Sleep aiding equipment control method and device, equipment and storage medium

Abstract

The invention relates to the technical field of intelligent medical equipment, and discloses a control method, device and equipment of sleep aiding equipment and a storage medium, the sleep aiding equipment comprises an electroencephalogram collection unit and an execution unit, and the control method of the sleep aiding equipment comprises the steps that electroencephalogram signals collected by the electroencephalogram collection unit are obtained; analyzing brain waves of different wave bands in the electroencephalogram signals, wherein the different wave bands comprise at least two of a delta wave band, a theta wave band, an alpha wave band, a beta wave band and a gamma wave band; adjusting the parameters of the execution unit based on the analysis results of the brain waves of different wave bands; and controlling the execution unit to work according to the adjusted parameters. The control method of the sleep-aiding equipment provided by the invention has personalized adjustment capability, can accurately adapt to individual differences, and improves the sleep-aiding effect and sleep-aiding efficiency.

Description

Technical Field

[0001] This invention relates to the field of intelligent medical device technology, specifically to a control method, device, equipment, and storage medium for a sleep aid device. Background Technology

[0002] Insomnia, a prevalent sleep disorder affecting approximately 20% of the global population, has long relied on drug treatment (such as benzodiazepines) for its treatment. (Classification) and cognitive behavioral therapy. However, problems such as drug dependence and poor adherence to cognitive therapy are driving the exploration of new non-invasive therapies. 40Hz light stimulation technology (a technology that affects brain activity by flashing light at a specific frequency. This technology is mainly studied for the treatment of neurodegenerative diseases such as Alzheimer's disease. Studies have shown that when the eyes are exposed to light that flashes 40 times per second, it can promote the generation of gamma waves in the brain. Gamma waves are high-frequency brain waves (usually between 30-100Hz) and are thought to be related to functions such as attention, memory, and consciousness) has attracted much attention due to its neuromodulatory potential in the treatment of Alzheimer's disease. The latest research has revealed its unique mechanism of improving sleep through the corticosteroid signaling pathway. However, optical sleep aids (such as sleep-aid eye masks) in related technologies usually use fixed sound and light stimulation parameters (such as white light with a single flashing frequency combined with white noise), lacking the ability to personalize and adapt to individual differences among users (such as anxiety levels, circadian rhythms, etc.). Summary of the Invention

[0003] In view of this, the present invention provides a control method, device, equipment and storage medium for a sleep aid device, in order to solve the problem that sleep aid devices in the related art lack personalized adjustment capabilities and cannot adapt to the individual differences of different users.

[0004] In a first aspect, the present invention provides a control method for a sleep aid device, the sleep aid device comprising an electroencephalogram (EEG) acquisition unit and an execution unit, the method comprising:

[0005] The EEG signal of the user is acquired by the EEG acquisition unit;

[0006] The brainwaves of different bands in the brainwave signal are analyzed, including the delta band, theta band, alpha band, beta band and gamma wave;

[0007] Based on the analysis results of the different bands of EEG, the parameters of the execution unit are adjusted;

[0008] The execution unit is controlled to work according to the adjusted parameters.

[0009] In one optional implementation, the analysis of different bands of brainwaves in the electroencephalogram (EEG) signal includes:

[0010] The analysis is based on at least one of the energy density, waveform, and energy intensity of the different frequency bands of EEG.

[0011] In one alternative implementation, the execution unit includes an acoustic subunit and / or an optical subunit;

[0012] The acoustic subunit is used to emit a sine wave sound and / or white noise at a frequency of 40Hz, and the volume of the acoustic subunit is adjustable from 30 to 70 decibels.

[0013] The optical subunit includes multiple red LEDs and multiple green LEDs, and the frequency range of the pulse modulation of the red LEDs and the green LEDs is 10-50Hz.

[0014] In one optional implementation, the analysis results of the different wavebands of brainwaves are the energy density ratios of the different wavebands of brainwaves; adjusting the parameters of the execution unit based on the analysis results of the different wavebands of brainwaves includes:

[0015] If the ratio is greater than a first preset threshold, the parameters of the execution unit are adjusted according to a first control strategy; wherein, the first control strategy is: green light dominates, the frequency of LED lamp pulse modulation is a first frequency, the first frequency is greater than a first frequency threshold, and the volume of the acoustic subunit is greater than a first volume threshold.

[0016] If the ratio is greater than or equal to the second preset threshold and less than or equal to the first preset threshold, the parameters of the execution unit are adjusted according to the second control strategy; wherein, the second control strategy is: to control the green LED and the red LED to work, the pulse modulation frequency of the green LED and the red LED is the first frequency and the second frequency, the second frequency is less than the second frequency threshold, and the volume of the acoustic subunit is greater than the second volume threshold and less than or equal to the first volume threshold;

[0017] If the ratio is less than the second preset threshold, the parameters of the execution unit are adjusted according to the third control strategy; wherein the third control strategy is: red light dominates, the frequency of LED lamp pulse modulation is the second frequency, and the volume of the acoustic subunit is less than or equal to the second volume threshold.

[0018] In one optional implementation, the analysis results of the different bands of brainwaves are the proportion of different bands of brainwaves calculated based on at least one of the energy density, waveform diagram, and energy intensity.

[0019] The adjustment of the parameters of the execution unit based on the analysis results of the different EEG bands includes:

[0020] If the proportions of gamma waves and beta waves are both greater than those of alpha waves, then it is determined that the user is currently in the first sleep aid stage, and the parameters of the execution unit are adjusted according to the fourth control strategy; wherein, the fourth control strategy is: controlling the green LED light to work, the frequency of the green LED light pulse modulation is a third frequency, and the third frequency is greater than the first frequency threshold;

[0021] If the proportion of alpha waves increases compared to the first sleep aid stage, and the energy intensity of alpha waves is greater than a preset energy intensity threshold, then it is determined that the user is currently in the second sleep aid stage, and the parameters of the execution unit are adjusted according to the fifth control strategy; wherein, the fifth control strategy is: sequentially turning off the green LED light and controlling the red LED light to work, and the frequency of the red LED light pulse modulation is the third frequency;

[0022] If the proportion of alpha waves decreases compared to the second sleep-aid stage, while the proportions of delta waves and theta waves increase compared to the second sleep-aid stage, then the user is determined to be in the third sleep-aid stage, and the parameters of the execution unit are adjusted according to the sixth control strategy; wherein, the sixth control strategy is to reduce the frequency of the red LED pulse modulation and reduce the volume of the acoustic subunit.

[0023] In one optional implementation, controlling the execution unit to operate according to the adjusted parameters includes:

[0024] After the EEG acquisition unit stops acquiring the EEG signal, the execution unit is controlled to work for a preset duration according to the adjusted parameters.

[0025] After controlling the execution unit to work for a preset duration according to the adjusted parameters, the method further includes: controlling the EEG acquisition unit to acquire the EEG signal again.

[0026] In one optional implementation, the parameter adjustment period of the execution unit is the target duration; the duration of the EEG signal acquired in each adjustment period is less than or equal to the target duration.

[0027] In one optional implementation, the analysis results of the different bands of brain waves are the energy density ratio of the different bands of brain waves.

[0028] After analyzing the different bands of brainwaves in the electroencephalogram (EEG) signal, the method further includes:

[0029] If the ratio is less than a third preset threshold, then determine whether the ratio obtained in the previous N calculations is less than the third preset threshold.

[0030] If so, then the execution unit is shut down.

[0031] In a second aspect, the present invention provides a control device for a sleep aid device, the sleep aid device comprising an electroencephalogram (EEG) acquisition unit and an execution unit, the device comprising:

[0032] The EEG signal acquisition module is used to acquire the user's EEG signal acquired by the EEG acquisition unit;

[0033] The analysis module is used to analyze the brain waves of different bands in the brain signal, wherein the different bands include at least two of the delta band, theta band, alpha band, beta band and gamma wave;

[0034] The parameter adjustment module is used to adjust the parameters of the execution unit based on the analysis results of the different bands of EEG.

[0035] The control execution module is used to control the execution unit to work according to the adjusted parameters.

[0036] Thirdly, the present invention provides a sleep aid device, comprising: a central processing unit, an electroencephalogram (EEG) acquisition unit, and an execution unit;

[0037] The EEG acquisition unit is used to acquire EEG signals;

[0038] The central processing unit is used to execute the control method of the sleep aid device of the first aspect or any corresponding embodiment described above;

[0039] The execution unit is controlled by the central processing unit.

[0040] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the control method of the sleep aid device according to the first aspect or any corresponding embodiment thereof.

[0041] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the control method of the sleep aid device described in the first aspect or any corresponding embodiment thereof.

[0042] The control method, apparatus, device, and storage medium for sleep aid devices provided in this invention can determine the user's real-time state based on the user's EEG feedback and dynamically adjust the execution parameters of the sleep aid device. This achieves personalized, dynamic, and precise neuromodulation based on the user's real-time state, solving the problem of control failure in related technologies due to the inability of sleep aid devices to adapt to individual differences among users (such as anxiety levels and circadian rhythms). The control method for sleep aid devices provided in this invention has personalized adjustment capabilities, accurately adapting to individual differences and improving the sleep aid effect and efficiency. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0044] Figure 1 This is a flowchart illustrating the control method of a sleep aid device according to an embodiment of the present invention;

[0045] Figure 2 This is a schematic block diagram of the hardware structure of a sleep aid device according to an embodiment of the present invention.

[0046] Figure 3 This is a schematic diagram of the parameter adjustment process of a sleep aid device according to an embodiment of the present invention;

[0047] Figure 4 This is a structural block diagram of the control device for a sleep aid device according to an embodiment of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] According to an embodiment of the present invention, a control method for a sleep aid device is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of executable computer instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0050] This embodiment provides a control method for a sleep aid device, the sleep aid device including an electroencephalogram (EEG) acquisition unit and an execution unit. Figure 1 This is a flowchart of a control method for a sleep aid device according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0051] Step S101: Obtain the user's brainwave signal (i.e., electroencephalography (EEG) signal) acquired by the brainwave acquisition unit.

[0052] In this embodiment of the invention, a flexible dry electrode array (SPI / I2C) can be used as the EEG acquisition unit to acquire raw EEG signals. Compared with traditional wet electrodes, dry electrodes do not require conductive paste or gel to work, making them more suitable for long-term wear and daily use. "SPI / I2C" refers to the communication protocol used for data transmission. SPI (Serial Peripheral Interface) is a synchronous serial communication interface specification, mainly used for short-distance communication and suitable for high-speed data transmission; I2C (Inter-Integrated Circuit) is also a synchronous serial communication interface, but it is usually used for lower-speed peripheral connections, characterized by requiring fewer pins and being simpler to implement.

[0053] Specifically, the sleep aid device can be a sleep-aid eye mask. A flexible dry electrode array can be deployed in the corresponding area of ​​the temporal lobe inside the eye mask (Fp1 / Fp2 / T3 / T4 sites), with a sampling rate ≥256Hz, a resolution of 0.5μV, and a bandwidth of 0.5-45Hz (covering the δ / θ / α / β / γ bands).

[0054] The raw EEG signals acquired can be preprocessed as follows:

[0055] 1. 50Hz power frequency filtering;

[0056] 2. Wavelet denoising (db4 wavelet basis) removes electromyographic noise.

[0057] Step S102 involves analyzing the brainwaves in different bands of the EEG signal, where the different bands include at least two of the delta, theta, alpha, beta, and gamma waves. Additionally, spindle waves and K-complexes in the EEG signal can also be analyzed.

[0058] In some optional embodiments, the analysis of different bands of brain waves in the EEG signal may specifically be based on at least one of the energy density, waveform, and energy intensity of the different bands of brain waves.

[0059] Specifically, the analysis results of different bands of brain waves can be the energy density ratio of the different bands of brain waves, or the proportion of different bands of brain waves calculated based on at least one of the energy density, waveform, and energy intensity.

[0060] For example, the energy ratio of the first and second bands in the electroencephalogram (EEG) signal can be calculated, and the specific steps include:

[0061] Step S1021: Obtain the energy of the first band and the second band of the EEG signal. The first band includes the delta band, and the second band includes the beta band. The delta band has a frequency between 0.5 Hz and 4 Hz. This wave is most prominent during deep sleep (especially stage 3 of non-rapid eye movement sleep, also known as deep sleep or slow-wave sleep). The beta band has a frequency between 13 Hz and 30 Hz. Beta waves are associated with arousal states such as active thinking, problem-solving, focus, or anxiety.

[0062] Specifically, the first band is the slow band (lower frequency), and the second band is the fast band (higher frequency). The energy of the delta band can be expressed as: delta_power = band_power (eeg, 0.5-4Hz). The energy of the beta band can be expressed as: beta_power = band_power (eeg, 13-30Hz). Here, we can first extract EEG features from the EEG signal, and then extract the slow band energy and fast band energy based on the extracted EEG features.

[0063] Step S1022: Calculate the ratio of the energy of the second band to the energy of the first band. This ratio can also be called the fast-slow wave energy ratio, and the specific calculation formula can be: ratio = beta_power / (delta_power + ε), where ε is a minimum value used to avoid division by zero, for example, 1 × 10⁻⁶. -6 .

[0064] In this embodiment, the energy ratio of the β band to the δ band is calculated. In other embodiments, the energy ratios of other bands can be calculated.

[0065] Step S103: Based on the analysis results of the different bands of EEG, adjust the parameters of the execution unit.

[0066] In some optional embodiments, the execution unit includes an acoustic subunit and / or an optical subunit;

[0067] The acoustic subunit is used to emit a sine wave sound and / or white noise at a frequency of 40Hz, and the volume of the acoustic subunit is adjustable from 30 to 70 decibels.

[0068] The optical subunit includes multiple red LEDs and multiple green LEDs, with the pulse modulation frequency range of the red and green LEDs being 10-50Hz. That is, the optical subunit employs a dual LED array (630nm red + 530nm green) supporting 10-50Hz pulse modulation. Furthermore, the dynamic range of the optical subunit's light intensity is 50-5000 lux (equivalent to 5-500 lux after transmission through the eyelid).

[0069] The embodiments of the present invention can synergistically optimize multiple audio-visual stimulation parameters (including flash frequency, light color, volume, and may also include sound frequency, etc.), thereby improving the sleep aid effect and sleep aid efficiency.

[0070] Specifically, red light promotes melatonin production, while green light lowers cortisol levels; 10Hz light frequency induces slow waves (i.e., delta / theta slow waves, which can induce drowsiness), and 40Hz light frequency increases adenosine (a regulator of sleep-wake cycles); medium to high volume enhances focus. The dual-band (red and green) light synergistically stimulates the brain; for example, simultaneously emitting 10Hz red light (inducing delta / theta slow waves) and 40Hz green and red light (inducing gamma waves, thereby affecting the release and distribution of various neuroregulatory substances, including adenosine) improves sleep onset efficiency by 32% compared to single-band light.

[0071] Step S104: Control the execution unit to work according to the adjusted parameters.

[0072] The following example illustrates the steps for adjusting the parameters of the execution unit based on the analysis results of the different bands of EEG.

[0073] In some optional specific embodiments, the analysis results of the different bands of brain waves are the energy density ratio of the different bands of brain waves;

[0074] Accordingly, step S103, namely adjusting the parameters of the execution unit based on the analysis results of the different EEG bands, includes:

[0075] Step S1031: If the ratio is greater than the first preset threshold, the parameters of the execution unit are adjusted according to the first control strategy; wherein, the first control strategy is: green light dominates, the frequency of LED lamp pulse modulation is the first frequency, the first frequency is greater than the first frequency threshold, and the volume of the acoustic subunit is greater than the first volume threshold.

[0076] Specifically, the first preset threshold can be, for example, 1.5. The first frequency can be, for example, 40Hz. When the fast-slow wave energy ratio is greater than 1.5, it indicates that the user is in a state of high alertness (not relaxed). At this time, a 40Hz-dominant, green light, and high-volume control strategy should be adopted. Green light dominance means that the proportion of green light is relatively large, for example, greater than or equal to 70%. High volume can be, for example, 60 decibels (dB). In addition, the first control strategy can also include increasing the proportion of white noise, for example, increasing the proportion of white noise to 80%; and increasing the light intensity by 30%.

[0077] Step S1032: If the ratio is greater than or equal to the second preset threshold and less than or equal to the first preset threshold, then adjust the parameters of the execution unit according to the second control strategy; wherein, the second control strategy is: control the green LED and the red LED to work, the pulse modulation frequency of the green LED and the red LED is the first frequency and the second frequency, the second frequency is less than the second frequency threshold, and the volume of the acoustic subunit is greater than the second volume threshold and less than or equal to the first volume threshold.

[0078] Specifically, the second preset threshold is less than the first preset threshold. The second volume threshold is less than the first volume threshold. The first frequency threshold is greater than the second frequency threshold.

[0079] The second preset threshold can be, for example, 0.8. The second frequency can be, for example, 10Hz. When the energy ratio of fast and slow waves is between 0.8 and 1.5, it indicates that the user is in a transitional state. At this time, a strategy of alternating between 10Hz and 40Hz, yellow light (both green and red LEDs are working), and medium volume control should be adopted.

[0080] Step S1033: If the ratio is less than the second preset threshold, the parameters of the execution unit are adjusted according to the third control strategy; wherein, the third control strategy is: red light dominates, the frequency of LED lamp pulse modulation is the second frequency, and the volume of the acoustic subunit is less than or equal to the second volume threshold.

[0081] When the ratio of fast to slow wave energy is less than 0.8, it indicates that the user is in a drowsy state. At this time, a strategy of using 10Hz as the primary frequency, red light, and low volume should be adopted. Red light dominance means that the proportion of red light is relatively large, for example, greater than or equal to 80%. Low volume could be, for example, 40 decibels (dB). A third control strategy could also include increasing the proportion of 40Hz sine wave sound, for example, increasing the proportion of 40Hz sine wave sound to 90%; and reducing light intensity by 50%.

[0082] The first preset threshold, the second preset threshold, the first frequency threshold, the second frequency threshold, the first volume threshold, and the second volume threshold mentioned above can all be determined based on experimental values, empirical values, or relevant research.

[0083] In some alternative implementations, the analysis results of the different wavebands of EEG are calculated based on at least one of the energy density, waveform, and energy intensity, representing the proportion of different wavebands of EEG. Specifically, the proportion of different wavebands can be determined by considering the proportion of energy density of a certain waveband in the total energy density, the proportion of energy intensity in the total energy intensity, and the waveform.

[0084] Accordingly, adjusting the parameters of the execution unit based on the analysis results of the different EEG bands includes:

[0085] Step S103a: If the proportions of both gamma waves and beta waves are greater than those of alpha waves, then it is determined that the user is currently in the first sleep-aid stage, and the parameters of the execution unit are adjusted according to the fourth control strategy. The fourth control strategy involves controlling the green LED light to operate, wherein the frequency of the green LED light pulse modulation is a third frequency, and the third frequency is greater than a first frequency threshold, for example, the third frequency can be 40Hz. Additionally, the volume of the acoustic subunit can be greater than a first volume threshold.

[0086] In other words, if gamma and beta waves account for a larger proportion, while alpha waves account for a relatively smaller proportion, for example, if gamma and beta waves account for 30%-50% and alpha waves account for 20%-40%, it indicates that the user is currently in the first sleep-aid stage (i.e., in a waking state). The sleep-aid stimulation is dominated by green light, and the frequency of the green light can be 40Hz.

[0087] Step S103b: If the proportion of alpha waves increases compared to the first sleep-aid stage, and the energy intensity of the alpha waves is greater than a preset energy intensity threshold, then it is determined that the user is currently in the second sleep-aid stage, and the parameters of the execution unit are adjusted according to the fifth control strategy; wherein, the fifth control strategy is: sequentially turning off the green LED light and controlling the red LED light to work, and the frequency of the red LED light pulse modulation is the third frequency. Additionally, the volume of the acoustic subunit can be greater than the second volume threshold and less than or equal to the first volume threshold.

[0088] In this embodiment, if the proportion of alpha waves gradually increases and the alpha wave energy is high, it indicates that the user is currently in the second sleep-inducing stage (i.e., in a relaxed state), and then the system switches to red light. At this time, the red light frequency remains unchanged at 40 Hz, and the green light gradually disappears. If the alpha waves do not increase, the stimulation from the first sleep-inducing stage remains dominant.

[0089] In step S103c, if the proportion of alpha waves decreases compared to the second sleep aid stage, the energy intensity of alpha waves decreases compared to the second sleep aid stage, and the proportions of delta waves and theta waves increase compared to the second sleep aid stage, then it is determined that the user is currently in the third sleep aid stage, and the parameters of the execution unit are adjusted according to the sixth control strategy; wherein, the sixth control strategy is: reducing the frequency of the red LED pulse modulation, for example, reducing it to the second frequency (10Hz), and reducing the volume of the acoustic subunit.

[0090] In this embodiment, if the proportion of alpha waves gradually decreases and the energy of alpha waves gradually decreases, while the concentrations of delta and theta waves gradually increase, it indicates that the user is currently in the third sleep-inducing stage (i.e., in a state of falling asleep). In this case, the red light frequency is reduced, gradually decreasing to 10 Hz. The sound is also gradually reduced. If the energy of alpha waves does not decrease, the stimulation from the second stage remains dominant.

[0091] This invention provides another sleep-aiding strategy that has a better sleep-aiding effect than the previous one.

[0092] In some optional implementations, step S104, namely controlling the execution unit to work according to the adjusted parameters, includes:

[0093] After the EEG acquisition unit stops acquiring the EEG signal, the execution unit is controlled to work for a preset duration according to the adjusted parameters.

[0094] In addition, after controlling the execution unit to work for a preset duration according to the adjusted parameters, the method further includes: controlling the EEG acquisition unit to acquire the EEG signal again.

[0095] Specifically, the preset duration could be, for example, 100ms. The duration of each EEG signal acquisition could be, for example, 20ms. Throughout the sleep aid process, EEG signal acquisition and the emission of audio-visual signals are performed alternately, that is, the EEG acquisition unit and the execution unit work alternately.

[0096] In this embodiment of the invention, the emission window of the stimulation signal (i.e., the audio-visual signal) is staggered from the EEG acquisition interval (a 20ms acquisition gap is reserved after every 50ms stimulation). This avoids mutual interference between the audio-visual stimulation signal and the EEG acquisition process, thereby preventing distortion of the acquired EEG signal, ensuring the accuracy of the feedback signal, and significantly improving the precision and reliability of EEG-based neuromodulation. Through the effective anti-interference mechanism described above for simultaneous EEG acquisition and audio-visual stimulation, this embodiment of the invention attenuates EEG signal crosstalk by 40dB and achieves a signal-to-noise ratio (SNR) > 15dB. Therefore, the sleep aid device can achieve medical device precision in a home environment (compliant with medical device industry standard: YY 9706.262), meeting clinical-grade precision requirements.

[0097] In some optional embodiments, the parameter adjustment period of the execution unit is the target duration; the duration of the EEG signal acquired in each adjustment period is less than or equal to the target duration.

[0098] For example, the parameter adjustment cycle of the execution unit could be 5 minutes. If, as mentioned above, to avoid interference between the audio-visual stimulation signals and the EEG acquisition process, the emission window of the stimulation signal (i.e., the audio-visual signal) is staggered from the EEG acquisition interval (a 20ms acquisition gap is reserved after every 50ms stimulation), then within a 5-minute parameter adjustment cycle, the duration of the acquired EEG signal is 2 minutes, and the total duration of the audio-visual stimulation is 3 minutes. Each adjustment of the execution unit's parameters is based on calculating the energy ratio of the second band to the first band based on the EEG signal acquired within one parameter adjustment cycle (2 minutes), and then adjusting the execution unit's parameters according to this energy ratio.

[0099] In some optional embodiments, the analysis results of the different bands of brainwaves are the energy density ratios of the different bands of brainwaves; after step S102, that is, after the analysis of the different bands of brainwaves in the brainwave signal, the method further includes:

[0100] Step S105: If the ratio is less than the third preset threshold, then determine whether the ratio obtained in the previous N calculations is less than the third preset threshold.

[0101] Step S106: If yes, then control the shutdown of the execution unit.

[0102] Specifically, the third preset threshold can be less than the second preset threshold. For example, the third preset threshold can be 0.5, and it can be determined based on experimental values, empirical values, or relevant research. The value of N can be adjusted according to actual needs, for example, it can be 2. That is, if the energy ratio calculated for three consecutive times (three parameter adjustment cycles) is less than the third preset threshold, it can be determined that the user has fallen asleep, and the execution unit can be shut down at this time.

[0103] In other words, the parameters of the execution unit need to be adjusted only if the energy ratio calculated in the current parameter adjustment cycle is greater than or equal to the third preset threshold, or if the energy ratio calculated in the previous N (previous N parameter adjustment cycles) is not all less than the third preset threshold. Otherwise, the execution unit is shut down directly, that is, the sound and light stimulation is turned off.

[0104] The control method for the sleep aid device provided in this embodiment can determine the user's real-time state based on the user's EEG feedback and dynamically adjust the execution parameters of the sleep aid device. This achieves personalized, dynamic, and precise neuromodulation based on the user's real-time state, solving the problem of control failure in related technologies due to the inability of sleep aid devices to adapt to individual differences among users (such as anxiety levels and circadian rhythms). The control method for the sleep aid device provided in this embodiment has personalized adjustment capabilities, accurately adapts to individual differences, and improves the sleep aid effect and efficiency.

[0105] Please see Figure 2 , Figure 2 This is a schematic diagram of the structure of a sleep aid device provided in an optional embodiment of the present invention, as shown below. Figure 2 As shown, the sleep aid device includes: a central processing unit, an EEG acquisition unit, and an execution unit;

[0106] The EEG acquisition unit is used to acquire EEG signals;

[0107] The central processing unit is used to execute the control method of any of the sleep aid devices in the above embodiments;

[0108] The execution unit is controlled by the central processing unit.

[0109] Specifically, the central processing unit can be, for example, a microcontroller unit, i.e., an MCU. The central processing unit and the execution unit can be connected and communicate via an SPI bus.

[0110] In some optional embodiments, the execution unit includes an acoustic subunit and / or an optical subunit;

[0111] The acoustic subunit is used to emit a sine wave sound and / or white noise at a frequency of 40Hz, and the volume of the acoustic subunit is adjustable from 30 to 70 decibels.

[0112] The optical subunit includes multiple red LEDs and multiple green LEDs, with the pulse modulation frequency range of the red and green LEDs being 10-50Hz. That is, the optical subunit employs a dual LED array (630nm red + 530nm green) supporting 10-50Hz pulse modulation. Furthermore, the dynamic range of the optical subunit's light intensity is 50-5000 lux (equivalent to 5-500 lux after transmission through the eyelid).

[0113] The embodiments of the present invention can synergistically optimize multiple audio-visual stimulation parameters (including flash frequency, light color, volume, and may also include sound frequency, etc.), and realize personalized and dynamic neuromodulation based on the user's real-time state (especially EEG state), thereby improving the sleep aid effect and sleep aid efficiency.

[0114] like Figure 3 As shown below, the parameter adjustment process of the sleep aid device (specifically, a sleep aid eye mask) provided in the embodiment of the present invention will be illustrated by an example.

[0115] 1. Initialization Phase

[0116] The user wears an eye mask, and then the system self-checks the contact impedance of the EEG acquisition electrodes (if <10kΩ, it will start); the default output basic mode is: 10Hz / 40Hz mixed light, 50dB volume (3 minutes).

[0117] 2. Real-time control stage

[0118] Step 1: The EEG acquisition unit continuously acquires raw signals, which are then transmitted to the MCU after being filtered by a Finite Impulse Response (FIR) bandpass filter (0.5-45Hz). The FIR bandpass filter is used to remove unwanted noise and interference while retaining the frequency bands of interest. For EEG signals, the frequency range of interest is typically from 0.5Hz to 45Hz, which covers delta waves (0.5-4Hz), theta waves (4-8Hz), alpha waves (8-13Hz), beta waves (13-30Hz), and some gamma waves (30-100Hz).

[0119] Step 2: The MCU calculates the current fast-slow wave energy ratio (referred to as R below) within a 2-minute time window and executes the following:

[0120] If R>1.5 (high alert): Control the LED lights to switch to green light dominant mode (green light ratio ≥70%), increase the pulse frequency to 40Hz, increase the light intensity by 30%; increase the volume to 60dB, and the white noise ratio to 80%;

[0121] If 0.8≤R≤1.5 (transition): control the LED light to a yellow light mixed mode (i.e., green light and red light each account for 50%), alternating between 10Hz and 40Hz;

[0122] If R < 0.8 (drowsy): Switch to red light dominant mode (red light ratio ≥ 80%), reduce pulse frequency to 10Hz, reduce light intensity by 50%; reduce volume to 40dB, and 40Hz sine wave ratio is 90%.

[0123] Step 3: The control parameters are sent to the execution unit via the SPI bus and take effect in real time.

[0124] 3. Termination Conditions

[0125] If R < 0.5 is detected for three consecutive time windows, the system determines that the user has fallen asleep and automatically shuts down the execution unit, i.e., the audio-visual stimulation, but keeps the EEG acquisition unit working, i.e., retains EEG monitoring to prevent awakening.

[0126] In summary, the sleep aid device provided in this embodiment of the invention can be a dual-band sound and light sleep aid device.

[0127] This embodiment also provides a control device for a sleep aid device, which is used to implement the control method embodiments and preferred embodiments of the sleep aid device described above. Details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0128] This embodiment provides a control device for a sleep aid device, such as... Figure 4 As shown, the sleep aid device includes an EEG acquisition unit and an execution unit. The device includes:

[0129] The EEG signal acquisition module 401 is used to acquire the EEG signals acquired by the EEG acquisition unit.

[0130] Analysis module 402 is used to analyze different bands of brain waves in the electroencephalogram (EEG) signal, wherein the different bands include at least two of the delta band, theta band, alpha band, beta band and gamma band;

[0131] The parameter adjustment module 403 is used to adjust the parameters of the execution unit based on the analysis results of the different bands of EEG.

[0132] The control execution module 404 is used to control the execution unit to work according to the adjusted parameters.

[0133] In some optional implementations, the analysis module 402 specifically performs analysis based on at least one of the energy density, waveform, and energy intensity of the different bands of brainwaves.

[0134] In some alternative implementations, the execution unit includes an acoustic subunit and / or an optical subunit;

[0135] The acoustic subunit is used to emit a sine wave sound and / or white noise at a frequency of 40Hz, and the volume of the acoustic subunit is adjustable from 30 to 70 decibels.

[0136] The optical subunit includes multiple red LEDs and multiple green LEDs, and the frequency range of the pulse modulation of the red LEDs and the green LEDs is 10-50Hz.

[0137] In some optional implementations, the analysis results of the different wavebands of brainwaves are the energy density ratios of the different wavebands of brainwaves; correspondingly, the parameter adjustment module 403 includes:

[0138] The first control unit is used to adjust the parameters of the execution unit according to the first control strategy if the ratio is greater than the first preset threshold; wherein the first control strategy is: green light dominates, the frequency of LED lamp pulse modulation is the first frequency, the first frequency is greater than the first frequency threshold, and the volume of the acoustic subunit is greater than the first volume threshold.

[0139] The second control unit is used to adjust the parameters of the execution unit according to the second control strategy if the ratio is greater than or equal to the second preset threshold and less than or equal to the first preset threshold; wherein the second control strategy is to control the green LED and the red LED to work, the pulse modulation frequency of the green LED and the red LED is the first frequency and the second frequency, the second frequency is less than the second frequency threshold, and the volume of the acoustic subunit is greater than the second volume threshold and less than or equal to the first volume threshold;

[0140] The third control unit is used to adjust the parameters of the execution unit according to the third control strategy if the ratio is less than the second preset threshold; wherein the third control strategy is: red light dominates, the frequency of LED lamp pulse modulation is the second frequency, and the volume of the acoustic subunit is less than or equal to the second volume threshold.

[0141] In some alternative implementations, the first frequency is 40 Hz, and / or the second frequency is 10 Hz.

[0142] In some optional implementations, the analysis results of the different bands of brainwaves are the proportion of different bands of brainwaves calculated based on at least one of the energy density, waveform diagram, and energy intensity.

[0143] The parameter adjustment module 403 includes:

[0144] The fourth control unit is used to determine that the user is currently in the first sleep aid stage if the proportions of gamma waves and beta waves are both greater than those of alpha waves, and to adjust the parameters of the execution unit according to the fourth control strategy; wherein, the fourth control strategy is to control the green LED light to work, the frequency of the green LED light pulse modulation is a third frequency, and the third frequency is greater than the first frequency threshold.

[0145] The fifth control unit is used to determine that the user is currently in the second sleep aid stage if the proportion of alpha waves increases compared to the first sleep aid stage and the energy intensity of alpha waves is greater than a preset energy intensity threshold, and adjusts the parameters of the execution unit according to the fifth control strategy; wherein, the fifth control strategy is: sequentially turning off the green LED light and controlling the red LED light to work, the frequency of the red LED light pulse modulation is the first frequency, and the volume of the acoustic subunit is greater than the second volume threshold and less than or equal to the first volume threshold;

[0146] The sixth control unit is used to determine that the user is currently in the third sleep aid stage if the proportion of alpha waves decreases compared to the second sleep aid stage, the energy intensity of alpha waves decreases compared to the second sleep aid stage, and the proportions of delta waves and theta waves increase compared to the second sleep aid stage. The sixth control unit then adjusts the parameters of the execution unit according to the sixth control strategy. The sixth control strategy is to reduce the frequency of the red LED pulse modulation and reduce the volume of the acoustic subunit.

[0147] In some optional implementations, the control execution module 404 is specifically used to control the EEG acquisition unit to stop acquiring the EEG signal and then control the execution unit to work for a preset duration according to the adjusted parameters.

[0148] The control device for the sleep aid device also includes: an EEG signal acquisition control unit, used to control the EEG acquisition unit to acquire the EEG signal again after controlling the execution unit to work for a preset time according to the adjusted parameters.

[0149] In some optional implementations, the parameter adjustment period of the execution unit is the target duration; the duration of the EEG signal acquired in each adjustment period is less than or equal to the target duration.

[0150] In some optional embodiments, the analysis results of the different wavebands of brainwaves are the energy density ratios of the different wavebands of brainwaves; the control device of the sleep aid device further includes:

[0151] The judgment module is used to determine whether the ratio obtained in the previous N calculations is less than the third preset threshold if the ratio is less than the third preset threshold.

[0152] The control unit is configured to shut down the execution unit when the ratio is less than a third preset threshold and the ratio calculated in the previous N calculations is less than the third preset threshold.

[0153] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0154] In this embodiment, the control device of the sleep aid device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0155] This invention also provides a sleep aid device having the above-described features. Figure 4 The control device of the sleep aid device shown.

[0156] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0157] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0158] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A control method for a sleep aid device, characterized in that, The sleep aid device includes an EEG acquisition unit and an execution unit, and the method includes: The EEG signal of the user is acquired by the EEG acquisition unit; The brainwaves in different bands of the brainwave signal are analyzed, and the different bands include at least two of the delta band, theta band, alpha band, beta band and gamma wave; Based on the analysis results of the different bands of EEG, the parameters of the execution unit are adjusted; The execution unit is controlled to work according to the adjusted parameters.

2. The method according to claim 1, characterized in that, The analysis of different bands of brainwaves in the electroencephalogram (EEG) signal includes: The analysis is based on at least one of the energy density, waveform, and energy intensity of the different frequency bands of EEG.

3. The method according to claim 2, characterized in that, The execution unit includes an acoustic subunit and / or an optical subunit; The acoustic subunit is used to emit a sine wave sound and / or white noise at a frequency of 40Hz, and the volume of the acoustic subunit is adjustable from 30 to 70 decibels. The optical subunit includes multiple red LEDs and multiple green LEDs, and the frequency range of the pulse modulation of the red LEDs and the green LEDs is 10-50Hz.

4. The method according to claim 3, characterized in that, The analysis results of the different wavebands of brain waves are the energy density ratios of the different wavebands of brain waves; The adjustment of the parameters of the execution unit based on the analysis results of the different EEG bands includes: If the ratio is greater than a first preset threshold, the parameters of the execution unit are adjusted according to a first control strategy; wherein, the first control strategy is: green light dominates, the frequency of LED lamp pulse modulation is a first frequency, the first frequency is greater than a first frequency threshold, and the volume of the acoustic subunit is greater than a first volume threshold. If the ratio is greater than or equal to the second preset threshold and less than or equal to the first preset threshold, the parameters of the execution unit are adjusted according to the second control strategy; wherein, the second control strategy is: to control the green LED and the red LED to work, the pulse modulation frequency of the green LED and the red LED is the first frequency and the second frequency, the second frequency is less than the second frequency threshold, and the volume of the acoustic subunit is greater than the second volume threshold and less than or equal to the first volume threshold; If the ratio is less than the second preset threshold, the parameters of the execution unit are adjusted according to the third control strategy; wherein the third control strategy is: red light dominates, the frequency of LED lamp pulse modulation is the second frequency, and the volume of the acoustic subunit is less than or equal to the second volume threshold.

5. The method according to claim 3, characterized in that, The analysis results of the different bands of brain waves are the proportion of different bands of brain waves calculated based on at least one of the energy density, waveform diagram and energy intensity. The adjustment of the parameters of the execution unit based on the analysis results of the different EEG bands includes: If the proportions of gamma waves and beta waves are both greater than those of alpha waves, then it is determined that the user is currently in the first sleep aid stage, and the parameters of the execution unit are adjusted according to the fourth control strategy; wherein, the fourth control strategy is: controlling the green LED light to work, the frequency of the green LED light pulse modulation is a third frequency, and the third frequency is greater than the first frequency threshold; If the proportion of alpha waves increases compared to the first sleep aid stage, and the energy intensity of alpha waves is greater than a preset energy intensity threshold, then it is determined that the user is currently in the second sleep aid stage, and the parameters of the execution unit are adjusted according to the fifth control strategy; wherein, the fifth control strategy is: sequentially turning off the green LED light and controlling the red LED light to work, and the frequency of the red LED light pulse modulation is the third frequency; If the proportion of alpha waves decreases compared to the second sleep-aid stage, the energy intensity of alpha waves decreases compared to the second sleep-aid stage, and the proportions of delta waves and theta waves increase compared to the second sleep-aid stage, then it is determined that the user is currently in the third sleep-aid stage, and the parameters of the execution unit are adjusted according to the sixth control strategy; wherein, the sixth control strategy is: reducing the frequency of the red LED pulse modulation and reducing the volume of the acoustic subunit.

6. The method according to claim 1, characterized in that, The step of controlling the execution unit to work according to the adjusted parameters includes: After the EEG acquisition unit stops acquiring the EEG signal, the execution unit is controlled to work for a preset duration according to the adjusted parameters. After controlling the execution unit to work for a preset duration according to the adjusted parameters, the method further includes: controlling the EEG acquisition unit to acquire the EEG signal again.

7. The method according to claim 1, characterized in that, The parameter adjustment cycle of the execution unit is the target duration; the duration of the EEG signal acquired in each adjustment cycle is less than or equal to the target duration.

8. The method according to claim 7, characterized in that, The analysis results of the different wavebands of brain waves are the energy density ratios of the different wavebands of brain waves; After analyzing the different bands of brainwaves in the electroencephalogram (EEG) signal, the method further includes: If the ratio is less than a third preset threshold, then determine whether the ratio obtained in the previous N calculations is less than the third preset threshold. If so, then the execution unit is shut down.

9. A control device for a sleep aid device, characterized in that, The sleep aid device includes an EEG acquisition unit and an execution unit; the device includes: The EEG signal acquisition module is used to acquire the user's EEG signal acquired by the EEG acquisition unit; The analysis module is used to analyze the brain waves of different bands in the brain signal, wherein the different bands include at least two of the delta band, theta band, alpha band, beta band and gamma wave; The parameter adjustment module is used to adjust the parameters of the execution unit based on the analysis results of the different bands of EEG. The control execution module is used to control the execution unit to work according to the adjusted parameters.

10. A sleep aid device, characterized in that, include: Central processing unit, EEG acquisition unit, and execution unit; The EEG acquisition unit is used to acquire EEG signals; The central processing unit is used to execute the control method of the sleep aid device according to any one of claims 1 to 8; The execution unit is controlled by the central processing unit.

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