A method for implementing visual space ability evaluation based on non-immersive virtual reality

Abstract

The application provides a method for evaluating visual space ability based on non-immersive virtual reality. The method is used for a computer device, and the method comprises the following steps: displaying a path learning interface through a display screen, so that a subject performs path learning; the path learning interface displays a two-dimensional plane map; the map has a specified path marked with a starting point and an ending point; a virtual three-dimensional space is displayed through the display screen, so that the subject performs a three-dimensional virtual space walking test; when the subject performs the three-dimensional virtual space walking test, the subject starts from the starting point and walks along the street to the ending point according to the specified path remembered by the subject, or returns to the starting point from the ending point; the eye movement track and the mouse action of the subject are used to calculate an evaluation index of the subject; and the visual space ability of the subject is evaluated according to the evaluation index. The detection paradigm of the application can evaluate the visual space ability of subjects of different ages or different cognitive function levels, and realizes a visual space test close to a real scene.

Description

Technical Field

[0001] This invention relates to the technical field of cognitive function assessment, and more specifically, to a method for assessing visuospatial ability based on non-immersive virtual reality. Background Technology

[0002] Visuospatial function refers to an individual's ability to move from one location to another in familiar and unfamiliar environments. This function includes the processes of encoding, storing, solidifying, and retrieving spatial information. Impairment in visuospatial function is associated with difficulties in location perception, spatial orientation, distance determination, and cue recognition. These impairments significantly limit the daily activities of individuals with cognitive impairment and dementia. Visuospatial ability assessment can be used to diagnose the disease state of dementia patients and assess the degree of cognitive impairment in subjects, thereby enabling early diagnosis of Alzheimer's disease (AD), particularly large-scale screening and diagnosis of individuals with cognitive impairment before the onset of obvious symptoms.

[0003] Currently, the most commonly used methods for assessing visuospatial abilities in clinical settings are neuropsychological questionnaire tests, including the Mini Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA), the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS-Cog), and the Frontal Assessment Battery (FAB). These scales have been widely used in clinical settings for mild cognitive impairment (MCI) and Alzheimer's disease screening. These scales assess subjects' cognitive functions from multiple dimensions (memory, executive function, language, visuospatial ability, information processing, etc.). When assessing visuospatial abilities using the MMSE and MoCA, subjects are required to redraw two overlapping pentagons (MMSE test) or a cube (MoCA test) on paper based on the figures given in the questionnaire. However, the MMSE and MoCA tests are prone to the "ceiling effect" (for highly educated groups) or the "floor effect" (for less educated groups), resulting in false negatives or false positives. Diagnostic results based on questionnaires are also easily influenced by many external factors, failing to accurately reflect the subject's condition and making it difficult to identify individuals with MCI exhibiting symptoms of premature memory loss.

[0004] Furthermore, drawing methods can be used clinically to assess visuospatial abilities. Currently commonly used tests include the Clock Drawing Test (CDT) and the Rey-Osterrieth Complex Figure (RCF). The former requires subjects to draw a complete clock, including a circular dial, three hands (hour, minute, and second), and the 12 numbers correctly arranged at the hour positions on the dial. The latter requires subjects to draw a complex geometric figure from memory.

[0005] The third type of method for assessing visuospatial ability is the maze method. The MATRICS consensus cognitive battery (MCCB) test includes a set of planar mazes of varying difficulty. Participants are required to enter the maze from the entrance, navigate a series of twists and turns, and exit from the exit. The difficulty progresses from the easiest maze to the most challenging. Based on the complexity of the maze and the time taken to complete it, the participant's visuospatial ability can be assessed.

[0006] In summary, although the aforementioned existing methods for assessing visuospatial abilities can provide some results, their effectiveness and usability are unsatisfactory. These methods are based on two-dimensional planar graphics and cannot reflect the subject's true experience in three-dimensional space, thus leading to contradictory conclusions.

[0007] Therefore, we urgently need to develop a novel method for assessing visuospatial capabilities to address the shortcomings of existing visuospatial capability assessment methods. Summary of the Invention

[0008] The present invention aims to solve at least one of the technical problems existing in the prior art or related art.

[0009] Therefore, the purpose of this invention is to propose a method for evaluating visuospatial capabilities based on non-immersive virtual reality.

[0010] To achieve the above objectives, the present invention provides a method for assessing visuospatial ability based on non-immersive virtual reality, using a computer device. The computer device includes: a mouse, a display screen, an eye tracker, a jaw rest, a memory, a processor, and a computer program stored in the memory and executable on the processor. The mouse controls the movement of a cursor on the display screen, which displays test content corresponding to the visuospatial ability assessment method. The eye tracker records the eye movement trajectory of the subject when responding to the corresponding test content. The jaw rest stabilizes the subject's head. The processor executes the computer program to implement the visuospatial ability assessment method. The visuospatial ability assessment method includes: Step S1: After receiving an instruction to enter path learning, the path learning interface is displayed on the display screen for the subject to perform path learning. The path learning interface displays a two-dimensional map. The two-dimensional map shows crisscrossing streets, and buildings are distributed within blocks formed by these streets. A prescribed path is marked along the streets on the two-dimensional map, with one end of the prescribed path... The starting point is marked as the first end of the path, and the other end is marked as the ending point. Several intersections are distributed along the path. This path is the walking path the subject must follow during a subsequent three-dimensional virtual space walking test. During path learning, the subject begins memorizing the path until an instruction to end path learning is received. Each intersection serves as a decision point. Step S2: After receiving the instruction to enter the space, a virtual three-dimensional space is displayed on the screen for the subject to perform a three-dimensional virtual space walking test. This virtual three-dimensional space is a three-dimensional representation of the two-dimensional plane map. During the three-dimensional virtual space walking test, the subject, based on the memorized path, uses the mouse to decide whether to start from the starting point, walk along the street towards the ending point, and make decisions such as forward, left turn, right turn, or U-turn at each intersection until the mouse determines that the subject has reached the ending point. Step S3: Using the eye-tracking device to record the subject's eye movement trajectory and the mouse's movements, the subject's evaluation indicators are recorded and calculated. Step S4: Based on the subject's evaluation indicators, the evaluation result of the subject's visuospatial ability is obtained.

[0011] Preferably, after step S2 and before step S3, the method further includes: after receiving the instruction to return from the space, the subject, according to the memorized path, uses the mouse to make a decision to start from the endpoint, move along the street towards the starting point, and make decisions to move forward, turn left, turn right, or make a U-turn at each intersection along the way, until the mouse makes a decision to reach the starting point.

[0012] Preferably, the evaluation indicators for the subjects include one or a combination of the following: the duration of path learning, the number of attention points focused on planar buildings during path learning, the total duration of attention to planar buildings during path learning, the total duration of walking in the three-dimensional virtual space, the segmented duration of walking in the three-dimensional virtual space, the number of attention points focused on spatial buildings during walking in the three-dimensional virtual space, the total duration of attention to spatial buildings during walking in the three-dimensional virtual space, the number of decision errors during walking in the three-dimensional virtual space, the path deviation ρ during walking in the three-dimensional virtual space, the total duration of returning to the three-dimensional virtual space, the segmented duration of returning to the three-dimensional virtual space, and the number of attention points focused on spatial buildings during the return to the three-dimensional virtual space. The parameters include: number of attention points, total duration of gaze at buildings during the 3D virtual space return process, number of decision errors during the 3D virtual space return process, and path deviation ε during the 3D virtual space return process; wherein, the duration of path learning completion is the time between receiving the instruction to enter path learning and receiving the instruction to end path learning; the number of attention points for gazing at planar buildings during path learning is the number of attention points on the 2D planar map where the subject's gaze lingers for more than 150 milliseconds during path learning; and the total duration of gaze at planar buildings during path learning is the total duration of gaze at buildings on the 2D planar map during path learning. The total time for completing the three-dimensional virtual space walk is: the time taken for the mouse to move from the starting point to the ending point during the three-dimensional virtual space walk test; the segmented time for completing the three-dimensional virtual space walk is: the time taken for the mouse to move from the Nth decision point to the (N+1)th decision point during the three-dimensional virtual space walk test; N is a positive integer greater than or equal to 1; the number of attention points for buildings in the three-dimensional virtual space walk is: the number of attention points for which the subject's gaze lingers on buildings in the three-dimensional virtual space for more than 150 milliseconds during the three-dimensional virtual space walk test; the time taken for the mouse to move from the Nth decision point to the (N+1)th decision point during the three-dimensional virtual space walk test. The total duration of the virtual space building is: the total time the subject's gaze rests on a point of focus on a building in the 3D virtual space during the test of walking in the 3D virtual space; the number of decision-making errors during the 3D virtual space walking process is: the number of incorrect decisions made by the subject during the test of walking in the 3D virtual space; the path deviation ρ of the 3D virtual space walking is: the degree of deviation between the subject's actual walking path in the 3D virtual space and the prescribed path during the test of walking in the 3D virtual space; the total time for completing the return from the 3D virtual space is: the length of time it takes for the mouse to return from the endpoint to the starting point during the test of returning from the 3D virtual space.The segmented time for completing the 3D virtual space return is defined as follows: the time taken for the mouse to move from the Mth decision point to the (M-1)th decision point during the 3D virtual space return test; M is a positive integer greater than or equal to 2. The number of attention points on buildings during the 3D virtual space return process is defined as the number of attention points on buildings in the 3D virtual space where the subject's gaze lingers for more than 150 milliseconds during the 3D virtual space return test. The total time spent on buildings during the 3D virtual space return process is defined as the total time the subject's gaze lingers on attention points on buildings in the 3D virtual space during the 3D virtual space return test. The number of decision errors during the 3D virtual space return process is defined as the number of incorrect decisions made by the subject during the 3D virtual space return test. The path deviation ε of the 3D virtual space return is defined as the degree of deviation between the subject's actual return path in the 3D virtual space and the reverse path of the specified path during the 3D virtual space return test.

[0013] Preferably, the calculation process of the path deviation ρ for walking in the three-dimensional virtual space specifically includes: marking the decision point sequence of the specified path as X = [x1, x2, ..., x...]. n ]; where x i It is the i-th decision point on the specified path; where n is the total number of decision points on the specified path; the sequence of decision points of the subject's actual walking path in the three-dimensional virtual space is labeled as Y = [y1, y2, ..., y]. m ]; where y j Let be the j-th decision point on the actual walking path; where m is the total number of decision points on the actual walking path; construct an n×m distance matrix D based on the decision point sequence of the specified path and the decision point sequence of the actual walking path; where the element d(i,j) of the distance matrix D is the decision point x of the specified path. i Decision point y on the actual walking path j The absolute value of the distance between; a cumulative distance matrix C is constructed from the distance matrix D; wherein, the element c(i,j) of the cumulative distance matrix C is the element d(i,j) of the distance matrix D plus the minimum value among the elements {c(i-1,j),c(i,j-1),c(i-1,j-1)} in the cumulative distance matrix C; the minimum value among the elements {c(i-1,j),c(i,j-1),c(i-1,j-1)} in the cumulative distance matrix C is x. i With y jThe minimum cumulative distance between two points; the value of element c(n,m) in the cumulative distance matrix C is the degree of deviation between the subject's actual walking path in the three-dimensional virtual space and the prescribed path; when the subject's actual walking path is completely consistent with the prescribed path, the deviation ρ of the walking path in the three-dimensional virtual space is zero.

[0014] Preferably, the calculation process of the path deviation ε returned by the three-dimensional virtual space specifically includes: the reverse path of the specified path is opposite to the specified path of spatial walking, that is, the decision point sequence of the reverse path of the specified path is denoted as... X =[ x n , x n-1 ,…, x1 ];in, x i It is the first path on the reverse path of the specified path. i There are n decision points; where n is the total number of decision points on the reverse path of the specified path; the sequence of decision points on the actual return path of the subject in the three-dimensional virtual space is marked as _____. Y =[y m ,y m-1 ,…,y 1 ]; where y j Let m be the j-th decision point on the actual return path; where m is the total number of decision points on the actual return path; and construct an n×m distance matrix based on the decision point sequence of the reverse path of the specified path and the decision point sequence of the actual return path. D Wherein, the distance matrix D The element d(i,j) is the decision point x of the reverse path of the specified path. i Decision point y of the actual return path j The absolute value of the distance between them; derived from the distance matrix. D Construct a cumulative distance matrix C ; wherein, the cumulative distance matrix C The element c(i,j) is the distance matrix. D The element d(i,j) plus the cumulative distance matrix C The minimum value among the elements {c(i-1,j),c(i,j-1),c(i-1,j-1)} in the cumulative distance matrix C is x; i With y j The minimum cumulative distance between two points; the value of element c(n,m) in the cumulative distance matrix C is the degree of deviation between the subject's actual return path in the three-dimensional virtual space and the reverse path of the specified path; when the subject's actual return path in the three-dimensional virtual space is completely consistent with the reverse path of the specified path, the deviation ε of the path returned by the three-dimensional virtual space is zero.

[0015] The beneficial effects of this invention are:

[0016] This invention provides a method for assessing visuospatial abilities based on non-immersive virtual reality, integrating an eye-tracking system and non-immersive virtual reality technology. Non-immersive virtual reality utilizes the virtual environment to accurately monitor and analyze human behavior, reflecting the subject's natural responses to stimuli in the virtual space. Furthermore, the virtual environment of non-immersive virtual reality can be designed for specific populations or tasks, possessing broad versatility. This standardized design also ensures comparability and referenceability of test results across different locations and times, potentially becoming a standardized tool for assessing cognitive function. In addition, research indicates that non-immersive virtual reality technology demonstrates significant advantages in assessing visuospatial abilities in patients with brain injury and chronic stroke.

[0017] Eye tracking is a new technology that measures eye movements while subjects objectively read, scan, and saccade. In recent years, it has been used for cognitive function assessment, such as trajectory testing, saccades and countersaccades, emotion recognition, and cognitive evaluation. Eye tracking systems have unique technological advantages. First, eye movements are spontaneous responses to brain sensory activities (visual and / or auditory), independent of conscious control, and can accurately reflect a subject's cognitive activity. Second, eye tracking systems can continuously monitor and record eye movements, providing dynamic information on cognitive performance in real-time, rather than static results, such as positron emission tomography (PET), magnetic resonance imaging (MRI), or scale tests. Third, the eye trajectories projected onto the monitor have higher spatial resolution (pixel-level) and temporal resolution (millisecond-level), reflecting rapid brain activity. These digital testing methods are more accurate, convenient, and subject-friendly than results based on traditional paper-and-pencil questionnaires.

[0018] Therefore, the method for assessing visuospatial ability based on non-immersive virtual reality provided by this invention provides visual stimulation to subjects while simultaneously recording their unconscious responses using eye-tracking technology. Specifically, we designed detection paradigms for [path learning], [spatial walking], and [spatial return] to assess the visuospatial abilities of subjects of different ages or with different cognitive function levels, achieving a truly meaningful visuospatial test. The importance of this invention is unparalleled by the currently used "paper-and-pen" experimental paradigm.

[0019] Furthermore, our invention is unique compared to existing research and testing methods. First, in addition to the total memory time of path learning, we also obtain the number of attention points, their distribution, and the duration of each attention point during the path learning process. Second, we can obtain the total completion time of spatial walking and spatial return, the number of attention points, their distribution, and the duration of each attention point, as well as the number of decision-making errors, for each subject in spatial landmarks. More importantly, we are the first to use the path deviation index to measure the degree of deviation between the subject's actual path and the prescribed path during spatial walking, and the degree of deviation between the actual path and the reverse sequence of the prescribed path during return, which can accurately assess the subject's visuospatial ability.

[0020] Additional aspects and advantages of the invention will become apparent from the description which follows, or may be learned by practice of the invention. Attached Figure Description

[0021] Figure 1 A schematic block diagram illustrating the working principle of a computer device according to an embodiment of the present invention is shown.

[0022] Figure 2 A schematic flowchart of a method for evaluating visuospatial capabilities based on non-immersive virtual reality for a computer device, according to an embodiment of the present invention, is shown.

[0023] Figure 3 A schematic diagram of a two-dimensional map in a path learning test according to an embodiment of the present invention is shown;

[0024] Figure 4 This diagram illustrates a screenshot of the "starting point" during a spacewalk test according to an embodiment of the present invention.

[0025] Figure 5 This diagram shows a screenshot of an intersection during a spatial walking test according to an embodiment of the present invention.

[0026] Figure 6 This diagram illustrates a screenshot of the "finish line" during a spacewalk test according to an embodiment of the present invention.

[0027] Figure 7 This diagram illustrates the total time taken for young and elderly subjects to complete path learning, respectively, according to an embodiment of the present invention.

[0028] Figure 8 This diagram illustrates the number of attention points for young and elderly subjects in path learning, according to an embodiment of the present invention.

[0029] Figure 9a This diagram illustrates the distribution of focus points of young subjects on a two-dimensional planar map according to an embodiment of the present invention.

[0030] Figure 9b This diagram illustrates the distribution of attention points of elderly subjects on a two-dimensional planar map according to an embodiment of the present invention.

[0031] Figure 10 This diagram illustrates the attention duration of young and elderly subjects during path learning, according to an embodiment of the present invention.

[0032] Figure 11 This diagram illustrates the total time taken for young and elderly subjects to complete spatial walking, respectively, according to an embodiment of the present invention.

[0033] Figure 12 A schematic diagram showing the total number of attention points for young and elderly subjects during spatial walking, according to an embodiment of the present invention;

[0034] Figure 13 This diagram illustrates the total attention time of young and elderly subjects during spatial walking, according to an embodiment of the present invention.

[0035] Figure 14 This diagram illustrates the path deviation of young and elderly subjects during spatial walking, according to an embodiment of the present invention.

[0036] Figure 15 This diagram illustrates the path deviation distribution of young and elderly subjects during spatial walking, according to an embodiment of the present invention.

[0037] Figure 16 A schematic diagram showing the distribution of first-time errors in spacewalking according to an embodiment of the present invention is provided.

[0038] Figure 17 A schematic diagram of a spatial walking example 1 according to an embodiment of the present invention is shown;

[0039] Figure 18 A schematic diagram of a spatial walking example 2 according to an embodiment of the present invention is shown;

[0040] Figure 19 A schematic diagram of a spatial walking example 3 according to an embodiment of the present invention is shown;

[0041] Figure 20 A schematic diagram of a spatial walking example 4 according to an embodiment of the present invention is shown;

[0042] Figure 21 A schematic diagram of a spatial walking example 5 according to an embodiment of the present invention is shown;

[0043] Figure 22 A schematic diagram of a spatial walking example 6 according to an embodiment of the present invention is shown;

[0044] Figure 23 A schematic diagram of a space walking example 7 according to an embodiment of the present invention is shown;

[0045] Figure 24 A schematic diagram of a spatial walking example 8 according to an embodiment of the present invention is shown;

[0046] Figure 25 A schematic diagram of a spatial walking example 9 of an embodiment of the present invention is shown. Detailed Implementation

[0047] To better understand the above-mentioned objects, features, and advantages of the present invention, such as Figures 1 to 25 As shown in the accompanying drawings and specific embodiments, the present invention will be further described in detail below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0048] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0049] Figure 1 A schematic block diagram illustrating the structure of a computer device according to an embodiment of the present invention is shown. Figure 2 A schematic flowchart illustrating an embodiment of the present invention is shown of a method for assessing visuospatial capabilities for a computer device based on non-immersive virtual reality. Figure 1 and Figure 2As shown, this method for assessing visuospatial ability based on non-immersive virtual reality is used in a computer device. The computer device includes: a mouse, a display screen, an eye tracker, a jaw rest, a memory, a processor, and a computer program stored in the memory and executable on the processor. The mouse controls the movement of a cursor on the display screen, which displays the test content corresponding to the visuospatial ability assessment method. The eye tracker records the eye movement trajectory of the subject when responding to the corresponding test content. The jaw rest stabilizes the subject's head, ensuring that the subject's head does not move significantly during the assessment, thereby ensuring the acquisition of high-quality eye movement data. The processor executes the computer program to implement the visuospatial ability assessment method. The visuospatial ability assessment method includes:

[0050] Step S10: After receiving the instruction to enter path learning, a path learning interface is displayed on the screen for the subject to learn the path. The path learning interface displays a two-dimensional map. The map shows crisscrossing streets, with buildings distributed within the blocks formed by these streets. A prescribed path is marked along the streets on the map, with one end marked as the starting point and the other end as the ending point. Several intersections are located along the prescribed path. This prescribed path is the walking path the subject must follow during subsequent three-dimensional virtual space walking tests. During path learning, the subject begins to memorize the prescribed path until the instruction to end path learning is received. The intersections are decision points.

[0051] Step S20: After receiving the instruction to enter the space for walking, a virtual three-dimensional space is displayed on the screen for the subject to conduct a three-dimensional virtual space walking test; wherein, the virtual three-dimensional space is a three-dimensional representation of the two-dimensional plane map; when the subject conducts the three-dimensional virtual space walking test, the subject uses the mouse to make a decision to start from the starting point and walk along the street to the destination according to the memorized prescribed path, and make decisions to move forward, turn left, turn right, or make a U-turn at each intersection along the way, until the mouse makes a decision to reach the destination;

[0052] Step S30: After receiving the instruction to return from the space, the subject uses the mouse to make a decision to start from the end point, walk along the street towards the starting point, and make decisions to go forward, turn left, turn right, or make a U-turn at each intersection along the way, until the mouse makes the decision to reach the starting point.

[0053] Step S40: Using the eye-tracking device to record the subject's eye movement trajectory and mouse movements, record and calculate the subject's assessment indicators;

[0054] Step S50: Based on the subject's assessment indicators, obtain the assessment results of the subject's visuospatial ability.

[0055] In this embodiment, non-immersive virtual reality technology is an emerging technology. Its virtual scene utilizes computer peripherals such as a mouse, keyboard, and microphone. It combines actual scene data obtained through a screen or photography with some computer-generated environment data to create an ideal window-like virtual environment for the user. The advantage of non-immersive virtual reality technology is that it offers users relatively more freedom, allowing multiple users to enter the system simultaneously.

[0056] In this embodiment, the method for assessing visuospatial ability based on non-immersive virtual reality mainly includes three steps: path learning, spatial walking, and spatial return. The method for assessing visuospatial ability based on non-immersive virtual reality provided by this invention provides visual stimulation to the subject while simultaneously recording the subject's unconscious responses using eye-tracking technology. Specifically, we designed detection paradigms for [path learning], [spatial walking], and [spatial return] to assess the visuospatial ability of subjects of different age groups or different cognitive function levels, achieving a truly meaningful visuospatial test. The importance of this invention is unparalleled by the currently used "paper-and-pen" experimental paradigm.

[0057] In a specific embodiment, the first item of this visuospatial ability assessment method is path learning. The user enters the [Path Learning] interface. This interface displays a two-dimensional planar map. The map has crisscrossing streets, and within the blocks formed by these streets are buildings such as residential areas, schools, hospitals, and supermarkets. A red line runs along the streets on the map. One end of the red line is marked as the "starting point," and the other end as the "ending point." This red line is the prescribed path, the walking path that the subject must follow when performing the second item, [Spatial Walking]. The subject needs to memorize this prescribed path. There is no time limit for the learning process. After the subject feels familiar with and has memorized the prescribed path, they can proceed to the second item, the [Spatial Walking] test. Further, the second item of this visuospatial ability assessment method is walking in a three-dimensional virtual space. After entering the [Spatial Walking] interface, a virtual three-dimensional space is displayed on the screen. It is a three-dimensional representation of the two-dimensional planar map in the [Path Learning] interface. The subject needs to follow the memorized prescribed path, starting from the "starting point," and walking along the streets towards the "ending point." Participants can use the mouse to make decisions to move forward, turn left, turn right, or turn around (backward) at each intersection until they reach the "endpoint." Each intersection serves as a decision point where participants need to make these decisions using the mouse. Furthermore, the third aspect of this visuospatial ability assessment method involves returning within a three-dimensional virtual space. After reaching the "endpoint" from the "starting point" in the "spatial walking" test, participants can begin the "spatial return" test. Participants must follow a prescribed path on a two-dimensional map, returning from the "endpoint" to the "starting point." Further, the step of determining the assessment result of the subject's visuospatial ability based on the subject's assessment indicators specifically includes: determining whether the subject's assessment indicators fall within a preset assessment indicator range; the preset assessment indicator range is: the assessment indicator range for elderly subjects (over 60 years old) or the assessment indicator range for young subjects (under 30 years old); when it is determined that the subject's assessment indicators fall within the assessment indicator range for elderly subjects, it is concluded that the subject's visuospatial ability is equivalent to that of elderly people; when it is determined that the subject's assessment indicators fall within the assessment indicator range for young subjects, it is concluded that the subject's visuospatial ability is equivalent to that of young people.

[0058] In one embodiment of the present invention, the evaluation indicators of the subject include one or a combination of the following: the time taken to complete path learning, the number of attention points focused on planar buildings during path learning, the total time spent focusing on planar buildings during path learning, the total time taken to complete 3D virtual space walking, the segmented time taken to complete 3D virtual space walking, the number of attention points focused on spatial buildings during 3D virtual space walking, the total time spent focusing on spatial buildings during 3D virtual space walking, the number of decision errors during 3D virtual space walking, the path deviation ρ during 3D virtual space walking, the total time taken to complete the 3D virtual space return, the segmented time taken to complete the 3D virtual space return, and the time spent focusing on spatial buildings during the 3D virtual space return. The parameters include: the number of attention points on buildings, the total duration of gaze at buildings during the 3D virtual space return process, the number of decision errors during the 3D virtual space return process, and the path deviation ε during the 3D virtual space return process; wherein, the duration of path learning is the time between receiving the instruction to enter path learning and receiving the instruction to end path learning; the number of attention points on buildings during path learning is the number of attention points on buildings on the 2D map where the subject's gaze lingers for more than 150 milliseconds during path learning; and the total duration of gaze at buildings during path learning is the total duration of gaze at buildings on the 2D map during path learning. The total time spent on each point of focus in the three-dimensional virtual space is: the total time taken for the mouse to move from the starting point to the ending point during the three-dimensional virtual space walking test; the segmented time for completing the three-dimensional virtual space walking test is: the time taken for the mouse to move from the Nth decision point to the (N+1)th decision point during the three-dimensional virtual space walking test; N is a positive integer greater than or equal to 1; the number of points of focus on buildings in the three-dimensional virtual space walking test is: the number of points of focus where the subject's gaze lingers on buildings in the three-dimensional virtual space for more than 150 milliseconds during the three-dimensional virtual space walking test; the total time spent on each point of focus in the three-dimensional virtual space walking test is: the total time taken for the subject's gaze to linger on buildings in the three-dimensional virtual space for more than 150 milliseconds during the three-dimensional virtual space walking test; the total time taken for each point of focus in the three-dimensional virtual space walking test is: the total time taken for the mouse to move from the starting point to the ending point during ... The total duration of gaze at buildings in the 3D virtual space is: the total time that the subject's gaze lingers on a point of focus on a building in the 3D virtual space during the 3D virtual space walking test; the number of decision-making errors during the 3D virtual space walking test is: the number of incorrect decisions made by the subject during the 3D virtual space walking test; the path deviation ρ of the 3D virtual space walking test is: the degree of deviation between the subject's actual walking path in the 3D virtual space and the prescribed path during the 3D virtual space walking test; the total time to complete the 3D virtual space return is: the time taken for the mouse to return from the endpoint to the starting point during the 3D virtual space return test;The segmented time for completing the 3D virtual space return is defined as follows: the time taken for the mouse to move from the Mth decision point to the (M-1)th decision point during the 3D virtual space return test; M is a positive integer greater than or equal to 2. The number of attention points on buildings during the 3D virtual space return process is defined as the number of attention points on buildings in the 3D virtual space where the subject's gaze lingers for more than 150 milliseconds during the 3D virtual space return test. The total time spent on buildings during the 3D virtual space return process is defined as the total time the subject's gaze lingers on attention points on buildings in the 3D virtual space during the 3D virtual space return test. The number of decision errors during the 3D virtual space return process is defined as the number of incorrect decisions made by the subject during the 3D virtual space return test. The path deviation ε of the 3D virtual space return is defined as the degree of deviation between the subject's actual return path in the 3D virtual space and the reverse path of the specified path during the 3D virtual space return test.

[0059] In this embodiment, the actual walking path of the subject in the three-dimensional virtual space is the walking path taken by the subject using a mouse in the three-dimensional virtual space.

[0060] In one embodiment of the present invention, the calculation process of the path deviation ρ for walking in the three-dimensional virtual space specifically includes: marking the decision point sequence of the specified path as X = [x1, x2, ..., x...]. n ]; where x i It is the i-th decision point on the specified path; where n is the total number of decision points on the specified path; the sequence of decision points of the subject's actual walking path in the three-dimensional virtual space is labeled as Y = [y1, y2, ..., y]. m ]; where y j Let be the j-th decision point on the actual walking path; where m is the total number of decision points on the actual walking path; construct an n×m distance matrix D based on the decision point sequence of the specified path and the decision point sequence of the actual walking path; where the element d(i,j) of the distance matrix D is the decision point x of the specified path. i Decision point y on the actual walking path jThe absolute value of the distance between; a cumulative distance matrix C is constructed from the distance matrix D; wherein, the element c(i,j) of the cumulative distance matrix C is the element d(i,j) of the distance matrix D plus the minimum value among the elements {c(i-1,j),c(i,j-1),c(i-1,j-1)} in the cumulative distance matrix C; the minimum value among the elements {c(i-1,j),c(i,j-1),c(i-1,j-1)} in the cumulative distance matrix C is x. i With y j The minimum cumulative distance between two points; the value of element c(n,m) in the cumulative distance matrix C is the degree of deviation between the subject's actual walking path in the three-dimensional virtual space and the prescribed path; when the subject's actual walking path is completely consistent with the prescribed path, the deviation ρ of the walking path in the three-dimensional virtual space is zero.

[0061] In one embodiment of the present invention, the calculation process of the path deviation ε returned by the three-dimensional virtual space specifically includes: the reverse path of the specified path is opposite to the specified path of spatial walking, that is, the decision point sequence of the reverse path of the specified path is denoted as... X =[ x n , x n-1 ,…, x1 ];in, x i It is the first path on the reverse path of the specified path. i There are n decision points; where n is the total number of decision points on the reverse path of the specified path; the sequence of decision points on the actual return path of the subject in the three-dimensional virtual space is marked as _____. Y =[y m ,y m-1 ,…,y 1 ]; where y j Let m be the j-th decision point on the actual return path; where m is the total number of decision points on the actual return path; and construct an n×m distance matrix based on the decision point sequence of the reverse path of the specified path and the decision point sequence of the actual return path. D Wherein, the distance matrix D The element d(i,j) is the decision point x of the reverse path of the specified path. i Decision point y of the actual return path j The absolute value of the distance between them; derived from the distance matrix. D Construct a cumulative distance matrix C ; wherein, the cumulative distance matrix C The element c(i,j) is the distance matrix. D The element d(i,j) plus the cumulative distance matrix CThe minimum value among the elements {c(i-1,j),c(i,j-1),c(i-1,j-1)} in the cumulative distance matrix C is x; i With y j The minimum cumulative distance between two points; the value of element c(n,m) in the cumulative distance matrix C is the degree of deviation between the subject's actual return path in the three-dimensional virtual space and the reverse path of the specified path; when the subject's actual return path in the three-dimensional virtual space is completely consistent with the reverse path of the specified path, the deviation ε of the path returned by the three-dimensional virtual space is zero.

[0062] In this embodiment, the path deviation ε of the three-dimensional virtual space return is defined as the degree of deviation between the subject's actual return path in the three-dimensional virtual space and the reverse path of the prescribed path during a three-dimensional virtual space return test. The calculation process for the path deviation ε of the three-dimensional virtual space return is similar to the calculation process for the path deviation ρ of the three-dimensional virtual space walking. The difference is that the reverse path of the prescribed path is opposite to the prescribed path of spatial walking. When the subject's actual return path in the three-dimensional virtual space is completely consistent with the reverse path of the prescribed path, the path deviation ε of the three-dimensional virtual space return is zero.

[0063] The technical solution of the present invention will be illustrated below with a specific embodiment 1.

[0064] Example 1

[0065] Experimental subjects:

[0066] To verify the evaluation effect of this invention, 60 subjects were recruited to participate in this experiment. The youth group (under 30 years old) consisted of students from schools; the elderly group (over 60 years old) consisted of ordinary community residents and grassroots workers. Information for each age group is shown in Table 1.

[0067] Inclusion criteria for participants in this experiment: (1) normal daily living and social interaction abilities; (2) junior high school education or above; (3) no major physical illnesses or eye diseases affecting vision (including color blindness); (4) participants should have sufficient cognitive and language abilities to complete the neuropsychological assessment; (5) able to correctly understand the significance of this study and have good compliance; (6) voluntarily join this study. Exclusion criteria for volunteers participating in this experiment: (1) history of mental illness; (2) brain trauma; (3) eye diseases affecting vision.

[0068] Table 1 Subject Information

[0069]

[0070] Ethical Statement:

[0071] This study adhered to the principles of the Declaration of Helsinki and passed the evaluation and acceptance of the Research Ethics Committee of China Medical University (No.: 202373). All research participants read the research informed consent form and signed the informed consent form before participating in the study. All participants were verbally informed of the overall purpose of the experiment and agreed to participate.

[0072] Experimental design and experimental procedures:

[0073] The subjects sat comfortably in front of the cognitive function testing instrument, placing their chin on the instrument's jaw support, and tried to keep their heads still during the test.

[0074] Click on the [Video Demonstration] to learn how to conduct the test. You can use the [Practice] mode to familiarize yourself with the test content and mouse usage. The 2D map in [Practice] mode differs from the one in the subsequent formal test. Test takers can practice three times.

[0075] In this test, such as Figure 3 As shown, the red line represents the route the participants must follow in the subsequent spatial walking test. The 2D map for path learning features a path with six intersections: three requiring left turns, two requiring right turns, and one requiring going straight. There is no time limit for the path learning process. Once participants feel they have memorized the path, they can request permission from staff to enter the spatial walking test.

[0076] In the spatial walking exercise of this test, participants were required to follow a prescribed path memorized in the path learning exercise, starting from the "starting point" (e.g., ...). Figure 4 As shown) to reach the "end point" (e.g. Figure 6 As shown). Figure 5 As shown, at each intersection, the test taker needs to use the mouse to make a decision to "turn left", "turn right" or "go straight".

[0077] Statistical analysis:

[0078] The results of this experiment are expressed as mean ± standard deviation. Homogeneity of variance and normality of data were tested using the Shapiro-Wilk and Levene methods. If the samples were normally distributed and had homogeneous variances, comparisons between multiple groups were performed using ANOVA and the Buffoni test. If the data did not follow a normal distribution and showed homogeneity of variance, comparisons between multiple groups were performed using the Kruskal-Wallis one-way ANOVA and the Buffoni-corrected Mann-Whitney test. Statistical analysis was performed using Origin 2022 software, and a p-value < 0.05 was considered statistically significant.

[0079] Experimental results:

[0080] Traditional Mini-Mental State Examination (MMSE) methods for assessing visuospatial function include time and spatial orientation tests, drawing imitation diagrams, immediate memory, and recall. Table 2 shows the test results of the MMSE. As shown in Table 2, the MMSE has low specificity and sensitivity in identifying visuospatial abilities between subjects of different age groups.

[0081] Table 2 MMSE Scale Test Results

[0082]

[0083] The test results of the two different age groups using the present invention are shown in Table 3.

[0084] Table 3 Test results of the present invention

[0085]

[0086]

[0087] Furthermore, such as Figure 7 As shown, the total time for young subjects to complete path learning was significantly shorter than that for older subjects.

[0088] Furthermore, such as Figure 8 As shown, the number of attention points for young subjects in path learning on a two-dimensional map was significantly less than that for older subjects. These attention points had the following characteristics: young subjects concentrated more on the prescribed path and intersections (such as...). Figure 9a As shown), while the attention of older subjects was more scattered (e.g. Figure 9b (As shown).

[0089] Furthermore, such as Figure 10 As shown, the attention span of young subjects on the two-dimensional map was significantly shorter than that of older subjects.

[0090] Furthermore, such as Figure 11 As shown, the time taken for young subjects to complete "spatial walking" in three-dimensional space was shorter than that for older subjects.

[0091] Furthermore, such as Figure 12 As shown, younger subjects paid less attention to spatial landmarks than older subjects during the "spatial walk".

[0092] Furthermore, such as Figure 13 As shown, younger subjects paid less attention to spatial landmarks during the "spatial walk" than older subjects.

[0093] Furthermore, such as Figure 14 As shown, during the "spatial walking" process, the deviation between the actual path and the prescribed path was significantly smaller in young subjects than in older subjects.

[0094] Furthermore, such as Figure 15 As shown, subgroup 1: able to complete the spatial walk completely according to the prescribed route (ρ=0.0); subgroup 2: able to complete the spatial walk completely according to the prescribed route, but with slight errors in the process; subgroup 3: unable to complete the walk completely according to the prescribed route. It can be seen that the actual walking paths of the vast majority of young subjects did not deviate from the prescribed path (subgroup 1), while the actual walking paths of the vast majority of elderly subjects deviated significantly from the prescribed path (subgroups 2 and 3).

[0095] Furthermore, such as Figure 16 As shown, the distribution of the first errors during the "spatial walk" process for young and elderly subjects indicates that the third intersection is where elderly subjects are most likely to make mistakes.

[0096] Furthermore, in the spatial walking test, the inconsistency between the actual path and the prescribed path can be clearly characterized by quantitative path deviation.

[0097] a) such as Figure 17 As shown, Example 1 (ρ = 0.00);

[0098] b) such as Figure 18 As shown, Example 2 (ρ = 1.00);

[0099] c) such as Figure 19 As shown, Example 3 (ρ = 3.41);

[0100] d) such as Figure 20 As shown, Example 4 (ρ = 4.24);

[0101] e) such as Figure 21 As shown, Example 5 (ρ = 3.41);

[0102] f) such as Figure 22 As shown, Example 6 (ρ = 12.48);

[0103] g) such as Figure 23 As shown, Example 7 (ρ = 2.00);

[0104] h) such as Figure 24 As shown, Example 8 (ρ = 4.00);

[0105] i) Such as Figure 25 As shown, Example 9 (ρ = 2.00).

[0106] in conclusion:

[0107] The method for assessing visuospatial abilities based on non-immersive virtual reality, as described in this invention, can effectively identify differences in subjects' visuospatial abilities (path learning, spatial walking), with results far superior to existing assessment methods. Therefore, the method for assessing visuospatial abilities based on non-immersive virtual reality, as described in this invention, can be used for accurate and comprehensive assessment of visuospatial ability, one of the dimensions of cognitive function.

[0108] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for implementing a visual spatial ability assessment based on non-immersive virtual reality, for a computer device, the computer device comprising: Mouse, display screen, eye tracker, jaw bracket, memory, processor and computer program stored on the memory and executable on the processor; wherein the mouse is used to control the movement of the cursor on the display screen, the display screen is used to display the corresponding test content of the visual space ability evaluation method, the eye tracker is used to record the eye movement trajectory of the subject when responding to the corresponding test content, the jaw bracket is used to stabilize the head of the subject, and the processor is used to implement the visual space ability evaluation method when the computer program is executed; characterized in that the visual space ability evaluation method comprises: Step S1: after receiving the instruction to enter path learning, displaying the path learning interface on the display screen for the subject to learn the path; wherein a two-dimensional plane map is displayed on the path learning interface; the two-dimensional plane map is distributed with longitudinally and transversely interlaced streets, and buildings are distributed in the blocks surrounded by the streets; a prescribed path is marked along the streets on the two-dimensional plane map, one end of the prescribed path is marked as the starting point, the other end of the prescribed path is marked as the ending point, and a plurality of crossroads are distributed on the prescribed path; the prescribed path is the walking path that the subject needs to follow when subsequently receiving the test of walking in a three-dimensional virtual space; when the subject learns the path, the subject starts to memorize the prescribed path until receiving the instruction to end the path learning; wherein the crossroads are decision points; Step S2: after receiving the instruction to enter space walking, displaying a virtual three-dimensional space on the display screen for the subject to perform the test of walking in a three-dimensional virtual space; wherein the virtual three-dimensional space is a three-dimensional solidification of the two-dimensional plane map; when the subject performs the test of walking in a three-dimensional virtual space, the subject uses the mouse to make a decision to start from the starting point, walk along the streets to the ending point, make a decision to advance, turn left, turn right or U-turn at each crossroad on the way, until the mouse makes a decision to reach the ending point according to the memorized prescribed path; Step S3: using the eye movement trajectory of the subject recorded by the eye tracker and the action of the mouse to record and calculate the evaluation index of the subject; Step S4: according to the evaluation index of the subject, obtaining the evaluation result of the visual space ability of the subject; After step S2 and before step S3, it further comprises: After receiving the instruction to enter space return, the subject uses the mouse to make a decision to start from the ending point, walk along the streets to the starting point, make a decision to advance, turn left, turn right or U-turn at each crossroad on the way, until the mouse makes a decision to reach the starting point according to the memorized prescribed path; The evaluation index of the subject includes one or a combination of the following: a length of time for completing path learning, a number of fixation points of gazing at a planar building during path learning, a total length of time of gazing at the planar building during path learning, a total length of time for completing walking in a three-dimensional virtual space, a segmented length of time for completing walking in the three-dimensional virtual space, a number of fixation points of gazing at a spatial building during walking in the three-dimensional virtual space, a total length of time of gazing at the spatial building during walking in the three-dimensional virtual space, a number of decision-making errors during walking in the three-dimensional virtual space, a path deviation degree of walking in the three-dimensional virtual space , a total length of time for completing returning in the three-dimensional virtual space, a segmented length of time for completing returning in the three-dimensional virtual space, a number of fixation points of gazing at the spatial building during returning in the three-dimensional virtual space, a total length of time of gazing at the spatial building during returning in the three-dimensional virtual space, a number of decision-making errors during returning in the three-dimensional virtual space, a path deviation degree of returning in the three-dimensional virtual space ; Wherein, the length of time for completing path learning is the length of time between receiving the instruction to enter path learning and receiving the instruction to end path learning; The number of attention points of the fixation plane building in the path learning process is the number of attention points at which the subject's gaze stays on the buildings on the two-dimensional plane map for more than 150 milliseconds during the path learning of the subject. The total time length of the gaze on the building in the path learning process is the total time length of the gaze of the subject on the attention point on the building in the two-dimensional plane map in the path learning process; The total time length of the completion of the three-dimensional virtual space walking is the time length of the mouse from the starting point to the ending point in the three-dimensional virtual space walking test; The segmented time length of the completion of the three-dimensional virtual space walking is the time length of the mouse from the Nth decision point to the N+1th decision point in the three-dimensional virtual space walking test; N is a positive integer greater than or equal to 1; The number of attention points on the building in the three-dimensional virtual space walking process is the number of attention points on the building in the three-dimensional virtual space walking test, whose gaze time on the building is more than 150 milliseconds; The total time length of the gaze on the building in the three-dimensional virtual space walking process is the total time length of the gaze of the subject on the attention point on the building in the three-dimensional virtual space walking test; The number of decision errors in the three-dimensional virtual space walking process is the number of errors in the decision of the subject in the three-dimensional virtual space walking test; Path deviation degree of the three-dimensional virtual space walking is: the deviation degree of the real walking path of the subject in the three-dimensional virtual space from the prescribed path in the test of the three-dimensional virtual space walking of the subject; The total time length of the completion of the three-dimensional virtual space return is the time length of the mouse from the ending point to the starting point in the three-dimensional virtual space return test; The segmented time length of the completion of the three-dimensional virtual space return is the time length of the mouse from the Mth decision point to the M-1th decision point in the three-dimensional virtual space return test; M is a positive integer greater than or equal to 2; The number of attention points on the building in the three-dimensional virtual space return process is the number of attention points on the building in the three-dimensional virtual space return test, whose gaze time on the building is more than 150 milliseconds; The total time length of the gaze on the building in the three-dimensional virtual space return process is the total time length of the gaze of the subject on the attention point on the building in the three-dimensional virtual space return test; The number of decision errors in the three-dimensional virtual space return process is the number of errors in the decision of the subject in the three-dimensional virtual space return test; The path deviation degree of the three-dimensional virtual space return is: the deviation degree of the real return path of the subject in the three-dimensional virtual space from the reverse path of the prescribed path in the test of three-dimensional virtual space return; Path deviation degree of the three-dimensional virtual space walking The computing process specifically comprises: marking a decision point sequence of the prescribed path as X = [x1, x2, …, xn]; wherein xi is the i-th decision point on the prescribed path; wherein n is the total number of decision points on the prescribed path n ]; wherein xi is the i-th decision point on the prescribed path; wherein n is the total number of decision points on the prescribed path i ​ mark a decision point sequence of a real walking path of the subject in a three-dimensional virtual space as Y = [y1, y2, …, y m ]; wherein y j is the jth decision point on the real walking path; wherein m is the total number of decision points on the real walking path; According to the decision point sequence of the prescribed path and the decision point sequence of the real walking path, a distance matrix D of n*m dimensions is constructed; wherein, an element d(i,j) of the distance matrix D is an absolute value of a distance between a decision point x i of the prescribed path and a decision point y j of the real walking path. constructing a cumulative distance matrix C from the distance matrix D; wherein an element c(i,j) of the cumulative distance matrix C is the element d(i,j) of the distance matrix D plus the minimum of the elements {c(i-1,j), c(i,j-1), c(i-1,j-1)} in the cumulative distance matrix C; the minimum of the elements {c(i-1,j), c(i,j-1), c(i-1,j-1)} in the cumulative distance matrix C is x i and y j the minimum cumulative distance between two points; The value of the element c(n,m) in the cumulative distance matrix C is the deviation degree of the real walking path of the subject in the three-dimensional virtual space from the prescribed path. the path deviation degree of the three-dimensional virtual space walking when the subject's actual walking path and the prescribed path are completely consistent is zero; The path deviation degree of the three-dimensional virtual space returned The computing process specifically comprises: The reverse path of the prescribed path is the opposite of the prescribed path for spatial walking, that is, the sequence of decision points for the reverse path of the prescribed path is denoted as... X = [ x n , x n-1 , …, x1 ];in, x i It is the first path on the reverse path of the specified path. i There are n decision points; where n is the total number of decision points on the reverse path of the specified path. marking a sequence of decision points of a real return path of the subject in a three-dimensional virtual space as being Y = [ y m , y m-1 , …, y1 ];wherein, y j is the jth decision point on the real return path; wherein m is the total number of decision points on the real return path; a distance matrix of n x m dimensions is constructed from the sequence of decision points of the inverse of the prescribed path and the sequence of decision points of the real return path D ; wherein the elements D (i,j) of the distance matrix d are the absolute values of the distances between the decision points x i of the inverse of the prescribed path y j and the decision points of the real return path From the distance matrix D Construct a cumulative distance matrix C ; wherein, the cumulative distance matrix C elements c (i,j) is the distance matrix D elements d (i,j) plus the cumulative distance matrix C middle element { c (i-1,j), c (i,j-1), c The minimum value in (i-1,j-1)}; the element { in the cumulative distance matrix C} c (i-1,j), c (i,j-1), c The minimum value in (i-1, j-1)} is x i and y j The minimum cumulative distance between two points; The element in the cumulative distance matrix C c The value of (n, m) is the deviation degree of the real return path of the subject in the three-dimensional virtual space from the inverse path of the prescribed path. The path deviation degree of the three-dimensional virtual space return path is zero when the real return path of the subject in the three-dimensional virtual space is completely consistent with the inverse path of the prescribed path. is zero.

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