Visual-based spatial perception memory-response touch training system

Abstract

The application discloses a kind of based on visual space perception memory-reaction touch type training system, including login display module, build module, visual display and touch sensing module and data acquisition and processing module.The application can explore the change rule of people's space perception memory by real-time monitoring means and building corresponding database, can optimize the crowd with strong space perception memory in a short time, in addition, a convenient and easy training method is proposed to improve people's space perception memory ability, suitable for different applicable crowd to carry out targeted training, for the crowd with poor space perception memory, with the increase of training times, the accuracy and success rate of user touch response will continue to improve, the time used will be shortened, and the space perception memory ability is improved, thereby improving their space perception memory ability.

Description

Technical Field

[0001] This invention relates to the field of brain cognitive science and technology, specifically to a visual spatial perception memory-response touch training system. Background Technology

[0002] Spatial perception and memory is one of the most important aspects of human memory. Based on spatial cognition theory, factors such as the distance, depth, and direction of an object significantly influence spatial perception. In other words, while people can accurately judge what's ahead using a large amount of external information, they rely on spatial perception and memory to complete certain tasks. Young children develop accurate spatial awareness (front, back, left, right, near, far) through spatial perception and memory, and as they grow older, they gradually memorize various walking routes and follow them to their destination. Young students can improve their concentration, judgment, and even overall learning ability through spatial perception and memory. The elderly can prevent memory decline and early symptoms of Alzheimer's disease through spatial perception and memory. Athletes can perform high-level athletic techniques within a defined space, such as in diving, gymnastics, and trampoline. Individuals with high levels of spatial perception and memory are often able to complete related tasks more quickly and effectively.

[0003] Currently, to improve people's spatial perception and memory abilities, most training methods for the general population use traditional drawing or filling methods. These methods are too simplistic and their application is mostly limited to young children or elderly people experiencing memory decline. Furthermore, these training methods do not incorporate real-world scenarios and lack real-time visualization and monitoring, which significantly reduces the effectiveness of the training. Summary of the Invention

[0004] To address the aforementioned technical problems, a visualization-based spatial perception memory-response touch-based training system is provided. This technical solution solves the problems mentioned in the background technology, such as the current training methods being too simple, not being combined with real-world scenarios, and lacking visualization and real-time monitoring methods, which greatly reduces the training effect.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A visualization-based spatial perception memory-response touch-based training system includes:

[0007] The login display module is used to display selectable, randomly generated visual spatial perception memory training route images, personal login information, and training results to logged-in users.

[0008] A construction module is used to complete the construction of a real scene including touch sensors based on the coordinate points of the visual spatial perception memory image route map.

[0009] The visualization display and touch sensing module is used to perform touch sensing training in a real scene according to the randomly generated visualization spatial perception memory training route image content, and at the same time present the real-time visualization spatial perception memory training route map.

[0010] The data acquisition and processing module is used to collect real-time data on whether the logged-in user's touch response to each time based on the route map is successful and how long it takes. The module also preprocesses the collected real-time data, including data deduplication, missing value filling, and outlier handling, to generate a valid database.

[0011] Training feedback module: The training methods of the training feedback module include pre-training and formal training. The training feedback module evaluates the improvement process of the user's spatial memory perception ability based on whether the user's touch response is successful and how long it takes.

[0012] Preferably, the step of constructing a realistic scene including touch sensors based on the coordinates of the route map in the visualized spatial perception memory image specifically includes the following steps:

[0013] Obtain randomly generated spatially perceptual memory image data;

[0014] Uniformly segmented grids visualize spatially perceptual memory image data;

[0015] Establish a matrix that corresponds one-to-one with each grid point [a ij ] nn ;

[0016] The grid points correspond to the positions of points in the image. The grayscale value of the image point corresponding to the grid point is assigned to the corresponding element 'a' in the grid matrix. ij This yields the set of coordinates corresponding to the memory image data.

[0017] The touch-sensitive device, which includes sensors, is constructed sequentially according to the coordinate points. The touch-sensitive device includes a touch light, a vertical cone, a power bank, a single-channel receiver, a four-channel receiver, a Bluetooth receiver, and a receiving antenna.

[0018] Preferably, the step of performing touch-sensing training in a real-world scene based on randomly generated visual spatial perception memory training route images, while simultaneously presenting a real-time visual spatial perception memory training route map, specifically includes the following steps:

[0019] Modeling is performed using Python, setting the number of sensors, their coordinates, and the total path length to generate a model that meets the requirements.

[0020] Based on the model that meets the requirements, an actual training field map is generated. The actual training field map is composed of Arabic numerals between 1 and 50 and the path between each node indicated by arrows. Each visualized path map is different.

[0021] The design includes several haptic sensors. When a user taps a sensor, a visual line node corresponding to that sensor is displayed.

[0022] The success of the visual monitoring display is determined by the color change after the user taps the haptic sensor.

[0023] Preferably, after the user taps the haptic sensor, if it displays green, it indicates that it corresponds to a node in the visualized route; if it displays red, it indicates that the correspondence is incorrect, and the training activity should be stopped and restarted until all nodes in the route map are correct and all display green before the user's score is recorded and displayed for visual monitoring.

[0024] Preferably, the visualization display and touch sensing module is further provided with a timing unit, which is used to evaluate the time taken by the user to complete the entire route map, and to evaluate the improvement process of the user's spatial memory perception ability based on the number of times the user succeeds and the amount of time taken.

[0025] Preferably, the data deduplication includes the following steps:

[0026] Arrange all data coordinates (x, y) into a single column;

[0027] Check for duplicates between the first coordinate and subsequent coordinates; if duplicates are found, delete the subsequent coordinates.

[0028] After the search is complete, check for duplicates between the second coordinate and subsequent coordinates. If duplicates are found, delete the subsequent coordinates.

[0029] Repeat the above steps until all data coordinates have been detected.

[0030] Preferably, the missing value filling includes the following steps:

[0031] Arrange all data coordinates (x, y) into a single column;

[0032] Retrieve all data coordinates (x, y). If there is a missing x or y coordinate, fill in the missing data at that position. The data collected is the average of adjacent data at the same position.

[0033] Preferably, the outlier handling includes the following steps:

[0034] Arrange all data coordinates (x, y) into a single column;

[0035] Calculate the deviation k of the data coordinates (x, y) from the adjacent data coordinates (a, b) and (c, d). When the deviation k is greater than 100%, the data coordinates (x, y) are outliers, and the data coordinates (x, y) are replaced by the mean of the adjacent data.

[0036] The formula for calculating the deviation value is:

[0037]

[0038] Preferably, the pre-training includes the user memorizing a visual spatial perception memory training route image specified by the system for pre-training. The user carries the route image in a real scene according to the route image and practices without time limit until the user has completely memorized the route image and completes a full practice session. Real-time data of the user completing each touch according to the route image is collected. The real-time data includes whether each touch was successful in touch response training and the time taken to complete all touch points.

[0039] The formal training includes a visual spatial perception memory training route image randomly generated by the system and selected by the user for use in the formal training. Once the image is selected, the timer starts immediately. The user needs to quickly memorize the route image and perform touch-based exercises and training in a real-world scenario according to the route image. After completing one full touch training exercise according to the route image, the timer ends, and real-time data of each touch completed by the user according to the route image is collected. The real-time data includes whether each touch was successful in the touch response training and the time taken to complete all touch points.

[0040] Preferably, the process of assessing the improvement of the user's spatial memory perception ability based on the success and time of the user's touch response specifically includes the following steps:

[0041] A performance evaluation formula is constructed based on the number of successful user touch responses and the time taken. The performance evaluation formula is as follows:

[0042]

[0043] In the formula, V represents the user's score, and t i The time taken for the i-th successful touch is given, and n is the total number of successful touch responses from the user.

[0044] The V value is compared with a preset threshold. If the V value is less than or equal to the preset threshold, the user's performance is considered good.

[0045] If the V value is greater than the preset threshold, the user's performance is considered poor.

[0046] Compared with existing technologies, this invention provides a visualization-based spatial perception memory-response touch-based training system, which has the following beneficial effects:

[0047] This invention first constructs a realistic spatial perception memory training scenario, providing a scientific basis for accurately identifying changes in people's spatial perception memory. Furthermore, this invention can explore the patterns of changes in people's spatial perception memory through visualized real-time monitoring and the establishment of a corresponding database, enabling the selection of individuals with strong spatial perception memory in a relatively short time. In addition, this invention proposes a convenient and easy-to-implement training method to improve people's spatial perception memory ability, suitable for targeted training for different groups. For individuals with poor spatial perception memory, as the number of training sessions increases, the accuracy and success rate of their touch responses will continuously improve, the time required will shorten, and their spatial perception memory ability will increase accordingly, thereby enhancing their spatial perception memory capacity. Attached Figure Description

[0048] Figure 1 This is a block diagram of the reactive touch-based training system of the present invention;

[0049] Figure 2 This is a schematic diagram illustrating the method for constructing a real-world scene including touch sensors in this invention;

[0050] Figure 3 This is a schematic diagram of the method for conducting touch sensing training in a real-world scenario according to the present invention;

[0051] Figure 4 This is a schematic diagram of the data deduplication method in this invention;

[0052] Figure 5 This is a schematic diagram of the missing value filling method in this invention;

[0053] Figure 6 This is a schematic diagram of the outlier handling method in this invention. Detailed Implementation

[0054] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0055] Example 1

[0056] Please refer to Figures 1-6 As shown, a visualization-based spatial perception memory-response touch-based training system includes:

[0057] The login display module is used to display selectable, randomly generated images of spatial perception memory training routes, personal login information, and training results to logged-in users.

[0058] The building module is used to build a real scene including touch sensors based on the coordinate points of the visual spatial perception memory image route map.

[0059] The visualization and touch sensing module is used to perform touch sensing training in a real scene according to the randomly generated visualization spatial perception memory training route image, while presenting a real-time visualization spatial perception memory training route map.

[0060] The data acquisition and processing module is used to collect real-time data on whether the logged-in user's touch response to the route map is successful and how long it takes. The module also preprocesses the collected real-time data, including data deduplication, missing value filling, and outlier handling, to generate a valid database.

[0061] Training Feedback Module: The training feedback module includes pre-training and formal training. Based on the success and time taken by the user's touch response, the training feedback module evaluates the improvement process of the user's spatial memory perception ability.

[0062] Those skilled in the art will understand that the present invention first constructs a realistic spatial perception memory training scenario, which provides a scientific basis for accurately identifying changes in people's spatial perception memory. Furthermore, the present invention can explore the patterns of changes in people's spatial perception memory through visualized real-time monitoring and the establishment of a corresponding database.

[0063] Based on the coordinates of the visualized spatial perception memory image route map, the following steps are involved in constructing a realistic scene including touch sensors:

[0064] Obtain randomly generated spatially perceptual memory image data;

[0065] Uniformly segmented grids visualize spatially perceptual memory image data;

[0066] Establish a matrix that corresponds one-to-one with each grid point [a ij ] nn ;

[0067] The grid points correspond to the positions of points in the image. The grayscale value of the image point corresponding to the grid point is assigned to the corresponding element 'a' in the grid matrix. ij This yields the set of coordinates corresponding to the memory image data.

[0068] The touch-sensitive device, which includes sensors, is constructed sequentially according to the coordinate points. The touch-sensitive device includes a touch light, a cone-shaped device, a power bank, a single-channel receiver, a four-channel receiver, a Bluetooth receiver, and a receiving antenna.

[0069] Touch-sensing training is conducted in a real-world scenario based on randomly generated, visualized spatial perception memory training route images, while simultaneously presenting a real-time visualized spatial perception memory training route map. The specific steps include:

[0070] Modeling is performed using Python, setting the number of sensors, their coordinates, and the total path length to generate a model that meets the requirements.

[0071] Based on the qualified model, generate a real training field map. The real training field map is composed of Arabic numerals between 1 and 50 and the path between each node pointed by arrows. Each visualization of the path map is different.

[0072] The design includes several haptic sensors. When a user taps a sensor, a visual line node corresponding to that sensor is displayed.

[0073] The success of the visual monitoring display is determined by the color change after the user taps the haptic sensor.

[0074] When a user taps the haptic sensor, if it displays green, it means that the sensor corresponds to a node on the visualized route. If it displays red, it means that the correspondence is incorrect, and the training activity should be stopped and restarted. The user's score will only be recorded and displayed for visual monitoring when all nodes on the route map are correct and all nodes display green.

[0075] The visualization and touch sensing module also includes a timing unit, which is used to evaluate the time it takes for the user to complete the entire route map. Based on the number of times the user succeeds and the amount of time taken, the system assesses the improvement process of the user's spatial memory perception ability.

[0076] Data deduplication includes the following steps:

[0077] Arrange all data coordinates (x, y) into a single column;

[0078] Check for duplicates between the first coordinate and subsequent coordinates; if duplicates are found, delete the subsequent coordinates.

[0079] After the search is complete, check for duplicates between the second coordinate and subsequent coordinates. If duplicates are found, delete the subsequent coordinates.

[0080] Repeat the above steps until all data coordinates have been detected.

[0081] Missing value imputation includes the following steps:

[0082] Arrange all data coordinates (x, y) into a single column;

[0083] Retrieve all data coordinates (x, y). If there is a missing x or y coordinate, fill in the missing data at that position. The data collected is the average of adjacent data at the same position.

[0084] Outlier handling includes the following steps:

[0085] Arrange all data coordinates (x, y) into a single column;

[0086] Calculate the deviation k of the data coordinates (x, y) from the adjacent data coordinates (a, b) and (c, d). When the deviation k is greater than 100%, the data coordinates (x, y) are outliers, and the data coordinates (x, y) are replaced by the mean of the adjacent data.

[0087] The formula for calculating the deviation value is:

[0088]

[0089] Pre-training includes the user memorizing a visual spatial perception memory training route image specified by the system for pre-training. The user carries the route image in a real scene according to the route image and practices without time limit until the user fully memorizes the route image and completes a full practice session. Real-time data is collected on each touch completed by the user according to the route image. The real-time data includes whether each touch was successful in touch response training and the time taken to complete all touch points.

[0090] Formal training includes a visual spatial perception memory training route image randomly generated by the system and selected by the user for use in formal training. Once the image is selected, the timer starts immediately. The user needs to quickly memorize the route image and perform touch-based exercises and training in a real-world scenario according to the route. After completing a full touch training exercise according to the route image, the timer ends, and real-time data of each touch completed by the user according to the route image is collected. The real-time data includes whether each touch was successful in the touch response training and the time taken to complete all touch points.

[0091] Based on the success and time taken of a user's touch response, the process of assessing the improvement of a user's spatial memory perception ability includes the following steps:

[0092] A performance evaluation formula is constructed based on the number of successful user touch responses and the time taken. The performance evaluation formula is as follows:

[0093]

[0094] In the formula, V represents the user's score, and t iThe time taken for the i-th successful touch is given, and n is the total number of successful touch responses from the user.

[0095] The V value is compared with a preset threshold. If the V value is less than or equal to the preset threshold, the user's performance is considered good.

[0096] If the V value is greater than the preset threshold, the user's performance is considered poor.

[0097] In summary, this invention first constructs a realistic spatial perception memory training scenario, providing a scientific basis for accurately identifying changes in people's spatial perception memory. Furthermore, this invention can explore the patterns of changes in people's spatial perception memory through visualized real-time monitoring and the establishment of a corresponding database, enabling the selection of individuals with strong spatial perception memory in a relatively short time. In addition, this invention proposes a convenient and easy-to-implement training method to improve people's spatial perception memory ability, suitable for targeted training for different groups. For individuals with poor spatial perception memory, as the number of training sessions increases, the accuracy and success rate of their touch responses will continuously improve, the time required will shorten, and their spatial perception memory ability will increase accordingly, thereby enhancing their spatial perception memory capacity.

[0098] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A visualization-based spatial perception memory-response touch-based training system, characterized in that, include: The login display module is used to display selectable, randomly generated visual spatial perception memory training route images, personal login information, and training results to logged-in users. A construction module is used to complete the construction of a real scene including touch sensors based on the coordinate points of the visual spatial perception memory image route map. The visualization display and touch sensing module is used to perform touch sensing training in a real scene according to the randomly generated visualization spatial perception memory training route image content, and at the same time present the real-time visualization spatial perception memory training route map. The data acquisition and processing module is used to collect real-time data on whether the logged-in user's touch response to each time based on the route map is successful and how long it takes. The module also preprocesses the collected real-time data, including data deduplication, missing value filling, and outlier handling, to generate a valid database. Training feedback module: The training methods of the training feedback module include pre-training and formal training. The training feedback module evaluates the improvement process of the user's spatial memory perception ability based on whether the user's touch response is successful and how long it takes.

2. The visualization-based spatial perception memory-response touch-based training system according to claim 1, characterized in that, The process of constructing a realistic scene including touch sensors based on the coordinate points of the visualized spatial perception memory image route map includes the following steps: Obtain randomly generated spatially perceptual memory image data; Uniformly segmented grids visualize spatially perceptual memory image data; Establish a matrix that corresponds one-to-one with each grid point [a ij ] nn ; The grid points correspond to the positions of points in the image. The grayscale value of the image point corresponding to the grid point is assigned to the corresponding element 'a' in the grid matrix. ij This yields the set of coordinates corresponding to the memory image data. The touch-sensitive device, which includes sensors, is constructed sequentially according to the coordinate points. The touch-sensitive device includes a touch light, a vertical cone, a power bank, a single-channel receiver, a four-channel receiver, a Bluetooth receiver, and a receiving antenna.

3. The visualization-based spatial perception memory-response touch-based training system according to claim 2, characterized in that, The step of conducting touch-sensing training in a real-world scenario based on randomly generated visual spatial perception memory training route images, while simultaneously presenting a real-time visual spatial perception memory training route map, specifically includes the following steps: Modeling is performed using Python, setting the number of sensors, their coordinates, and the total path length to generate a model that meets the requirements. Based on the model that meets the requirements, an actual training field map is generated. The actual training field map is composed of Arabic numerals between 1 and 50 and the path between each node indicated by arrows. Each visualized path map is different. The design includes several haptic sensors. When a user taps a sensor, a visual line node corresponding to that sensor is displayed. The success of the visual monitoring display is determined by the color change after the user taps the haptic sensor.

4. The visualization-based spatial perception memory-response touch-based training system according to claim 3, characterized in that, When a user taps the haptic sensor, if it displays green, it means that the sensor corresponds to a node on the visualized route. If it displays red, it means that the correspondence is incorrect, and the training activity should be stopped and restarted. The user's score will only be recorded and displayed for visual monitoring when all nodes on the route map are correct and all nodes display green.

5. A visualization-based spatial perception memory-response touch-based training system according to claim 4, characterized in that, The visualization and touch sensing module also includes a timing unit, which is used to evaluate the time it takes for the user to complete the entire route map. Based on the number of times the user succeeds and the amount of time taken, the system assesses the improvement process of the user's spatial memory perception ability.

6. The visualization-based spatial perception memory-response touch-based training system according to claim 5, characterized in that, The data deduplication process includes the following steps: Arrange all data coordinates (x, y) into a single column; Check for duplicates between the first coordinate and subsequent coordinates; if duplicates are found, delete the subsequent coordinates. After the search is complete, check for duplicates between the second coordinate and subsequent coordinates. If duplicates are found, delete the subsequent coordinates. Repeat the above steps until all data coordinates have been detected.

7. A visualization-based spatial perception memory-response touch-based training system according to claim 6, characterized in that, The missing value filling includes the following steps: Arrange all data coordinates (x, y) into a single column; Retrieve all data coordinates (x, y). If there is a missing x or y coordinate, fill in the missing data at that position. The data collected is the average of adjacent data at the same position.

8. A visualization-based spatial perception memory-response touch-based training system according to claim 7, characterized in that, The outlier handling includes the following steps: Arrange all data coordinates (x, y) into a single column; Calculate the deviation k of the data coordinates (x, y) from the adjacent data coordinates (a, b) and (c, d). When the deviation k is greater than 100%, the data coordinates (x, y) are outliers, and the data coordinates (x, y) are replaced by the mean of the adjacent data. The formula for calculating the deviation value is:

9. A visualization-based spatial perception memory-response touch-based training system according to claim 8, characterized in that, The pre-training includes the user memorizing a visual spatial perception memory training route image specified by the system for pre-training. The user carries the route image in a real scene according to the route image and practices without time limit until the user has completely memorized the route image and completes a full practice session. Real-time data of the user completing each touch according to the route image is collected. The real-time data includes whether each touch was successful during touch response training and the time taken to complete all touch points. The formal training includes a visual spatial perception memory training route image randomly generated by the system and selected by the user for use in the formal training. Once the image is selected, the timer starts immediately. The user needs to quickly memorize the route image and perform touch-based exercises and training in a real-world scenario according to the route image. After completing one full touch training exercise according to the route image, the timer ends, and real-time data of each touch completed by the user according to the route image is collected. The real-time data includes whether each touch was successful in the touch response training and the time taken to complete all touch points.

10. A visualization-based spatial perception memory-response touch-based training system according to claim 9, characterized in that, The process of assessing the improvement of a user's spatial memory perception ability based on the success and time of the user's touch response specifically includes the following steps: A performance evaluation formula is constructed based on the number of successful user touch responses and the time taken. The performance evaluation formula is as follows: In the formula, V represents the user's score, and t i The time taken for the i-th successful touch is given, and n is the total number of successful touch responses from the user. The V value is compared with a preset threshold. If the V value is less than or equal to the preset threshold, the user's performance is considered good. If the V value is greater than the preset threshold, the user's performance is considered poor.

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