Cognitive decision-making evaluation training system and method in instantaneous super-heavy and weightlessness states

Abstract

Provided in the present invention are a cognitive decision-making evaluation training system and method in instantaneous super-heavy and weightlessness states. The system comprises a multi-degree-of-freedom super-heavy and weightlessness simulation platform, a VR head-mounted display having an eye movement tracking function, a multi-mode controller, a gesture recognition sensor, a flight seat and frame structure, a super-heavy and weightlessness simulation platform module, and a cognitive decision-making evaluation training module. In super-heavy and weightlessness states of the system, the spatial perception capability, the attention, and the learning and memory capabilities of a person are affected to varying degrees. Therefore, by performing cognitive training in such a simulation scenario and by means of the acquisition and comprehensive analysis of real physiological parameters in a task stage, a more real and efficient training solution can be provided to people, thus helping people to better implement reinforcement training of cognitive behaviors.

Description

Cognitive decision-making assessment training system and method under transient hypergravity and weightlessness Technical Field

[0001] The present invention relates to the technical field of cognitive training reinforcement, and in particular to a cognitive decision-making evaluation training system and method under transient overweight and weightlessness states. Background Art

[0002] The Chinese patent with publication number CN103268392A discloses a cognitive function training system and method based on scenario interaction. The system includes a human-computer interaction device and a touch screen display and an interactive scene memory respectively connected thereto. A user wearing 3D glasses can interact with the human-computer interaction device by touching the display screen. The human-computer interaction device includes an information input, recognition, analysis, storage, feedback, output module and a virtual scene simulation module. The information of the touch screen reaches the information analysis module through the input module of the human-computer interaction device, and is then distributed to the information storage module and the information feedback module. The information of the information feedback module is output to the virtual scene simulation module. The information of the interactive scene memory is output to the information output module and the second input end of the virtual scene simulation module, and the output of the virtual scene simulation module is connected to the display screen. The information feedback module pre-stores a cognitive function training program feedback system.

[0003] A Chinese patent with announcement number CN108335747B discloses a cognitive training system, which includes a first operating terminal, a second operating terminal, and a system terminal. The first operating terminal can edit cognitive training media and save it to the system terminal. During use, the system terminal transfers the media file to the second operating terminal for display, collects data from the second operating terminal for judgment, and completes cognitive training. The system terminal includes a database, a sample extraction module, and a cognitive training module. This patent is characterized by the ability to conduct intensive training based on features with low accuracy rates derived from statistics of cognitive results, and can provide customized services to improve training effectiveness.

[0004] The Chinese patent with publication number CN110827953A discloses a VR-based cognitive memory training evaluation system, method and storage medium. The evaluation system includes a host, a touch panel, a motion sensing sensor, a 3D stereo display and a database. The host determines the difficulty level of the patient's training performance based on the patient's training history data or the patient's last evaluation level. The touch panel is used for patient operation, and the operation data is collected and sent to the host. The motion sensing sensor is worn on the patient's head and collects hand movement data. The 3D stereo display can display virtual reality scenes and provide an immersive training environment. The database stores preset training scenes, patient evaluation levels, training data, etc. The deep learning unit in the evaluation unit collects operation data and hand movement numbers, generates a training evaluation report based on the deep learning unit, and adjusts the patient's next training difficulty and scene data according to the report.

[0005] The Chinese patent publication number CN113192600A discloses a cognitive assessment and correction training system based on virtual reality and eye tracking, which includes an eye tracking module, an assessment module, and a training module. The eye tracking module obtains the gaze point coordinates from the VR device, and the eye tracking module is connected to the assessment module and the training module respectively. The assessment module includes attention, executive function, and memory assessment modules. The training module includes training modules in the above three aspects. After the patient's experience, this system scores the patient's computing ability, positive emotions, and other seven dimensions. After collecting eye movement data, it calculates features such as gaze time and gaze hit rate to complete cognitive assessment and training functions.

[0006] However, the above patents all evaluate cognitive behavior in a "static" state, that is, the subjects are in a static environment in real scenarios and cannot truly experience the real simulated tasks in cognitive training. They have the defect of mechanical training and cannot truly stimulate the state of the subjects in cognitive training, nor can they truly conduct subsequent intensive training on the subjects. At the same time, the existing technology cannot obtain physiological parameter information during cognitive training, but physiological parameter information in cognitive training is very important for analyzing the physical state of the subjects. In particular, when multiple intensive training is required for the subjects, physiological parameter information can provide very clear guidance for specific training and can establish a truly personalized cognitive model, which is very important for individuals.

[0007] Summary of the Invention

[0008] In order to achieve the above-mentioned objectives and other advantages of the present invention, the first objective of the present invention is to provide a cognitive decision-making assessment training system under transient overweight and weightlessness conditions, comprising a multi-degree-of-freedom overweight and weightlessness simulation platform, a VR head display with eye tracking, a multi-mode controller, a gesture recognition sensor, a flight seat and frame structure, an overweight and weightlessness simulation platform module, and a cognitive decision-making assessment training module; wherein,

[0009] The multi-degree-of-freedom overweight and weightlessness simulation platform is used to achieve instantaneous rapid rotation in three major directions: lateral, horizontal, and pitch through electric drive, so that the human body reaches a state of weightlessness or overweight;

[0010] The VR headset with eye tracking is used to provide the subject with a virtual environment scene, while capturing the subject's eye movement data information in real time to obtain the subject's true response during the task phase;

[0011] The multi-mode controller is used to allow the subject to dynamically control the system platform in multiple directions during the task phase, thereby enhancing the subject's cognitive training experience;

[0012] The gesture recognition sensor is used to recognize the subject's gestures and confirm the task results under the preset task type;

[0013] The flight seat and frame structure are the mechanical structures that constitute the multi-degree-of-freedom overweight and weightlessness simulation platform;

[0014] The overweight and weightlessness simulation platform module is a function built on the hardware basis of the VR head display with eye tracking, the multi-mode controller, and the gesture recognition sensor;

[0015] The cognitive decision-making assessment training module is used to set a variety of task types, collect physiological parameter data corresponding to the task types and perform multimodal data analysis, adjust the task type and task intensity, and build a multi-faceted evaluation model.

[0016] Furthermore, the multi-mode controller includes a joystick, a throttle, a rudder pedal and a VR handle.

[0017] Furthermore, the overweight and weightlessness simulation platform module is provided with a gesture recognition module, a tactile feedback module, a force tactile module, an eye movement interaction control module, a display module and an environment simulation module; wherein,

[0018] The gesture recognition module builds functions on the hardware basis of the gesture recognition sensor to achieve real-time manipulation of task functions;

[0019] The tactile feedback module uses multiple control modes in the multi-mode controller to realistically simulate relevant task scenarios of cognitive training in virtual scene tasks;

[0020] The force tactile module is used to sense the force of the subject's manipulation in real time and transmit the stability data of the subject's manipulation force;

[0021] The eye movement interaction control module is based on the VR head display with eye tracking, and is used to trigger the task process and obtain eye movement changes throughout the task process by capturing and analyzing eye movement data;

[0022] The display module includes a scene display of a VR helmet and a scene display of multiple screens spliced ​​together on a multi-degree-of-freedom hypergravity and weightlessness simulation platform;

[0023] The environment simulation module is used to adjust the task environment in real time through auditory and visual means according to the task type.

[0024] Furthermore, the display module has two different display states, namely a clear state and a blurred state; in the clear state, the subject can focus on visual interaction with the cognitive training task; in the blurred state, the subject can focus more on auditory and tactile perception.

[0025] Furthermore, the environment simulation module has two major environment scenes, namely daytime and nighttime.

[0026] Furthermore, the task types include sustained attention, position memory, perceptual decision-making, intuitive decision-making, proprioception inhibition, attention allocation, selective attention, and comprehensive tasks.

[0027] Furthermore, the attention is sustained throughout the entire process without any auxiliary interference from the overweight and weightlessness simulation platform modules;

[0028] The position memory is continuously performed in the overweight and weightlessness state of the overweight and weightlessness simulation platform module;

[0029] The perception decision is made when the overweight and weightlessness simulation platform module is shaking forward, backward, left and right;

[0030] The intuitive decision-making is performed when the overweight and weightlessness simulation platform module is tilting left and right;

[0031] The attention allocation is carried out when the overweight and weightlessness simulation platform module simulates the ship motion state;

[0032] The comprehensive task is carried out under the state that the overweight and weightlessness simulation platform module performs multi-motion scene transformation.

[0033] Furthermore, during the sustained attention, changes in key points are displayed on the multiple screens of the display module. In response to the subject's confirmation using the VR handle in the tactile feedback module, the subject's eye movement data and hand control data are recorded throughout the entire process for analyzing the subject's status at this task stage.

[0034] In the position memory, the VR helmet of the display module displays the changes in the position of the key point. In response to the subject using the VR handle to select the corresponding position of the key point in the memory, the subject's EEG data and ECG data are recorded in real time during the entire task. The EEG data and ECG data are combined with the task effect of the task stage to analyze the subject's comprehensive state;

[0035] In the perception decision, a rotating ball and a fixed column are displayed on multiple screens of the display module, and a position mark is performed in response to the subject's thrust tactile module. The thrust tactile module records the force changes at the beginning and end of the thrust, and simultaneously records the subject's eye movement data and electrocardiogram data in real time;

[0036] In the intuitive decision-making, the VR helmet of the display module displays a plurality of thin bars, and the direction is confirmed in response to the direction of the plurality of thin bars in the image observed by the subject wearing the VR helmet;

[0037] The proprioception inhibition is achieved by setting opposite task types, displaying the task on multiple screens of the display module, and responding to the subject using a joystick in the tactile feedback module, while recording the subject's EEG data and ECG data throughout the process;

[0038] In the attention allocation, the VR helmet of the display module displays a marker, and records the eye movement data when the subject observes the marker appearing in the VR helmet of the display module and performs a specified action;

[0039] The selective attention is achieved by giving different instructions to the left and right ears of the subject, and the subject uses a tactile feedback module to record the selection in response, and the entire process records EEG information in real time;

[0040] In the comprehensive task, different pictures are displayed on the multiple screens of the display module, and the subject's gesture is judged by the gesture recognition control module. In response to the relevance judgment given by the subject through the tactile feedback module, the subject's eye movement data, gesture action data, electrocardiogram data and electroencephalogram data are recorded in real time during this task stage.

[0041] Furthermore, the cognitive decision-making evaluation training module analyzes and compiles the physiological parameter data under the simplified version of the task type to establish a preliminary evaluation model, wherein the simplified version of the task type is the task type with the parameters set to the lowest version;

[0042] Based on the evaluation criteria of the task types in the evaluation model, a comprehensive analysis of the subjects' cognitive behavior is conducted, and based on the analysis results, the task types that need to be strengthened are selected and a preliminary cognitive training plan is formulated;

[0043] Conduct multiple cognitive training sessions according to the established cognitive training program. Analyze the physiological parameter data obtained from each task type each time to evaluate the training effect under each task type. At the same time, conduct a comprehensive analysis of all physiological parameter data in the current stage, establish a longitudinal evaluation model, and obtain quantitative results of the subject's cognitive training.

[0044] If the quantitative results meet the required standards, it means that the training objectives have been achieved;

[0045] If the quantification results do not meet the required standards, it is necessary to strengthen the corresponding task types based on the quantification results of each training.

[0046] A second object of the present invention is to provide a cognitive decision-making assessment training method under transient overweight and weightlessness conditions of the above-mentioned cognitive decision-making assessment training system under transient overweight and weightlessness conditions, comprising the following steps:

[0047] Analyzing and statistically analyzing physiological parameter data under a simplified version of a task type, wherein the parameters of the simplified version of the task type are set to the lowest version, and establishing a preliminary evaluation model;

[0048] Based on the evaluation criteria of the task types in the evaluation model, a comprehensive analysis of the subjects' cognitive behavior is conducted, and based on the analysis results, the task types that need to be strengthened are selected and a preliminary cognitive training plan is formulated;

[0049] Conduct multiple cognitive training sessions according to the established cognitive training program. Analyze the physiological parameter data obtained from each task type each time to evaluate the training effect under each task type. At the same time, conduct a comprehensive analysis of all physiological parameter data in the current stage, establish a longitudinal evaluation model, and obtain quantitative results of the subject's cognitive training.

[0050] If the quantitative results meet the required standards, it means that the training objectives have been achieved;

[0051] If the quantification results do not meet the required standards, it is necessary to strengthen the corresponding task types based on the quantification results of each training.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] The present invention provides a system and method for assessing cognitive decision-making in transient hypergravity and weightlessness. This system simulates the effects of hypergravity and weightlessness on a person's spatial perception, attention, learning, and memory abilities. Therefore, cognitive training in this simulated scenario, supplemented by the acquisition and comprehensive analysis of real physiological parameters acquired during the task phase, can provide a more realistic and efficient training program, helping to better enhance cognitive behavioral training.

[0054] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and to implement it according to the contents of the description, the following preferred embodiments of the present invention are described in detail with reference to the accompanying drawings. The specific implementation methods of the present invention are given in detail by the following embodiments and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0056] FIG1 is a hardware diagram of a cognitive decision-making assessment training system under transient overweight and weightlessness conditions of Example 1;

[0057] FIG2 is a diagram showing the motion of the overweight and weightlessness simulation platform of Example 1;

[0058] FIG3 is a schematic diagram of the overweight and weightlessness simulation platform module of Example 1;

[0059] FIG4 is a schematic diagram of the cognitive decision-making assessment training module of Example 1. DETAILED DESCRIPTION

[0060] The present invention will be further described below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that, under the premise of no conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0061] Example 1

[0062] The cognitive decision-making evaluation training system 1 under instantaneous overweight and weightlessness conditions, as shown in Figures 1 and 3, includes a multi-degree-of-freedom overweight and weightlessness simulation platform 2-1, a VR head display with eye tracking 2-2, a multi-mode controller 2-3, a gesture recognition sensor 2-4, a flight seat and frame structure 2-5, an overweight and weightlessness simulation platform module, and a cognitive decision-making evaluation training module; wherein,

[0063] The multi-degree-of-freedom overweight and weightlessness simulation platform is used to achieve instantaneous rapid rotation in the three major directions of lateral, horizontal, and pitch through electric drive, thereby allowing the human body to reach a state of weightlessness or overweight;

[0064] VR headsets with eye tracking are used to provide subjects with a virtual environment and capture their eye movement data in real time, thereby obtaining their true responses during the task.

[0065] The multi-mode controller is used to allow subjects to dynamically control the system platform in multiple directions during the task phase, enhancing the subjects' cognitive training experience;

[0066] In this embodiment, the multi-mode controller includes joystick control, throttle control, rudder control and VR handle control.

[0067] The gesture recognition sensor is used to realize the general gesture recognition of the subject, so as to realize the confirmation of task results under specific task types;

[0068] The flight seat and frame structure are the mechanical components of the multi-degree-of-freedom overweight and weightlessness simulation platform. The flight seat combined with the multi-degree-of-freedom overweight and weightlessness simulation platform allows the subject to experience a more realistic overweight or weightlessness state.

[0069] The overweight and weightlessness simulation platform module is a function built on the hardware foundation of a VR headset with eye tracking, a multi-mode controller, and a gesture recognition sensor.

[0070] Figure 2 shows a schematic diagram of the motion of the hypergravity and weightlessness simulation platform, which consists of a multi-degree-of-freedom hypergravity and weightlessness simulation platform, a flight seat, and a frame structure. As can be seen from the diagram, the platform can translate forward and backward, with a maximum forward movement of 250 mm, a maximum rearward movement of 220 mm, a maximum left and right movement of 280 mm, and a maximum vertical and horizontal movement of 369 mm. In addition to translation, the platform also has rotation capabilities, with a maximum left and right tilt angle of 13.5° and a maximum forward and backward tilt angle of 15°. The platform is capable of full-scale motion with multiple degrees of freedom.

[0071] The cognitive decision-making assessment training module is used to set up various task types, collect physiological parameter data corresponding to the task types and perform multimodal data analysis, adjust the task type and task intensity, and build a multi-faceted evaluation model.

[0072] As shown in Figure 3, the overweight and weightlessness simulation platform module 3 is equipped with a gesture recognition module 4-1, a tactile feedback module 4-2, a force tactile module 4-3, an eye movement interaction control module 4-4, a display module 4-5, and an environment simulation module 4-6. These six modules, based on the hardware components, together form the functional framework of the entire system.

[0073] The gesture recognition module builds functions on the hardware foundation of the gesture recognition sensor and can realize real-time manipulation of task functions in specific tasks;

[0074] The tactile feedback module uses multiple control methods in the multi-mode controller to ensure that the relevant task scenarios of cognitive training are truly simulated in the virtual scene tasks, ensuring that the subjects can feel the authenticity of the training tasks to the greatest extent, thereby achieving the training enhancement effect;

[0075] The force tactile module is used to sense the force exerted by the subject during manipulation in real time and transmit the data on the stability of the subject's manipulation force;

[0076] The eye-movement interaction control module is developed based on a VR headset with eye tracking. It can capture and analyze eye movement data in specific task types to trigger task progress and also obtain eye movement changes throughout the task process.

[0077] The display module includes the scene display of the VR helmet and the scene display of multiple screens on the multi-degree-of-freedom hypergravity and weightlessness simulation platform. In this embodiment, the scene display is composed of three screens on the multi-degree-of-freedom hypergravity and weightlessness simulation platform. These two modes together constitute the display module of the entire system, and the display module has two different display states: clear state and blurred state. In the clear state, the subject can focus on visual interaction with the cognitive training task, while in the blurred state, the subject can focus more on auditory and tactile perception.

[0078] The environmental simulation module is used to adjust the task environment in real time through hearing and vision according to the task type. There are two major environmental scenes: day and night.

[0079] Figure 4 is an overview of the cognitive assessment training method designed based on Figures 1 and 3. There are eight major task types, including sustained attention 5-1, location memory 5-2, perceptual decision-making 5-3, intuitive decision-making 5-4, proprioceptive inhibition 5-5, attention allocation 5-6, selective attention 5-7, and comprehensive tasks 5-8.

[0080] The attention span task (5-1) is a simple task, performed without the aid of the weightlessness or hypergravity simulation platform (Module 3). The subject observes the key point changes on the three-screen display (Module 4-5) and uses the VR controller (Module 4-2) to confirm them in real time. Throughout the process, the subject's eye movement data and hand control data are recorded to analyze their status during this task phase.

[0081] Position memory 5-2 is continuously performed in the hypergravity and weightlessness conditions of the hypergravity and weightlessness simulation platform module 3. The subject observes the changes in the positions of key points in the VR helmet in the display module 4-5 with the naked eye under the conditions of extreme weightlessness and hypergravity and weightlessness, quickly memorizes the position information, and uses the VR handle to select the corresponding position of the key point in the memory. During the entire task, the subject's EEG data and ECG data are recorded in real time. This data is combined with the task effect of this stage to analyze the subject's comprehensive state;

[0082] In Perception Decision 5-3, the hypergravity and weightlessness simulation platform module 3 sways forward, backward, and left, right, and right, simulating the swaying of a ship. Using a rotating ball and a fixed column displayed on the three-screen mosaic of display module 4-5, the subject is required to observe the ball's motion on the moving platform and immediately push tactile module 4-3 forward when the ball reaches the same level as the column to mark its position. This task records the force changes at the beginning and end of the push through tactile module 4-3, while also recording the subject's eye movement data and electrocardiogram data in real time.

[0083] Intuitive Decision-Making 5-4 is performed in a state where the hypergravity and weightlessness simulation platform module 3 is tilted left and right. The subject wears a VR helmet to observe the direction of several thin bars on the screen and then confirms the direction. The subject's directional perception will change during the tilting state, so this task can enhance the subject's directional perception ability in different environments.

[0084] Proprioceptive inhibition 5-5 sets the opposite task type. The subject needs to face the display task on the three-screen splicing in the display module 4-5 and use the joystick in the tactile feedback module 4-2 to respond immediately. The subject's EEG data and ECG data are recorded during the whole process.

[0085] Attention allocation 5-6: The ship's motion is simulated in the hypergravity and weightlessness simulation platform module 3. On this basis, the subject observes the "bird" or other "car" that appears in the VR helmet in the display module 4-5 and performs the specified action. The eye movement data at this time is recorded;

[0086] The selective attention task 5-7 involves giving the subject different instructions to their left and right ears, and having them make the correct choice based on the instructions. The choice is recorded using the tactile feedback module 4-2, and the EEG information of the entire process is recorded in real time.

[0087] Comprehensive tasks 5-8 include the trigger types of the previous tasks. When the overweight and weightlessness simulation platform module 3 is performing multi-motion scene transformation, the three screens in the display module 4-5 display different pictures. The subject needs to use both hands to simulate the picture gestures. The gesture recognition control module 4-1 is used to judge the subject's gestures, and at the same time, the correlation between the previous and next gestures is memorized, and the correlation judgment is given with the help of the tactile feedback module 4-2. During this task stage, the subject's eye movement data, gesture movement data, electrocardiogram data and electroencephalogram data are recorded in real time.

[0088] After each training session, multimodal data analysis is performed on the physiological parameter data corresponding to the task type performed by the subjects, and personalized scoring is performed on the tasks based on the intuitive results of the tasks and the data analysis results, so as to provide guidance for the next cognitive training. Specifically, the next task type needs to be adjusted, and the task intensity also needs to be adjusted in a timely manner.

[0089] Each of the above eight tasks has parameter adjustments for the number of targets, the time of appearance, and the speed, thereby ensuring the diversity and differentiation of the tasks. It can set up subsequent cognitive enhancement training that is more suitable for the subjects based on the response of physiological parameters, achieve more targeted and efficient training, and shorten the training time.

[0090] The specific implementation process of the cognitive decision-making assessment training system under transient hypergravity and weightlessness is as follows:

[0091] When the subjects first attempted the task, they were required to perform simplified versions of the eight tasks (i.e., time, quantity, speed, etc. were all set to the minimum version) in turn, and the physiological signals under the eight task states were analyzed and statistically analyzed to establish a preliminary evaluation model;

[0092] Based on the evaluation criteria of the eight major tasks in the evaluation model, a comprehensive analysis of the subjects' cognitive behavior is conducted, and based on the analysis results, the types of tasks that need to be strengthened are selected, and a preliminary cognitive training plan is formulated;

[0093] Conduct multiple cognitive training sessions based on customized training plans. Each time, analyze the physiological data obtained from each task type to evaluate the training effect of each task type. At the same time, conduct a comprehensive analysis of all physiological data in each stage and establish a longitudinal evaluation model to obtain quantitative results of the subject's cognitive training.

[0094] If the quantitative results can meet the required standards (the standards are set by doctors or professionals), it means that the training goals have been achieved; if the quantitative results cannot meet the required standards, it is necessary to strengthen the corresponding task types according to the quantitative results of each training, so as to carry out more targeted and efficient intensive training.

[0095] The present invention designs a cognitive enhancement training system under overweight and weightlessness conditions, which can achieve more realistic cognitive training; constructs a physiological parameter evaluation model based on overweight and weightlessness conditions, which can construct a quantitative model for cognition under weightlessness and overweight conditions; fills the gap in the traditional fixed-form cognitive training model, and has a training system with both rehabilitation and enhancement functions.

[0096] Example 2

[0097] The cognitive decision-making assessment training method for transient overweight and weightlessness provided in Example 1, corresponding to the cognitive decision-making assessment training system for transient overweight and weightlessness, can be found in the corresponding description of the above system embodiment and will not be repeated here. As shown in Figure 4, the method includes the following steps:

[0098] When the subjects first attempted the task, they were required to perform simplified versions of the eight tasks (i.e., time, quantity, speed, etc. were all set to the minimum version) in turn, and the physiological signals under the eight task states were analyzed and statistically analyzed to establish a preliminary evaluation model;

[0099] Based on the evaluation criteria of the eight major tasks in the evaluation model, a comprehensive analysis of the subjects' cognitive behavior is conducted, and based on the analysis results, the types of tasks that need to be strengthened are selected, and a preliminary cognitive training plan is formulated;

[0100] Conduct multiple cognitive training sessions based on customized training plans. Each time, analyze the physiological data obtained from each task type to evaluate the training effect of each task type. At the same time, conduct a comprehensive analysis of all physiological data in each stage and establish a longitudinal evaluation model to obtain quantitative results of the subject's cognitive training.

[0101] If the quantitative results can meet the required standards (the standards are set by doctors or professionals), it means that the training goals have been achieved; if the quantitative results cannot meet the required standards, it is necessary to strengthen the corresponding task types according to the quantitative results of each training, so as to carry out more targeted and efficient intensive training.

[0102] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0103] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0104] The above are merely examples of the present invention and are not intended to limit one or more embodiments of the present invention. For those skilled in the art, various modifications and variations of one or more embodiments of the present invention may be made. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of the present invention shall be included within the scope of the claims of one or more embodiments of the present invention.

Claims

1. A cognitive decision-making assessment training system under transient overweight and weightlessness conditions, characterized by: It includes a multi-degree-of-freedom overweight and weightlessness simulation platform, a VR headset with eye tracking, a multi-mode controller, a gesture recognition sensor, a flight seat and frame structure, an overweight and weightlessness simulation platform module, and a cognitive decision-making assessment training module; among them, The multi-degree-of-freedom overweight and weightlessness simulation platform is used to realize instantaneous rapid rotation in three major directions, namely, lateral, horizontal and pitch, through electric drive, so that the human body reaches a state of weightlessness or overweight; The VR head display with eye tracking is used to provide a virtual environment scene for the subject, and at the same time capture the subject's eye movement data information in real time to obtain the subject's real reaction during the task stage; The multi-mode controller is used to allow the subject to actually dynamically control the system platform in multiple directions during the task phase, thereby enhancing the subject's cognitive training experience; The gesture recognition sensor is used to realize gesture recognition of the subject and to realize task result confirmation under the preset task type; The flight seat and frame structure are mechanical structures that constitute a multi-degree-of-freedom overweight and weightlessness simulation platform; The overweight and weightlessness simulation platform module is a function built on the hardware basis of the VR head display with eye tracking, the multi-mode controller, and the gesture recognition sensor; The cognitive decision-making evaluation training module is used to set a variety of task types, collect physiological parameter data corresponding to the task types and perform multimodal data analysis, adjust the task type and task intensity, and build a multi-faceted evaluation model.

2. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 1, characterized in that: The multi-mode controller includes a joystick, a throttle, a rudder pedal and a VR handle.

3. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 2, characterized in that: The overweight and weightlessness simulation platform module is provided with a gesture recognition module, a tactile feedback module, a force tactile module, an eye movement interaction control module, a display module and an environment simulation module; wherein, The gesture recognition module builds functions on the hardware of the gesture recognition sensor to achieve real-time manipulation of task functions; The tactile feedback module uses multiple control modes in the multi-mode controller to truly simulate relevant task scenes of cognitive training in virtual scene tasks; The force tactile module is used to sense the force of the subject's manipulation in real time and transmit the stability data of the subject's manipulation force; The eye movement interaction control module is based on the VR head display with eye movement tracking, and is used to trigger the task process and obtain the eye movement changes throughout the task process by capturing and analyzing the eye movement data; The display module includes a scene display of a VR helmet and a scene display of multiple screens spliced ​​together on a multi-degree-of-freedom supergravity and weightlessness simulation platform; The environment simulation module is used to adjust the task environment in real time through hearing and vision according to the task type.

4. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 3, characterized in that: The display module has two different display states, namely a clear state and a blurred state; in the clear state, the subject can focus on the visual interaction with the cognitive training task; in the blurred state, the subject can focus more on auditory and tactile perception.

5. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 3, characterized in that: The environment simulation module has two major environment scenes, namely day and night.

6. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 3, characterized in that: The task types include sustained attention, position memory, perceptual decision-making, intuitive decision-making, proprioceptive inhibition, divided attention, selective attention, and comprehensive tasks.

7. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 6, characterized in that: The attention is sustained throughout the process without any auxiliary interference from the overweight and weightlessness simulation platform modules; The position memory is continuously performed under the overweight and weightlessness conditions of the overweight and weightlessness simulation platform module; The perception decision is made when the overweight and weightlessness simulation platform module is shaking forward, backward, left and right; The intuitive decision is made when the overweight and weightlessness simulation platform module is tilted left and right; The attention allocation is performed when the overweight and weightlessness simulation platform module simulates the ship motion state; The comprehensive task is carried out under the condition that the overweight and weightlessness simulation platform module performs multi-motion scene transformation.

8. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 6, characterized in that: During the attention, the key point changes are displayed on the multiple screens of the display module, and in response to the subject's confirmation using the VR handle in the tactile feedback module, the subject's eye movement data and hand control data are recorded throughout the process for analyzing the subject's state at this task stage; In the position memory, the VR helmet of the display module displays the change of the key point position, in response to the subject using the VR handle to select the corresponding position of the key point in the memory, the EEG data and ECG data of the subject are recorded in real time during the whole task process, and the EEG data and ECG data are combined with the task effect of the task stage to analyze the comprehensive state of the subject; In the perception decision, a rotating ball and a fixed column are displayed on the multiple screens of the display module, and the position is marked in response to the thrust tactile module of the subject, and the force changes at the beginning and end of the thrust are recorded by the thrust tactile module, and the eye movement data and electrocardiogram data of the subject are recorded in real time; In the intuitive decision, the VR helmet of the display module displays a plurality of thin bars, and confirms the direction in response to the direction of the plurality of thin bars in the picture observed by the subject wearing the VR helmet; The proprioceptive inhibition is performed by setting opposite task types, displaying the task on multiple screens of the display module, responding to the subject using a joystick in the tactile feedback module, and recording the subject's EEG data and ECG data during the whole process; In the attention allocation, the VR helmet of the display module displays a marker, and records the eye movement data when the subject observes the marker appearing in the VR helmet of the display module and performs a specified action; The selective attention is performed by giving different instructions to the left and right ears of the subject, and in response to the subject using a tactile feedback module to record the selection, and the whole process records the EEG information in real time; In the comprehensive task, different pictures are displayed on the multiple screens of the display module, and the subject's gesture is judged by the gesture recognition control module. In response to the relevance judgment given by the subject through the tactile feedback module, the subject's eye movement data, gesture action data, electrocardiogram data and electroencephalogram data are recorded in real time during this task stage.

9. The cognitive decision-making assessment training system under transient overweight and weightlessness conditions as claimed in claim 6, characterized in that: The cognitive decision-making evaluation training module analyzes and counts the physiological parameter data under the simplified version of the task type to establish a preliminary evaluation model, wherein the simplified version of the task type is a task type with parameters set to the lowest version; Based on the evaluation criteria of the task type in the evaluation model, the subjects’ cognitive behaviors were comprehensively graded. Analyze and select the task types that need to be strengthened based on the analysis results, and develop a preliminary cognitive training plan; Conduct multiple cognitive training sessions according to the developed cognitive training program, analyze the physiological parameter data obtained from each task type, evaluate the training effect under each task type, and conduct a comprehensive analysis of all physiological parameter data at the current stage, establish a longitudinal evaluation model, and obtain the quantitative results of the subject's cognitive training; If the quantitative results meet the required standards, it means that the training objectives have been achieved; If the quantification results do not meet the required standards, it is necessary to strengthen the corresponding task types in a targeted manner based on the quantification results of each training.

10. The cognitive decision-making assessment training method under transient overweight and weightlessness conditions of the cognitive decision-making assessment training system under transient overweight and weightlessness conditions according to any one of claims 1 to 9, characterized in that: The following steps are involved: Analyzing and statistically analyzing the physiological parameter data under the simplified version of the task type to establish a preliminary evaluation model, wherein the simplified version of the task type is a task type with parameters set to the lowest version; Based on the evaluation criteria of the task types in the evaluation model, a comprehensive analysis of the subjects' cognitive behaviors was conducted, and the task types that needed to be strengthened were selected based on the analysis results, and a preliminary cognitive training program was developed; Conduct multiple cognitive training sessions according to the developed cognitive training program, analyze the physiological parameter data obtained from each task type, evaluate the training effect under each task type, and conduct a comprehensive analysis of all physiological parameter data at the current stage, establish a longitudinal evaluation model, and obtain the quantitative results of the subject's cognitive training; If the quantitative results meet the required standards, it means that the training objectives have been achieved; If the quantification results do not meet the required standards, it is necessary to strengthen the corresponding task types in a targeted manner based on the quantification results of each training.

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