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CN-121996945-A - Virtual reality anti-addiction system and method

CN121996945ACN 121996945 ACN121996945 ACN 121996945ACN-121996945-A

Abstract

The invention discloses a virtual reality anti-addiction system and method, wherein the method comprises the steps of loading VR safety parameters corresponding to a target child age group, establishing a personal brain electrical baseline of the target child, synchronously collecting brain electrical data, behavior data and cognitive task data of the target child, carrying out multidimensional addiction risk assessment once by using a multidimensional addiction risk assessment model every first time interval, executing hierarchical intervention measures according to a multidimensional addiction risk assessment result, generating a cognitive development report every second time interval, and iterating the personal brain electrical baseline and the multidimensional addiction risk assessment model based on the cognitive development report. The intelligent cognitive radio system has the remarkable effects that technologies such as nerve monitoring, cognitive development law and VR are fused, and accurate identification, personalized intervention and cognitive promotion are realized through a four-layer closed-loop architecture of data acquisition, data analysis, dynamic intervention and safety monitoring.

Inventors

  • WEI ZHIXIA
  • PENG LIHUA
  • WANG XIUFANG

Assignees

  • 廊坊师范学院

Dates

Publication Date
20260508
Application Date
20251224

Claims (10)

  1. 1. The virtual reality anti-addiction method is characterized by comprising the following steps of: Step 1, loading VR safety parameters corresponding to a target child age group, and establishing a personal brain electricity base line of the target child; step 2, synchronously acquiring brain electrical data, behavior data and cognitive task data of a target child, and performing multi-dimensional addiction risk assessment once by using a multi-dimensional addiction risk assessment model every first time interval; step 3, performing hierarchical intervention measures according to the multidimensional addiction risk assessment result; and 4, generating a cognitive development report at each second time interval, and iterating the personal brain electrical baseline and the multidimensional addiction risk assessment model based on the cognitive development report.
  2. 2. The method for preventing addiction to virtual reality of claim 1 wherein said establishing a personal electroencephalogram baseline comprises: Step 1.1, acquiring the age and cognitive development basis of a target child; Step 1.2, loading brain electricity index normal range, cognitive task library and VR safety parameters of a target child corresponding to an age group; Step 1.3, guiding the child to complete basic electroencephalogram calibration operation of a third duration; and 1.4, establishing a personal brain electrical baseline of the target child according to brain electrical data after calibration operation is completed.
  3. 3. The virtual reality anti-addiction method of claim 1, wherein in step 2, the electroencephalogram data comprises event-related potential P300, N400 components and alpha/theta wave frequency spectrum power ratio, the behavior data comprises head rotation frequency, interactive operation frequency, content type and education/entertainment content duty ratio, and the cognitive task data comprises performance data of a target child when completing a non-interference random embedding task in VR content corresponding to an age group.
  4. 4. The method of claim 3, wherein the electroencephalogram data is collected by an EEG head ring and the behavioral data is collected by a VR device.
  5. 5. The method for preventing addiction to virtual reality of claim 1 wherein said performing a multi-dimensional addiction risk assessment using a multi-dimensional addiction risk assessment model in step 2 specifically comprises: If the calculated value output by the multidimensional addiction risk assessment model is smaller than a first threshold value, judging that the risk is low; if the calculated value output by the multidimensional addiction risk assessment model is larger than a first threshold value and smaller than a second threshold value, judging that the model is middle risk; and if the calculated value output by the multidimensional addiction risk assessment model is larger than the second threshold value, judging that the risk is high.
  6. 6. The method of claim 1, wherein the step 3 of performing a hierarchical intervention based on the multi-dimensional addiction risk assessment results comprises: When the multidimensional addiction risk assessment result is low risk, pushing a natural scene reminder every fourth time interval; When the multidimensional addiction risk assessment result is a stroke risk, forcibly switching to a light VR cognitive training task matched with a cognitive development target, training a fifth duration, and returning to the original VR content after reaching the standard; when the multidimensional addiction risk assessment result is high risk, the VR content is immediately paused and the parent-child interaction task is pushed, and after the completion of the confirmation of parents, the locking of the VR content can be restored or the education VR content can be pushed.
  7. 7. A virtual reality anti-addiction system capable of implementing the method of any one of claims 1-6, comprising: The data acquisition module is used for acquiring brain electricity data, behavior data and cognitive task data of the target child in real time; The data analysis module is used for constructing an individual brain electricity base line based on the age bracket of the target child and carrying out one-time multidimensional addiction risk assessment by utilizing the multidimensional addiction risk assessment model; the dynamic intervention module is used for executing hierarchical intervention measures according to the multidimensional addiction risk assessment result; and the iteration updating module is used for generating a cognitive development report in each second time interval and iterating the personal brain electrical baseline and the multidimensional addiction risk assessment model based on the cognitive development report.
  8. 8. The virtual reality anti-addiction system of claim 7, wherein said data acquisition module comprises: the brain electricity monitoring unit is used for acquiring brain electricity data of a target child when the VR equipment is used by the target child through an EEG head ring; the behavior monitoring unit is used for acquiring behavior data of a target child when the VR device is used by the target child through a sensor arranged in the VR device; And the cognitive task unit is used for completing the cognitive task data when the non-interference random embedded task in the built-in age-divided cognitive task library through the target child.
  9. 9. The virtual reality anti-addiction system of claim 7, wherein said data analysis module comprises: The age bracket adapting unit is used for loading preset parameters according to the age of the target child; The addiction risk assessment unit is used for constructing a multidimensional addiction risk assessment model; the cognitive state analysis unit is used for associating the normal range of the brain electrical indexes, the behavior data and the cognitive task data of the target children corresponding to the age groups and analyzing the current cognitive state of the target children.
  10. 10. The virtual reality anti-addiction system of claim 7, wherein said dynamic intervention module comprises: the scene switching unit is used for triggering natural scene reminding, light cognitive training or parent-child interaction tasks according to the risk level output by the multidimensional addiction risk assessment model; the cognitive training unit is used for matching VR cognitive training content with a cognitive development target; And the parent cooperation unit is used for receiving the child use report, customizing the intervention strategy and completing parent-child interaction tasks in real time.

Description

Virtual reality anti-addiction system and method Technical Field The invention relates to the technical field of digital media intervention of children, in particular to a virtual reality anti-addiction system and method. Background The on-line education shows a diversified teaching mode, so that the time for the child to contact the electronic screen is obviously increased. With the popularity of mobile terminals such as tablet computers and smart phones, more and more children come into contact with electronic screens from the low age stage. Overuse of electronic screen devices may indeed lead to a child developing dependency behavior and profound effects on its cognitive development. The long-term use of electronic screens may affect the development of cognitive functions such as attention, memory, language skills, social skills, etc. of children. Meanwhile, depending on an electronic screen, a series of health problems such as vision problems, sleep disorders, difficulty in emotion adjustment and the like of children can be caused. Therefore, in the digital background of education, how to reasonably utilize electronic screen devices to promote the cognitive development of children and prevent electronic screen dependence from causing negative effects on children has become an important issue to be solved in families, schools and society. Therefore, there is a need for a closed loop anti-addiction system and method that fuses nerve monitoring, cognitive development laws and VR techniques. Disclosure of Invention Aiming at the defects of the prior art, the invention aims to provide a virtual reality anti-addiction system and a virtual reality anti-addiction method, which integrate nerve monitoring, cognition development rules and VR technology, and can realize accurate identification, personalized intervention and cognition promotion through a four-layer closed-loop architecture of data acquisition, data analysis, dynamic intervention and safety monitoring. In order to achieve the above purpose, the invention adopts the following technical scheme: in a first aspect, the invention provides a virtual reality anti-addiction method, which is characterized by comprising the following steps: Step 1, loading VR safety parameters corresponding to a target child age group, and establishing a personal brain electricity base line of the target child; step 2, synchronously acquiring brain electrical data, behavior data and cognitive task data of a target child, and performing multi-dimensional addiction risk assessment once by using a multi-dimensional addiction risk assessment model every first time interval; step 3, performing hierarchical intervention measures according to the multidimensional addiction risk assessment result; and 4, generating a cognitive development report at each second time interval, and iterating the personal brain electrical baseline and the multidimensional addiction risk assessment model based on the cognitive development report. Further, the establishing process of the personal brain electricity base line comprises the following steps: Step 1.1, acquiring the age and cognitive development basis of a target child; Step 1.2, loading brain electricity index normal range, cognitive task library and VR safety parameters of a target child corresponding to an age group; Step 1.3, guiding the child to complete basic electroencephalogram calibration operation of a third duration; and 1.4, establishing a personal brain electrical baseline of the target child according to brain electrical data after calibration operation is completed. Further, in the step 2, the electroencephalogram data comprises event-related potential P300, N400 components and alpha/theta wave frequency spectrum power ratio, the behavior data comprises head rotation frequency, interactive operation frequency, content type and education/entertainment content ratio, and the cognitive task data comprises performance data of a target child when the target child completes a non-interference random embedding task in VR content corresponding to an age group. Further, the electroencephalogram data is collected by an EEG head loop, and the behavioral data is collected by a VR device. Further, in the step 2, performing a multi-dimensional addiction risk assessment by using the multi-dimensional addiction risk assessment model specifically includes: If the calculated value output by the multidimensional addiction risk assessment model is smaller than a first threshold value, judging that the risk is low; if the calculated value output by the multidimensional addiction risk assessment model is larger than a first threshold value and smaller than a second threshold value, judging that the model is middle risk; and if the calculated value output by the multidimensional addiction risk assessment model is larger than the second threshold value, judging that the risk is high. Further, the step 3 of performing the step intervention measure accordi