Binaural differential frequency sleep modulation method and system

Abstract

This invention provides a method and system for binaural differential frequency sleep conditioning, aiming to solve the technical problems of existing sleep regulation methods being weakly targeted, easily affected by environmental interference, and difficult to adapt to different types of sleep disorders in users. The method includes: acquiring user sleep target information; acquiring user physiological data collected in real time; determining the user's current sleep state information based on the user's physiological data; determining differential frequency audio information based on the user's current sleep state information and user sleep target information; generating a first audio signal and a second audio signal based on the differential frequency audio information, wherein the first audio signal and the second audio signal have a specific frequency difference; and sending the first audio signal and the second audio signal with the specific frequency difference to the user's left and right ears respectively, based on the first audio signal and the second audio signal. Through the output and dynamic adjustment of binaural differential frequency audio, sleep disorders are effectively improved, with strong safety and applicability.

Description

Technical Field

[0001] This application relates to the fields of sleep aids and neuromodulation technology, and in particular to a method and system for binaural frequency difference sleep regulation. Background Technology

[0002] With the fast pace of life and increased stress, sleep disorders such as difficulty falling asleep, light sleep, frequent awakenings at night, and REM sleep abnormalities have become common health problems. Sleep disorders not only affect daytime mental state, but in the long term, they may also induce various complications such as cardiovascular disease and neurological dysfunction, seriously endangering human health.

[0003] Current sleep regulation methods are mainly divided into two categories: drug-based and non-drug-based. While drug-based methods can quickly induce sleep, long-term use can easily lead to dependence and drug tolerance, and may cause side effects such as dizziness and drowsiness, resulting in poor safety. Among non-drug-based methods, traditional audio sleep aids can only play light music with fixed melodies, and cannot accurately guide the user's sleep brain waves, thus limiting their regulatory effect. Some sleep monitoring devices can only collect basic sleep data and cannot be linked with sleep aid functions, making dynamic adaptation difficult. At the same time, most sleep aids lack effective noise reduction design, are easily affected by external environmental interference, leading to unstable regulatory effects, and cannot provide targeted solutions based on different users' sleep disorder types, resulting in poor applicability.

[0004] Binaural Beats, a non-invasive neuromodulation technique, works by receiving audio signals with specific frequency differences in each ear. The auditory cortex of the brain automatically generates neural oscillations corresponding to these frequency differences, thus synchronizing with target sleep brain waves. However, existing devices based on this technology mostly output fixed parameters, lacking real-time sleep state feedback and dynamic parameter adjustment mechanisms. Furthermore, they suffer from low audio transmission accuracy and weak anti-interference capabilities, making it difficult to meet the personalized sleep needs of different users and hindering their widespread application in clinical and home sleep regulation scenarios.

[0005] Therefore, developing a binaural differential frequency sleep conditioning system with precise audio output, real-time status monitoring, dynamic parameter adjustment, and personalized adaptation capabilities to solve the problems of weak targeting, susceptibility to interference, and poor adaptability of existing technologies has become an urgent technical need. Summary of the Invention

[0006] This invention aims to overcome the shortcomings of existing sleep regulation methods and provides a binaural difference frequency sleep regulation method and system. Through the collaborative work of multiple modules, it achieves precise output and dynamic adjustment of binaural difference frequency audio, guiding the brain into the target sleep state without relying on drugs, effectively improving different types of sleep disorders, and enhancing the safety, targeting and applicability of sleep regulation.

[0007] This invention provides a method for binaural frequency difference sleep regulation, the method comprising: Obtain user sleep target information, including sleep onset time, sleep duration, and percentage of target sleep stages; Acquire real-time monitoring and collection of user physiological data, including at least one of heart rate, electroencephalogram (EEG), and respiratory rate; Based on the user's physiological data, determine the user's current sleep state information; Based on the user's current sleep state information and the user's sleep target information, determine the difference frequency audio information; Based on the difference frequency audio information, a first audio signal and a second audio signal are generated, and there is a specific frequency difference between the first audio signal and the second audio signal, which corresponds to the brain wave frequency of the target sleep stage. Based on the first audio signal and the second audio signal, a first audio signal and a second audio signal with the specific frequency difference are sent to the user's left ear and right ear respectively.

[0008] In some embodiments, the specific frequency difference ranges from 0.5 to 30 Hz.

[0009] In some embodiments, the target sleep stage includes the sleep onset stage, light sleep stage, deep sleep stage, and REM sleep stage.

[0010] In some embodiments, the specific frequency difference ranges from 8 to 13 Hz, corresponding to the sleep stage. For the light sleep stage, the specific frequency difference ranges from 4 to 7 Hz; Corresponding to the deep sleep stage, the specific frequency difference ranges from 0.5 to 3 Hz; For the REM sleep stage, the specific frequency difference range is selected from one or both of 4-7Hz and 13-30Hz.

[0011] This invention provides a binaural frequency difference sleep regulation system, the system comprising: an audio generation module, a binaural audio output module, a sleep state monitoring module, and a user interaction module; The user interaction module is used to obtain user sleep target information and send the user sleep target information to the audio generation module. The user sleep target information includes sleep onset time, sleep duration, and target sleep stage percentage. The sleep state monitoring module is used to acquire real-time monitored user physiological data and send the user physiological data to the audio generation module. The user physiological data includes at least one of heart rate, brain waves, and respiratory rate. The audio generation module is used to determine the user's current sleep state information based on the user's physiological data, determine the difference frequency audio information based on the user's current sleep state information and the user's sleep target information, generate a first audio signal and a second audio signal based on the difference frequency audio information, and send the first audio signal and the second audio signal to the binaural audio output module. The first audio signal and the second audio signal have a specific frequency difference, and the specific frequency difference corresponds to the brain wave frequency of the target sleep stage. The binaural audio output module is used to send a first audio signal and a second audio signal with the specific frequency difference to the user's left and right ears respectively, based on the first audio signal and the second audio signal.

[0012] In some embodiments, the binaural audio output module adopts a lightweight noise-canceling headphone structure, including a headphone body, an audio decoding unit, a noise-canceling unit, and a battery life unit, for transmitting the first audio and the second audio to the user's left and right ears, and isolating external environmental interference.

[0013] In some embodiments, the sleep state monitoring module includes a multimodal human factors data acquisition terminal and a data transmission unit, used to monitor and collect the user's physiological data in real time, and send the user's physiological data to the audio generation module.

[0014] In some embodiments, the specific frequency difference ranges from 0.5 to 30 Hz.

[0015] In some embodiments, the target sleep stage includes the sleep onset stage, light sleep stage, deep sleep stage, and REM sleep stage, and the audio generation module matches a specific frequency difference according to the user's current target sleep stage.

[0016] In some embodiments, the specific frequency difference ranges from 8 to 13 Hz, corresponding to the sleep stage. For the light sleep stage, the specific frequency difference ranges from 4 to 7 Hz; Corresponding to the deep sleep stage, the specific frequency difference ranges from 0.5 to 3 Hz; For the REM sleep stage, the specific frequency difference range is selected from one or both of 4-7Hz and 13-30Hz.

[0017] The method and system of the above embodiments of the present invention can accurately output and dynamically adjust the binaural difference frequency audio to match the specific frequency difference corresponding to the user's sleep state information, guide the brain into the target sleep state without relying on drugs, effectively improve sleep disorders, and have strong safety and applicability. Attached Figure Description

[0018] The accompanying drawings illustrate, by way of example and not limitation, the various embodiments discussed herein.

[0019] Figure 1 This is a schematic diagram of the steps of a binaural frequency difference sleep regulation method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the components of a binaural frequency difference sleep regulation system according to an embodiment of the present invention; Figure 3 This is a block diagram of the internal structure of the audio generation module. Detailed Implementation

[0020] In order to gain a more detailed understanding of the features and technical content of the embodiments of this application, the implementation of the embodiments of this application will be described in detail below with reference to the accompanying drawings. The accompanying drawings are for reference and illustration only and are not intended to limit the embodiments of this application.

[0021] In the embodiments described in this application, it should be noted that, unless otherwise stated and limited, the term "connection" should be interpreted broadly. For example, it can be an electrical connection, or a connection between two internal components. It can be a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above term according to the specific circumstances.

[0022] Figure 1 This is a schematic diagram of the steps of a binaural frequency difference sleep regulation method according to an embodiment of the present invention.

[0023] This invention provides a method for regulating bilateral ear frequency difference sleep, such as... Figure 1 As shown, the method includes the following steps: Step 101: Obtain the user's sleep target information, including sleep onset time, sleep duration, and the percentage of target sleep stages.

[0024] Here, the target sleep stages include the sleep onset stage, light sleep stage, deep sleep stage, and REM sleep stage.

[0025] Step 102: Obtain real-time monitoring and collection of user physiological data, including at least one of heart rate, electroencephalogram (EEG), and respiratory rate.

[0026] Step 103: Determine the user's current sleep status information based on the user's physiological data.

[0027] User physiological data may include at least one of the following: electrocardiogram (ECG) signals, heart rate, respiratory rate, body movement signals, blood oxygen saturation, and sleep posture. Among these, the EEG signals are used to directly analyze the user's current sleep brainwave type and sleep stage; heart rate and respiratory rate are used to help determine sleep depth; body movement signals are used to detect whether the user is prone to waking up at night; and blood oxygen saturation is used to monitor the body's state during sleep and prevent abnormalities from occurring.

[0028] Step 104: Determine the difference frequency audio information based on the user's current sleep state information and the user's sleep goal information.

[0029] Here, the difference-frequency audio information is used to characterize the specific frequency difference between the user's current sleep state information and the user's sleep target information. It can be generated according to the difference-frequency audio algorithm. By calling the pre-stored difference-frequency audio parameter models adapted to the light sleep stage, deep sleep stage, REM sleep stage, and sleep disorder types such as difficulty falling asleep, light sleep, and easy awakening through multiple preset difference-frequency audio algorithms, the algorithm can generate independent audio signals for the left and right ears based on preset parameters or user sleep physiological data fed back by the sleep state monitoring module, so that the audio signals received by the two ears form a specific frequency difference.

[0030] Step 105: Generate a first audio signal and a second audio signal based on the difference frequency audio information. The first audio signal and the second audio signal have a specific frequency difference.

[0031] In some embodiments, the specific frequency difference ranges from 0.5 to 30 Hz.

[0032] In some embodiments, a specific frequency difference corresponds to the brainwave frequency of the target sleep stage.

[0033] In some embodiments, the specific frequency difference ranges from 8 to 13 Hz, corresponding to the sleep stage.

[0034] For the light sleep stage, the specific frequency difference range is 4-7Hz.

[0035] The specific frequency difference ranges from 0.5 to 3 Hz for the deep sleep stage.

[0036] For the REM sleep stage, the specific frequency difference range is selected from one or both of 4-7Hz and 13-30Hz.

[0037] In some embodiments, corresponding to the REM sleep stage, a specific frequency difference is dynamically switched or superimposed between two ranges: 4-7Hz and 13-30Hz, and signals with two frequency differences are input alternately.

[0038] Step 106: Send a first audio signal and a second audio signal with a specific frequency difference to the user's left and right ears respectively, based on the first audio signal and the second audio signal.

[0039] The binaural difference frequency sleep regulation method described in the above embodiments, through the output and dynamic adjustment of binaural difference frequency audio, matches the specific frequency difference corresponding to the user's sleep state information, and can guide the brain into the target sleep state without relying on drugs, effectively improving different types of sleep disorders and enhancing the safety, pertinence and applicability of sleep regulation.

[0040] This invention provides a binaural frequency difference sleep regulation system, which can be used to implement the binaural frequency difference sleep regulation method described above. Figure 2 This is a schematic diagram of a binaural frequency difference sleep regulation system according to an embodiment of the present invention, as shown below. Figure 2 As shown, the system includes: an audio generation module 1, a binaural audio output module 2, a sleep state monitoring module 3, and a user interaction module 4. These modules work together to form a closed-loop control system.

[0041] User interaction module 4 is used to obtain user sleep target information and send the user sleep target information to audio generation module 1. The user sleep target information includes sleep onset time, sleep duration, and target sleep stage percentage.

[0042] User interaction module 4 includes an interactive interface and a mobile application, supporting user-customized operations to meet personalized sleep needs. Users can set sleep goals through the interactive interface or the application, including sleep onset time, sleep duration, and the percentage of target sleep stages; select audio types, including natural sounds, white noise, and pure difference frequency waves; adjust the initial volume and difference frequency intensity; and view historical sleep data, including sleep duration, the percentage of each sleep stage, sleep quality scores, and adjustment records, making it easy for users to understand their own sleep status.

[0043] In addition, the user interaction module 4 supports preset scene modes and has built-in multiple scenes such as "Quick Sleep Mode", "Deep Sleep Mode" and "Sleep Maintenance Mode". Users can directly select the corresponding mode according to their own sleep disorder type, and the system will automatically call the matching difference frequency audio parameters to simplify the operation process and adapt to different user needs.

[0044] The sleep state monitoring module 3 is used to acquire real-time monitored user physiological data and send the user physiological data to the audio generation module 1. The user physiological data includes at least one of heart rate, brain waves, and respiratory rate.

[0045] In some embodiments, the sleep state monitoring module 3 includes a multimodal human factors data acquisition terminal and a data transmission unit, used to monitor and collect user physiological data in real time and send the user physiological data to the audio generation module 1.

[0046] The sleep state monitoring module 3 includes a multimodal human factors data acquisition terminal and a data transmission unit, which are used to collect physiological data of the user during sleep in real time and feed the data back to the audio generation module 1 to provide a basis for dynamic adjustment of parameters.

[0047] The multimodal human factors data acquisition terminal can collect physiological data including electrocardiogram (EEG) signals, heart rate, respiratory rate, body movement signals, blood oxygen saturation, and sleep posture. Among these, EEG signals are used to directly analyze the user's current sleep brain wave type and sleep stage; heart rate and respiratory rate are used to help determine sleep depth; body movement signals are used to detect whether the user is prone to waking up at night; and blood oxygen saturation is used to monitor the body's state during sleep and prevent abnormalities from occurring.

[0048] The data transmission unit employs low-power Bluetooth and WiFi technologies to achieve real-time and stable transmission of physiological data, with a transmission latency of no more than 100ms. It also features data encryption to ensure user privacy and security. The sleep monitoring module 3 incorporates a data preprocessing algorithm that filters, denoises, and normalizes the collected raw data, improving data accuracy and reducing the impact of invalid data on audio parameter adjustments.

[0049] The audio generation module 1 is used to determine the user's current sleep state information based on the user's physiological data, determine the difference frequency audio information based on the user's current sleep state information and the user's sleep target information, generate a first audio signal and a second audio signal based on the difference frequency audio information, and send the first audio signal and the second audio signal to the binaural audio output module 2. The first audio signal and the second audio signal have a specific frequency difference.

[0050] Figure 3 Here is a block diagram of the internal structure of audio generation module 1, as follows: Figure 3 As shown, the audio generation module 1 is the core control unit of the system, with a built-in microprocessor 11, memory 12, difference frequency audio algorithm unit 13, and data interaction unit 14. The difference frequency audio algorithm unit 13 pre-stores multiple sets of difference frequency audio algorithms, and the memory 12 pre-stores difference frequency audio parameter models adapted to light sleep, deep sleep, REM sleep, and sleep disorder types such as difficulty falling asleep, light sleep, and frequent awakenings. The difference frequency audio algorithm is designed based on the binaural difference frequency principle and can generate independent audio signals for the left and right ears according to preset parameters or user sleep physiological data fed back by the sleep state monitoring module 3, so that the audio signals received by the two ears form a specific frequency difference. The data interaction unit 14 is used to interact with the binaural audio output module 2, the sleep state monitoring module 3, and the user interaction module 4.

[0051] In some embodiments, the specific frequency difference ranges from 0.5 to 30 Hz. This specific frequency difference corresponds to the brainwave frequencies of the target sleep stage, which includes the sleep onset stage, light sleep stage, deep sleep stage, and REM sleep stage. The audio generation module 1 matches the corresponding specific frequency difference based on the user's current target sleep stage. For the sleep onset stage, the specific frequency difference ranges from 8 to 13 Hz.

[0052] For the light sleep stage, the specific frequency difference range is 4-7Hz.

[0053] The specific frequency difference ranges from 0.5 to 3 Hz for the deep sleep stage.

[0054] For the REM sleep stage, the specific frequency difference range is selected from one or both of 4-7Hz and 13-30Hz.

[0055] In some embodiments, the audio generation module 1 has a dynamic parameter adjustment function. It can receive physiological data transmitted by the sleep state monitoring module 3 in real time, analyze the deviation between the user's current sleep state and the target sleep state through a built-in algorithm, and automatically adjust the frequency difference, volume, playback duration, and audio waveform of the difference frequency audio. The audio waveform includes sine waves, cosine waves, and natural sound superposition waveforms to ensure that the brain nerve oscillations are synchronized with the target sleep brain waves, thereby achieving precise sleep guidance. At the same time, the audio generation module 1 supports data interaction with external terminals and can update the algorithm model and audio parameter library.

[0056] The binaural audio output module 2 is used to send a first audio signal and a second audio signal with a specific frequency difference to the user's left and right ears respectively, based on the first audio signal and the second audio signal.

[0057] In some embodiments, the binaural audio output module 2 adopts a lightweight noise-canceling headphone structure, including a headphone body, an audio decoding unit, a noise-canceling unit, and a battery life unit, for transmitting the first audio and the second audio to the user's left and right ears, and isolating external environmental interference.

[0058] In some embodiments, the main body of the earphones is made of soft, skin-friendly material, designed to conform to the contours of the human ear, making them comfortable to wear and suitable for extended sleep use. The audio decoding unit supports high-fidelity decoding, ensuring distortion-free transmission of audio signals and guaranteeing the accuracy of frequency differences. The noise cancellation unit combines active noise cancellation with passive sound isolation. The active noise cancellation unit uses a microphone to collect ambient noise and generates reverse sound waves to cancel it out. The passive sound isolation unit uses a sealed earcup structure to further block low-frequency and high-frequency noise, achieving a noise reduction effect of 25-40 decibels, ensuring that the audio signal is not interfered with by external factors. The battery unit uses a rechargeable lithium battery with a battery life of no less than 8 hours, supports wireless charging, and meets the needs of overnight use. The earphones also support both Bluetooth and wired connections to adapt to different usage scenarios.

[0059] The binaural difference frequency sleep conditioning method and system of the present invention described above have the following advantages: Highly targeted and widely adaptable: By incorporating multiple sets of difference frequency audio algorithms and combining real-time sleep physiological data feedback, parameters can be dynamically adjusted to adapt to different sleep stages and different types of sleep disorders, meeting the personalized needs of different users and solving the problem of weak targeting of existing devices.

[0060] Strong anti-interference capability and precise adjustment: The binaural audio output module 2 adopts an active + passive dual noise reduction design, which effectively isolates external interference and ensures accurate transmission of difference frequency audio signals; at the same time, based on real-time monitoring of multimodal data, it realizes dynamic closed-loop adjustment of audio parameters, guides the brain to accurately synchronize with the target sleep brain waves, and the adjustment effect is significant.

[0061] High safety and no side effects: It does not rely on sedative-hypnotic drugs. It guides sleep through non-invasive binaural frequency difference technology, avoiding drug dependence, drug resistance and side effects such as dizziness and drowsiness. It is suitable for long-term sleep regulation, and is comfortable to wear without harming the human body.

[0062] Easy to operate and adaptable to various scenarios: It supports user-defined settings and preset scene modes, and also features wireless connectivity and long battery life, making it suitable for home and business trip scenarios, balancing practicality and convenience.

[0063] To further realize the binaural difference frequency sleep regulation system of the above embodiments of the present invention, the present invention provides a specific configuration scheme for the constituent modules of the binaural difference frequency sleep regulation system, as follows: Audio Generation Module 1: Utilizing an STM32H7 series microprocessor as the core control unit, and employing a 16GB Flash chip for memory, it pre-stores five sets of difference-frequency audio algorithm models adapted to different sleep scenarios, including a model for difficulty falling asleep, a model for improving light sleep, a model for adjusting waking up easily, a model for enhancing deep sleep, and a model for optimizing REM sleep. It supports continuous adjustment of the frequency difference within the range of 0.5-30Hz, and the audio waveform can be switched between a sine wave and a natural sound superimposed waveform. The microprocessor analyzes the data transmitted by the sleep state monitoring module 3 through its built-in algorithm, adjusting the difference-frequency parameters every 30 seconds to ensure synchronization with the user's sleep brainwaves.

[0064] Dual-ear audio output module 2: Utilizes lightweight over-ear noise-canceling headphones. The headphone body 21 features memory foam earcups and an adjustable headband for comfortable wear. The audio decoding unit 22 supports 24bit / 96kHz high-fidelity decoding, ensuring distortion-free audio signals. The active noise cancellation unit 23 employs hybrid noise cancellation technology to cancel ambient noise from 20-2000Hz. The passive noise isolation unit uses sealed silicone material, achieving a noise reduction effect of up to 35 decibels. The battery life unit 24 is a 300mAh lithium battery, supporting Bluetooth 5.0 connectivity and providing up to 10 hours of battery life. It also features a universal wired charging interface.

[0065] Sleep monitoring module 3: The multimodal data acquisition terminal adopts a wrist-worn smart bracelet with built-in EEG sensors, heart rate sensors, accelerometers, and blood oxygen sensors, which can collect EEG signals, heart rate, body movement signals, and blood oxygen saturation in real time; the data preprocessing unit performs Kalman filtering to denoise the collected raw data, removing environmental interference and motion artifacts; the data transmission unit uses low-power Bluetooth to transmit data with a transmission latency of 80ms, and the data uses the Advanced Encryption Standard (AES) encryption algorithm to ensure privacy.

[0066] User interaction module 4 includes the built-in touch buttons on the headphones and a companion mobile application. The touch buttons support power on / off, volume adjustment, and mode switching. The mobile application supports setting sleep goals, including falling asleep within 30 minutes, total sleep duration of 8 hours, and deep sleep percentage of no less than 25%. Users can also select audio types, including pure difference frequency wave, rain sound + difference frequency wave, and white noise + difference frequency wave. Users can view historical sleep data and sleep quality scores, and the algorithm model can be updated online.

[0067] For example, the system workflow is as follows: When preparing for sleep, the user wears the binaural audio output module 2 and the sleep state monitoring module 3, selects "Quick Sleep Mode" through the mobile application of the user interaction module 4, sets the target sleep time to 30 minutes, selects "Rain Sound + Difference Frequency Wave" for the audio type, and the system automatically loads the corresponding difference frequency audio initial parameters, with a frequency difference of 8Hz, corresponding to alpha waves, and a volume of 20 decibels.

[0068] The audio generation module 1 generates independent audio signals for the left and right ears based on the initial parameters. The audio frequency for the left ear is 440Hz and the audio frequency for the right ear is 432Hz. The background sound of rain is superimposed and transmitted to the dual-ear audio output module 2 via Bluetooth. The headphones activate the dual noise reduction function to isolate external interference and accurately transmit the audio signal to the user's ears.

[0069] The smart bracelet in the sleep monitoring module 3 collects the user's EEG signals, heart rate, and body movement signals in real time. After being processed by the data preprocessing unit, the data is transmitted in real time to the audio generation module 1 via Bluetooth Low Energy. The microprocessor in the audio generation module 1 analyzes the data using a built-in algorithm to determine the user's current sleep state: if the proportion of alpha waves in the user's EEG signal is less than 60%, it indicates that the progress of falling asleep is slow. The differential frequency is automatically adjusted to 10Hz and the volume is increased to 25dB to enhance the guidance effect. If the proportion of theta waves in the user's EEG signal is more than 70%, it indicates that the user has entered a light sleep state. The differential frequency is automatically adjusted to 5Hz and the volume is reduced to 15dB to maintain the light sleep state and guide the user to transition to deep sleep.

[0070] After the user enters a deep sleep state, the sleep state monitoring module 3 detects that the proportion of delta waves in the EEG signal exceeds 60%. The audio generation module 1 adjusts the difference frequency to 2Hz and maintains a low volume of 10dB. At the same time, it fine-tunes the audio waveform based on heart rate and respiratory rate data to ensure a stable deep sleep state. If the user's body movement signal exceeds the preset threshold at night, it indicates that the user may be about to wake up. The system automatically adjusts the difference frequency to 4Hz and increases the volume to 18dB to guide the user to maintain a sleep state.

[0071] After sleep ends, the sleep state monitoring module 3 summarizes the sleep data of the whole night and transmits it to the mobile application to generate a sleep quality report, including the sleep onset time, the proportion of each sleep stage, and the sleep score. Users can view the report through the application. At the same time, the system optimizes the adjustment parameters for the next time based on the sleep data to improve adaptability.

[0072] The technical solutions described in the embodiments of this application can be combined arbitrarily without conflict.

[0073] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for regulating sleep patterns based on difference in frequency in both ears, characterized in that, The method includes: Obtain user sleep target information, including sleep onset time, sleep duration, and percentage of target sleep stages; Acquire real-time monitoring and collection of user physiological data, including at least one of heart rate, electroencephalogram (EEG), and respiratory rate; Based on the user's physiological data, determine the user's current sleep state information; Based on the user's current sleep state information and the user's sleep target information, determine the difference frequency audio information; Based on the difference frequency audio information, a first audio signal and a second audio signal are generated, and there is a specific frequency difference between the first audio signal and the second audio signal, which corresponds to the brain wave frequency of the target sleep stage. Based on the first audio signal and the second audio signal, a first audio signal and a second audio signal with the specific frequency difference are sent to the user's left ear and right ear respectively.

2. The binaural frequency difference sleep regulation method according to claim 1, characterized in that, The specific frequency difference ranges from 0.5 to 30 Hz.

3. The binaural frequency difference sleep regulation method according to claim 2, characterized in that, The target sleep stages include the sleep onset stage, light sleep stage, deep sleep stage, and REM sleep stage.

4. The binaural frequency difference sleep regulation method according to claim 3, characterized in that, For the sleep stage, the specific frequency difference ranges from 8 to 13 Hz; For the light sleep stage, the specific frequency difference ranges from 4 to 7 Hz; Corresponding to the deep sleep stage, the specific frequency difference ranges from 0.5 to 3 Hz; For the REM sleep stage, the specific frequency difference range is selected from one or both of 4-7Hz and 13-30Hz.

5. A binaural frequency difference sleep regulation system, characterized in that, The system includes: an audio generation module, a binaural audio output module, a sleep state monitoring module, and a user interaction module; The user interaction module is used to obtain user sleep target information and send the user sleep target information to the audio generation module. The user sleep target information includes sleep onset time, sleep duration, and target sleep stage percentage. The sleep state monitoring module is used to acquire real-time monitored user physiological data and send the user physiological data to the audio generation module. The user physiological data includes at least one of heart rate, brain waves, and respiratory rate. The audio generation module is used to determine the user's current sleep state information based on the user's physiological data, determine the difference frequency audio information based on the user's current sleep state information and the user's sleep target information, generate a first audio signal and a second audio signal based on the difference frequency audio information, and send the first audio signal and the second audio signal to the binaural audio output module. The first audio signal and the second audio signal have a specific frequency difference, and the specific frequency difference corresponds to the brain wave frequency of the target sleep stage. The binaural audio output module is used to send a first audio signal and a second audio signal with the specific frequency difference to the user's left and right ears respectively, based on the first audio signal and the second audio signal.

6. The binaural frequency difference sleep regulation system according to claim 5, characterized in that, The binaural audio output module adopts a lightweight noise-canceling headphone structure, including the headphone body, audio decoding unit, noise cancellation unit and battery life unit, which is used to transmit the first audio and the second audio to the user's left and right ears and isolate external environmental interference.

7. The binaural frequency difference sleep regulation system according to claim 5, characterized in that, The sleep state monitoring module includes a multimodal human factors data acquisition terminal and a data transmission unit, which are used to monitor and collect the user's physiological data in real time and send the user's physiological data to the audio generation module.

8. The binaural frequency difference sleep regulation system according to claim 5, characterized in that, The specific frequency difference ranges from 0.5 to 30 Hz.

9. The binaural frequency difference sleep regulation system according to claim 8, characterized in that, The target sleep stage includes the sleep onset stage, light sleep stage, deep sleep stage, and REM sleep stage. The audio generation module matches a specific frequency difference based on the user's current target sleep stage.

10. The binaural frequency difference sleep regulation system according to claim 9, characterized in that, For the sleep stage, the specific frequency difference ranges from 8 to 13 Hz; For the light sleep stage, the specific frequency difference ranges from 4 to 7 Hz; Corresponding to the deep sleep stage, the specific frequency difference ranges from 0.5 to 3 Hz; For the REM sleep stage, the specific frequency difference range is selected from one or both of 4-7Hz and 13-30Hz.

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