Sleep induction method, device and equipment
By acquiring sleep status and adjusting parameters in real time, and releasing sleep induction information, the problem of difficulty falling asleep when wearing a sleep apnea machine is solved, and flexible induction and automatic adjustment during sleep are achieved, thus improving sleep quality and efficiency.
Patent Information
- Application Number
- CN202511748136.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-26
- Publication Date
- 2026-01-02
AI Technical Summary
Existing sleep apnea machines cannot effectively solve the problem of users having difficulty falling asleep while wearing a mask. Traditional environmental induction methods cannot be flexibly changed during sleep, resulting in poor sleep quality and efficiency.
By acquiring the first sleep stage state in real time during sleep, obtaining sleep adjustment parameters, and releasing corresponding sleep induction information, including auditory, visual, and electrical stimulation induction information, flexible changes and automatic adjustments in sleep induction can be achieved.
It improves sleep quality and efficiency during sleep, automatically adjusts sleep induction information according to changes in sleep state, and responds promptly to scenarios such as difficulty falling asleep, achieving timeliness and automation of sleep induction.
Smart Images
Figure CN121243581A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of sleep induction technology, and in particular to a sleep induction method, apparatus and device. Background Technology
[0002] In the field of sleep medical devices, sleep apnea machines are used to treat sleep apnea syndrome. They work by providing a continuous positive pressure airflow into the user's upper airway through a mask, preventing upper airway collapse and obstruction during sleep. While modern sleep apnea machines can dynamically adjust and provide appropriate therapeutic pressure to maintain airway patency based on monitored respiratory rate and airflow changes, they cannot solve the problem of insomnia. In fact, wearing the mask and experiencing the impact of airflow can even cause difficulty falling asleep.
[0003] Therefore, in related technologies, when a user lies down to prepare for sleep, the sound and brightness in the environment are usually adjusted to induce sleep and thus help the user fall asleep faster. For example, white noise is released in the environment, and the brightness of various devices (such as the white noise-releasing device) is adjusted to the lowest level to reduce the overall brightness of the environment, thereby achieving sleep induction. However, this traditional and fixed environmental induction method cannot effectively solve the sleep onset problem in the application scenario of sleep apnea machines. Summary of the Invention
[0004] This application provides a sleep induction method, apparatus, and device, enabling flexible changes in sleep induction during the sleep process, which is beneficial for improving the overall sleep quality and efficiency. The technical solution is as follows: On one hand, embodiments of this application provide a sleep induction detection method, the method comprising: The first sleep stage state is acquired in real time during sleep, which includes wakefulness, light sleep, light sleep, deep sleep, and REM sleep. If the sleep induction requirements are met in the first sleep stage, obtain sleep adjustment parameters; Based on the sleep adjustment parameters, sleep induction information is released; wherein, the sleep induction information is used to induce sleep during the sleep process.
[0005] On the other hand, embodiments of this application provide a sleep induction device for implementing the above-described sleep induction method, the device comprising: The sleep monitoring module is used to obtain the state of the first sleep stage in real time during sleep. The sleep stages include the awake stage, light sleep stage, light sleep stage, deep sleep stage, and REM sleep stage. The sleep induction module is used to obtain sleep adjustment parameters when the sleep induction requirements are met in the first sleep stage state; A sleep control module is used to release sleep induction information based on the sleep adjustment parameters; wherein the sleep induction information is used to induce sleep during the sleep process.
[0006] In another aspect, embodiments of this application provide a computer device, which includes a processor and a memory, wherein the memory stores a computer program, which is loaded and executed by the processor to implement the above-described sleep induction method.
[0007] In another aspect, embodiments of this application provide a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described sleep induction method.
[0008] In another aspect, embodiments of this application provide a computer program product that, when the computer program product is run, causes a computer device to execute the aforementioned sleep induction method.
[0009] Compared with the prior art, the technical solution provided in this application can bring the following beneficial effects: (1) By obtaining the first sleep stage state in real time during sleep, the sleep adjustment parameters are determined, and then the sleep induction information is released. That is, the sleep induction information will change with the change of the first sleep stage state during sleep, so that the sleep induction can be flexibly changed during sleep, which is conducive to improving the overall sleep quality and sleep efficiency of the sleep process. (2) The sleep induction information is changed in real time during sleep. When the user is in a sleep state and cannot move his hands, the sleep induction information is automatically adjusted, thus realizing the automation of sleep induction during sleep. (3) Sleep induction is performed when the sleep induction requirement is met in the first sleep stage. That is, the sleep induction is not based on the change of sleep stage. Even if the sleep stage does not change during sleep, sleep induction can still be performed, making sleep induction more timely. Attached Figure Description
[0010] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a schematic diagram of a sleep induction system provided in one embodiment of this application; Figure 2 This is a flowchart of a sleep induction method provided in one embodiment of this application; Figure 3 This is a block diagram of a sleep induction device provided in one embodiment of this application; Figure 4 This is a block diagram of a sleep induction device provided in another embodiment of this application. Detailed Implementation
[0011] Please refer to Figure 1 The diagram illustrates a sleep induction system according to an embodiment of this application. The sleep induction system may include a ventilator 10 and a computer device 20.
[0012] A ventilator 10 refers to a machine used to assist or replace spontaneous breathing in the human body. In this embodiment, the ventilator 10 has a sleep monitoring function. Optionally, the ventilator 10 includes a bioelectrical monitoring unit, through which the ventilator 10 acquires bioelectrical information and sends the bioelectrical information to a computer device 20.
[0013] Computer device 20 refers to a device used for sleep induction. Exemplarily, computer device 20 can be an electronic device such as a microcomputer, mobile phone, tablet computer, backend server, or PC (Personal Computer) installed on the ventilator 10; this embodiment does not limit the scope of the application. In this embodiment, computer device 20 acquires the first sleep stage state in real time based on the aforementioned bioelectrical information; further, if the first sleep stage state meets the sleep induction requirements, it acquires sleep adjustment parameters; further, based on the sleep adjustment parameters, it releases sleep induction information. The sleep induction information is used to induce sleep during sleep.
[0014] Optionally, the ventilator 10 and the computer device 20 communicate via a network.
[0015] It should be noted that the above description of the sleep induction system is merely exemplary and illustrative. In practical applications, the ventilator 10 can be replaced with any device that has sleep monitoring functionality, and this application embodiment does not limit this. Of course, in other possible implementations, the ventilator 10 can also be replaced with a component in the computer device 20 that has sleep monitoring functionality.
[0016] Please refer to Figure 2 The diagram illustrates a flowchart of a sleep induction method provided in one embodiment of this application. The method is applied to... Figure 1 The computer device 20 in the sleep induction system shown. The method may include the following steps (201-203): Step 201: Acquire the state of the first sleep stage in real time during sleep.
[0017] In this embodiment of the application, during sleep induction, the computer device acquires the first sleep stage state in real time during the sleep process. The first sleep stage state refers to the current sleep stage state during the sleep process. For example, the sleep process refers to the process of the body being in a lying-down position.
[0018] Optionally, in this embodiment, the computer device acquires bioelectrical information in real time during sleep through a bioelectrical monitoring unit; further, the bioelectrical information is processed for sleep stage segmentation to obtain the first sleep stage state. Optionally, the bioelectrical detection unit is installed on the ventilator.
[0019] For example, the bioelectric detection unit includes an electroencephalogram (EEG) monitoring unit and an electrooculogram (EOG) monitoring unit. The EEG monitoring unit monitors the activity of neurons in the brain to generate EEG information. For example, the EEG monitoring unit includes a first electrode attached to the head (e.g., the temple), through which a computer device monitors the activity of neurons in the brain to obtain EEG information (including an electroencephalogram). The EOG monitoring unit monitors eye movements to generate EOG information. For example, the EOG monitoring unit includes a second electrode attached around the eyes, through which a computer device monitors the potential difference between the cornea and retina during eye movements to obtain EOG information (including an electrooculogram).
[0020] Optionally, the first sleep stage state is used to indicate the changes in sleep stages during sleep, with the current time as the endpoint. In the embodiments of this application, sleep stages include wakefulness, light sleep, light sleep, deep sleep, and REM sleep.
[0021] For example, a computer device performs sleep stage processing on electroencephalogram (EEG) and electrooculogram (EOG) information using a pre-set sleep stage algorithm to obtain the first sleep stage state.
[0022] For example, the awake phase can be referred to as the W phase. Computer devices use sleep staging algorithms to monitor mixed frequency activity of alpha waves and low voltage based on electroencephalogram (EEG) information, thereby determining whether the sleep process is in the awake phase. For example, the awake phase can be understood as the beginning and end of the sleep process.
[0023] For example, the light sleep stage can be called N1 stage. The computer device uses a sleep staging algorithm to detect the disappearance of alpha waves based on EEG information and their replacement by low-voltage and mixed-frequency theta waves, thereby determining that the sleep process is in the light sleep stage.
[0024] For example, the light sleep stage can be called N2 stage. The computer device uses a sleep staging algorithm to monitor brief bursts of σ rhythms based on EEG information, as well as a high peak negative wave followed by a positive slow wave, and thus determines that the sleep process is in the light sleep stage.
[0025] For example, the deep sleep stage can be called N3 stage. Computer devices use sleep staging algorithms to monitor high-amplitude slow waves based on electroencephalogram (EEG) information, thereby determining that the sleep process is in the deep sleep stage.
[0026] For example, the REM sleep period can be called the R stage. The computer device uses a sleep staging algorithm to detect sawtooth waves similar to the N1 stage and exhibiting "desynchronization" based on EEG information, and detects rapid eye movements based on EEG information, thereby determining that the sleep process is in the REM sleep period.
[0027] Step 202: Under the condition that the sleep induction requirements are met in the first sleep stage, obtain the sleep adjustment parameters.
[0028] In this embodiment, after obtaining the first sleep state, if the computer device finds that the first sleep state meets the sleep induction requirements, it obtains sleep adjustment parameters. These sleep adjustment parameters are used to adjust the sleep induction method during the sleep process.
[0029] Optionally, sleep adjustment parameters include sleep induction information, induction duration, induction information intensity, and induction timing. For example, sleep induction information includes, but is not limited to, at least one of the following: auditory induction information, visual induction information, and electrical stimulation induction information. For instance, auditory induction information may be rhythmic ticking, pink noise, or white noise; visual induction information may be blue light of a specific wavelength and illuminance; and electrical stimulation induction information may be transcranial microcurrent stimulation or vagus nerve auricular branch stimulation.
[0030] Optionally, in this embodiment, the aforementioned sleep induction requirements include, but are not limited to, at least one of the following: the duration of the sleep latency is greater than a first threshold, the ratio between deep sleep and total sleep duration is less than a second threshold, and the duration of wakefulness during non-sleep latency periods is greater than a third threshold. Here, sleep latency refers to the first wakefulness period in the aforementioned sleep process. Exemplarily, the first, second, and third thresholds are all preset thresholds, and can be flexibly set and adjusted according to actual conditions; this embodiment does not limit this. It should be noted that the first threshold is greater than the second threshold. For example, the first threshold is 30 minutes, and the second threshold is 5 minutes.
[0031] Step 203: Based on sleep adjustment parameters, release sleep-inducing information.
[0032] In this embodiment, after obtaining the aforementioned sleep adjustment parameters, the computer device releases sleep induction information based on these parameters. The sleep induction information is used to induce sleep during sleep.
[0033] Optionally, the sleep adjustment parameters include sleep induction information, induction duration, induction information intensity, and induction timing. Based on the sleep adjustment parameters, the computer device releases sleep induction information at the induction timing with the induction information intensity and duration. Taking auditory induction information as an example, if the sleep adjustment parameter is "immediately play 30 minutes of 0.5Hz rhythmic ticking sound", then the sleep induction information is rhythmic ticking sound, the induction duration is 30 minutes, the induction information intensity is 0.5Hz, and the induction timing is the current time.
[0034] For example, the sleep adjustment parameters mentioned above also include operating mode adjustment parameters for the ventilator. The computer device adjusts the operating mode of the ventilator based on the sleep adjustment parameters to induce sleep with the assistance of the ventilator.
[0035] Optionally, in this embodiment, when the current time is a preset wake-up time, the computer device releases wake-up stimulus information. This wake-up stimulus information is used to indicate the end of the sleep process. Exemplarily, the preset wake-up time is a time set by the user, and this preset wake-up time can be flexibly set and adjusted according to actual conditions, such as 7:00 am, 7:30 am, 8:00 am, etc., and this embodiment does not limit this. Exemplarily, the wake-up stimulus information can be auditory information, visual information, electrical stimulation information, etc., and this embodiment does not limit this.
[0036] In summary, the technical solution provided in this application determines sleep adjustment parameters by acquiring the first sleep stage state in real time during sleep, thereby releasing sleep induction information. This means that the sleep induction information changes with the first sleep stage state during sleep, allowing for flexible changes in sleep induction, which is beneficial for improving overall sleep quality and efficiency. Furthermore, by changing the sleep induction information in real time during sleep, and automatically adjusting it when the user is unable to move while asleep, the sleep induction process is automated. Moreover, sleep induction is initiated when the first sleep stage state meets the sleep induction requirements; that is, sleep induction is not determined based on changes in the sleep stage. Sleep induction can still be initiated even if the sleep stage remains unchanged, making sleep induction more timely.
[0037] In addition, by processing the bioelectrical information during sleep through sleep stages, the first sleep stage state can be obtained. Since the bioelectrical information is information that can be obtained in real time during sleep, it is beneficial to realize real-time insomnia induction during sleep and improve the timeliness of insomnia induction.
[0038] In addition, it can meet the sleep induction needs in three scenarios: difficulty falling asleep, poor sleep quality (i.e., the ratio between deep sleep and total sleep duration is less than the second threshold), and prolonged awakening during sleep. In other words, sleep induction can be performed in multiple scenarios, which is conducive to further improving the overall sleep quality and sleep efficiency during the sleep process.
[0039] In addition, when the current time is the preset wakefulness time, it releases wakefulness stimuli to indicate the end of the sleep process, and has a wake-up function while inducing sleep, thus achieving functional diversification.
[0040] The following is a detailed introduction to how to obtain sleep adjustment parameters.
[0041] In an exemplary embodiment, step 202 above includes the following steps: 1. Obtain static user profiles based on physiological and personality characteristics.
[0042] In this embodiment of the application, when acquiring sleep adjustment parameters, the computer device acquires a static user profile constructed based on physiological and personality characteristics.
[0043] Physiological characteristics are used to describe changes in sleep stages and biometric information during historical sleep processes. Historical sleep processes refer to more than one sleep process preceding the aforementioned sleep processes. For example, changes in sleep stages include, but are not limited to, at least one of the following: the proportion of each sleep stage in the historical sleep process, the average duration of sleep latency, the number of awakenings, and the average number of awakenings per hour. For example, changes in biometric information include, but are not limited to, at least one of the following: electroencephalogram (EEG) fluctuations, electrooculogram (EOG) fluctuations, the number of apneas, and the number of hypopnea episodes induced by mechanical ventilation.
[0044] Personality traits are used to describe sensitivity to more than one type of sleep-inducing information. For example, these personality traits are obtained through a questionnaire survey.
[0045] 2. Based on the static user profile, and combined with the target sleep period indicated by the sleep state, construct the sleep user profile.
[0046] In this embodiment of the application, after obtaining the aforementioned static user profile, the computer device constructs a sleep user profile based on the static user profile and in conjunction with the target sleep period indicated by the sleep state. The target sleep period is the current sleep period.
[0047] Optionally, in this embodiment, the computer device obtains a first dynamic user profile based on the target sleep period and constructs a second dynamic user profile based on real-time physiological characteristics. Furthermore, the static user profile, the first dynamic user profile, and the second dynamic user profile are fused to obtain a sleep user profile. The sleep period physiological characteristics are used to describe the changes in biological information during the target sleep period in historical sleep processes; the real-time physiological characteristics are used to describe the changes in biological information during the aforementioned sleep process.
[0048] 3. Obtain sleep adjustment parameters based on sleep user profiles.
[0049] In this embodiment of the application, after obtaining the above-mentioned sleep user profile, the computer device obtains sleep adjustment parameters based on the sleep user profile.
[0050] Optionally, in this embodiment, the computer device inputs the sleep user profile into a pre-trained sleep induction model to obtain sleep adjustment parameters. These sleep adjustment parameters include sleep induction information, information duration, information intensity, and information timing.
[0051] For example, the sleep induction model is a supervised learning model. Optionally, in this embodiment, the computer device acquires a second sleep state after the release of the aforementioned sleep induction information has ended; further, if the second sleep state does not meet the aforementioned sleep induction requirements, a training sample for the sleep induction model is generated using the sleep user profile as sample input information and the sleep adjustment parameters as sample label information. The training sample includes the sample input information and the sample label information. For example, the second sleep state is used to indicate the changes in the sleep period received after the release of the aforementioned sleep induction information.
[0052] In summary, the technical solution provided in this application constructs a sleep user profile by combining a static user profile with the target sleep period indicated by the sleep state. Then, sleep adjustment parameters are obtained based on the user profile. When inducing sleep, both user characteristics and real-time sleep period are considered simultaneously, which helps improve the accuracy of sleep induction. Furthermore, the static user profile is constructed based on physiological and personality characteristics. That is, when constructing the static user profile, the user's own sleep patterns and sensitivity to sleep induction information are considered simultaneously. This facilitates the subsequent identification of sleep induction information with low sensitivity that matches the user's own sleep patterns, further improving the accuracy of sleep induction and ultimately enhancing the overall sleep quality and efficiency during the sleep process.
[0053] Furthermore, a first dynamic user profile is constructed based on the physiological characteristics of the target sleep stage, and a second dynamic user profile is constructed based on real-time physiological characteristics. The static user profile, the first dynamic user profile, and the second dynamic user profile are then fused to obtain the sleep user profile. This fusion of multi-dimensional user profiles accurately constructs the user profile from both static and dynamic perspectives, improving the accuracy of the sleep user profile and consequently the accuracy of sleep induction. Moreover, the first dynamic user profile characterizes the physiological characteristics of the target sleep stage, making subsequent sleep induction more targeted to the target sleep stage. The second dynamic user profile characterizes the real-time physiological characteristics of the current sleep process, allowing subsequent sleep induction to be flexibly adjusted for the current sleep process, which helps improve the accuracy of insomnia induction and, consequently, the overall sleep quality and efficiency.
[0054] Furthermore, obtaining sleep adjustment parameters through a pre-trained sleep induction model is simple, time-saving, and improves sleep induction efficiency. Additionally, after the release of sleep induction information, a training sample for the sleep induction model is generated using the sleep user profile as input and the sleep adjustment parameters as label information. During application, the sleep induction model is continuously trained, enabling it to obtain appropriate and accurate sleep adjustment parameters even in the face of subtle changes in the user (such as a sudden increase in sensitivity to a particular type of sleep induction information). This improves the sleep induction model's adaptability to different scenarios, further enhancing the accuracy and broad applicability of sleep induction.
[0055] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.
[0056] Please refer to Figure 3 This diagram illustrates a block diagram of a sleep induction device according to an embodiment of this application. The device has the function of implementing the aforementioned sleep induction method; this function can be implemented in hardware or by hardware executing corresponding software. The device can be a computer device or can be installed within a computer device. The device may include: a sleep monitoring module 310, a sleep induction module 320, and a sleep control module 330.
[0057] The sleep monitoring module 310 is used to acquire the state of the first sleep stage in real time during sleep. The sleep stages include the awake stage, light sleep stage, light sleep stage, deep sleep stage, and REM sleep stage.
[0058] The sleep induction module 320 is used to obtain sleep adjustment parameters when the sleep induction requirements are met in the first sleep state.
[0059] The sleep control module 330 is used to release sleep induction information based on the sleep adjustment parameters; wherein the sleep induction information is used to induce sleep during the sleep process.
[0060] In an exemplary embodiment, the sleep induction module 320 is used for: Obtain a static user profile based on physiological and personality characteristics; wherein the physiological characteristics are used to describe changes in sleep periods and changes in biological information during historical sleep processes, and the personality characteristics are used to describe the sensitivity to more than one type of sleep-inducing information; Based on the static user profile, and combined with the target sleep period indicated by the sleep state, a sleep user profile is constructed. Based on the sleep user profile, the sleep adjustment parameters are obtained.
[0061] In an exemplary embodiment, the sleep induction module 320 is used for: Based on the target sleep period, a first dynamic user profile is obtained based on the physiological characteristics of the sleep period; wherein, the physiological characteristics of the sleep period are used to describe the changes in biological information during the target sleep period in the historical sleep process; A second dynamic user profile is constructed based on real-time physiological features; wherein, the real-time physiological features are used to describe the changes in biological information during the sleep process; The static user profile, the first dynamic user profile, and the second dynamic user profile are fused together to obtain the sleep user profile.
[0062] In an exemplary embodiment, the sleep induction module 320 is used for: The sleep user profile is input into a pre-trained sleep induction model to obtain the sleep adjustment parameters; The sleep adjustment parameters include the sleep induction information, the duration of the information, the intensity of the information effect, and the timing of the information effect.
[0063] In an exemplary embodiment, such as Figure 4 As shown, the device also includes a sample generation module 340.
[0064] The sleep monitoring module 310 is used to acquire the second sleep state after the release of the sleep induction information ends.
[0065] The sample generation module 340 is used to generate a training sample for the sleep induction model when the sleep induction requirement is not met in the second sleep state, using the sleep user profile as sample input information and the sleep adjustment parameters as sample label information; wherein, the training sample includes the sample input information and the sample label information.
[0066] In an exemplary embodiment, the sleep monitoring module 310 is used for: During the sleep process, bioelectrical information is acquired in real time through a bioelectrical monitoring unit; The bioelectrical information is processed for sleep stages to obtain the first sleep stage state.
[0067] In an exemplary embodiment, the sleep induction requirement includes at least one of the following: the duration of the sleep latency is greater than a first threshold, the ratio between deep sleep and total sleep duration is less than a second threshold, and the duration of wakefulness during non-sleep latency is greater than a third threshold. The sleep latency period refers to the first waking period during the sleep process.
[0068] In an exemplary embodiment, such as Figure 4 As shown, the device includes: a wakefulness stimulation module 350.
[0069] The wakefulness stimulation module 350 is used to release wakefulness stimulation information when the current time is a preset wakefulness time; wherein, the wakefulness stimulation information is used to indicate the end of the sleep process.
[0070] In summary, the technical solution provided in this application determines sleep adjustment parameters by acquiring the first sleep stage state in real time during sleep, thereby releasing sleep induction information. This means that the sleep induction information changes with the first sleep stage state during sleep, allowing for flexible changes in sleep induction, which is beneficial for improving overall sleep quality and efficiency. Furthermore, by changing the sleep induction information in real time during sleep, and automatically adjusting it when the user is unable to move while asleep, the sleep induction process is automated. Moreover, sleep induction is initiated when the first sleep stage state meets the sleep induction requirements; that is, sleep induction is not determined based on changes in the sleep stage. Sleep induction can still be initiated even if the sleep stage remains unchanged, making sleep induction more timely.
[0071] In an exemplary embodiment, a computer device is also provided, the computer device including a processor and a memory, the memory storing a computer program, the computer program being loaded and executed by the processor to implement the above-described sleep induction method.
[0072] In an exemplary embodiment, a non-transitory computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the above-described sleep induction method.
[0073] In an exemplary embodiment, a computer program product is also provided, which, when run, causes a computer device to perform the sleep induction method described above.
[0074] The above embodiments are merely illustrative of the technical concept and features of the present invention, intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly, and should not be construed as limiting the scope of protection of the present invention. It will be apparent to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects. The scope of the present invention is defined by the appended claims rather than the foregoing description, and thus all changes falling within the meaning and scope of the equivalents of the claims are intended to be included within the invention.
[0075] It should be understood that "multiple" as used herein refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the step numbers described herein are merely illustrative of one possible execution order. In some other embodiments, the steps may not be executed in numerical order, such as two steps with different numbers being executed simultaneously, or two steps with different numbers being executed in the reverse order of the illustration. This application does not limit this.
[0076] The above description is merely an exemplary embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A sleep induction method, characterized in that, The method includes: The first sleep stage state is acquired in real time during sleep, which includes wakefulness, light sleep, light sleep, deep sleep, and REM sleep. If the sleep induction requirements are met in the first sleep stage, obtain sleep adjustment parameters; Based on the sleep adjustment parameters, sleep induction information is released; wherein, the sleep induction information is used to induce sleep during the sleep process.
2. The method according to claim 1, characterized in that, The acquisition of sleep adjustment parameters includes: Obtain a static user profile based on physiological and personality characteristics; wherein the physiological characteristics are used to describe changes in sleep periods and changes in biological information during historical sleep processes, and the personality characteristics are used to describe the sensitivity to more than one type of sleep-inducing information; Based on the static user profile, and combined with the target sleep period indicated by the sleep state, a sleep user profile is constructed. Based on the sleep user profile, the sleep adjustment parameters are obtained.
3. The method according to claim 2, characterized in that, The step of constructing a sleep user profile based on the static user profile and combining it with the target sleep period indicated by the sleep state includes: Based on the target sleep period, a first dynamic user profile is obtained based on the physiological characteristics of the sleep period; wherein, the physiological characteristics of the sleep period are used to describe the changes in biological information during the target sleep period in the historical sleep process; A second dynamic user profile is constructed based on real-time physiological features; wherein, the real-time physiological features are used to describe the changes in biological information during the sleep process; The static user profile, the first dynamic user profile, and the second dynamic user profile are fused together to obtain the sleep user profile.
4. The method according to claim 2, characterized in that, The step of obtaining the sleep adjustment parameters based on the sleep user profile includes: The sleep user profile is input into a pre-trained sleep induction model to obtain the sleep adjustment parameters; The sleep adjustment parameters include the sleep induction information, the duration of the information, the intensity of the information effect, and the timing of the information effect.
5. The method according to claim 4, characterized in that, The method further includes: Upon completion of the release of the sleep induction information, the second sleep state is obtained; If the sleep induction requirement is not met in the second sleep state, a training sample for the sleep induction model is generated using the sleep user profile as the sample input information and the sleep adjustment parameters as the sample label information; wherein, the training sample includes the sample input information and the sample label information.
6. The method according to claim 1, characterized in that, The method of acquiring the first sleep stage state in real time during sleep includes: During the sleep process, bioelectrical information is acquired in real time through a bioelectrical monitoring unit; The bioelectrical information is processed for sleep stages to obtain the first sleep stage state.
7. The method according to any one of claims 1 to 6, characterized in that, The sleep induction requirement includes at least one of the following: the duration of the sleep latency is greater than a first threshold, the ratio between deep sleep and total sleep duration is less than a second threshold, and the duration of wakefulness is greater than a third threshold when there is no sleep latency. The sleep latency period refers to the first waking period during the sleep process.
8. The method according to any one of claims 1 to 6, characterized in that, The method further includes: If the current moment is a preset wakefulness moment, a wakefulness stimulus is released; wherein, the wakefulness stimulus is used to indicate the end of the sleep process.
9. A sleep induction device, characterized in that, The sleep induction device is used to implement the method as described in any one of claims 1 to 8, the device comprising: The sleep monitoring module is used to obtain the state of the first sleep stage in real time during sleep. The sleep stages include the awake stage, light sleep stage, light sleep stage, deep sleep stage, and REM sleep stage. The sleep induction module is used to obtain sleep adjustment parameters when the sleep induction requirements are met in the first sleep stage state; A sleep control module is used to release sleep induction information based on the sleep adjustment parameters; wherein the sleep induction information is used to induce sleep during the sleep process.
10. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing a computer program that is loaded and executed by the processor to implement the method as claimed in any one of claims 1 to 8.