Intelligent sleep detection and intervention eyeshade system and method combined with brain-computer interface

Abstract

The invention discloses an intelligent sleep detection and intervention eyeshade system and method combined with a brain-computer interface, and belongs to the technical field of sleep detection and intervention. The intelligent sleep detection and intervention eyeshade system comprises a neural signal detection module, a core control module, a bone conduction module and a light stimulation module; the core control module is electrically connected with the neural signal detection module, the bone conduction module and the light stimulation module. Through the neural signal detection module, the system can perform electroencephalogram monitoring on a user and detect a corresponding neural signal of the user, real-time analysis is performed through the core control module based on a brain-computer interface technology to obtain an accurate sleep detection result, personalized sleep detection is provided for the user, and the sleep quality of the user can be improved according to the personalized sleep detection result. And real-time sleep intervention is realized, so that the sleep intervention effect on the user is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of sleep detection and intervention, and specifically relates to an intelligent sleep detection and intervention eye mask system and method combined with a brain-computer interface. Background Art

[0002] In today's fast-paced lifestyle and high-intensity work pressures, sleep disorders and poor sleep quality have become widespread health issues, seriously threatening people's physical and mental health and quality of life. Long-term sleep deprivation or poor sleep quality not only leads to short-term problems such as difficulty concentrating, memory loss, and mood swings, but can also lead to long-term health risks such as cardiovascular disease, metabolic disorders, and a weakened immune system.

[0003] Traditionally, treatments for sleep problems have relied on medications. However, these approaches often come with a series of significant drawbacks. Medication can cause side effects such as headaches, drowsiness, and dependency. Long-term use can also affect the body's natural sleep mechanisms and even lead to drug tolerance, rendering previously effective medications ineffective.

[0004] Meanwhile, a number of sleep-aid products and sleep-tracking devices have emerged on the market. Most of these solutions are based on one-size-fits-all solutions, failing to fully consider individual sleep differences and the real-time dynamics of neural states. These products often lack personalized assessment and intervention strategies, failing to provide precise and effective assistance tailored to the specific needs of individual users.

[0005] While some wearable devices can monitor physiological indicators such as sleep cycles, heart rate, and breathing, providing some data support for sleep quality assessment, they are still insufficient in translating this data into personalized interventions. They often only provide basic sleep recommendations, but are unable to dynamically adjust based on the user's real-time neurological state and sleep stages to achieve more precise intervention effects.

[0006] As mentioned above, how to provide an intelligent sleep detection and intervention eye mask system and method combined with a brain-computer interface that can provide users with personalized intelligent sleep detection and improve the effect of sleep intervention has become an urgent problem to be solved in this field. Summary of the Invention

[0007] The purpose of the present invention is to provide an intelligent sleep detection and intervention eye mask system combined with a brain-computer interface to solve the above-mentioned problems existing in the prior art.

[0008] In order to achieve the above object, the present invention adopts the following technical solutions:

[0009] In a first aspect, the present invention provides an intelligent sleep detection and intervention eye mask system combined with a brain-computer interface, comprising: a neural signal detection module, a core control module, a bone conduction module, and a light stimulation module, wherein the core control module is electrically connected to the neural signal detection module, the bone conduction module, and the light stimulation module, respectively, wherein:

[0010] The neural signal detection module is configured to contact the user's skin to obtain the user's neural signal and send the user's neural signal to the core control module;

[0011] The core control module is configured to receive the user neural signal sent by the neural signal detection module, perform neural signal analysis on the user neural signal to obtain a user sleep detection result, generate a corresponding intervention control signal based on the user sleep detection result, and send the intervention control signal to the bone conduction module and the light stimulation module respectively;

[0012] The bone conduction module is configured to receive the intervention control signal and play sleep intervention noise of different frequencies and volumes to the user according to the intervention control signal;

[0013] The light stimulation module is used to receive the intervention control signal and emit sleep intervention light waves of different wavelengths and different light intensities to the user according to the intervention control signal.

[0014] In one possible design, the neural signal detection module includes a neural signal detection unit and a neural signal preprocessing unit;

[0015] The detection end of the neural signal detection unit is used to contact the skin at the user's forehead or the skin around the eyes and obtain the original user neural signal. The signal output end of the neural signal detection unit is electrically connected to the signal input end of the neural signal preprocessing unit to send the original user neural signal to the neural signal preprocessing unit.

[0016] The neural signal preprocessing unit is used to perform signal preprocessing on the input original user neural signal and generate a user neural signal. The signal output end of the neural signal preprocessing unit is electrically connected to the signal input end of the core control module to send the user neural signal to the core control module.

[0017] In one possible design, the core control module includes an analog-to-digital conversion unit, a data analysis and control signal generation unit, and a data storage unit;

[0018] The signal input end of the analog-digital conversion unit is configured to receive the user neural signal transmitted by the neural signal detection module and perform signal transformation on the user neural signal to generate user neural data. The data transmission end of the analog-digital conversion unit is electrically connected to the data reception end of the data analysis and control signal generation unit, so as to transmit the user neural data to the data analysis and control signal generation unit.

[0019] The data analysis and control signal generation unit is configured to perform neural signal analysis on the received user neural data to obtain a user sleep detection result, and generate a corresponding intervention control signal according to the user sleep detection result. The first output end of the data analysis and control signal generation unit is electrically connected to the data input end of the data storage unit, so as to store the user sleep detection result into the data storage unit. The second output end of the data analysis and control signal generation unit is electrically connected to the signal input end of the bone conduction module, so as to transmit the intervention control signal to the bone conduction module. The third output end of the data analysis and control signal generation unit is electrically connected to the signal input end of the light stimulation module, so as to transmit the intervention control signal to the light stimulation module. The user sleep detection result includes a user sleep stage detection result and a user neural state detection result.

[0020] The data storage unit is configured to store the user sleep detection result.

[0021] In a possible design, the system further includes a host computer and a display.

[0022] The input end of the host computer is electrically connected to the output end of the data storage unit, so as to obtain the user sleep detection result stored in the data storage unit and generate a user sleep detection result diagram according to the user sleep detection result. The output end of the host computer is electrically connected to the display, so as to visually display the user sleep detection result diagram on the display.

[0023] In a possible design, the bone conduction module includes a micro bone conduction speaker.

[0024] The signal input end of the micro bone conduction speaker is configured to receive the intervention control signal. The noise output end of the micro bone conduction speaker is configured to contact the skin of the user's temporal bone and play sleep intervention noise of different frequencies and different volumes to the user according to the intervention control signal. The sleep intervention noise includes pink noise.

[0025] In a possible design, the light stimulation module includes an LED lamp hole matrix.

[0026] The signal input end of the LED lamp hole matrix is used for receiving the intervention control signal, and the light wave output end of the LED lamp hole matrix is used for emitting sleep intervention light waves of different wavelengths and different light intensities to the eye area of the user, wherein the LED lamp hole matrix is arranged corresponding to the eye area of the user, and the sleep intervention light waves include warm light waves.

[0027] In a possible design, the intervention effect feedback module is further included, and the intervention effect feedback module is electrically connected with the core control module, the bone conduction module and the light stimulation module respectively;

[0028] The trigger signal input end of the intervention effect feedback module is electrically connected with the bone conduction module and the light stimulation module respectively, is used for detecting the working state of the bone conduction module and / or the light stimulation module, and sends a trigger signal to the intervention effect feedback module when the bone conduction module and / or the light stimulation module work, so that the intervention effect feedback module starts to work;

[0029] The intervention effect detection end of the intervention effect feedback module is used for contacting the skin of the user to obtain the user nerve signal after intervention, and the feedback signal output end of the intervention effect feedback module is electrically connected with the core control module to send the user nerve signal after intervention to the core control module.

[0030] In a second aspect, the application provides an intelligent sleep detection and intervention method combined with a brain-computer interface, which is realized based on the core control module in the brain-computer interface combined intelligent sleep detection and intervention eyecup system in the first aspect.

[0031] Real-time acquisition of user nerve signals;

[0032] Based on the brain-computer interface technology, the user nerve signals are analyzed to obtain a user sleep detection result;

[0033] According to the user sleep detection result, a corresponding intervention control signal is generated and output.

[0034] In a possible design, based on the brain-computer interface technology, the user nerve signals are analyzed to obtain a user sleep detection result, including:

[0035] Based on the brain-computer interface technology, historical user nerve signals are acquired, and the historical user nerve signals are used for training to establish an intelligent sleep detection model with the sleep detection result as an output;

[0036] The user nerve signals are input into the intelligent sleep detection model to obtain a user sleep detection result.

[0037] In one possible design, generating and outputting a corresponding intervention control signal according to the user sleep detection result includes:

[0038] Obtain pre-set intervention strategies;

[0039] Using the preset intervention strategy, matching the user's sleep detection result with a corresponding intervention control instruction;

[0040] Based on the user sleep detection result, determine whether the user is in the rapid eye movement sleep period. If not, output the corresponding intervention control signal to the bone conduction module and / or light stimulation module according to the intervention control instruction. If so, obtain the user's neural signal again and perform neural signal analysis to determine whether the user is in the rapid eye movement sleep period again based on the obtained user sleep detection result, until the result is no.

[0041] In a third aspect, the present invention provides an intelligent sleep detection and intervention eye mask device combined with a brain-computer interface, comprising a skin-friendly material layer, a core controller, a status indicator light, an electromagnetic shielding layer, a patch electrode layer, an adjustable fixing device, an inner lining light emitter, and a bone conductor;

[0042] The skin-friendly material layer covers the contact surface between the eye mask device and the user's skin and is used for contacting the user's skin, and the skin-friendly material layer is made of a flexible and breathable material;

[0043] The core controller is used to carry the core control module, and the core controller is integrated with an analog-to-digital converter, a microprocessor and a memory;

[0044] The status indicator light is arranged on the outside of the eye mask device, and is used to intuitively display information such as the power status, working status and network status of the device;

[0045] The patch electrode layer is arranged on the inner side of the eye mask device and is made of a flexible conductive material. It can comfortably fit the user's skin at the forehead or around the eyes, and serves as the detection end of the neural signal detection module to collect the user's neural signals. The number and position distribution of the electrodes in the patch electrode layer conform to the layout of the international 10-20 electrode placement protocol.

[0046] The electromagnetic shielding layer is provided between the patch electrode layer and the external environment to block electromagnetic interference and reduce the influence of external electromagnetic interference on the collection of the user's neural signals, thereby improving the accuracy of the sleep detection results;

[0047] The adjustable fixing device adopts an elastic band structure to ensure that the eye mask device can fit firmly with different head shapes and ensure the wearing stability of the eye mask device;

[0048] The inner lining light emitter is arranged on the inner side of the eye mask device and corresponds to the user's eye area, and is configured to carry the light stimulation module and emit sleep intervention light waves of different wavelengths and different light intensities.

[0049] The bone conduction device is arranged on the inner side of the eye mask device and corresponds to the user's temporal bone area, and is configured to carry the bone conduction module and play sleep intervention noise of adjustable frequency and volume.

[0050] Beneficial effects: The present application provides an intelligent sleep detection and intervention eye mask system and method combined with brain-computer interface, which comprises a neural signal detection module, a core control module, a bone conduction module and a light stimulation module. The core control module is electrically connected to the neural signal detection module, the bone conduction module and the light stimulation module. The neural signal detection module is used to contact the user's skin to obtain the user's neural signal and send the user's neural signal to the core control module. The core control module is used to receive the user's neural signal sent by the neural signal detection module, analyze the user's neural signal to obtain the user's sleep detection result, and generate a corresponding intervention control signal according to the user's sleep detection result, and send the intervention control signal to the bone conduction module and the light stimulation module. The bone conduction module is used to receive the intervention control signal and play sleep intervention noise of different frequencies and different volumes to the user according to the intervention control signal. The light stimulation module is used to receive the intervention control signal and emit sleep intervention light waves of different wavelengths and different light intensities to the user according to the intervention control signal. Through the neural signal detection module, the system can monitor the user's brain waves, detect the corresponding user's neural signal, and based on the brain-computer interface technology, analyze in real time through the core control module to obtain accurate sleep detection result, provide personalized sleep detection for the user, and realize real-time sleep intervention according to the personalized sleep detection result, to improve the sleep intervention effect on the user. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 A functional structure diagram of an intelligent sleep detection and intervention eye mask system combined with brain-computer interface is provided for the embodiments of the present application.

[0052] Figure 2 A step flowchart of an intelligent sleep detection and intervention method combined with brain-computer interface is provided for the embodiments of the present application.

[0053] Figure 3 A schematic structural diagram of an intelligent sleep detection and intervention eye mask device combined with a brain-computer interface provided by an embodiment of the present invention;

[0054] Figure 4 A schematic diagram of a lined light emitter provided in an embodiment of the present invention;

[0055] Figure 5 Schematic diagram of a bone conductor provided by an embodiment of the present invention.

[0056] Among them, 1. Skin-friendly material layer; 2. Core controller; 3. Status indicator light; 4. Electromagnetic shielding layer; 5. Patch electrode layer; 6. Adjustable fixing device; 7. Lined light emitter; 8. Bone conductor. DETAILED DESCRIPTION

[0057] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the present invention will be briefly introduced below in conjunction with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structure of the drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0058] It should be understood that although the terms "first," "second," etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element can be referred to as a second element, and similarly, a second element can be referred to as a first element without departing from the scope of the exemplary embodiments of the present invention.

[0059] It should be understood that the term "and / or" that may appear in this document is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B may indicate three situations: A exists alone, B exists alone, and A and B exist at the same time. The term " / and" that may appear in this document describes another type of association object relationship, indicating that two relationships may exist. For example, A / and B may indicate two situations: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the previous and subsequent associated objects are in an "or" relationship.

[0060] Example:

[0061] like Figure 1As shown, the first aspect of this embodiment provides an intelligent sleep detection and intervention eye mask system combined with a brain-computer interface, which includes: a neural signal detection module, a core control module, a bone conduction module and a light stimulation module, wherein the core control module is electrically connected to the neural signal detection module, the bone conduction module and the light stimulation module respectively, wherein:

[0062] The neural signal detection module is configured to contact the user's skin to obtain the user's neural signal and send the user's neural signal to the core control module;

[0063] The core control module is configured to receive the user neural signal sent by the neural signal detection module, perform neural signal analysis on the user neural signal to obtain a user sleep detection result, generate a corresponding intervention control signal based on the user sleep detection result, and send the intervention control signal to the bone conduction module and the light stimulation module respectively;

[0064] The bone conduction module is configured to receive the intervention control signal and play sleep intervention noise of different frequencies and volumes to the user according to the intervention control signal;

[0065] The light stimulation module is used to receive the intervention control signal and emit sleep intervention light waves of different wavelengths and different light intensities to the user according to the intervention control signal.

[0066] It should be noted that the intelligent sleep detection and intervention eye mask system provided in this embodiment is based on brain-computer interface technology (Brain-Computer Interface, BCI). It monitors the user's EEG through a neural signal detection module (i.e., brain-computer interface), detects the corresponding user's neural signals, and performs real-time analysis through the core control module to obtain accurate sleep detection results, providing users with personalized sleep detection and able to implement real-time sleep intervention based on the personalized sleep detection results, so as to improve the sleep intervention effect on the user.

[0067] Among them, the brain-computer interface technology is a technology that establishes a direct information exchange channel between the biological brain and an intelligent machine, aiming to achieve two-way interaction between the brain and external devices. The brain-computer interface technology in this embodiment is implemented through a neural signal detection module and a core control module. The neural signal detection module is used to extract corresponding electrical signals from human brain activities (which can be collected through electrodes), and the core control module is used to convert the extracted electrical signals into digital information and generate sleep detection results to complete subsequent sleep intervention.

[0068] In addition, the bone conduction module is implemented using bone conduction technology. Utilizing this unique audio transmission method, the sleep intervention noise used to assist sleep can be transmitted directly to the user's inner ear through the bones, which can effectively reduce the interference of environmental noise and greatly improve the sleep intervention effect; while the light stimulation module can effectively regulate the human body's circadian rhythm, have a beneficial effect on sleep and wakefulness, and help improve the user's sleep quality.

[0069] Among them, sleep intervention noise and sleep intervention light waves are used to assist users in entering a healthier sleep mode. Sleep intervention noises of different frequencies and volumes are used to adjust users' different sleep stages, such as white noise and pink noise; sleep intervention light waves of different wavelengths and light intensities are also used to ensure the comfort of users in different sleep stages, such as soft white light.

[0070] In a possible implementation, the neural signal detection module includes a neural signal detection unit and a neural signal preprocessing unit;

[0071] The detection end of the neural signal detection unit is used to contact the skin at the user's forehead or the skin around the eyes and obtain the original user neural signal. The signal output end of the neural signal detection unit is electrically connected to the signal input end of the neural signal preprocessing unit to send the original user neural signal to the neural signal preprocessing unit.

[0072] The neural signal preprocessing unit is used to perform signal preprocessing on the input original user neural signal and generate a user neural signal. The signal output end of the neural signal preprocessing unit is electrically connected to the signal input end of the core control module to send the user neural signal to the core control module.

[0073] In a possible implementation, the core control module includes an analog-to-digital conversion unit, a data analysis and control signal generation unit, and a data storage unit;

[0074] The signal input end of the analog-to-digital conversion unit is used to receive the user neural signal sent by the neural signal detection module and perform signal conversion on the user neural signal to generate user neural data. The data transmitting end of the analog-to-digital conversion unit is electrically connected to the data receiving end of the data analysis and control signal generation unit to send the user neural data to the data analysis and control signal generation unit.

[0075] The data analysis and control signal generation unit is used to perform neural signal analysis on the received user neural data to obtain a user sleep detection result, and generate a corresponding intervention control signal according to the user sleep detection result. The first output end of the data analysis and control signal generation unit is electrically connected to the data input end of the data storage unit to store the user sleep detection result in the data storage unit. The second output end of the data analysis and control signal generation unit is electrically connected to the signal input end of the bone conduction module to send the intervention control signal to the bone conduction module. The third output end of the data analysis and control signal generation unit is electrically connected to the signal input end of the light stimulation module to send the intervention control signal to the light stimulation module. The user sleep detection result includes a user sleep stage detection result and a user neural state detection result.

[0076] The data storage unit is used to store the user sleep detection result.

[0077] In a possible implementation, it further includes a host computer and a display;

[0078] Among them, the input end of the host computer is electrically connected to the output end of the data storage unit to obtain the user sleep detection results stored in the data storage unit, and generate a user sleep detection result graph based on the user sleep detection results. The output end of the host computer is electrically connected to the display to visualize the user sleep detection result graph through the display.

[0079] In one possible implementation, the bone conduction module includes a miniature bone conduction speaker;

[0080] The signal input end of the miniature bone conduction speaker is used to receive the intervention control signal, and the noise output end of the miniature bone conduction speaker is used to contact the skin at the user's temporal bone and play sleep intervention noise of different frequencies and volumes to the user according to the intervention control signal, wherein the sleep intervention noise includes pink noise.

[0081] It should be noted that pink noise refers to an audio signal whose power spectral density is inversely proportional to frequency, and its energy remains equal within each octave. Pink noise has higher energy in the low-frequency region and gradually decreases in the high-frequency region. Pink noise is a mixture of low-frequency and high-frequency components, but the low-frequency energy is more prominent. Pink noise can stimulate the user's auditory system and mask background noise, providing a quieter and more comfortable listening environment. Therefore, it helps users relieve stress and improve sleep quality, and is very suitable as a sleep intervention noise for the bone conduction module of this system.

[0082] In one possible implementation, the light stimulation module includes an LED light hole matrix;

[0083] The signal input end of the LED lamp hole matrix is ​​used to receive the intervention control signal, and the light wave output end of the LED lamp hole matrix is ​​used to emit sleep intervention light waves of different wavelengths and different light intensities to the user's eye area, wherein the LED lamp hole matrix is ​​set corresponding to the user's eye area, and the sleep intervention light waves include warm light waves.

[0084] In a possible implementation, an intervention effect feedback module is further included, wherein the intervention effect feedback module is electrically connected to the core control module, the bone conduction module, and the light stimulation module respectively;

[0085] The trigger signal input end of the intervention effect feedback module is electrically connected to the bone conduction module and the light stimulation module, respectively, for detecting the working status of the bone conduction module and / or the light stimulation module, and when the bone conduction module and / or the light stimulation module are working, a trigger signal is sent to the intervention effect feedback module, and the intervention effect feedback module starts working;

[0086] The intervention effect detection end of the intervention effect feedback module is used to contact the user's skin to obtain the user's neural signal after intervention, and the feedback signal output end of the intervention effect feedback module is electrically connected to the core control module to send the user's neural signal after intervention to the core control module.

[0087] It should be noted that the introduction of the intervention effect feedback module can evaluate and adjust the sleep intervention effect to a certain extent, and feed back the real-time intervention effect to the core control module. The core control module can adaptively adjust the intervention strategy according to the intervention effect, so as to optimize the personalized intervention strategy that is more suitable for the user according to different external factors such as the user's physique and sleep habits. Through this feedback adjustment, the adaptability of this system and the sleep intervention effect on the user are greatly improved.

[0088] like Figure 2 As shown, the second aspect of this embodiment provides an intelligent sleep detection and intervention method combined with a brain-computer interface, which is implemented based on the core control module in the intelligent sleep detection and intervention eye mask system combined with a brain-computer interface described in any of the first aspects of this embodiment, wherein the method includes the following steps:

[0089] S1. Acquire user neural signals in real time;

[0090] S2. Based on brain-computer interface technology, performing neural signal analysis on the user's neural signal to obtain the user's sleep detection result;

[0091] S3. Generate and output a corresponding intervention control signal according to the user sleep detection result.

[0092] In a possible design, the user neural signal is analyzed based on the brain-computer interface technology to obtain a user sleep detection result, including:

[0093] S21. Obtain historical user neural signals based on the brain-computer interface technology, and train the historical user neural signals to obtain a sleep detection result as an output to establish an intelligent sleep detection model;

[0094] S22. Input the user neural signal into the intelligent sleep detection model to obtain a user sleep detection result.

[0095] Specifically, the intelligent sleep detection model provided in this embodiment first needs to collect historical electroencephalogram (EEG) signal data of a user in a natural sleep process by using a total of eight non-invasive patch electrodes arranged in the forehead and occipital region, perform band-pass filtering (such as 0.5-45 Hz) on the historical EEG signal data to remove power frequency and low frequency drift, remove electrooculogram (EOG) signals and electromyogram (EMG) signals by using independent component analysis (ICA) or an adaptive threshold method, and process by a segmented window function (such as a 30-second sliding window) to form multiple groups of data and form a multi-channel EEG signal matrix, so as to use the multi-channel EEG signal matrix as historical user neural signals. Second, for the historical user neural signals, a feature vector is extracted based on multi-channel time domain (such as mean, variance, and zero-crossing rate) and frequency domain features (such as alpha wave, theta wave, and delta wave power density), and a corresponding label is constructed according to a preset label or standard polysomnography (PSG) record. Then, a deep neural network model (such as a one-dimensional convolutional neural network (CNN) or a bidirectional LSTM-RNN) is preferentially selected to iteratively train the input feature vector, and finally an intelligent sleep detection model is obtained.

[0096] In a possible design, according to the user sleep detection result, a corresponding intervention control signal is generated and output, including:

[0097] S31. Obtain a preset intervention strategy;

[0098] S32. Match a corresponding intervention control instruction for the user sleep detection result by using the preset intervention strategy;

[0099] S33. According to the user sleep detection result, determine whether the user is in a rapid eye movement (REM) sleep period. If not, output a corresponding intervention control signal to a bone conduction module and / or a light stimulation module according to the intervention control instruction. If yes, obtain user neural signals again and perform neural signal analysis to determine whether the user is in the REM sleep period again according to the obtained user sleep detection result, until the result is no.

[0100] like Figures 3-5 As shown, the third aspect of this embodiment provides an intelligent sleep detection and intervention eye mask device combined with a brain-computer interface, which is used to carry the intelligent sleep detection and intervention eye mask system combined with a brain-computer interface described in the first aspect of this embodiment, including a skin-friendly material layer 1, a core controller 2, a status indicator light 3, an electromagnetic shielding layer 4, a patch electrode layer 5, an adjustable fixing device 6, an inner lining light emitting device 7 and a bone conductor 8;

[0101] The skin-friendly material layer 1 covers the contact surface between the eye mask device and the user's skin and is used for contacting the user's skin. The skin-friendly material layer 1 is made of a flexible and breathable material.

[0102] The core controller 2 is used to carry the core control module, and the core controller 2 is integrated with an analog-to-digital converter, a microprocessor and a memory;

[0103] The status indicator light 3 is arranged on the outside of the eye mask device and is used to intuitively display information such as the power status, working status and network status of the device;

[0104] The patch electrode layer 5 is arranged on the inner side of the eye mask device and is made of a flexible conductive material. It can comfortably fit the user's forehead skin or skin around the eyes, and serves as the detection end of the neural signal detection module to collect the user's neural signals. The number and position distribution of the electrodes in the patch electrode layer 5 conform to the layout of the international 10-20 electrode placement protocol.

[0105] The electromagnetic shielding layer 4 is provided between the patch electrode layer 5 and the external environment to block electromagnetic interference and reduce the influence of external electromagnetic interference on the collection of the user's neural signals, thereby improving the accuracy of the sleep detection results;

[0106] The adjustable fixing device 6 adopts an elastic band structure to ensure that the eye mask device can fit firmly with different head shapes and ensure the wearing stability of the eye mask device;

[0107] The inner lining light emitting device 7 is arranged on the inner side of the eye mask device and is arranged corresponding to the user's eye area, and is used to carry the light stimulation module and is configured to emit sleep intervention light waves of different wavelengths and different light intensities. The inner lining light emitting device 7 can emit warm light waves to the user to promote melatonin secretion, and can also simulate the natural sunrise effect, gradually increase the light wave brightness and blue light ratio to intervene in the user's sleep;

[0108] The bone conductor 8 is arranged on the inner side of the eye mask device and is arranged corresponding to the user's temporal bone area. It is used to carry the bone conduction module and is configured to play sleep intervention noise with adjustable frequency and volume; it can play sleep intervention noise to promote the user to fall asleep, and can also adjust the audio and volume or stop playing the sleep intervention noise to intervene in the user's sleep.

[0109] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. An intelligent sleep detection and intervention eye mask system combined with a brain-computer interface, characterized in that: include: A neural signal detection module, a core control module, a bone conduction module, and a light stimulation module, wherein the core control module is electrically connected to the neural signal detection module, the bone conduction module, and the light stimulation module, respectively. The neural signal detection module is configured to contact the user's skin to obtain the user's neural signal and send the user's neural signal to the core control module; The core control module is configured to receive the user neural signal sent by the neural signal detection module, perform neural signal analysis on the user neural signal to obtain a user sleep detection result, generate a corresponding intervention control signal based on the user sleep detection result, and send the intervention control signal to the bone conduction module and the light stimulation module respectively; The bone conduction module is configured to receive the intervention control signal and play sleep intervention noise of different frequencies and volumes to the user according to the intervention control signal; The light stimulation module is used to receive the intervention control signal and emit sleep intervention light waves of different wavelengths and different light intensities to the user according to the intervention control signal.

2. The intelligent sleep detection and intervention eye mask system combined with brain-computer interface according to claim 1 is characterized in that: The neural signal detection module includes a neural signal detection unit and a neural signal preprocessing unit; The detection end of the neural signal detection unit is used to contact the skin at the user's forehead or the skin around the eyes and obtain the original user neural signal. The signal output end of the neural signal detection unit is electrically connected to the signal input end of the neural signal preprocessing unit to send the original user neural signal to the neural signal preprocessing unit. The neural signal preprocessing unit is used to perform signal preprocessing on the input original user neural signal and generate a user neural signal. The signal output end of the neural signal preprocessing unit is electrically connected to the signal input end of the core control module to send the user neural signal to the core control module.

3. The intelligent sleep detection and intervention eye mask system combined with brain-computer interface according to claim 1 is characterized in that: The core control module includes an analog-to-digital conversion unit, a data analysis and control signal generation unit, and a data storage unit; The signal input end of the analog-to-digital conversion unit is used to receive the user neural signal sent by the neural signal detection module and perform signal conversion on the user neural signal to generate user neural data. The data transmitting end of the analog-to-digital conversion unit is electrically connected to the data receiving end of the data analysis and control signal generation unit to send the user neural data to the data analysis and control signal generation unit. The data analysis and control signal generation unit is used to perform neural signal analysis on the received user neural data to obtain a user sleep detection result, and generate a corresponding intervention control signal according to the user sleep detection result. The first output end of the data analysis and control signal generation unit is electrically connected to the data input end of the data storage unit to store the user sleep detection result in the data storage unit. The second output end of the data analysis and control signal generation unit is electrically connected to the signal input end of the bone conduction module to send the intervention control signal to the bone conduction module. The third output end of the data analysis and control signal generation unit is electrically connected to the signal input end of the light stimulation module to send the intervention control signal to the light stimulation module. The user sleep detection result includes a user sleep stage detection result and a user neural state detection result. The data storage unit is used to store the user sleep detection result.

4. The intelligent sleep detection and intervention eye mask system combined with a brain-computer interface according to claim 3 is characterized in that: It also includes a host computer and a display; Among them, the input end of the host computer is electrically connected to the output end of the data storage unit to obtain the user sleep detection results stored in the data storage unit, and generate a user sleep detection result graph based on the user sleep detection results. The output end of the host computer is electrically connected to the display to visualize the user sleep detection result graph through the display.

5. The intelligent sleep detection and intervention eye mask system combined with brain-computer interface according to claim 1 is characterized in that: The bone conduction module includes a miniature bone conduction speaker; The signal input end of the miniature bone conduction speaker is used to receive the intervention control signal, and the noise output end of the miniature bone conduction speaker is used to contact the skin at the user's temporal bone and play sleep intervention noise of different frequencies and volumes to the user according to the intervention control signal, wherein the sleep intervention noise includes pink noise.

6. The intelligent sleep detection and intervention eye mask system combined with brain-computer interface according to claim 1 is characterized in that: The light stimulation module includes an LED light hole matrix; The signal input end of the LED lamp hole matrix is ​​used to receive the intervention control signal, and the light wave output end of the LED lamp hole matrix is ​​used to emit sleep intervention light waves of different wavelengths and different light intensities to the user's eye area, wherein the LED lamp hole matrix is ​​set corresponding to the user's eye area, and the sleep intervention light waves include warm light waves.

7. The intelligent sleep detection and intervention eye mask system combined with brain-computer interface according to claim 1 is characterized in that: It also includes an intervention effect feedback module, which is electrically connected to the core control module, the bone conduction module and the light stimulation module respectively; The trigger signal input end of the intervention effect feedback module is electrically connected to the bone conduction module and the light stimulation module, respectively, for detecting the working status of the bone conduction module and / or the light stimulation module, and when the bone conduction module and / or the light stimulation module are working, a trigger signal is sent to the intervention effect feedback module, and the intervention effect feedback module starts working; The intervention effect detection end of the intervention effect feedback module is used to contact the user's skin to obtain the user's neural signal after intervention, and the feedback signal output end of the intervention effect feedback module is electrically connected to the core control module to send the user's neural signal after intervention to the core control module.

8. A method for intelligent sleep detection and intervention in combination with a brain-computer interface, implemented based on the core control module of the intelligent sleep detection and intervention eye mask system in combination with a brain-computer interface according to any one of claims 1 to 7, characterized in that: The method comprises the following steps: Acquire user neural signals in real time; Based on brain-computer interface technology, neural signal analysis is performed on the user's neural signal to obtain a user sleep detection result; According to the user sleep detection result, a corresponding intervention control signal is generated and output.

9. The intelligent sleep detection and intervention method combined with brain-computer interface according to claim 8, characterized in that: Based on brain-computer interface technology, neural signal analysis is performed on the user's neural signal to obtain the user's sleep detection result, including: Based on brain-computer interface technology, historical user neural signals are obtained and used for training, with sleep detection results as output to establish an intelligent sleep detection model; The user's neural signal is input into the intelligent sleep detection model to obtain a user's sleep detection result.

10. The intelligent sleep detection and intervention method combined with brain-computer interface according to claim 8, characterized in that: Generating and outputting a corresponding intervention control signal according to the user sleep detection result, including: Obtain pre-set intervention strategies; Using the preset intervention strategy, matching the user's sleep detection result with a corresponding intervention control instruction; Based on the user sleep detection result, determine whether the user is in the rapid eye movement sleep period. If not, output the corresponding intervention control signal to the bone conduction module and / or light stimulation module according to the intervention control instruction. If so, obtain the user's neural signal again and perform neural signal analysis to determine whether the user is in the rapid eye movement sleep period again based on the obtained user sleep detection result, until the result is no.

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