Rescue scene training method, system and device based on virtual reality and medium

Abstract

The invention relates to the technical field of virtual reality, and discloses a virtual reality-based rescue scene training method, system and device and a medium, and the method comprises the steps: obtaining real-time operation data executed by a user for target rescue equipment and a to-be-rescued virtual character; analyzing data through a standardized operation instruction, obtaining timeliness and accuracy parameters, and judging whether operation deviation exists or not; when the operation deviation does not exist, the vital signs of the virtual character are adjusted to the health state; when the operation deviation exists, the vital signs are adjusted to the critical state, training is suspended, error correction guidance is sent out, and an error correction record is generated; acquiring feedback data of the user, and recovering the training process when judging that the feedback data accord with the regulations; after training is finished, training data, error correction records and sign changes are integrated, and a comprehensive evaluation report is generated. By implementing the technical scheme provided by the invention, the problem that existing VR training lacks precise, standardized and actual combat teaching is solved, and the quality and effectiveness of rescue skill training are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the virtual reality technical field, and in particular to a rescue scene training method, system, device and medium based on virtual reality. BACKGROUND

[0002] Emergency rescue skills, such as the correct use of positive pressure respirators, automatic external defibrillators and other equipment, are an important part of the social public safety system. Whether or not to seize the golden four minutes before professional rescuers arrive often depends on whether there is someone on the scene who masters these key operations. Therefore, popularizing first aid skills can not only improve the public self-help and mutual help ability, but also effectively reduce the casualty rate of emergencies.

[0003] However, the current common first aid training still relies on paper manuals or offline teaching organizations. Although this type of method is useful, it has limited coverage and is time-consuming and laborious to organize, making it difficult to promote on a large scale and efficiently. In recent years, VR technology has indeed made many attempts in the field of simulation training, but there are still few VR special training systems focusing on emergency rescue equipment. In particular, in the detailed design of some technical equipment, for example: interactive feedback of device operation, action correction prompt, and restoration of real use situation, often do not fit the actual use characteristics of first aid equipment, which also leads to many VR training systems being inconvenient or unreasonable to use, and the training effect is also discounted. Therefore, an optimized virtual rescue training method is needed to improve the training effect. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a rescue scene training method and system based on virtual reality to solve the problem that the design of scene modeling, interactive feedback and automatic correction function in virtual reality rescue training does not fully combine the operation characteristics of rescue equipment, making it difficult to meet the actual combat and precision of emergency rescue equipment training.

[0006] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a rescue scene training method based on virtual reality, comprising: In response to the operation instruction of the user, the target rescue equipment used in the current training in the current virtual scene is determined, and the standardized operation procedure corresponding to the target rescue equipment is obtained; Start the training process, and obtain the real-time operation data performed on the target rescue equipment and the virtual person to be rescued through the preset interactive device; The real-time operation data is analyzed by a standardized operation procedure to obtain time effectiveness parameters and accuracy parameters of an operation step corresponding to the real-time operation data, and whether the operation step has an operation deviation is determined, the analysis including determination of at least one of time effectiveness, accuracy and logical sequence; When it is determined that there is no operation deviation, a vital sign parameter of a virtual person to be rescued is adjusted to a preset health state according to the time effectiveness parameters and the accuracy parameters; When it is determined that there is an operation deviation, the vital sign parameter is adjusted to a preset critical state according to a preset influence level of the operation deviation, and a training process is paused, an error correction guide is issued through an interactive device, and an error correction record is generated; In the state that the training process is paused, feedback data of the user is obtained based on the error correction guide, and whether the feedback data conforms to the standardized operation procedure is determined, if yes, the training process is resumed; After the training is completed, the real-time operation data, the error correction record and a vital sign change process of the virtual person to be rescued are integrated, a quantitative score is performed and a comprehensive evaluation report including ability analysis is generated.

[0007] As a preferred scheme of the virtual reality-based rescue scene training method, the training process is started, and real-time operation data performed on target rescue equipment and a virtual person to be rescued is obtained through a preset interactive device, including: In the training process, the spatial position and the posture of the interactive device in the current virtual scene are continuously obtained; When a preset interaction event occurs between the interactive device and a target component of the target rescue equipment and / or a target body part of the virtual person to be rescued, a state change of the target component and / or a relative position relationship between the interactive device and the target body part are recorded, the target component is any one of each preset component of the target rescue equipment, and the target body part is any one of each preset body part of the virtual person to be rescued; The spatial position, the posture, the state change and the relative position relationship are integrated to generate the real-time operation data.

[0008] The preferred technical scheme has the beneficial effect that by integrating the spatial position, the posture and the state change of the interactive device and the relative position relationship with the body part of the virtual person, the physical operation of the user can be accurately mapped into quantitative data for system analysis, providing a data basis for subsequent accurate determination.

[0009] As a preferred embodiment of the virtual reality-based emergency rescue scenario training method described in this invention, the step of analyzing real-time operation data through standardized operating procedures to obtain timeliness and accuracy parameters of the operation steps corresponding to the real-time operation data, and determining whether there are operational deviations in the operation steps, includes: Determine the current operation step corresponding to the real-time operation data and the previous step of the current operation step; Determine the first operation step corresponding to the previous step in the standardized operating procedure, determine the second operation step adjacent to the first operation step, compare the second operation step with the current operation step, and determine whether there is a logical order deviation. The state changes and relative positional relationships in the real-time operation data are compared with the standard parameters defined by the standardized operation procedure for the current operation step. Based on the degree of matching of the comparison, the accuracy parameters are generated, and it is determined whether there is an accuracy deviation. The execution time of the current operation step is obtained, and the execution time is compared with the time threshold set for the current operation step in the standardized operation procedure. Based on the relationship between the execution time and the time threshold, the timeliness parameter is generated to determine whether there is a timeliness deviation. When any one of the logical order deviation, the accuracy deviation, and the timeliness deviation exists, it is determined that the operation steps corresponding to the real-time operation data have the operation deviation.

[0010] The beneficial effect of this preferred technical solution is that it enables accurate determination of logical sequence deviations by comparing the current operating steps with the second operating step set in the standardized operating procedure. It defines how to generate accuracy and timeliness parameters by comparing state changes and execution time, respectively, providing clear criteria for analysis, rewards, and penalties.

[0011] As a preferred embodiment of the virtual reality-based emergency rescue scenario training method described in this invention, wherein: when the training process is paused, based on error correction guidance, user feedback data is acquired, and it is determined whether the feedback data conforms to standardized operating procedures, including: Determine the current error correction step indicated by the real-time operation data corresponding to the feedback data; Determine whether the current error correction step is the second operation step; If the current error correction step is the second operation step, the real-time operation data is compared and analyzed with the standard parameters defined for the second operation step in the standardized operation procedure in terms of timeliness and accuracy. When the real-time operation data meets the standard parameters in terms of both timeliness and accuracy, the feedback data is determined to conform to the standardized operation procedure.

[0012] The beneficial effect of this preferred technical solution is that, through the second operation step of the determination, it is ensured that the system can only resume when the user executes the expected correct steps in the paused state, thus achieving a precise and strict error correction closed loop.

[0013] As a preferred embodiment of the virtual reality-based emergency rescue scenario training method described in this invention, the step of adjusting the vital sign parameters of the virtual character to be rescued to a preset healthy state based on the timeliness parameter and the accuracy parameter when it is determined that there is no operational deviation includes: The treatment effectiveness coefficient is calculated based on the timeliness parameter and the accuracy parameter. Multiply the treatment effectiveness coefficient by the preset adjustment amount for the vital signs parameters to obtain the vital signs parameter adjustment value of the virtual character to be rescued in this operation; The vital signs parameters are added to the adjusted vital signs parameters to obtain the adjusted vital signs parameters.

[0014] The beneficial effect of this preferred technical solution is that by quantifying the timeliness and accuracy parameters into a treatment effectiveness coefficient and multiplying it by a preset adjustment amount, a reward mechanism proportional to the quality of user operation is realized, making positive feedback more refined and fair.

[0015] As a preferred embodiment of the virtual reality-based emergency rescue scenario training method described in this invention, wherein: when an operational deviation is determined to exist, the vital signs parameters are adjusted to a preset critical state according to the preset impact level of the operational deviation, the training process is paused, error correction guidance is issued through an interactive device, and an error correction record is generated, including: The preset impact level is determined by matching the operational deviation with a preset deviation rule; Based on the preset impact level, the deterioration adjustment value of the vital signs parameters is calculated, and the vital signs parameters are updated based on the deterioration adjustment value. The error correction guidance is issued through the interactive device in at least one of visual presentation, sound prompts, and tactile vibration, pausing the training process and generating the error correction record.

[0016] As a preferred embodiment of the virtual reality-based emergency rescue scenario training method described in this invention, the method includes: calculating the deterioration adjustment value of vital sign parameters according to the preset impact level, and updating the vital sign parameters according to the deterioration adjustment value, comprising: From the preset mapping relationship, find the deterioration coefficient corresponding to the preset impact level; The deterioration coefficient is multiplied by the pre-set deterioration amount for the vital sign parameters to obtain the deterioration adjustment value.

[0017] Secondly, the present invention provides a virtual reality-based emergency rescue scenario training system, comprising: The acquisition module is used to respond to the user's operation instructions, determine the target rescue equipment used for the current training in the current virtual scene, and acquire the standardized operating procedures corresponding to the target rescue equipment. The startup module is used to start the training process and acquire real-time operation data of the target rescue equipment and the virtual character to be rescued through a preset interactive device. The first judgment module is used to analyze real-time operation data through standardized operating procedures, obtain the timeliness and accuracy parameters of the operation steps corresponding to the real-time operation data, and determine whether there is an operation deviation in the operation steps. The analysis includes the judgment of at least one dimension among timeliness, accuracy and logical order. The first adjustment module is used to adjust the vital signs parameters of the virtual character to be rescued to a preset healthy state based on the timeliness parameter and the accuracy parameter when it is determined that there is no operational deviation. The second adjustment module is used to adjust the vital signs parameters to a preset critical state according to the preset impact level of the operational deviation when an operational deviation is determined, and to pause the training process, issue error correction guidance through the interactive device, and generate an error correction record. The second judgment module is used to obtain user feedback data based on error correction guidance when the training process is paused, and determine whether the feedback data conforms to the standardized operating procedures. If it does, the training process is resumed. The report generation module is used to integrate real-time operation data, error correction records, and the changes in vital signs of the virtual character to be rescued after training, to perform quantitative scoring and generate a comprehensive evaluation report that includes capability analysis.

[0018] Thirdly, the present invention provides an electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of a virtual reality-based rescue scenario training method.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the virtual reality-based rescue scenario training method.

[0020] Compared with existing technologies, the beneficial effects of this invention are as follows: By introducing a three-dimensional judgment matrix that considers logical order, accuracy, and timeliness, and analyzing interactive data such as spatial position and posture, this invention overcomes the shortcomings of traditional VR training, which can only make simple right-or-wrong judgments, and achieves a precise profile of user operations. Through a treatment effectiveness coefficient, the quality of user operations is proportionally linked to the degree of improvement in vital signs. Simultaneously, by presetting influence levels and deterioration coefficients, the severity of operational deviations is proportionally linked to the degree of deterioration in vital signs, thereby enhancing the realism and scientific rigor of the training. When a deviation is detected, the system pauses and guides the user through a recovery threshold, verifying that the user's feedback operations meet the standards in terms of timeliness and accuracy before resuming the process. This further ensures the user's complete mastery of the correct procedures and solves the problem of unreliable and inadequate training. Attached Figure Description

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the overall process of a virtual reality-based emergency rescue scenario training method according to an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram of an exemplary system architecture for a virtual reality-based emergency rescue scenario training method according to an embodiment of the present invention.

[0024] Figure 3 This is a schematic diagram of an exemplary electronic device structure for a virtual reality-based emergency rescue scenario training method according to an embodiment of the present invention.

[0025] Explanation of reference numerals in the attached figures: 100, System architecture; 101, First terminal device; 102, Second terminal device; 103, Third terminal device; 104, Network; 105, Server; 301, Processor; 302, Communication bus; 303, User interface; 304, Network interface; 305, Memory. Detailed Implementation

[0026] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0027] Example 1, referring to Figure 1 As an embodiment of the present invention, a training method for rescue scenarios based on virtual reality is provided, comprising: S201: In response to the user's operation command, determine the target rescue equipment used for the current training in the current virtual scene, and obtain the standardized operating procedures corresponding to the target rescue equipment.

[0028] In the embodiments of this application, standardized operating procedures refer to guidance documents that are formulated for specific rescue equipment or specific rescue scenarios, conform to professional medical standards, and have clear steps, execution order, and technical parameters (such as time limits and operation locations).

[0029] For example, standardized operating procedures for automated external defibrillators (AEDs) may include: step one, turning on the device; step two, attaching the electrode pads according to the voice prompts; step three, prohibiting contact during heart rhythm analysis; and step four, delivering the electric shock, along with a series of standard actions and judgment criteria.

[0030] Specifically, when a training task is initialized, the system receives user commands. These commands can manifest as the user selecting a specific training subject from a preset training menu using a VR interaction device's controller, such as positive pressure respirator (PPR) training. The current virtual scene refers to the simulated environment preset for this training, such as a smoke-filled room, which may display various virtual first aid equipment. After receiving the user's commands, the system identifies the PPR as the target first aid equipment in the current virtual scene, possibly through highlighting or guidance. Once the target equipment is uniquely identified, the system automatically retrieves and loads the standardized operating procedure that perfectly corresponds to the target equipment (PPR) from a local or cloud-configured procedure database, providing a basis for analysis and judgment in subsequent steps.

[0031] S202: Start the training process and acquire real-time operation data of the target rescue equipment and the virtual character to be rescued through the preset interactive device.

[0032] For example, this step implements multi-source operation data acquisition based on VR interaction. After starting the training process, the system continuously acquires the user's continuous spatial position and posture data stream in the virtual scene through preset interactive devices (such as controllers). The system monitors in real time whether preset interaction events occur between these interactive devices and key components of the target rescue equipment or body parts of the virtual character. Once an event occurs, the system discretely records the corresponding state changes (e.g., a button is pressed) and relative positional relationships (e.g., the coordinate deviation between the actual pressing point and the standard pressing center point). The system integrates the continuous motion data with the discrete interaction event data to generate real-time operation data containing motion trajectories and interaction events with timestamps, providing the necessary input for subsequent accurate analysis and judgment.

[0033] In one possible implementation, a training process is initiated, and real-time operation data executed on the target rescue equipment and the virtual character to be rescued is acquired through a preset interactive device. Specifically, this includes: continuously acquiring the spatial position and posture of the interactive device in the current virtual scene during the training process; when a preset interaction event occurs between the interactive device and the target component of the target rescue equipment and / or the target body part of the virtual character to be rescued, recording the state change of the target component and / or the relative positional relationship between the interactive device and the target body part, where the target component is any one of the preset components of the target rescue equipment and the target body part is any one of the preset body parts of the virtual character to be rescued; and integrating the spatial position, posture, state change, and relative positional relationship to generate real-time operation data.

[0034] In this embodiment of the application, real-time operation data refers to a structured data stream that is continuously generated and integrated during the training process, used to fully reproduce all actions performed by the user on the virtual environment through the interactive device; for example, the data includes not only the continuous trajectory of the user's virtual hand in space, i.e., spatial position and posture, but also discrete events (i.e., state changes) in which the hand interacts with a specific virtual object, such as the switch of an AED, as well as the precise positional correspondence (i.e., relative positional relationship) when the hand contacts a virtual character's body part, such as the chest compression point.

[0035] Specifically, after the training process begins, the system captures the user's movements using pre-defined interactive devices, such as VR controllers representing the user's hands or data gloves with position trackers. Throughout the training process, the system continuously acquires the spatial position and posture data of the interactive device in the current virtual scene at a high frequency of possibly 90 times per second. Simultaneously, the system performs real-time collision detection to determine whether the interactive device has engaged in a pre-defined interaction event (e.g., touch, grasp) with a target component of the target rescue equipment and / or a target body part of the virtual person to be rescued. The target component is any one of the pre-defined interactive components on the target rescue equipment, such as the power button of an AED, the electrode pad packaging, or the valve of a breathing mask. The target body part is any one of the pre-defined critical areas on the virtual person to be rescued, such as the chest electrode pad attachment area, chest compression points, or the mouth and nose area. When a pre-defined interactive event is triggered, the system immediately records the state change of the target component caused by the event. For example, a button changes from an unpressed state to a pressed state, and / or records the relative positional relationship between the interactive device and the target body part, such as the positional relationship between a handheld electrode pad and the chest. The system integrates the continuously acquired spatial position and posture data stream with the discretely generated state change and relative positional relationship data at the time of the interactive event, and packages them into a complete, timestamped real-time operation data for use by subsequent analysis modules.

[0036] S203: Analyze real-time operation data through standardized operating procedures, obtain the timeliness and accuracy parameters of the operation steps corresponding to the real-time operation data, and determine whether there are operation deviations in the operation steps. The analysis includes the determination of at least one dimension of timeliness, accuracy and logical sequence.

[0037] For example, this step enables multi-dimensional and quantitative analysis of user operations. The system determines the current operation step based on real-time operation data and, using correctly executed operations as a benchmark, searches for the expected subsequent steps in standardized operating procedures to determine if there are any logical sequence deviations. The system generates accuracy parameters and determines accuracy deviations by matching the physical details of the operation, such as state changes and relative positions, with the standard operating procedures; and generates timeliness parameters and determines timeliness deviations by comparing execution time with time thresholds. The system uses any deviation in these three dimensions—logical sequence, accuracy, and timeliness—as the basis for determining operational deviations and outputs quantitative parameters for subsequent positive incentives, providing comprehensive and quantifiable data support for the reward and punishment mechanism throughout the training process.

[0038] In one possible implementation, real-time operation data is analyzed using standardized operating procedures to obtain timeliness and accuracy parameters for the operation steps corresponding to the real-time operation data, and to determine whether there are operational deviations in the operation steps. Specifically, this includes: determining the current operation step corresponding to the real-time operation data and the previous step; determining the first operation step corresponding to the previous step in the standardized operating procedures, determining the second operation step adjacent to the first operation step, comparing the second operation step with the current operation step to determine if there is a logical order deviation; comparing the state changes and relative positional relationships in the real-time operation data with the standard parameters defined for the current operation step in the standardized operating procedures, generating accuracy parameters based on the degree of matching, and determining if there is an accuracy deviation; obtaining the execution time of the current operation step, comparing the execution time with the time threshold set for the current operation step in the standardized operating procedures, generating timeliness parameters based on the relationship between the execution time and the time threshold, and determining if there is a timeliness deviation; when any one of logical order deviation, accuracy deviation, or timeliness deviation exists, it is determined that there is an operational deviation in the operation steps corresponding to the real-time operation data.

[0039] In this embodiment, operational deviation refers to a conclusive indicator that, after analyzing real-time operational data according to standardized operating procedures, the current operational steps performed by the user do not meet preset standards in terms of logical order, operational accuracy, or execution efficiency. For example, if the standardized operating procedures require "Step A" to be followed by "Step B", but the user skips "Step B" and directly performs "Step C", the system will determine that "Step C" has a logical order deviation. Alternatively, even if the user performs the correct "Step B", but the pressing point, i.e., the operation position, exceeds the tolerance range defined by the standard parameters, an accuracy deviation will be determined.

[0040] Specifically, upon receiving the real-time operation data generated in the previous step, the system parses the data to determine the corresponding current operation step (e.g., the user is currently attaching electrode pads) and the previous step (e.g., the user has just turned on the AED). The system queries the standardized operating procedure, identifying the step matching "turning on the AED" as the first operation step, and then determines the adjacent second operation step (i.e., the expected step defined in the procedure, such as "attaching electrode pads as prompted by voice"). The system compares this expected second operation step with the user's actual current operation step ("attaching electrode pads") to determine if there is a logical sequence deviation. The system compares the state changes and relative positional relationships (e.g., the final coordinates of the electrode pad attachment position) contained in the real-time operation data with the standard parameters (e.g., the standard coordinate range of the left and right sides of the chest) predefined in the standardized operating procedure for the current operation step of "attaching electrode pads". Based on the degree of matching in this comparison (e.g., whether the coordinates fall 100% within the standard range), the system generates a quantified accuracy parameter (e.g., 0.9 points) and determines whether there is an accuracy deviation based on whether the matching result is lower than a certain preset threshold. In addition, the system also obtains the execution time of the current operation step of "attaching electrode pads" (e.g., the user spent 25 seconds) and compares this execution time with the time threshold set for this current operation step in the standardized operating procedure (e.g., the standard requirement is 20 seconds). Based on the relationship between the execution time and the time threshold (e.g., 25 seconds > 20 seconds), the system generates a timeliness parameter (0 points because of timeout) and determines whether there is a timeliness deviation. It should be noted that the timeliness parameter and the timeliness deviation are two independent outputs generated in this comparison. In the example above, because the execution time (25 seconds) is greater than the time threshold (20 seconds), the system determines the timeliness deviation as "true". At this time, the system will execute the penalty in step S205. Although the timeliness parameter is generated as 0.0 points according to the scoring rules (e.g., "≥20 seconds" gets 0.0 points), this parameter will not be used for the reward in step S204.

[0041] As another example, if the execution time is 19 seconds (less than 20 seconds), the system determines the timeliness deviation as "false." In this case, the system will execute the reward step S204 and generate a timeliness parameter greater than 0.0 (e.g., 0.5) based on the relationship between the execution time and the time threshold (e.g., the "15-20 seconds" range) to calculate the reward. The system will summarize the judgment results of the above three dimensions. When any one of the logical order deviation, accuracy deviation, or timeliness deviation exists (in the above example, timeliness deviation is triggered), the system will determine that there is an operational deviation in the operation step corresponding to the real-time operation data. The system will then output the generated timeliness parameter (0) and accuracy parameter (0.9) for use in subsequent steps.

[0042] In an alternative implementation, to handle more complex standardized operating procedures, the determination of whether there is a logical order deviation in step S203 may further include the processing of parallel steps and conditional branches.

[0043] For parallel steps: Standardized operating procedures can predefine a "parallel step group." For example, after "Step A: Turn on the AED power," "Step B: Attach the electrode pads" and "Step C: Prepare the balloon mask" can be defined as parallel steps. In this case, the second operating step adjacent to the first will return a set of steps containing B and C. When the system determines the current operating step to be either B or C, no logical order deviation is considered. The system will also record that one step in this set (e.g., B) has been completed and continue waiting for the remaining steps in the set (e.g., C) to be executed, or proceed to the next non-parallel step (e.g., D).

[0044] For conditional branches: Standardized operating procedures can include a conditional decision step, such as: Step A: Check the virtual character's breathing. Standard parameters not only include the accuracy of the operation, such as whether the user correctly positions their head near the virtual character's mouth and nose, but also a "conditional result" generated by the system simulation. For example, the system randomly or according to a preset script returns "breathing" or "no breathing." After executing "Step A," the system dynamically selects different second operating steps from the procedure based on this "conditional result." For example, if the result is "breathing," the second operating step is determined as "Step B: Place in the recovery position"; if the result is "no breathing," the second operating step is determined as "Step C: Begin chest compressions." This approach allows training to simulate more complex real-world decision-making scenarios.

[0045] S204: When it is determined that there is no operational deviation, the vital signs parameters of the virtual character to be rescued are adjusted to the preset healthy state based on the timeliness parameter and the accuracy parameter.

[0046] For example, this step implements a quantitative positive incentive based on operational quality. Once it is confirmed that the user's operation is free of deviation, the system activates the incentive mechanism. This mechanism combines the user's operational efficiency (timeliness parameter) and operational precision (accuracy parameter) to calculate a comprehensive treatment effectiveness coefficient. Based on this coefficient, the system proportionally calculates and generates corresponding vital sign parameter adjustment values, improving the virtual character's vital signs towards a healthy state. This ensures that while the user performs the operation correctly, the efficiency (timeliness parameter) and precision (accuracy parameter) of their operation are directly and dynamically reflected in the treatment effect, thus providing the user with immediate feedback on operational quality.

[0047] In one possible implementation, when it is determined that there is no operational deviation, the vital signs parameters of the virtual character to be rescued are adjusted to a preset healthy state based on the timeliness parameter and the accuracy parameter. Specifically, this includes: calculating the treatment effectiveness coefficient based on the timeliness parameter and the accuracy parameter; multiplying the treatment effectiveness coefficient by the preset adjustment amount for the vital signs parameters to obtain the adjusted value of the vital signs parameters of the virtual character to be rescued in this operation; and adding the vital signs parameters to the adjusted value to obtain the adjusted vital signs parameters.

[0048] In this embodiment, the treatment effectiveness coefficient is a comprehensive quantitative indicator used to evaluate the quality of a user's operation when performing the correct operation (i.e., without operational deviation). It is jointly determined by the user's operational efficiency (timeliness parameter) and operational precision (accuracy parameter). For example, an operation with a timeliness parameter of 1.0 and an accuracy parameter of 1.0 might be calculated to have a treatment effectiveness coefficient of 1.0; while an operation with a timeliness parameter of 0.6 (slower) but an accuracy parameter of 0.9 (more accurate) might be calculated to have a treatment effectiveness coefficient of 0.75 through weighted averaging or other algorithms. This coefficient directly affects the magnitude of the reward.

[0049] Specifically, when no operational deviation is determined, the system will activate a positive incentive mechanism. This mechanism calculates the treatment effectiveness coefficient based on the timeliness and accuracy parameters obtained in the analysis step. For example, multiplying the timeliness parameter of 0.9 by the accuracy parameter of 0.8 yields 0.72. The system will read the vital signs parameters, such as heart rate and blood pressure, from the current status configuration of the virtual character to be rescued, and set preset adjustment amounts. These adjustment amounts represent the maximum improvement that a single perfect operation can bring; for example, the maximum improvement in heart rate is +5. The system multiplies the newly obtained treatment effectiveness coefficient of 0.72 by the preset adjustment amount (+5) for the vital signs parameter to obtain the adjusted value of the vital signs parameter for the virtual character to be rescued in this operation (+3.6). The system adds the current vital signs parameters of the virtual character to be rescued (assuming a heart rate of 60) to the adjusted value of the vital signs parameters (+3.6) to obtain the adjusted vital signs parameters (i.e., 63.6). In this way, the vital signs parameters of the virtual character to be rescued are adjusted to a preset healthy state.

[0050] S205: When an operational deviation is detected, the vital signs parameters are adjusted to the preset critical state according to the preset impact level of the operational deviation, the training process is paused, error correction guidance is issued through the interactive device, and an error correction record is generated.

[0051] For example, this step implements a graded penalty and forced error correction mechanism based on the severity of the error. When the analysis determines that an operational deviation exists, the system determines a corresponding deterioration adjustment value based on the nature of the deviation and a preset impact level, and uses this value to dynamically worsen the vital signs parameters of the virtual character to simulate the consequences of the deviation. Simultaneously, the system forcibly pauses the training process and provides the user with error correction guidance containing the specific error type through visual, auditory, or tactile interactions. The system generates an error correction record containing error details, thus completing the workflow of immediate penalty, warning, and recording, creating the necessary conditions for subsequent user self-correction.

[0052] In one possible implementation, when an operational deviation is determined, the vital signs parameters are adjusted to a preset critical state based on the preset impact level of the operational deviation, the training process is paused, error correction guidance is issued through an interactive device, and an error correction record is generated. Specifically, this includes: determining the preset impact level by matching the operational deviation with preset deviation rules; calculating the deterioration adjustment value of the vital signs parameters based on the preset impact level, and updating the vital signs parameters based on the deterioration adjustment value; issuing error correction guidance through an interactive device using at least one of visual presentation, sound prompts, and tactile vibration, pausing the training process, and generating an error correction record.

[0053] In this application embodiment, the preset impact level refers to a classification standard for grading the possible consequences of operational deviations. It is defined in preset deviation rules and is used to distinguish the severity of different errors. For example, a logical sequence deviation may be determined as a "severe" level, such as skipping a critical cardiopulmonary resuscitation step, which would have a high preset impact level; while a slight timeliness deviation may be determined as a "minor" level, such as completing bandaging only 1 second late, which would have a low preset impact level. This level will directly determine the subsequent punishment, that is, the extent of the deterioration of vital signs.

[0054] Specifically, when an operational deviation is detected, the system will immediately execute a negative feedback and error correction process. The system will match the detected operational deviation with preset deviation rules to determine the preset impact level of the deviation. Based on this preset impact level, the system will calculate a deterioration adjustment value for vital signs parameters, such as a large deduction value corresponding to the severity level, and update the current vital signs parameters accordingly. For example, reducing the virtual character's heart rate by 10, thereby adjusting the vital signs parameters towards a preset critical state. Simultaneously, the system will provide error correction guidance to the user through at least one of the following methods: visual presentation (e.g., highlighting the erroneous device in red); audio prompts (e.g., issuing a voice message indicating an incorrect operation sequence); or tactile vibration (e.g., vibrating the controller). After issuing the guidance, the system will pause the current training process and generate an error correction record containing deviation details, stopping the training at the erroneous step and awaiting the user's corrective action.

[0055] In one possible implementation, the deterioration adjustment value of vital signs parameters is calculated based on a preset impact level, and the vital signs parameters are updated based on the deterioration adjustment value. Specifically, this includes: finding the deterioration coefficient corresponding to the preset impact level from a preset mapping relationship; multiplying the deterioration coefficient by a preset deterioration amount for the vital signs parameters to obtain the deterioration adjustment value.

[0056] In this embodiment, the degradation coefficient refers to a value pre-stored in a preset mapping relationship, used to represent the penalty magnitude multiplier corresponding to a preset impact level. For example, a "slight" preset impact level may correspond to a degradation coefficient of 0.2; a "medium" level may correspond to a degradation coefficient of 0.5; and a "severe" level (such as a fatal error that leads to training failure) may correspond to a degradation coefficient of 1.0. This coefficient will be used to scale the base degradation penalty value.

[0057] Specifically, in the process of calculating the deterioration adjustment value of vital sign parameters based on the preset impact level, the system looks up the deterioration coefficient 1.0 corresponding to the currently determined preset impact level "Severe" from a pre-configured preset mapping relationship, such as a lookup table storing key-value pairs "Mild: 0.2", "Moderate: 0.5", and "Severe: 1.0". The system reads the preset deterioration amount for the current vital sign parameter from the virtual character's configuration, such as blood oxygen saturation of -5%. The system multiplies the found deterioration coefficient (1.0) with the preset deterioration amount (-5%) for that vital sign parameter to obtain the final deterioration adjustment value (i.e., -5%); this deterioration adjustment value is then used to update the vital sign parameter.

[0058] In an optional implementation, the error correction guidance issued through the interactive device in step S205 can adopt an adaptive multi-level guidance strategy, which dynamically adjusts the clarity of the guidance according to the preset impact level of the operational deviation and the number of consecutive errors made by the user.

[0059] For example, the error log not only records the error itself but also the number of consecutive failures for the same second step. When a user makes an operational error for the first time, it might be a logical sequence error, and the system issues a first-level guidance (i.e., an indirect prompt). For example, an audio prompt might say: "The operation sequence is incorrect; please rethink what to do after the previous step." When a user makes an operational error for the second time in the same location, the system issues a second-level guidance (i.e., explicit instructions). For example, an audio prompt might say: "You have turned on the power; the next step is to attach the electrode pads." Simultaneously, the visual presentation will highlight the electrode pad packaging. When a user makes an operational error for the third time in the same location, the system issues a third-level guidance (i.e., a demonstration). For example, the system might visually demonstrate how to grasp and attach the electrode pads using a virtual hand, or provide directional pulling guidance via tactile vibration through a handle. Furthermore, the guidance content can be differentiated based on the type of error: for logical sequence errors, the guidance focuses on "what to do next"; while for accuracy errors, the guidance focuses on "how to do the current step correctly," for example, an audio prompt might say: "Insufficient pressure; please apply more force."

[0060] S206: When the training process is paused, based on error correction guidance, obtain user feedback data, determine whether the feedback data conforms to the standardized operating procedures, and if it does, resume the training process.

[0061] For example, this step aims to provide an automated error correction and recovery mechanism. After training is paused due to operational deviations, the system receives feedback data from the user, based on previously issued error correction guidance, to correct the error. The system compares this feedback data with the next expected correct action in the standardized operating procedure from multiple dimensions. This determination has a double threshold: verifying the logical correctness of the feedback data (i.e., whether it is the expected step) and checking its timeliness and accuracy (i.e., execution quality). Only when the feedback data meets both logical and quality standards will the system determine that it conforms to the procedure and resume the training process, thus completing the closed loop of this error correction.

[0062] In one possible implementation, while the training process is paused, user feedback data is acquired based on error correction guidance. The system then determines whether the feedback data conforms to standardized operating procedures. Specifically, this includes: identifying the current error correction step indicated by the real-time operating data corresponding to the feedback data; determining whether the current error correction step is a second operating step; and if the current error correction step is a second operating step, comparing the real-time operating data with the standard parameters defined in the standardized operating procedures for the second operating step in terms of timeliness and accuracy. If the real-time operating data conforms to the standard parameters in both timeliness and accuracy, the feedback data is determined to conform to the standardized operating procedures.

[0063] In this embodiment of the application, feedback data refers to the set of all new operation instructions entered by the user in response to the error correction guidance issued by the system when the training process is paused, which are intended to correct the previous erroneous operation. For example, if the system prompts the user to "please attach the electrode pads", and the user subsequently performs a series of actions such as "take the electrode pads out of the packaging bag" and "attach the electrode pads to the virtual character", the new real-time operation data generated by these actions and the intentions behind them together constitute the feedback data that needs to be judged.

[0064] Specifically, while the training process is paused, the system continuously monitors user input. Under error-correction guidance, assuming the user is guided to execute "step B," the system acquires all feedback data from the user's input. The system determines the current error-correction step indicated by the real-time operation data corresponding to the feedback data, assuming the user actually attempted to execute "step B." The system then performs a first-level logical judgment to determine if the current error-correction step is the second operation step, which is the expected subsequent step in the error-correction guidance. If the current error-correction step (e.g., "step B") is not the second operation step (assuming the user incorrectly attempted "step C"), the system takes no action, remains paused, and waits for new feedback. Only when the current error-correction step is the second operation step (i.e., the user executed the correct step B) will the system initiate a second-level precise judgment. At this point, the system compares and analyzes the position, posture, and time information recorded in the real-time operation data with the standard parameters defined for the second operation step in the standardized operating procedure, focusing on timeliness and accuracy. When the real-time operational data meets the standard parameters in terms of both timeliness and accuracy, assuming that step B is executed quickly and accurately, the system will determine that the feedback data conforms to the standardized operating procedure and then resume the training process.

[0065] It should be noted that step S206 achieves graded punishment (deterioration of vital signs) corresponding to the severity of the error by matching the operational deviation to a preset impact level. Simultaneously, it specifies that error correction guidance can be issued through at least one method, such as visual, auditory, or tactile, clarifying the specific interactive form for the system to issue warnings and guidance to the user.

[0066] S207: After training, integrate real-time operation data, error correction records, and the changes in vital signs of the virtual character to be rescued, conduct quantitative scoring, and generate a comprehensive assessment report that includes capability analysis.

[0067] In this embodiment of the application, the comprehensive evaluation report refers to a summary document automatically generated by the system after the training session ends, which is used to represent the user's overall performance, operational strengths and weaknesses, and skill level in this rescue scenario training; for example, the report may include a total score (quantitative score), a graphical curve of the process of changes in vital signs, and a capability analysis module that details the user's performance data in three dimensions: logical order, accuracy, and timeliness.

[0068] Specifically, after training concludes—for example, if the user successfully restores the virtual character's vital signs to a healthy state, or if the virtual character dies due to a serious error—the system will initiate an evaluation process. The system will integrate complete logs of real-time operational data throughout the training process, all triggered error correction records, including error type, severity level, and correction time, as well as the changes in the virtual character's vital signs, such as time-axis curves of heart rate, blood pressure, and blood oxygen levels. Based on this integrated data, the system will execute a preset scoring algorithm to quantify the score, calculating a final score based on factors such as the correctness of the operation, total time, and the extent of vital sign deterioration. The system will then structure the above scores, data summaries, and analysis results to generate a comprehensive evaluation report containing capability analysis. This report aims to visually demonstrate the user's strengths and weaknesses in mastering the operation skills of the target rescue equipment, providing an objective basis for subsequent targeted training.

[0069] In an optional implementation, the quantitative scoring in step S207 can be based on a specific deduction and addition model. Base score: The user starts training with a base score of 100. Deviation deduction: The system iterates through all error correction records. For each record, the system deducts points based on its preset impact level and corresponding deterioration coefficient. For example, a "minor" level (deterioration coefficient 0.2) deducts 5 points, and a "serious" level (deterioration coefficient 1.0) deducts 30 points. Quality addition: The system iterates through all operations determined to have no operational deviations and extracts their timeliness and accuracy parameters. The system calculates the treatment effectiveness coefficient based on these parameters and adds points based on this coefficient, for example: 5 points for a coefficient of 1.0, and 3 points for a coefficient of 0.8. Final score = Base score - Total deviation deductions + Total quality additions. Correspondingly, the comprehensive evaluation report including capability analysis can specifically include: radar chart analysis, where the capability analysis can be presented as a radar chart, with the vertices representing logical order, operational accuracy, and operational timeliness, respectively. The user's score is based on their average performance across these three dimensions. For example, the logical order score is the percentage of times no logical order deviation occurred. The vital sign change curve report displays a timeline chart of the virtual character's vital signs changes, clearly marking key operational points that led to improvement and deterioration. The improvement section automatically summarizes error correction records and lists the most common user mistakes, such as incorrect electrode placement three times, providing clear suggestions for subsequent training.

[0070] It should be noted that step S207 achieves a quantitative penalty calculation based on preset rules by finding the corresponding deterioration coefficient for different preset impact levels and multiplying it by the preset deterioration amount, so that the degree of deterioration of vital signs is directly linked to the severity of operational errors.

[0071] In summary, the above technical solutions, by acquiring standardized procedures and real-time operational data and conducting comparative analysis, achieve immediate judgment of user operations. This analysis can derive timeliness and accuracy parameters and determine whether any deviations exist. Based on this, when the operation is correct, the system uses parameters to adjust the virtual human's physical characteristics towards a healthy state, achieving positive incentives; when the operation is incorrect, the system adjusts the physical characteristics towards a critical state, pauses training, issues error correction guidance, and records it, achieving immediate punishment. In the paused state, the system verifies the user's feedback data, and only resumes training when the feedback conforms to the procedures, constructing a mandatory error correction closed loop. The system integrates all data to generate an evaluation report. This error correction closed loop mechanism ensures that users must learn and master the correct operating procedures in real time, thereby solving the problem of existing VR training lacking precise, standardized, and practical teaching, and significantly improving the quality and effectiveness of first aid skills training.

[0072] Example 2 illustrates a virtual reality-based emergency medical scenario training method. It should be noted that the technical solution of this virtual reality-based emergency medical scenario training system belongs to the same concept as the aforementioned virtual reality-based emergency medical scenario training method. Details not described in detail in this example of the virtual reality-based emergency medical scenario training system can be found in the description of the aforementioned virtual reality-based emergency medical scenario training method.

[0073] This embodiment also provides another virtual reality-based emergency rescue scenario training system, including: The acquisition module is used to respond to the user's operation instructions, determine the target rescue equipment used for the current training in the current virtual scene, and acquire the standardized operating procedures corresponding to the target rescue equipment. The startup module is used to start the training process and acquire real-time operation data of the target rescue equipment and the virtual character to be rescued through a preset interactive device. The first judgment module is used to analyze real-time operation data through standardized operating procedures, obtain the timeliness and accuracy parameters of the operation steps corresponding to the real-time operation data, and determine whether there is an operation deviation in the operation steps. The analysis includes the judgment of at least one dimension among timeliness, accuracy and logical order. The first adjustment module is used to adjust the vital signs parameters of the virtual character to be rescued to a preset healthy state based on the timeliness parameter and the accuracy parameter when it is determined that there is no operational deviation. The second adjustment module is used to adjust the vital signs parameters to a preset critical state according to the preset impact level of the operational deviation when an operational deviation is determined, and to pause the training process, issue error correction guidance through the interactive device, and generate an error correction record. The second judgment module is used to obtain user feedback data based on error correction guidance when the training process is paused, and determine whether the feedback data conforms to the standardized operating procedures. If it does, the training process is resumed. The report generation module is used to integrate real-time operation data, error correction records, and the changes in vital signs of the virtual character to be rescued after training, to perform quantitative scoring and generate a comprehensive evaluation report that includes capability analysis.

[0074] like Figure 2 As shown, the system architecture 100 may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0075] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, and 103, such as model training applications, video recognition applications, web browser applications, social platform software, etc.

[0076] Terminal devices 101, 102, and 103 can be either hardware or software. When terminal devices 101, 102, and 103 are hardware, they can be various electronic devices with displays, including but not limited to smartphones, tablets, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptops, and desktop computers, etc. When terminal devices 101, 102, and 103 are software, they can be installed in the aforementioned electronic devices. They can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services) or as a single software program or software module. No specific limitations are imposed here.

[0077] When terminals 101, 102, and 103 are hardware devices, video capture devices can also be installed on them. These video capture devices can be various devices capable of capturing video, such as cameras, sensors, etc. Users can use the video capture devices on terminals 101, 102, and 103 to capture video.

[0078] Server 105 can be a server that provides various services, such as a backend server for processing data displayed on terminal devices 101, 102, and 103. The backend server can analyze and process the received data and can feed back the processing results (such as recognition results) to the terminal devices.

[0079] It should be noted that a server can be either hardware or software. When the server is hardware, it can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When the server is software, it can be implemented as multiple software programs or software modules (e.g., multiple software programs or software modules used to provide distributed services), or as a single software program or software module. No specific limitations are made here.

[0080] It should be understood that Figure 2 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included. In particular, if the target data does not need to be obtained remotely, the above system architecture may exclude the network and include only terminal devices or servers.

[0081] This embodiment also discloses an electronic device, as shown in the reference. Figure 3 The electronic device may include: at least one processor 301, at least one communication bus 302, user interface 303, network interface 304, and at least one memory 305.

[0082] The communication bus 302 is used to enable communication between these components.

[0083] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0084] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0085] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0086] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. Figure 3 As shown, the memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for training a rescue scenario based on virtual reality.

[0087] exist Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 301 can be used to call an application stored in the memory 305 for a virtual reality-based rescue scenario training method. When executed by one or more processors 301, the electronic device executes one or more methods as described in the above embodiments.

[0088] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0089] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0090] In some embodiments of this application, a computer-readable storage medium is provided, including instructions that, when executed on the electronic device, cause the electronic device to perform a virtual reality-based rescue scenario training method according to an embodiment of this application.

[0091] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A virtual reality-based rescue scenario training method, characterized by, The method comprises the following steps: In response to the operation instruction of the user, the target rescue equipment used in the current virtual scene is determined, and the standardized operation procedure corresponding to the target rescue equipment is obtained; The training process is started, and real-time operation data performed by the target rescue equipment and the virtual person to be rescued is obtained through the preset interactive device; The real-time operation data is analyzed through the standardized operation procedure to obtain the timeliness parameter and the accuracy parameter of the operation step corresponding to the real-time operation data, and it is determined whether there is an operation deviation in the operation step, the analysis including the determination of at least one dimension of timeliness, accuracy and logical sequence; When it is determined that there is no operation deviation, the vital sign parameter of the virtual person to be rescued is adjusted to the preset health state according to the timeliness parameter and the accuracy parameter; When it is determined that there is an operation deviation, the vital sign parameter is adjusted to the preset critical state according to the preset influence level of the operation deviation, the training process is suspended, the error correction guide is issued through the interactive device, and the error correction record is generated; In the state that the training process is suspended, the feedback data of the user is obtained based on the error correction guide, it is determined whether the feedback data conforms to the standardized operation procedure, and if so, the training process is resumed; After the training is completed, the real-time operation data, the error correction record and the vital sign change process of the virtual person to be rescued are integrated, the quantitative score is performed and the comprehensive evaluation report including the ability analysis is generated.

2. The virtual reality-based rescue scenario training method of claim 1, wherein, The method comprises the following steps: In the training process, the spatial position and the posture of the interactive device in the current virtual scene are continuously obtained; When the interactive device and the target component of the target rescue equipment and / or the target body part of the virtual person to be rescued occur a preset interaction event, the state change of the target component and / or the relative position relationship between the interactive device and the target body part are recorded, the target component is any one of the preset components of the target rescue equipment, and the target body part is any one of the preset body parts of the virtual person to be rescued; The spatial position, the posture, the state change and the relative position relationship are integrated to generate the real-time operation data.

3. A virtual reality based rescue scenario training method as claimed in claim 2, wherein, The method comprises the following steps: The current operation step corresponding to the real-time operation data and the previous step of the current operation step are determined; The first operation step corresponding to the previous step in the standardized operation procedure is determined, the second operation step adjacent to the first operation step is determined, the second operation step is compared with the current operation step, and it is determined whether there is a logical sequence deviation; The state change in the real-time operation data and the relative position relationship are compared with standard parameters defined by the standardized operation procedure for the current operation step, an accuracy parameter is generated according to a matching degree of the comparison, and it is determined whether there is an accuracy deviation; An execution time of performing the current operation step is obtained, the execution time is compared with a time threshold set for the current operation step in the standardized operation procedure, a timeliness parameter is generated according to a relationship between the execution time and the time threshold, and it is determined whether there is a timeliness deviation; When any one of the logical sequence deviation, the accuracy deviation and the timeliness deviation exists, it is determined that the operation step corresponding to the real-time operation data has the operation deviation.

4. A virtual reality based rescue scenario training method as claimed in claim 3, wherein, In the state that the training process is paused, feedback data of a user is obtained based on error correction guidance, and it is determined whether the feedback data conforms to the standardized operation procedure, including: A current error correction step indicated by real-time operation data corresponding to the feedback data is determined; It is determined whether the current error correction step is the second operation step; When the current error correction step is the second operation step, the real-time operation data is compared and analyzed with standard parameters defined for the second operation step in the standardized operation procedure in terms of timeliness and accuracy; When the real-time operation data conforms to the standard parameters in terms of timeliness and accuracy, it is determined that the feedback data conforms to the standardized operation procedure.

5. A virtual reality based rescue scenario training method as claimed in claim 4, wherein, When it is determined that there is no operation deviation, a life sign parameter of a virtual person to be rescued is adjusted to a preset healthy state according to the timeliness parameter and the accuracy parameter, including: A rescue effectiveness coefficient is calculated according to the timeliness parameter and the accuracy parameter; The rescue effectiveness coefficient is multiplied by a preset adjustment amount of the life sign parameter to obtain a life sign parameter adjustment value of the virtual person to be rescued in this operation; The life sign parameter is added to the life sign parameter adjustment value to obtain an adjusted life sign parameter.

6. A virtual reality based rescue scenario training method as claimed in claim 5, wherein, When it is determined that there is an operation deviation, the life sign parameter is adjusted to a preset critical state according to a preset influence level of the operation deviation, the training process is paused, error correction guidance is issued through an interactive device, and an error correction record is generated, including: The preset influence level is determined by matching the operation deviation with a preset deviation rule; A deterioration adjustment value of the life sign parameter is calculated according to the preset influence level, and the life sign parameter is updated according to the deterioration adjustment value; The error correction guidance is issued in at least one of visual presentation, sound prompt and tactile vibration through the interactive device, the training process is paused, and the error correction record is generated.

7. A virtual reality based rescue scenario training method according to any one of claims 1-6, characterized in that, A deterioration adjustment value of the life sign parameter is calculated according to the preset influence level, and the life sign parameter is updated according to the deterioration adjustment value, including: A deterioration coefficient corresponding to the preset influence level is found from a preset mapping relationship; The deterioration coefficient is multiplied by a preset deterioration amount of the life sign parameter to obtain the deterioration adjustment value.

8. A virtual reality based rescue scenario training system applying the method according to any one of claims 1 - 7, characterized in that, including: An acquisition module is configured to determine target rescue equipment used in a current virtual scene in response to an operation instruction of a user, and acquire a standardized operation procedure corresponding to the target rescue equipment; A starting module is configured to start a training process, and acquire real-time operation data performed on the target rescue equipment and a virtual person to be rescued through a preset interactive device; A first judgment module is configured to analyze the real-time operation data through the standardized operation procedure, acquire time effectiveness parameters and accuracy parameters of operation steps corresponding to the real-time operation data, and determine whether there is an operation deviation in the operation steps, wherein the analysis includes a determination of at least one dimension of time effectiveness, accuracy and logical sequence; A first adjustment module is configured to adjust a vital sign parameter of the virtual person to be rescued to a preset healthy state according to the time effectiveness parameters and the accuracy parameters when it is determined that there is no operation deviation; A second adjustment module is configured to adjust the vital sign parameter to a preset critical state according to a preset influence level of the operation deviation when it is determined that there is an operation deviation, and to suspend the training process, issue a correction guide through the interactive device, and generate a correction record; A second judgment module is configured to acquire feedback data of the user based on the correction guide when the training process is suspended, determine whether the feedback data conforms to the standardized operation procedure, and resume the training process if the feedback data conforms to the standardized operation procedure; A report generation module is configured to integrate the real-time operation data, the correction record and a vital sign change process of the virtual person to be rescued after the training is completed, perform quantitative scoring, and generate a comprehensive evaluation report including an ability analysis.

9. An electronic device, comprising: comprise: a memory and a processor; the memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions, so as to implement steps of the virtual reality based rescue scene training method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The memory has stored computer executable instructions, and the processor is configured to execute the computer executable instructions, so as to implement steps of the virtual reality based rescue scene training method according to any one of claims 1 to 7.

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