In-ear brain-computer interface system, in-ear device and sleep intervention method

Abstract

The invention provides an in-ear brain-computer interface system, in-ear equipment and a sleep intervention method.The in-ear brain-computer interface system comprises a cloud processor and the in-ear equipment, and the cloud processor is in communication connection with the in-ear equipment; the in-ear device comprises an electroencephalogram collection module and an intervention module, the electroencephalogram collection module is used for collecting ear canal electroencephalogram signals of a user in the sleep process, the intervention module is used for responding to an instruction of the cloud processor to intervene the user, and the user wears the in-ear device; the cloud processor is used for receiving the ear canal electroencephalogram signals from the in-ear device so as to determine the sleep stage of the user and generate a first instruction corresponding to the sleep stage. The auditory meatus electroencephalogram signals in the sleep process can be collected, the sleep stage of the user can be accurately recognized, the instruction corresponding to the sleep stage is generated in real time to intervene the user, and the sleep quality of the user is greatly improved.

Description

Technical Field

[0001] The present application relates to the field of brain-computer interface technology, and in particular to an in-ear brain-computer interface system, an in-ear device, and a sleep intervention method. Background Art

[0002] According to statistics, more than 300 million people in China suffer from sleep disorders to varying degrees, and the incidence of insomnia among adults is as high as 38.2%. Many insomnia patients seek non-drug therapies to solve the problem, so accurate sleep monitoring has become a prerequisite for solving insomnia problems.

[0003] In serious medical settings, polysomnography (PSG) is often used to monitor sleep status. This device requires the patient to wear multiple sensors, including EEG sensors, ECG sensors, nasal airflow sensors, chest and abdominal movement sensors, and myoelectric sensors. This device is bulky and complex to use, and its comfort issues negatively impact the patient's sleep, making it difficult to use as a long-term monitoring tool.

[0004] In daily application scenarios, current sleep monitoring technology mainly uses photoplethysmography (PPG), which is a method of measuring human physiological data based on LED light sources and detectors. It measures the attenuation of light reflected by blood vessels and other tissues on the surface of human skin, and then records the pulsation state of blood vessels. At the same time, it measures pulse waves. There are also sleep monitoring methods that use millimeter waves.

[0005] Most existing sleep monitoring technologies rely on non-EEG signals, which have low accuracy. They generally only record sleep status. After waking up, users can see their sleep information on wearable devices such as bracelets and watches, but this cannot improve the user's sleep quality. Summary of the Invention

[0006] In view of this, the present application provides an in-ear brain-computer interface system, an in-ear device and a sleep intervention method. The in-ear structure ensures that it is convenient and comfortable to wear while being able to collect EEG signals, making the detected sleep stages more accurate so that timely intervention can be made, greatly improving the user's sleep quality.

[0007] In a first aspect, an embodiment of the present application provides an in-ear brain-computer interface system, comprising:

[0008] A cloud processor and an in-ear device, wherein the cloud processor and the in-ear device are communicatively connected;

[0009] The in-ear device includes an EEG acquisition module and an intervention module. The EEG acquisition module is used to collect EEG signals from the ear canal of the user during sleep. The intervention module is used to intervene in the user in response to instructions from the cloud processor. The user wears the in-ear device.

[0010] The cloud-based processor is used to receive the ear canal electroencephalogram signal from the in-ear device to determine the sleep stage of the user and generate a first instruction corresponding to the sleep stage.

[0011] In a possible embodiment, the intervention module includes an electric pulse module, and the electric pulse module is configured to generate a first electric pulse in response to a first instruction corresponding to the light sleep stage when the sleep stage is the light sleep stage.

[0012] In a possible embodiment, the intervention module includes an audio module, which is used to play sleep-aid audio in response to a first instruction corresponding to the light sleep stage when the sleep stage is a light sleep stage; or, the audio module is used to play wake-up audio in response to a first instruction corresponding to the close-to-wakefulness stage when the sleep stage is a close-to-wakefulness stage.

[0013] In a possible embodiment, the in-ear device further includes a sound sensor, which is used to collect sound data of the user during sleep. The cloud processor is used to receive the sound data from the in-ear device and generate a second instruction when it is recognized that the sound data includes snoring.

[0014] In a possible embodiment, the intervention module includes an electric pulse module, and the electric pulse module is configured to generate a second electric pulse in response to the second instruction.

[0015] In a possible embodiment, the intervention module includes a vibration module, and the vibration module is configured to vibrate in response to the second instruction.

[0016] In a possible embodiment, the in-ear device further includes a vital sign sensor, which is used to collect vital sign data of the user during sleep.

[0017] In the second aspect, an embodiment of the present application provides an in-ear device, which includes a main body and a charging compartment, the main body including a shell, an EEG acquisition module, an intervention module and a main circuit board, the EEG acquisition module including electrodes, the electrodes being arranged on the shell, the EEG acquisition module and the intervention module being connected to the main circuit board through built-in wires, the main circuit board being arranged inside a cavity wrapped by the shell, and the shell being provided with charging contacts; the charging compartment includes a charging interface, a compartment battery and a charging control board, the charging control board being connected to the battery, and the charging interface being used to contact the charging contacts to charge the main body.

[0018] In a third aspect, an embodiment of the present application provides a sleep intervention method, which is applied to a cloud processor in an in-ear brain-computer interface system, wherein the in-ear brain-computer interface system also includes an in-ear device, and the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module and an intervention module, wherein the EEG acquisition module is used to collect EEG signals from the user's ear canal during sleep, and the intervention module is used to intervene in the user in response to instructions from the cloud processor, and the user wears the in-ear device; the method includes:

[0019] determining the user's sleep stage based on the ear canal EEG signal from the in-ear device;

[0020] A first instruction corresponding to the sleep stage is generated.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in any method of the third aspect of the embodiment of the present application.

[0022] In a fifth aspect, embodiments of the present application provide a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to execute some or all of the steps described in any method of the third aspect of the embodiments of the present application. The computer program product may be a software installation package.

[0023] It can be seen that the above-mentioned in-ear brain-computer interface system, in-ear device and sleep intervention method include a cloud processor and an in-ear device, the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module and an intervention module, the EEG acquisition module is used to collect the user's ear canal EEG signals during sleep, and the intervention module is used to intervene in the user in response to the instructions of the cloud processor, and the user wears the in-ear device; the cloud processor is used to receive the ear canal EEG signals from the in-ear device to determine the user's sleep stage and generate a first instruction corresponding to the sleep stage. The ear canal EEG signals during sleep can be collected, the user's sleep stage can be accurately identified, and instructions corresponding to the sleep stage can be generated in real time to intervene in the user, which greatly improves the user's sleep quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 A schematic structural diagram of an in-ear brain-computer interface system provided in an embodiment of the present application;

[0026] Figure 2 A schematic diagram of the main components of an in-ear device provided in an embodiment of the present application;

[0027] Figure 3 A schematic diagram of the main structure of an in-ear device provided in an embodiment of the present application;

[0028] Figure 4 A schematic diagram of the main structure of a charging compartment for an in-ear device provided in an embodiment of the present application;

[0029] Figure 5 A flowchart of a sleep intervention method provided in an embodiment of the present application;

[0030] Figure 6 A flowchart of another sleep intervention method provided in an embodiment of the present application;

[0031] Figure 7 This is an operating logic diagram of an in-ear brain-computer interface system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0033] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0034] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document indicates that the associated objects are in an "or" relationship. The "plurality" appearing in the embodiments of this application refers to two or more.

[0035] In the embodiments of the present application, "at least one item" or similar expressions refers to any combination of these items, including any combination of single items or plural items, and refers to one or more, and multiple refers to two or more. For example, at least one item (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0036] The "connection" appearing in the embodiments of the present application refers to various connection methods such as direct connection or indirect connection to achieve communication between devices, and the embodiments of the present application do not impose any limitations on this.

[0037] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0038] First combine Figure 1 The in-ear brain-computer interface system in the embodiment of the present application is described. Figure 1 A structural diagram of an in-ear brain-computer interface system provided in an embodiment of the present application includes a cloud processor 110 and an in-ear device 120, and the cloud processor 110 and the in-ear device 120 are communicatively connected.

[0039] Among them, the in-ear device 120 includes an EEG acquisition module 121 and an intervention module 122. The EEG acquisition module 121 is used to collect the user's ear canal EEG signals during sleep, and the intervention module 122 is used to intervene in the user in response to the instructions of the cloud processor. The user wears the in-ear device 120.

[0040] The cloud processor 110 is configured to receive the ear canal electroencephalogram signal from the in-ear device 120 to determine the sleep stage of the user and generate a first instruction corresponding to the sleep stage.

[0041] The in-ear device 120 can take various forms, such as wireless headphones, ear-hook headphones, bone conduction headphones, wired headphones, earplugs, etc., and can be customized according to the shape of the user's ear canal to ensure user comfort while collecting more accurate ear canal EEG signals. This is not specifically limited here.

[0042] The EEG acquisition module 121 may include multiple electrodes, which can be divided into active EEG acquisition electrodes, reference electrodes, and ground electrodes. The active EEG acquisition electrodes need to be in contact with the user's ear canal skin, while the reference electrodes and ground electrodes need to be in contact with the user's skin. Because bioelectric signals are inherently weak and susceptible to interference, the reference electrode can be placed at a location on the human body that is relatively zero potential or has a stable potential, such as the earlobe or mastoid process. In this embodiment, the reference electrode can be placed at a location corresponding to the cymba concha in the ear.

[0043] Among them, the cloud processor 110 can have a built-in sleep staging algorithm. The sleep staging algorithm can be a unimodal model that only uses unimodal data of auditory canal EEG signals to model, or it can be a multimodal model that integrates other sensor data to obtain sleep staging results through AI algorithms.

[0044] The cloud processor 110 may have a built-in snoring detection algorithm to detect snoring events based on audio data, vital sign data, and other data.

[0045] Among them, the cloud processor 110 can detect the user's sleep stage in real time and generate different instructions for different sleep stages. The instructions can be sent to the intervention module 122, so that the intervention module 122 intervenes in the user, greatly improving the user's sleep quality.

[0046] In a possible embodiment, the intervention module 122 may include an electric pulse module, which is configured to generate a first electric pulse in response to a first instruction corresponding to the light sleep stage when the sleep stage is the light sleep stage.

[0047] The duration of the first electric pulse can be a preset time, such as a maximum duration of 30 minutes, and the first electric pulse automatically stops after 30 minutes. Alternatively, after the cloud processor 110 recognizes that the user has entered a deep sleep stage, it can send a stop instruction to the electric pulse module to stop the first electric pulse. The frequency and intensity of the first electric pulse can adopt the frequency and intensity of transcutaneous vagus nerve stimulation (tVNS) therapy, which can promote relaxation and help the user fall asleep, thereby improving sleep quality.

[0048] In a possible embodiment, the intervention module 122 may include an audio module, which is used to play sleep-aiding audio in response to a first instruction corresponding to the light sleep stage when the sleep stage is a light sleep stage; or, the audio module is used to play wake-up audio in response to a first instruction corresponding to the close-to-wakefulness stage when the sleep stage is a close-to-wakefulness stage.

[0049] When the cloud processor 110 detects that the user has entered a deep sleep phase, it can send a stop command to the audio module to stop the sleep-aiding audio, ensuring no audio interference during deep sleep and ensuring sleep efficiency. The wake-up audio can be gentle to prevent startling the user and gradually awaken them. The sleep-aiding audio can be any audio preferred by the user, etc., and is not specifically limited here.

[0050] In a possible embodiment, the in-ear device 120 may further include a sound sensor, and the sound is used to collect sound data of the user during sleep. The cloud processor 110 is used to receive the sound data from the in-ear device 120 and generate a second instruction when it is recognized that the sound data includes snoring.

[0051] The sound sensor may include a directional microphone array, etc., to reduce the interference of environmental noise and collect as much sound as possible from the user. The cloud processor 110 can extract sound features and match the sound features with snoring features. When the matching value is greater than a preset matching value, it can be determined that the user is snoring and a second instruction can be generated. Specifically, the cloud processor 110 can determine the severity of the snoring based on the size and duration of the sound and generate a second instruction corresponding to the severity of the snoring. In this way, it is possible to detect in real time whether the user is snoring and intervene in time to improve the user's sleep quality.

[0052] In a possible embodiment, the intervention module 122 may include an electric pulse module, which is configured to generate a second electric pulse in response to the second instruction.

[0053] The frequency and intensity of the second electrical pulse can be positively correlated with the severity of snoring, i.e., the more severe the snoring, the higher the frequency and intensity of the second electrical pulse. It should be noted that even the highest frequency and intensity of the second electrical pulse will not harm the user. Transcutaneous vagus nerve stimulation can be performed at the cavum concha to intervene in snoring. Upon detecting that the user's snoring has ceased, the cloud processor 110 can send a stop command to the electrical pulse module, stopping the second electrical pulse and preventing it from disturbing the user's sleep.

[0054] In a possible embodiment, the intervention module includes a vibration module, and the vibration module is configured to vibrate in response to the second instruction.

[0055] The frequency and intensity of the vibrations can be positively correlated with the severity of snoring. That is, the more severe the snoring, the higher the frequency and intensity of the vibrations. It should be noted that even the highest frequency and intensity of vibrations will not harm the user. Vibration can be used to intervene in snoring. Once the cloud processor 110 detects that the user's snoring has stopped, it can send a stop command to the vibration module, stopping the vibrations and preventing them from disturbing the user's sleep.

[0056] In a possible embodiment, the in-ear device further includes a vital sign sensor, which is used to collect vital sign data of the user during sleep.

[0057] Among them, vital sign sensors can include photoplethysmography sensors, which typically consist of one or more light-emitting diodes (LEDs) and a photodetector. When light emitted by the LEDs strikes the skin surface, some of the light is absorbed by tissues such as skin, bone, and muscle, while some is absorbed by hemoglobin in the blood. Because the blood volume in arteries changes periodically with the heartbeat, when the heart contracts, the arteries dilate, blood flow increases, and the amount of light absorbed increases accordingly. When the heart relaxes, the arteries contract, blood flow decreases, and the amount of light absorbed decreases accordingly. The photodetector detects the changes in light intensity caused by these changes in blood volume and converts them into electrical signals. After signal processing such as amplification and filtering, a pulse wave signal reflecting the heartbeat and blood circulation is obtained. For example, a reflective PPG sensor can be used, with the LED and photodetector located on the same side of the tissue being measured. Vital sign sensors can also include skin electrodermal activity sensors, which are not described in detail here. In a possible embodiment, after the user wears the in-ear device, the vital sign sensor can be located exactly at the user's earlobe, or at other locations suitable for collecting the user's vital sign data, which will not be described in detail here.

[0058] The cloud processor 110 can also receive vital sign data and combine it with ear canal EEG signals to determine the user's sleep stage, which can make the real-time determination of sleep stages more accurate. The cloud processor 110 can combine vital sign data and sound data to identify whether the user is snoring, improving the accuracy of real-time snoring detection.

[0059] It can be seen that the above-mentioned in-ear brain-computer interface system includes a cloud processor and an in-ear device, and the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module and an intervention module, the EEG acquisition module is used to collect the user's ear canal EEG signals during sleep, and the intervention module is used to intervene in the user in response to the instructions of the cloud processor, and the user wears the in-ear device; the cloud processor is used to receive the ear canal EEG signals from the in-ear device to determine the user's sleep stage and generate a first instruction corresponding to the sleep stage. The ear canal EEG signals during sleep can be collected, the user's sleep stage can be accurately identified, and instructions corresponding to the sleep stage can be generated in real time to intervene in the user, which greatly improves the user's sleep quality.

[0060] The in-ear device is described below. The in-ear device includes a main body and a charging compartment. The main body includes a shell, an EEG acquisition module, an intervention module and a main circuit board. The EEG acquisition module includes electrodes, which are arranged on the shell. The EEG acquisition module and the intervention module are connected to the main circuit board through built-in wires. The main circuit board is arranged inside the cavity wrapped by the shell, and the shell is provided with charging contacts; the charging compartment includes a charging interface, a compartment battery and a charging control board. The charging control board is connected to the battery, and the charging interface is used to contact the charging contacts to charge the main body.

[0061] Specifically, for ease of understanding, the following Figure 2-Figure 4 Taking the in-ear device as an example, it is necessary to explain that Figure 2 This is only one possible form factor of an in-ear device and does not limit the scope of in-ear devices. Figure 2 A schematic diagram of the main components of an in-ear device provided in an embodiment of the present application, including a main body 1 and a charging case 2.

[0062] See also Figure 3 , Figure 3 A schematic diagram of the main structure of an in-ear device provided in an embodiment of the present application includes an earphone housing 11, a speaker unit 12, an active EEG acquisition electrode 13, a reference electrode 14, a ground electrode 15, a main circuit board 16, an earphone battery 17 and an earphone charging contact 18.

[0063] Among them, the EEG acquisition active electrode 13 is located in the ear canal insertion part of the earphone. The EEG acquisition active electrode 13 needs to contact the ear canal to collect ear canal EEG signals. The reference electrode 14 and the ground electrode 15 are located in the non-ear canal insertion part. The reference electrode 14 is located on the part of the earphone housing 11 that contacts the cymba concha, and the ground electrode 15 is located on the part of the earphone housing 11 that contacts the lower side of the cavum concha. The EEG acquisition active electrode 13 is connected to the EEG acquisition module in the main circuit board 16 through a built-in wire. The main circuit board 16 is located inside the cavity wrapped by the earphone housing 11 and is mainly used to control EEG signal acquisition and data transmission. The main circuit board 16 is connected to the speaker unit 12 and is also connected to the earphone battery 17. The earphone housing 11 has an earphone charging contact 18.

[0064] See also Figure 4 , Figure 4 A schematic diagram of the main structure of a charging compartment for an in-ear device provided in an embodiment of the present application includes a charging interface 21, a compartment battery 22, a charging control board 23, an interface 24, and a power indicator light 25.

[0065] The charging port 21 is used to contact the earphone charging contacts 18 to wirelessly charge the earphones. The earphone charging compartment contains a battery 22 and a charging control board 23. The charging control board 23 is connected to the battery 22 and has a port 24 for connecting to an external power source to charge the battery 22. The charging compartment has a battery indicator light 25 to indicate whether the battery is fully charged. Red indicates a partial charge, and green indicates a full charge.

[0066] It should be noted that the intervention module Figure 2-Figure 4 The intervention module is not shown in the figure, and can be flexibly set as needed. No further details are given here.

[0067] See also Figure 5 , Figure 5 A sleep intervention method provided in an embodiment of the present application is applied to a cloud processor in an in-ear brain-computer interface system. The in-ear brain-computer interface system also includes an in-ear device, and the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module electrode and an intervention module. The EEG acquisition module electrode is used to collect EEG signals from the user's ear canal during sleep, and the intervention module is used to intervene in the user in response to instructions from the cloud processor, and the user wears the in-ear device. The method specifically includes the following steps:

[0068] Step 501: Determine the user's sleep stage based on the ear canal EEG signal from the in-ear device.

[0069] Sleep stages can include light sleep and deep sleep. Specifically, sleep stages based on EEG signals are generally divided into wake, N1, N2, N3, and rapid eye movement (REM), with N1 and N2 belonging to light sleep and N3 to deep sleep. The user's sleep stage can be accurately determined based on ear canal EEG signals.

[0070] In a possible embodiment, the user's sleep stage can be determined based on the ear canal EEG signal combined with multimodal data. The multimodal data may include the user's vital signs data during sleep, such as blood oxygen data, heart rate data, etc., which will not be elaborated here.

[0071] It can be seen that the user's sleep stage is determined based on the ear canal EEG signal from the in-ear device. Since EEG signal is the gold standard for determining sleep stage, a more accurate sleep stage can be determined, which facilitates subsequent timely intervention and improves the user's sleep quality.

[0072] Step 502: Generate a first instruction corresponding to the sleep stage.

[0073] Among them, when the sleep stage is a light sleep stage, a first instruction corresponding to the light sleep stage is generated. At this time, several pre-modules include an electric pulse module, which can control the electric pulse module to generate a first electric pulse to promote the user's sleep.

[0074] In a possible embodiment, the plurality of pre-modules include an audio module, and the audio module can be controlled to generate sleep-aiding audio.

[0075] When the sleep stage is a deep sleep stage, a stop instruction may be generated to control the intervention module to stop intervention to prevent affecting the user's sleep.

[0076] When the sleep stage is close to the wakefulness stage, the plurality of pre-modules include an audio module, which can control the audio module to generate a wake-up audio.

[0077] It can be seen that the above-mentioned in-ear brain-computer interface system, in-ear device and sleep intervention method include a cloud processor and an in-ear device, the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module and an intervention module, the EEG acquisition module is used to collect the user's ear canal EEG signals during sleep, and the intervention module is used to intervene in the user in response to the instructions of the cloud processor, and the user wears the in-ear device; the cloud processor is used to receive the ear canal EEG signals from the in-ear device to determine the user's sleep stage and generate a first instruction corresponding to the sleep stage. The ear canal EEG signals during sleep can be collected, the user's sleep stage can be accurately identified, and instructions corresponding to the sleep stage can be generated in real time to intervene in the user, which greatly improves the user's sleep quality.

[0078] See also Figure 6 , Figure 6 A flow chart of another sleep intervention method provided in an embodiment of the present application is provided, which is applied to a cloud processor in an in-ear brain-computer interface system, wherein the in-ear brain-computer interface system also includes an in-ear device, and the cloud processor and the in-ear device are communicatively connected; the in-ear device includes electrodes of an EEG acquisition module, an intervention module, and a sound sensor, wherein the electrodes of the EEG acquisition module are used to collect EEG signals from the user's ear canal during sleep, the intervention module is used to intervene in the user in response to instructions from the cloud processor, and the sound sensor is used to collect sound data of the user during sleep, and the user wears the in-ear device; the method includes:

[0079] Step 601: Determine the user's sleep stage based on the ear canal EEG signal from the in-ear device.

[0080] Step 602: Generate a first instruction corresponding to the sleep stage.

[0081] Step 603: Receive sound data from the in-ear device, and generate a second instruction when recognizing that the sound data includes snoring.

[0082] The second instruction is used to control the intervention module to stop the user from snoring.

[0083] In a possible embodiment, the intervention module includes an electric pulse module, and the electric pulse module is configured to generate a second electric pulse in response to the second instruction.

[0084] The frequency and intensity of the second electrical pulse can be positively correlated with the severity of snoring, i.e., the more severe the snoring, the higher the frequency and intensity of the second electrical pulse. It should be noted that even the highest frequency and intensity of the second electrical pulse will not harm the user. Transcutaneous vagus nerve stimulation can be performed at the cavum concha to intervene in snoring. Upon detecting that the user's snoring has ceased, the cloud processor 110 can send a stop command to the electrical pulse module, stopping the second electrical pulse and preventing it from disturbing the user's sleep.

[0085] In a possible embodiment, the intervention module includes a vibration module, and the vibration module is configured to vibrate in response to the second instruction.

[0086] The frequency and intensity of the vibrations can be positively correlated with the severity of snoring. That is, the more severe the snoring, the higher the frequency and intensity of the vibrations. It should be noted that even at the highest frequency and intensity, the vibrations will not cause harm to the user. Vibration can be used to intervene in snoring. Once the cloud processor detects that the user's snoring has stopped, it can send a stop command to the vibration module, stopping the vibrations and preventing them from disturbing the user's sleep.

[0087] For easier understanding, see Figure 7 , Figure 7The operation logic diagram of an in-ear brain-computer interface system provided in an embodiment of the present application shows that the user wears the in-ear brain-computer interface system when he starts to sleep. The in-ear brain-computer interface system here can be in the form of an in-ear device. The sleep-aiding mode is started, and the system collects the user's EEG signals and / or multimodal data (snoring, PPG, etc.), transmits the EEG signals and / or multimodal data to the cloud for storage, calculation, and analysis, and the calculation results are generated in real time to determine the user's sleep period and implement precise intervention strategies based on the sleep period. Sleep staging based on EEG signals is generally divided into the wake stage W (wake), N1, N2, N3 and rapid eye movement (REM) period, of which N1 and N2 belong to the light sleep stage, and N3 belongs to the deep sleep stage. During the falling asleep stage, the first stage experienced is the light sleep stage, and sleep-aiding audio is played in the light sleep stage to assist the user to fall asleep quickly. Once it is detected that the user has entered the deep sleep stage, all audio will automatically stop playing. Ensure that the user has a higher sleep quality. Generally, this intelligent adjustment is performed during the first sleep cycle, and can be activated by the user as needed. Otherwise, the sleep aid mode remains off. During the last sleep cycle, when the user is close to awake, the in-ear alarm will automatically sound for a gentle wake-up. The in-ear alarm can also be manually set according to the user's needs; otherwise, it will remain off.

[0088] The closed-loop control based on the in-ear brain-computer interface system also focuses on monitoring and stopping snoring. The microphone on the earphones is used to monitor snoring data during sleep. At the same time, other multimodal data can be collected, including blood oxygen data and heart rate data based on PPG data, to comprehensively judge the individual's snoring data. Electrical stimulation electrodes are set at the corresponding parts of the concha cavity. The electrical stimulation electrodes are in contact with the ear skin, forming a closed-loop control with the above-mentioned snoring monitoring process. During sleep, the snoring level can be comprehensively judged and calculated through the collection of multimodal data such as EEG, snoring, and PPG data. Transcutaneous vagus nerve electrical stimulation can be used to intervene and stop snoring based on the results of snoring event detection. Snoring can also be stopped by earphone vibration.

[0089] In addition, in order not to affect people around, the system also sets an in-ear alarm to gently wake up when it detects that the light sleep stage of the sleep cycle is close to the awake state.

[0090] It should be noted that sleep monitoring intervention and snoring monitoring intervention can be carried out at the same time.

[0091] It can be seen that the above-mentioned in-ear brain-computer interface system, in-ear device and sleep intervention method include a cloud processor and an in-ear device, the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module and an intervention module, the EEG acquisition module is used to collect the user's ear canal EEG signals during sleep, and the intervention module is used to intervene in the user in response to the instructions of the cloud processor, and the user wears the in-ear device; the cloud processor is used to receive the ear canal EEG signals from the in-ear device to determine the user's sleep stage and generate a first instruction corresponding to the sleep stage. The ear canal EEG signals during sleep can be collected, the user's sleep stage can be accurately identified, and instructions corresponding to the sleep stage can be generated in real time to intervene in the user, which greatly improves the user's sleep quality.

[0092] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0093] The present application also provides a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments. The computer program product may be a software installation package, and the computer may comprise an electronic device.

[0094] It should be noted that, for the above-mentioned various embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. Those skilled in the art should know that this application is not limited by the order of the actions described, because some steps in the embodiments of the present application can be performed in other orders or simultaneously. In addition, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions, steps, modules or units involved are not necessarily required by the embodiments of the present application.

[0095] In the above embodiments, the embodiments of the present application have different focuses on the description of each embodiment. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0096] The steps of the method or algorithm described in the embodiments of the present application can be implemented in hardware or by a processor executing software instructions. The software instructions can be composed of corresponding software modules, which can be stored in RAM, flash memory, ROM, EPROM, electrically erasable programmable read-only memory (EEPROM), registers, hard disks, mobile hard disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be an integral part of the processor. The processor and storage medium can be located in an ASIC. In addition, the ASIC can be located in a terminal device or a management device. Of course, the processor and storage medium can also be present in a terminal device or a management device as discrete components.

[0097] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, they can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

[0098] The modules / units included in the devices and products described in the above embodiments may be software modules / units, hardware modules / units, or partly software modules / units and partly hardware modules / units. For example, for the devices and products applied to or integrated in the chip, the modules / units included therein may all be implemented in the form of hardware such as circuits, or at least part of the modules / units may be implemented in the form of software programs, which run on the processor integrated inside the chip, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits; for the devices and products applied to or integrated in the chip module, the modules / units included therein may all be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (such as chip, circuit module, etc.) or different components of the chip module, or at least part of the modules / units may be It is implemented in the form of a software program, which runs on the processor integrated inside the chip module, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits; for various devices and products applied to or integrated in the terminal equipment, the various modules / units contained therein can be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component (for example, chip, circuit module, etc.) or different components in the terminal equipment, or, at least some modules / units can be implemented in the form of a software program, which runs on the processor integrated inside the terminal equipment, and the remaining (if any) modules / units can be implemented in the form of hardware such as circuits.

[0099] The specific implementation methods described above further illustrate the purpose, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above description is only a specific implementation method of the embodiments of the present application and is not intended to limit the scope of protection of the embodiments of the present application. Any modifications, equivalent replacements, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the scope of protection of the embodiments of the present application.

Claims

1. An in-ear brain-computer interface system, characterized in that: include: A cloud processor and an in-ear device, wherein the cloud processor and the in-ear device are communicatively connected; The in-ear device includes an EEG acquisition module and an intervention module. The EEG acquisition module is used to collect EEG signals from the ear canal of the user during sleep. The intervention module is used to intervene in the user in response to instructions from the cloud processor. The user wears the in-ear device. The cloud-based processor is used to receive the ear canal electroencephalogram signal from the in-ear device to determine the sleep stage of the user and generate a first instruction corresponding to the sleep stage.

2. The system according to claim 1, wherein: The intervention module includes an electric pulse module, which is configured to generate a first electric pulse in response to a first instruction corresponding to the light sleep stage when the sleep stage is the light sleep stage.

3. The system according to claim 1, wherein: The intervention module includes an audio module, which is used to play sleep-aiding audio in response to a first instruction corresponding to the light sleep stage when the sleep stage is a light sleep stage; or, the audio module is used to play wake-up audio in response to a first instruction corresponding to the close-to-wakefulness stage when the sleep stage is a close-to-wakefulness stage.

4. The system according to claim 1, wherein: The in-ear device also includes a sound sensor, which is used to collect sound data of the user during sleep. The cloud processor is used to receive the sound data from the in-ear device and generate a second instruction when it is recognized that the sound data includes snoring.

5. The system according to claim 4, characterized in that The intervention module includes an electrical pulse module configured to generate a second electrical pulse in response to the second instruction.

6. The system according to claim 4, characterized in that The intervention module includes a vibration module, and the vibration module is configured to vibrate in response to the second instruction.

7. The system according to claim 1 or 4, characterized in that The in-ear device further includes a vital sign sensor, which is used to collect vital sign data of the user during sleep.

8. An in-ear device, characterized in that The in-ear device includes a main body and a charging compartment. The main body includes a shell, an EEG acquisition module, an intervention module and a main circuit board. The EEG acquisition module includes electrodes, which are arranged on the shell. The EEG acquisition module and the intervention module are connected to the main circuit board through built-in wires. The main circuit board is arranged inside the cavity wrapped by the shell, and the shell is provided with charging contacts; the charging compartment includes a charging interface, a compartment battery and a charging control board. The charging control board is connected to the battery, and the charging interface is used to contact the charging contacts to charge the main body.

9. A sleep intervention method, characterized in that: A cloud processor is used in an in-ear brain-computer interface system, wherein the in-ear brain-computer interface system also includes an in-ear device, and the cloud processor and the in-ear device are communicatively connected; the in-ear device includes an EEG acquisition module and an intervention module, wherein the EEG acquisition module is used to collect EEG signals from the user's ear canal during sleep, and the intervention module is used to intervene in the user in response to instructions from the cloud processor, and the user wears the in-ear device; the method includes: determining the user's sleep stage based on the ear canal EEG signal from the in-ear device; A first instruction corresponding to the sleep stage is generated.

10. A computer storage medium, characterized in that The computer storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the processor is caused to perform the method according to claim 9 .

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