CN114306873A - Sleep awakening method and device, intelligent eye patch and storage medium - Google Patents
Sleep awakening method and device, intelligent eye patch and storage medium Download PDFInfo
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Abstract
The application discloses a sleep awakening method, which comprises the following steps: collecting electroencephalogram signals of a user in a preset awakening period; judging whether the user is in a light sleep stage or not according to the electroencephalogram signals; if so, waking up the user by adopting a preset wake-up mode, wherein the preset wake-up mode comprises at least one of a light stimulation wake-up mode, a sound wake-up mode, an electrical stimulation wake-up mode and a vibration wake-up mode. The application also discloses a sleep awakening device, an intelligent eyeshade and a computer readable storage medium. The present application is directed to timely and comfortable waking up a user with an intelligent eyeshade.
Description
Technical Field
The application relates to the field of intelligent wearable equipment, in particular to a sleep awakening method, a sleep awakening device, an intelligent eyeshade and a computer readable storage medium applied to the intelligent eyeshade.
Background
Compare in the tradition and only possess the eye-shade of eyeshield shading effect, intelligent eye-shade still possesses awakening up the function. After the user wears the intelligent eye patch and falls asleep, the sleep quality can be improved by utilizing the eye protection shading effect of the intelligent eye patch, and the user can be awakened by the intelligent eye patch through light stimulation, a buzzer and other means as soon as the user gets up.
However, the current intelligent eyeshade simply combines the function of an alarm clock, the logic of waking up the user is similar to that of a common alarm clock, and the user is forcibly woken up in a relatively strong mode at fixed time and fixed point. However, since the user is awakened in different sleep stages, different influences can be caused on the mental state of the user when the user is awakened, if the user is directly awakened in a strong manner at regular time and fixed point, the user may feel uncomfortable in case that the current sleep state of the user is not good.
The above is only for the purpose of assisting understanding of the technical solutions of the present application, and does not represent an admission that the above is prior art.
Disclosure of Invention
A primary object of the present application is to provide a sleep wake-up method, a sleep wake-up apparatus, an intelligent eyeshade, and a computer readable storage medium, which aim to wake up a user in time and comfortably using the intelligent eyeshade.
In order to achieve the above object, the present application provides a sleep wake-up method, including the following steps:
collecting electroencephalogram signals of a user in a preset awakening period;
judging whether the user is in a light sleep stage or not according to the electroencephalogram signals;
if so, waking up the user by adopting a preset wake-up mode, wherein the preset wake-up mode comprises at least one of a light stimulation wake-up mode, a sound wake-up mode, an electrical stimulation wake-up mode and a vibration wake-up mode.
Optionally, the sleep wake-up method further includes:
and when the user is awakened by adopting a preset awakening mode, adjusting the awakening intensity of the preset awakening mode according to the intensity corresponding to the electroencephalogram signal.
Optionally, before the step of waking up the user in the preset wake-up manner, the method further includes:
acquiring the sleeping time of a user;
and determining the awakening intensity of the preset awakening mode according to the sleep duration.
Optionally, before the step of waking up the user in the preset wake-up manner, the method further includes:
determining the sleep quality of a user according to the electroencephalogram signals of the user in a sleep period, wherein the intelligent eyeshade collects the electroencephalogram signals of the user in a timing or real-time mode in the sleep period;
and determining the awakening intensity of the preset awakening mode according to the sleep quality.
Optionally, after the step of determining the sleep quality of the user according to the electroencephalogram signal of the user in the sleep period, the method further includes:
and outputting the sleep quality to an associated terminal.
Optionally, after the step of determining whether the user is in the light sleep stage according to the electroencephalogram signal, the method further includes:
if not, detecting whether the current time reaches the end time point of the preset awakening time period;
and if the current time does not reach the end time point, returning to the step of executing the step of collecting the electroencephalogram signals of the user in the preset awakening time period.
Optionally, after the step of detecting whether the current time reaches the end time point of the preset wakeup period, the method further includes:
and if the current time point reaches the end time point, awakening the user by adopting the preset awakening mode.
Optionally, the step of determining whether the user is in a light sleep stage according to the electroencephalogram signal includes:
inputting the EEG signals into a learning model, and judging whether a user is in a light sleep stage by using the learning model;
the learning model is obtained by training according to a plurality of training samples, and the training samples comprise mapping characteristics between historical electroencephalogram signals and the user in a light sleep stage.
In order to achieve the above object, the present application further provides a sleep wake-up apparatus, including:
the acquisition module is used for acquiring the electroencephalogram signals of the user in a preset awakening period;
the judging module is used for judging whether the user is in a light sleep stage according to the electroencephalogram signals;
and the awakening module is used for awakening the user in the light sleep stage by adopting a preset awakening mode, wherein the preset awakening mode comprises at least one of a light stimulation awakening mode, a sound awakening mode, an electrical stimulation awakening mode and a vibration awakening mode.
Optionally, the sleep wake-up apparatus further includes:
and the adjusting module is used for adjusting the awakening intensity of the preset awakening mode according to the intensity corresponding to the electroencephalogram signal when the preset awakening mode is adopted to awaken the user.
To achieve the above object, the present application also provides an intelligent eyeshade, which includes: the sleep wake-up program comprises a memory, a processor and a sleep wake-up program which is stored on the memory and can run on the processor, wherein the sleep wake-up program realizes the steps of the sleep wake-up method when being executed by the processor.
To achieve the above object, the present application also provides a computer readable storage medium, which stores a sleep wake-up program, and when the sleep wake-up program is executed by a processor, the sleep wake-up program implements the steps of the above sleep wake-up method.
The application provides a sleep awakening method, sleep awakening device, intelligent eye patch and computer readable storage medium, utilize intelligent eye patch to gather the EEG signal when the user sleeps at awakening period, and whether be in the shallow sleep stage when awakening the period and arriving on the basis of EEG signal detection user, and when the user awakens up and sleeps comfortable shallow sleep stage more easily, adopt at least one mode such as light stimulation, electro photoluminescence, sound, vibration to awaken the user, can guarantee that the user can in time be awakened up, can guarantee again that the user is awakened up the comfort after.
Drawings
Fig. 1 is a schematic diagram illustrating a sleep wake-up method according to an embodiment of the present application;
FIG. 2 is a diagram illustrating a sleep wake-up method according to a second embodiment of the present application;
FIG. 3 is a diagram illustrating a sleep wake-up method according to a third embodiment of the present application;
FIG. 4 is a diagram illustrating a fourth embodiment of a method for waking up from sleep;
fig. 5 is a schematic block diagram of a sleep wake-up apparatus according to an embodiment of the present application;
fig. 6 is a schematic block diagram of the internal structure of the intelligent eyeshade according to an embodiment of the present application.
The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be illustrative of the present invention and should not be construed as limiting the present invention, and all other embodiments that can be obtained by one skilled in the art based on the embodiments of the present invention without inventive efforts shall fall within the scope of protection of the present invention.
Referring to fig. 1, in an embodiment, the sleep wake-up method includes:
step S10, collecting electroencephalogram signals of a user in a preset awakening period;
step S20, judging whether the user is in a light sleep stage according to the electroencephalogram signal;
and step S30, if yes, waking up the user by adopting a preset wake-up mode, wherein the preset wake-up mode comprises at least one of a light stimulation wake-up mode, a sound wake-up mode, an electrical stimulation wake-up mode and a vibration wake-up mode.
In this embodiment, the execution terminal in the embodiment is an intelligent eyeshade (or sleep wake-up device), and may also be a device for controlling the intelligent eyeshade. The following description will take an execution terminal as an example of an intelligent eyeshade.
As described in step S10, the smart mask is equipped with EEG (Electroencephalogram) electrodes, and when the user wears the smart mask, the smart mask can collect electroencephalograms of the user through the EEG electrodes.
Optionally, when the intelligent eye mask detects that the current time point is in the preset wake-up period, the current electroencephalogram signal of the user is acquired. And the preset awakening time period is determined according to the preset time length and the ringing time point.
Optionally, the intelligent eyeshade is provided with an alarm clock function, and a user can set a ringing time point by using the alarm clock function; the preset time period can be set by the user, or can be a preset value, and the value of the preset value can range from 5 minutes to 1 hour, preferably 20 minutes or 30 minutes, because the light sleep stage of the human body during sleep generally lasts for 20-30 minutes.
Optionally, the ring time point is used as an end time point of the preset wake-up period, and the preset time duration is backed up at the end time point, which is a start time point of the preset wake-up period (that is, the time duration corresponding to the preset wake-up period is the preset time duration).
As shown in step S20, the sleep cycle of the human body during sleep can be roughly divided into an in-sleep stage, a light sleep stage, a deep sleep stage and a continuous deep sleep stage. Wherein, the human body generally starts to stay about 10 minutes from the sleep stage and then shifts to the shallow sleep stage; when the light sleep stage lasts for about 20 minutes, the deep sleep stage is started; in the deep sleep stage, which lasts about 40 minutes, a continuation deep sleep stage may be entered. Since the continuation of the deep sleep stage is an extension of the deep sleep stage, not everyone can enter this stage while sleeping, and may only stay in the deep sleep stage if the sleep quality is not good. Generally, however, the sleep cycle of the human body lasts for about 90 minutes on average, that is, every 90 minutes, the human body gradually turns from deep sleep back to shallow sleep, and then goes back to deep sleep again from shallow sleep, and so on.
When the human body is in different sleep stages, the activity degrees of the electroencephalogram signals of the human body are different. Generally, the intensity of the EEG signals in the sleep stage and the light sleep stage is greater than that in the deep sleep stage and the extended deep sleep stage.
Optionally, as long as the deep sleep stage is an extension of the deep sleep stage, the sleep-in stage may also be equivalent to the beginning of the light sleep stage, and the intensities of the electroencephalograms of the sleep-in stage and the light sleep stage are relatively similar, so the sleep-in stage may also be classified as the light sleep stage in this embodiment.
Optionally, the intelligent eye mask may be a pre-recorded mapping relationship between the intensity of the electroencephalogram signal and the corresponding sleep stage when the user is in different sleep stages. If the electroencephalogram signal with the intensity of A corresponds to a light sleep stage, and the electroencephalogram signal with the intensity of B corresponds to a deep sleep stage, when the intensity of the current electroencephalogram signal of the user is the intensity of A, the user is indicated to be in the light sleep stage.
Optionally, after the intelligent eyeshade collects the current electroencephalogram signals of the user, whether the mapping relation exists between the strength of the electroencephalogram signals and the light sleep stage or not is detected, and whether the user is in the light sleep stage or not is detected.
Optionally, when the intelligent eye patch detects that the mapping relation exists between the intensity of the current electroencephalogram signal of the user and the light sleep stage, it is determined that the user is currently in the light sleep stage; when the intelligent eye patch detects that the intensity of the current electroencephalogram signal of the user does not have a mapping relation with the light sleep stage, the intelligent eye patch judges that the user is not in the light sleep stage at present (if the intensity of the current electroencephalogram signal has a mapping relation with the deep sleep stage substantially, the user is in the deep sleep stage at present).
In step S30, when the intelligent eyeshade detects that the user is currently in the light sleep stage, the user is woken up in a preset wake-up manner.
Optionally, the preset wake-up mode includes at least one of a light stimulation wake-up mode, a sound wake-up mode, an electrical stimulation wake-up mode, and a vibration wake-up mode.
Optionally, the intelligent eye mask has two layers, a part attached to the eyes is a semi-transparent fabric, an outer layer part is a material completely isolating the light source, and an led (light Emitting diode) light source is arranged in the interlayer. When the intelligent eyeshade executes a light stimulation awakening mode, the LED light source is scattered through the semi-transparent cloth, an effect similar to sunlight irradiation is formed, and eyes of a user are stimulated, so that the user is awakened.
Optionally, the intelligent eye patch is provided with a buzzer. When the intelligent eyeshade executes a voice awakening mode, music or an alarm sound can be output through the buzzer, so that a user is awakened.
Alternatively, when the smart eyewear performs the electrical stimulation wake-up mode, a slight current (within a range of current that the human body can endure) may be output through the electrodes in contact with the skin of the user to wake up the user by the electrical stimulation.
Optionally, the intelligent eye shield is provided with a vibrating device. When the intelligent eyeshade executes the vibration awakening mode, the user can be awakened through the vibration device.
Because the light sleep stage belongs to the sleep stage which is easy to be awakened by the user, the body of the user can not resist too much when the user is awakened in the light sleep stage; when the user is in the deep sleep stage, the user is difficult to wake up, and the body can resist to the wake up, even discomfort such as dizziness, somnolence and the like can occur in a period of time just after the user wakes up.
Therefore, when the user is detected to be in the shallow sleep stage in the preset awakening period, the user is awakened by adopting the preset awakening mode, so that the user can be awakened in a state of being easy to awaken and comfortable to sleep, and the user can be ensured to be awakened in time and comfortable after being awakened.
Optionally, according to the actual requirement, a combination of multiple preset wake-up modes can be selected to wake up the user, so that the user can be easily woken up. For example, when the user is awakened by adopting the light stimulation awakening mode, the user can be awakened by adopting the voice awakening mode.
In an embodiment, the intelligent eyeshade is used for collecting electroencephalograms when a user sleeps in an awakening period, whether the user is in a shallow sleep stage when the awakening period arrives is detected based on the electroencephalograms, and when the user is easily awakened and the sleep is comfortable in the shallow sleep stage, the user is awakened by adopting at least one mode of light stimulation, electrical stimulation, sound, vibration and the like, so that the user can be ensured to be awakened in time, and the comfort of the user after being awakened can be ensured.
In an embodiment, on the basis of the above embodiments, the sleep wake-up method further includes:
and step S31, when a preset awakening mode is adopted to awaken the user, adjusting the awakening intensity of the preset awakening mode according to the intensity corresponding to the electroencephalogram signal.
In this embodiment, when the intelligent eyeshade wakes up the user in the preset wake-up mode, the intelligent eyeshade also adjusts the wake-up intensity of the preset wake-up mode according to the intensity corresponding to the current electroencephalogram signal. The higher the intensity corresponding to the current electroencephalogram signal is, the higher the awakening intensity of the preset awakening mode is.
Because the electroencephalogram signals are more and more active (namely the intensity corresponding to the electroencephalogram signals is more and more increased) in the process of gradually awakening the human body, when the preset awakening mode is executed at first, the user can be awakened by adopting the appropriate awakening intensity, and in the process of gradually awakening the user, the intensity corresponding to the electroencephalogram signals is more and more increased, so that the awakening intensity of the preset awakening mode can be correspondingly increased.
Therefore, the user in the sleep can gradually adapt to the awakening mode and awaken the user comfortably and pleasantly step by step, and the awakening strength of the preset awakening mode can be ensured to be enough to awaken the user in time.
For example, when the preset wake-up mode is the light stimulation wake-up mode, the intelligent eyeshade may initially light the LED light source at a certain light source brightness, and gradually increase the brightness of the LED light source according to the gradually enhanced electroencephalogram signal in the process that the user gradually wakes up (i.e., increase the wake-up intensity of the light stimulation wake-up mode), so that the user is more comfortable and is more easily woken up.
For example, when the preset wake-up mode is a sound wake-up mode, the intelligent eyeshade may initially control the buzzer to output a certain volume, and gradually increase the volume output by the buzzer according to the gradually-enhanced electroencephalogram signals in the process that the user wakes up gradually (i.e., increase the wake-up intensity of the sound wake-up mode), so that the user is more comfortable and is more easily woken up.
For example, when the preset wake-up mode is an electrical stimulation wake-up mode, the intelligent eyeshade may initially output a certain current to electrically stimulate the user, and gradually increase the output current according to the gradually-enhanced electroencephalogram signals in the process that the user gradually wakes up (i.e., increase the wake-up intensity of the electrical stimulation wake-up mode is achieved), so that the user is more comfortable and is more easily woken up. It should be noted that, when the intelligent eyeshade performs an electrical stimulation wake-up mode on the user, the output current does not exceed the range that the human body can bear at most, and the physical health of the user is not affected.
For example, when the preset wake-up mode is a vibration wake-up mode, the intelligent eyeshade may initially output a certain power to control the operation of the vibration device, and gradually increase the output power according to the gradually enhanced electroencephalogram signal in the process that the user gradually wakes up, so as to increase the vibration amplitude of the vibration device (thus increasing the wake-up intensity of the vibration wake-up mode), so that the user is more comfortable and is more easily woken up.
It should be noted that, although the electroencephalogram signal tends to increase gradually during the gradual waking process of the user, the curve of the signal intensity in the process is not linearly increasing, but has a certain fluctuation. Therefore, when the awakening intensity of the preset awakening mode is adjusted according to the intensity corresponding to the electroencephalogram signal, the determination of the intensity corresponding to the electroencephalogram signal can be that the sum of the intensities corresponding to the electroencephalogram signals in a certain time length (or the mean value of the intensities corresponding to the electroencephalogram signals) is calculated at intervals of the certain time length, and then the awakening intensity of the preset awakening mode is adjusted according to the calculation result.
Therefore, in the process of waking up the user by adopting the preset wake-up mode, according to the strength of the brain electrical signal gradually increased by the user, the wake-up strength of the preset wake-up mode is gradually increased, so that the user in sleep can gradually adapt to the wake-up mode and wake up the user gradually and comfortably, and the wake-up strength of the preset wake-up mode can be ensured to be enough to wake up the user in time.
In an embodiment, on the basis of the above embodiment, before the step of waking up the user in the preset wake-up manner, the method further includes:
step S40, obtaining the sleep duration of the user;
and step S41, determining the awakening intensity of the preset awakening mode according to the sleep time length.
In this embodiment, the intelligent eye patch can monitor and record the sleep duration of the user.
Optionally, when the intelligent eye patch detects that the user is in the shallow sleep stage in the preset wake-up period, the wake-up intensity of the preset wake-up mode is determined according to the recorded sleep duration of the user. And determining that the awakening intensity of the preset awakening mode is larger as the sleep duration is longer.
Optionally, after the intelligent eye patch determines the wakeup intensity of the preset wakeup mode according to the sleep duration, the corresponding preset wakeup mode is executed by adopting the wakeup intensity, so as to wake up the user.
Therefore, the longer the sleeping time of the user is, the better the sleeping quality of the user is, so that when the user is awakened by adopting a preset awakening mode, the user can be awakened by adopting higher awakening strength, and the user is quickly awakened; the smaller the sleeping time of the user is, the worse the sleeping quality of the user is, so that when the user is awakened by adopting a preset awakening mode, the user can be awakened gently by adopting relatively smaller awakening strength to ensure the comfort when the user is awakened.
Optionally, the intelligent eyeshade determines the wakeup intensity of the preset wakeup mode according to the sleep duration, and in the process of executing the preset wakeup mode, the wakeup intensity of the execution mode can be adjusted according to the current intensity of the electroencephalogram signal of the user on the basis of the wakeup intensity of the current execution mode (i.e., step S31 is executed at the same time). The higher the intensity corresponding to the current electroencephalogram signal is, the higher the awakening intensity of the preset awakening mode is.
Therefore, the awakening intensity of the preset awakening mode is adjusted according to the sleep quality of the user and the strength of the electroencephalogram signal, the user in sleep can adapt to the awakened mode gradually and awaken the user comfortably step by step, the awakening intensity of the preset awakening mode can be ensured to be enough to awaken the user in time, and the comfort of the user in awakening can be further ensured.
In an embodiment, on the basis of the above embodiment, before the step of waking up the user in the preset wake-up manner, the method further includes:
step S50, determining the sleep quality of the user according to the electroencephalogram signals of the user in the sleep period, wherein the intelligent eye patch collects the electroencephalogram signals of the user in the sleep period in a timing or real-time mode;
and step S51, determining the awakening intensity of the preset awakening mode according to the sleep quality.
In the embodiment, when the user falls asleep, the intelligent eyeshade can continuously monitor the electroencephalogram signals of the user in the sleep period in a timing or real-time mode. The sleep period of the user at the current time may be a period of falling asleep before a preset wake-up period, or may be a period of falling asleep before the current time point.
Optionally, when the intelligent eyeshade detects that the user is in a shallow sleep stage in the preset wake-up period, the sleep quality of the user is determined according to the electroencephalogram signals of the user in the current sleep period.
Optionally, the intelligent eyeshade may calculate a mean value of intensities of all electroencephalograms in the whole sleep period, and then determine the sleep quality of the user according to the calculated mean value. The intelligent eyeshade is preset with a mapping relation between the mean value of the strength of the electroencephalogram signals and the sleep quality, and the lower the mean value of the strength of the electroencephalogram signals is, the better the sleep quality is reflected (the quality of the sleep quality can be measured by corresponding quality grades, and the better the sleep quality is, the higher the corresponding quality grade is).
Optionally, after the intelligent eyeshade determines the sleep quality of the user, the awakening intensity of the preset awakening mode is further determined according to the sleep quality. And determining that the awakening intensity of the obtained preset awakening mode is higher when the quality grade corresponding to the sleep quality is higher.
Optionally, after the intelligent eyeshade determines the awakening intensity of the preset awakening mode according to the sleep quality of the user, the intelligent eyeshade executes the corresponding preset awakening mode according to the awakening intensity, so as to awaken the user.
Therefore, the better the sleep quality of the user is, the higher the awakening intensity can be adopted to awaken the user when the user is awakened by adopting the preset awakening mode, so that the user is awakened quickly; and the worse the sleep quality of the user is, when the user is awakened by adopting a preset awakening mode, the user can be awakened gently by adopting relatively smaller awakening intensity so as to ensure the comfort when the user is awakened.
Optionally, the intelligent eye patch determines the wakeup intensity of the preset wakeup mode according to the sleep quality of the user, and in the process of executing the preset wakeup mode, the wakeup intensity of the execution mode can be adjusted according to the current strength of the electroencephalogram signal of the user on the basis of the wakeup intensity of the current execution mode (i.e., step S31 is executed at the same time). The higher the intensity corresponding to the current electroencephalogram signal is, the higher the awakening intensity of the preset awakening mode is.
Therefore, the awakening intensity of the preset awakening mode is adjusted according to the sleep quality of the user and the strength of the electroencephalogram signal, the user in sleep can adapt to the awakened mode gradually and awaken the user comfortably step by step, the awakening intensity of the preset awakening mode can be ensured to be enough to awaken the user in time, and the comfort of the user in awakening can be further ensured.
In an embodiment, on the basis of the above embodiment, after the step of determining the sleep quality of the user according to the electroencephalogram signal of the user in the sleep period, the method further includes:
and step S52, outputting the sleep quality to a related terminal.
In this embodiment, after the intelligent eyeshade determines the sleep quality of the user according to the electroencephalogram signals of the user in the current sleep period, the sleep quality of the user may be output to the associated terminal associated with the intelligent eyeshade in advance. Wherein, the associated terminal can be a smart watch, a mobile terminal and the like.
In this way, automatic generation and push of sleep quality is achieved. After the user wakes up, the user can conveniently know the sleep quality of the user after the user falls asleep through the associated terminal.
In an embodiment, referring to fig. 2, on the basis of the embodiment shown in fig. 1, after the step of determining whether the user is in the light sleep stage according to the electroencephalogram signal, the method further includes:
step S60, if not, detecting whether the current time reaches the end time point of the preset awakening time interval;
and step S61, if the current time does not reach the end time point, returning to the step of collecting the electroencephalogram signals of the user in the preset awakening time period.
In this embodiment, when the intelligent eye patch detects that the user is not currently in the light sleep stage (if it is detected that the user is currently in the deep sleep stage) in the preset wake-up period, it is further detected whether the current time point reaches the end time point of the preset wake-up period.
Optionally, when the intelligent eye mask detects that the current time point does not reach the end time point of the preset wake-up period, the step of performing the step of collecting the electroencephalogram signal of the user in the preset wake-up period is returned (i.e., the step S10 is performed). Thus, the steps S10-S20 are executed in a loop until the user is detected to be in the light sleep stage, and the user is awakened by adopting the preset awakening mode, or until the current time point is detected to reach the end time point of the preset awakening period.
Like this, do not be in the light sleep stage at the user at present, and when not reaching the end time point of presetting awakening period again at present, the intelligent eye-shade can not wake up the user earlier, but continuously monitors whether the user is in the light sleep stage to detect the user and shift into the light sleep stage after, awaken up the user in the mode of carrying out presetting awakening, can guarantee that the user can in time be awakened up, can guarantee the comfort after the user is awakened up again.
In an embodiment, referring to fig. 3, on the basis of the above embodiments shown in fig. 1 to fig. 2, after the step of detecting whether the end time point of the preset wake-up period is reached currently, the method further includes:
and step S62, if the current end time point is detected to be reached, awakening the user by adopting the preset awakening mode.
In this embodiment, when the intelligent eye patch detects that the user is not currently in the light sleep stage (if it is detected that the user is currently in the deep sleep stage) in the preset wake-up period, it is further detected whether the current time point reaches the end time point of the preset wake-up period.
Optionally, when the intelligent eyeshade detects that the current time point reaches the end time point of the preset awakening period, the user can be awakened by directly adopting a preset awakening mode so as to ensure that the user can be awakened in time.
Optionally, the intelligent eyewear may determine the wake-up intensity of the preset wake-up mode by performing steps S40-S41 or by performing steps S50-S51 before performing the preset wake-up mode. Of course, in the process of waking up the user by the intelligent eyeshade in the preset wake-up mode, the wake-up intensity of the execution mode may still be adjusted according to the current strength of the electroencephalogram signal of the user on the basis of the wake-up intensity of the current execution mode (i.e. step S31 is executed at the same time). The higher the intensity corresponding to the current electroencephalogram signal is, the higher the awakening intensity of the preset awakening mode is.
Therefore, the awakening intensity of the preset awakening mode is adjusted according to the sleep quality of the user and the strength of the electroencephalogram signal, the user in sleep can adapt to the awakened mode gradually and awaken the user comfortably step by step, the awakening intensity of the preset awakening mode can be ensured to be enough to awaken the user in time, and the comfort of the user in awakening can be further ensured.
In an embodiment, referring to fig. 4, on the basis of the embodiments shown in fig. 1 to 3, the step of determining whether the user is in the light sleep stage according to the electroencephalogram signal includes:
step S21, inputting the electroencephalogram signals into a learning model, and judging whether a user is in a light sleep stage by using the learning model;
the learning model is obtained by training according to a plurality of training samples, and the training samples comprise mapping characteristics between historical electroencephalogram signals and the user in a light sleep stage.
In this embodiment, a learning model is constructed in advance based on a machine learning technique.
Optionally, a related engineer may collect, in advance, historical electroencephalograms of a plurality of users in a plurality of historical periods through the intelligent eyeshade, and mapping characteristics of the historical electroencephalograms and the users in the light sleep stage, construct a plurality of training samples, and input the plurality of training samples into the learning model for iterative training, so that the learning model can continuously learn the mapping characteristics of the electroencephalograms and the users in the light sleep stage until the training of the learning model is completed. Therefore, the trained learning model has the capability of judging whether the user is in the light sleep stage according to the electroencephalogram signal of the user.
Optionally, the trained learning model may be recorded into a database of the intelligent eyeshade, or uploaded to a server, and the server and the intelligent eyeshade may be communicatively connected.
Optionally, when the intelligent eye patch collects the electroencephalogram signals of the user in the preset awakening period, the electroencephalogram signals of the user in the preset awakening period are input into the learning model. When the learning model receives the electroencephalogram signals input by the intelligent eye shield, whether the electroencephalogram signals have a mapping relation with the light sleep stage or not is detected. When the mapping relation between the electroencephalogram signal and the light sleep stage is detected, judging that the user corresponding to the electroencephalogram signal is in the light sleep stage; and if the electroencephalogram signal is detected to have no mapping relation with the light sleep stage, judging that the user corresponding to the electroencephalogram signal is not in the light sleep stage.
Then the learning model outputs the corresponding result that the user is in the shallow sleep stage or not in the shallow sleep stage, and the intelligent eyeshade can judge whether the user is in the shallow sleep stage according to the output result of the learning model.
Therefore, through the pre-constructed learning model, whether the user is in a light sleep stage or not can be identified more accurately according to the electroencephalogram signals, and the opportunity of waking up the user is managed more accurately, so that the user can be woken up more comfortably.
Optionally, the training samples of the learning model may further include mapping features between historical electroencephalograms and historical Polysomnography (PSG). The method is characterized in that a relevant engineer training a learning model simultaneously acquires a historical polysomnogram corresponding to a historical electroencephalogram and adds the acquired polysomnogram into a training sample when acquiring the historical electroencephalogram to make the training sample. Therefore, when the learning model is trained based on the training samples, the learning model can learn the mapping characteristics between the electroencephalogram signal and the polysomnogram of the user, and the trained learning model can have the capability of generating the polysomnogram of the user according to the electroencephalogram signal of the user. And performing auxiliary analysis based on the corresponding wave band of the electroencephalogram signal of the shallow sleep stage reflected by the polysomnogram (each sleep stage of the user can be divided more accurately according to the polysomnogram, whether the current electroencephalogram signal of the user is in the signal wave band corresponding to the shallow sleep stage or not is detected, that is, whether the user is currently in the shallow sleep stage or not is detected), so that whether the user is in the shallow sleep stage or not can be identified more accurately.
Optionally, by using the trained learning model, the intelligent eye patch can also generate a corresponding polysomnogram according to all electroencephalogram signals collected at the sleep stage of the user, and output the generated polysomnogram to the associated terminal, so that after the user wakes up, the sleep state of the user can be known more intuitively based on the polysomnogram received by the associated terminal.
Referring to fig. 5, an embodiment of the present application further provides a sleep wake-up apparatus 10, including:
the acquisition module 11 is used for acquiring electroencephalogram signals of a user in a preset awakening period;
the judging module 12 is used for judging whether the user is in a light sleep stage according to the electroencephalogram signal;
and the awakening module 13 is used for awakening the user in the light sleep stage by adopting a preset awakening mode, wherein the preset awakening mode comprises at least one of a light stimulation awakening mode, a sound awakening mode, an electrical stimulation awakening mode and a vibration awakening mode.
Optionally, on the basis of the above embodiment, the sleep wake-up apparatus further includes:
and the adjusting module is used for adjusting the awakening intensity of the preset awakening mode according to the intensity corresponding to the electroencephalogram signal when the preset awakening mode is adopted to awaken the user.
Referring to fig. 6, the embodiment of the present application further provides an intelligent eyeshade, and the internal structure of the intelligent eyeshade can be as shown in fig. 6. The intelligent eyewear includes a processor, memory, network interface, and database connected by a system bus. Wherein the computer designed processor is used to provide computational and control capabilities. The memory of the intelligent eye patch comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the intelligent eyewear is used for a sleep wake-up procedure. The network interface of the intelligent eye patch is used for connecting and communicating with an external terminal through a network. The input device of the intelligent eyeshade is used for receiving signals input by external equipment. The computer program is executed by a processor to implement a sleep wake-up method as described in the above embodiments.
It will be understood by those skilled in the art that the structure shown in fig. 6 is a block diagram of only a portion of the structure associated with the present application, and does not constitute a limitation on the intelligent eyewear to which the present application is applied.
Furthermore, the present application also proposes a computer-readable storage medium, which includes a sleep wake-up program, and the sleep wake-up program, when executed by a processor, implements the steps of the sleep wake-up method according to the above embodiments. It is to be understood that the computer-readable storage medium in the present embodiment may be a volatile-readable storage medium or a non-volatile-readable storage medium.
In summary, according to the sleep wake-up method, the sleep wake-up apparatus, the intelligent eyeshade and the storage medium provided in the embodiments of the present application, the intelligent eyeshade is used to collect the electroencephalogram signals of the user during sleep in the wake-up period, and detect whether the user is in the shallow sleep stage when the wake-up period arrives based on the electroencephalogram signals, and when the user wakes up the shallow sleep stage which is comfortable to sleep and is relatively easy to wake up, the user is woken up by at least one of light stimulation, electrical stimulation, sound, vibration and the like, so that the user can be ensured to be woken up in time, and the comfort of the user after being woken up can be ensured.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
The above description is only for the preferred embodiment of the present application and not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application, or which are directly or indirectly applied to other related technical fields, are intended to be included within the scope of the present application.
Claims (12)
1. A sleep wake-up method, comprising:
collecting electroencephalogram signals of a user in a preset awakening period;
judging whether the user is in a light sleep stage or not according to the electroencephalogram signals;
if so, waking up the user by adopting a preset wake-up mode, wherein the preset wake-up mode comprises at least one of a light stimulation wake-up mode, a sound wake-up mode, an electrical stimulation wake-up mode and a vibration wake-up mode.
2. The sleep wake-up method according to claim 1, characterized in that the sleep wake-up method further comprises:
and when the preset awakening mode is adopted to awaken the user, adjusting the awakening intensity of the preset awakening mode according to the intensity corresponding to the electroencephalogram signal.
3. The sleep wake-up method according to claim 1, wherein before the step of waking up the user in the preset wake-up manner, the method further comprises:
acquiring the sleeping time of a user;
and determining the awakening intensity of the preset awakening mode according to the sleep duration.
4. The sleep wake-up method according to claim 1, wherein before the step of waking up the user in the preset wake-up manner, the method further comprises:
determining the sleep quality of a user according to the electroencephalogram signals of the user in a sleep period, wherein the electroencephalogram signals of the user are collected in a timing or real-time mode in the sleep period;
and determining the awakening intensity of the preset awakening mode according to the sleep quality.
5. The sleep wake-up method according to claim 4, characterized in that after the step of determining the sleep quality of the user according to the electroencephalogram signal of the user during the sleep period, the method further comprises:
and outputting the sleep quality to an associated terminal.
6. The sleep wake-up method according to claim 1, characterized in that after the step of determining whether the user is in a light sleep stage according to the electroencephalogram signal, the method further comprises:
if not, detecting whether the current time reaches the end time point of the preset awakening time period;
and if the current time does not reach the end time point, returning to the step of executing the step of collecting the electroencephalogram signals of the user in the preset awakening time period.
7. The sleep wake-up method according to claim 6, characterized in that after the step of detecting whether the end time point of the preset wake-up period is reached currently, the method further comprises:
and if the current time point reaches the end time point, awakening the user by adopting the preset awakening mode.
8. The sleep wake-up method according to any of the claims 1-7, characterized in that the step of determining whether the user is in a light sleep stage according to the brain electrical signal comprises:
inputting the EEG signals into a learning model, and judging whether a user is in a light sleep stage by using the learning model;
the learning model is obtained by training according to a plurality of training samples, and the training samples comprise mapping characteristics between historical electroencephalogram signals and the user in a light sleep stage.
9. A sleep wake-up device, comprising:
the acquisition module is used for acquiring the electroencephalogram signals of the user in a preset awakening period;
the judging module is used for judging whether the user is in a light sleep stage according to the electroencephalogram signals;
and the awakening module is used for awakening the user in the light sleep stage by adopting a preset awakening mode, wherein the preset awakening mode comprises at least one of a light stimulation awakening mode, a sound awakening mode, an electrical stimulation awakening mode and a vibration awakening mode.
10. The sleep wake-up device according to claim 9, characterized in that it further comprises:
and the adjusting module is used for adjusting the awakening intensity of the preset awakening mode according to the intensity corresponding to the electroencephalogram signal when the preset awakening mode is adopted to awaken the user.
11. An intelligent eyewear, comprising a memory, a processor, and a sleep wake-up program stored on the memory and executable on the processor, the sleep wake-up program when executed by the processor implementing the steps of the sleep wake-up method of any of claims 1-8.
12. A computer-readable storage medium, having stored thereon a sleep wake-up program, which when executed by a processor implements the steps of the sleep wake-up method according to any one of claims 1 to 8.
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