阅读说明：本技术 基于智能眼罩的睡眠监测处理方法、装置、智能眼罩 (Sleep monitoring processing method and device based on intelligent eyeshade and intelligent eyeshade ) 是由 罗中华 贺文强 于 2021-08-24 设计创作，主要内容包括：本发明公开了基于智能眼罩的睡眠监测处理方法、装置、智能眼罩,其中,上述基于智能眼罩的睡眠监测处理方法包括：通过设置在智能眼罩上的电极片采集睡眠用户的脑电信号；基于所述脑电信号,进行带通滤波提取出预设的脑电波形；对所提取出预设的脑电波形进行分析判断,得到睡眠质量参数；将所述睡眠质量参数通过智能眼罩的BLE模块发送给用户移动终端输出显示。旨在解决现有技术中的眼罩只能为用户提供睡眠环境的问题,使用户在使用眼罩提高睡眠环境的同时利用电极片采集睡眠用户脑电信号进而处理得到用户的脑电波形分析用户的睡眠质量参数,使用户了解自身睡眠质量,提高用户睡眠体验。(The invention discloses a sleep monitoring processing method and device based on an intelligent eyeshade and the intelligent eyeshade, wherein the sleep monitoring processing method based on the intelligent eyeshade comprises the following steps: collecting electroencephalogram signals of a sleeping user through an electrode plate arranged on an intelligent eyeshade; based on the electroencephalogram signals, performing band-pass filtering to extract preset electroencephalogram waveforms; analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters; and sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade. The eye shield aims to solve the problem that the eye shield in the prior art can only provide a sleep environment for a user, so that the user can acquire the brain electrical signals of the sleep user by using the electrode plate while using the eye shield to improve the sleep environment, and then the brain electrical signals are processed to obtain the sleep quality parameters of the user, so that the user can know the sleep quality of the user, and the sleep experience of the user is improved.)

1. A sleep monitoring processing method based on an intelligent eye patch is characterized by comprising the following steps:

collecting electroencephalogram signals of a sleeping user through an electrode plate arranged on an intelligent eyeshade;

based on the electroencephalogram signals, performing band-pass filtering to extract preset electroencephalogram waveforms;

analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters;

and sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade.

2. The sleep monitoring processing method based on the intelligent eyeshade according to the claim 1, characterized in that, the step of collecting the brain electrical signals of the sleeping user through the electrode slice arranged on the intelligent eyeshade comprises the following steps:

the passband range of the electroencephalogram signal is preset.

3. The sleep monitoring processing method based on the intelligent eyeshade according to the claim 1, characterized in that the step of collecting the brain electrical signals of the sleeping user through the electrode slice arranged on the intelligent eyeshade comprises:

when the intelligent eye patch is detected to be worn on the eyes of the user and waits for a preset time, the electrode plates on the intelligent eye patch are controlled to acquire the electroencephalogram signals of the sleeping user in a 4-channel analog-to-digital detection mode.

4. The sleep monitoring processing method based on the intelligent eyeshade according to claim 1, wherein the step of collecting the brain electrical signals of the sleeping user through electrode pads arranged on the intelligent eyeshade further comprises:

collecting simulated electroencephalogram signals of a sleeping user by adopting signals with the sampling frequency of 500HZ and the sensitivity of 400 plus one 800uV/cm through electrode plates arranged on an intelligent eyeshade;

and converting the acquired analog brain electrical signals into digital brain electrical signals.

5. The sleep monitoring processing method based on intelligent eyepatches as claimed in claim 1, wherein the step of performing band-pass filtering to extract a preset brain waveform based on the brain electrical signals comprises:

removing baseline drift and power frequency interference from the acquired digital electroencephalogram signals;

and performing band-pass filtering on the processed digital electroencephalogram signals to extract a preset electroencephalogram waveform.

6. The sleep monitoring processing method based on intelligent eyepatches as claimed in claim 1, wherein the step of performing band-pass filtering to extract a preset brain waveform based on the brain electrical signals further comprises:

enabling the electroencephalogram signal to pass through a preset first pass band of 0.5-4HZ, and performing Fourier transform and inverse Fourier transform on the electroencephalogram signal to obtain a delta electroencephalogram waveform; wherein the delta brain waveform is a deep sleep brain waveform;

the electroencephalogram signal is subjected to Fourier transform and inverse Fourier transform through a preset second passband 4-8HZ to obtain a theta electroencephalogram waveform; wherein the theta brain waveform is a brain waveform in light sleep;

enabling the electroencephalogram signal to pass through a preset third passband 8-13HZ, and performing Fourier transform and inverse Fourier transform on the electroencephalogram signal to obtain an alpha electroencephalogram waveform; wherein the alpha brain waveform is a half-sleep half-wake brain waveform;

the electroencephalogram signal passes through a preset fourth passband 13-31HZ, and Fourier transform and inverse Fourier transform are carried out on the electroencephalogram signal to obtain a beta electroencephalogram waveform; wherein the beta brain waveform is a brain waveform that occurs while awake;

and performing the Fourier transform processing on the electroencephalogram signals to respectively obtain a delta brain waveform, a theta brain waveform, an alpha brain waveform and a beta brain waveform.

7. The sleep monitoring processing method based on intelligent eyepatches as claimed in claim 6, wherein the step of analyzing and judging the extracted preset brain waveforms to obtain sleep quality parameters comprises:

analyzing the obtained delta brain waveform, theta brain waveform, alpha brain waveform and beta brain waveform;

whether the sleep is asleep or not is analyzed by the energy mean of the alpha brain waveform Ua/beta brain waveform Ub, and the sleep depth is distinguished by the energy mean of the alpha brain waveform Ua/delta brain waveform Ud, resulting in a sleep quality parameter.

8. A sleep monitor processing apparatus based on intelligent eye patch, the apparatus comprising:

the acquisition module is used for acquiring electroencephalogram signals of the sleeping user through electrode plates arranged on the intelligent eyeshade;

the band-pass filtering processing module is used for carrying out band-pass filtering on the basis of the electroencephalogram signals to extract preset electroencephalogram waveforms;

the analysis and judgment module is used for analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters;

and the sending module is used for sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade.

9. An intelligent eye shield, comprising: the intelligent eyeshade comprises an intelligent eyeshade body, a memory and a processor which are arranged in the intelligent eyeshade body, an electrode plate arranged on the intelligent eyeshade body, and a sleep monitoring processing program based on the intelligent eyeshade, wherein the sleep monitoring processing program based on the intelligent eyeshade is stored on the memory and can run on the processor, the steps of the sleep monitoring processing method based on the intelligent eyeshade are realized according to any one of claims 1 to 7 when the sleep monitoring processing program based on the intelligent eyeshade is executed by the processor, and the electrode plate is used for collecting electroencephalogram signals of a sleeping user.

10. A computer-readable storage medium, wherein the computer-readable storage medium has a smart eyewear-based sleep monitoring processing program stored thereon, which when executed by a processor, implements the steps of the smart eyewear-based sleep monitoring processing method of any of claims 1-7.

Technical Field

The invention relates to the technical field of eyepatches, in particular to a sleep monitoring processing method and device based on an intelligent eyepatch and the intelligent eyepatch.

Background

The main functions of the sleeping eye mask are to block light, eliminate interference and create a low-light environment suitable for sleeping. The eyeshade (sleep eyeshade) in the prior art can only provide a dark sleep environment for a user so as to improve the sleep quality of the user, but cannot further help the user to know or analyze the sleep quality, and is sometimes inconvenient for the user to use.

Thus, there is still a need for improvement and development of the prior art.

Disclosure of Invention

The invention mainly aims to provide a sleep monitoring processing method and device based on an intelligent eye patch, the intelligent eye patch and a computer readable storage medium.

In order to achieve the above object, a first aspect of the present invention provides a sleep monitoring processing method based on a smart eyewear, the method comprising:

collecting electroencephalogram signals of a sleeping user through an electrode plate arranged on an intelligent eyeshade;

based on the electroencephalogram signals, performing band-pass filtering to extract preset electroencephalogram waveforms;

analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters;

and sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade.

Optionally, the step of collecting the electroencephalogram signals of the sleeping user through the electrode slice arranged on the intelligent eyeshade comprises the following steps:

the passband range of the electroencephalogram signal is preset.

Optionally, the step of collecting the electroencephalogram signals of the sleeping user through the electrode plates arranged on the intelligent eyeshade comprises the following steps:

when the intelligent eye patch is detected to be worn on the eyes of the user and waits for a preset time, the electrode plates on the intelligent eye patch are controlled to acquire the electroencephalogram signals of the sleeping user in a 4-channel analog-to-digital detection mode.

Optionally, the step of collecting the electroencephalogram signals of the sleeping user through the electrode plates arranged on the intelligent eyeshade further comprises:

collecting simulated electroencephalogram signals of a sleeping user by adopting signals with the sampling frequency of 500HZ and the sensitivity of 400 plus one 800uV/cm through electrode plates arranged on an intelligent eyeshade;

and converting the acquired analog brain electrical signals into digital brain electrical signals.

Optionally, the step of performing band-pass filtering to extract a preset brain waveform based on the brain electrical signal includes:

removing baseline drift and power frequency interference from the acquired digital electroencephalogram signals;

and performing band-pass filtering on the processed digital electroencephalogram signals to extract a preset electroencephalogram waveform.

Optionally, the step of performing band-pass filtering to extract a preset brain waveform based on the brain electrical signal further includes:

enabling the electroencephalogram signal to pass through a preset first pass band of 0.5-4HZ, and performing Fourier transform and inverse Fourier transform on the electroencephalogram signal to obtain a delta electroencephalogram waveform; wherein the delta brain waveform is a deep sleep brain waveform;

the electroencephalogram signal is subjected to Fourier transform and inverse Fourier transform through a preset second passband 4-8HZ to obtain a theta electroencephalogram waveform; wherein the theta brain waveform is a brain waveform in light sleep;

enabling the electroencephalogram signal to pass through a preset third passband 8-13HZ, and performing Fourier transform and inverse Fourier transform on the electroencephalogram signal to obtain an alpha electroencephalogram waveform; wherein the alpha brain waveform is a half-sleep half-wake brain waveform;

the electroencephalogram signal passes through a preset fourth passband 13-31HZ, and Fourier transform and inverse Fourier transform are carried out on the electroencephalogram signal to obtain a beta electroencephalogram waveform; the beta brain waveform is a brain waveform appearing while awake;

and performing the Fourier transform processing on the electroencephalogram signals to respectively obtain a delta brain waveform, a theta brain waveform, an alpha brain waveform and a beta brain waveform.

Optionally, the analyzing and determining the extracted preset brain waveform to obtain the sleep quality parameter includes:

analyzing the obtained delta brain waveform, theta brain waveform, alpha brain waveform and beta brain waveform;

whether the sleep is asleep or not is analyzed by the energy mean of the alpha brain waveform Ua/beta brain waveform Ub, and the sleep depth is distinguished by the energy mean of the alpha brain waveform Ua/delta brain waveform Ud, resulting in a sleep quality parameter.

The invention provides a sleep monitoring processing device based on an intelligent eyeshade, wherein the device comprises:

the acquisition module is used for acquiring electroencephalogram signals of the sleeping user through electrode plates arranged on the intelligent eyeshade;

the band-pass filtering processing module is used for carrying out band-pass filtering on the basis of the electroencephalogram signals to extract preset electroencephalogram waveforms;

the analysis and judgment module is used for analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters;

and the sending module is used for sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade.

A third aspect of the present invention provides an intelligent eyewear, comprising: the intelligent eyeshade comprises an intelligent eyeshade body, a memory and a processor which are arranged in the intelligent eyeshade body, an electrode plate arranged on the intelligent eyeshade body, and a sleep monitoring processing program which is stored on the memory and can run on the processor and is based on the intelligent eyeshade, wherein when the sleep monitoring processing program based on the intelligent eyeshade is executed by the processor, any step of the sleep monitoring processing method based on the intelligent eyeshade is realized, and the electrode plate is used for collecting electroencephalogram signals of a sleep user

The intelligent eye shield comprises a memory, a processor and a sleep monitoring processing program based on the intelligent eye shield, wherein the sleep monitoring processing program based on the intelligent eye shield is stored on the memory and can run on the processor, and when being executed by the processor, the sleep monitoring processing program based on the intelligent eye shield realizes any step of the sleep monitoring processing method based on the intelligent eye shield.

A fourth aspect of the present invention provides a storage medium, wherein the storage medium stores a sleep monitoring processing program based on a smart mask, and the sleep monitoring processing program based on the smart mask is executed by a processor to implement any one of the steps of the sleep monitoring processing method based on the smart mask.

Therefore, the scheme of the invention is realized based on electroencephalogram signal detection, sleep quality judgment and BLE transmission technology. The user wears the intelligent eye patch in the sleeping process, the electroencephalogram signals are detected in real time, the electroencephalogram signals collected by the electrodes are processed, analyzed and identified to obtain sleeping quality parameters, and then the user is informed of sleeping quality through BLE communication. The purposes that the user can know the sleep information at the client and can adjust the life rule in time are achieved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a schematic flowchart of a sleep monitoring processing method based on an intelligent eyeshade according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart illustrating the implementation of step S100 in FIG. 1;

FIG. 3 is a schematic flow chart illustrating the implementation of step S200 in FIG. 1;

FIG. 4 is a schematic flow chart illustrating the implementation of step S300 in FIG. 1;

fig. 5 is a schematic specific flowchart of a sleep monitoring process performed by an intelligent eyeshade according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a sleep monitoring processing device based on an intelligent eyeshade according to an embodiment of the present invention;

fig. 7 is a schematic block diagram of the internal structure of an intelligent eyeshade according to an embodiment of the present invention.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

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

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

The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to the drawings of the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.

With the development of science and technology, people pay more and more attention to body health and high-quality work and rest, and health data of a body can be detected in real time by wearing the intelligent bracelet in the working, life and exercise processes in the daytime, but the more important sleeping time period is less concerned by people, the user usually uses a method for improving the sleeping quality to adjust the work and rest level by taking melatonin, wear an eye cover to reduce the influence of ambient light, and wear an earplug to reduce the influence of the sleeping quality caused by ambient sound.

Similarly, the user sleeps, and some people feel that much more sleeps and feel less sleepy, because the user only blindly follows up and improves the quality of the sleep environment without actually observing the change of the sleep quality of the user, that is, no scheme capable of monitoring the quality of the sleep of the user while meeting the requirement of the environment of improving the sleep quality of the user exists in the prior art.

In order to solve the problems in the prior art, the scheme of the invention is realized based on electroencephalogram signal detection, sleep quality judgment and BLE transmission technology. The user wears the intelligent eye patch in the sleeping process, the electroencephalogram signals are detected in real time, the electroencephalogram signals collected by the electrodes are processed, analyzed and identified to obtain sleeping quality parameters, and then the user is informed of sleeping quality through BLE communication. The purposes that the user can know the sleep information at the client and can adjust the life rule in time are achieved.

Exemplary method

As shown in fig. 1, an embodiment of the present invention provides a sleep monitoring processing method based on an intelligent eyeshade, and specifically, the method includes the following steps:

s100, acquiring electroencephalogram signals of a sleeping user through electrode plates arranged on an intelligent eyeshade;

in the embodiment, the intelligent eyeshade collects electroencephalogram signals sent by a user during sleep through electrode plates arranged on the intelligent eyeshade. The brain electrical signal is biological electromagnetic wave generated according to human brain thinking. The number, shape and position distribution of the electrode plates can be designed at will, and the frequency range of the electroencephalogram signals mainly collected by the electrode plates is within the range of 0.5-31 Hz. The electrode plates record electroencephalogram signals which are related to sleep quality and are sent by the user at every moment of sleeping in real time or at intervals, and the intelligent eyeshade is further beneficial to analyzing specific sleep data of the user and analyzing the sleep quality of the user.

S200, performing band-pass filtering to extract a preset brain waveform based on the brain electrical signal;

in this embodiment, based on the electroencephalogram signals collected by the intelligent eye mask, a preset electroencephalogram waveform is obtained through the electroencephalogram signal processing. The brain waveform is a waveform diagram obtained by mathematically transforming brain electrical signals. The signal processing comprises processing methods such as amplification, filtering, signal transformation and the like, and the electroencephalogram signals after filtering are analyzed, extracted and transformed to obtain multiple preset electroencephalogram waveforms. For example, the electroencephalogram signals appearing in the sleep of the user throughout the night comprise electroencephalogram signals with a plurality of frequency ranges including 0.5-4Hz, 4-8Hz, 8-13Hz and 13-31Hz, and the intelligent eye mask amplifies, filters, transforms and the like the whole electroencephalogram signal data and then extracts electroencephalogram waveforms corresponding to the frequencies of 0.5-4Hz, 4-8Hz, 8-13Hz and 13-31 Hz. The electroencephalogram signals with multiple frequencies and the brain waveforms can reflect multiple sleep states of the user during sleep, for example, the electroencephalogram signals with various frequencies and the brain waveforms are respectively characteristic waveforms or frequencies of sleep stages such as light sleep, deep sleep, rapid eye movement and the like, so that the intelligent eyeshade can accurately analyze the sleep stages of the user at every moment through the brain waveforms obtained through the electroencephalogram signals. The sleep quality of the intelligent eyeshade for the user is effectively judged in a mode of processing and extracting the electroencephalogram signals into the preset electroencephalogram waveforms, and the electroencephalogram information obtained through the electrode plates is more visual.

Step S300, analyzing and judging the extracted preset brain wave to obtain sleep quality parameters;

in this embodiment, the intelligent eyeshade analyzes and judges the extracted multiple preset brain waveforms to obtain the sleep quality of the user during sleep. In the analyzing and judging process, for example, the sleep state of the user at each time in the sleep is obtained according to brain waveform analysis, and further the sleep quality and other sleep characteristics of the user, such as the time for the user to enter light sleep, the time for the user to enter deep sleep, the time for maintaining a rapid eye movement period, the stability of the user deep sleep, and the like, are obtained. The method for obtaining the sleep quality of the user by intelligently analyzing the brain waveforms accurately and visually feeds the sleep quality and the sleep condition of the user back to the user, and improves the use experience of the user and the technological sense of the intelligent eyeshade.

And S400, sending the sleep quality parameters to a user mobile terminal through a BLE module of the intelligent eyeshade for output and display.

In this embodiment, the intelligent eyeshade wirelessly transmits the sleep quality parameters obtained by analysis to the mobile terminal bound by the user through the BLE module, i.e. the bluetooth module, and performs output display. The wireless transmission mode is not limited to the Bluetooth module, and data transmission can be performed through other short-distance wireless transmission modes such as WIFI and ZigBee. Furthermore, after the mobile terminal of the user acquires the corresponding sleep quality data, an improvement scheme can be provided for the user pertinently through the internet, so that a more comprehensive sleep quality monitoring and sleep quality improvement scheme can be provided for the user.

As can be seen from the above, in the sleep monitoring processing method based on the intelligent eyeshade provided by the embodiment of the present invention, the electrode slice arranged on the intelligent eyeshade is used for collecting the electroencephalogram of the sleeping user; based on the electroencephalogram signals, performing band-pass filtering to extract preset electroencephalogram waveforms; analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters; and sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade. Compared with the prior art, the intelligent eye patch provided by the scheme can be used for detecting the sleep quality of the user while providing a good sleep environment for the user. The sleep quality parameters are obtained by real-time or interval detection of the electroencephalogram signals, processing, analysis and identification of the electroencephalogram signals collected by the electrodes, and then the sleep quality parameters are transmitted to the mobile terminal bound by the user through a wireless transmission technology. The purposes that the user can know the sleep information at the client and can adjust the life rule in time are achieved.

When the intelligent eyeshade is other equipment, the specific scheme in the embodiment can be referred.

In an application scene, the intelligent eyeshade collects electroencephalogram signals of a user during sleeping through electrode plates arranged on the eyeshade.

Specifically, as shown in fig. 2, the step S100 includes:

and S101, when the intelligent eye patch is detected to be worn on the eyes of the user and waits for a preset time, controlling an electrode plate on the intelligent eye patch to acquire electroencephalograms of the sleeping user in a 4-channel analog-to-digital detection mode.

Wherein, include before the step of gathering sleep user's EEG signal through the electrode slice of setting on intelligent eye-shade:

the passband range of the electroencephalogram signal is preset.

For example, when a user sleeps at ten nights, the user wears the intelligent eyeshade on the eyes at ten nights, and at the moment, the intelligent eyeshade judges that the user is in a wearing state currently through a pressure sensor or a human body infrared detection sensor or the like in a mode of detecting pressure or detecting human body approaching. When the intelligent eyeshade is judged to be in a wearing state, the electroencephalogram signals of the sleeping user are controlled to be acquired after a preset time, wherein the preset time is a preparation time set by an intelligent eyeshade manufacturer or set by a user for confirming that the user is in a sleeping state currently, and if the user does not take off the intelligent eyeshade when the preset time is up, the intelligent eyeshade is continuously in a standby state or a sleeping state. When the intelligent eyeshade passes through preset time, the electrode plates distributed on the periphery of the forehead are controlled to detect the electroencephalogram signals of the sleeping user in an analog-digital detection mode of 4 channels, and the analog-digital detection mode of 4 channels is an analog-digital conversion mode which supports the simultaneous conversion of four analog quantities into digital quantities. The acquired electroencephalogram signals are correspondingly preset to be divided into 4 passband ranges including a delta passband of 0.5-4Hz frequency band, a theta passband of 4-8Hz frequency band, an alpha passband of 8-13Hz frequency band and a beta passband of 13-31Hz frequency band, the four passbands respectively correspond to one analog-to-digital conversion channel, and when the intelligent eyeshade receives electroencephalograms containing the four passbands, the electroencephalogram analog signals of all frequencies are respectively input into the channels corresponding to the analog-to-digital converters to obtain electroencephalogram digital signals, namely the electroencephalogram signals in the embodiment. The system comprises a power supply, a power supply and the like, wherein the power supply, the power supply and the like are sequentially arranged. In order to further improve the EEG signal acquisition precision of the sleeping user, the intelligent eyeshade is set to acquire EEG signals through the electrode plate, wherein the sampling frequency is 500Hz, and the sensitivity is 400 + 800 uV/cm. The electroencephalogram signals with different frequency passbands generated in the sleeping process of the user are subjected to multi-path processing through the intelligent eyeshade, so that the acquired electroencephalogram signals are more accurate, the subsequent processing is facilitated, and more accurate sleep quality analysis of the user is obtained.

In an application scenario, the intelligent eyeshade performs band-pass filtering on the acquired electroencephalogram signals of the user during sleep, and extracts a preset electroencephalogram waveform.

Specifically, as shown in fig. 3, the step S200 includes:

step S201, removing baseline drift and power frequency interference from the acquired digital electroencephalogram signals;

and S202, performing band-pass filtering on the processed digital electroencephalogram signals to extract a preset electroencephalogram waveform.

For example, the intelligent eyeshade performs baseline drift removal and power frequency interference removal processing on the acquired electroencephalogram digital signals, wherein the baseline drift removal and power frequency interference removal processing is a processing method applied to the field of electrocardio to remove interference signals, and more accurate electroencephalograms of sleeping users can be further acquired through the processing method. Furthermore, the digital electroencephalogram signals of the sleeping users after the interference signals are removed are subjected to band-pass filtering, and the band-pass filtering is a signal processing mode of only reserving a certain specific frequency signal and filtering other signals except the specific frequency signal.

Further, the electroencephalogram signal passes through a preset first passband 0.5-4HZ, and Fourier transform and inverse Fourier transform are carried out on the electroencephalogram signal to obtain a delta electroencephalogram waveform;

the electroencephalogram signal is subjected to Fourier transform and inverse Fourier transform through a preset second passband 4-8HZ to obtain a theta electroencephalogram waveform;

enabling the electroencephalogram signal to pass through a preset third passband 8-13HZ, and performing Fourier transform and inverse Fourier transform on the electroencephalogram signal to obtain an alpha electroencephalogram waveform;

the electroencephalogram signal passes through a preset fourth passband 13-31HZ, and Fourier transform and inverse Fourier transform are carried out on the electroencephalogram signal to obtain a beta electroencephalogram waveform;

wherein the delta brain waveform is a brain waveform that mainly appears in deep sleep, the theta brain waveform is a brain waveform that mainly appears in shallow sleep, the alpha brain waveform is a brain waveform that mainly appears in half sleep and half wake, and the beta brain waveform is a brain waveform that mainly appears in waking;

and performing the Fourier transform processing on the electroencephalogram signals to respectively obtain a delta brain waveform, a theta brain waveform, an alpha brain waveform and a beta brain waveform. The four characteristic brain waveforms for representing the sleep state of the user are respectively obtained by the method, so that the analysis of the sleep instruction of the user is further facilitated.

In an application scenario, the intelligent eyeshade analyzes and judges the extracted preset brain waveform to obtain sleep quality parameters representing the sleep quality of the user.

Specifically, as shown in fig. 4, the step S300 includes:

step S301, analyzing and processing the obtained delta brain waveform, the theta brain waveform, the alpha brain waveform and the beta brain waveform;

step S302, whether or not the sleep is asleep is analyzed by the energy mean of the alpha brain waveform Ua/beta brain waveform Ub, and the sleep depth is distinguished by the energy mean of the alpha brain waveform Ua/delta brain waveform Ud, resulting in sleep quality parameters.

For example, the intelligent eyeshade control analyzes and processes the acquired four characteristic brain waveforms, including analyzing whether the user is asleep through the energy mean of the alpha brain waveform Ua/beta brain waveform Ub; the sleep depth is distinguished by the energy mean of the alpha brain waveform Ua/delta brain waveform Ud. Furthermore, the sleep quality parameters of the total sleep time, the short sleep time ratio, the deep sleep time ratio, the waking times and the like of the user are measured and calculated according to the energy mean value, the main occurrence time and the occurrence time ratio of the delta brain waveform, the theta brain waveform, the alpha brain waveform and the beta brain waveform. The four characteristic brain waveforms are analyzed to obtain a series of sleep quality parameters representing the sleep health degree of the user, so that the sleep problems existing in the sleep process of the user can be analyzed and corrected, better sleep experience is provided for the user, and the user stickiness is improved.

In an application scenario, the intelligent eyeshade sends the sleep quality parameters to a mobile terminal bound by a user through a BLE module and outputs and displays the sleep quality parameters.

For example, a user binds a mobile terminal device of the user with the smart eyeshade in advance, where the mobile terminal device may be a mobile phone or a tablet computer, and may be bound in a software APP or a wechat applet manner. After the intelligent eyeshade analyzes and acquires and analyzes the sleep quality parameters, the sleep quality parameters are sent to the mobile phone or the tablet device corresponding to the user through the BLE module (Bluetooth module). The user can check the sleep quality during sleeping according to the APP or the WeChat applet on the corresponding mobile phone or the tablet device, and check the method for improving the sleep quality in a targeted manner through the history recording function and the sleep correction function. The sleep eye mask has the new functions by the method: the method comprises the steps of collecting and obtaining brain wave information of a user, analyzing and obtaining sleep quality parameters of the user, and further transmitting the sleep quality parameters to a mobile terminal of the user to help the user know the sleep condition of the user and improve the sleep quality.

In the embodiment of the present invention, a sleep monitoring processing method based on an intelligent eyeshade is further specifically described based on an application scenario, and fig. 5 is a specific flow diagram illustrating a sleep monitoring processing method based on an intelligent eyeshade, which is provided by the embodiment of the present invention, and includes the steps of:

s10, start, go to step S11;

s11, the intelligent eyeshade collects user electroencephalogram signals through electrode plates and enters the step S12;

s12, the intelligent eyeshade carries out filtering processing on the electroencephalogram signals and then the step S13 is carried out;

s13, setting a passband range corresponding to the four-stroke electroencephalogram waveform to be obtained, and entering the step S14;

s14, inputting the electroencephalogram signals into each channel for filtering, performing Fourier transform and inverse Fourier transform, and entering the step S15;

s15, obtaining four-high electroencephalogram waveforms including alpha, beta, theta and delta through the steps, and entering the step S16;

s16, analyzing and processing the brain waveforms, including whether or not it is asleep by energy mean analysis of the alpha brain waveform Ua/beta brain waveform Ub, and distinguishing a sleep depth by energy mean of the alpha brain waveform Ua/delta brain waveform Ud, proceeding to step S17;

s17, obtaining sleep quality information of the user by analyzing and processing the electroencephalogram, and going to step S18;

s18, the intelligent eyeshade sends the neglected sleep quality information to a mobile phone of a user through a wireless technology, and the step S20 is carried out;

and S20, ending.

In the embodiment of the invention, after the user wears the intelligent eyeshade, the eyeshade automatically collects the electroencephalogram information of the user through the electrode plate and filters the acquired electroencephalogram information. Furthermore, the method comprises the steps of correspondingly dividing a passband range according to four-midbrain electrical waveforms commonly used for judging the sleep state and the brain activity state of a human body, inputting the brain electrical signals into each passband after the division is finished, and performing Fourier transform and inverse Fourier transform to obtain four brain waveforms comprising alpha waves, beta waves, theta waves and delta waves, wherein the four brain waves mainly appear in half-sleep, waking, light sleep and deep sleep respectively, the sleep quality and the sleep condition of a user can be obtained through analysis according to the appearance and occupied proportion of each wave in each sleep period of the user, and the sleep depth is specifically determined through energy mean analysis of the alpha brain waveform Ua/beta brain waveform Ub to determine whether the user is asleep or not, and through energy mean of the alpha brain waveform Ua/delta brain waveform Ud. And finally, the intelligent eyeshade sends the sleep quality information of the user to a mobile phone bound by the user through a wireless technology.

Exemplary device

As shown in fig. 6, corresponding to the sleep monitoring processing method based on the intelligent eyeshade, an embodiment of the present invention further provides a sleep monitoring processing apparatus based on the intelligent eyeshade, where the sleep monitoring processing apparatus based on the intelligent eyeshade includes:

the acquisition module 610 is used for acquiring electroencephalograms of the sleeping user through electrode plates arranged on the intelligent eyeshade;

in the embodiment, the intelligent eyeshade collects electroencephalogram signals sent by a user during sleep through electrode plates arranged on the intelligent eyeshade. The number, shape and position distribution of the electrode plates can be designed at will, and the frequency range of the electroencephalogram signals mainly collected by the electrode plates is within the range of 0.5-31 Hz. The electrode plates record electroencephalogram signals which are related to sleep quality and are sent by the user at every moment of sleeping in real time or at intervals, and the intelligent eyeshade is further beneficial to analyzing specific sleep data of the user and analyzing the sleep quality of the user.

A band-pass filtering processing module 620, configured to perform band-pass filtering based on the electroencephalogram signal to extract a preset electroencephalogram waveform;

in this embodiment, based on the electroencephalogram signals collected by the intelligent eye mask, a preset electroencephalogram waveform is obtained through the electroencephalogram signal processing. The signal processing comprises processing methods such as amplification, filtering, signal transformation and the like, and the electroencephalogram signals after filtering are analyzed, extracted and transformed to obtain multiple preset electroencephalogram waveforms. For example, the electroencephalogram signals appearing in the sleep of the user throughout the night comprise electroencephalogram signals with a plurality of frequency ranges including 0.5-4Hz, 4-8Hz, 8-13Hz and 13-31Hz, and the intelligent eye mask amplifies, filters, transforms and the like the whole electroencephalogram signal data and then extracts electroencephalogram waveforms corresponding to the frequencies of 0.5-4Hz, 4-8Hz, 8-13Hz and 13-31 Hz. The electroencephalogram signals with multiple frequencies and the brain waveforms can reflect multiple sleep states of the user during sleep, for example, the electroencephalogram signals with various frequencies and the brain waveforms are respectively characteristic waveforms or frequencies of sleep stages such as light sleep, deep sleep, rapid eye movement and the like, so that the intelligent eyeshade can accurately analyze the sleep stages of the user at every moment through the brain waveforms obtained through the electroencephalogram signals. The sleep quality of the intelligent eyeshade for the user is effectively judged in a mode of processing and extracting the electroencephalogram signals into the preset electroencephalogram waveforms, and the electroencephalogram information obtained through the electrode plates is more visual.

An analyzing and judging module 630, configured to analyze and judge the extracted preset brain waveform to obtain a sleep quality parameter;

in this embodiment, the intelligent eyeshade analyzes and judges the extracted multiple preset brain waveforms to obtain the sleep quality of the user during sleep. In the analyzing and judging process, for example, the sleep state of the user at each time in the sleep is obtained according to brain waveform analysis, and further the sleep quality and other sleep characteristics of the user, such as the time for the user to enter light sleep, the time for the user to enter deep sleep, the time for maintaining a rapid eye movement period, the stability of the user deep sleep, and the like, are obtained. The method for obtaining the sleep quality of the user by intelligently analyzing the brain waveforms accurately and visually feeds the sleep quality and the sleep condition of the user back to the user, and improves the use experience of the user and the technological sense of the intelligent eyeshade.

And the sending module 640 is configured to send the sleep quality parameter to the user mobile terminal through a BLE module of the smart eye patch for output and display.

In this embodiment, the intelligent eyeshade wirelessly transmits the sleep quality parameters obtained by analysis to the mobile terminal bound by the user through the BLE module, i.e. the bluetooth module, and performs output display. The wireless transmission mode is not limited to the Bluetooth module, and data transmission can be performed through other short-distance wireless transmission modes such as WIFI and ZigBee. Furthermore, after the mobile terminal of the user acquires the corresponding sleep quality data, an improvement scheme can be provided for the user pertinently through the internet, so that a more comprehensive sleep quality monitoring and sleep quality improvement scheme can be provided for the user.

As can be seen from the above, in the sleep monitoring processing method based on the intelligent eyeshade provided by the embodiment of the present invention, through the collecting module 610, the electroencephalogram signals of the sleeping user are collected through the electrode patch arranged on the intelligent eyeshade; performing band-pass filtering to extract a preset brain waveform based on the brain electrical signal through the band-pass filtering processing module 620; analyzing and judging the extracted preset brain waveform through the analyzing and judging module 630 to obtain sleep quality parameters; through the sending module 640, the sleep quality parameters are sent to a user mobile terminal through a BLE module of the intelligent eyeshade for output and display. Compared with the prior art, the intelligent eye patch provided by the scheme can be used for detecting the sleep quality of the user while providing a good sleep environment for the user. The sleep quality parameters are obtained by real-time or interval detection of the electroencephalogram signals, processing, analysis and identification of the electroencephalogram signals collected by the electrodes, and then the sleep quality parameters are transmitted to the mobile terminal bound by the user through a wireless transmission technology. The purposes that the user can know the sleep information at the client and can adjust the life rule in time are achieved.

Specifically, in this embodiment, the specific functions of each module of the sleep monitoring processing apparatus based on the intelligent eyeshade may refer to the corresponding descriptions in the sleep monitoring processing method based on the intelligent eyeshade, and are not described herein again.

Based on the above embodiments, the present invention further provides an intelligent eyeshade, whose functional block diagram can be shown in fig. 7. The intelligent eyeshade comprises a processor, a memory and a network interface which are connected through a system bus. Wherein the processor of the intelligent eyewear is configured to provide computing 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 and a sleep monitoring processing program based on the intelligent eyeshade. The internal memory provides an environment for the operation of an operating system and a sleep monitoring processing program based on the intelligent eyeshade in the nonvolatile storage medium. The network interface of the intelligent eyeshade is used for being connected and communicated with an external eyeshade through a network. When being executed by a processor, the sleep monitoring processing program based on the intelligent eyeshade realizes the steps of any one of the sleep monitoring processing methods based on the intelligent eyeshade.

It will be understood by those skilled in the art that the block diagram of fig. 7 is merely a block diagram of a portion of the structure associated with the present invention and is not intended to limit the intelligent eyewear to which the present invention may be applied, and that a particular intelligent eyewear may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a smart eyewear is provided, the smart eyewear comprising a memory, a processor, and a smart eyewear-based sleep monitoring handler stored on the memory and executable on the processor, the smart eyewear-based sleep monitoring handler executing the following instructions when executed by the processor:

collecting electroencephalogram signals of a sleeping user through an electrode plate arranged on an intelligent eyeshade;

based on the electroencephalogram signals, performing band-pass filtering to extract preset electroencephalogram waveforms;

analyzing and judging the extracted preset brain waveform to obtain sleep quality parameters;

and sending the sleep quality parameters to a user mobile terminal for output and display through a BLE module of the intelligent eyeshade.

The embodiment of the invention also provides a computer-readable storage medium, wherein the computer-readable storage medium is stored with a sleep monitoring processing program based on the intelligent eyeshade, and the sleep monitoring processing program based on the intelligent eyeshade realizes the steps of any sleep monitoring processing method based on the intelligent eyeshade provided by the embodiment of the invention when being executed by a processor.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned functions may be distributed as different functional units and modules according to needs, that is, the internal structure of the apparatus may be divided into different functional units or modules to implement all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Those of ordinary skill in the art would appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the embodiments provided herein, it should be understood that the disclosed apparatus/ocular shield device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/ocular shield apparatus are merely illustrative, and for example, the division of the above-described modules or units is merely a logical division, and the actual implementation may be achieved by another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not implemented.

The integrated modules/units described above, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium and can implement the steps of the embodiments of the method when the computer program is executed by a processor. The computer program includes computer program code, and the computer program code may be in a source code form, an object code form, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying the above-mentioned computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunication signal, software distribution medium, etc. It should be noted that the contents contained in the computer-readable storage medium can be increased or decreased as required by legislation and patent practice in the jurisdiction.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein.