WO2022100407A1

WO2022100407A1 - Intelligent eye mask, terminal device, and health management method and system

Info

Publication number: WO2022100407A1
Application number: PCT/CN2021/125596
Authority: WO
Inventors: 张慧; 李靖
Original assignee: 华为技术有限公司
Priority date: 2020-11-10
Filing date: 2021-10-22
Publication date: 2022-05-19
Also published as: CN114451874A

Abstract

An intelligent eye mask (100), a terminal device (200), and a health management method and system. The intelligent eye mask (100) is provided with a signal acquisition unit (110), a processing unit (120), and an EEG electrode (191). The signal acquisition unit (110) can detect an EEG signal corresponding to the EEG electrode (191), and a heart rate signal and a head motion signal of a wearer; the processing unit (120) can carry out epilepsy detection according to the EEG signal, the heart rate signal and the head motion signal, and when an epileptic seizure is detected, send epileptic seizure data to the terminal device (200) connected to the intelligent eye mask (100); the terminal device (200) displays, in response to an operation of a user, an epileptic seizure record generated on the basis of the obtained epileptic seizure data. The intelligent eye mask (100) can implement monitoring and management on epileptic diseases, and improves the accuracy of epilepsy detection results.

Description

Smart eye mask, terminal equipment, health management method and system

This application claims the priority of the Chinese patent application with the application number 202011244217.9 and the application name "Smart Eye Mask, Terminal Equipment, Health Management Method and System", which was submitted to the State Intellectual Property Office on November 10, 2020, the entire contents of which are by reference Incorporated in this application.

technical field

The present application relates to the technical field of health management, and in particular, to a smart eye mask, a terminal device, and a health management method and system.

Background technique

Epilepsy is a chronic disease caused by the sudden abnormal discharge of neurons in the brain, resulting in transient brain dysfunction. For patients with epilepsy, it is necessary to record the seizures of epilepsy to help doctors understand the patient's condition.

Seizures are unpredictable, recurring, and may occur during the day or at night. For epileptic seizures during the day, they can be found and recorded by the patient’s relatives and friends; while during sleep at night, the patient is generally alone, and it is difficult to detect epileptic seizures, which is not conducive to the management of epilepsy disease. Therefore, it is necessary to treat epileptic seizures during sleep. (i.e. sleep epilepsy) for monitoring.

SUMMARY OF THE INVENTION

In view of this, the present application provides a smart eye mask, a terminal device, and a health management method and system for monitoring and managing epilepsy diseases.

In order to achieve the above object, in the first aspect, the embodiments of the present application provide a smart eye mask, the smart eye mask is provided with a signal acquisition unit, a processing unit and an electroencephalography (electroencephalography, EEG) electrode, wherein,

The signal acquisition unit is used for:

detecting the EEG signal corresponding to the EEG electrode;

Detect the wearer's heart rate signal;

detecting the head movement signal of the wearer;

The processing unit is used for:

Perform epilepsy detection according to the EEG signal, the heart rate signal and the head movement signal;

When an epileptic seizure is detected, the epileptic seizure data is sent to the terminal device connected with the smart eye mask.

The smart goggles provided by the embodiments of the present application can detect epilepsy through EEG signals, heart rate signals, and head motion signals collected by the smart goggles, so as to monitor sleep epilepsy; Help users with epilepsy management. In addition, the brain waves of patients during epilepsy have obvious changes, and abnormal heartbeats, body convulsions, etc. will also occur. EEG signals can well reflect the changes of brain waves during epileptic seizures, and heart rate signals can reflect the user's heart rate during epileptic seizures. The head movement signal can reflect the head movement of the user during epileptic seizure, and the signal is less disturbed by body movement (such as hand movement), so the EEG signal, heart rate signal and head movement signal are combined for epilepsy detection. It can effectively improve the accuracy of epilepsy detection results.

In a possible implementation of the first aspect, the smart eye mask includes an eye mask body and a fixing band connected to both ends of the eye mask body, and the EEG electrodes are located on the eye mask body corresponding to the forehead of the human body. area. In this way, more accurate EEG signals can be collected.

In a possible implementation manner of the first aspect, the signal acquisition unit includes: an analog front-end chip, a photoplethysmography sensor, and an acceleration sensor, and the smart eye mask further includes: reference signals electrically connected to the analog front-end chip respectively. Electrodes, the analog front-end chip is used to output the EEG signal corresponding to the EEG electrode according to the signal collected by the reference electrode and the signal collected by the EEG electrode; the photoplethysmography sensor is used to detect the heart rate signal of the wearer ; The acceleration sensor is used to detect the head movement signal of the wearer.

In the above embodiment, by setting reference electrodes, the EEG signals corresponding to each EEG electrode are obtained according to the signals collected by the reference electrodes and the signals collected by each EEG electrode, which can improve the accuracy of the obtained EEG signals; moreover, the analog front-end chip has a signal filter. , amplification and analog-to-digital conversion and other functions, the use of analog front-end chips can further improve the accuracy of the obtained EEG signals, so the accuracy of epilepsy detection results can be improved through reference electrodes and analog front-end chips. In addition, the photoplethysmography sensor is used to measure the heart rate, which has a simple structure and can provide the portability of the smart eye mask and the comfort of the user; the signal collected by the acceleration sensor can well reflect the head movement and ensure the accuracy of the detection results.

In a possible implementation manner of the first aspect, the reference electrode is connected to the fixing band through a connecting wire. The setting method of the reference electrode is simple, and the complexity of the smart eye mask can be reduced.

In a possible implementation manner of the first aspect, a nasal mask is provided on the lower side of the middle of the eye mask body, and the reference electrode is provided on the nasal mask at a position corresponding to the nose tip of the human body. The setting method of this reference electrode is convenient for users to use, and a better EEG reference potential can be obtained.

In a possible implementation of the first aspect, a position corresponding to the bridge of the nose on the eye mask body is provided with a bridge strip matching the bridge of the nose. In this way, the user can adjust the nose bridge strip to make the nose mask fit the nose better, thereby improving the accuracy of the reference potential measured by the reference electrode.

In a possible implementation manner of the first aspect, the EEG electrodes include multiple, the smart eye mask further includes: a tightness adjustment module, and the processing unit is specifically configured to: detect the EEG corresponding to each of the EEG electrodes The signal quality of the signal, in the case that the signal quality of each EEG signal meets the requirements, the epilepsy detection is performed according to the EEG signal, the heart rate signal and the head motion signal; in the signal quality of any EEG signal If the requirements are not met, the tightness adjustment module is controlled to adjust the tightness of the smart eye mask.

In the above embodiment, when the signal quality of each EEG signal meets the requirements, epilepsy detection is performed according to the signal data collected by the signal acquisition unit, so that the accuracy of the epilepsy detection result can be ensured; when the signal quality of the EEG signal does not meet the requirements Under the circumstance of , control the tightness adjustment module to adjust the tightness of the smart eye mask, so that the EEG electrodes can be fully contacted with the skin to obtain better EEG signal quality, thereby improving the accuracy of epilepsy detection results.

In a possible implementation manner of the first aspect, the processing unit is further configured to: determine a target EEG signal from each EEG signal, and detect the signal quality of the target EEG signal. When the requirements are met, the sleep state of the user is detected according to the target EEG signal; when the signal quality of the target EEG signal does not meet the requirements, the tightness adjustment module is controlled to adjust the tightness of the smart eye mask; Send corresponding sleep state data to the terminal device.

In the above embodiment, the target EEG signal is determined from each EEG signal of the signal data, and when the signal quality of the target EEG signal meets the requirements, the sleep state of the user is detected according to the signal data, so as to ensure the accuracy of the sleep detection result, And can improve the processing efficiency; when the signal quality of the target EEG signal does not meet the requirements, control the tightness adjustment module to adjust the tightness of the smart eye mask, so that the EEG electrode can be fully contacted with the skin to obtain better EEG signal quality , thereby improving the accuracy of sleep detection results; in addition, the smart eye mask can send corresponding sleep state data to the terminal device to help users manage sleep.

In a possible implementation manner of the first aspect, at least two EEG electrodes are symmetrically arranged on both sides of the smart eye mask, and the processing unit is specifically configured to: detect the sleeping posture of the user according to the head motion signal; If the sleeping position of the user is lying on the side, the EEG signal corresponding to the EEG electrode on the same side of the sleeping position of the user is determined as the target EEG signal; if the sleeping position of the user is lying flat, the EEG signal of each EEG The EEG signal with the best signal quality among the signals is determined as the target EEG signal.

In the above embodiment, at least two EEG electrodes are symmetrically arranged on both sides of the smart eye mask, which can adapt to different sleeping positions of users and improve the accuracy of sleep detection results. In addition, the smart eye mask detects the user's sleeping position according to the head motion signal; when the user's sleeping position is lying on his side, the EEG signal collected by the EEG electrode on the same side as the user's sleeping position is determined as the target EEG signal; When the posture is lying flat, the EEG signal with the best signal quality among the EEG signals is determined as the target EEG signal, so that when the user is determined to lie on his side, there is no need to judge the signal quality of each EEG signal, so it can be used to a certain extent. Improve detection efficiency, and can reduce power consumption.

In a possible implementation manner of the first aspect, the processing unit is specifically configured to: determine the EEG signal with the best signal quality among the EEG signals as the target EEG signal. This method does not need other sensor signals when determining the target EEG signal, and the detection method is relatively simple.

In a possible implementation manner of the first aspect, the smart eye mask further includes: a sleep stimulation module, and the processing unit is further configured to control the sleep stimulation module to output a sleep stimulation module according to the EEG signal and the detected sleep state. Stimuli used to improve the user's sleep state. This can improve the user's sleep quality by stimulating the signal.

In a possible implementation of the first aspect, the epileptic seizure data includes a plurality of the following data: epileptic seizure time, epileptic seizure duration, severity of epileptic seizure, and the signal acquisition unit before the seizure The EEG signal, heart rate signal and head motion signal detected between the first moment and the second moment after the end of the epileptic seizure.

In a second aspect, an embodiment of the present application provides a health management method, which is applied to a terminal device, including:

Obtain the epileptic seizure data detected by the smart eye mask described in the first aspect;

In response to the user's first operation, epileptic seizure records generated based on the acquired epileptic seizure data are displayed, and each of the epileptic seizure records includes the severity, onset time, and onset duration of the seizure.

The first operation may be a user's voice command input operation, or may be a user's click operation on a target option (such as an epilepsy record card provided by a terminal device in a health management application). The terminal device can display epileptic seizure records on the epilepsy record details page.

In the health management method provided by the embodiments of the present application, a terminal device can acquire epileptic seizure data from a smart eye mask, and can respond to user operations to display an epileptic seizure record generated based on the acquired epileptic seizure data, which can facilitate users to view and manage epileptic seizures .

In a possible implementation of the second aspect, the method further includes: in response to the second operation of the user, acquiring epileptic seizure data input by the user; and updating the epileptic seizure record.

The second operation may include various operations for the user to manually add epileptic seizure data. For example, the terminal device may provide an add control on the epilepsy record details page, and the user may click on the control and enter the epileptic seizure data in the opened epilepsy record adding interface. After that, confirm the added seizure record by confirming the operation.

By providing the function of manually adding epileptic seizure data, the terminal device can facilitate the user to record the epileptic seizure data, thereby improving the convenience for the user to manage epilepsy.

In a possible implementation manner of the second aspect, the method further includes: when it is determined according to the epileptic seizure data that the user is in a state of epileptic seizure and the severity of the epileptic seizure reaches a target severity, reminding the target to contact the people. In this way, the guardian can be reminded in time when the patient has a severe epileptic seizure, and the adverse effect of the epileptic seizure on the patient can be reduced.

In a possible implementation of the second aspect, the reminding the target contact includes:

sending help information to the target contact;

And/or, calling the target contact, and playing a help recording to the target contact, where both the help information and the help recording indicate the severity of the seizure.

By using help information or help calls, the guardian can be notified in time; and the severity of epileptic seizures is indicated in the help information and help recording, which can facilitate the guardian to understand the patient's epilepsy situation and take better countermeasures.

In a possible implementation manner of the second aspect, before the reminding the target contact, the method further includes:

In response to the user's third operation, displaying the smart eye mask setting interface;

In response to the fourth operation performed by the user in the smart eye mask setting interface, the emergency calling function is activated, and the target contact set by the user is saved.

Among them, the terminal device can provide device editing options corresponding to various paired smart health devices (such as smart goggles), and the third operation can be a user's click operation on the device editing options corresponding to the smart goggles; in addition, in the smart goggle device interface An emergency call option may be provided, and the fourth operation may include the operation of the user clicking the emergency call option, and the operation of starting the function of automatically sending the help message, the function of automatically dialing the call for help, and/or setting the emergency contact in the opened emergency call interface. .

By providing the above emergency call setting function, the terminal device can facilitate the user to perform personalized emergency call setting for epileptic seizures, thereby improving user experience.

In a possible implementation of the second aspect, the method further includes: in response to a fifth operation performed by the user in the smart eyewear setting interface, controlling the smart eyewear to turn on or off a target function, the target Functions include epilepsy monitoring functions for continuous epilepsy detection and/or sleep monitoring functions for continuous sleep state detection.

The terminal device may provide an epilepsy monitoring option and/or a sleep monitoring option in the smart eye mask setting interface, and the fifth operation may be a switch operation performed by the user on the epilepsy monitoring option and/or the sleep monitoring option.

By providing switch options for the epilepsy monitoring function and the sleep monitoring function on the terminal device, the convenience for users to set the smart eye mask can be improved.

In a possible implementation of the second aspect, the method further includes: in response to a sixth operation of the user, displaying statistical data generated based on the epileptic seizure data, the statistical data including any severity corresponding to The number of seizures and the duration of seizures in different statistical periods.

The terminal device may provide a statistical control on the epilepsy record details page, and the sixth operation may be an operation of the user clicking the statistical control.

By providing the epileptic seizure statistics function on the terminal device, it is convenient for the user to know the epileptic seizures of the patient in each cycle.

In a third aspect, an embodiment of the present application provides a health management apparatus, which is applied to a terminal device, including:

a communication module for acquiring epileptic seizure data detected by the smart goggles described in the first aspect;

The display module is used for displaying the epileptic seizure records generated based on the acquired epileptic seizure data in response to the first operation of the user, and each of the epileptic seizure records includes the severity, onset time and onset duration of the seizure.

In a possible implementation manner of the third aspect, the apparatus further includes: an input module, configured to acquire epileptic seizure data input by the user in response to the second operation of the user;

The display module is also used to update the epileptic seizure record.

In a possible implementation manner of the third aspect, the apparatus further includes: a processing module configured to, when it is determined according to the epileptic seizure data that the user is in a state of epileptic seizure, and the severity of the epileptic seizure reaches a target severity Next, the communication module is instructed to remind the target contact.

In a possible implementation manner of the third aspect, the communication module is specifically configured to:

sending help information to the target contact;

In a possible implementation manner of the third aspect, the display module is further configured to: display a smart eye mask setting interface in response to a third operation of the user before the processing module instructs the communication module to remind the target contact ;

The processing module is further configured to: in response to a fourth operation performed by the user in the smart eye mask setting interface, start an emergency call function, and save the target contact set by the user.

In a possible implementation manner of the third aspect, the processing module is further configured to: in response to a fifth operation performed by the user in the setting interface of the smart eye mask, control the smart eye mask to turn on or off the target function, so that the The target function is an epilepsy monitoring function for continuous epilepsy detection or a sleep monitoring function for continuous sleep state detection.

In a possible implementation manner of the third aspect, the display module is further configured to: in response to a sixth operation of the user, display statistical data generated based on the epileptic seizure data, the statistical data including any serious The degree corresponds to the number of epileptic seizures and the duration of epileptic seizures in units of different statistical periods.

In a fourth aspect, an embodiment of the present application provides a terminal device, including: a memory and a processor, where the memory is configured to store a computer program; the processor is configured to execute the second aspect when the computer program is invoked method.

For the beneficial effects of the third aspect and the fourth aspect, reference may be made to the relevant descriptions in the second aspect, which will not be repeated here.

In a fifth aspect, an embodiment of the present application provides a health management system, including: the smart goggles described in the first aspect and the terminal device described in the fourth aspect.

For the beneficial effects of the fifth aspect, reference may be made to the relevant descriptions in the first aspect and the second aspect, which will not be repeated here.

In a sixth aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the method described in the second aspect or any implementation manner of the second aspect.

In a seventh aspect, an embodiment of the present application provides a computer program product that, when the computer program product runs on a terminal device, enables the terminal device to execute the method described in the second aspect or any implementation manner of the second aspect.

In an eighth aspect, an embodiment of the present application provides a chip system, including a processor, where the processor is coupled to a memory, and the processor executes a computer program stored in the memory to implement the second aspect or any of the second aspect. The method of one embodiment. Wherein, the chip system may be a single chip or a chip module composed of multiple chips.

It can be understood that, for the beneficial effects of the sixth aspect to the eighth aspect, reference may be made to the relevant description in the second aspect, which will not be repeated here.

Description of drawings

1 is a schematic structural diagram of a health management system provided by an embodiment of the present application;

FIG. 2 is a schematic diagram of functional modules of the smart eye mask provided by the embodiment of the present application;

3 is a schematic structural diagram of a smart eye mask provided in an embodiment of the present application;

FIG. 4 is another schematic structural diagram of the smart eye mask provided by the embodiment of the present application;

FIG. 5 is a schematic structural diagram of a terminal device provided by an embodiment of the present application;

6 is a schematic flowchart of epilepsy detection provided by an embodiment of the present application;

FIG. 7 is a schematic flowchart of sleep detection provided by an embodiment of the present application;

8-12 are schematic diagrams of some application interfaces provided by the embodiments of the present application;

FIG. 13 is a schematic structural diagram of a health management apparatus provided by an embodiment of the present application.

Detailed ways

The embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. The terms used in the implementation part of the embodiments of the present application are only used to explain the specific embodiments of the present application, and are not intended to limit the present application.

In order to monitor sleep epilepsy, a feasible technical solution is to detect epileptic seizures through smart bracelets, smart watches, etc. that can be worn on the wrist or arm. Taking a smart watch as an example, a photoplethysmograph (PPG) sensor, a gyroscope, and an acceleration (accelerator, ACC) sensor can be set on the smart watch to monitor the user's heart rate change through the PPG sensor, and monitor the user's heart rate through the gyroscope and ACC sensor. The user's movement changes are combined with the user's heart rate changes and movement changes to detect the user's epileptic seizures.

Because the heart rate changes in mild epilepsy are small and the hand twitching is not obvious, the above scheme has a low detection accuracy for mild epileptic seizures, and this method is easily disturbed by movement, such as hand movement during sleep. Motion interference, and thus also affects the accuracy of the detection results.

To this end, the embodiments of the present application provide a health management system to monitor and manage sleep epilepsy and improve the accuracy of epilepsy detection.

FIG. 1 is a schematic structural diagram of a health management system provided by an embodiment of the present application. As shown in FIG. 1 , the epilepsy monitoring system provided by this embodiment may include: a smart eye mask 100 and a terminal device 200 .

The terminal device 200 may be an electronic device such as a mobile phone, a tablet, or a computer, and a mobile phone is used as an example for illustration in FIG. 1 . A wireless communication connection can be established between the smart eye mask 100 and the terminal device 200 through short-range communication technologies such as Bluetooth or wireless-fidelity (Wi-Fi) or other wireless communication technologies, so as to facilitate the use of the user; A wired communication connection is established by using a universal serial bus (USB) interface (not shown) to provide a more flexible data transmission manner. In this embodiment, a wireless communication connection is used as an example for illustration.

In this embodiment, the smart eye mask 100 can monitor the EEG information, heart rate information, and motion information of the user (ie, the wearer), and can perform epilepsy detection based on these information; the terminal device 200 can obtain epilepsy seizure data from the smart eye mask 100 , and can be used by users to record epileptic seizure data during the day, as well as obtain epileptic seizure data recorded by other smart health devices, to help users better monitor and manage epilepsy.

FIG. 2 is a schematic diagram of functional modules of a smart eye mask provided by an embodiment of the present application, FIG. 3 is a schematic structural diagram of a smart eye mask provided by an embodiment of the present application, and FIG. 4 is another schematic structural diagram of the smart eye mask provided by an embodiment of the present application .

As shown in FIG. 2, the smart eye mask 100 may include: a signal acquisition unit 110, a processing unit 120, a data buffering module 130, a tightness adjustment module 140, a sleep stimulation module 150, a wireless communication module 160, a notification module 170, a power supply module 180, and a EEG electrodes 191 and the like. The signal acquisition unit 110 may include sensor detection modules such as an EEG detection module 111, a heart rate detection module 112, and a motion detection module 113. The EEG detection module 111 may include an analog front end (AFE) chip 1111; a heart rate detection module 112 may include a PPG sensor 1121 ; the motion detection module 113 may include an ACC sensor 1131 .

It can be understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the smart eye mask 100 . In other embodiments of the present application, the smart eyewear 100 may include more or less components than shown, or combine some components, or separate some components, or arrange different components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The EEG electrode 191 is used to monitor the changes of the user's brain waves, wherein, the EEG electrode 191 may include one or more, so as to improve the accuracy of the detection result. In FIGS. 3 and 4 , three EEG electrodes 191 are used as the example to illustrate. The EEG electrodes 191 may be located on the smart eye mask 100 at positions corresponding to the forehead of the human body. As shown in FIG. 3 and FIG. 4 , the three EEG electrodes 191 are respectively located on the smart eye mask 100 and the left frontal pole (Fp1) area of the human body. , the positions corresponding to the right frontal pole (Fp2) area and the middle frontal pole (FpZ) area, that is, after the user wears the smart eye mask 100, the three EEG electrodes 191 are located at the user's Fp1 and Fp2 respectively. and the FpZ region.

It can be understood that the EEG electrode 191 may also be located on the smart eye mask 100 at a position corresponding to the left frontal (F3) area or the right frontal (F4) area of the human body. In this embodiment, the EEG electrode 191 The specific location of the sensor is not particularly limited, as long as the EEG signal with better quality can be detected.

In order to improve the accuracy of the detection result, the smart eye mask 100 may further include a reference electrode (REF) 192 for providing a reference potential for the EEG electrode 191 , and the EEG signal recorded by the EEG detection module 111 is collected by the EEG electrode 191 The difference between the signal and the signal acquired by the reference electrode 192 . The reference electrode 192 can be placed at a position close to zero potential on the human body, that is, after the user wears the smart eye mask 100, the reference electrode 192 is located at a position close to zero potential on the user's body; The back, the tip of the nose, or other locations that are less affected by physiology and external influences.

As shown in FIG. 3 , the smart eye mask 100 may include an eye mask body 11 and a fixing band 12 , and the reference electrode 192 may be connected to the fixing band 12 of the smart eye mask 100 through a connecting wire. When in use, the user can paste the reference electrode 192 on the earlobe , behind the ear or at the tip of the nose.

As shown in FIG. 4 , a nasal mask 13 may also be provided on the lower side of the middle of the eye mask body 11 , and a reference electrode 192 may be provided on the nasal mask 13 for the convenience of the user. In specific settings, the reference electrode 192 may be located on the nasal mask 13 at a position opposite to the nose tip of the human body, so as to improve the accuracy of the EEG signal detection result.

The AFE chip 1111 is electrically connected to each EEG electrode 191 and the reference electrode 192, respectively, and is used to determine the EEG signal according to the signal collected by the EEG electrode 191 and the signal collected by the reference electrode 192, and perform filtering, amplification, and analog-to-digital conversion on the EEG signal. , and then transmitted to the processing unit 120 .

The PPG sensor 1121 is mainly used to monitor the change of the user's heart rate, and it can collect the PPG signal on the user's forehead. The PPG sensor 1121 can be arranged at a position such as the upper edge or the side surface of the eyecup body 11 where it can closely fit the skin and has better comfort. One PPG sensor 1121 can be provided to improve the portability of the eye mask; multiple PPG sensors can also be provided to improve the accuracy of the detection results. The specific implementation can be selected as needed. In this embodiment, one PPG sensor 1121 is used as an example for example. Sexual description. The heart rate detection module 112 uses the PPG sensor 1121 to detect the heart rate signal (ie the PPG signal), which can improve the comfort of the user; it is understandable that the heart rate detection module 112 can also use the piezoelectric sensor to collect the heart rate signal to improve the accuracy of the detection result .

The ACC sensor 1131 is mainly used to monitor the movement of the user's head, and it can collect the ACC signal of the user's head. Similar to the PPG sensor 1121, the ACC sensor 1131 can also be arranged on the upper edge or the side of the eyecup body 11. One can be arranged to improve the portability of the eyecup; The specific implementation can be selected as required. In this embodiment, an ACC sensor 1131 is used as an example for illustration.

It can be understood that the motion detection module 113 may also include an angular velocity sensor such as a gyroscope to improve the accuracy of head motion detection, and the motion detection module 113 may also use an inertial measurement unit integrated with an ACC sensor and a gyroscope. Measurement unit, IMU) implementation, and the specific implementation can be selected according to needs. In the figure, the motion detection module 113 only includes the ACC sensor 1131 as an example for exemplary illustration.

The processing unit 120 is a general control unit of the smart eye mask 100, which may adopt a processing unit such as a microcontroller unit (MCU) or a digital signal processor (DSP). The processing unit 120 can obtain the signal data collected by the signal collecting unit 110, perform filtering and denoising processing on the obtained signal data, and can further detect the user's epileptic seizures in real time according to these signal data, so as to realize epilepsy monitoring, specifically epilepsy detection. The process can be found in the subsequent content.

The processing unit 120 may also detect the sleep state of the user according to the signal data collected by the signal collection unit 110, and implement sleep monitoring, so as to facilitate the user to perform sleep management. Among them, the sleep state can include: falling asleep, light sleep, deep sleep, deep sleep and rapid eye movement sleep, etc. The user's heart rate, EEG and exercise state will be different in different sleep states. When detecting the user's sleep state, The detection may be performed according to one of the EEG signal, the PPG signal and the ACC signal to improve the detection efficiency; the detection may also be performed according to a plurality of the EEG signal, the PPG signal and the ACC signal to improve the accuracy of sleep detection. Specifically, a pre-trained sleep state identification model or other detection methods may be used to detect the sleep state, which is not particularly limited in this embodiment. For the convenience of description, the following embodiments of the present application use a sleep state identification model to perform sleep detection based on an EEG signal, a PPG signal, and an ACC signal as an example for illustrative description. For the specific sleep detection process, refer to the subsequent method embodiments, here No longer.

For the convenience of the user, a function switch key (not shown) can be set on the smart eye mask 100, and the user can set the smart eye mask to activate the epilepsy monitoring function and/or the sleep monitoring function through the key.

It can be understood that the processing unit 120 can also transmit the signal data collected by the signal acquisition unit 110 to the terminal device 200 through the wireless communication module 160, and the terminal device 200 can perform epilepsy detection and sleep detection; The detection function activated by the smart eye mask.

Considering that one or all of the EEG electrodes may be in poor contact due to loose wearing, turning over, sleeping on the side, etc., which will affect the detection result, therefore, in order to improve the accuracy of the detection result, in this embodiment, the processing unit 120 obtains the After the EEG signal, the signal quality of the EEG signal can be detected. If the signal quality does not meet the requirements, the tightness adjustment module 140 can be controlled to adjust the tightness of the smart eye mask, so that the EEG electrode is fully in contact with the skin, so as to obtain better EEG signal quality.

Wherein, the tightness adjustment module 140 may include a fixing belt adjusting device for adjusting the length of the fixing belt 12 , the device may include a motor and a transmission mechanism, etc., the transmission mechanism is respectively connected with the motor and the fixing belt 12 , and the motor may be in the processing unit 120 . The transmission mechanism is driven to move under control to increase or shorten the length of the fixing belt 12 .

The tightness adjustment module 140 can also be implemented with an inflatable device to improve comfort. Specifically, the inflatable device can be arranged near the EEG electrode, and is used to apply pressure to the EEG electrode toward the skin, so that the EEG electrode is close to the skin. The inflating device may include an air pump, an air bag, and a trachea. The air bag communicates with the air pump through the air tube. The air pump can inflate the air bag through the air tube under the control of the processing unit 120 to pressurize the air bag to the EEG electrode. An air bag can be set near each EEG electrode, each air bag has a corresponding trachea, and each air bag can use a different air pump or the same air pump; or a large air bag can be used to simultaneously pressurize each EEG electrode Control, for example, an array air bag can be used, the array air bag covers each EEG electrode, and during inflation, part or all of the air bag units of the array air bag can be controlled to inflate, so as to pressurize some or all of the EEG electrodes.

In order to improve the user's sleep quality, in this embodiment, the processing unit 120 may control the sleep stimulation module 150 to output stimulation signals to stimulate the brain according to the acquired EEG signal and the detected sleep state, so as to improve the user's sleep state. The sleep stimulation module 150 may include an audio stimulation module and/or a micro-electric stimulation module.

The audio stimulation module is used to realize the audio function, which may include a speaker and an audio module for audio digital-to-analog conversion, etc., and the processing unit 120 can use a relevant audio control method to control the audio stimulation module to play music or other audio signals to improve user sleep. state. For example, before the user falls asleep, the type of audio to be played can be determined according to the energy ratio of each frequency band of the EEG signal, and then it can be determined whether the user's drowsiness has increased according to the EEG signal; The type of audio played can be adjusted; after the user falls asleep, the music can be stopped, or an audio signal of a certain frequency can be played, and the user can be guided to enter the slow-wave sleep period by adjusting the frequency and volume of the audio signal.

The micro-electric stimulation module is used to realize micro-current stimulation, which can include a pulse generator and stimulation electrodes, etc. The processing unit 120 can control the micro-electric stimulation module to output stimulation current by using the relevant micro-electric control method, so as to improve the sleep state of the user. For example, after the user falls asleep, parameters such as the waveform, intensity, frequency, and cycle period of the stimulation current can be controlled according to the user's EEG signal, so as to guide the user to enter the slow-wave sleep period. The control methods corresponding to the audio stimulation module and the micro-electrical stimulation module may adopt various current related algorithms. The above-mentioned audio control method and micro-electrical control method are only examples, and can be selected according to needs during specific implementation. This is not particularly limited.

The data buffering module 130 is used for buffering the signal data collected by the signal collecting unit 110 , which may be an independent storage device or may be integrated in the processing unit 120 . When an epileptic seizure is detected, the processing unit 120 can generate epileptic seizure data and send it to the terminal device 200; in order to improve flexibility, the processing unit 120 can also store the epileptic seizure data in the data cache module 130, and the subsequent user triggers data synchronization At the same time, the signal data in the data buffer module 130 is synchronized to the terminal device 200, so that retransmission can also be performed in the case of a transmission failure, and thus the reliability of data management can also be improved. Among them, the seizure data can include epilepsy detection results (which can include seizure time, duration and severity of seizures, etc.), and can include signal data a few minutes before the seizure, during the seizure, and a few minutes after the end of the seizure, That is, the signal data between the first moment before the epileptic seizure and the second moment after the epileptic seizure ends. Similarly, the processing unit 120 may generate sleep state data according to the sleep state detection result and send it to the terminal device 200 in real time, or cache it in the data cache module 130, where the sleep state data may include the detected sleep state and the sleep state corresponding to the sleep state time.

The wireless communication module 160 can provide a wireless communication solution including wireless local area networks (WLAN) (such as Wi-Fi network), Bluetooth, etc. applied on the smart eyewear 100 . The processing unit 120 may communicate with the terminal device 200 through the wireless communication module 160 , and send the detected epileptic seizure data and sleep state data to the terminal device 200 .

The notification module 170 is used to indicate user operations, which may include a speaker, a motor, and/or an indicator light, etc., for performing sound prompts, vibration prompts, and/or light prompts. The notification module 170 can also be used to indicate charging status, power change and working status, etc.

The power module 180 is used to supply power to the smart eyewear 100, and it may include a battery and a power management unit. The power management unit can receive charging input from a wired charger through a USB interface, or can receive wireless charging input through a wireless charging coil, so as to charge the battery ; And can monitor parameters such as battery capacity and battery health status. The power management unit may be an independent device or may be integrated in the processing unit 120 .

Among them, the above-mentioned EEG electrodes 191 and PPG sensors 1121 can be arranged on the inner side of the smart eye mask 100 for contact with the skin; The parts of the wireless communication module 160, the notification module 170 and the power supply module 180 that do not need to be exposed can be arranged in the interlayer of the eye mask body 11, and the parts that need to be exposed can be arranged on the outer surface of the smart eye mask 100. The setting positions can be selected according to actual needs, which are not particularly limited in this embodiment.

The above-mentioned FIGS. 3 and 4 exemplarily show two structures of the smart eye mask 100 , and the difference mainly lies in the difference between the fixing strap 12 and the nasal mask 13 .

As shown in FIG. 3 , the fixing straps 12 may be ear-mounted fixing straps 12 . Correspondingly, there are two fixing straps 12 , and two fixing straps 12 are respectively connected to the two sides of the eyecup body 11 . As shown in FIG. 4 , the fixing strap 12 can also be a head-mounted fixing strap 12 , which can include one as shown in FIG. 4 . One end of the fixing strap 12 is connected to one side of the eye mask body 11 , and the other end is connected to the eye mask body. The other side of 11 is connected.

It can be understood that, the head-mounted fixing belt 12 may also include two, one of which is connected to one side of the eyecup body 11 , the other fixing belt 12 is connected to the other side of the eyecup body 11 , and the two fixing belts 12 can be joined together by knots, Velcro or connecting buckles etc. In addition, FIG. 3 and FIG. 4 are only used to illustrate different implementations of the fixing strap 12 , which are not intended to limit the present application. The smart eyewear 100 shown in FIG. 3 can also use the head-mounted fixing strap 12 , as shown in FIG. 4 The smart eye mask 100 can also use the ear-hook type fixing belt 12 .

In order to improve the user's comfort and wearing convenience, the fixing strap 12 can be an elastic fixing strap 12, which can also make the eye mask body 11 better fit the skin.

In order to improve the accuracy of the signal detection result of the reference electrode 192 , the position of the eye mask body 11 corresponding to the nose bridge can be provided with a nose bridge strip 14 that matches the nose bridge, and the user can adjust the nose bridge strip 14 to make the nose mask 13 better fit nose.

The eye mask body 11 may be made of materials such as fiber fabric, elastic foam, plastic, metal and/or silica gel, and the specific material is not particularly limited in this embodiment.

In this embodiment, the terminal device 200 may be a portable electronic device such as a mobile phone or a tablet, or a non-portable electronic device such as a computer. The embodiment of the present application takes the terminal device 200 as a mobile phone as an example for illustration.

FIG. 5 is a schematic structural diagram of a terminal device provided by an embodiment of the application. As shown in FIG. 5 , the terminal device 200 may include a processor 210, an external memory interface 220, an internal memory 221, a USB interface 230, a charging management module 240, and a power management module. Module 241, Battery 242, Antenna 1, Antenna 2, Mobile Communication Module 250, Wireless Communication Module 260, Audio Module 270, Speaker 270A, Receiver 270B, Microphone 270C, Headphone Interface 270D, Sensor Module 280, Key 290, Motor 291, Indication 292, camera 293, display screen 294, and subscriber identification module (subscriber identification module, SIM) card interface 295 and so on. The sensor module 280 may include a pressure sensor 280A, a gyroscope sensor 280B, an air pressure sensor 280C, a magnetic sensor 280D, an acceleration sensor 280E, a distance sensor 280F, a proximity light sensor 280G, a fingerprint sensor 280H, a temperature sensor 280J, a touch sensor 280K, and ambient light Sensor 280L, Bone Conduction Sensor 280M, etc.

It can be understood that the structures illustrated in the embodiments of the present invention do not constitute a specific limitation on the terminal device 200 . In other embodiments of the present application, the terminal device 200 may include more or less components than those shown in the drawings, or combine some components, or separate some components, or arrange different components. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

The terminal device 200 can receive the epileptic seizure data and sleep state data detected by the smart eye mask 100 through the wireless communication module 260 or the USB interface 230, and can provide the user with epilepsy management services according to the epileptic seizure data, and provide the user with sleep management according to the sleep state data. Serve. In addition, the terminal device 200 can also upload the epileptic seizure data and sleep state data of the user to the cloud for storage, so as to be further analyzed by the subsequent doctor.

The processor 210 may include one or more processing units, for example, the processor 210 may include an application processor (application processor, AP), a modem processor, a graphics processor (sraphics processing unit, GPU), an image signal processor (image signal processor, ISP), controller, memory, video codec, digital signal processor (digital signal processor, DSP), baseband processor, and/or neural-network processing unit (NPU) Wait. Wherein, different processing units may be independent devices, or may be integrated in one or more processors.

The controller may be the nerve center and command center of the terminal device 200 . The controller can generate an operation control signal according to the instruction operation code and timing signal, and complete the control of fetching and executing instructions.

A memory may also be provided in the processor 210 for storing instructions and data. In some embodiments, the memory in processor 210 is cache memory. The memory may hold instructions or data that have just been used or recycled by the processor 210 . If the processor 210 needs to use the instruction or data again, it can be called directly from the memory. Repeated accesses are avoided, and the waiting time of the processor 210 is reduced, thereby improving the efficiency of the system.

In some embodiments, the processor 210 may include one or more interfaces. The interface may include an integrated circuit (inter-integrated circuit, I2C) interface, an integrated circuit built-in audio (inter-integrated circuit sound, I2S) interface, a pulse code modulation (pulse code modulation, PCM) interface, a universal asynchronous transceiver (universal asynchronous transmitter) receiver/transmitter, UART) interface, mobile industry processor interface (MIPI), general-purpose input/output (GPIO) interface, subscriber identity module (SIM) interface, and / or universal serial bus (universal serial bus, USB) interface, etc.

The I2C interface is a bidirectional synchronous serial bus that includes a serial data line (SDA) and a serial clock line (SCL). In some embodiments, the processor 210 may contain multiple sets of I2C buses. The processor 210 can be respectively coupled to the touch sensor 280K, the charger, the flash, the camera 293 and the like through different I2C bus interfaces. For example, the processor 210 can couple the touch sensor 280K through the I2C interface, so that the processor 210 and the touch sensor 280K communicate with each other through the I2C bus interface, so as to realize the touch function of the terminal device 200 .

The I2S interface can be used for audio communication. In some embodiments, the processor 210 may contain multiple sets of I2S buses. The processor 210 may be coupled with the audio module 270 through an I2S bus to implement communication between the processor 210 and the audio module 270 . In some embodiments, the audio module 270 can transmit audio signals to the wireless communication module 260 through the I2S interface, so as to realize the function of answering calls through the Bluetooth headset.

The PCM interface can also be used for audio communications, sampling, quantizing and encoding analog signals. In some embodiments, the audio module 270 and the wireless communication module 260 may be coupled through a PCM bus interface. In some embodiments, the audio module 270 can also transmit audio signals to the wireless communication module 260 through the PCM interface, so as to realize the function of answering calls through the Bluetooth headset. Both the I2S interface and the PCM interface can be used for audio communication.

The UART interface is a universal serial data bus used for asynchronous communication. The bus may be a bidirectional communication bus. It converts the data to be transmitted between serial communication and parallel communication. In some embodiments, a UART interface is typically used to connect the processor 210 with the wireless communication module 260 . For example, the processor 210 communicates with the Bluetooth module in the wireless communication module 260 through the UART interface to implement the Bluetooth function. In some embodiments, the audio module 270 can transmit audio signals to the wireless communication module 260 through the UART interface, so as to realize the function of playing music through the Bluetooth headset.

The MIPI interface can be used to connect the processor 210 with peripheral devices such as the display screen 294 and the camera 293 . MIPI interfaces include camera serial interface (CSI), display serial interface (DSI), etc. In some embodiments, the processor 210 communicates with the camera 293 through a CSI interface to implement the shooting function of the terminal device 200 . The processor 210 communicates with the display screen 294 through the DSI interface to implement the display function of the terminal device 200 .

The GPIO interface can be configured by software. The GPIO interface can be configured as a control signal or as a data signal. In some embodiments, the GPIO interface may be used to connect the processor 210 with the camera 293, the display screen 294, the wireless communication module 260, the audio module 270, the sensor module 280, and the like. The GPIO interface can also be configured as I2C interface, I2S interface, UART interface, MIPI interface, etc.

The USB interface 230 is an interface that conforms to the USB standard specification, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, and the like. The USB interface 230 can be used to connect a charger to charge the terminal device 200, and can also be used to transmit data between the terminal device 200 and peripheral devices. It can also be used to connect headphones to play audio through the headphones. This interface can also be used to connect other terminal devices, such as AR devices.

It can be understood that the interface connection relationship between the modules illustrated in the embodiment of the present invention is only a schematic illustration, and does not constitute a structural limitation of the terminal device 200 . In other embodiments of the present application, the terminal device 200 may also adopt different interface connection manners in the foregoing embodiments, or a combination of multiple interface connection manners.

The charging management module 240 is used to receive charging input from the charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 240 may receive charging input from the wired charger through the USB interface 230 . In some wireless charging embodiments, the charging management module 240 may receive wireless charging input through the wireless charging coil of the terminal device 200 . While the charging management module 240 charges the battery 242 , it can also supply power to the terminal device through the power management module 241 .

The power management module 241 is used to connect the battery 242 , the charging management module 240 and the processor 210 . The power management module 241 receives input from the battery 242 and/or the charging management module 240, and supplies power to the processor 210, the internal memory 221, the external memory, the display screen 294, the camera 293, and the wireless communication module 260. The power management module 241 can also be used to monitor parameters such as battery capacity, battery cycle times, battery health status (leakage, impedance). In some other embodiments, the power management module 241 may also be provided in the processor 210 . In other embodiments, the power management module 241 and the charging management module 240 may also be provided in the same device.

The wireless communication function of the terminal device 200 may be implemented by the antenna 1, the antenna 2, the mobile communication module 250, the wireless communication module 260, the modulation and demodulation processor, the baseband processor, and the like.

Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in terminal device 200 may be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, the antenna 1 can be multiplexed as a diversity antenna of the wireless local area network. In other embodiments, the antenna may be used in conjunction with a tuning switch.

The mobile communication module 250 may provide a wireless communication solution including 2G/3G/4G/5G, etc. applied on the terminal device 200 . The mobile communication module 250 may include at least one filter, switch, power amplifier, low noise amplifier (LNA), and the like. The mobile communication module 250 can receive electromagnetic waves from the antenna 1, filter and amplify the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 250 can also amplify the signal modulated by the modulation and demodulation processor, and then convert it into electromagnetic waves for radiation through the antenna 1 . In some embodiments, at least part of the functional modules of the mobile communication module 250 may be provided in the processor 210 . In some embodiments, at least part of the functional modules of the mobile communication module 250 may be provided in the same device as at least part of the modules of the processor 210 .

The modem processor may include a modulator and a demodulator. Wherein, the modulator is used to modulate the low frequency baseband signal to be sent into a medium and high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low frequency baseband signal. Then the demodulator transmits the demodulated low-frequency baseband signal to the baseband processor for processing. The low frequency baseband signal is processed by the baseband processor and passed to the application processor. The application processor outputs sound signals through audio devices (not limited to the speaker 270A, the receiver 270B, etc.), or displays images or videos through the display screen 294 . In some embodiments, the modem processor may be a stand-alone device. In other embodiments, the modem processor may be independent of the processor 210, and may be provided in the same device as the mobile communication module 250 or other functional modules.

The wireless communication module 260 can provide applications on the terminal device 200 including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellites Wireless communication solutions such as global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), and infrared technology (IR). The wireless communication module 260 may be one or more devices integrating at least one communication processing module. The wireless communication module 260 receives electromagnetic waves via the antenna 2 , modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 210 . The wireless communication module 260 can also receive the signal to be sent from the processor 210 , perform frequency modulation on the signal, amplify the signal, and then convert it into an electromagnetic wave for radiation through the antenna 2 .

In some embodiments, the antenna 1 of the terminal device 200 is coupled with the mobile communication module 250, and the antenna 2 is coupled with the wireless communication module 260, so that the terminal device 200 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), broadband Code Division Multiple Access (WCDMA), Time Division Synchronous Code Division Multiple Access (TD-SCDMA), Long Term Evolution (LTE), BT, GNSS, WLAN , NFC, FM, and/or IR technology, etc. The GNSS may include global positioning system (global positioning system, GPS), global navigation satellite system (global navigation satellite system, GNSS), Beidou navigation satellite system (beidou navigation satellite system, BDS), quasi-zenith satellite system (quasi satellite system) -zenith satellite system, QZSS) and/or satellite based augmentation systems (SBAS).

The terminal device 200 implements a display function through a GPU, a display screen 294, an application processor, and the like. The GPU is a microprocessor for image processing, and is connected to the display screen 294 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 210 may include one or more GPUs that execute program instructions to generate or alter display information.

Display screen 294 is used to display images, videos, and the like. Display screen 294 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (active-matrix organic light). emitting diode, AMOLED), flexible light-emitting diode (flex light-emitting diode, FLED), Mini LED, Micro LED, quantum dot light emitting diode (quantum dot light emitting diodes, QLED) and so on. In some embodiments, the terminal device 200 may include one or N display screens 294 , where N is a positive integer greater than one.

The terminal device 200 can realize the shooting function through the ISP, the camera 293, the video codec, the GPU, the display screen 294 and the application processor.

The ISP is used to process the data fed back by the camera 293 . For example, when taking a photo, the shutter is opened, the light is transmitted to the camera photosensitive element through the lens, the light signal is converted into an electrical signal, and the camera photosensitive element transmits the electrical signal to the ISP for processing, and converts it into an image visible to the naked eye. ISP can also perform algorithm optimization on image noise, brightness, and skin tone. ISP can also optimize the exposure, color temperature and other parameters of the shooting scene. In some embodiments, the ISP may be provided in the camera 293 .

Camera 293 is used to capture still images or video. The object is projected through the lens to generate an optical image onto the photosensitive element. The photosensitive element may be a charge coupled device (CCD) or a complementary metal-oxide-semiconductor (CMOS) phototransistor. The photosensitive element converts the optical signal into an electrical signal, and then transmits the electrical signal to the ISP to convert it into a digital image signal. The ISP outputs the digital image signal to the DSP for processing. DSP converts digital image signals into standard RGB, YUV and other formats of image signals. In some embodiments, the terminal device 200 may include 1 or N cameras 293 , where N is a positive integer greater than 1.

A digital signal processor is used to process digital signals, in addition to processing digital image signals, it can also process other digital signals. For example, when the terminal device 200 selects a frequency point, the digital signal processor is used to perform Fourier transform on the frequency point energy and so on.

Video codecs are used to compress or decompress digital video. The terminal device 200 may support one or more video codecs. In this way, the terminal device 200 can play or record videos in various encoding formats, such as: moving picture experts group (moving picture experts group, MPEG) 1, MPEG2, MPEG3, MPEG4, and so on.

The NPU is a neural-network (NN) computing processor. By drawing on the structure of biological neural networks, such as the transfer mode between neurons in the human brain, it can quickly process the input information, and can continuously learn by itself. Applications such as intelligent cognition of the terminal device 200 can be implemented through the NPU, such as image recognition, face recognition, speech recognition, text understanding, and the like.

The external memory interface 220 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the terminal device 200 . The external memory card communicates with the processor 210 through the external memory interface 220 to realize the data storage function. For example to save files like music, video etc in external memory card.

Internal memory 221 may be used to store computer executable program code, which includes instructions. The processor 210 executes various functional applications and data processing of the terminal device 200 by executing the instructions stored in the internal memory 221 . The internal memory 221 may include a storage program area and a storage data area. The storage program area can store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like. The storage data area may store data (such as audio data, phone book, etc.) created during the use of the terminal device 200 and the like. In addition, the internal memory 221 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, universal flash storage (UFS), and the like.

The terminal device 200 can implement audio functions through an audio module 270, a speaker 270A, a receiver 270B, a microphone 270C, an earphone interface 270D, and an application processor. Such as music playback, recording, etc.

The audio module 270 is used for converting digital audio information into analog audio signal output, and also for converting analog audio input into digital audio signal. Audio module 270 may also be used to encode and decode audio signals. In some embodiments, the audio module 270 may be provided in the processor 210 , or some functional modules of the audio module 270 may be provided in the processor 210 .

Speaker 270A, also referred to as a "speaker", is used to convert audio electrical signals into sound signals. The terminal device 200 can listen to music through the speaker 270A, or listen to a hands-free call.

The receiver 270B, also referred to as an "earpiece", is used to convert audio electrical signals into sound signals. When the terminal device 200 answers a call or a voice message, the voice can be answered by placing the receiver 270B close to the human ear.

The microphone 270C, also called "microphone" or "microphone", is used to convert sound signals into electrical signals. When making a call or sending a voice message, the user can make a sound by approaching the microphone 270C through the human mouth, and input the sound signal into the microphone 270C. The terminal device 200 may be provided with at least one microphone 270C. In other embodiments, the terminal device 200 may be provided with two microphones 270C, which may implement a noise reduction function in addition to collecting sound signals. In other embodiments, the terminal device 200 may further be provided with three, four or more microphones 270C to collect sound signals, reduce noise, identify sound sources, and implement directional recording functions.

The headphone jack 270D is used to connect wired headphones. The earphone interface 270D may be a USB interface 230, or a 3.5mm open mobile terminal platform (OMTP) standard interface, a cellular telecommunications industry association of the USA (CTIA) standard interface.

The pressure sensor 280A is used to sense pressure signals, and can convert the pressure signals into electrical signals. In some embodiments, the pressure sensor 280A may be provided on the display screen 294 . There are many types of pressure sensors 280A, such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, and the like. The capacitive pressure sensor may be comprised of at least two parallel plates of conductive material. When a force is applied to pressure sensor 280A, the capacitance between the electrodes changes. The terminal device 200 determines the intensity of the pressure according to the change in capacitance. When a touch operation acts on the display screen 294, the terminal device 200 detects the intensity of the touch operation according to the pressure sensor 280A. The terminal device 200 may also calculate the touched position according to the detection signal of the pressure sensor 280A. In some embodiments, touch operations acting on the same touch position but with different touch operation intensities may correspond to different operation instructions. For example, when a touch operation whose intensity is less than the first pressure threshold acts on the short message application icon, the instruction for viewing the short message is executed. When a touch operation with a touch operation intensity greater than or equal to the first pressure threshold acts on the short message application icon, the instruction to create a new short message is executed.

The gyro sensor 280B can be used to determine the motion attitude of the terminal device 200 . In some embodiments, the angular velocity of end device 200 about three axes (ie, x, y, and z axes) may be determined by gyro sensor 280B. The gyro sensor 280B can be used for image stabilization. Exemplarily, when the shutter is pressed, the gyroscope sensor 280B detects the shaking angle of the terminal device 200, calculates the distance to be compensated by the lens module according to the angle, and allows the lens to offset the shaking of the terminal device 200 through reverse motion to achieve anti-shake. The gyro sensor 280B can also be used for navigation and somatosensory game scenarios.

Air pressure sensor 280C is used to measure air pressure. In some embodiments, the terminal device 200 calculates the altitude through the air pressure value measured by the air pressure sensor 280C to assist in positioning and navigation.

Magnetic sensor 280D includes a Hall sensor. The terminal device 200 can detect the opening and closing of the flip holster using the magnetic sensor 280D. In some embodiments, when the terminal device 200 is a flip machine, the terminal device 200 can detect the opening and closing of the flip according to the magnetic sensor 280D. Further, according to the detected opening and closing state of the leather case or the opening and closing state of the flip cover, characteristics such as automatic unlocking of the flip cover are set.

The acceleration sensor 280E can detect the magnitude of the acceleration of the terminal device 200 in various directions (generally three axes). The magnitude and direction of gravity can be detected when the terminal device 200 is stationary. It can also be used to identify the posture of terminal devices, and can be used in applications such as horizontal and vertical screen switching, pedometers, etc.

Distance sensor 280F for measuring distance. The terminal device 200 can measure the distance by infrared or laser. In some embodiments, when shooting a scene, the terminal device 200 can use the distance sensor 280F to measure the distance to achieve fast focusing.

Proximity light sensor 280G may include, for example, light emitting diodes (LEDs) and light detectors, such as photodiodes. The light emitting diodes may be infrared light emitting diodes. The terminal device 200 emits infrared light to the outside through the light emitting diode. The terminal device 200 detects infrared reflected light from nearby objects using a photodiode. When sufficient reflected light is detected, it can be determined that there is an object near the terminal device 200 . When insufficient reflected light is detected, the terminal device 200 may determine that there is no object near the terminal device 200 . The terminal device 200 can use the proximity light sensor 280G to detect that the user holds the terminal device 200 close to the ear to talk, so as to automatically turn off the screen to save power. Proximity light sensor 280G can also be used in holster mode, pocket mode automatically unlocks and locks the screen.

The ambient light sensor 280L is used to sense ambient light brightness. The terminal device 200 can adaptively adjust the brightness of the display screen 294 according to the perceived ambient light brightness. The ambient light sensor 280L can also be used to automatically adjust the white balance when taking pictures. The ambient light sensor 280L can also cooperate with the proximity light sensor 280G to detect whether the terminal device 200 is in the pocket, so as to prevent accidental touch.

The fingerprint sensor 280H is used to collect fingerprints. The terminal device 200 can use the collected fingerprint characteristics to realize fingerprint unlocking, accessing application locks, taking pictures with fingerprints, answering incoming calls with fingerprints, and the like.

The temperature sensor 280J is used to detect the temperature. In some embodiments, the terminal device 200 uses the temperature detected by the temperature sensor 280J to execute the temperature processing strategy. For example, when the temperature reported by the temperature sensor 280J exceeds a threshold value, the terminal device 200 reduces the performance of the processor located near the temperature sensor 280J, so as to reduce power consumption and implement thermal protection. In other embodiments, when the temperature is lower than another threshold, the terminal device 200 heats the battery 242 to avoid abnormal shutdown of the terminal device 200 caused by the low temperature. In some other embodiments, when the temperature is lower than another threshold, the terminal device 200 boosts the output voltage of the battery 242 to avoid abnormal shutdown caused by low temperature.

Touch sensor 280K, also called "touch panel". The touch sensor 280K may be disposed on the display screen 294, and the touch sensor 280K and the display screen 294 form a touch screen, also called a "touch screen". The touch sensor 280K is used to detect a touch operation on or near it. The touch sensor can pass the detected touch operation to the application processor to determine the type of touch event. Visual output related to touch operations may be provided through display screen 294 . In other embodiments, the touch sensor 280K may also be disposed on the surface of the terminal device 200 , which is different from the position where the display screen 294 is located.

The bone conduction sensor 280M can acquire vibration signals. In some embodiments, the bone conduction sensor 280M can acquire the vibration signal of the vibrating bone mass of the human voice. The bone conduction sensor 280M can also contact the pulse of the human body and receive the blood pressure beating signal. In some embodiments, the bone conduction sensor 280M can also be disposed in the earphone, combined with the bone conduction earphone. The audio module 270 can analyze the voice signal based on the vibration signal of the vocal vibration bone block obtained by the bone conduction sensor 280M, so as to realize the voice function. The application processor can analyze the heart rate information based on the blood pressure beat signal obtained by the bone conduction sensor 280M, so as to realize the function of heart rate detection.

The keys 290 include a power-on key, a volume key, and the like. Keys 290 may be mechanical keys. It can also be a touch key. The terminal device 200 may receive key input and generate key signal input related to user settings and function control of the terminal device 200 .

Motor 291 can generate vibrating cues. The motor 291 can be used for vibrating alerts for incoming calls, and can also be used for touch vibration feedback. For example, touch operations acting on different applications (such as taking pictures, playing audio, etc.) can correspond to different vibration feedback effects. The motor 291 can also correspond to different vibration feedback effects for touch operations on different areas of the display screen 294 . Different application scenarios (for example: time reminder, receiving information, alarm clock, games, etc.) can also correspond to different vibration feedback effects. The touch vibration feedback effect can also support customization.

The indicator 292 can be an indicator light, which can be used to indicate the charging status, the change of power, and can also be used to indicate messages, missed calls, notifications, and the like.

The SIM card interface 295 is used to connect a SIM card. The SIM card can be connected to and separated from the terminal device 200 by inserting into the SIM card interface 295 or pulling out from the SIM card interface 295 . The terminal device 200 may support 1 or N SIM card interfaces, where N is a positive integer greater than 1. The SIM card interface 295 can support Nano SIM card, Micro SIM card, SIM card and so on. The same SIM card interface 295 can insert multiple cards at the same time. The types of the plurality of cards may be the same or different. The SIM card interface 295 can also be compatible with different types of SIM cards. The SIM card interface 295 is also compatible with external memory cards. The terminal device 200 interacts with the network through the SIM card to realize functions such as call and data communication. In some embodiments, the terminal device 200 employs an eSIM, ie an embedded SIM card. The eSIM card can be embedded in the terminal device 200 and cannot be separated from the terminal device 200 .

The above health management system can detect epilepsy through the EEG signal, PPG signal and ACC signal collected by the smart eye mask, so as to realize the monitoring of sleep epilepsy; and the smart eye mask can transmit the seizure data to the terminal device to help users manage epilepsy. In addition, the brain waves of patients during epilepsy have obvious changes, and abnormal heartbeats, body convulsions, etc. will also occur. EEG signals can well reflect the changes of brain waves during epileptic seizures, and PPG signals can reflect the heart rate of users during epileptic seizures. The head ACC signal can reflect the head movement information of the user during epileptic seizure, and the signal is less disturbed by body movement (such as hand movement), so the EEG signal, PPG signal and head ACC signal are combined for epilepsy detection. It can effectively improve the accuracy of epilepsy detection results.

The epilepsy detection process is described below. Referring to FIG. 6 , FIG. 6 is a schematic flowchart of epilepsy detection according to an embodiment of the present application.

In order to save processing resources and reduce system power consumption, the smart eye mask can start epilepsy detection after detecting that the user has fallen asleep. Among them, the smart eye mask can detect whether the user falls asleep according to the signal data collected by the signal acquisition unit, or can also determine whether the user falls asleep based on the sleep monitoring results when the sleep monitoring function is turned on, so as to further save processing resources. For the specific sleep-onset detection method, reference may be made to the subsequent description of the sleep-detection process, which will not be repeated here.

When specifically performing epilepsy detection, the detection may be performed at a preset epilepsy detection cycle, and in each cycle, epilepsy detection is performed according to a signal segment (referred to as a first signal segment) corresponding to the cycle. The period may be several seconds, the first signal segment corresponding to the period may include signal data of a preset duration before the detection time corresponding to the period, and the preset duration (ie, the duration of the first signal segment) may be greater than or equal to the duration of the period. For example: the duration of the cycle is 2 seconds, and the duration of the first signal segment can be 4 seconds, that is, epilepsy detection is performed every 2 seconds, and the latest 4 seconds of signal data collected is used each time, that is, two adjacent cycles will be multiplexed 2 Seconds of signal data; or, the duration of the cycle and the duration of the first signal segment are both 4 seconds, the data collected by the signal acquisition unit is not multiplexed, and the signal data collected in the cycle is used for each epilepsy detection. For each cycle, epilepsy detection can be performed using the method shown in Figure 6.

As shown in FIG. 6 , for each cycle, after the first signal segment corresponding to the cycle is acquired, signal processing, feature extraction and epileptic seizure detection can be performed in sequence according to the signal data in the first signal segment, and the Calculation of the duration of the seizure and assessment of the severity of the seizure were performed after the seizure was over.

Among them, when performing signal processing, a band-pass filter such as a Butterworth can generally be used to filter the signal data in the first signal segment to remove noise and useless signals such as baseline, low frequency and high frequency, and obtain useful Signal.

Compared with the situation without epilepsy, when epilepsy patients have epilepsy, the amplitude of brain waves will increase significantly, and various abnormal waves will appear in the brain waves, and their frequencies will also change; and there will also be rapid heartbeat, body convulsions, etc. symptom. Correspondingly, the signal characteristics of the EEG signal, the PPG signal, and the ACC signal will also change; by analyzing the signal characteristics of these signal data, it can be determined whether the user has epilepsy. Therefore, after signal processing is performed on the first signal segment, features related to epilepsy detection in the first signal segment can be extracted first, and then epileptic seizure judgment can be performed based on the extracted features.

Among them, the features related to epilepsy detection in the EEG signal may include: EEG amplitude and its statistical features, and the statistical features of the EEG signal may include time domain features such as mean, variance, covariance matrix and other frequency band signals (α, β, θ). Some or all of the features in the frequency domain such as the energy ratio of , delta waves, etc.; the features related to epilepsy detection in the PPG signal may include: related features such as heart rate and heart rate variability; features related to epilepsy detection in the ACC signal It may include: ACC amplitude and its statistical features, and the statistical features of the ACC signal may include: time-domain features such as mean, variance, and standard deviation, and some or all of the frequency features such as signal energy.

After the signal features of the first signal segment are extracted, the pre-trained first classification model can be used to detect epileptic seizures, that is, the extracted signal features can be input into the first classification model to obtain an epileptic seizure detection result. If a seizure is detected, information such as the duration and severity of the seizure can be further calculated when the end of the seizure is detected; if no seizure is detected, no processing is required.

For the EEG signal, as mentioned above, in order to improve the accuracy of the detection result, there are multiple EEG electrodes, that is, the EEG signal includes multiple channels, and the signal characteristics of the EEG signal input to the first classification model may include each channel of EEG signal. The signal characteristic of the EEG signal can also be the mean value of each signal characteristic of the EEG signal determined according to the signal characteristic of each EEG signal.

When judging whether the epileptic seizure is over, it can be judged according to the seizure detection result of the subsequent first signal segment. Specifically, in the process of subsequent detection of each first signal segment, if no epilepsy is detected for the first time or several times in a row, then The seizure can be determined to be over.

The duration of a seizure can be determined based on when the seizure started and when it ended. Seizure severity can be determined using a pre-trained second classification model.

In a specific implementation, the signal features of each first signal segment during the seizure, the duration of the seizure, and the aggregated feature of each first signal segment can be input into the second classification model to obtain the severity of the seizure. The aggregated feature of each first signal segment may be determined according to various signal features of each first signal segment, which may, for example, include: an average value of each signal feature determined according to the values of various signal features in each first signal segment and variance etc. The severity of epileptic seizures may also be divided into several levels, for example, may include three levels of mild, moderate, and severe, and the number of specific levels is not particularly limited in this embodiment.

Specifically, the first classification model and the second classification model may be a classifier or a regressor. The machine learning algorithm used by both can be Bayesian algorithm, Support Vector Machine (SVM) algorithm or classification algorithm based on neural network.

Similar to the conventional model training method, for the first classification model, a first training sample set can be obtained in advance, and the first training sample set includes training samples corresponding to epileptic seizures and training samples corresponding to non-seizure epilepsy, and each training sample includes: Signal data (EEG signal, PPG signal and ACC signal) and classification labels (including epilepsy and no epilepsy); then feature extraction is performed on the signal data in each training sample, and the extracted signal features and corresponding classification labels Input the initial first classification model to be trained for training to obtain the first classification model. For the second classification model, a second training sample set may be obtained in advance, the second training sample set includes training samples corresponding to epileptic seizures of various severities, and each training sample may include: each first signal segment during an epileptic seizure The signal data (EEG signal, PPG signal, and ACC signal) and classification labels (i.e., the severity of the seizure); then feature extraction is performed on the signal data of each first signal segment in each training sample, and the duration of the seizure is determined duration and aggregated features of each first signal segment; then the extracted signal features, the determined duration of epileptic seizures, and the classification labels corresponding to the aggregated features of each first signal segment are input into the initial second classification model to be trained for training , to get the second classification model.

In order to improve the accuracy of the detection result, as shown in FIG. 6 , before the signal processing is performed on the first signal segment, the signal quality detection of the EEG signal in the first signal segment can be performed first. When the signal quality of the EEG signal meets the requirements In this case, follow-up epilepsy detection is performed; if the signal quality of the EEG signal does not meet the requirements, the tightness adjustment module can be controlled to adjust the tightness of the smart eye mask, so that the EEG electrodes are fully in contact with the skin to obtain better EEG Signal quality.

Specifically, whether the signal quality of the EEG signal meets the requirements can be determined according to the signal-to-noise ratio of the EEG signal; in order to improve the accuracy, feature extraction can also be performed on the EEG signal, according to the relationship between the extracted features and the corresponding feature value range, to Determine whether the signal quality of the EEG signal meets the requirements. For example: when the extracted features are all within the corresponding feature value range (that is, each feature meets the requirements), or when the number of features that meet the requirements reaches the preset number, the signal quality of the EEG signal can be considered to meet the requirements, otherwise, It is considered that the signal quality of the EEG signal does not meet the requirements.

For the EEG signal corresponding to each EEG electrode in the first signal segment, the above method can be used to perform signal quality detection, and if the signal quality of each EEG signal meets the requirements, subsequent epilepsy detection can be performed. In the case that the signal quality of any EEG signal does not meet the requirements, the tightness adjustment module can be controlled to adjust the tightness of the smart eye mask.

When adjusting the tightness, the tightness adjusting module can be controlled to adjust the preset tightness adjustment amount; in order to quickly determine the appropriate tightness adjustment amount, the tightness adjusting module can also be controlled to continuously adjust at a preset adjustment speed For the tightness of the smart eye mask, during the adjustment process, the signal quality of the EEG signal is detected. When the detected signal quality of the EEG signal meets the requirements, the tightness adjustment module is controlled to stop the adjustment; or it can also be adjusted according to the detected signal quality. Determine the tightness adjustment amount, and then control the tightness adjustment module to adjust according to the tightness adjustment amount. For example, the ratio of the number of features that meet the requirements to the total number of features can be used to measure the signal quality. According to the preset signal quality and tightness The corresponding relationship between the adjustment amounts is used to determine the adjustment amount of the tightness.

In addition, a maximum tightness can be pre-determined according to the relationship between the tightness of the smart eye mask and the wearing comfort of the user; when adjusting, if the tightness of the smart eye mask reaches the preset maximum tightness, it can also be controlled The tightness adjustment module stops adjustment to improve the comfort of the user wearing the smart eye mask.

It should be noted that the above-mentioned signal quality detection method and tightness adjustment method are merely exemplary descriptions, which are not intended to limit the present application, and specific implementation methods can be set as required, which are not particularly limited in this embodiment.

The above-mentioned epilepsy detection method combines EEG signal, PPG signal and ACC signal for epilepsy detection. Among them, the brain waves of patients with epilepsy have obvious changes, abnormal heartbeat, body convulsions, etc., and EEG signals can well reflect epilepsy. The brain wave changes during the seizure, the PPG signal can reflect the heart rate change of the user during the seizure, the head ACC signal can reflect the head movement information of the user during the seizure, and the signal is disturbed by body movement (such as hand movement) Therefore, combining EEG signal, PPG signal and head ACC signal for epilepsy detection can effectively improve the accuracy of epilepsy detection results. In addition, when the signal quality of the EEG signal meets the requirements, the subsequent epilepsy detection process is carried out. When the signal quality of the EEG signal does not meet the requirements, the tightness of the smart eye mask is adjusted through the tightness adjustment module to ensure the signal of the EEG signal. The quality meets the requirements, which can further improve the accuracy of epilepsy detection results.

The sleep detection process will be described below. Referring to FIG. 7 , FIG. 7 is a schematic flowchart of sleep detection according to an embodiment of the present application.

Similar to the above-mentioned process of epilepsy detection, when performing sleep detection, the detection can be performed at a preset sleep detection cycle. For each cycle, after acquiring the signal segment corresponding to the cycle (called the second signal segment) , and sequentially perform processing processes such as signal processing, feature extraction, and sleep state judgment according to the signal data in the second signal segment, to obtain sleep parameters such as the user's sleep state and sleep duration. The sleep detection period and the epilepsy detection period may be the same or different, and the duration of the second signal segment corresponding to the sleep detection period and the first signal segment corresponding to the epilepsy detection period may be different, and a longer duration may be set, such as 30 seconds; the manner of determining the second signal segment is similar to the manner of determining the first signal segment in epilepsy detection, and details are not repeated here.

Similar to the processing process of the relevant steps in epilepsy detection, when performing signal processing, a band-pass filter can be used to filter the signal data in the second signal segment; then the amplitude and statistical features of the EEG signal in the second signal segment can be extracted. , the heart rate characteristics of the PPG signal, the amplitude and statistical characteristics of the ACC signal, etc. After extracting the signal characteristics of the second signal segment, the pre-trained third classification model (ie, the sleep state recognition model) can be used to determine the sleep state detection result. . Among them, the features used in sleep detection and epilepsy detection can be the same or different, and can be selected according to the specific implementation; the third classification model is similar to the first classification model, but the training sample set during training is different. The training sample set contains training samples corresponding to various sleep states; as mentioned above, the sleep states may include: falling asleep, light sleep, deep sleep, deep sleep, rapid eye movement sleep, etc. For other detailed descriptions of these steps, please refer to the relevant descriptions in Epilepsy Detection, which will not be repeated here.

Similarly, in order to improve the accuracy of the detection results, as shown in FIG. 7 , before signal processing is performed on the second signal segment, signal quality detection may be performed on the EEG signal in the second signal segment. If the requirements are met, follow-up sleep detection is performed; if the signal quality of the EEG signal does not meet the requirements, the tightness adjustment module can be controlled to adjust the tightness of the smart eye mask. The specific signal quality detection method and the tightness adjustment method are similar to the related methods in epilepsy detection, and will not be repeated here.

In the case of multiple EEG electrodes, the EEG signals of all EEG electrodes can be used during sleep detection, or only the EEG signals collected by one of the EEG electrodes can be used to improve the processing efficiency. Correspondingly, the signal quality detection is performed , the EEG signal with the best signal quality (here called the target EEG signal) can be selected, and the subsequent sleep detection can be performed if the signal quality of the signal meets the requirements; if the signal quality of the signal does not meet the requirements In this case, control the tightness adjustment module to adjust the tightness of the smart eye mask.

In order to improve the accuracy of the detection results, at least two EEG electrodes can be symmetrically arranged on both sides of the smart eye mask to adapt to the different sleeping positions of the user. For example, the two EEG electrodes can be symmetrically arranged on the smart eye mask at positions corresponding to the FP1 and FP2 regions of the human body as shown in FIG. 3 , or can also be arranged on the smart eye mask at other symmetrical positions relative to the midline of the frontal pole , such as the positions corresponding to the F3 area and the F4 area. Correspondingly, as shown in FIG. 7 , when performing signal quality detection, the sleeping position may be judged according to the ACC signal in the second signal segment. If the sleeping position of the user is lying flat, it may be determined according to the signal quality of each EEG signal. The EEG signal with the best signal quality is the target EEG signal; if the user's sleeping position is lying on his side, the EEG signal corresponding to the EEG electrode on the same side of the user's sleeping position can be determined as the target EEG signal, and then the determined target EEG signal can be determined. Whether the signal quality of the signal meets the requirements. When determining that the user is lying on the side, the solution does not need to judge the signal quality of each EEG signal, so the detection efficiency can be improved to a certain extent, and the power consumption can be reduced. Of course, it is also possible to directly determine the EEG signal with the best signal quality from each EEG signal without judging the sleeping posture. This method does not require other sensor signals, and the detection method is relatively simple.

Considering that the duration of the second signal segment of sleep detection is relatively long, the signal quality monitoring may also be performed at a preset signal quality detection cycle while performing the above sleep detection, and the duration of the third signal segment corresponding to each cycle may be the same as the duration of the third signal segment. The duration of the first signal segment corresponding to the epilepsy detection period is the same, and may also be slightly longer or shorter than the duration of the first signal segment. When the signal quality of the EEG signal meets the requirements, no processing is required; when the signal quality of the EEG signal does not meet the requirements, the tightness adjustment module can be controlled to adjust the tightness of the smart eye mask.

It is understandable that if the smart eye mask enables both the epilepsy detection function and the sleep detection function, the signal quality detection requirements of epilepsy detection and sleep detection can be met at the same time through the signal quality detection during the epilepsy detection process. There is no need for additional signal quality monitoring; in addition, in epilepsy detection, the signal quality of each EEG signal will be detected. After the tightness adjustment, the signal quality of each EEG signal meets the requirements, and can be selected arbitrarily when performing sleep detection. One or more EEG signals meeting the signal quality requirements are used for subsequent sleep state judgment.

The above sleep detection method, combined with the EEG signal for sleep monitoring, can improve the accuracy of the sleep state detection result. In addition, when the signal quality of the EEG signal meets the requirements, the subsequent sleep detection process is performed. When the signal quality of the EEG signal does not meet the requirements, the tightness of the smart eye mask is adjusted through the tightness adjustment module to ensure the signal of the EEG signal. The quality meets the requirements, which can further improve the accuracy of the sleep state detection results.

As mentioned above, the smart eye mask can send epileptic seizure data and sleep state data to the terminal device, so as to facilitate the management of epilepsy disease and sleep for the user. The following takes epilepsy management as an example to introduce the epilepsy management process in the terminal device.

The terminal device may provide an epilepsy management function. The epilepsy management function may be a function in an application or a separate application. In this embodiment, the epilepsy detection function is used as an example in a health management application for illustrative description.

FIG. 8 is a schematic diagram of an application interface provided by an embodiment of the present application. As shown in (a) of FIG. 8 , an application icon corresponding to a health management application is displayed on the screen interface of the terminal device 200 (for example, as shown in FIG. 8 ). sports health icon 11) and other application icons, the user can click the sports health icon 11 to open the health management application; as shown in (b) in FIG. The main interface 10 of the main interface 10 may include a function name 101, a card list 102 and a navigation bar 103, wherein:

The function name 101 may be used to indicate a function that is currently turned on, such as the "health" function shown in the figure.

The card list 102 may include cards corresponding to various health management functions provided by the health management application, such as the main card 1021 shown in the figure (which can be used to view basic activity data such as steps and calories), epilepsy record card 1022, sleep card 1023, weight card 1024 and exercise record card 1025, as well as heart rate card and blood sugar card not shown, all or part of the cards can be displayed in the card list 102; the user can view the hidden part of the card list 102 by sliding operation, for example: weight Hidden parts of cards 1024 and log cards 1025, and other cards in card list 102 (eg, heart rate cards). In addition, an edit card control (not shown) may be provided below the card list 102 for the user to edit the cards contained in the card list 102; the bottom of the card list 102 may also contain other content, such as healthy life recommendation content.

The navigation bar 103 may include various function menus, for example, as shown in (b) of FIG. 8 : a "health" function for viewing various health management functions, a "sports" function for viewing various exercise data, The "Device" function for managing connected smart health devices and the "My" function for personal account management.

As mentioned above, the smart eye mask 100 can send the detected epileptic seizure data and sleep state data to the terminal device 200, and correspondingly, the terminal device 200 can manage these data for the user to view. Specifically, the user can click on the card to open the card details page to view the data corresponding to the card. The epilepsy record card is used as an example for illustration below.

As shown in (b) of FIG. 8, the user can enter the epilepsy record details page 20 after clicking the epilepsy record card 1022. As shown in (c) of FIG. 8, the epilepsy record details page 20 can display the user's epilepsy record details 203, and may include a return control 201 and a seizure severity selection control 202, the user can return to the upper-level interface of the epilepsy record details page 20 through the return control 201; select the seizure severity to be displayed through the seizure severity selection control 202 Seizure records of the severity, wherein the severity of seizures corresponds to the severity recognized by the smart eye mask 100, for example, it may include mild, moderate and severe, as shown in (c) of FIG. 8, the epilepsy record details page 20 The epileptic seizure records 203 of all severity levels can be displayed by default, wherein each epileptic seizure record can display the seizure severity, onset date, onset duration, onset and end time, and the like. It can be understood that the terminal device 200 can also obtain epileptic seizure data through other smart health devices with epilepsy monitoring functions. Correspondingly, the above-mentioned epileptic seizure record 203 may include the terminal device 200 according to the seizure data obtained from other smart health devices. Data generated records.

In addition, the epilepsy record details page 20 may include controls such as an add control 204 and a statistics control 205. The user can manually add epileptic seizure data through the add control 204 to open the epilepsy record addition interface, and view the epilepsy statistics through the statistics control 205. The following example illustrate.

As shown in (a) and (b) of FIG. 9 , the user can click the add control 204 to open the seizure record adding interface 30 , and the seizure record adding interface 30 may include parameter editing items 301 , cancel controls 302 and confirmation controls 303 , wherein, the parameter editing items 301 may include editing options related to epileptic seizure data such as severity, attack date, start time and end time, and through these parameter editing items 301, the user can be guided to complete the addition of the epileptic seizure record; the user can click The cancel control 302 cancels the addition of the epileptic seizure record, and returns to the previous interface of the epileptic seizure record adding interface 30; as shown in (b) and (c) in FIG. By clicking the confirmation control 303 to confirm the added epileptic seizure record, the epileptic seizure record added by the user can be updated in the epilepsy record detail page 20 .

As shown in (a) and (b) of FIG. 10, the user can click on the statistics control 205 to open the seizure statistics interface 40, which can display the user's seizure statistics 403, and can include the return control 401 and the seizures Severity selection control 402, the user can return to the upper-level interface of the epileptic seizure statistics interface 40 through the return control 201; through the seizure severity selection control 402, select the seizure statistical data of the seizure severity to be displayed, as shown in Figure 10 As shown in (b), statistical data of mild epileptic seizures may be displayed in the epileptic seizure statistics interface 40 by default. The epileptic seizure statistical data may include weekly statistical data in days, monthly statistical data in weeks, annual statistical data and total statistical data in months, and the like. These statistical data may be in columnar form. Figures and other methods show the duration of epileptic seizures, and can display data such as the number of epileptic seizures under the corresponding statistical methods.

Similarly, users can view the corresponding health management data through the card details pages corresponding to other cards, and can also manually add health management data and view the corresponding statistics, etc. The card details pages of different cards can be displayed according to the health management data to be displayed. The characteristics of the data are displayed in different manners, which can be set as required during specific implementation, which is not particularly limited in this embodiment.

As mentioned above, the smart eyewear 100 can automatically transmit epileptic seizure data and sleep state data to the terminal device 200 under the condition of establishing a connection with the terminal device 200, or it can store these data first, and store the data when the user triggers data synchronization. The stored data is synchronized to the terminal device 200 . Correspondingly, the terminal device 200 may provide an automatic synchronization function and a manual synchronization function, and obtain the user's health data from the smart health device including the smart eye mask through these two functions.

As shown in FIG. 11 , the terminal device 200 can provide a synchronization control 501 corresponding to manual synchronization of data and a switch control 502 of automatic synchronization in the application setting interface 50. The user can manually synchronize data by clicking the synchronization control 501, and click the switch Control 502 selects to turn the auto-sync function on or off. Wherein, the application setting interface 50 can be opened by clicking the setting option in the "My" function, and the interface may also include other setting options, such as the data sharing, message management, privacy and clearing cache options shown in the figure, This embodiment does not specifically limit this. For the convenience of the user, the user can also perform data synchronization by touching and sliding down on the main interface 10 .

For the convenience of the user, the health management application can also provide a device control function for controlling the connected smart health device. Specifically, the device control function can be implemented under the "device" function in the navigation bar 103 . As shown in (a) and (b) of FIG. 12 , the user can click on the “device” function to open the device management interface 60; the device management interface 60 may include an add device control 601 and a my device bar, where the add The device control 601 can be displayed in a card or other way, and the user can add a new smart health device through the control; the My Device column lists the device editing options corresponding to various smart health devices that the terminal device 200 has paired with, as shown in the figure The shown eye mask editing option 602 corresponding to the smart eye mask and the wristband editing option 603 corresponding to the smart bracelet, the user can set the corresponding smart health device through the device editing option.

For example, as shown in (b) and (c) of FIG. 12 , the user can click the eye mask editing option 602 to open the eye mask setting interface 70 , and the eye mask setting interface 70 may include a device card 701 for displaying device status information and various functions Edit options, where the device status information can include the device name of the smart eyewear (for example, "Aaa 111"), connection status, and remaining battery power.

The function editing options may include a usage guide option 702, an epilepsy monitoring option 703, a sleep monitoring option 704, an emergency call option 705, a Bluetooth disconnection reminder option 706, an unpairing option 707, and the like. The user can view the relevant usage guide through the usage guide option 702, turn on or off the epilepsy monitoring function of the smart eye mask 100 through the epilepsy monitoring option 703, and turn on or off the sleep monitoring function of the smart eye mask 100 through the sleep monitoring option 704. The emergency call option 705 activates the emergency call function, the Bluetooth disconnection reminder option 706 is used to enable or disable the Bluetooth disconnection reminder service, and the unpairing option 707 is used to release the pairing connection between the smart eye mask 100 and the terminal device 200 . Through the above functions, the user can conveniently set the smart eye mask, and can remind the guardian in time through the emergency call function to reduce the adverse effect of epilepsy on the patient.

(d) in FIG. 12 is a schematic diagram of the emergency call interface. As shown in (c) and (d) in FIG. 12 , the user can click the emergency call option 705 to open the emergency call interface 80, which may include: return control 801. Automatically send help information option 802, automatically dial help call option 803, emergency contact option 804, and emergency call time period option 805, etc. The user can return to the upper-level interface of the emergency call interface 80 through the return control 801. Help information option 802 enables or disables the function of automatically sending help information, and enables or disables the function of automatically dialing help calls through the automatic help call option 803. After the function of automatically sending help information is enabled, the terminal device 200 can When the severity reaches the target level (such as severe), it can automatically send help information including the health status (such as the occurrence of severe epilepsy) to the emergency contact; after the function of automatically dialing for help is enabled, the terminal device 200 can detect the severity of the epileptic seizure. When the target level is reached, the emergency contact can be automatically called and the recording of help can be played, and the call can be automatically hung up after playing. The recording of help can include information such as the severity of the user's epilepsy. For the convenience of the user, as shown in the figure, corresponding function prompt information may be displayed under the option 802 of automatically sending help information and the option 803 of automatically dialing help calls.

In addition, the user can set the emergency contact through the emergency contact option 804, specifically, the phone number of the emergency contact can be manually input, or the emergency contact can also be selected from the address book. In order to improve flexibility, the health management application can provide the above-mentioned emergency call time period option 805 for the user to set the emergency call time period. The emergency call function is not enabled during the daytime period. Correspondingly, the emergency call time period can be set to the corresponding time period at night, such as 22:00 to 07:00 the next day; if the patient has no guardian around during the day, then The emergency call time period can be set to all day as shown.

In the terminal device provided in this embodiment, through the above-mentioned epilepsy management function, the user can conveniently manage the seizure data of the epilepsy disease, and the user can conveniently set the relevant functions of the smart eye mask. In addition, through the emergency call function, the guardian can be reminded in time , which can reduce the adverse effects of epileptic seizures on patients.

It can be understood that the terminal device can also perform sleep management according to the sleep state data obtained from the smart eye mask. Similar to epilepsy management, the terminal device can display the sleep state history after the user clicks the sleep card 1023, and can also provide sleep statistics. The user can also manually input sleep data such as sleep records, and the specific interface can refer to various current sleep management interfaces, which will not be repeated here.

Based on the same inventive concept, as an implementation of the above method, an embodiment of the present application provides a health management device, which corresponds to the foregoing method embodiment. For ease of reading, this device embodiment does not refer to the foregoing method embodiment. The detailed contents are described one by one, but it should be clear that the apparatus in this embodiment can correspondingly implement all the contents in the foregoing method embodiments.

FIG. 13 is a schematic structural diagram of a health management device provided by an embodiment of the present application. As shown in FIG. 13 , the device provided by this embodiment includes:

Display module 310 , input module 320 , processing module 330 and communication module 340 .

The display module 310 is used to support the terminal device to perform the interface display operations in the above-mentioned embodiments and/or other processes for the technology described herein. The display unit may be a touch screen or other hardware or a combination of hardware and software.

The input module 320 is used to receive the user's input on the display interface of the terminal device, such as touch input, voice input, gesture input, etc. The input module is used to support the terminal to perform the steps and/or functions related to receiving user operations in the above-mentioned embodiments. Other procedures for the techniques described herein. The input module can be a touch screen or other hardware or a combination of hardware and software.

The processing module 330 is used to support the terminal device to perform the processing operations in the above-described embodiments and/or other processes for the techniques described herein.

The communication module 340 is used to support the terminal device to perform the operations related to the communication process between the cloud and the smart eyewear in the above embodiments and/or other processes for the techniques described herein.

The apparatus provided in this embodiment may execute the foregoing method embodiments, and the implementation principles and technical effects thereof are similar, and details are not described herein again.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit, and the above-mentioned integrated units may adopt hardware. It can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above-mentioned system, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described in the foregoing method embodiment is implemented.

The embodiments of the present application further provide a computer program product, when the computer program product runs on a terminal device, the terminal device executes the method described in the above method embodiments.

An embodiment of the present application further provides a chip system, including a processor, where the processor is coupled to a memory, and the processor executes a computer program stored in the memory to implement the method described in the above method embodiments. Wherein, the chip system may be a single chip or a chip module composed of multiple chips.

In the above-mentioned embodiments, it may be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented in software, it 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, all or part of the processes or functions described in the embodiments of the present application are generated. The computer may be a general purpose computer, special purpose computer, computer network, or other programmable device. The computer instructions may be stored in or transmitted over a computer-readable storage medium. The computer instructions can be sent from one website site, computer, server or data center to another website site, computer, server or data center for transmission. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that includes an integration of one or more available media. The usable medium may be a magnetic medium (eg, a floppy disk, a hard disk, or a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium (eg, a Solid State Disk (SSD)), and the like.

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented. The process can be completed by instructing the relevant hardware by a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed , which may include the processes of the foregoing method embodiments. The aforementioned storage medium may include: ROM or random storage memory RAM, magnetic disks or optical disks and other mediums that can store program codes.

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/device and method may be implemented in other manners. For example, the apparatus/equipment embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or Components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

It is to be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described feature, integer, step, operation, element and/or component, but does not exclude one or more other The presence or addition of features, integers, steps, operations, elements, components and/or sets thereof.

It will also be understood that, as used in this specification and the appended claims, the term "and/or" refers to and including any and all possible combinations of one or more of the associated listed items.

As used in the specification of this application and the appended claims, the term "if" may be contextually interpreted as "when" or "once" or "in response to determining" or "in response to detecting ". Similarly, the phrases "if it is determined" or "if the [described condition or event] is detected" may be interpreted, depending on the context, to mean "once it is determined" or "in response to the determination" or "once the [described condition or event] is detected. ]" or "in response to detection of the [described condition or event]".

In addition, in the description of the specification of the present application and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the description, and should not be construed as indicating or implying relative importance.

References in this specification to "one embodiment" or "some embodiments" and the like mean that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc. in various places in this specification are not necessarily All refer to the same embodiment, but mean "one or more but not all embodiments" unless specifically emphasized otherwise. The terms "including", "including", "having" and their variants mean "including but not limited to" unless specifically emphasized otherwise.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features thereof can be equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present application. scope.

Claims

A smart eye mask, characterized in that the smart eye mask is provided with a signal acquisition unit, a processing unit and an EEG electrode, wherein,

The signal acquisition unit is used for:

detecting the EEG signal corresponding to the EEG electrode;

Detect the wearer's heart rate signal;

detecting the head movement signal of the wearer;

The processing unit is used for:

Perform epilepsy detection according to the EEG signal, the heart rate signal and the head movement signal;

When an epileptic seizure is detected, the epileptic seizure data is sent to the terminal device connected with the smart eye mask.
The smart eye mask according to claim 1, wherein the smart eye mask comprises an eye mask body and a fixing strap connected to both ends of the eye mask body, and the EEG electrodes are located on the eye mask body and correspond to the human forehead Area.
The smart eye mask according to claim 2, wherein the signal acquisition unit comprises: an analog front-end chip, the smart eye-mask further comprises: reference electrodes electrically connected to the analog front-end chip respectively, the analog front-end chip It is used for outputting the EEG signal corresponding to the EEG electrode according to the signal collected by the reference electrode and the signal collected by the EEG electrode.
The smart eye mask according to claim 3, wherein the reference electrode is connected to the fixing band through a connecting wire.
The smart eye mask according to claim 3, wherein a nose mask is arranged on the lower side of the middle part of the eye mask body, and the reference electrode is arranged on the nose mask at a position corresponding to the nose tip of the human body.
The smart eye mask according to claim 5, wherein a position corresponding to the bridge of the nose on the eye mask body is provided with a bridge strip matching the bridge of the nose.
The smart eye mask according to any one of claims 1-6, wherein the EEG electrode comprises a plurality of electrodes, the smart eye mask further comprises: a tightness adjustment module, and the processing unit is specifically configured to: detect each The signal quality of the EEG signal corresponding to the EEG electrode, in the case that the signal quality of each of the EEG signals meets the requirements, the epilepsy detection is performed according to the EEG signal, the heart rate signal and the head motion signal; When the signal quality of one EEG signal does not meet the requirements, the tightness adjustment module is controlled to adjust the tightness of the smart eye mask.
The smart eye mask according to claim 7, wherein the processing unit is further configured to: determine a target EEG signal from each of the EEG signals, detect the signal quality of the target EEG signal, When the signal quality of the target EEG signal meets the requirements, the user's sleep state is detected according to the target EEG signal; when the signal quality of the target EEG signal does not meet the requirements, the tightness adjustment module is controlled to adjust the Tightness; send corresponding sleep state data to the terminal device.
The smart eye mask according to claim 8, wherein at least two EEG electrodes are symmetrically arranged on both sides of the smart eye mask, and the processing unit is specifically configured to: detect the sleeping posture of the user according to the head motion signal ; If the sleeping position of the user is lying on the side, then the EEG signal corresponding to the EEG electrode on the same side of the sleeping position of the user is determined as the target EEG signal; if the sleeping position of the user is lying flat, then each Among the EEG signals, the EEG signal with the best signal quality is determined as the target EEG signal.
The smart eye mask according to claim 8, wherein the processing unit is specifically configured to: determine the EEG signal with the best signal quality among the EEG signals as the target EEG signal.
The smart eye mask according to any one of claims 1-10, characterized in that, the smart eye mask further comprises: a sleep stimulation module, and the processing unit is further configured to control the sleep state according to the EEG signal and the detected sleep state. The sleep stimulation module outputs stimulation signals for improving the sleep state of the user.
The smart eye mask according to any one of claims 1-11, wherein the epileptic seizure data includes a plurality of the following data: epileptic seizure time, epileptic seizure duration, seizure severity, and the signal acquisition The unit detects the EEG signal, the heart rate signal and the head movement signal between the first moment before the seizure and the second moment after the end of the seizure.
A health management method, applied to terminal equipment, is characterized in that, comprising:

Obtain the epileptic seizure data detected by the smart eye mask of any one of claims 1-12;

In response to the user's first operation, epileptic seizure records generated based on the acquired epileptic seizure data are displayed, and each of the epileptic seizure records includes the severity, onset time, and onset duration of the seizure.
The method of claim 13, wherein the method further comprises:

In response to the second operation of the user, acquiring the epileptic seizure data input by the user;

Update seizure records.
The method according to claim 13 or 14, wherein the method further comprises:

When it is determined according to the epileptic seizure data that the user is in a state of epileptic seizure, and the severity of the epileptic seizure reaches the target severity, the target contact is alerted.
The method according to claim 15, wherein the reminding the target contact comprises:

sending help information to the target contact;

And/or, calling the target contact, and playing a help recording to the target contact, where both the help information and the help recording indicate the severity of the seizure.
The method according to claim 15 or 16, wherein before the reminding the target contact, the method further comprises:

In response to the user's third operation, displaying the smart eye mask setting interface;

In response to the fourth operation performed by the user in the smart eye mask setting interface, the emergency calling function is activated, and the target contact set by the user is saved.
The method of claim 17, wherein the method further comprises:

In response to the fifth operation performed by the user in the smart eye mask setting interface, the smart eye mask is controlled to turn on or off a target function, the target function including an epilepsy monitoring function for continuous epilepsy detection and/or for continuous Sleep monitoring function for sleep state detection.
The method according to any one of claims 13-18, wherein the method further comprises:

In response to the sixth operation of the user, the statistical data generated based on the epileptic seizure data is displayed, and the statistical data includes the number of epileptic seizures and the duration of epileptic seizures counted in units of different statistical periods corresponding to any severity.
A terminal device, characterized in that it comprises: a memory and a processor, wherein the memory is used to store a computer program; the processor is used to execute the method according to any one of claims 13-19 when the computer program is invoked method.
A health management system, characterized by comprising: the smart goggles according to any one of claims 1-12 and the terminal device according to claim 20 .
A computer-readable storage medium on which a computer program is stored, characterized in that, when the computer program is executed by a processor, the method according to any one of claims 13-19 is implemented.
A chip system, characterized in that the chip system includes a processor, the processor is coupled with a memory, and the processor executes a computer program stored in the memory, so as to realize the method according to any one of claims 13-19 Methods.