CN117476182A - Cognitive decision-making assessment training system and method under instantaneous overweight and weightlessness conditions - Google Patents

Abstract

The invention provides a cognitive decision evaluation training system and a cognitive decision evaluation training method in an instantaneous overweight and weightlessness state. The spatial perceptibility and attentiveness of the person and the ability to learn and memorize will be affected to different extents in the overweight and weightless state of the system. Therefore, the cognitive training is performed under the simulation scene, the acquisition and comprehensive analysis of the real physiological parameters acquired through the task stage are assisted, a more real and efficient training scheme can be provided for people, and the better reinforcement training of the cognitive behaviors can be realized.

Description

Cognitive decision-making assessment training system and method under instantaneous overweight and weightlessness conditions

Technical field

The present invention relates to the technical field of cognitive training enhancement, and in particular to cognitive decision-making assessment training systems and methods under instantaneous overweight and weightlessness states.

Background technique

The Chinese patent with publication number CN103268392A discloses a cognitive function training system and method based on situational interaction. The system includes a human-computer interaction device and a touch display screen and interactive scene memory connected to it respectively. The user wearing 3D glasses touches the display. You can interact with the human-computer interaction device through the screen. The human-computer interaction device includes information input, recognition, analysis, storage, feedback, and output modules and a virtual scene simulation module. The information on 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 from 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 cognitive function training program feedback system is pre-stored in the information feedback module.

The Chinese patent with announcement number CN108335747B discloses a cognitive training system. The system includes a first operating end, a second operating end and a system end. The first operating terminal can edit cognitive training media and save it to the system. During use, the system transmits media files to the second operating terminal for display, and collects data from the second operating terminal for judgment to complete cognitive training. The system side includes database, sample extraction module and cognitive training module. The characteristic of this patent is that it can conduct intensive training based on the statistics of cognitive results to obtain features with low accuracy, and can provide customized services to improve training effects.

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, touch panel, motion sensor, 3D display and database. The host determines the difficulty level of the patient's current 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 computer. The motion sensor is worn on the patient's head and collects hand movement data. The 3D stereoscopic display can display virtual reality scenes and provide an immersive training environment. The database stores preset training scenarios, patient assessment levels, training data, etc. The deep learning unit in the evaluation unit collects operation data and hand movement data. Based on the data, the deep learning unit generates a training evaluation report and adjusts the patient's next training difficulty and scene data based on the report.

The Chinese patent with publication number CN113192600A discloses a cognitive assessment and correction training system based on virtual reality and eye tracking, including an eye tracking module, an assessment module and a training module. The eye tracking module obtains the coordinates of the gaze point from the VR device, and the eye tracking module is connected to the evaluation module and the training module respectively. Assessment modules include attention, executive function and memory assessment modules. The training module includes the above three aspects. This system scores the patient's calculation ability, positive emotions and other seven dimensions after the experience. After collecting the eye movement data, it calculates the gaze time, gaze hit rate and other characteristics to complete the cognitive assessment function. and training functions.

However, the above patents all evaluate cognitive behavior under "static" conditions, that is, the subjects are in a static environment in a real scene and cannot truly feel the real simulation tasks in cognitive training. There is mechanical training. Therefore, it is impossible to truly stimulate the subject's state in cognitive training, and it is also impossible to truly conduct later intensive training for the subject. At the same time, existing technology cannot obtain physiological parameter information in cognitive training, but physiological parameter information in cognitive training is very important for analyzing the physical status of the subject, especially when the subject needs to undergo multiple intensive trainings. , 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.

Contents of the invention

In order to achieve the above objects and other advantages of the present invention, the first object of the present invention is to provide a cognitive decision-making evaluation training system under instantaneous overweight and weightlessness conditions, including a multi-degree-of-freedom overweight and weightlessness simulation platform, and a VR head with eye tracking Display, multi-mode controller, gesture recognition sensor, flight seat and frame structure, overweight and weightlessness simulation platform module, cognitive decision-making assessment training module; among them,

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

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

The multi-mode controller is used to allow subjects to actually dynamically control the system platform in multiple directions during the task phase to enhance the subjects' cognitive training experience;

The gesture recognition sensor is used to realize gesture recognition of subjects and confirm task results under preset task types;

The flight seat and frame structure are mechanical structures that form 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 assessment training module is used to set multiple task types, collect physiological parameter data corresponding to the task types and perform multi-modal data analysis, adjust task types and task intensity, and build a multi-faceted evaluation model.

Further, the multi-mode controller includes a joystick, throttle, foot rudder and VR handle.

Further, the overweight and weightlessness simulation platform module is equipped 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 based on the hardware of the gesture recognition sensor to realize real-time manipulation of task functions;

The tactile feedback module uses a variety of control methods in the multi-mode controller to truly simulate cognitive training-related task scenarios 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 smoothness 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 through the capture and analysis of eye movement data, and obtain the eye movement changes throughout the task process;

The display module includes the scene display of the VR helmet and the scene display of multiple screens spliced on the multi-degree-of-freedom overgravity and weightlessness simulation platform;

The environment simulation module is used to adjust the environment of the task in real time through hearing and vision according to the task type.

Further, 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 hearing and tactile perception.

Further, the environment simulation module has two major environmental scenes, namely day and night.

Further, the task types include sustained attention, location memory, perceptual decision-making, intuitive decision-making, proprioceptive inhibition, attention distribution, selective attention, and comprehensive tasks.

Further, there is no auxiliary interference from the overgravity and weightlessness simulation platform modules throughout the entire process of sustained attention;

The position memory continues in the overgravity and weightlessness states of the overgravity and weightlessness simulation platform module;

The sensing decision-making is performed while the overgravity and weightlessness simulation platform modules are rocking back and forth, left and right;

The intuitive decision-making is performed when the overgravity and weightlessness simulation platform modules are tilting left and right;

The attention distribution is performed when the overweight and weightless simulation platform modules simulate ship motion;

The comprehensive task is carried out in the state of multi-motion scene transformation by the overgravity and weightlessness simulation platform modules.

Further, while the attention is sustained, key point changes are displayed on the multiple screens of the display module. In response to the subject using the VR handle in the tactile feedback module for confirmation, the entire process records the subject's eyesight. Movement data and hand control data are used to analyze the subject's status during this task stage;

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

In the perception decision-making, the multiple screens of the display module are spliced to display rotating balls and fixed columns. In response to the subject's thrust tactile module, the position is marked, and the thrust tactile module records the beginning and end of the thrust. changes, while recording the subject’s eye movement data and ECG data in real time;

In the intuitive decision-making, the VR helmet of the display module displays several thin bars, and the direction is confirmed in response to the direction of the several thin bars in the observation screen of the subject wearing the VR helmet;

The proprioceptive suppression is performed by setting the opposite task type, displaying the task on multiple screens of the display module, responding to the subject's reaction using the joystick in the tactile feedback module, and recording the subject's brain throughout the process. Electrical data and ECG data;

In the distribution of attention, the VR helmet of the display module displays a marker, and records eye movement data when the subject observes the marker appearing in the VR helmet of the display module and makes 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 the tactile feedback module to record the selection, the entire process records EEG information in real time;

In the comprehensive task, different pictures are displayed on multiple screens of the display module, and the subject's gesture is judged through the gesture recognition control module, in response to the correlation judgment given by the subject through the tactile feedback module. , During this task phase, the subject's eye movement data, gesture action data, ECG data and EEG data are recorded in real time.

Further, the cognitive decision-making assessment training module analyzes and statistics the physiological parameter data under a simplified version of the task type, and establishes a preliminary evaluation model. The simplified version of the task type is the task type with the parameters set to the lowest version;

Based on the evaluation criteria of task types in the evaluation model, conduct a comprehensive analysis of the cognitive behavior of the subjects, select the task types that need to be strengthened based on the analysis results, and formulate a preliminary cognitive training plan;

Conduct multiple cognitive trainings according to the formulated cognitive training plan. Each time, the physiological parameter data obtained from the task type is analyzed, and the training effect under each task type is evaluated. At the same time, all the tasks under the current stage are analyzed. Comprehensive analysis of physiological parameter data, establishing a longitudinal evaluation model, and obtaining quantitative results of subjects' cognitive training;

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

If the quantitative results do not meet the required standards, the corresponding task type needs to be strengthened based on the quantitative results of each training session.

The second object of the present invention is to provide the above-mentioned cognitive decision-making evaluation and training system for instant overweight and weightlessness, and a method for cognitive decision-making evaluation and training under instantaneous overweight and weightlessness, which includes the following steps:

Analyze and count the physiological parameter data under a simplified version of the task type, and establish a preliminary evaluation model. The simplified version of the task type is the task type with the parameters set to the lowest version;

Based on the evaluation criteria of task types in the evaluation model, conduct a comprehensive analysis of the cognitive behavior of the subjects, select the task types that need to be strengthened based on the analysis results, and formulate a preliminary cognitive training plan;

Conduct multiple cognitive trainings according to the formulated cognitive training plan. Each time, the physiological parameter data obtained from the task type is analyzed, and the training effect under each task type is evaluated. At the same time, all the tasks under the current stage are analyzed. Comprehensive analysis of physiological parameter data, establishing a longitudinal evaluation model, and obtaining quantitative results of subjects' cognitive training;

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

If the quantitative results do not meet the required standards, the corresponding task type needs to be strengthened based on the quantitative results of each training session.

Compared with the prior art, the beneficial effects of the present invention are:

The present invention provides a system and method for cognitive decision-making evaluation and training under instantaneous overweight and weightlessness conditions. In the system's overweight and weightlessness conditions, people's spatial perception ability and attention, as well as learning and memory abilities will be affected to varying degrees. Therefore, conducting cognitive training under this simulated scenario, and assisting in the acquisition and comprehensive analysis of real physiological parameters obtained through the task stage, can provide people with more realistic and efficient training programs and help people better achieve cognitive behavior. Intensive training.

The above description is only an overview of the technical solutions of the present invention. In order to have a clearer understanding of the technical means of the present invention and implement them according to the contents of the description, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Specific embodiments of the present invention are given in detail by the following examples and accompanying drawings.

Description of the drawings

The drawings described here are used to provide a further understanding of the present invention and constitute a part of this application. The illustrative 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 attached picture:

Figure 1 is a hardware composition diagram of the cognitive decision-making assessment and training system under instantaneous overweight and weightlessness conditions in Embodiment 1;

Figure 2 is a movement display diagram of the overgravity and weightlessness simulation platform in Embodiment 1;

Figure 3 is a schematic diagram of the overgravity and weightlessness simulation platform module of Embodiment 1;

Figure 4 is a schematic diagram of the cognitive decision-making assessment training module of Embodiment 1.

Detailed ways

Below, the present invention will be further described with reference to the accompanying drawings and specific embodiments. It should be noted that, on the premise that there is no conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments. .

Example 1

The cognitive decision-making assessment and training system 1 under instantaneous overweight and weightlessness states, as shown in Figures 1 and 3, includes a multi-degree-of-freedom overweight and weightlessness simulation platform 2-1, a VR headset with eye tracking 2-2, and multiple Model controller 2-3, gesture recognition sensor 2-4, flight seat and frame structure 2-5, overweight and weightlessness simulation platform module, cognitive decision-making assessment training module; among them,

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

VR headsets with eye tracking are used to provide subjects with virtual environment scenes, and at the same time, they can capture the subjects' eye movement data information in real time to obtain the subjects' real reactions during the task phase;

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

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

Gesture recognition sensors are used to realize general gesture recognition of subjects, thereby confirming task results under specific task types;

The flight seat and frame structure are the mechanical structural parts of the multi-degree-of-freedom overgravity and weight-loss simulation platform; among them, the flight seat plus the multi-degree-of-freedom overgravity and weight-loss simulation platform can allow subjects to be in a more realistic overweight or weightlessness state. under;

The overgravity and weightlessness simulation platform module is a function built on the hardware of a VR head-mounted display with eye tracking, a multi-mode controller, and a gesture recognition sensor.

Figure 2 shows the motion diagram of the overgravity and weightlessness simulation platform, which is composed of a multi-degree-of-freedom overgravity and weightlessness simulation platform, a flight seat, and a frame structure. As can be seen from the figure, the platform can translate forward and backward, with the forward movement limit distance being 250 mm, the rear movement limit distance being 220 mm, the left and right side movement limit distance being 280 mm, and the up and down raising and lowering distances being 369 mm. At the same time, in addition to the translation function, the platform also has a rotation function. The limit angle of left and right side tilt is 13.5°, and the angle of front and rear tilt is 15°. This platform can realize all-round motion with multiple degrees of freedom.

The cognitive decision-making assessment training module is used to set multiple task types, collect physiological parameter data corresponding to the task types and conduct multi-modal data analysis, adjust task types and task intensity, and build a multi-faceted evaluation model.

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 haptic module 4-3, an eye movement interaction control module 4-4, and a display module 4- 5 and environment simulation modules 4-6; the six modules, based on the hardware composition, together form the functional framework of the entire system. in,

The gesture recognition module builds functions based on the hardware of the gesture recognition sensor, and can realize real-time manipulation of task functions in specific tasks;

The tactile feedback module uses a variety of control methods in the multi-mode controller to ensure that the relevant task scenarios of cognitive training are truly simulated in the virtual scene task, ensuring that the subjects can experience the authenticity of the training task to the greatest extent, thereby achieving training enhancement. Effect;

The force haptic module is used to sense the force of the subject's manipulation in real time and transmit the smoothness data of the subject's manipulation force;

The eye movement interaction control module is developed based on a VR headset with eye tracking. It can trigger the task process through the capture and analysis of eye movement data in specific task types, and can also obtain the entire eye movement changes during the task process;

The display module includes the scene display of the VR helmet and the scene display of multiple screens spliced on the multi-degree-of-freedom overgravity and weight-loss simulation platform; in this embodiment, three screens are spliced on the multi-degree-of-freedom overgravity and weight-loss simulation platform. The two modes together constitute the display module of the entire system, and the display module has two different display states, namely clear state and blurred state. In the clear state, the subject can focus on the visual interaction with the cognitive training task, and in the blurred state, the subject can focus on the visual interaction with the cognitive training task. In this state, subjects can focus more on hearing and tactile perception.

The environment 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, namely day and night.

Figure 4 is a general diagram of the cognitive assessment training method based on the design of Figures 1 and 3. There are 8 major task types. Task types include attention sustainment 5-1, location memory 5-2, perceptual decision-making 5-3, intuitive decision-making 5-4, proprioceptive inhibition 5-5, attention allocation 5-6, and selectivity. Note 5-7 and comprehensive tasks 5-8.

The task of attention span 5-1 is a simple task. There is no auxiliary interference from overweight and weightlessness simulation platform module 3 in the whole process. The subjects change the key points through the three-screen splicing in the display module 4-5 and use tactile feedback. The VR controller in module 4-2 is confirmed in time. The entire process records the subject's eye movement data and hand control data, which is used to analyze the subject's status during this task stage;

Position memory 5-2 continues in the overweight and weightless state of the overweight and weightless simulation platform module 3. The subject observes with the naked eye the key in the VR helmet in module 4-5 in the state of extreme weightlessness and overweight and weightlessness. point position changes, quickly memorize the position information, and use 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 effects are used to analyze the subject’s comprehensive state;

In Perception Decision 5-3, the overweight and weightlessness simulation platform module 3 rocks back and forth, left and right, to simulate the shaking of the ship. With the help of the rotating ball and fixed column displayed on the three-screen splicing in the display module 4-5, the subject needs Observe the movement state of the ball on the moving platform, and when the ball moves to the same level as the column, immediately push the tactile module 4-3 forward to mark the position. In this task, the force changes at the beginning and end of the thrust were recorded through the thrust tactile module 4-3. At the same time, the subject's eye movement data and ECG data were also recorded in real time;

Intuitive decision-making 5-4 is carried out in the state of overweight and weightlessness simulation platform module 3 tilting left and right. The subject wears a VR helmet to observe the direction of several thin strips in the screen, and then confirms the direction. Under the state of tilting left and right, the subject The subject's direction perception will change, so this task can strengthen the subject's direction perception ability in different environments;

Proprioceptive Inhibition 5-5 By setting 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, and the entire During the process, the subject's EEG data and ECG data were recorded;

Attention allocation 5-6 simulates the ship's motion state in the overweight and weightless simulation platform module 3. On this basis, the subject observes the "bird" or other "car" appearing in the VR helmet in the display module 4-5. ", and make the specified action to record the eye movement data at this time;

The Selective Attention 5-7 task is performed by giving different instructions to the left and right ears of the subject, making correct choices according to the instructions, and using the tactile feedback module 4-2 to record the choices. The EEG information of the entire process is recorded in real time;

Comprehensive tasks 5-8 include the first several task trigger types. In the state of multi-sport scene transformation in the overweight and weightless simulation platform module 3, the three screens in the display module 4-5 are spliced to display different pictures. The subjects need to use Simulate picture gestures with both hands, use the gesture recognition control module 4-1 to judge the subject's gestures, and at the same time remember the correlation between the previous and next gestures, and use the tactile feedback module 4-2 to make a correlation judgment. In this task During this stage, the subject's eye movement data, gesture action data, ECG data and EEG data were recorded in real time.

After each training session, multi-modal data analysis is performed on the physiological parameter data corresponding to the task type performed by the subject, and personalized scores are given for the task based on the visual results of the task and the data analysis results. Give guiding opinions for the next cognitive training, specifically adjusting the type of tasks to follow, and also need to make timely adjustments to the intensity of the tasks.

Each of the above 8 major tasks has parameter adjustments for the number of targets, appearance time and speed, thereby ensuring the diversity and distinction of the tasks, and can be set according to the response of physiological parameters to be more in line with the subject's subsequent cognition. Strengthen training to achieve more targeted and efficient training and shorten training time.

The specific implementation process of the cognitive decision-making assessment training system under instantaneous overweight and weightlessness conditions is as follows:

When the subjects try it for the first time, they need to do the simplified versions of the 8 tasks (that is, the time, quantity, speed, etc. are all set to the lowest version) in turn, and analyze the physiological signals under the 8 task states to establish a preliminary evaluation. Model;

Based on the evaluation criteria under the 8 major tasks in the evaluation model, conduct a comprehensive analysis of the cognitive behavior of the subjects, select the types of tasks that need to be strengthened based on the analysis results, and formulate a preliminary cognitive training plan;

Conduct multiple cognitive trainings according to customized training programs. Each time, the physiological data obtained from the task type needs to be analyzed, and the training effect under each task type needs to be evaluated. At the same time, all physiological data at each stage must be analyzed. Conduct comprehensive analysis and establish a longitudinal evaluation model to obtain quantitative results of subjects' cognitive training;

If the quantified results can meet the required standards (the standards are specified by doctors or professionals), it means that the training goals have been achieved; if the quantified results cannot meet the required standards, it is necessary to strengthen targeted measures based on the quantified results of each training. Corresponding task types, so as to conduct more targeted and efficient intensive training.

The present invention designs a cognitive strengthening training system in overweight and weightless states, which can achieve more realistic cognitive training; and constructs a physiological parameter evaluation model based on overweight and weightless states, which can evaluate the physiological parameters in weightless and overweight states. Cognitive construction quantitative model; a training system that fills in the traditional fixed-form cognitive training model and has both rehabilitation and strengthening functions.

Example 2

The cognitive decision-making evaluation and training system for instantaneous overweight and weightlessness provided in Embodiment 1 corresponds to the cognitive decision-making evaluation and training method for instantaneous overweight and weightlessness. For a detailed description of the system, please refer to the corresponding description in the above system embodiment. , which will not be described in detail here. As shown in Figure 4, the method includes the following steps:

When the subjects try it for the first time, they need to do the simplified versions of the 8 tasks (that is, the time, quantity, speed, etc. are all set to the lowest version) in turn, and analyze the physiological signals under the 8 task states to establish a preliminary evaluation. Model;

Based on the evaluation criteria under the 8 major tasks in the evaluation model, conduct a comprehensive analysis of the cognitive behavior of the subjects, select the types of tasks that need to be strengthened based on the analysis results, and formulate a preliminary cognitive training plan;

Conduct multiple cognitive trainings according to customized training programs. Each time, the physiological data obtained from the task type needs to be analyzed, and the training effect under each task type needs to be evaluated. At the same time, all physiological data at each stage must be analyzed. Conduct comprehensive analysis and establish a longitudinal evaluation model to obtain quantitative results of subjects' cognitive training;

If the quantified results can meet the required standards (the standards are specified by doctors or professionals), it means that the training goals have been achieved; if the quantified results cannot meet the required standards, it is necessary to strengthen targeted measures based on the quantified results of each training. Corresponding task types, so as to conduct more targeted and efficient intensive training.

It should also be noted that the terms "comprises," "comprises" or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements not only includes those elements, but also includes Other elements are not expressly listed or are inherent to the process, method, article or equipment. Without further limitation, an element qualified by the statement "comprises a..." does not exclude the presence of additional identical elements in the process, method, good, or device that includes the element.

Each embodiment in this specification is described in a progressive manner. The same and similar parts between the various embodiments can be referred to each other. Each embodiment focuses on its differences from other embodiments.

The above are only embodiments of this specification and are not intended to limit one or more embodiments of this specification. For those skilled in the art, various modifications and transformations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of this specification shall be included in the scope of the claims of one or more embodiments of this specification.

Claims (10)

1. The cognitive decision evaluation training system in the instantaneous overweight and weightlessness state is characterized in that: the system comprises a multi-degree-of-freedom overweight and weightlessness simulation platform, a VR head display with eye tracking, a multimode controller, a gesture recognition sensor, a flight seat and frame structure, an overweight and weightlessness simulation platform module and a cognitive decision evaluation training module; wherein,

the multi-degree-of-freedom overweight and weightlessness simulation platform is used for realizing instantaneous rapid rotation in three directions of transverse, horizontal and pitching through electric drive, so that a human body can achieve a weightlessness or overweight state;

the VR head display with eye movement tracking is used for providing a virtual environment scene for a subject, capturing eye movement data information of the subject in real time, and acquiring real response of the subject in a task stage;

the multimode controller is used for enabling the subjects to actually control the system platform in multiple directions in a task stage, so that the cognitive training experience of the subjects is enhanced;

the gesture recognition sensor is used for realizing gesture recognition of a subject and realizing task result confirmation under a preset task type;

the flight seat and the frame structure are mechanical structures forming an overweight and weightlessness simulation platform with multiple degrees of freedom;

the overweight and weightlessness simulation platform module is a function constructed on the basis of hardware of the VR head display with eye movement tracking, the multimode controller and the gesture recognition sensor;

the cognitive decision evaluation training module is used for setting a plurality of task types, collecting physiological parameter data corresponding to the task types, performing multi-mode data analysis, adjusting the task types and task intensity, and constructing a multi-azimuth evaluation model.

2. The cognitive decision assessment training system in transient overweight and weightlessness conditions of claim 1, wherein: the multimode controller includes a joystick, throttle, rudder, and VR handle.

3. The cognitive decision assessment training system in transient overweight and weightlessness conditions of claim 2, wherein: the overweight and weightlessness simulation platform module is provided with a gesture recognition module, a touch feedback module, a force touch module, an eye movement interaction control module, a display module and an environment simulation module; wherein,

the gesture recognition module builds functions on the basis of hardware of the gesture recognition sensor, and realizes real-time manipulation of task functions;

the haptic feedback module uses a plurality of control modes in the multimode controller to truly simulate relevant task scenes of cognitive training in virtual scene tasks;

the force touch module is used for sensing the force of the subject during the manipulation in real time and transmitting the stability data of the manipulation force of the subject;

the eye movement interaction control module is used for triggering a task process and acquiring the whole eye movement change in the task process through capturing and analyzing eye movement data based on the VR head display with eye movement tracking;

the display module comprises scene display of the VR helmet and scene display under the splicing of a plurality of screens on the overweight and weightless simulation platform with multiple degrees of freedom;

the environment simulation module is used for adjusting the environment where the task is located in real time through auditory vision according to the task type.

4. A cognitive decision assessment training system in transient overweight and weightlessness conditions according to claim 3, wherein: the display module is provided with two different display states, namely a clear state and a fuzzy state; in a clear state, the subject can concentrate on visual interaction with the cognitive training task; in the blurred state, the subject is able to focus more on auditory and tactile sensations.

5. A cognitive decision assessment training system in transient overweight and weightlessness conditions according to claim 3, wherein: the environment simulation module has two large environment scenes, namely day and night.

6. A cognitive decision assessment training system in transient overweight and weightlessness conditions according to claim 3, wherein: the task types include attention duration, location memory, perceptual decision, intuitive decision, ontology suppression, attention allocation, selective attention, comprehensive tasks.

7. The cognitive decision assessment training system in transient overweight and weightlessness status of claim 6, wherein:

the whole continuous attention process is free of auxiliary interference of overweight and weightlessness simulation platform modules;

the position memory is continuously performed in overweight and weightlessness states of the overweight and weightlessness simulation platform module;

the perception decision is carried out in a front-back left-right shaking state by the overweight and weightlessness simulation platform module;

the intuitionistic decision is carried out in a state that the overweight and weightlessness simulation platform module carries out left-right tilting motion;

the attention distribution is carried out under the state that the overweight and weightless simulation platform module simulates the ship movement;

the comprehensive tasks are carried out under the state that the overweight and weightless simulation platform module carries out multi-motion scene transformation.

8. The cognitive decision assessment training system in transient overweight and weightlessness status of claim 6, wherein: in the continuous attention, key point changes are displayed on a plurality of screens of the display module in a spliced manner, and in response to confirmation of a subject by using a VR handle in the haptic feedback module, the whole process records eye movement data and hand control data of the subject and is used for analyzing the state of the subject in the task stage;

in the position memory, a VR helmet of the display module displays the change of the positions of the key points, the corresponding positions of the key points in the memory are selected in response to the use of a VR handle by a subject, the brain electrical data and the electrocardio data of the subject are recorded in real time in the whole task process, and the comprehensive state of the subject is analyzed by combining the brain electrical data and the electrocardio data with the task effect of the task stage;

in the perception decision, a plurality of screens of the display module are spliced to display a rotary small ball and a fixed upright post, the position of the rotary small ball and the fixed upright post is marked in response to the thrust touch module of the subject, the thrust touch module is used for recording the force change in the beginning and the ending of the thrust, and simultaneously, the eye movement data and the electrocardiograph data of the subject are recorded in real time;

in the intuitionistic decision, a VR helmet of the display module displays a plurality of thin strips, and the direction is confirmed in response to the direction that a subject wears the plurality of thin strips in an observation picture of the VR helmet;

the body suppresses display tasks on a plurality of screens of the display module by setting opposite task types, responds to the response of a subject by using a control rod in the touch feedback module, and records brain electricity data and electrocardio data of the subject in the whole process;

in the attention distribution, the VR helmet of the display module displays a marker, and eye movement data when a subject observes the marker appearing in the VR helmet of the display module and makes a specified action is recorded;

the selective attention responds to the record selection of the subject by giving different instructions to the left ear and the right ear of the subject, and the whole process records the electroencephalogram information in real time;

in the comprehensive task, different pictures are displayed on the multiple screens of the display module in a spliced manner, the gesture of the subject is judged through the gesture recognition control module, and in response to the correlation judgment given by the subject through the touch feedback module, the eye movement data, gesture movement data, electrocardiographic data and electroencephalogram data of the subject are recorded in real time in the task stage.

9. The cognitive decision assessment training system in transient overweight and weightlessness status of claim 6, wherein: the cognitive decision evaluation training module analyzes and counts physiological parameter data under a simplified version task type, and a preliminary evaluation model is established, wherein the simplified version task type is a task type with parameters set as the lowest version;

comprehensively analyzing the cognitive behaviors of the subjects based on the evaluation standard of task types in the evaluation model, selecting the task types needing to be enhanced according to the analysis result, and formulating a preliminary cognitive training scheme;

performing multiple cognitive training according to a formulated cognitive training scheme, analyzing physiological parameter data acquired by the task types, evaluating training effect under each task type, comprehensively analyzing all physiological parameter data under the current stage, and establishing a longitudinal evaluation model to obtain a quantized result of the cognitive training of a subject;

if the quantized result reaches the required standard, the training target is indicated to be achieved;

if the quantized result does not reach the required standard, the corresponding task type needs to be pertinently reinforced according to the quantized result of each training.

10. Method for training the cognitive decision evaluation in transient overweight and weightlessness conditions of a cognitive decision evaluation training system according to any of claims 1 to 9, comprising the steps of:

analyzing and counting physiological parameter data under a simplified version task type, and establishing a preliminary evaluation model, wherein the simplified version task type is a task type with parameters set as the lowest version;

comprehensively analyzing the cognitive behaviors of the subjects based on the evaluation standard of task types in the evaluation model, selecting the task types needing to be enhanced according to the analysis result, and formulating a preliminary cognitive training scheme;

performing multiple cognitive training according to a formulated cognitive training scheme, analyzing physiological parameter data acquired by the task types, evaluating training effect under each task type, comprehensively analyzing all physiological parameter data under the current stage, and establishing a longitudinal evaluation model to obtain a quantized result of the cognitive training of a subject;

if the quantized result reaches the required standard, the training target is indicated to be achieved;

if the quantized result does not reach the required standard, the corresponding task type needs to be pertinently reinforced according to the quantized result of each training.