Rehabilitation training system and method for spatial neglect, electronic equipment and storage medium

Abstract

The invention provides a space neglect rehabilitation training system and method, electronic equipment and a storage medium, and the system comprises a training control module which is used for receiving patient archive information sent by an information management module, determining task parameters of a rehabilitation training plan, and sending the task parameters to the information management module; the task parameters of the rehabilitation training plan are adjusted in real time according to the training condition received in real time; the calibration and training module is used for controlling the patient to complete different cognitive interaction task training based on the task parameters of the rehabilitation training plan and determining the training condition of the patient in the cognitive interaction task training process; the data acquisition module is used for acquiring action data of the patient in a cognitive interaction task training process in real time; the data analysis module is used for performing data analysis on the action data to generate a visual chart; the report feedback module analyzes the visual chart and determines the task parameters of the next rehabilitation training plan of the patient, so that the training efficiency is improved, and the training safety and effectiveness are ensured.

Description

Technical Field

[0001] The present application relates to the field of medical equipment technology, and in particular to a rehabilitation training system, method, electronic device and storage medium for spatial neglect. Background Art

[0002] Spatial neglect is a common cognitive dysfunction in stroke patients, with an incidence of about 30% to 40% in stroke patients. Patients are unable to perceive or respond to stimuli in a specific space, which is mainly manifested as patients ignoring the space on one side of the body, especially in terms of attention, perception and action, which seriously affects patients' daily living ability and quality of life. The main treatment method for traditional spatial neglect rehabilitation is prism adaptation therapy. Its core principle is to use prism glasses to shift the patient's visual input, and patients achieve treatment effects through adaptive training. For example, when patients wear prism glasses, the position of objects they see will shift to one side. This shift forces patients to recalibrate when performing hand-eye coordination tasks (such as touching or pointing to a target) to adapt to the new visual input. Through continuous practice and adaptation, the patient's brain gradually readjusts its spatial perception, thereby improving attention and response ability to the neglected side of the space. Traditional rehabilitation training has the following shortcomings: (1) Intervention training requires therapists to supervise and guide patients one-on-one, which is labor-intensive. (2) Patients need to be trained in a specific treatment environment, which lacks flexibility. (3) The training intensity and effect of traditional methods are difficult to evaluate, which is not conducive to medical workers to judge the rehabilitation status. (4) The collected data is limited, and it is impossible to fully collect data such as the patient's head movement, hand movement, and reaction time, which limits the analysis and evaluation of the training effect. Therefore, how to improve the efficiency of rehabilitation training for spatial neglect has become a technical issue that cannot be underestimated. Summary of the invention

[0003] In view of this, the purpose of the present application is to provide a rehabilitation training system, method, electronic device and storage medium for spatial neglect, which uses automated data collection and analysis to improve training efficiency. The data analysis module converts data into visual charts, provides doctors with a quantitative training effect evaluation tool to improve the accuracy of the evaluation, and allows doctors to observe the patient's training performance in real time, and adjust the training difficulty or terminate the training as needed. This real-time feedback mechanism ensures the safety and effectiveness of the training.

[0004] The embodiment of the present application provides a rehabilitation training system for spatial neglect, the rehabilitation training system comprising an information management module, a training control module, a calibration and training module, a data acquisition module, a data analysis module and a report feedback module, the training control module is respectively connected to the information management module and the calibration and training module, the data acquisition module is respectively connected to the calibration and training module and the data analysis module, and the report feedback module is connected to the data analysis module; wherein,

[0005] The information management module is used to obtain the patient file information entered by the doctor;

[0006] The training control module is used to receive the patient file information sent by the information management module, determine the task parameters of the patient's rehabilitation training plan based on the patient file information, send the task parameters of the rehabilitation training plan to the calibration and training module, and receive the training situation sent by the calibration and training module in real time, and adjust the task parameters of the rehabilitation training plan in real time based on the training situation;

[0007] The calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, send data collection instructions to the data collection module, and determine the training status of the patient during the cognitive interaction task training; wherein the cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, visual search target elimination training, and advanced sustained attention reaction training;

[0008] The data acquisition module is used to collect the patient's motion data in real time during the cognitive interaction task training after receiving the data acquisition instruction, and send the motion data to the data analysis module;

[0009] The data analysis module is used to perform data analysis on the motion data to generate a visualization chart; wherein the visualization chart includes the game completion, operation speed, operation accuracy, head rotation degree and hand operation status of the patient under different cognitive interaction task training:;

[0010] The report feedback module is used to analyze the game completion, operation speed, operation accuracy, head rotation degree and hand operation of the patient in the visualization chart, determine the task parameters of the patient's next rehabilitation training plan, and combine the results of data analysis during the patient's game process and the patient's basic information to provide feedback to the patient and doctor.

[0011] In a possible implementation manner, when the training control module is used to adjust the task parameters of the rehabilitation training plan in real time based on the training situation, the training control module is specifically used to:

[0012] Determining whether the current task difficulty among the task parameters matches the ability of the patient based on the training situation;

[0013] If so, controlling the patient wearing the virtual reality device to continue training based on the task parameters of the rehabilitation training plan;

[0014] If not, the rehabilitation training program is terminated and the difficulty of the current task is adjusted.

[0015] In a possible implementation manner, before the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is also used to:

[0016] The patient is controlled to interact with the interactive device based on the mirror operation teaching and voice prompt learning of wearing the virtual reality device, so as to complete the calibration training and determine the maximum range of the patient's head rotation and the maximum range of the arm extension; wherein the interaction method includes the interaction method of raising the left hand and the right hand during virtual gestures, the interaction method of clicking the button with the left hand and the right hand when using the handle controller, and the interaction method of rotating the head to the left and to the right.

[0017] In a possible implementation, for the virtual reality prism adaptation training, when the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to:

[0018] The patient wearing the virtual reality device is set to be in the central position of a virtual natural scene, and the number of times the patient raises his virtual hand or uses a handle to correctly click on a target that appears randomly in front of the field of vision at different difficulty levels, as well as the patient's hand operation during the virtual reality prism adaptation training, are determined.

[0019] In a possible implementation, for the head and torso rotation training, when the calibration and training module is used to control the patient wearing the virtual reality device to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to:

[0020] The patient wearing the virtual reality device is placed in the center of a virtual natural scene, and the number of times the patient raises a virtual hand or uses a handle to correctly move an object to a target on the neglected side at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the head and torso rotation training.

[0021] In a possible implementation manner, when the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to:

[0022] For the visual search and target elimination training, the patient wearing the virtual reality device is set to be in the central position of the virtual natural scene, and the time for the patient to raise the virtual hand or use the handle to completely eliminate the ignored side aerial target matrix correctly under different difficulty levels is determined, as well as the patient's head rotation degree and hand operation during the visual search and target elimination training;

[0023] For the advanced sustained attention reaction training, the patient wearing the virtual reality device is placed on a high platform in the center of a virtual natural scene, and the number of times the patient raises his virtual hand or uses the handle to correctly defend against a target flying out of the bushes at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the advanced sustained attention reaction training.

[0024] In a possible implementation manner, when the data analysis module is used to perform data analysis on the action data to generate a visual chart, the data analysis module is specifically used to:

[0025] Data analysis is performed on the game completion degree, average operation reaction time, operation accuracy, maximum head rotation range, and arm lifting and extension range in the action data to generate a visual chart.

[0026] The present application also provides a rehabilitation training method for spatial neglect, the rehabilitation training method comprising:

[0027] Determine the task parameters of the patient's rehabilitation training plan based on the patient's file information;

[0028] Controlling the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, and determining the training status and motion data of the patient during the cognitive interaction task training; wherein the cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, visual search and elimination target training, and advanced sustained attention reaction training;

[0029] Based on the training situation, the task parameters of the rehabilitation training plan are adjusted in real time, and the action data are analyzed to generate a visual chart;

[0030] The patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status in the visualization chart are analyzed to determine the task parameters of the patient's next rehabilitation training plan, and the results of the data analysis during the patient's game and the patient's basic information are combined to provide feedback to the patient and doctor.

[0031] An embodiment of the present application also provides an electronic device, including: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and when the machine-readable instructions are executed by the processor, the steps of the above-mentioned spatial neglect rehabilitation training method are performed.

[0032] An embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned spatial neglect rehabilitation training method are executed.

[0033] The embodiment of the present application provides a rehabilitation training system, method, electronic device and storage medium for spatial neglect. The rehabilitation training system includes an information management module, a training control module, a calibration and training module, a data acquisition module, a data analysis module and a report feedback module. The training control module is respectively communicated with the information management module and the calibration and training module, the data acquisition module is respectively communicated with the calibration and training module and the data analysis module, and the report feedback module is communicated with the data analysis module; wherein the information management module is used to obtain the patient file information entered by the doctor; the training control module is used to receive the patient file information sent by the information management module, determine the task parameters of the patient's rehabilitation training plan based on the patient file information, send the task parameters of the rehabilitation training plan to the calibration and training module, and receive the training situation sent by the calibration and training module in real time, and adjust the task parameters of the rehabilitation training plan in real time based on the training situation; the calibration and training module is used to control the patient to complete the task parameters of the rehabilitation training plan under different virtual reality conditions based on the task parameters of the rehabilitation training plan The data acquisition module is used to perform real-time collection of the patient's motion data during the cognitive interaction task training after receiving the data acquisition instruction, and send the motion data to the data analysis module; the data analysis module is used to perform data analysis on the motion data to generate a visualization chart; the visualization chart includes the game completion, operation speed, operation accuracy, head rotation degree and hand operation of the patient under different cognitive interaction task training; the report feedback module is used to analyze the game completion, operation speed, operation accuracy, head rotation degree and hand operation of the patient in the visualization chart, determine the task parameters of the patient's next rehabilitation training plan, and provide feedback to the patient and the doctor based on the results of the data analysis during the patient's game and the patient's basic information. The use of automated data collection and analysis improves training efficiency. The data analysis module converts data into visual charts, providing doctors with a quantitative training effect evaluation tool to improve the accuracy of the evaluation. It allows doctors to observe the patient's training performance in real time and adjust the training difficulty or terminate the training as needed. This real-time feedback mechanism ensures the safety and effectiveness of the training.

[0034] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A schematic diagram of the structure of a rehabilitation training system for spatial neglect provided in an embodiment of the present application;

[0037] Figure 2 An interactive schematic diagram of a rehabilitation training system for spatial neglect provided in an embodiment of the present application;

[0038] Figure 3 A flowchart of a rehabilitation training for spatial neglect provided in an embodiment of the present application;

[0039] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0040] Icon: 100 - Rehabilitation training system for spatial neglect; 110 - Information management module; 120 - Training control module; 130 - Calibration and training module; 140 - Data acquisition module; 150 - Data analysis module; 160 - Report feedback module; 400 - Electronic device; 410 - Processor; 420 - Memory; 430 - Bus. DETAILED DESCRIPTION

[0041] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0042] First, the application scenarios to which the present application is applicable are introduced. The present application can be applied in the field of medical device technology.

[0043] Studies have found that spatial neglect is a common cognitive dysfunction in stroke patients, with an incidence of about 30% to 40% in stroke patients. Patients are unable to perceive or respond to stimuli in a specific space, which is mainly manifested as patients ignoring the space on one side of the body, especially in terms of attention, perception and action, which seriously affects patients' daily living ability and quality of life. The main treatment method for traditional spatial neglect rehabilitation is prism adaptation therapy, the core principle of which is to use prism glasses to shift the patient's visual input, and patients achieve treatment effects through adaptive training. For example, when patients wear prism glasses, the position of objects they see will shift to one side. This shift forces patients to recalibrate when performing hand-eye coordination tasks (such as touching or pointing to a target) to adapt to the new visual input. Through continuous practice and adaptation, the patient's brain gradually readjusts its spatial perception, thereby improving attention and response to the neglected side of the space. Traditional rehabilitation training has the following shortcomings: (1) Intervention training requires therapists to supervise and guide patients one-on-one, which is labor-intensive. (2) Patients need to be trained in a specific treatment environment, which lacks flexibility. (3) The training intensity and effect of traditional methods are difficult to evaluate, which is not conducive to medical workers to judge the rehabilitation status. (4) The collected data is limited, and it is impossible to fully collect data such as the patient's head movement, hand movement and reaction time, which limits the analysis and evaluation of the training effect. Therefore, how to improve the efficiency of spatial neglect rehabilitation training has become a technical issue that cannot be underestimated.

[0044] Based on this, the embodiment of the present application provides a rehabilitation training system for spatial neglect, which uses automated data collection and analysis to improve training efficiency. The data analysis module converts data into visual charts, provides doctors with a quantitative training effect evaluation tool to improve the accuracy of the evaluation, and allows doctors to observe the patient's training performance in real time, and adjust the training difficulty or terminate the training as needed. This real-time feedback mechanism ensures the safety and effectiveness of the training.

[0045] See also Figure 1 , Figure 1 This is one of the structural diagrams of the spatial neglect rehabilitation training system 100 provided in the embodiment of the present application. Figure 1 As shown in, the rehabilitation training system 100 for spatial neglect provided in the embodiment of the present application includes an information management module 110, a training control module 120, a calibration and training module 130, a data acquisition module 140, a data analysis module 150 and a report feedback module 160. The training control module 120 is respectively communicated with the information management module 110 and the calibration and training module 130, the data acquisition module 140 is respectively communicated with the calibration and training module 130 and the data analysis module 150, and the report feedback module 160 is communicated with the data analysis module 150.

[0046] Specifically, the information management module 110 is used to obtain the patient file information entered by the doctor; the training control module 120 is used to receive the patient file information sent by the information management module 110, determine the task parameters of the patient's rehabilitation training plan based on the patient file information, send the task parameters of the rehabilitation training plan to the calibration and training module 130, and receive the training status sent by the calibration and training module 130 in real time, and adjust the task parameters of the rehabilitation training plan in real time based on the training status; the calibration and training module 130 is used to control the patient to complete the cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, send data collection instructions to the data collection module 140, and determine the training status of the patient during the cognitive interaction task training; wherein, the cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, and so on. rotation training, visual search and elimination target training and advanced sustained attention reaction training; the data acquisition module 140 is used to collect the patient's motion data in real time during the cognitive interaction task training after receiving the data acquisition instruction, and send the motion data to the data analysis module 150; the data analysis module 150 is used to analyze the motion data and generate a visual chart; wherein the visual chart includes the patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status under different cognitive interaction task training, the report feedback module 160 is used to analyze the patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status in the visual chart, determine the task parameters of the patient's next rehabilitation training plan, and combine the results of the data analysis during the patient's game and the patient's basic information, and feedback to the patient and doctor.

[0047] In a specific embodiment, the training control module 120 receives the patient file information sent by the information management module 110, determines the task parameters of the patient's rehabilitation training plan according to the patient file information, and sends the task parameters of the rehabilitation training plan to the calibration and training module 130. The calibration and training module 130 controls the patient to complete the cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, sends a data collection instruction to the data collection module 140, and determines the patient's training status during the cognitive interaction task training; the training control module 120 receives the training status sent by the calibration and training module 130 in real time, and based on the training status The task parameters of the rehabilitation training plan are adjusted in real time; after receiving the data collection instruction, the data acquisition module 140 collects the patient's motion data in real time during the cognitive interaction task training, and sends the task execution to the data analysis module 150; the data analysis module 150 analyzes the motion data to generate a visual chart, and the report feedback module 160 analyzes the patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation in the visual chart to determine the task parameters of the patient's next rehabilitation training plan, and combines the results of the data analysis during the patient's game and the patient's basic information, and feeds back to the patient and doctor.

[0048] Here, the patient file information includes the patient's name, gender, age, course of disease, severity, dominant hand, spatial neglect side, etc. A rehabilitation training plan is formulated according to the severity of the patient's spatial neglect. The task parameters of the rehabilitation training plan include other parameters such as training difficulty and task type.

[0049] In it, the patient wears a virtual reality device.

[0050] Among them, the information management module 110 is used by the doctor to input the basic information of the patient, including name, gender, age, course of disease, spatial neglect side, severity, training status, etc.; the training control module 120 is used by the doctor to start, pause and terminate the task, and adjust the difficulty of the task by monitoring the completion of the patient's task training; the calibration and training module 130 is used by the patient to guide the patient to complete cognitive interaction tasks under different virtual reality conditions through the pictures and voice prompts of the virtual reality glasses; the data acquisition module 140 is used by the patient to collect the task completion status, head rotation angle and arm extension range of the patient during the task training process through the handle / virtual gesture recognition sensor and head movement sensor of the virtual reality glasses; the data analysis module 150 is used to analyze and extract the collected data to obtain visual charts of the game completion, operation speed, operation accuracy, head rotation degree and hand operation status under each task training.

[0051] Here, when the patient is performing the task, the calibration and training module 130 will feed back the images and voice signals in the game to the training control module 120 in real time. The doctor will determine whether to pause, end or adjust the difficulty of the task based on the patient's performance in the task. At the same time, the calibration and training module 130 will trigger the data acquisition module 140 to start recording the patient's motion data, such as head position information, hand position information, etc.

[0052] Here, further statistical analysis is performed based on the generated visualization charts, including the completion rate, error rate and correction ability within the specified time, training adaptability indicators, long-term rehabilitation trend judgment, and a comprehensive scoring system. Combined with the patient's actual performance in the task, a feedback report for the current task is generated. The doctor evaluates the training effect based on the feedback report provided by the report feedback module 160, and adjusts the task parameters of the rehabilitation training plan in the training control module 120, such as increasing the training difficulty or changing the training content; at the same time, the doctor updates the patient's training status record in the information management module 110 to provide data support for the patient's long-term rehabilitation tracking.

[0053] In a possible implementation manner, when the training control module 120 is used to adjust the task parameters of the rehabilitation training plan in real time based on the training situation, the training control module 120 is specifically used to:

[0054] A: Determine whether the current task difficulty among the task parameters matches the patient's ability based on the training situation.

[0055] Here, it is determined based on the training situation whether the current task difficulty among the task parameters matches the patient's ability.

[0056] B: If so, control the patient wearing the virtual reality device to continue training based on the task parameters of the rehabilitation training plan; if not, terminate the rehabilitation training plan and adjust the difficulty of the current task.

[0057] Here, if yes, the patient wearing the virtual reality device is controlled to continue training according to the task parameters of the rehabilitation training plan; if no, the rehabilitation training plan is terminated and the difficulty of the current task is adjusted.

[0058] Here, the doctor monitors the real-time status of the patient's task training through the monitor, and identifies whether the current task difficulty matches the patient's ability based on the patient's operational performance. If there is a mismatch, the doctor will terminate the task in time and adjust the difficulty. In addition, the task training can be temporarily suspended or terminated according to the patient's wishes.

[0059] In a possible implementation manner, before the calibration and training module 130 is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module 130 is further used to:

[0060] The patient is controlled to interact with the interactive device based on the mirror operation teaching and voice prompt learning of wearing the virtual reality device, so as to complete the calibration training and determine the maximum range of the patient's head rotation and the maximum range of the arm extension; wherein the interaction method includes the interaction method of raising the left hand and the right hand during virtual gestures, the interaction method of clicking the button with the left hand and the right hand when using the handle controller, and the interaction method of rotating the head to the left and to the right.

[0061] Here, a scene interaction environment is set up to collect information about how far the patient's left and right hands can reach respectively and the maximum angle the head can turn. A virtual person sitting face to face with the patient's perspective appears in the virtual environment, and voice prompts the patient to perform mirror movements. If a handle controller is used, prompt the patient to raise his left and right hands in turn and stretch them to the maximum distance, hold the button for 5 seconds and then put it down, and repeat three times for each hand. If using virtual gestures, just raise your hand and stretch it as far as possible, hold it for 5 seconds and then put it down. Head rotation calibration prompts the patient to rotate his head to the maximum angle to the left and right respectively, hold it for 5 seconds and then resume. This task helps patients become familiar with the basic operations of subsequent training and records the maximum range of head rotation and arm extension.

[0062] In a possible implementation, for the virtual reality prism adaptation training, when the calibration and training module 130 is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module 130 is specifically used to:

[0063] The patient wearing the virtual reality device is set to be in the central position of a virtual natural scene, and the number of times the patient raises his virtual hand or uses a handle to correctly click on a target that appears randomly in front of the field of vision at different difficulty levels, as well as the patient's hand operation during the virtual reality prism adaptation training, are determined.

[0064] Here, patients wearing virtual reality devices were set in the center of a virtual natural scene, and the number of times the patients raised their virtual hands or used the handles to correctly click on targets that appeared randomly in front of their field of vision at different difficulty levels was determined, as well as the patients' hand operations during the virtual reality prism adaptation training.

[0065] In a specific embodiment, the virtual reality prism adaptation training is: setting a scene interaction environment, and the patient is in the center of a virtual natural scene. A target appears randomly in front of the field of vision, and the patient needs to raise the virtual hand or use the handle to click the target, and continue the next round of operation after the target disappears. The warm-up session guides the patient to operate correctly, and the formal session records the operation parameters and scores. The primary difficulty includes four random positions, 4 rounds of warm-up training, and the maximum field of view of the head rotation is 45° on the left and right; the advanced difficulty includes eight random positions, 8 rounds of warm-up training, and the field of view is 60° on the left and right. The formal training is 100 rounds. As the number of rounds increases, the angle between the virtual hand and the real hand gradually increases. The angle increases by 1° for every 4 rounds, with a maximum of 25°. For example, if the patient is neglected in the left space, the virtual hand is on the right side of the real hand, and the opposite is true for the patient neglected in the right space.

[0066] In a possible implementation, for the head and torso rotation training, when the calibration and training module 130 is used to control the patient wearing the virtual reality device to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module 130 is specifically used to:

[0067] The patient wearing the virtual reality device is placed in the center of a virtual natural scene, and the number of times the patient raises a virtual hand or uses a handle to correctly move an object to a target on the neglected side at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the head and torso rotation training.

[0068] Here, patients wearing virtual reality devices were placed in the center of a virtual natural scene, and the number of times the patients raised their virtual hands or used the handle to correctly move objects to the neglected side target at different difficulty levels was determined, as well as the degree of head rotation and hand manipulation of the patients during head and torso rotation training.

[0069] In a specific embodiment, the head and torso rotation training is as follows: a scene interaction environment is set up, and the patient is in the center of a virtual natural scene. A target appears in the air on the side of the neglected object, and an object appears in the air on the opposite side. The patient needs to use a virtual hand or handle to move the object to the target. The warm-up session guides the patient to operate correctly, and the formal session records the operation parameters and scores. The angle between the object and the target for the elementary difficulty is 40° to 90°, and the angle for the advanced difficulty is 40° to 120°. The left neglected target appears on the left, and the right neglected target is the opposite. The formal training is 50 rounds, and the patient needs to turn his head or body to complete the operation.

[0070] In a possible implementation manner, when the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to:

[0071] For the visual search and target elimination training, the patient wearing the virtual reality device is set to be in the central position of the virtual natural scene, and the time for the patient to raise the virtual hand or use the handle to correctly eliminate the ignored side aerial target matrix completely is determined at different difficulty levels, as well as the patient's head rotation degree and hand operation during the visual search and target elimination training.

[0072] In the specific implementation, the visual search and elimination target training is as follows: set up a scene interaction environment, and the patient is in the center of a virtual natural scene. Ignore the target that appears in the side air, and the patient needs to use a virtual hand or handle to eliminate the target. The warm-up session guides the patient to operate correctly, and the formal session records the operation parameters and scores. The warm-up training is a row of 10 targets. The farthest angle of the primary difficulty target is 45°, and the advanced difficulty is 60°. The formal training is three 5×5 target matrices. After each matrix is ​​completely eliminated, enter the next one, and the matrix position deviates 10° away from the midline. The angle range of the primary difficulty is 25°~45°, and the advanced difficulty is 40°~60°.

[0073] For the advanced sustained attention reaction training, the patient wearing the virtual reality device is placed on a high platform in the center of a virtual natural scene, and the number of times the patient raises his virtual hand or uses the handle to correctly defend against a target flying out of the bushes at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the advanced sustained attention reaction training.

[0074] In a specific embodiment, the advanced sustained attention reaction training is as follows: a scene interaction environment is set up, and the patient is on a high platform in the center of a virtual natural scene with a row of bushes in front of him. When the prompt sound is heard, a target randomly flies out of the bushes, and the patient needs to block the target with a virtual hand or handle. The warm-up session guides the patient to operate correctly, and the formal session records the operating parameters and scores. The primary difficulty warm-up training is 4 rounds, the formal training is 80 rounds, and the maximum angle of the target flying out is 90°; the advanced difficulty warm-up is 8 rounds, the formal training is 80 rounds, and the maximum angle of the target flying out is 120°. If the target is blocked correctly three times in a row in the game, the speed will increase next time; if it is not blocked three times in a row, the speed will decrease.

[0075] In a possible implementation manner, when the data analysis module 150 is used to perform data analysis on the action data to generate a visual chart, the data analysis module 150 is specifically used to:

[0076] Data analysis is performed on the game completion degree, average operation reaction time, operation accuracy, maximum head rotation range, and arm lifting and extension range in the action data to generate a visual chart.

[0077] Here, statistical analysis is performed based on the motion data collected during the task training process. The motion data includes the overall game completion, average operation reaction time, operation accuracy, maximum head rotation range and arm lift and extension range, and visual charts are generated based on this.

[0078] In the present application, through the visual and auditory feedback in the virtual reality environment, the scene of the real world can be simulated to reduce the discomfort caused by visual deviation. In addition, through virtual reality technology, patients can be trained in a richer and more dynamic environment, which helps to improve the patient's participation and interest. Through virtual reality technology, patients can complete training tasks independently under the guidance of a doctor. This autonomous training helps to improve the patient's self-management ability. At the same time, the real-time feedback and adjustment mechanism provided by the system enables patients to understand the effect of their training in a timely manner, so that they are more motivated to carry out self-rehabilitation. Since the present invention reduces the direct dependence on therapists, doctors can devote more time and energy to the evaluation of patients and the formulation of training plans, rather than daily training supervision. This allows medical resources to be more focused on the diagnosis of patients and the optimization of treatment strategies.

[0079] For further information, see Figure 3 , Figure 3 This is an interactive schematic diagram of a rehabilitation training system for spatial neglect provided in an embodiment of the present application. Figure 3 As shown, the information management module is used by the doctor to input the basic information of the patient, including name, gender, age, course of disease, dominant hand, spatial neglect side, severity, training status, etc. The training control module is used to monitor the completion of the patient's task training through the monitor on the doctor's side, to start, pause and terminate the task, and to adjust the difficulty of the task. The calibration and training module is used by the patient to guide the patient to complete the cognitive interaction tasks under different virtual reality conditions through the screen and voice prompts of the virtual reality glasses. The data acquisition module is used by the patient to collect the task completion status, head rotation angle and arm extension range of the patient's task training process through the handle / virtual gesture recognition sensor and head motion sensor of the virtual reality glasses; the data analysis module is used to analyze and extract the collected data to obtain the visual charts of the game completion, operation speed, operation accuracy, head rotation degree and hand operation status under each task training. The report feedback module is used to analyze and feedback the completion status of the patient's training tasks based on the data in the above-mentioned visual charts, and the doctor evaluates the training effect and adjusts the difficulty of the next training.

[0080] An embodiment of the present application provides a rehabilitation training system for spatial neglect, the rehabilitation training system comprising an information management module, a training control module, a calibration and training module, a data acquisition module, a data analysis module and a report feedback module, wherein the training control module is respectively communicated with the information management module and the calibration and training module, the data acquisition module is respectively communicated with the calibration and training module and the data analysis module, and the report feedback module is communicated with the data analysis module; wherein the information management module is used to obtain the patient file information entered by the doctor; the training control module is used to receive the task parameters of the rehabilitation training plan for the patient determined based on the patient file information sent by the information management module, send the task parameters of the rehabilitation training plan to the calibration and training module, and receive the training situation sent by the calibration and training module in real time, and adjust the task parameters of the rehabilitation training plan in real time based on the training situation; the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan. , sending a data collection instruction to the data collection module, and determining the training status of the patient during the cognitive interaction task training; wherein the cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, visual search and elimination target training, and advanced sustained attention reaction training; the data collection module is used to collect the patient's action data in real time during the cognitive interaction task training after receiving the data collection instruction, and send the action data to the data analysis module; the data analysis module is used to analyze the action data and generate a visualization chart; wherein the visualization chart includes the patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status under different cognitive interaction task training; the report feedback module is used to analyze the patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status in the visualization chart, determine the task parameters of the patient's next rehabilitation training plan, and combine the results of the data analysis during the patient's game and the patient's basic information, and feedback to the patient and the doctor. The use of automated data collection and analysis improves training efficiency. The data analysis module converts data into visual charts, providing doctors with a quantitative training effect evaluation tool to improve the accuracy of the evaluation. It allows doctors to observe the patient's training performance in real time and adjust the training difficulty or terminate the training as needed. This real-time feedback mechanism ensures the safety and effectiveness of the training.

[0081] See also Figure 3 , Figure 3 A flowchart of a spatial neglect rehabilitation training provided by an embodiment of the present application. Figure 3As shown in , the rehabilitation training method provided in the embodiment of the present application includes:

[0082] S301: Determine task parameters of the patient's rehabilitation training plan based on the patient's file information.

[0083] In this step, the task parameters of the patient's rehabilitation training plan are determined based on the patient's file information.

[0084] S302: Controlling the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, and determining the training status and motion data of the patient during the cognitive interaction task training.

[0085] In this step, the patient is controlled to complete cognitive interaction task training under different virtual reality conditions according to the task parameters of the rehabilitation training plan, and the training status and movement data of the patient during the cognitive interaction task training are determined.

[0086] The cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, visual search and elimination target training, and advanced sustained attention reaction training.

[0087] S303: Adjusting the task parameters of the rehabilitation training plan in real time based on the training situation, and performing data analysis on the motion data to generate a visual chart.

[0088] In this step, the task parameters of the rehabilitation training plan are adjusted in real time according to the training situation, and the motion data are analyzed to generate visual charts.

[0089] S304: Analyze the game completion, operation speed, operation accuracy, head rotation degree and hand operation of the patient in the visualization chart, determine the task parameters of the patient's next rehabilitation training plan, and combine the results of the data analysis during the patient's game and the patient's basic information to provide feedback to the patient and the doctor.

[0090] In this step, the patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status in the visualization chart are analyzed to determine the task parameters of the patient's next rehabilitation training plan. The results of the data analysis during the patient's game and the patient's basic information are combined and fed back to the patient and doctor.

[0091] In a specific embodiment, the doctor enters the patient's basic information, including name, gender, age, course of disease, severity, dominant hand, spatial neglect side, etc., through the doctor-side program, establishes a patient file, and formulates a rehabilitation training plan according to the severity of the patient's spatial neglect; the patient wears a virtual reality device, sits on a chair in a safe area, and pairs the virtual reality device with the doctor-side program through the patient-side program. Multiple virtual reality devices can be paired with the same doctor-side program; task training is started according to the rehabilitation training plan formulated by the doctor for the patient, including selecting simple or difficult task difficulty, left-hand operation or right-hand operation, handle controller operation or gesture recognition operation, and which training task combinations. The completion status and basic task parameters of the patient's task training are recorded, including task completion, game duration, operation reaction time, left and right rotation angle of the head, and whether the hands are raised and lowered; the doctor monitors the real-time status of the patient's task training through the monitor, and identifies whether the current task difficulty matches the patient's ability based on the patient's operation performance. If there is a mismatch, the task training is terminated in time and the difficulty is adjusted. In addition, the task training can be temporarily suspended or terminated according to the patient's wishes; statistical analysis is performed based on the parameters collected during the task training, including the overall game completion, average operation reaction time, operation accuracy, maximum head rotation range and arm lifting and extension range, and visual charts are generated accordingly; based on the generated visual charts and further statistical analysis, including the completion rate, error rate and correction ability within the specified time, training adaptability indicators, long-term rehabilitation trend judgment, and comprehensive scoring system, combined with the patient's actual performance in the task, a feedback report on the current task is generated, and the doctor evaluates the training effect and appropriately adjusts the subsequent training plan.

[0092] Furthermore, based on the training situation, the task parameters of the rehabilitation training plan are adjusted in real time, including:

[0093] Determining whether the current task difficulty among the task parameters matches the ability of the patient based on the training situation;

[0094] If so, controlling the patient wearing the virtual reality device to continue training based on the task parameters of the rehabilitation training plan;

[0095] If not, the rehabilitation training program is terminated and the difficulty of the current task is adjusted.

[0096] Furthermore, before controlling the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the rehabilitation training method further includes:

[0097] The patient is controlled to interact with the interactive device based on the mirror operation teaching and voice prompt learning of wearing the virtual reality device, so as to complete the calibration training and determine the maximum range of the patient's head rotation and the maximum range of the arm extension; wherein the interaction method includes the interaction method of raising the left hand and the right hand during virtual gestures, the interaction method of clicking the button with the left hand and the right hand when using the handle controller, and the interaction method of rotating the head to the left and to the right.

[0098] Furthermore, for the virtual reality prism adaptation training, cognitive interaction task training under different virtual reality conditions is completed based on the task parameters of the rehabilitation training plan, including:

[0099] The patient wearing the virtual reality device is set to be in the central position of a virtual natural scene, and the number of times the patient raises his virtual hand or uses a handle to correctly click on a target that appears randomly in front of the field of vision at different difficulty levels, as well as the patient's hand operation during the virtual reality prism adaptation training, are determined.

[0100] Furthermore, for the head and body rotation training, the cognitive interaction task training under different virtual reality conditions is completed based on the task parameters of the rehabilitation training plan, including:

[0101] The patient wearing the virtual reality device is placed in the center of a virtual natural scene, and the number of times the patient raises a virtual hand or uses a handle to correctly move an object to a target on the neglected side at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the head and torso rotation training.

[0102] Further, controlling the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan includes:

[0103] For the visual search and target elimination training, the patient wearing the virtual reality device is set to be in the central position of the virtual natural scene, and the time for the patient to raise the virtual hand or use the handle to completely eliminate the ignored side aerial target matrix correctly under different difficulty levels is determined, as well as the patient's head rotation degree and hand operation during the visual search and target elimination training;

[0104] For the advanced sustained attention reaction training, the patient wearing the virtual reality device is placed on a high platform in the center of a virtual natural scene, and the number of times the patient raises his virtual hand or uses the handle to correctly defend against a target flying out of the bushes at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the advanced sustained attention reaction training.

[0105] Furthermore, the action data is analyzed to generate a visual chart, including:

[0106] Data analysis is performed on the game completion degree, average operation reaction time, operation accuracy, maximum head rotation range, and arm lifting and extension range in the action data to generate a visual chart.

[0107] A rehabilitation training method for spatial neglect provided in an embodiment of the present application comprises: determining task parameters of a rehabilitation training plan for a patient based on patient file information; controlling the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, and determining the training situation and motion data of the patient during the cognitive interaction task training; wherein the cognitive interaction task training comprises virtual reality prism adaptation training, head and body rotation training, visual search and target elimination training, and advanced sustained attention reaction training; adjusting the task parameters of the rehabilitation training plan in real time based on the training situation, and performing data analysis on the motion data to generate a visualization chart, analyzing the patient's game completion, operation speed, operation accuracy, head rotation degree, and hand operation situation in the visualization chart, determining the task parameters of the patient's next rehabilitation training plan, and providing feedback to the patient and doctor based on the results of the data analysis during the patient's game and the patient's basic information. The use of automated data collection and analysis improves training efficiency. The data analysis module converts data into visual charts, providing doctors with a quantitative training effect evaluation tool, improving the accuracy of the evaluation, and allowing doctors to observe the patient's training performance in real time, and adjust the training difficulty or terminate the training as needed. This real-time feedback mechanism ensures the safety and effectiveness of the training.

[0108] See also Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 4 As shown in , the electronic device 400 includes a processor 410 , a memory 420 and a bus 430 .

[0109] The memory 420 stores machine-readable instructions executable by the processor 410. When the electronic device 400 is running, the processor 410 communicates with the memory 420 via the bus 430. When the machine-readable instructions are executed by the processor 410, the above-mentioned Figure 4 The steps of the rehabilitation training method for spatial neglect in the method embodiment shown in the figure, and the specific implementation methods can be found in the method embodiment, which will not be described in detail here.

[0110] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figure 4 The steps of the rehabilitation training method for spatial neglect in the method embodiment shown in the figure, and the specific implementation methods can be found in the method embodiment, which will not be described in detail here.

[0111] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0112] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0113] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0114] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0115] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0116] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A rehabilitation training system for spatial neglect, It is characterized in that The rehabilitation training system includes an information management module, a training control module, a calibration and training module, a data acquisition module, a data analysis module and a report feedback module. The training control module is respectively connected to the information management module and the calibration and training module in communication, the data acquisition module is respectively connected to the calibration and training module and the data analysis module in communication, and the report feedback module is connected to the data analysis module in communication; wherein, The information management module is used to obtain the patient file information entered by the doctor; The training control module is used to receive the patient file information sent by the information management module, determine the task parameters of the patient's rehabilitation training plan based on the patient file information, send the task parameters of the rehabilitation training plan to the calibration and training module, and receive the training situation sent by the calibration and training module in real time, and adjust the task parameters of the rehabilitation training plan in real time based on the training situation; The calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, send data collection instructions to the data collection module, and determine the training status of the patient during the cognitive interaction task training; wherein the cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, visual search target elimination training, and advanced sustained attention reaction training; The data acquisition module is used to collect the patient's motion data in real time during the cognitive interaction task training after receiving the data acquisition instruction, and send the task execution to the data analysis module; The data analysis module is used to perform data analysis on the motion data to generate a visualization chart; wherein the visualization chart includes the game completion degree, operation speed, operation accuracy, head rotation degree and hand operation status of the patient under different cognitive interaction task training; The report feedback module is used to analyze the game completion, operation speed, operation accuracy, head rotation degree and hand operation of the patient in the visualization chart, determine the task parameters of the patient's next rehabilitation training plan, and combine the results of data analysis during the patient's game process and the patient's basic information to provide feedback to the patient and doctor.

2. The rehabilitation training system according to claim 1, It is characterized in that When the training control module is used to adjust the task parameters of the rehabilitation training plan in real time based on the training situation, the training control module is specifically used to: Determining whether the current task difficulty among the task parameters matches the ability of the patient based on the training situation; If so, controlling the patient wearing the virtual reality device to continue training based on the task parameters of the rehabilitation training plan; If not, the rehabilitation training program is terminated and the difficulty of the current task is adjusted.

3. The rehabilitation training system according to claim 1, It is characterized in that Before the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is also used to: The patient is controlled to interact with the interactive device based on the mirror operation teaching and voice prompt learning of wearing the virtual reality device, so as to complete the calibration training and determine the maximum range of the patient's head rotation and the maximum range of the arm extension; wherein the interaction method includes the interaction method of raising the left hand and the right hand during virtual gestures, the interaction method of clicking the button with the left hand and the right hand when using the handle controller, and the interaction method of rotating the head to the left and to the right.

4. The rehabilitation training system according to claim 1, It is characterized in that With respect to the virtual reality prism adaptation training, when the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to: The patient wearing the virtual reality device is set to be in the central position of a virtual natural scene, and the number of times the patient raises his virtual hand or uses a handle to correctly click on a target that appears randomly in front of the field of vision at different difficulty levels, as well as the patient's hand operation during the virtual reality prism adaptation training, are determined.

5. The rehabilitation training system according to claim 1, It is characterized in that With respect to the head and torso rotation training, when the calibration and training module is used to control the patient wearing the virtual reality device to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to: The patient wearing the virtual reality device is placed in the center of a virtual natural scene, and the number of times the patient raises a virtual hand or uses a handle to correctly move an object to a target on the neglected side at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the head and torso rotation training.

6. The rehabilitation training system according to claim 1, It is characterized in that When the calibration and training module is used to control the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, the calibration and training module is specifically used to: For the visual search and target elimination training, the patient wearing the virtual reality device is set to be in the central position of the virtual natural scene, and the time for the patient to raise the virtual hand or use the handle to completely eliminate the ignored side aerial target matrix correctly under different difficulty levels is determined, as well as the patient's head rotation degree and hand operation during the visual search and target elimination training; For the advanced sustained attention reaction training, the patient wearing the virtual reality device is placed on a high platform in the center of a virtual natural scene, and the number of times the patient raises his virtual hand or uses the handle to correctly defend against a target flying out of the bushes at different difficulty levels is determined, as well as the degree of head rotation and hand operation of the patient during the advanced sustained attention reaction training.

7. The rehabilitation training system according to claim 1, It is characterized in that When the data analysis module is used to perform data analysis on the action data to generate a visual chart, the data analysis module is specifically used to: Data analysis is performed on the game completion degree, average operation reaction time, operation accuracy, maximum head rotation range, and arm lifting and extension range in the action data to generate a visual chart.

8. A rehabilitation training method for spatial neglect. It is characterized in that The rehabilitation training method is applied to the rehabilitation training system for spatial neglect according to any one of claims 1 to 7, and the rehabilitation training method comprises: Determine the task parameters of the patient's rehabilitation training plan based on the patient's file information; Controlling the patient to complete cognitive interaction task training under different virtual reality conditions based on the task parameters of the rehabilitation training plan, and determining the training status and motion data of the patient during the cognitive interaction task training; wherein the cognitive interaction task training includes virtual reality prism adaptation training, head and body rotation training, visual search and elimination target training, and advanced sustained attention reaction training; Based on the training situation, the task parameters of the rehabilitation training plan are adjusted in real time, and the action data are analyzed to generate a visual chart; The patient's game completion, operation speed, operation accuracy, head rotation degree and hand operation status in the visualization chart are analyzed to determine the task parameters of the patient's next rehabilitation training plan, and the results of the data analysis during the patient's game and the patient's basic information are combined to provide feedback to the patient and doctor.

9. An electronic device, It is characterized in that include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the rehabilitation training method for spatial neglect as described in claim 8.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the rehabilitation training method for spatial neglect as claimed in claim 8 are executed.

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