features, and slope direction. It receives and overlays the dynamic positions and movement trajectories of each worker on the three-dimensional digital topographic map in real time. Specifically, it includes:

[0102] Based on the three-dimensional spatial absolute trajectory data output by the motion inertial navigation unit, virtual entity labels representing workers are generated on the corresponding geographic coordinates of the three-dimensional digital terrain map, and the real-time movement trajectory lines of the workers are outlined on the surface of the terrain map through continuous coordinate updates.

[0103] Based on the graded early warning logic output by the functional injury risk assessment module, the visual features of the virtual entity tags and movement trajectory lines of the workers are dynamically mapped, specifically including:

[0104] When a subject's alert status is at the attention level, the terminal receives a yellow drive signal and renders the subject's virtual entity label on the 3D terrain map as yellow.

[0105] When the warning status is upgraded to the alert level, the terminal receives an orange drive signal and renders the virtual entity label color as orange;

[0106] When the warning status is upgraded to the danger level, the terminal receives a red drive signal, renders the virtual entity label color as bright red, and visually flashes at a preset frequency to forcibly attract the visual attention of the management personnel.

[0107] The three-dimensional situation visualization and early warning terminal is equipped with a spatial dynamic rendering mechanism:

[0108] Dynamic triggering: When a worker triggers a warning-level alert, the 3D situation visualization and early warning terminal immediately renders and generates a risk ripple aura that dynamically spreads outward on a horizontal plane on the 3D digital terrain map, with the worker's current geographical coordinates as the geometric center.

[0109] Nonlinear mapping of dimensions: The diffusion radius of the risk ripple aura is proportional to the amplitude of the centroid drift vector output in real time by the functional injury risk assessment module; specifically, the heavier the individual's compensatory load and the larger the amplitude of the centroid drift vector, the larger the physical radius area of ​​the risk ripple aura below the worker on the three-dimensional topographic map; through this spatial visual mapping, the commander does not need to read specific values, but can directly assess the severity of the worker's health crisis through the visual area of ​​the aura;

[0110] The three-dimensional situation visualization and early warning terminal is also equipped with a local multi-dimensional linkage and collaborative interactive interface, including:

[0111] Forced pop-up window: When a worker triggers the warning level alert, the visualization screen of the three-dimensional situation visualization warning terminal immediately triggers the highest priority dynamic interface interruption response, forcibly popping up an independent secondary monitoring window in the sidebar area of ​​the command screen.

[0112] Dynamic rendering of topological distortion trajectory: In the secondary monitoring window that pops up forcibly, the three-dimensional situation visualization and early warning terminal will dynamically draw the dynamic trajectory of the topological distortion of the two-dimensional physiological response hysteresis loop of the test subject; by dynamically refreshing the orthogonal projection points and lines of the force channel features on the horizontal axis and the biochemical channel features on the vertical axis, the command personnel can intuitively see the dynamic evolution animation of the expansion of the hysteresis loop area, the trajectory disorder and the deviation of the centroid from the reference state.

[0113] The evolution diagram of core risk factors is presented as follows: The time series evolution data of core risk factors is rendered collaboratively below the hysteresis loop. Specifically, it includes: the instantaneous value of the rate of decline of blood oxygen saturation, the scalar value of the increase in sweat sodium ion concentration, and the percentage of environmental oxygen partial pressure deficit of the workers are presented in the form of a dynamic one-dimensional time series data matrix; the discrete digital stream of time series evolution data is presented to the command personnel to extract the variation characteristics of core risk factors within the current time window.

[0114] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0115] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements the functional modules of a proactive early warning visualization system for personnel functional impairment risks in high-altitude environments, as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0116] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A proactive early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments, characterized in that: It includes a multimodal data acquisition module, an edge data processing and alignment module, a hysteresis loop state space construction module, a functional damage risk assessment module, and a three-dimensional situation visualization and early warning terminal; The multimodal data acquisition module is used to acquire real-time field environmental data, exercise load data, and physiological characteristic signals of workers in high-altitude environments. The edge data processing and alignment module is connected to the multimodal data acquisition module and is used to perform spatiotemporal synchronization alignment and noise reduction on the acquired multimodal data, and calculate the effective hypoxia work index based on the aligned data. The hysteresis loop state space construction module is used to extract force channel features that characterize the compensatory driving force of the cardiovascular system of workers, as well as biochemical channel features that characterize tissue oxygenation and metabolic state. The force channel features and the biochemical channel features are respectively mapped to a two-dimensional state space as orthogonal control axes, and a physiological response hysteresis loop is dynamically generated over time. The functional damage risk assessment module is used to extract the topological geometric features of the physiological response hysteresis loop in real time, calculate the centroid drift vector amplitude and coupling coherence coefficient of the physiological response hysteresis loop relative to the individual's resting baseline state, and construct a comprehensive health risk index in combination with the effective hypoxia work index, so as to calculate and characterize the biophysical damage risk of the body from the collaborative compensation stage to the desynchronization compensation stage in real time. The three-dimensional situation visualization and early warning terminal is connected to the functional damage risk assessment module. It is used to dynamically map the comprehensive health risk index and the topological distortion state of the physiological response hysteresis loop into hierarchical early warning visual elements, and to present the situation perception in an integrated manner on the three-dimensional geographic information platform.

2. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 1, characterized in that: The multimodal data acquisition module includes an environmental sensor unit, a wearable physiological monitoring unit, and a motion inertial navigation unit; The environmental sensor unit is integrated into the housing of a portable terminal worn by the operator and is used to collect environmental parameters including altitude, atmospheric pressure, temperature and oxygen partial pressure; wherein, the environmental sensor unit includes a piezoresistive digital meteorological pressure sensor as a barometer, a semiconductor digital temperature sensor and an electrochemical oxygen sensor. The wearable physiological monitoring unit is attached to the skin surface of the worker in the form of a skin patch to collect physiological parameters including heart rate, blood oxygen saturation, respiratory rate, body temperature, and sweat electrolyte concentration. The wearable physiological monitoring unit includes a multi-wavelength photoplethysmography (PPG) sensor group, a patch-type negative temperature coefficient thermistor array, and a flexible microfluidic sweat collection chip deployed on the worker's body. The flexible microfluidic sweat collection chip has a built-in ion-selective electrode. The motion inertial navigation unit is rigidly fixed at the center of gravity of the operator's torso and is used to collect acceleration and three-dimensional trajectory data characterizing physical load. The motion inertial navigation unit includes a three-axis accelerometer, a three-axis gyroscope, and a dual-mode positioning chip for the Global Positioning System and the BeiDou Navigation Satellite System, all integrated within a microelectromechanical system.

3. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 2, characterized in that: The multimodal data acquisition module is triggered by a unified clock source to synchronize the control mechanism during operation. The data acquired by the environmental sensor unit, wearable physiological monitoring unit and motion inertial navigation unit within the same sampling period are encapsulated in the local microcontroller unit as multimodal sensing data frames with the same source timestamp. The multimodal sensing data frames are synchronously transmitted to the backend edge data processing and alignment module through a low-power wireless communication network.

4. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 1, characterized in that: The edge data processing and alignment module specifically includes the following: Extract the same source timestamps from each received raw data stream, use a preset time step as the standard time grid, and use cubic spline interpolation to reconstruct and align physiological data, exercise load data and environmental data on the time axis; Using the triaxial acceleration signal output by the motion inertial navigation unit as a reference noise source, an adaptive filter is used to filter out motion artifacts in the photoplethysmography pulse wave signal and the respiratory signal; and a wavelet packet transform algorithm is used to smooth and denoise the environmental air pressure and altitude data. Within a set time window, the elevation gradient is calculated by taking the first derivative of the aligned dynamic elevation; the measured local oxygen partial pressure is obtained and its deficit ratio relative to the standard sea level oxygen partial pressure is calculated; the elevation gradient and the deficit ratio are integrated and summed to construct the environmental exposure accumulation factor. The denoised triaxial acceleration signal is integrally shaped over a full wave to calculate the dynamic motion energy value. The effective hypoxia work index is calculated using a nonlinear exponential coupling formula. The effective hypoxia work index is equal to the dynamic motion energy value multiplied by the power of the base of the natural logarithm, where the exponent of the power is the product of a preset plateau environment sensitivity coefficient and the environmental exposure accumulation factor.

5. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 1, characterized in that: The hysteresis loop state space construction module specifically includes the following: The input physiological signals are windowed to extract force channel features and biochemical channel features. The force channel features include heart rate variability and blood pressure variability. The heart rate variability includes the root mean square value and standard deviation of the difference between adjacent heartbeats, while the blood pressure variability is extracted based on a pulse wave transit time estimation algorithm. The biochemical channel features include the rate of change of blood oxygen saturation, the trend of respiratory rate evolution, and the variability of sweat electrolytes. The rate of change of blood oxygen saturation is calculated based on first-order difference, the trend of respiratory rate evolution is extracted based on polynomial fitting, and the variability of sweat electrolytes is obtained by calculating the variance of sweat sodium and potassium ion concentrations. The baseline values ​​of resting heart rate variability and resting blood oxygen saturation of the workers in a completely quiet state are obtained. The range normalization algorithm is used to convert the force channel features and the biochemical channel features extracted in real time into dimensionless standardized relative scalars with numerical ranges limited to zero and one. Using the dimensionless force channel features as the x-axis and the dimensionless biochemical channel features as the y-axis, an orthogonal two-dimensional geometric state space is constructed. Within a preset rolling monitoring window, aligned horizontal and vertical coordinate data points are continuously projected onto a point set trajectory in a two-dimensional geometric state space. As time evolves, the projected point set is connected to generate a closed dynamic physiological response hysteresis loop.

6. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 1, characterized in that: The functional impairment risk assessment module specifically includes the following: Topological geometric feature extraction: Morphological features of the physiological response hysteresis loop generated within the current scrolling monitoring window are extracted. The topological geometric features include the hysteresis loop area, eccentricity, and geometric centroid coordinates. The hysteresis loop area is obtained by performing Green's formula discrete integral on the two-dimensional region enclosed by the hysteresis loop closed curve. The eccentricity is obtained by calculating the ratio of the focal length to the major axis length of the optimal circumscribed ellipse of the hysteresis loop trajectory. The geometric centroid coordinates are obtained by performing first-order geometric moments on the set of all orthogonal projection points of the hysteresis loop trajectory. After extracting the above topological features, the degree of deviation and co-degeneration of the organism's physiological state is quantified, specifically including: Calculate the centroid drift vector amplitude: Obtain the reference centroid coordinates of the reference hysteresis loop established under the worker's resting state, calculate the Euclidean distance between the geometric centroid coordinates of the hysteresis loop in the current time window and the reference centroid coordinates. The Euclidean distance is obtained by adding the square of the difference between the current geometric centroid abscissa and the reference centroid abscissa, plus the square of the difference between the current geometric centroid ordinate and the reference centroid ordinate, and then taking the square root of the sum. Calculate the coupling coherence coefficient: Using the cross-spectral density algorithm, perform frequency domain correlation analysis on the original force channel signal and biochemical channel signal that construct the physiological response hysteresis loop to obtain the coupling coherence coefficient; The comprehensive health risk index is calculated based on the nonlinear weighted coupling formula by combining the effective hypoxia work index and the centroid drift vector amplitude. The comprehensive health risk index is equal to the product of the effective hypoxia work index and the centroid drift vector amplitude, divided by the coupling coherence coefficient.

7. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 6, characterized in that: The functional impairment risk assessment module compares the calculated comprehensive health risk index, the centroid drift vector amplitude, and the coupling coherence coefficient with a preset multivariate safety threshold matrix in real time, performs the following graded early warning judgment, and outputs corresponding instructions and visual driving signals: Attention-level warning: When the area of ​​the hysteresis loop shows an increasing trend, the amplitude of the centroid drift vector is less than a preset first threshold, and the coupling coherence coefficient is higher than a preset safety boundary, an attention-level warning is triggered, and a command to restrict physical activity and a yellow visual drive signal are output. Warning-level alert: When the magnitude of the centroid drift vector is greater than a preset first threshold and the coupling coherence coefficient shows a downward trend within a continuous preset period, a warning-level alert is triggered, and an instruction to stop the current operation and immediately inhale oxygen is output, as well as an orange visual drive signal. Danger warning: When the trajectory of the physiological response hysteresis loop is not closed, the geometric centroid coordinates accelerate and drift, and the coupling coherence coefficient falls below the preset limit of step loss threshold, a danger warning is triggered, and emergency evacuation and medical rescue instructions are output, as well as a red visual flashing drive signal.

8. The active early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments according to claim 1, characterized in that: The three-dimensional situation visualization and early warning terminal specifically includes the following: Run a 3D geographic information platform built on geographic information system and digital twin engine, load high-precision digital elevation model data and satellite remote sensing image data to generate 3D digital topographic map; receive 3D spatial absolute trajectory data output by motion inertial navigation unit, generate virtual entity labels representing workers on the geographic coordinates of 3D digital topographic map, and generate the movement trajectory line of workers on the surface of 3D digital topographic map through real-time coordinate updates. Based on the graded early warning logic output by the functional impairment risk assessment module and the corresponding visual driving signal, the virtual entity label and movement trajectory line are dynamically rendered: When the operator's warning status is at the attention level, respond to the yellow drive signal and render the virtual entity label in yellow; When the warning status is at the alert level, respond to the orange drive signal and render the virtual entity label in orange; When the warning status is at the danger level, respond to the red drive signal, render the virtual entity label as bright red and perform visual flashing at a preset frequency; When the operator triggers the warning level or the danger level warning, a risk ripple aura is generated on the three-dimensional digital terrain map with the operator's current geographical coordinates as the geometric center. The aura's diffusion radius is proportional to the centroid drift vector amplitude output in real time by the functional damage risk assessment module.

9. A proactive early warning and visualization system for the risk of functional impairment in personnel in high-altitude environments, as described in claim 8, is characterized in that: When an operator triggers a warning-level alert or a danger-level alert, the three-dimensional situation visualization and early warning terminal also performs the following interactive steps: The interface interrupts the response and forcibly pops up a secondary monitoring window in the sidebar of the command screen. It dynamically draws the dynamic trajectory of the topological distortion of the two-dimensional physiological response hysteresis loop of the operator. In conjunction with the two-dimensional physiological response hysteresis loop, a discrete digital stream containing the instantaneous value of the rate of decline of blood oxygen saturation, the scalar value of the increase of sweat sodium ion concentration, and the percentage of the proportion of environmental oxygen partial pressure deficit is displayed in a dynamic one-dimensional time series data matrix below the two-dimensional physiological response hysteresis loop.

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