A dream guiding method and system based on a brain-computer interface

Abstract

The application belongs to the technical field of dream intervention, and discloses a dream guiding method and system based on a brain-computer interface. The brain-computer interface is used to collect brain electrical signals in real time, accurately identify a preset dream period, and play a pre-screened dream stimulation package in the period, that is, a multi-sensory combined data package with strong semantic correlation and related to target memory content is played synchronously with sound and picture until the stimulation is stopped after the rapid eye movement period. The method realizes stable and accurate guidance of dream content, can generate a positive dream corresponding to the target memory as expected, overcomes the defects of strong randomness of traditional olfactory induction, single stimulation dimension of pure music induction, and passive termination of nightmare intervention, and truly achieves customized dream induction, and fully plays the positive role of dreams in memory consolidation and creativity stimulation.

Description

Technical Field

[0001] This invention belongs to the field of dream intervention technology, and in particular relates to a dream guidance method and system based on brain-computer interface. Background Technology

[0002] Modern neuroscience research confirms that dream activity during sleep participates in the clearance of metabolic waste from the brain, the balance regulation of hormones and neurotransmitters, and also undertakes important cognitive functions such as memory consolidation, emotion regulation, and the stimulation of creative thinking. As public demand for sleep health and cognitive enhancement continues to grow, the application value of actively regulating dream content and obtaining emotional and cognitive gains through positive dreams is gradually becoming more prominent; various dream intervention techniques have been developed accordingly. However, current technologies can only achieve rough and simple dream intervention and do not yet have the ability to precisely customize dream content.

[0003] Existing dream intervention techniques are mainly divided into three categories, each with significant technical shortcomings. The first category is olfactory-induced dream technology, which releases specific odors during sleep, utilizing the neural connections between smell and the limbic system (hippocampus, amygdala, etc.) to stimulate memories or emotions in an attempt to induce dreams on the corresponding themes. This technique requires no drug intervention and is simple to operate, but the induced dream content is highly random and unpredictable, with the possibility of inducing negative dreams. It cannot achieve customized dream guidance, and the reliability and stability of the intervention effect are insufficient. The second category is pure music-based dream induction technology based on targeted memory reactivation. This technique artificially establishes a forced association between pure music and target memories during the waking phase, and plays the corresponding pure music during sleep to activate the associated memories and induce dreams. In this technique, the association between sound and memory is artificially forced, fundamentally different from the natural multi-sensory memory associations formed by real experiences. Furthermore, it only applies stimulation through a single auditory channel, lacking key sensory information such as vision, resulting in incomplete stimulation dimensions and difficulty in consistently inducing dream content that meets expectations. The third category is nightmare intervention technology, which identifies nightmare signs by monitoring physiological signals such as heart rate, respiration, and body movement, and then forcibly interrupts the nightmare with stimuli such as alarm sounds and bright lights. This technology can only passively terminate negative dreams and lacks a mechanism to actively implant positive dream content. It cannot leverage the positive effects of dreams on memory consolidation and creativity stimulation, nor can it achieve the induction of customized positive dreams. From a core perspective, existing technologies generally have two key shortcomings: First, the amount of memory cues used to induce dreams is limited, and the association between memory cues and sensory stimuli is artificially constructed, which does not conform to the natural physiological mechanism of memory formation in the brain; second, the accuracy of dream induction is insufficient, and it cannot stably generate the target dream expected by the user.

[0004] It is evident that current technologies have not yet developed a customized dream induction scheme that can accurately identify the dreaming stage of sleep and achieve targeted stimulation based on natural multi-sensory memory cues, and cannot stably and accurately generate dream content corresponding to the target memory. Summary of the Invention

[0005] This invention provides a brain-computer interface-based dream guidance method and system. Using this method and system, a customized dream induction scheme can be formed that can accurately identify the dreaming stage of sleep and achieve targeted stimulation based on natural multi-sensory memory cues. It can stably and accurately generate dream content corresponding to the target memory.

[0006] To achieve the above objectives, the present invention employs the following technical content: A brain-computer interface-based dream guidance method includes: Collect raw electrical signals of the brain state of sleep users; Identifying brain sleep states based on raw electrical signals of the brain; If the brain's sleep state is identified as entering a preset dream stage, which includes the N1 sleep transition period, N2 stage, N3 stage, or REM rapid eye movement stage, a pre-selected dream stimulus package is played to guide the sleep user's dream. The dream stimulus package is a combination data package of sound and images. The synchronously played sound and images can synergistically produce visual and auditory stimulation for the sleep user, and the sound and images have a strong semantic association, both of which are related to the sleep user's target memory content. The system continuously monitors the user's sleep state until the sleep state deviates from the preset dream period, at which point the dream stimulation package is stopped.

[0007] Furthermore, the dream stimulation package is generated based on the original audio and video materials of the sleep user's real experiences, real learning scenarios, or local online videos while awake; the original audio and video materials include one or more of the following: online learning recordings, offline course / meeting records, daily life scene records, records of important life ceremonies, local videos, and online videos; the images and sounds of the original audio and video materials are naturally synchronized and have a strong natural semantic and logical correlation with the sleep user's target memory.

[0008] Furthermore, when playing the dream stimulation package, a low-volume audio output and a dim-brightness screen output are used to provide gentle stimulation to the sleep user at a hypnotic level.

[0009] Furthermore, the method of identifying sleep state based on the original electrical signals of the brain state specifically adopts an identification algorithm that integrates spatial frequency domain feature extraction of convolutional neural network and temporal feature extraction of long short-term memory network. By extracting the spatial frequency domain features and temporal features of the EEG signal, it determines whether the current sleep state has entered the REM sleep stage.

[0010] Furthermore, before collecting the raw electrical signals of the sleep user's brain state, the process also includes: Build a dream-oriented material library, convert the audio and video materials in the dream-oriented material library into corresponding dream stimulus packages and store them; Before falling asleep, select a target dream stimulus package from the dream orientation material library to complete the preset configuration for this dream guidance; Once the user is detected to have woken up, the playback of the dream stimulation package will be stopped and the dream guidance process will end.

[0011] A brain-computer interface-based dream guidance system includes a sleep monitoring module, a main control module, a visual output module, and an auditory output module; The sleep monitoring module is used to collect raw electrical signals of the sleep user's brain state in real time and transmit the signals to the main control module; The main control module is used to receive the raw electrical signals of the brain state and identify the brain sleep state; when the brain sleep state is detected to enter the REM sleep stage, a synchronous playback command is sent to the visual output module and the auditory output module to control the playback of the pre-screened dream stimulation package; when the brain sleep state is detected to leave the REM sleep stage, a stop playback command is sent. The visual output module and the auditory output module are used to synchronously receive playback instructions and output the images and sounds of the dream stimulation package accordingly, so as to generate visual and auditory stimulation for the sleeping user. The dream stimulation package is an audio-visual combination data package, in which the sound and images have a strong semantic correlation and both correspond to the target memory content of the sleeping user.

[0012] Furthermore, the main control module includes a material management unit and a sleep state recognition unit; The material management unit is used to receive audio and video materials uploaded by users, convert the audio and video materials into dream stimulation packages and build a dream-oriented material library, and also supports users to select target dream stimulation packages before falling asleep; The sleep state recognition unit incorporates a recognition algorithm that combines spatial frequency domain extraction from a convolutional neural network with temporal domain extraction from a long short-term memory network, used to identify rapid eye movement (REM) sleep states based on electroencephalogram (EEG) signals.

[0013] Furthermore, the visual output module adopts a flexible display eye mask, configured as a three-layer integrated structure, consisting of a flexible semi-shading fabric layer, a flexible OLED display layer, and a flexible textile outer layer, arranged sequentially from the side closest to the eyelid to the outside; the flexible OLED display layer projects video images toward the inner side of the sleeping user's closed eyelids.

[0014] Furthermore, the sleep monitoring module adopts any one of the following: a consumer-grade EEG monitoring headband, a medical-grade polysomnography system, a sleep monitoring ring, a smart mattress, or a non-contact visual sleep monitoring device, and is connected to the main control module via wired or wireless communication.

[0015] Furthermore, the dream guidance system adopts a head-mounted integrated structure or a mobile terminal external structure; In the integrated head-mounted structure, the visual output module and the auditory output module are integrated on the head-mounted carrier, and are either integrated with the sleep monitoring module or fixedly assembled separately. In the external mobile terminal structure, the visual output module uses the mobile terminal screen, which is fixed above the sleeping user's face by a bracket, so that the weak light image penetrates the closed eyelids to achieve visual stimulation, and the auditory output module uses an external audio device.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This invention provides a brain-computer interface-based dream guidance method. It collects brain electrical signals in real time via the brain-computer interface, accurately identifies preset dream periods, and plays pre-selected dream stimulation packages during these periods—multi-sensory data packages with synchronized sound and visuals, strong semantic associations, and relevance to target memory content—until stimulation ceases after REM sleep. This method utilizes the brain-computer interface to lock onto the dream window during sleep, avoiding the application of ineffective stimulation during non-dreaming stages. Simultaneously, it employs synergistic stimulation through both audiovisual channels, with sound and visuals designed based on natural multi-sensory associations of real memories, rather than artificially forced binding. This better aligns with the physiological mechanisms of memory formation in the brain, enabling the stimulation information to effectively activate target memories and integrate into the dream. This method achieves stable and precise guidance of dream content, generating positive dreams corresponding to target memories as expected. It overcomes the shortcomings of traditional olfactory induction with its strong randomness, pure music induction with its limited stimulation dimensions, and nightmare intervention that can only be passively terminated. It truly achieves customized dream induction, fully leveraging the positive role of dreams in memory consolidation and creativity stimulation.

[0017] This invention provides a brain-computer interface-based dream guidance system. A sleep monitoring module collects brain electrical signals in real time, and a main control module identifies the sleep state. Once REM sleep begins, the system simultaneously instructs the visual and auditory modules to play a pre-screened dream stimulus package—a data packet combining images and sounds with strong semantic association and corresponding to the target memory. The system stops immediately after REM sleep ends. This system uses a brain-computer interface to precisely lock onto the dreaming stage, ensuring that stimulation is only effective within the dream window and avoiding ineffective intervention outside of the dreaming period. It employs dual-channel audiovisual stimulation, with sound and images designed based on natural multi-sensory memory associations rather than artificial binding, better aligning with the physiological mechanisms of memory formation in the brain. This allows the stimulus information to efficiently activate the target memory and integrate into the dream. The system automatically monitors changes in sleep state and stops promptly to prevent interference with subsequent sleep structure. This system achieves precise and stable guidance of dream content, actively implanting positive, customized dreams. It overcomes the shortcomings of existing technologies such as the strong randomness of olfactory induction, the single dimension of pure music stimulation, and the passive termination of nightmare intervention, fully leveraging the positive role of dreams in memory consolidation and creativity stimulation. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of dream selection and storage provided in an embodiment of the present invention; Figure 2 A schematic diagram illustrating the mathematical theme of dream induction provided in this embodiment of the invention; Figure 3 A flowchart illustrating a brain-computer interface-based dream guidance method provided in an embodiment of the present invention; Figure 4 The diagram shows the components of a dream-inducing system provided in an embodiment of the present invention; wherein, (a) is the main control terminal; (b) is the headband; and (c) is the flexible display screen eye mask. Figure 5 This is a schematic diagram illustrating video uploading and dream selection as provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of multi-component collaborative operation provided in an embodiment of the present invention; Figure 7 This is a diagram illustrating the usage of the mobile terminal-type structure provided in an embodiment of the present invention; Figure 8 This is a schematic diagram of a head-mounted structure provided in an embodiment of the present invention; Figure 9 This is a diagram illustrating the usage of the head-mounted structure provided in an embodiment of the present invention.

[0019] Figure label: 1. EEG monitoring headband; 2. Speaker; 3. Flexible display screen eye mask; 4. Family reunion dream stimulation video package; Detailed Implementation To make the technical problems solved by the present invention, the technical solutions, and the beneficial effects clearer, the following specific embodiments provide a further detailed description of the present invention. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of the invention.

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0021] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0022] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0023] The technical terms involved in this invention are explained as follows: REM sleep: one of the sleep cycles in humans, and dreams occur during this cycle.

[0024] Targeted memory reactivation technology refers to a technique that associates specific memory content with specific sensory cues while the person is awake, and then re-presents those sensory cues during sleep, thereby selectively triggering the reactivation and consolidation of the associated memory network.

[0025] Dream stimulation package: refers to a data package containing a combination of sound and images. The sound and images can be a single video or different audio and video files. The audio files and video files (sound and images) are semantically related and are associated with the user's target memory content.

[0026] Good Dream APP: In this invention, it refers to the system control application software installed on the main control terminal, which is used to receive the original video material uploaded by the user and generate dream stimulation packages, receive the EEG signals transmitted by the sleep monitoring device to identify whether the user is currently in the dreaming stage, and send audio and video synchronous playback instructions to the near-eye display device and the auditory output device when it is determined that the user is in the dreaming stage, and record the user's dream feedback the next day to optimize the intervention parameters.

[0027] For example, this embodiment provides a brain-computer interface-based dream guidance system. This system can determine whether a person's current brain state is in a dreaming stage. If so, the system will synchronously play audio and video recordings of things the person has personally learned, experienced, or participated in (low volume and dim lighting, analogous to the language-guided prompting therapy used in hypnotic dream states by psychologists), thereby inducing dreams corresponding to the person's pre-selected video content. This achieves the goal of customized dream creation, from pre-selected video content to the targeted generation of related dreams. Thus, it achieves the goals of memory consolidation, emotion regulation, and creativity stimulation.

[0028] like Figure 1 and Figure 2 As shown in this embodiment, when an external device detects that the brain is in a dreaming state, it starts to play the audio and video synchronously for recorded online courses, videos of meeting friends, or videos of attending weddings, etc., to activate the relevant memories in the brain and make the brain "replay" the preset content in the dream, thereby achieving targeted dream induction.

[0029] Figure 1 In the scenario where users learn mathematics, they record online math lessons they have learned and import them into a mobile app. The app then converts the videos into dream stimulus packages, which are either stored locally or uploaded to a cloud server. Figure 2 In the process, the raw electrical signals of the brain state are uploaded to the Good Dream APP on the mobile phone; the APP uses a recognition algorithm based on the fusion of CNN spatial frequency extraction and LSTM temporal extraction to identify whether the EEG features are REM (Rapid Eye Movement) features, in order to determine whether dreaming can be initiated; when in REM phase, the flexible eye mask and speaker start to play video sound and picture synchronously, thereby inducing the preset dream.

[0030] For example, combined Figure 3 , Figure 5 and Figure 6 As shown, this embodiment provides a dream guidance method based on a brain-computer interface, and the specific steps are as follows: Step 1: Create a dream-oriented material library in the Good Dreams app on your phone. The videos in the material library are the dream stimulation packages.

[0031] Step 2: Before falling asleep, select a dream stimulus package from the dream material library that you want to induce related memories or experiences (in this example, select the dream stimulus package of the wedding video of the person's wedding).

[0032] Step 3: During sleep, the EEG monitoring headband transmits the raw electrical signals of the brain state collected to the Good Dream APP.

[0033] Step 4: The Good Dream app uses algorithms to identify in real time whether the current sleep state is REM (dreaming). If it is determined to be REM (dreaming), the Good Dream app immediately sends instructions to the Bluetooth headphones and flexible sleep mask. If it is determined not to be REM, it continues to monitor the brain's sleep state.

[0034] Step 5: After receiving the instructions from the app, the Bluetooth earphones and flexible sleep mask begin to play the wedding video audio and visuals synchronously. During playback, low volume and dim lighting are used, analogous to the verbal guidance and prompting used in hypnotic dream therapy.

[0035] Step Six: Continue monitoring the brain's sleep state. If the brain's sleep state is still in the REM (dreaming) stage, continue playing audio and video. If the brain's sleep state is not in the REM (dreaming) stage, stop playing audio and video.

[0036] Step 7: Continue monitoring until the user wakes up.

[0037] It should be noted that the dream stimulation package in this embodiment is not limited to specific audio and video content, and can be flexibly configured according to the user's target needs. This includes, but is not limited to, online course videos that the user actually studied during the day, recordings of offline courses / lectures / conferences that the user personally participated in or witnessed, videos of pleasant moments in life recorded by the user or by others (such as travel experiences, family and friends gatherings, important ceremonies, etc.), and real-life scene videos recorded by family and friends at important life occasions such as weddings. The common characteristic of the above materials is that they all originate from the user's real experiences or real learning scenarios during their waking hours, and their visual and audio content are naturally integrated, with a natural, authentic, and strongly correlated semantic and logical connection to the user's target memory.

[0038] To achieve the goal of customized dreams, the dream guidance system provided in this embodiment mainly includes: a sleep monitoring module, a main control module, a visual output module, and an auditory output module. The sleep monitoring module collects raw electrical signals of the sleep user's brain state in real time and transmits the signals to the main control module. The main control module receives the raw electrical signals of the brain state and identifies the sleep state. When the brain sleep state enters the REM (Rapid Eye Movement) stage, it sends a synchronized playback command to the visual and auditory output modules to control the playback of a pre-selected dream stimulus package. When the brain sleep state exits the REM stage, it sends a stop playback command. The visual and auditory output modules synchronously receive the playback command and output the corresponding images and sounds of the dream stimulus package to collaboratively stimulate the sleep user's vision and hearing. The dream stimulus package is a combined audio-visual data package, where the sound and images have a strong semantic correlation and both correspond to the sleep user's target memory content.

[0039] Explainable, the specific hardware composition of this system is as follows: Figure 4 As shown, specifically as follows Figure 4 As shown in (a), (b), and (c), this dream system includes a mobile terminal, a main control terminal, a near-eye display device, an auditory output device, and an external sleep monitoring device. The mobile terminal, near-eye display device, auditory output device, and external sleep monitoring device are electrically or wirelessly connected to the main control terminal, respectively.

[0040] like Figure 4 As shown in (c), the near-eye display device of this system is a three-layer integrated structure of a flexible display eye mask. The display screen projects video images onto the inner side of the closed eyelids. All near-eye display devices, under the control of the main control terminal, execute controlled audio and video synchronous playback based on the rapid eye movement (dreaming) signals provided by the external sleep monitoring device. Specifically, the flexible display eye mask is configured with a three-layer integrated structure, consisting of a flexible semi-opaque fabric layer, a flexible OLED display layer, and a flexible textile outer layer, arranged sequentially from the side closest to the eyelid to the outside. During use, the flexible OLED display layer projects video images towards the inner side of the sleeper's closed eyelids. This structural design of the flexible display eye mask considers both safety to avoid damage to the sleeper's eyes and ensures effective video projection.

[0041] The auditory output devices of this system use Bluetooth headsets. All auditory output devices are controlled by the main control terminal, and execute controlled audio output based on the REM sleep (dreaming) signals provided by external sleep monitoring devices.

[0042] The main control terminal of this system uses a mobile APP. The main control terminal allows people to upload recorded videos and convert them into dream stimulation packages. It also receives raw electrical signals of the brain state and uses a recognition algorithm based on the fusion of CNN spatial frequency extraction and LSTM temporal extraction to determine the current sleep state. When the person is in the REM sleep stage (dreaming), the flexible eye mask and headphones start to play video sound and images synchronously to induce the desired dream.

[0043] The sleep monitoring device in this system uses an EEG monitoring headband, which transmits the raw electrical signals of the brain state to the main control terminal via WiFi connection. The main control terminal uses a recognition algorithm based on the fusion of CNN spatial frequency extraction and LSTM temporal extraction to identify the current sleep state.

[0044] In this embodiment, the specific forms of the near-eye display device and the auditory output device are not limited, nor are the specific types of the external sleep monitoring device limited. The near-eye display device can be a flexible eye mask or a combined structure; the auditory output device can be a near-ear speaker, bone conduction headphones, or Bluetooth headphones; the external sleep monitoring device can be a medical-grade PSG system, a consumer-grade EEG headband, a smart mattress, a sleep monitoring ring, or a non-contact visual monitoring device, specifically divided into the following two structures: like Figure 7 As shown, the near-eye display device and auditory output device adopt a mobile terminal structure. The near-eye display device and auditory output device can each be powered by the user's own devices. The user wears their own headphones (such as wired headphones, Bluetooth headphones, or bone conduction headphones), while a mobile terminal such as a mobile phone or tablet is fixed above the face during sleep using a stand or suspension device. This allows the dim light from the screen to penetrate the closed eyelids and be perceived by the retina. The mobile terminal communicates with the main control terminal via Bluetooth or Wi-Fi, receiving information about the brain's current sleep state (REM, dreaming) and triggering synchronized audio and video playback. In this structure, the user falls asleep while using the head EEG sleep monitoring device. The system determines the current sleep state (REM, dreaming) based on real-time EEG signals and then performs intervention.

[0045] like Figure 8 and Figure 9 As shown, the near-eye display device and auditory output device adopt a head-mounted structure. The near-eye display device and auditory output device can be powered by the user's own devices. The user wears their own headphones (such as wired headphones, Bluetooth headphones, or bone conduction headphones), and mobile terminals such as mobile phones and tablets are fixed above the face during sleep using a bracket or suspension device. This allows the weak light from the screen to penetrate the closed eyelids and be perceived by the retina. The mobile terminal communicates with the main control terminal via Bluetooth or Wi-Fi, and after receiving the brain's current sleep state, such as whether it is in the REM (rapid eye movement) stage (dreaming), it triggers the synchronous playback of audio and video. In this structure, the user falls asleep with the head EEG sleep state monitoring device. The system determines the current sleep state of the brain as REM (dreaming) based on real-time EEG signals and then performs intervention. Specifically, the EEG monitoring headband 1 detects the raw electrical signals of the sleeper's brain state, audio is played through the speaker 2, and video is played through the flexible display eye mask 3; both the audio and video are derived from the family reunion dream stimulation package video 4.

[0046] As can be seen, all users wear EEG sleep monitoring devices to fall asleep. The system accurately determines whether the brain is in the dreaming stage based on real-time EEG signals, and only triggers synchronized audio and video playback when the brain is in the dreaming stage, thereby achieving safe, accurate, and individualized targeted dream induction.

[0047] In summary, compared with dream guidance methods, the dream guidance method and system based on brain-computer interface provided by this invention, for the first time combining brain-computer interface recognition with audio and video self-recording feedback, constitutes a closed-loop brain-computer dream regulation system, which has the following advantages: First, the memory cues are natural and authentic, with extremely strong semantic connections: Existing pure music-based dream induction techniques artificially and mechanically link unrelated musical sounds to memories during waking hours, resulting in rigid and unnatural associations. Olfactory-based dream induction techniques rely entirely on specific odors, lacking a directional connection to the target memory, leading to highly random and unpredictable dreams. This invention uses videos of people's real-life learning, experiences, and participation as dream memory cues. The visuals and audio are naturally integrated with the memory, exhibiting a natural, authentic, and strongly correlated semantic and logical connection with the target memory. Therefore, during REM sleep (dreaming), when reactivating memories, it can precisely induce dreams highly consistent with the original brain memories, making the customized dreams more stable and reliable.

[0048] Secondly, the synchronized audio and video playback is stimulating, making the dream reconstruction more complete: Human memory is formed through the combined experience of multiple senses, with auditory and visual senses being the two most important channels for memory. This invention, in helping people customize and induce dreams and recall memories, employs simultaneous audio-visual dual-modal playback, activating both auditory and visual memory senses simultaneously. This provides the brain with complete sensory information, enabling comprehensive and precise reactivation of memories during REM sleep (dreaming), thereby effectively inducing the desired and customized dreams.

[0049] Third, to achieve customized dream goals and meet individual needs: Existing technologies induce dreams that are either highly random and unpredictable or have very poor effects, failing to help people customize happy and joyful dreams. This invention's system, through a complete chain of "pre-selecting video content → accurately identifying the dreaming stage → synchronously writing audio and video → targeted generation of related dreams," allows people to flexibly choose dream materials according to their own needs (such as online courses, wedding videos, travel experiences, etc.), thereby achieving the customized goal of "dreaming whatever you want." The system no longer uses the same intervention method for different users, but instead constructs targeted dreams based on individual real experiences, exhibiting a high degree of individualization and scene adaptability.

[0050] The above embodiments are merely one of the implementation methods for achieving the technical solution of the present invention. The scope of protection claimed by the present invention is not limited to this embodiment, but also includes any variations, substitutions and other implementation methods that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention.

Claims

1. A dream guidance method based on brain-computer interface, characterized in that, include: Collect raw electrical signals of the brain state of sleep users; Identifying brain sleep states based on raw electrical signals of the brain; If the brain's sleep state is identified as entering a preset dream stage, which includes the N1 sleep transition period, N2 stage, N3 stage, or REM rapid eye movement stage, a pre-selected dream stimulus package is played to guide the sleep user's dream. The dream stimulus package is a combination data package of sound and images. The synchronously played sound and images can synergistically produce visual and auditory stimulation for the sleep user, and the sound and images have a strong semantic association, both of which are related to the sleep user's target memory content. The system continuously monitors the user's sleep state until the sleep state deviates from the preset dream period, at which point the dream stimulation package is stopped.

2. The dream guidance method based on brain-computer interface according to claim 1, characterized in that, The dream stimulation package is generated based on the original audio and video materials of the sleep user's real experiences, real learning scenarios, or local online videos while awake. The original audio and video materials include one or more of the following: online learning recordings, offline course / meeting records, daily life scene records, records of important life ceremonies, local videos, and online videos. The images and sounds of the original audio and video materials are naturally synchronized and have a strong natural semantic and logical correlation with the sleep user's target memory.

3. The dream guidance method based on brain-computer interface according to claim 1, characterized in that, When playing the dream stimulation package, a low-volume audio output and dim-brightness screen output are used to provide gentle stimulation to the sleep user at a hypnotic level.

4. The dream guidance method based on brain-computer interface according to claim 1, characterized in that, The method for identifying sleep states based on raw brain electrical signals specifically employs an identification algorithm that integrates spatial frequency domain feature extraction from convolutional neural networks and temporal feature extraction from long short-term memory networks. By extracting the spatial frequency domain features and temporal features of the EEG signals, it determines whether the current sleep state has entered the rapid eye movement (REM) phase.

5. The dream guidance method based on brain-computer interface according to claim 1, characterized in that, Before collecting raw electrical signals of the sleep user's brain state, the process also includes: Build a dream-oriented material library, convert the audio and video materials in the dream-oriented material library into corresponding dream stimulus packages and store them; Before falling asleep, select a target dream stimulus package from the dream orientation material library to complete the preset configuration for this dream guidance; Once the user is detected to have woken up, the playback of the dream stimulation package will be stopped and the dream guidance process will end.

6. A dream guidance system based on a brain-computer interface, characterized in that, It includes a sleep monitoring module, a main control module, a visual output module, and an auditory output module; The sleep monitoring module is used to collect raw electrical signals of the sleep user's brain state in real time and transmit the signals to the main control module; The main control module is used to receive the raw electrical signals of the brain state and identify the brain sleep state; when the brain sleep state is detected to enter the REM sleep stage, a synchronous playback command is sent to the visual output module and the auditory output module to control the playback of the pre-screened dream stimulation package; when the brain sleep state is detected to leave the REM sleep stage, a stop playback command is sent. The visual output module and the auditory output module are used to synchronously receive playback instructions and output the images and sounds of the dream stimulation package accordingly, so as to generate visual and auditory stimulation for the sleeping user. The dream stimulation package is an audio-visual combination data package, in which the sound and images have a strong semantic correlation and both correspond to the target memory content of the sleeping user.

7. A dream guidance system based on a brain-computer interface according to claim 6, characterized in that, The main control module includes a material management unit and a sleep state recognition unit; The material management unit is used to receive audio and video materials uploaded by users, convert the audio and video materials into dream stimulation packages and build a dream-oriented material library, and also supports users to select target dream stimulation packages before falling asleep; The sleep state recognition unit incorporates a recognition algorithm that combines spatial frequency domain extraction from a convolutional neural network with temporal domain extraction from a long short-term memory network, used to identify rapid eye movement (REM) sleep states based on electroencephalogram (EEG) signals.

8. A dream guidance system based on a brain-computer interface according to claim 6, characterized in that, The visual output module uses a flexible display eye mask, which is configured as a three-layer integrated structure. From the side closest to the eyelid to the outside, it consists of a flexible semi-shading fabric layer, a flexible OLED display layer, and a flexible textile outer layer. The flexible OLED display layer projects video images toward the inner side of the sleeping user's closed eyelids.

9. A dream guidance system based on a brain-computer interface according to claim 6, characterized in that, The sleep monitoring module adopts any one of the following: a consumer-grade EEG monitoring headband, a medical-grade polysomnography system, a sleep monitoring ring, a smart mattress, or a non-contact visual sleep monitoring device, and is connected to the main control module via wired or wireless communication.

10. A dream guidance system based on a brain-computer interface according to claim 6, characterized in that, The dream guidance system adopts either a head-mounted integrated structure or an external mobile terminal structure; In the integrated head-mounted structure, the visual output module and the auditory output module are integrated on the head-mounted carrier, and are either integrated with the sleep monitoring module or fixedly assembled separately. In the external mobile terminal structure, the visual output module uses the mobile terminal screen, which is fixed above the sleeping user's face by a bracket, so that the weak light image penetrates the closed eyelids to achieve visual stimulation, and the auditory output module uses an external audio device.

Images