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

Abstract

The invention discloses a sleep aiding method, a sleep aiding device, sleep aiding equipment and a storage medium. The sleep aiding method comprises the following steps: acquiring a plurality of sleep aiding audios; inputting the acquired multiple sleep-aiding audios into a classification model, and classifying the multiple sleep-aiding audios according to audio types and sleep-aiding effects; performing feature extraction on the classified sleep-aiding audios to obtain sleep-aiding audio feature parameters; inputting the obtained sleep-aiding audio characteristic parameters into a conversion model for conversion, and outputting different sleep-aiding magnetic signals; classifying the sleep-aiding magnetic signals according to audio types and sleep-aiding effects and storing the sleep-aiding magnetic signals as various sleep-aiding magnetic stimuli; according to the method, corresponding sleep-aiding magnetic stimulation is sent out according to a selection instruction of a user, different types of sleep-aiding audios are converted into corresponding sleep-aiding magnetic signals, the advantages of the sleep-aiding audios and the sleep-aiding magnetic stimulation are integrated, the sleep quality of the user is improved, and in addition, due to the fact that the sleep-aiding audios are converted into the specific sleep-aiding magnetic stimulation, the sleep quality of the user is improved. Dependency can be avoided while the sleep aiding effect is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of sleep aid, and in particular to a sleep aid method, a sleep aid device, a sleep aid equipment and a storage medium. Background Art

[0002] According to current research findings, although sleep aid audio has a certain sleep aid effect, since it does not directly act on the brain, the effect varies significantly among different people, and some people will develop dependence on sleep aid audio, resulting in poor sleep without the help of audio, and even interfering with normal sleep.

[0003] Magnetic stimulation is an effective and non-invasive sleep aid means that can directly act on the brain and generally does not cause dependence. However, current research only shows that magnetic stimulation can aid sleep, but it is not clear which frequency of signal has a better sleep aid effect.

[0004] Therefore, there is an urgent need to develop a sleep aid method that converts sleep aid audio into sleep aid magnetic signals. Summary of the Invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide a sleep aid method, a sleep aid device, a sleep aid equipment and a storage medium, which combine the advantages of sleep aid audio and sleep aid magnetic stimulation to improve the sleep quality of users.

[0006] In view of this purpose, an embodiment of the present invention provides a sleep aid method, including:

[0007] Obtain a variety of sleep aid audio;

[0008] Input the obtained various sleep aid audio into a classification model and classify them according to audio types or sleep aid effects;

[0009] Extract features from the classified sleep aid audio to obtain sleep aid audio feature parameters;

[0010] Input the obtained sleep aid audio feature parameters into a conversion model for conversion, and output different sleep aid magnetic signals;

[0011] Classify the sleep aid magnetic signals according to audio types or sleep aid effects and store them as various sleep aid magnetic stimulations;

[0012] Send corresponding sleep aid magnetic stimulations according to the user's selection instruction or the user's current sleep state.

[0013] Optionally, the audio types include at least one of sleep aid music, five-tone therapy in traditional Chinese medicine, and white noise.

[0014] Optionally, the sleep aid effects include at least promoting falling asleep and / or promoting deep sleep.

[0015] Optionally, the sleep-aid audio feature parameters include at least one of pitch, loudness, and timbre.

[0016] Optionally, inputting the obtained sleep-aid audio feature parameters into a conversion model for conversion, and outputting different sleep-aid magnetic signals, includes:

[0017] Analyzing and calculating various sleep-aid audio feature parameters based on the conversion model, and outputting different categories of magnetic signals.

[0018] Optionally, analyzing and calculating various sleep-aid audio feature parameters based on the conversion model, and outputting different categories of magnetic signals, includes:

[0019] Calculating a frequency value according to the pitch; calculating an amplitude value according to the loudness; classifying the waveforms of the sleep-aid audio into different waveform categories according to the timbre, to obtain sleep-aid magnetic signals with different frequencies, amplitudes, and waveform categories.

[0020] Optionally, classifying the sleep-aid magnetic signals according to audio types or sleep-aid effects and storing them as various sleep-aid magnetic stimulations, and emitting corresponding sleep-aid magnetic stimulations according to a user's selection instruction, includes:

[0021] Classifying and storing the various sleep-aid magnetic stimulations in a memory, and outputting an action instruction to a magnetic field generator by a processor according to the user's selection instruction, and the magnetic field generator emits a corresponding sleep-aid magnetic stimulation.

[0022] In addition, a sleep-aid device is also provided, including:

[0023] An acquisition module, configured to acquire a variety of sleep-aid audios;

[0024] A classification module, configured to classify the acquired variety of sleep-aid audios according to audio types or sleep-aid effects;

[0025] A feature extraction module, configured to extract features from the classified sleep-aid audios to obtain sleep-aid audio feature parameters;

[0026] A conversion module, configured to input the obtained sleep-aid audio feature parameters into a conversion model for conversion, and output different sleep-aid magnetic signals;

[0027] A storage module, configured to classify the sleep-aid magnetic signals according to audio types or sleep-aid effects and store them as various sleep-aid magnetic stimulations;

[0028] A magnetic stimulation output module, configured to emit corresponding sleep-aid magnetic stimulations according to a user's selection instruction or the user's current sleep state.

[0029] In addition, a sleep aid device is provided, including at least one processor and a memory communicatively connected to the at least one processor. The memory stores a computer program executable by the at least one processor. When the computer program is executed by the at least one processor, the at least one processor is enabled to execute the sleep aid method described above.

[0030] Optionally, the computer-readable storage medium stores computer instructions for enabling a processor to implement the sleep aid method when executed.

[0031] Advantages of the present invention: The embodiments of the present invention provide a sleep aid method, a sleep aid device, a sleep aid device, and a storage medium. By obtaining a variety of sleep aid audio; inputting the obtained variety of sleep aid audio into a classification model and classifying them according to audio types or sleep aid effects; extracting features of the classified sleep aid audio to obtain sleep aid audio feature parameters; inputting the obtained sleep aid audio feature parameters into a conversion model for conversion and outputting different sleep aid magnetic signals; classifying the sleep aid magnetic signals according to audio types or sleep aid effects and storing them as various sleep aid magnetic stimulations; and emitting corresponding sleep aid magnetic stimulations according to a user's selection instruction or the user's current sleep state, converting different types of sleep aid audio into corresponding sleep aid magnetic signals, integrating the advantages of sleep aid audio and sleep aid magnetic stimulations, improving the user's sleep quality. In addition, since the sleep aid audio is converted into specific sleep aid magnetic stimulations, dependence can be avoided while enhancing the sleep aid effect. Description of the Drawings

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 It is a flowchart of the steps of a sleep aid method provided by an embodiment of the present invention;

[0034] Figure 2 It is a schematic diagram of the modules of a sleep aid device provided by an embodiment of the present invention;

[0035] Figure 3 It is a flowchart of converting sleep aid audio into sleep aid magnetic stimulation in a sleep aid method provided by an embodiment of the present invention;

[0036] Figure 4 It is a specific overall flowchart of a sleep aid method provided by an embodiment of the present invention. Detailed Embodiments

[0037] An embodiment of the present invention provides a sleep aid method, a sleep aid device, a sleep aid device and a storage medium, which combines the advantages of sleep aid audio and sleep aid magnetic stimulation to improve the sleep quality of users.

[0038] In order to make the invention objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0039] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and through specific embodiments.

[0040] Embodiment 1:

[0041] Please refer to Figure 1 An embodiment of the present invention provides a sleep aid method, including:

[0042] Step S10: Obtain various sleep aid audios; initially, search for publicly available sleep aid audios on the Internet. The types of the sleep aid audios include at least one of sleep aid music, five traditional Chinese medicine tones, and white noise. Then, sort and classify the collected publicly available sleep aid audios, and classify the sleep aid audios according to the sleep aid effect. It should be noted that the sleep aid effect of the sleep aid audio can be classified by referring to the audio functions introduced in the audio instruction manual during collection, or can be self-evaluated through various evaluation methods. The evaluation method can be to apply the sleep aid audio to the tester and evaluate according to the results of the sleep diary, sleep scale, or polysomnogram. The sleep aid effect includes at least promoting falling asleep and promoting deep sleep. And establish a classification model for each audio according to the evaluation results of the sleep aid effect.

[0043] Step S20: Input the obtained various sleep aid audios into the classification model and classify them according to the audio type or the sleep aid effect;

[0044] Specifically, after establishing the classification model, publicly available sleep aid audios on the Internet can be automatically captured and input into the classification model, and the sleep aid audios can be classified according to the audio type or the sleep aid effect. According to the audio type, it can be divided into sleep aid music, five traditional Chinese medicine tones, white noise, etc. According to the sleep aid effect classification, it can be divided into promoting falling asleep, promoting deep sleep, etc.

[0045] Step S30: Extract the features of the classified sleep aid audios to obtain the sleep aid audio feature parameters;

[0046] Specifically, according to the existing feature extraction method, the classified sleep-aid audio is subjected to feature extraction to obtain sleep-aid audio features. The sleep-aid audio feature parameters include at least one of pitch, loudness, and timbre. The purpose of extracting the sleep-aid audio feature parameters is to make the variation law of the magnetic signal consistent with that of the sleep-aid audio, absorb the characteristics of the sleep-aid audio, and improve the sleep-aid effect.

[0047] Step S40: Input the obtained sleep-aid audio feature parameters into the conversion model for conversion, and the output is different sleep-aid magnetic signals;

[0048] See Figure 3 , specifically, first construct a conversion model, input the obtained sleep-aid audio features into the conversion model for conversion, and the output is different sleep-aid magnetic signals, that is, the output is different categories of magnetic stimulations.

[0049] The main feature parameters of audio are pitch, loudness, and timbre. Pitch is determined by frequency. Therefore, the frequency value can be calculated according to the pitch. Different changes in frequency are also important differences between white noise, music, etc. So, the obtained frequency values are significantly different; Loudness is determined by amplitude and distance. Therefore, the distance value can be fixed as L, and then the amplitude value can be calculated according to the loudness; Timbre is determined by other characteristics of the waveform and can be classified into square waves, sawtooth waves, sine waves, pulse waves, etc. Therefore, the waveform of the sleep-aid audio can be classified into different categories.

[0050] It should be noted that in the selection of the model, LSTM (Long Short-Term Memory network) and Transformer (a deep learning model based on self-attention mechanism) are two advanced deep learning models, and they perform excellently in processing sequence data (such as audio signals).

[0051] LSTM can capture the long-term dependencies in audio signals, which is crucial for understanding the dynamic changes of audio signals. Transformer, through the self-attention mechanism, can efficiently process the complex relationships in audio signals, especially those correlations between different time points.

[0052] Both LSTM and Transformer models can be trained to learn the complex non-linear relationship from audio signals to magnetic signals. This relationship is based on the mapping between the feature parameters of audio signals (such as pitch, loudness, timbre, etc.) and the characteristics of magnetic signals (such as magnetic field strength, frequency, waveform, etc.).

[0053] In the training stage, the model will receive a large number of audio signals as inputs and try to predict the corresponding magnetic signals. Through continuous iteration and optimization, the model can gradually learn the mapping law from audio signals to magnetic signals.

[0054] In the conversion stage, the pre-trained model receives new audio signals as input. Based on the learned mapping relationship, the model outputs corresponding magnetic signals. These magnetic signals can be used to generate controllable magnetic field pulses, thus achieving the effect of helping users fall asleep.

[0055] It can be understood that when starting to build such a conversion model, the following technology stack can be adopted to quickly build a prototype system:

[0056] (1) Audio preprocessing stage: Use the OpenAL audio model for feature extraction and combine it with TTSMaker for timbre control to ensure the quality and accuracy of the audio signal.

[0057] (2) Signal generation link: Use GAN or LSTM models to achieve cross-modal mapping, and introduce reinforcement learning algorithms for dynamic parameter adjustment to optimize the efficiency and accuracy of signal generation.

[0058] (3) In terms of hardware deployment: Use Raspberry Pi as the core platform for signal generation and equip it with electromagnetic coils to achieve the emission and regulation of magnetic fields.

[0059] It is worth emphasizing that the implementation of this solution needs to be closely combined with specific hardware interfaces and user physiological data for continuous iteration and optimization, so as to achieve the precise conversion from basic sleep-aiding audio to low-frequency magnetic field pulses (frequency range between 0.5 - 3 Hz), providing a more efficient and personalized sleep-aiding solution for users.

[0060] Step S50: Classify the sleep-aiding magnetic signals according to audio types or sleep-aiding effects and store them as various sleep-aiding magnetic stimulations.

[0061] Specifically, store various sleep-aiding magnetic stimulations through a memory. The final sleep-aiding magnetic stimulations include different types or sleep-aiding effects. Users can choose the corresponding sleep-aiding magnetic stimulations according to their own needs and preferences. The classification of the sleep-aiding magnetic stimulations is the same as the classification of the corresponding sleep-aiding audio or sleep-aiding effects.

[0062] Step S60: Send out corresponding sleep-aiding magnetic stimulations according to the user's selection instruction or the user's current sleep state.

[0063] Specifically, the processor receives the user's selection instruction and issues an instruction to the magnetic field generator according to the user's selection. The magnetic field generator emits corresponding sleep-aiding magnetic stimulation. For example, if the user wants to fall asleep as soon as possible or wants to relax before going to sleep, the user can manually select the corresponding instruction. Alternatively, the processor can also automatically select and issue a suitable instruction to the magnetic field generator according to the detected current sleep state of the user, and the magnetic field generator emits corresponding sleep-aiding magnetic stimulation. For example, when it is detected that the user's current sleep state is a light sleep state, the processor issues an instruction to make the magnetic field emitter select sleep-aiding magnetic stimulation that can promote the user to enter a deep sleep state from the light sleep state. It should be noted that the methods and devices for detecting the user's current sleep state are all prior arts in this field and will not be elaborated here.

[0064] Optionally, inputting the obtained sleep-aiding audio feature parameters into a conversion model for conversion, and outputting different sleep-aiding magnetic signals, including:

[0065] Analyzing and calculating various sleep-aiding audio feature parameters based on the conversion model, and outputting different categories of magnetic signals.

[0066] Optionally, analyzing and calculating various sleep-aiding audio feature parameters based on the conversion model, and outputting different categories of magnetic signals, including:

[0067] Calculating a frequency value according to the pitch; calculating an amplitude value according to the loudness; classifying the waveforms of the sleep-aiding audio into different waveform categories according to the timbre, and obtaining sleep-aiding magnetic signals with different frequencies, amplitudes, and waveform categories.

[0068] Optionally, classifying the sleep-aiding magnetic signals according to audio types or sleep-aiding effects and storing them as various sleep-aiding magnetic stimulations, and emitting corresponding sleep-aiding magnetic stimulations according to the user's selection instruction, including:

[0069] Classifying and storing various sleep-aiding magnetic stimulations in a memory, and the processor outputs an action instruction to the magnetic field generator according to the user's selection instruction, and the magnetic field generator emits the corresponding sleep-aiding magnetic stimulation.

[0070] Embodiment 2:

[0071] In addition, a sleep-aiding device is provided, including:

[0072] An acquisition module 1, configured to acquire a variety of sleep-aiding audios; automatically acquire sleep-aiding audios through audio capture software.

[0073] A classification module 2, configured to input the acquired variety of sleep-aiding audios into a classification model and classify them according to audio types or sleep-aiding effects; the algorithms used in the classification model include linear SVM, quadratic SVM, cubic SVM, fine Gaussian SVM, medium Gaussian SVM, rough Gaussian SVM, rough tree, medium tree, fine tree, etc.

[0074] The feature extraction module 3 is used to extract features from the classified sleep-aid audio to obtain sleep-aid audio feature parameters. The algorithms for audio feature extraction mainly include: librosa for speech signal processing, timbral_models for timbre extraction, python_speech_features for speech recognition, etc.

[0075] The conversion module 4 is used to input the obtained sleep-aid audio feature parameters into a conversion model for conversion, and output different sleep-aid magnetic signals. The audio is converted into magnetic signals through an audio conversion software.

[0076] The storage module 5 is used to classify the sleep-aid magnetic signals according to audio types or sleep-aid effects and store them as various sleep-aid magnetic stimulations. The various sleep-aid magnetic stimulations are stored through a memory, such as a read-only memory (ROM), a random access memory (RAM), etc.

[0077] The magnetic stimulation output module 6 is used to emit corresponding sleep-aid magnetic stimulations according to the user's selection instruction.

[0078] The processor receives the user's instruction and outputs an action instruction to the magnetic field generator, and the magnetic field generator emits the corresponding sleep-aid magnetic stimulation. A commercially available magnetic field generator can be used to send magnetic signals.

[0079] Embodiment Three:

[0080] In addition, a sleep-aid device is provided, including at least one processor and a memory communicatively connected to the at least one processor. Wherein, the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute any one of the sleep-aid methods.

[0081] Specifically, the processor receives the user's instruction and outputs an action instruction to the magnetic field generator, and the magnetic field generator emits the corresponding sleep-aid magnetic stimulation. The processor can be various general and / or special processing components with processing and computing capabilities. For example, it includes, but is not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc.

[0082] Embodiment Four:

[0083] In addition, a computer-readable storage medium stores computer instructions for enabling a processor to implement any one of the sleep-aid methods when executed.

[0084] Specifically, a computer-readable storage medium may be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include electrical connections based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0085] In summary, the embodiments of the present invention provide a sleep aid method, a sleep aid device, a sleep aid apparatus, and a storage medium. By obtaining a variety of sleep aid audio; inputting the obtained various sleep aid audio into a classification model and classifying them according to audio types or sleep aid effects; extracting features of the classified sleep aid audio to obtain sleep aid audio feature parameters; inputting the obtained sleep aid audio feature parameters into a conversion model for conversion to output different sleep aid magnetic signals; classifying the sleep aid magnetic signals according to audio types or sleep aid effects and storing them as various sleep aid magnetic stimulations; and emitting corresponding sleep aid magnetic stimulations according to a user's selection instruction, converting different types of sleep aid audio into corresponding sleep aid magnetic signals, integrating the advantages of sleep aid audio and sleep aid magnetic stimulations, enabling the user to improve the sleep quality. Additionally, since the sleep aid audio is converted into specific sleep aid magnetic stimulations, it can enhance the sleep aid effect while avoiding dependence.

[0086] In the above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for aiding sleep, characterized in that: include: Get a variety of sleep-aiding audios; Inputting the obtained multiple sleep-aiding audios into a classification model and classifying them according to audio types or sleep-aiding effects; Perform feature extraction on the classified sleep-aiding audio to obtain the sleep-aiding audio feature parameters; The acquired sleep-aiding audio feature parameters are input into the conversion model for conversion, and the output is different sleep-aiding magnetic signals; Classifying the sleep-aiding magnetic signals according to audio types or sleep-aiding effects and storing them as a plurality of sleep-aiding magnetic stimulations; Corresponding sleep-aiding magnetic stimulation is emitted according to the user's selection instructions or the user's current sleep state.

2. The sleep aid method according to claim 1, characterized in that: The audio types include at least one of sleep-aiding music, five tones of traditional Chinese medicine, and white noise.

3. The sleep aid method according to claim 1, characterized in that: The sleep-aiding effect at least includes promoting falling asleep and / or promoting deep sleep.

4. The sleep aid method according to claim 1, characterized in that: The sleep-aiding audio characteristic parameters include at least one of pitch, loudness, and timbre.

5. The sleep-aiding method according to claim 1, characterized in that: The acquired sleep-aiding audio feature parameters are input into the conversion model for conversion, and output as different sleep-aiding magnetic signals, including: Based on the conversion model, various sleep-aiding audio feature parameters are analyzed and calculated, and the output is magnetic signals of different categories.

6. The sleep aid method according to claim 5, characterized in that: The conversion model is based on analyzing and calculating various sleep-aiding audio feature parameters, and outputting different types of magnetic signals, including: The frequency value is calculated according to the pitch; the amplitude value is calculated according to the loudness; the waveform of the sleep-aiding audio is classified into different waveform categories according to the timbre, and sleep-aiding magnetic signals of different frequencies, amplitudes and waveform categories are obtained.

7. The sleep aid method according to claim 1, characterized in that: The sleep-aiding magnetic signal is classified according to the audio type or the sleep-aiding effect and stored as a plurality of sleep-aiding magnetic stimulations, and the corresponding sleep-aiding magnetic stimulations are issued according to the user's selection instruction, including: The multiple sleep-aiding magnetic stimulations are classified and stored in a memory, and the processor outputs an action instruction to the magnetic field generator according to the user's selection instruction, and the magnetic field generator emits the corresponding sleep-aiding magnetic stimulation.

8. A sleep aid device, characterized in that: include: Acquisition module, used to obtain a variety of sleep-aiding audios; A classification module, used to classify the obtained multiple sleep-aiding audios according to audio types or sleep-aiding effects; A feature extraction module is used to extract features from the classified sleep-aiding audio and obtain feature parameters of the sleep-aiding audio; A conversion module, used for inputting the acquired sleep-aiding audio feature parameters into a conversion model for conversion, and outputting different sleep-aiding magnetic signals; A storage module, used for classifying the sleep-aiding magnetic signals according to audio types or sleep-aiding effects and storing them as a plurality of sleep-aiding magnetic stimulations; The magnetic stimulation output module is used to issue corresponding sleep-aiding magnetic stimulation according to the user's selection instructions or the user's current sleep state.

9. A sleep aid device, characterized in that: The invention comprises at least one processor and a memory communicatively connected to the at least one processor, wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the sleep aid method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the sleep-aiding method according to any one of claims 1 to 7 when executed.

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