Brain-computer interface stimulation display method and system based on ar glasses

Abstract

The present application relates to the field of brain-computer interface and augmented reality technology, in particular to a brain-computer interface stimulation display method and system based on AR glasses. The method first scans the surrounding environment in real time through the environment perception module of the AR glasses, identifies the natural motion stimulus source in the environment, and the natural motion stimulus source is a periodic motion object existing in reality. Then, in response to the user's interactive intention, it is judged whether there is a usable natural motion stimulus source in the current field of view. Preferentially use the periodically moving object naturally existing in the environment as the stimulus source. Only when there is no available natural motion stimulus source in the environment, the system will enable a virtual flickering stimulus source as a backup. These two interaction modes make the user face real physical motion for part of the time in daily use, rather than artificial flickering interface, which fundamentally reduces visual fatigue and improves the comfort of long-term wear and use.

Description

Technical Field

[0001] This invention relates to the fields of brain-computer interface and augmented reality technology, and more specifically, to a brain-computer interface stimulation display method and system based on AR glasses. Background Technology

[0002] Brain-computer interface (BCI) technology enables direct communication between the human brain and external devices by decoding brain neural activity, and has broad application prospects in fields such as medical rehabilitation, intelligent control, and human-computer interaction. Among them, BCI based on steady-state visual evoked potentials (SSVEP) has become a research hotspot in the field of non-invasive BCI due to its advantages such as high information transmission rate, short training time, and no need for complex equipment.

[0003] Steady-state visual evoked potentials (SSVEPs) refer to the periodic electrophysiological responses generated in the visual cortex of the brain when the human eye fixates on a visual stimulus that flashes at a fixed frequency, consistent with that flashing frequency and its harmonic frequencies. By detecting this specific frequency of EEG signals, the system can infer which stimulus the user is looking at, thereby recognizing the user's intention. Traditional SSVEP systems typically present multiple flashing blocks of different frequencies on a computer screen or a dedicated stimulator, and the user issues commands by looking at the corresponding flashing block.

[0004] In recent years, with the development of augmented reality (AR) technology, combining the SSVEP brain-computer interface with AR glasses has become a new research trend. By rendering virtual flashing stimuli in AR glasses, the control interface of the brain-computer interface can be seamlessly overlaid into the real world, achieving a more natural and intuitive interactive experience. For example, users can see flashing virtual buttons in the AR field of view and control smart home devices, robotic arms, or perform text input by looking at these buttons.

[0005] However, existing SSVEP stimulus display methods based on AR glasses have the following drawbacks: First, visual fatigue is a significant problem. SSVEP technology relies on high-frequency flickering stimulation to induce brain signals, requiring users to stare at a rapidly flashing light source for extended periods. This continuous flickering stimulation easily leads to visual fatigue, dry eyes, headaches, and other discomfort. Visual fatigue not only affects the user experience but also degrades the quality of brain signals, reduces the system's recognition accuracy, and limits the long-term practical application of brain-computer interfaces.

[0006] Second, artificial stimuli undermine the immersive experience of augmented reality. Existing solutions require the continuous rendering of numerous flashing virtual buttons or icons within the AR field of view. These flashing artificial light sources clash with the real environment, causing severe visual pollution. The user's field of vision is filled with flashing light spots, undermining the core concept of "virtual-real integration" in augmented reality and reducing immersion and naturalness.

[0007] Therefore, how to provide an AR brain-computer interface stimulation display method that can make full use of environmental resources, reduce dependence on artificial stimuli, and improve user experience and adaptability has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0008] The purpose of this invention is to provide a brain-computer interface stimulation display method and system based on AR glasses. By prioritizing the use of naturally moving objects in the environment as stimulation sources and only activating virtual flashing stimulation sources when necessary, it solves the problems mentioned in the background art, namely, the significant problem of visual fatigue and the problem of artificial stimulation destroying the immersive feeling of augmented reality.

[0009] To achieve the above objectives, one objective of this invention is to provide a brain-computer interface stimulation-based display method based on AR glasses, comprising the following steps: S1. The AR glasses' environmental perception module scans the surrounding environment in real time and identifies natural motion stimuli in the environment, wherein the natural motion stimuli are periodically moving objects that exist in reality. S2. In response to the user's interaction intent, determine whether there are available natural motion stimuli in the current field of vision; S3. If a usable natural motion stimulus source exists, the first interaction mode is activated: on the display interface of the AR glasses, a visual guidance mark is rendered near the natural motion stimulus source to guide the user to look at the natural motion stimulus source; the EEG signal of the user looking at the natural motion stimulus source is collected, and the EEG signal is decoded with reference to the motion frequency of the natural motion stimulus source. S4. If no available natural motion stimulus source exists, the second interaction mode is activated: a virtual flashing stimulus source is rendered on the display interface of the AR glasses, the EEG signal of the user when looking at the virtual flashing stimulus source is collected, and the EEG signal is decoded with a preset flashing frequency as a reference.

[0010] The second objective of this invention is to provide a system for a brain-computer interface stimulation-based display method based on AR glasses, including... AR display module, used to render virtual images in the user's field of vision; An environmental perception module is used to scan the surrounding environment in real time and identify natural motion stimuli in the environment, wherein the natural motion stimuli are real-world periodically moving objects. The EEG acquisition module is used to acquire the user's EEG signals; The eye-tracking module is used to obtain the coordinates of the user's gaze point in real time; Processing unit, used to perform the following operations: In response to the user's interaction intent, determine whether there are available natural motion stimuli in the current field of vision; If present, the AR display module is controlled to render visual guidance markers near the natural motion stimulus source to guide the user to look at the natural motion stimulus source; the EEG acquisition module is controlled to acquire the EEG signal when the user looks at the source and decode it with the motion frequency of the natural motion stimulus source as a reference. If it does not exist, the AR display module is controlled to render a virtual flashing stimulus source, and the EEG acquisition module is controlled to acquire the EEG signal when the user looks at the virtual flashing stimulus source, and decode it with a preset flashing frequency as a reference.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. In this brain-computer interface stimulation-based display method and system based on AR glasses, naturally occurring periodic moving objects in the environment are prioritized as stimulation sources. These natural movements conform to the physiological characteristics formed by the human visual system during evolution, and their visual comfort is far superior to artificial flickering stimuli. Only when there are no available natural movement stimulation sources in the environment will the system activate virtual flickering stimulation sources as backup. These two interaction modes ensure that users spend a portion of their daily use facing real physical movement, rather than an artificial flickering interface, fundamentally reducing visual fatigue and improving the comfort of prolonged wear.

[0012] 2. In this brain-computer interface stimulation-based display method and system based on AR glasses, in the first interaction mode, static visual guidance markers are rendered only near the identified naturally moving objects. These markers are semi-transparent, low-contrast, and do not contain any periodic flickering or movement, so they will not interfere with the user's vision. The user will only briefly notice these markers when interaction is required, and they are not easily noticed at other times.

[0013] At the same time, the natural moving objects themselves serve as the interactive medium, allowing users to focus on the physical motion in the real world rather than artificial virtual patterns, making the interaction process more natural and intuitive. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating the overall method of the present invention; Figure 2 This is a schematic diagram illustrating the user's state in this invention. Figure 1 ; Figure 3 This is a schematic diagram illustrating the user's state in this invention. Figure 2 ; Figure 4 This is a schematic diagram illustrating the user's state in this invention. Figure 3 . Detailed Implementation

[0015] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] Combining brain-computer interface (BCI) technology with AR glasses has given BCI systems unprecedented portability, allowing users to wear them for extended periods in various everyday scenarios, including indoors and outdoors. In a typical application scenario, when a user needs to control a device, they simply look at the device, and the AR glasses will display several virtual buttons flashing at different frequencies. By looking at the corresponding virtual buttons, the system can decode the user's control intention based on the collected EEG signals, thereby controlling the device.

[0017] However, precisely because the improved portability allows users to wear them for extended periods, to avoid the visual fatigue caused by relying on high-frequency flashing virtual buttons in traditional solutions, this invention provides a brain-computer interface-based stimulation-based display method for AR glasses, such as... Figure 1 As shown, the method includes the following steps: S1. The AR glasses' environmental perception module scans the surrounding environment in real time and identifies natural motion stimuli in the environment. These natural motion stimuli are periodically moving objects that exist in reality. S2. In response to the user's interaction intent, determine whether there are available natural motion stimuli in the current field of vision; S3. If a usable natural motion stimulus source exists, the first interaction mode is activated: on the display interface of the AR glasses, a visual guidance mark is rendered near the natural motion stimulus source to guide the user to look at the natural motion stimulus source; the EEG signal of the user when looking at the natural motion stimulus source is collected, and the EEG signal is decoded with reference to the motion frequency of the natural motion stimulus source. S4. If no available natural motion stimulus is available, activate the second interaction mode: render a virtual flashing stimulus on the AR glasses' display interface, collect the EEG signal when the user looks at the virtual flashing stimulus, and decode the EEG signal with a preset flashing frequency as a reference.

[0018] The above method prioritizes using naturally occurring periodically moving objects in the environment as stimulus sources, replacing some of the artificial flickering stimuli that would otherwise need to be generated by the system. Studies have shown that periodic movements commonly found in nature—such as rotating fan blades, oscillating pendulums, and flowing water waves—can also induce stable visual evoked potentials in the brain's visual cortex, namely steady-state motion visual evoked potentials (SSMVEP). By combining natural motion stimuli with traditional virtual flickering stimuli, this invention can significantly reduce the time users are exposed to high-frequency flickering stimuli while ensuring system usability, thereby effectively alleviating visual fatigue and improving comfort during prolonged use.

[0019] The various steps of this invention will be described in detail below.

[0020] When a user wears a brain-computer interface device, the portability of AR glasses allows for free movement, such as walking around different areas indoors. During this time, the user can come into contact with various objects, some of which are in motion. Therefore, this invention first identifies whether this motion can induce stable visual evoked potentials in the visual cortex of the brain. The specific identification method is as follows: First, while the user is wearing the brain-computer interface device, the processing unit controls the environmental perception module to continuously collect image sequences of the surrounding environment.

[0021] Subsequently, the Farneback dense optical flow algorithm is applied to consecutive frames of images to calculate the motion vector for each pixel. Specifically, for two adjacent frames... and By solving the optical flow constraint equations, the motion vector of each pixel is obtained. ,in, For horizontal motion components, This represents the vertical motion component. Motion amplitude. .Will Pixels larger than a first threshold (e.g., 2 pixels) are marked as moving pixels.

[0022] Connectivity analysis is performed on moving pixels, and the eight-neighbor connectivity criterion is used to aggregate adjacent moving pixels into candidate motion regions. Each candidate region... It contains a set of spatially adjacent moving pixels and their motion vectors.

[0023] Taking a real-world scenario as an example: In a living room image, the fan blade area exhibits significant motion due to rotation. The motion amplitude of pixels in this area is generally between 5 and 8 pixels, exceeding the threshold, and is therefore marked as moving pixels. Meanwhile, stationary areas such as the walls and sofa have motion amplitudes close to 0 and are not marked. Therefore, in this example, the area containing the fan blades is extracted as a candidate region, denoted as […]. .

[0024] Next, the motion frequency is extracted for each candidate motion region. The visual features of the region are extracted as a sequence of changes over time. In this embodiment, the average brightness value within the region is extracted as a feature. Let the region be... shared within The pixel, the The average brightness of the frame is: ,in ; A timing signal is obtained by continuously acquiring a brightness sequence over a preset time period (e.g., 3 seconds). .right Preprocessing is performed: the mean is subtracted to eliminate the DC component, and a Hanning window is applied to reduce spectral leakage. Then, a Fast Fourier Transform is performed to obtain the spectrum. .

[0025] Search for spectral peaks within the frequency range of 1Hz to 30Hz. Let the peak frequency be... In this example, the spectrum is in A significant peak appears at 2.8 Hz, corresponding to the power spectral density. =120 Hz. Calculate adjacent frequency bands ( Hz, excluding Average power spectral density of the Hz guard band =15 Hz. Then the signal-to-noise ratio = =120 / 15=8 (linear value), converted to decibels is... 9.0dB.

[0026] Next, validity verification is performed. When the value exceeds the second threshold (e.g., 3.0, or approximately 4.8 dB), the motion region is determined to have stable periodicity and can be considered a candidate natural motion stimulus. In this example... =8 is much greater than 3.0, which passes periodic verification.

[0027] To further improve reliability, this implementation also employs a target detection algorithm for the region. Semantic recognition is performed. The object category in the region is identified. In this example, the model outputs the category "fan" with a confidence score of 0.95, which exists in the pre-defined list of interactive categories (such as fans, pendulums, air conditioners, etc.). Therefore, this candidate source is retained.

[0028] Thus, the camera pose is estimated in real time using a visual SLAM algorithm combined with IMU data. For each verified moving object, its three-dimensional spatial coordinates are calculated. = Create a data record including: object ID, object category, motion frequency, and signal-to-noise ratio. Spatial coordinates timestamp 2. Contours of the motion region. These records are stored in a list of available natural motion stimuli for use in subsequent steps. The list of natural motion stimuli is dynamically updated with each environmental scan.

[0029] Once a natural motion stimulus is obtained, its availability can be determined when the user requires interaction. In this invention, the interaction intent is preferably triggered by gaze, and the specific triggering method is as follows: First, the eye-tracking module acquires real-time images of the user's eyes. The pupil-corneal reflex method is used to calculate the gaze direction of both eyes, and the coordinates of the fixation point are obtained after fusion. = ,in These are two-dimensional coordinates (in pixels) on the display plane. This represents the estimated gaze depth (in meters). The raw gaze point data was smoothed using a Kalman filter to eliminate eye movement noise.

[0030] Next, the processing unit synchronously acquires the current field-of-view image and identifies the type of object in the image (e.g., fan, television, sofa) using an object detection algorithm. When the gaze point coordinates... When landing on a target object, the interactivity of that target object is assessed. If the target object is not interactive (e.g., a regular sofa), subsequent operations are stopped; if the target object is interactive (e.g., a fan or a television), a gaze timer is started.

[0031] Specifically, when the gaze coordinates are first detected Start the gaze timer when the gaze lands on the target object. The initial value is 0. Subsequently, the gaze coordinates are detected in each consecutive frame. Still on the same target object, gaze timer Increase the time interval by one frame. =1 / 120≈0.0083 seconds). When the gaze timer... When the cumulative time exceeds the preset wake-up time threshold (e.g., 1.5 seconds), it is determined that the gaze has been successfully triggered, and an interaction intent trigger command is generated.

[0032] After generating the interactive intent trigger command, a list of natural motion stimuli is obtained. If a natural motion stimuli are present in the list, the system enters the first interactive mode; otherwise, it enters the second interactive mode.

[0033] In this invention, the first interaction mode refers to the natural interaction mode, and the second interaction mode refers to the human interaction mode.

[0034] The first interaction mode includes the following steps: S31. For objects in the list of natural motion stimuli, generate visual guidance markers on the AR display interface and anchor the markers to a three-dimensional spatial position near the object. These visual guidance markers are rendered statically, meaning the markers themselves do not contain any periodic brightness changes or movement, to avoid inducing additional EEG signal interference.

[0035] The shape of the visual guidance signage adaptively generates an outline based on the shape of the object. A light blue color (RGB:173,216,230) is preferred to create a soft contrast with common environmental colors. The transparency is set to 50% to ensure the signage is visible but not overly obtrusive. The signage is anchored 10cm outside the edge of the object to avoid obscuring the object itself. Additionally, minimalist text prompts such as "fan" or "clock" can be rendered next to the signage.

[0036] S32. Obtain the user's gaze coordinates and determine whether the gaze coordinates fall within the visual guidance mark. If the user's gaze coordinates remain within the visual guidance mark for a period exceeding a preset threshold, it is determined that the user has gazed at the natural motion stimulus.

[0037] S33. Acquire the motion frequency of the natural motion stimulus and collect the user's EEG signal. The collection duration is, for example, 3 seconds. During the collection process, the eye-tracking module continuously verifies whether the user's gaze coordinates remain within the visual guidance marker. If the user leaves the stimulation area midway, the collection is terminated and the user is prompted to re-gaze.

[0038] S34. Generate an ideal reference signal Y based on the motion frequency obtained in S33, denote the EEG signal as X, and obtain the canonical correlation coefficient using the canonical correlation analysis (CCA) method. . The value range is [0,1], which represents the correlation strength between the EEG signal X and the reference signal Y.

[0039] After decoding the EEG signals, when the canonical correlation coefficient... If the value is greater than or equal to the preset threshold, the user's intent is deemed valid, and the currently viewed target object is confirmed as the object controlled by the user's intent; otherwise, the intent is deemed invalid.

[0040] It should be understood that canonical correlation analysis (CCA) is a well-known method in the field and has been widely used in SSVEP and SSVEP EEG decoding.

[0041] Taking a real-world scenario as an example, refer to Figure 2Suppose the user's intention is to turn off the TV. There is a fan near the TV with rotating blades, which are labeled as a natural motion stimulus. When the user looks at the TV, causing the system to enter interactive mode, the system renders a visual guidance icon on the AR glasses, located around the fan blades. An arrow is also rendered to guide the user. When the user looks at the rotating fan blades through the visual guidance icon, the blades induce stable visual evoked potentials in the visual cortex of the brain. Analyzing the correlation between the fan blades' motion frequency and the user's EEG signal, if the correlation meets preset conditions, it can be determined that the user's intention is to turn off the TV.

[0042] In another scenario, such as Figure 3 As shown, assuming the user's intention is to control the fan, the user's gaze at the fan causes the system to enter interactive mode, and visual guidance icons are directly rendered on the outer periphery of the fan blades. At this time, when the user gazes at the rotating fan blades, by analyzing the user's EEG signals, it can be determined that the user's intention is to control the fan to turn off.

[0043] The second interaction mode includes the following steps: S41. Render a virtual control panel on the AR display module. The virtual control panel contains at least one virtual button. Each button blinks at a different preset frequency. The virtual control panel is rendered around the object the user is looking at.

[0044] S42. Collect the user's EEG signals when the user looks at the virtual buttons around the object; S43. Generate a reference signal Y from the flashing frequency of the virtual button, and denote the user's EEG signal as X. Obtain the canonical correlation coefficient using the canonical correlation analysis (CCA) method. . The value range is [0,1], which represents the correlation strength between the EEG signal X and the reference signal Y.

[0045] When the canonical correlation coefficient If the value is greater than or equal to the preset threshold, the user's intent is deemed valid, and the currently viewed target object is confirmed as the object controlled by the user's intent; otherwise, the intent is deemed invalid.

[0046] For example Figure 4 When there are no natural motion stimuli in the surroundings, if the user wants to control the fan, the system will render multiple virtual buttons around the fan. Each virtual button has a different flashing frequency and corresponding function. When the user looks at the virtual button, the system can analyze the user's brain signals to understand the user's intention.

[0047] The second objective of this invention is to provide a system for a brain-computer interface stimulation-based display method based on AR glasses, including... AR display module, used to render virtual images in the user's field of vision; The environmental perception module is used to scan the surrounding environment in real time and identify natural motion stimuli in the environment. Natural motion stimuli are real-world periodically moving objects. The EEG acquisition module is used to acquire the user's EEG signals; The eye-tracking module is used to obtain the coordinates of the user's gaze point in real time; Processing unit, used to perform the following operations: In response to the user's interaction intent, determine whether there are available natural motion stimuli in the current field of vision; If present, the AR display module is controlled to render visual guidance markers near the natural motion stimulus source to guide the user to look at the natural motion stimulus source; the EEG acquisition module is controlled to acquire the EEG signal when the user looks at the source and decode it with the motion frequency of the natural motion stimulus source as a reference. If it does not exist, the AR display module is controlled to render a virtual flashing stimulus source, and the EEG acquisition module is controlled to acquire the EEG signal when the user looks at the virtual flashing stimulus source, and decode it with a preset flashing frequency as a reference.

[0048] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A brain-computer interface stimulation-based display method based on AR glasses, characterized in that: Includes the following steps: S1. The AR glasses' environmental perception module scans the surrounding environment in real time and identifies natural motion stimuli in the environment, wherein the natural motion stimuli are periodically moving objects that exist in reality. S2. In response to the user's interaction intent, determine whether there are available natural motion stimuli in the current field of vision; S3. If a usable natural motion stimulus source exists, the first interaction mode is activated: on the display interface of the AR glasses, a visual guidance mark is rendered near the natural motion stimulus source to guide the user to look at the natural motion stimulus source; the EEG signal of the user looking at the natural motion stimulus source is collected, and the EEG signal is decoded with reference to the motion frequency of the natural motion stimulus source. S4. If no available natural motion stimulus source exists, the second interaction mode is activated: a virtual flashing stimulus source is rendered on the display interface of the AR glasses, the EEG signal of the user when looking at the virtual flashing stimulus source is collected, and the EEG signal is decoded with a preset flashing frequency as a reference.

2. The brain-computer interface stimulation display method based on AR glasses according to claim 1, characterized in that: The identification of natural motion stimuli in S1 includes: S11. Acquire images of the surrounding environment, perform motion detection on consecutive frames, and extract motion regions; S12. Perform time-series signal analysis on the motion region and extract its motion frequency; S13. Calculate the signal-to-noise ratio of the motion frequency. When the signal-to-noise ratio is greater than a preset threshold, determine that the motion region has stable periodicity. S14. Perform semantic recognition on the motion area. When the recognition result is in the preset interactive category list, mark the motion area as a natural motion stimulus source. S15. Calculate the three-dimensional spatial coordinates of the natural motion stimulus source and store them in the list of available natural motion stimulus sources.

3. The brain-computer interface stimulation display method based on AR glasses according to claim 1, characterized in that: The user's interaction intent in S2 is triggered in the following ways: The system identifies the object the user is looking at. When the user's gaze remains on the object for more than a preset threshold, the gaze is considered successfully triggered, and an interaction intent trigger command is generated.

4. The brain-computer interface stimulation display method based on AR glasses according to claim 1, characterized in that: The visual guidance signage in S3 is displayed statically.

5. The brain-computer interface stimulation display method based on AR glasses according to claim 4, characterized in that: S3 further includes: S31. After rendering the visual guidance sign, the eye-tracking module is used to detect whether the user's gaze point is within the area of ​​the visual guidance sign. S32. When the gaze point falls on the visual guidance mark and remains there for more than a preset threshold, it is determined that the user has pre-selected the natural motion stimulus source. S33. Obtain the motion frequency of the pre-selected natural motion stimulus source; S34. When the user's gaze at a natural motion stimulus source continues for more than a preset threshold, EEG signals are collected. S35. Using the motion frequency measured in S33 as a reference, decode the collected EEG signals to obtain the user's intent.

6. The brain-computer interface stimulation display method based on AR glasses according to claim 4, characterized in that: The shape of the visual guidance sign is an outline that is adaptively generated based on the shape of the object.

7. The brain-computer interface stimulation display method based on AR glasses according to claim 1, characterized in that: The virtual flickering stimulus source rendered in S4 includes: A virtual control panel is rendered on the AR glasses display interface. The virtual control panel contains at least one virtual button, and each virtual button flashes at a different preset frequency.

8. The brain-computer interface stimulation display method based on AR glasses according to claim 7, characterized in that: S4 further includes: S41. Detect whether the user's gaze point falls on the virtual button by eye tracking; S42. When the gaze point falls on the virtual button and remains there for more than a preset threshold, collect EEG signals. S43. Using the flashing frequency corresponding to the virtual button as a reference, decode the collected EEG signal to obtain the user's intention.

9. A system for a brain-computer interface stimulation display method based on AR glasses as described in any one of claims 1-8, characterized in that: include AR display module, used to render virtual images in the user's field of vision; An environmental perception module is used to scan the surrounding environment in real time and identify natural motion stimuli in the environment, wherein the natural motion stimuli are real-world periodically moving objects. The EEG acquisition module is used to acquire the user's EEG signals; The eye-tracking module is used to obtain the coordinates of the user's gaze point in real time; Processing unit, used to perform the following operations: In response to the user's interaction intent, determine whether there are available natural motion stimuli in the current field of vision; If present, the AR display module is controlled to render visual guidance markers near the natural motion stimulus source to guide the user to look at the natural motion stimulus source; the EEG acquisition module is controlled to acquire the EEG signal when the user looks at the source and decode it with the motion frequency of the natural motion stimulus source as a reference. If it does not exist, the AR display module is controlled to render a virtual flashing stimulus source, and the EEG acquisition module is controlled to acquire the EEG signal when the user looks at the virtual flashing stimulus source, and decode it with a preset flashing frequency as a reference.

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