Earphone sleep aiding method and system, earphone and storage medium

Abstract

The invention discloses an earphone sleep aiding method and system, an earphone and a storage medium, and the method comprises the steps: obtaining the physiological data of a user at preset time intervals; determining the state of the user based on the change of the physiological data of the user in the interval; if the user is in the sleep state, outputting the corresponding sleep-aiding audio content based on the sleep state of the user, and enabling the sleep-aiding audio to always fit the sleep process of the user through real-time monitoring and dynamic adjustment, thereby avoiding the problem that the sleep is interfered by playing invalid audio when the user does not fall asleep or playing too strong audio in a deep sleep stage, and improving the user experience. According to the technical scheme, the sleep-aiding accuracy and comfort are remarkably improved, meanwhile, unnecessary power consumption is reduced, the use time of the earphone is prolonged, and more intelligent and efficient sleep-aiding experience is brought to a user.

Description

Technical Field

[0001] This application relates to the field of headphones, and more particularly to a headphone-based sleep aid method, system, headphone, and storage medium. Background Technology

[0002] In modern society, with the fast pace of life, increased work pressure, and widespread use of electronic devices, sleep disorders are becoming increasingly common. Statistics show that more than 50% of the global population experiences varying degrees of sleep problems, such as insomnia, light sleep, and frequent dreams. Long-term sleep disorders not only affect people's physical and mental health but also lead to decreased work efficiency, weakened immunity, and even an increased risk of cardiovascular disease and depression.

[0003] Traditional sleep aids mainly include medication, behavioral therapy, and physical therapy. For example: medication, such as sleeping pills, while effective in the short term, can lead to dependence and side effects with long-term use; behavioral therapy, such as meditation and cognitive behavioral therapy (CBT-I), requires long-term adherence and its effectiveness varies from person to person; physical therapy, such as white noise machines and eye masks, while having no side effects, has limited functionality and cannot be dynamically adjusted according to the user's real-time state.

[0004] In recent years, with the rapid development of smart wearable devices, sleep aid headphones have gradually become an emerging tool for improving sleep quality. However, existing sleep aid headphone products generally suffer from the following problems: Limited functionality: Most sleep aid headphones only provide audio playback and lack monitoring and feedback on the user's physiological state; lack of personalization: They cannot dynamically adjust according to the user's sleep habits and physiological data (such as heart rate and respiratory rate).

[0005] Therefore, existing technologies still need improvement. Summary of the Invention

[0006] The purpose of this application is to realize personalized intelligent sleep aid based on headphones, thereby improving the user's sleep quality.

[0007] The above-mentioned technical objective of this application is achieved through the following technical solution: A method for aiding sleep with headphones, comprising: Collect users' physiological data at predetermined intervals; Determine the user's status based on changes in the user's physiological data within the interval; If the user is asleep, then output the corresponding sleep-aid audio content based on the user's sleep state.

[0008] The solution described in this application, through real-time monitoring and dynamic adjustment, ensures that the sleep-aid audio always matches the user's sleep process, avoiding the problem of playing ineffective audio when the user is not asleep, or playing excessively loud audio during deep sleep, which significantly improves the accuracy and comfort of sleep aids. At the same time, it reduces unnecessary power consumption, extends the usage time of the headphones, and brings users a more intelligent and efficient sleep-aid experience.

[0009] Optionally, the headphone sleep aid method further includes: It pre-stores sleep aid audio corresponding to different sleep states, as well as sleep aid audio playback modes.

[0010] The above-mentioned solution in this application, by pre-storing sleep aid audio and playback modes corresponding to different sleep states, achieves the effect of quickly matching audio resources and playback parameters for the system, reducing response delay, ensuring that appropriate content can be output immediately after recognizing the user's state, improving service timeliness and stability, and providing basic support for precise sleep aid.

[0011] Optionally, the headphone sleep aid method further includes: Obtain the user's historical sleep data and adjust the playback mode of the sleep aid audio based on the user's historical sleep data.

[0012] The above-mentioned solution in this application obtains the user's historical sleep data and adjusts the playback mode of the sleep aid audio accordingly. This achieves the effect of adapting the playback mode to the user's sleep habits, realizing an upgrade from a general service to a personalized service. As the usage time increases, the sleep aid solution becomes more in line with the user's needs, and the sleep aid effect is continuously optimized.

[0013] Optionally, in the aforementioned headphone-based sleep aid method, if the user is in a sleep state, the corresponding sleep aid audio content output based on the user's sleep state includes: Based on the user's physiological data, determine whether the user is a target user; If the user is the target user, then output the corresponding sleep aid audio content based on the target user's sleep state; If the user is not the target user, standard sleep aid audio content will be output.

[0014] The above-mentioned solution in this application distinguishes between target users and non-target users based on physiological data, and outputs corresponding sleep aid audio or standard audio respectively, achieving the effect of balancing personalization and universality. It not only meets the exclusive needs of target users, but also provides effective basic services for non-target users, thus expanding the scope of product application.

[0015] Optionally, the headphone sleep aid method further includes: Get the user's sleep duration. If the user's sleep duration matches the user's preset sleep cycle, output the corresponding wake-up audio.

[0016] The above-mentioned solution in this application obtains the user's sleep duration and outputs a wake-up audio when it meets the preset sleep cycle. This helps the user get up according to the plan, avoids insufficient or excessive sleep, fits the user's schedule, reduces fatigue after waking up, and helps develop regular sleep habits.

[0017] Optionally, in the aforementioned headphone-assisted sleep method, the step of obtaining the user's sleep duration and, if the user's sleep duration matches the user's preset sleep cycle, outputting a wake-up audio includes: Obtain the user's current sleep state and output the corresponding wake-up audio according to the corresponding mode based on the different sleep states.

[0018] The above-mentioned solution in this application obtains the user's current sleep state and outputs wake-up audio according to the corresponding mode, so as to achieve the effect of scientifically waking up according to the depth of sleep. It adopts a gradual wake-up during the deep sleep stage and a gentle wake-up during the light sleep stage, reducing the discomfort of getting up and improving the state after waking up.

[0019] Optionally, the headphone sleep aid method further includes: Based on the user's sleep data over a certain period, a sleep report and sleep suggestions are generated.

[0020] The above-mentioned solution in this application outputs sleep reports and suggestions based on sleep data over a certain period, enabling users to fully understand their own sleep status, providing professional improvement directions, helping users discover sleep problems and proactively make adjustments, fundamentally improving sleep quality, and realizing health management functions.

[0021] In another aspect, this application discloses a headphone sleep aid system, comprising: The data acquisition module is used to acquire the user's physiological data at predetermined intervals; The status determination module is used to determine the user's status based on changes in the user's physiological data within an interval; The audio output module is used to output corresponding sleep-aid audio content based on the user's sleep state if the user is asleep.

[0022] The solution described in this application, through real-time monitoring and dynamic adjustment, ensures that the sleep-aid audio always matches the user's sleep process, avoiding the problem of playing ineffective audio when the user is not asleep, or playing excessively loud audio during deep sleep, which significantly improves the accuracy and comfort of sleep aids. At the same time, it reduces unnecessary power consumption, extends the usage time of the headphones, and brings users a more intelligent and efficient sleep-aid experience.

[0023] In another aspect, this application discloses an earphone, which includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the earphone sleep aid method as described above.

[0024] In another aspect, this application discloses a storage medium storing a computer program capable of being loaded and executing the headphone sleep aid method as described above.

[0025] In summary, this application has at least one of the following beneficial effects: 1. Through real-time monitoring and dynamic adjustment, the sleep aid audio always matches the user's sleep process, avoiding the problem of playing ineffective audio when the user has not fallen asleep, or playing too loud audio during the deep sleep stage to disturb sleep. This significantly improves the accuracy and comfort of sleep aid, while reducing unnecessary power consumption and extending the use time of the headphones, bringing users a smarter and more efficient sleep aid experience. 2. By pre-storing sleep aid audio and playback modes corresponding to different sleep states, the system can quickly match audio resources and playback parameters, reduce response delay, ensure that appropriate content can be output immediately after recognizing the user's state, improve service timeliness and stability, and provide basic support for precise sleep aid. 3. By acquiring users' historical sleep data, the solution adjusts the playback mode of sleep-aid audio accordingly, so that the playback mode can adapt to the user's sleep habits, realizing the upgrade from general service to personalized service. As the usage time increases, the sleep-aid solution becomes more in line with the user's needs, and the sleep-aid effect is continuously optimized. Attached Figure Description

[0026] Figure 1 This is a flowchart of the steps of the headphone sleep aid method described in this application.

[0027] Figure 2 This is a structural block diagram of the headphone sleep aid system described herein. Detailed Implementation

[0028] The present application will be further described in detail below with reference to the accompanying drawings.

[0029] This application discloses a method for using headphones to aid sleep, see embodiments thereof. Figure 1 Among them are: S1. Collect the user's physiological data at predetermined intervals; S2. Determine the user's status based on changes in the user's physiological data within the interval; S3. If the user is asleep, output the corresponding sleep aid audio content based on the user's sleep state.

[0030] The solution described in this application, through real-time monitoring and dynamic adjustment, ensures that the sleep-aid audio always matches the user's sleep process, avoiding the problem of playing ineffective audio when the user is not asleep, or playing excessively loud audio during deep sleep, which significantly improves the accuracy and comfort of sleep aids. At the same time, it reduces unnecessary power consumption, extends the usage time of the headphones, and brings users a more intelligent and efficient sleep-aid experience.

[0031] In practice, the first step is to embed physiological sensors, such as heart rate sensors, blood oxygen monitoring modules, and EEG electrodes, into the earphones and set a predetermined time interval (which can be customized by the user in the accompanying app). At each of these intervals, the sensors automatically collect the user's physiological data, which is then transmitted in real-time via Bluetooth to the earphone's main control chip. The main control chip analyzes this data from N consecutive data points, such as three, by comparing trends: if the heart rate drops from 70 beats per minute to 55 beats per minute and stabilizes, and the theta wave proportion in the EEG increases to over 40%, the user is determined to be in light sleep; if the heart rate further drops to 45 beats per minute and the delta wave proportion exceeds 60%, the user is determined to be in deep sleep. Once the system confirms that the user has entered a sleep state, it immediately retrieves the corresponding audio from the local storage module: during the light sleep stage, it plays 40 decibels of white noise from a stream (frequency concentrated in 200-500Hz); during the deep sleep stage, it switches to 30 decibels of low-frequency rain sound (frequency 100-300Hz). The audio playback is gradually weakened, decreasing by 5 decibels every 10 minutes, until it automatically pauses after the user enters the REM sleep stage.

[0032] Optionally, the headphone sleep aid method further includes: It pre-stores sleep aid audio corresponding to different sleep states, as well as sleep aid audio playback modes.

[0033] The above-mentioned solution in this application, by pre-storing sleep aid audio and playback modes corresponding to different sleep states, achieves the effect of quickly matching audio resources and playback parameters for the system, reducing response delay, ensuring that appropriate content can be output immediately after recognizing the user's state, improving service timeliness and stability, and providing basic support for precise sleep aid.

[0034] During implementation, a two-tier storage architecture needs to be built: commonly used audio is stored locally in the headphones' Flash memory, and an extended audio library is stored on the cloud server. Stored content is categorized by sleep state: light sleep includes white noise and soft music (such as piano sonatas), with a playback mode of "continuous loop + volume gradually decreasing"; deep sleep includes low-frequency sound waves and natural low frequencies (such as deep-sea ambient sounds), with a playback mode of "single playback + timed shutdown"; REM sleep has no audio output, only sensor monitoring. Playback mode parameters are refined to: the initial volume value for light sleep is set to 60% of the user's normal hearing threshold, decreasing by 10% every 5 minutes; the volume for deep sleep is fixed at 30% of the hearing threshold, with a playback duration not exceeding 2 hours. Users can manually add custom audio via the app. After uploading, the system automatically analyzes the audio spectrum, categorizes it into the corresponding sleep state folder, and generates matching playback parameters (e.g., the default loop count for soothing audio is set to 5 times).

[0035] Optionally, the headphone sleep aid method further includes: Obtain the user's historical sleep data and adjust the playback mode of the sleep aid audio based on the user's historical sleep data.

[0036] The above-mentioned solution in this application obtains the user's historical sleep data and adjusts the playback mode of the sleep aid audio accordingly. This achieves the effect of adapting the playback mode to the user's sleep habits, realizing an upgrade from a general service to a personalized service. As the usage time increases, the sleep aid solution becomes more in line with the user's needs, and the sleep aid effect is continuously optimized.

[0037] In practice, the earphone's accompanying app needs to request user data storage permissions. For example, it should automatically summarize the previous night's sleep data (including the duration of each stage and sensitivity to audio—such as the number of volume adjustments) at 5 AM every day and upload it to a cloud database. Analyzing historical data over a certain number of consecutive days: if it's found that a user needs to play 20 minutes of alpha wave music to fall asleep between 11:00 PM and 11:30 PM from Monday to Friday, and that their sleep time is later at 12:30 AM on weekends, with a better response to jazz music, the playback mode will be automatically adjusted: alpha wave music will be automatically pushed at 11:00 PM on weekdays, with the initial volume increased by 10% compared to the default value; at 12:30 AM on weekends, jazz music will be switched, with the playback duration extended to 30 minutes. The adjusted parameters are synchronized to the earphones in real time. When the user opens the app, they will receive a notification that "Sleep habits have been updated, audio scheme has been optimized," and can manually roll back to the default mode. Every 30 days, the system will retrain the model to ensure that the playback mode matches the user's latest sleep habits.

[0038] Optionally, in the aforementioned headphone-based sleep aid method, if the user is in a sleep state, the corresponding sleep aid audio content output based on the user's sleep state includes: Based on the user's physiological data, determine whether the user is a target user; If the user is the target user, then output the corresponding sleep aid audio content based on the target user's sleep state; If the user is not the target user, standard sleep aid audio content will be output.

[0039] The above-mentioned solution in this application distinguishes between target users and non-target users based on physiological data, and outputs corresponding sleep aid audio or standard audio respectively, achieving the effect of balancing personalization and universality. It not only meets the exclusive needs of target users, but also provides effective basic services for non-target users, thus expanding the scope of product application.

[0040] Upon first use, user registration is required, and baseline physiological characteristics (such as resting heart rate, ear temperature, and EEG baseline data) are collected and encrypted. For example, during use, after each data collection, the sensor compares it to the baseline characteristics: if the heart rate deviation is within ±5 beats / minute and the ear temperature fluctuation is less than 0.5℃, the user is identified as a target user; if the deviation exceeds 15%, the user is identified as a non-target user. In target user scenarios, the system calls their dedicated audio library (such as ocean wave sounds marked "valid" in the user's history) and enables personalized parameters (such as the user's preferred initial volume of 50 dB). In non-target user scenarios, a standard solution is automatically triggered: playing 35 dB of general white noise (clinically proven effective for 80% of the population), with the playback mode fixed at "stop after 1 hour of looping." To protect privacy, non-target user data is only temporarily stored locally and cannot access the target user's personalized settings. The standard audio library is updated quarterly based on user feedback.

[0041] Optionally, the headphone sleep aid method further includes: Get the user's sleep duration. If the user's sleep duration matches the user's preset sleep cycle, output the corresponding wake-up audio.

[0042] The above-mentioned solution in this application obtains the user's sleep duration and outputs a wake-up audio when it meets the preset sleep cycle. This helps the user get up according to the plan, avoids insufficient or excessive sleep, fits the user's schedule, reduces fatigue after waking up, and helps develop regular sleep habits.

[0043] During implementation, users need to set a sleep cycle in the app (e.g., 7 hours, 9 hours, with separate settings for weekdays / weekends). The system breaks down the cycle into three parts: "sleep preparation + sleep duration + wake-up buffer." The headphones have a built-in real-time clock module. When the user lies down, the system starts timing when the user's supine position is detected by an infrared sensor. If the user sets a 7-hour sleep cycle and falls asleep at 11 PM, the system will compare the actual sleep duration (7 hours) with the preset cycle at 6 AM the next day. If the conditions are met, the wake-up process will be initiated. The wake-up audio is retrieved locally, initially playing 30 decibels of birdsong (frequency 1000-2000Hz), increasing by 5 decibels every 30 seconds, while a soft white light illuminates the headphone's touch panel. If the user does not remove the headphones within 5 minutes, the system automatically sends a vibration reminder (intensity increasing from weak to strong, with 20-second intervals) to ensure the user wakes up promptly after the preset cycle ends.

[0044] Optionally, in the aforementioned headphone-assisted sleep method, the step of obtaining the user's sleep duration and, if the user's sleep duration matches the user's preset sleep cycle, outputting a wake-up audio includes: Obtain the user's current sleep state and output the corresponding wake-up audio according to the corresponding mode based on the different sleep states.

[0045] The above-mentioned solution in this application obtains the user's current sleep state and outputs wake-up audio according to the corresponding mode, so as to achieve the effect of scientifically waking up according to the depth of sleep. It adopts a gradual wake-up during the deep sleep stage and a gentle wake-up during the light sleep stage, reducing the discomfort of getting up and improving the state after waking up.

[0046] In practice, 5 minutes before the wake-up trigger, the system initiates a secondary confirmation of sleep status: real-time physiological data is collected through sensors. If the proportion of alpha waves in the brainwave rises to over 30% and the heart rate fluctuation increases by 15%, it is determined to be the late stage of light sleep; if delta waves still account for over 50% and the heart rate remains stable, it is determined to be the deep sleep stage. For users in the late stage of light sleep, the wake-up audio starts with a 40-decibel morning melody (such as a violin concerto) and plays continuously for 2 minutes. For users in the deep sleep stage, a 1-minute low-frequency guiding sound (below 200Hz) is played first, gradually transitioning to mid-frequency birdsong, with the volume slowly increasing from 20 decibels to 50 decibels, simultaneously accompanied by bone conduction vibration from the headphones (frequency 50Hz, increasing every 10 seconds). If the user manually pauses during the wake-up process, the system records this interruption event, includes it in the next day's sleep report, and adjusts the wake-up intensity in the next session (e.g., increasing the volume by 10%).

[0047] Optionally, the headphone sleep aid method further includes: Based on the user's sleep data over a certain period, a sleep report and sleep suggestions are generated.

[0048] The above-mentioned solution in this application outputs sleep reports and suggestions based on sleep data over a certain period, enabling users to fully understand their own sleep status, providing professional improvement directions, helping users discover sleep problems and proactively make adjustments, fundamentally improving sleep quality, and realizing health management functions.

[0049] The system automatically generates a sleep report every Monday at 8:00 AM, with a data collection period set for 7 days. The report includes: a daily sleep / wake cycle curve, a pie chart showing the percentage of each sleep stage (light sleep should account for 45%-55%, and deep sleep 20%-25% for a healthy standard), and an audio usage effectiveness score (e.g., "Audio during deep sleep reduced awakenings by 3 times"). The recommendations section uses a tiered mechanism: basic recommendations (e.g., "Insufficient deep sleep this week; recommend falling asleep before 10:30 PM"), advanced recommendations (e.g., "Sensitivity to low-frequency audio detected; recommend trying thunderstorm sounds below 400Hz"), and professional recommendations (e.g., "Consult a sleep physician if REM sleep abnormalities occur for 3 consecutive weeks"). The report is delivered to the app in a combined text and image format, supports PDF export, and uses color coding for data visualization (green for normal, yellow for warning, red for abnormal), along with anonymous comparative data with users of the same age group (e.g., "Your deep sleep duration exceeds 60% of your peers").

[0050] In some possible embodiments of this application, the headphones can also collect ambient sounds in real time through a built-in microphone to determine the ambient noise level, such as a noisy street or a quiet bedroom; simultaneously, it can use the phone's location function to obtain the user's geographical location, determining whether the user is in a city, countryside, hotel, or at home. This information is transmitted to the headphones' processing system in real time and, together with the user's physiological data, serves as the basis for adjusting the sleep aid strategy. Regarding the adjustment of sleep-aid audio, when the system detects that the user is in a noisy environment such as a city center, it will automatically increase the volume of the sleep-aid audio, usually 10-15% higher than in a quiet environment. It will prioritize white noise or natural sounds with more prominent low frequencies, such as the sound of heavy rain or waterfalls, using their sound wave characteristics to cancel out high-frequency noise in the environment and help the user block out distractions to fall asleep. If the user is in a quiet environment such as a rural area, the audio volume will be reduced to 30-40 decibels, and gentle natural sounds such as insect chirping or a breeze will be selected to avoid excessive volume affecting sleep. The solution is also adjusted accordingly for different geographical locations. When the system detects that the user is in a hotel, considering that the unfamiliar environment may make it difficult for the user to fall asleep, it will play more soothing sleep-inducing audio, such as long-looping piano music, with a playback duration 20% longer than at home, while maintaining stable audio volume to reduce discomfort caused by environmental changes. If the user is at home, the system will automatically match the most suitable audio combination based on previously recorded characteristics of the home environment, such as the usual slight noise at night. During the wake-up process, adjustments are made based on the user's geographical location, time zone, and ambient brightness. If a user is traveling across time zones, the system calculates the sleep cycle according to the local time zone. When it is time to wake up, if it is early morning and the ambient brightness is low, the wake-up audio starts with a gentle birdsong at 20 decibels and gradually increases to 50 decibels. If it is daytime and the ambient brightness is high, the initial volume is set to 40 decibels to accelerate the volume increase and ensure that the user can wake up on time and that the wake-up process is more comfortable. In addition, the system records users' sleep data in different environments and geographical locations, such as differences in sleep onset time in cities and rural areas, and responses to different audio. The regularly generated sleep reports analyze the impact of these factors on sleep and provide targeted suggestions, such as "in an urban environment, using low-frequency white noise can shorten sleep onset time by 15 minutes," to help users better utilize environmental information to improve sleep.

[0051] Another embodiment of this application discloses a headphone sleep aid system, see reference. Figure 2 Among them are: The data acquisition module 100 is used to acquire the user's physiological data at predetermined intervals; The state determination module 200 is used to determine the user's state based on changes in the user's physiological data within an interval; The audio output module 300 is used to output corresponding sleep-aid audio content based on the user's sleep state if the user is in a sleep state.

[0052] The functions of each module of the system described above in this application have been described in detail in the method steps, so they will not be repeated here.

[0053] In some possible embodiments of this application, the system further includes: The pre-storage module is used to pre-store sleep aid audio corresponding to different sleep states, as well as sleep aid audio playback modes.

[0054] In some possible embodiments of this application, the system further includes: The adjustment module is used to acquire the user's historical sleep data and adjust the playback mode of the sleep aid audio based on the user's historical sleep data.

[0055] In some possible embodiments of this application, the audio output module includes: The target user determination unit is used to determine whether a user is a target user based on the user's physiological data. The target user audio output unit outputs corresponding sleep-aid audio content based on the target user's sleep state if the user is the target user. Non-target user audio output unit: If the user is not a non-target user, it outputs standard sleep aid audio content.

[0056] In some possible embodiments of this application, the system further includes: The wake-up module is used to obtain the user's sleep duration. If the user's sleep duration matches the user's preset sleep cycle, the corresponding wake-up audio will be output.

[0057] In some possible embodiments of this application, the wake-up module includes: The wake-up unit is used to obtain the user's current sleep state and output the corresponding wake-up audio according to the corresponding mode based on the different sleep states.

[0058] In some possible embodiments of this application, the system further includes: The report output module is used to output sleep reports and sleep suggestions based on the user's sleep data over a certain period.

[0059] Another embodiment of this application discloses an earphone, comprising a memory and a processor. The memory stores a computer program that can be loaded by the processor and execute the earphone sleep aid method. When loaded, the program performs the following steps: Collect users' physiological data at predetermined intervals; Determine the user's status based on changes in the user's physiological data within the interval; If the user is asleep, then output the corresponding sleep-aid audio content based on the user's sleep state.

[0060] It pre-stores sleep aid audio corresponding to different sleep states, as well as sleep aid audio playback modes.

[0061] Obtain the user's historical sleep data and adjust the playback mode of the sleep aid audio based on the user's historical sleep data.

[0062] Based on the user's physiological data, determine whether the user is a target user; If the user is the target user, then output the corresponding sleep aid audio content based on the target user's sleep state; If the user is not the target user, standard sleep aid audio content will be output.

[0063] Get the user's sleep duration. If the user's sleep duration matches the user's preset sleep cycle, output the corresponding wake-up audio.

[0064] Obtain the user's current sleep state and output the corresponding wake-up audio according to the corresponding mode based on the different sleep states.

[0065] Based on the user's sleep data over a certain period, a sleep report and sleep suggestions are generated.

[0066] Another embodiment of this application discloses a storage medium storing a computer program capable of being loaded and executing the headphone sleep aid method. When loaded, the program performs the following steps: Collect users' physiological data at predetermined intervals; Determine the user's status based on changes in the user's physiological data within the interval; If the user is asleep, then output the corresponding sleep-aid audio content based on the user's sleep state.

[0067] It pre-stores sleep aid audio corresponding to different sleep states, as well as sleep aid audio playback modes.

[0068] Obtain the user's historical sleep data and adjust the playback mode of the sleep aid audio based on the user's historical sleep data.

[0069] Based on the user's physiological data, determine whether the user is a target user; If the user is the target user, then output the corresponding sleep aid audio content based on the target user's sleep state; If the user is not the target user, standard sleep aid audio content will be output.

[0070] Get the user's sleep duration. If the user's sleep duration matches the user's preset sleep cycle, output the corresponding wake-up audio.

[0071] Obtain the user's current sleep state and output the corresponding wake-up audio according to the corresponding mode based on the different sleep states.

[0072] Based on the user's sleep data over a certain period, a sleep report and sleep suggestions are generated.

[0073] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0074] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0075] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0076] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0077] This embodiment provides a computer-readable storage medium. Since the computer program stored therein can implement the various steps of the aforementioned embodiments after running on a processor, it can achieve the same technical effect as the aforementioned embodiments. The principle analysis can be referred to the relevant steps described above, and will not be repeated here.

[0078] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure and principles of this application should be covered within the scope of protection of this application.

Claims

1. A method for aiding sleep with headphones, characterized in that, include: Collect users' physiological data at predetermined intervals; Determine the user's status based on changes in the user's physiological data within the interval; If the user is asleep, then output the corresponding sleep-aid audio content based on the user's sleep state.

2. The headphone-assisted sleep method according to claim 1, characterized in that, The method further includes: It pre-stores sleep aid audio corresponding to different sleep states, as well as sleep aid audio playback modes.

3. The headphone-assisted sleep method according to claim 2, characterized in that, The method further includes: Obtain the user's historical sleep data and adjust the playback mode of the sleep aid audio based on the user's historical sleep data.

4. The headphone-assisted sleep method according to claim 1, characterized in that, If the user is asleep, the corresponding sleep aid audio content will be output based on the user's sleep state, including: Based on the user's physiological data, determine whether the user is a target user; If the user is the target user, then output the corresponding sleep aid audio content based on the target user's sleep state; If the user is not the target user, standard sleep aid audio content will be output.

5. The headphone-assisted sleep method according to claim 1, characterized in that, The method further includes: Get the user's sleep duration. If the user's sleep duration matches the user's preset sleep cycle, output the corresponding wake-up audio.

6. The headphone-assisted sleep method according to claim 5, characterized in that, The steps for obtaining the user's sleep duration and outputting a wake-up audio if the user's sleep duration matches the user's preset sleep cycle include: Obtain the user's current sleep state and output the corresponding wake-up audio according to the corresponding mode based on the different sleep states.

7. The headphone-assisted sleep method according to claim 1, characterized in that, The method further includes: Based on the user's sleep data over a certain period, a sleep report and sleep suggestions are generated.

8. A headphone sleep aid system, characterized in that, include: The data acquisition module is used to acquire the user's physiological data at predetermined intervals; The status determination module is used to determine the user's status based on changes in the user's physiological data within an interval; The audio output module is used to output corresponding sleep-aid audio content based on the user's sleep state if the user is asleep.

9. An earphone, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed as described in any one of claims 1-7.

10. A storage medium, characterized in that, The device stores a computer program capable of being loaded and executing the headphone sleep aid method as described in any one of claims 1-7.

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