Sleep monitoring-based stress analysis mitigation method and device, and computer device

Abstract

The application discloses a stress analysis and relief method and device based on sleep monitoring and a computer device, and the method comprises the following steps: acquiring physiological parameters, characteristic parameters and sleep parameters of a user; evaluating the mental stress state of the user according to the acquired physiological parameters, characteristic parameters and sleep parameters; analyzing the mental stress state of the user and outputting a personalized stress relief mode instruction to a mental stress relief mechanism; and the mental stress relief mechanism providing a personalized relief operation to the user according to the output personalized stress relief mode instruction, so that the mental state of the user is improved and the sleep quality of the user is improved.

Description

Technical Field

[0001] This invention relates to the field of sleep monitoring technology, and in particular to stress analysis and relief methods, devices, and computer equipment based on sleep monitoring. Background Technology

[0002] In today's fast-paced society, more and more people are paying attention to their mental stress levels. Mental stress is closely related to sleep quality; high stress is one of the main causes of insomnia. Therefore, monitoring mental stress is of great significance for sleep monitoring.

[0003] However, current technologies do not assess users' mental stress levels based on sleep monitoring, nor do they provide personalized stress relief methods based on users' mental states. Summary of the Invention

[0004] In order to solve the above-mentioned technical problems, the purpose of this invention is to provide a stress relief method, device and computer equipment based on sleep monitoring, so as to improve the user's mental state and improve the user's sleep quality.

[0005] In view of this, a stress relief method based on sleep monitoring is provided, including the following steps:

[0006] Obtain the user's physiological parameters, characteristic parameters, and sleep parameters;

[0007] The user's mental stress status is assessed based on the acquired physiological parameters, characteristic parameters, and sleep parameters.

[0008] The system analyzes the user's mental stress level and outputs personalized stress relief instructions to the mental stress relief organization.

[0009] The stress relief mechanism provides users with personalized stress relief operations based on the personalized stress relief instructions output.

[0010] Furthermore, the assessment of the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters includes:

[0011] A mental stress state assessment algorithm model is established through a data processor. Physiological parameters, characteristic parameters, and sleep parameters are input into the mental stress state assessment algorithm model. The output parameters of the mental stress state assessment algorithm model include the user's mental stress state type and severity parameters.

[0012] Furthermore, the step of analyzing the user's mental stress state and outputting personalized stress relief instructions to the mental stress relief institution includes:

[0013] The data processor establishes a stress relief method recommendation algorithm model. The model is input with physiological parameters, feature parameters, sleep parameters, stress state type and severity parameters. The output parameters of the stress relief method recommendation algorithm model include personalized stress relief methods and different levels of relief.

[0014] Furthermore, the physiological parameters include one or more of the following: sex, height, weight, heart rate, respiration, body movement, or heart rate variability; and / or

[0015] The characteristic parameters include time domain or frequency domain.

[0016] Furthermore, the sleep parameters include one or more of the following: sleep latency, sleep duration, sleep onset time, or percentage of deep sleep.

[0017] Furthermore, the types of mental stress states include normal, tense, anxious, excited, or depressed; the severity includes mild, moderate, or severe.

[0018] Furthermore, the personalized stress relief methods include music meditation recommendations or airbag fluctuations, with different levels of relief including meditation time, airbag fluctuation frequency, and amplitude.

[0019] Furthermore, the stress relief device may include a smart mattress, a massage chair, or a sleep aid app.

[0020] Additionally, a stress relief method device based on sleep monitoring is provided, comprising:

[0021] Monitoring devices are used to acquire users' physiological parameters, characteristic parameters, and sleep parameters;

[0022] The data processor is used to assess the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters; and to analyze the user's mental stress state and output personalized stress relief instructions to the mental stress relief institution.

[0023] A stress relief organization is used to provide users with personalized stress relief operations based on the personalized stress relief instructions output.

[0024] A computer device is provided, comprising a memory, a data processor, and a computer program stored in the memory and executable on the processor, characterized in that the data processor, when executing the computer program, implements the method described above.

[0025] The beneficial effects of this invention are as follows: This invention provides a stress analysis and relief method, device, and computer equipment based on sleep monitoring. It acquires the user's physiological parameters, characteristic parameters, and sleep parameters; assesses the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters; analyzes the user's mental stress state and outputs personalized stress relief instructions to a stress relief institution; the stress relief institution provides personalized relief operations to the user based on the output personalized stress relief instructions, thereby improving the user's mental state and enhancing the user's sleep quality. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A flowchart illustrating the steps of a stress relief method based on sleep monitoring provided in an embodiment of the present invention;

[0028] Figure 2 A schematic diagram of the mental stress state assessment algorithm model of the stress analysis and relief method based on sleep monitoring provided in an embodiment of the present invention;

[0029] Figure 3 A schematic diagram of the working algorithm model for recommending mental stress relief methods based on sleep monitoring stress analysis and relief methods provided in this embodiment of the invention;

[0030] Figure 4 This is a schematic diagram of a stress analysis and relief device based on sleep monitoring provided in an embodiment of the present invention. Detailed Implementation

[0031] This invention provides a method, apparatus, and computer device for stress relief based on sleep monitoring, which improves the user's mental state and enhances the user's sleep quality.

[0032] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0033] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0034] Example 1:

[0035] like Figure 1 As shown, a stress relief method based on sleep monitoring is provided, including the following steps:

[0036] Step 10: Obtain the user's physiological parameters, characteristic parameters, and sleep parameters;

[0037] Specifically, the monitoring device acquires the user's physiological parameters, characteristic parameters, and sleep parameters. This device may include a weight sensor, respiration, and heart rate monitors, etc. The structure and principles of the monitoring device are existing technologies and will not be elaborated upon here. Physiological parameters include, but are not limited to, gender, height, weight, heart rate, respiration, body movement, and heart rate variability. Characteristic parameters include, but are not limited to, time-domain and frequency-domain parameters; specifically, characteristic parameters include, but are not limited to, time-domain and frequency-domain parameters related to the user's BCG signal (cardiac impulse signal), heart rate signal, and respiration signal. Sleep parameters include, but are not limited to, sleep latency, sleep duration, sleep onset time, and percentage of deep sleep.

[0038] Step 20: Assess the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters;

[0039] Specifically, such as Figure 2 As shown, a mental stress state assessment algorithm model is established through a data processor. The algorithm model can be any of the following: linear SVM, Gaussian SVM, decision tree, KNN, bagged tree, and subspace KNN. The input parameters of the algorithm model include physiological parameters, feature parameters, and sleep parameters, and more parameters can also be input. The algorithm model outputs the mental stress state, which includes the user's mental stress state type and severity. The state type includes normal, tense, anxious, excited, depressed, etc., and the severity includes mild, moderate, severe, etc.

[0040] Step 30: Analyze the user's mental stress state and output personalized stress relief instructions to the mental stress relief organization;

[0041] Specifically, such as Figure 3As shown, the data processor establishes a recommendation algorithm model for stress relief methods. The algorithm model can be any recommendation algorithm model among linear SVM, Gaussian SVM, decision tree, KNN, bagged tree, and subspace KNN. The input parameters of the recommendation algorithm model include physiological parameters, feature parameters, sleep parameters, stress state type and severity. The output parameters of the algorithm model include personalized relief methods and different levels of relief. Personalized relief methods include music meditation recommendations or air sac fluctuations. Different levels of relief include meditation time, air sac fluctuation frequency and amplitude.

[0042] Step 40: The stress relief mechanism provides personalized stress relief operations to the user based on the output personalized stress relief instructions.

[0043] Specifically, the process of relieving mental stress involves a data processor issuing instructions to a stress relief mechanism based on the output of a stress relief method recommendation algorithm. This mechanism can include devices or software, such as smart mattresses, massage chairs, or sleep aid apps. Smart mattresses and massage chairs are equipped with multiple adjustable inflatable airbag modules. After receiving the instructions, the associated devices or software provide personalized relief operations to the user.

[0044] The user can also choose how to relieve mental stress. The data processor sends the mental stress assessment results and the recommended mental stress relief methods to the user. The user can then choose the relief method and the degree of relief based on the mental stress assessment results, the recommended relief methods and their own preferences. They can also choose other devices to relieve mental stress.

[0045] Furthermore, the assessment of the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters includes:

[0046] A mental stress state assessment algorithm model is established through a data processor. Physiological parameters, characteristic parameters, and sleep parameters are input into the mental stress state assessment algorithm model. The output parameters of the mental stress state assessment algorithm model include the user's mental stress state type and severity parameters.

[0047] Furthermore, the step of analyzing the user's mental stress state and outputting personalized stress relief instructions to the mental stress relief institution includes:

[0048] A stress relief method recommendation algorithm model is established using a data processor. Physiological parameters, characteristic parameters, sleep parameters, stress state type and severity parameters are input into the stress relief method recommendation algorithm model. The output parameters of the stress relief method recommendation algorithm model include personalized stress relief methods and different levels of relief.

[0049] In addition, the physiological parameters include one or more of the following: gender, height, weight, heart rate, respiration, body movement, or heart rate variability; the characteristic parameters include time domain or frequency domain; and the sleep parameters include one or more of the following: sleep latency, sleep duration, sleep onset time, or percentage of deep sleep.

[0050] Example 2:

[0051] like Figure 4 As shown, a stress analysis and relief method device based on sleep monitoring is provided, comprising:

[0052] Monitoring devices are used to acquire users' physiological parameters, characteristic parameters, and sleep parameters;

[0053] Specifically, the monitoring device acquires the user's physiological parameters, characteristic parameters, and sleep parameters. There are no restrictions on the type or number of monitoring devices. The physiological parameters based on sleep monitoring include heart rate, respiration, body movement, and heart rate variability; the characteristic parameters include time domain, frequency domain, and sleep parameters; and the sleep parameters include sleep latency, sleep duration, sleep onset time, and the percentage of deep sleep.

[0054] The data processor is used to assess the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters; and to analyze the user's mental stress state and output personalized stress relief instructions to the mental stress relief institution.

[0055] Specifically, the data processor establishes an algorithm model for assessing mental stress status and an algorithm model for recommending mental stress relief methods. The algorithm model assesses the user's mental stress status, including the type and severity of the mental state. The data processor is electrically connected to a monitoring device and connects to a mental stress relief institution via a network interface or wireless network communication. Based on the acquired physiological parameters, characteristic parameters, and sleep parameters, it assesses the user's mental stress status; and based on the analysis of the user's mental stress status, it outputs personalized stress relief instructions to the mental stress relief institution.

[0056] A stress relief organization is used to provide users with personalized stress relief operations based on the personalized stress relief instructions output.

[0057] Specifically, based on the user's stress level, the system connects them with stress relief institutions, including devices or software such as smart mattresses, massage chairs, and sleep aid apps, offering various personalized adjustment methods such as music meditation recommendations or airbag fluctuations; as well as different levels of adjustment (the frequency and amplitude of airbag fluctuations). Users can also independently choose stress relief methods and levels based on their own stress level and preferences.

[0058] Example 3:

[0059] A computer device is provided, including a memory, a data processor, and a computer program stored in the memory and executable on the processor, characterized in that the data processor implements the method when executing the computer program.

[0060] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A stress relief method based on sleep monitoring, characterized in that, Includes the following steps: Obtain the user's physiological parameters, characteristic parameters, and sleep parameters; The user's mental stress status is assessed based on the acquired physiological parameters, characteristic parameters, and sleep parameters. The system analyzes the user's mental stress level and outputs personalized stress relief instructions to the mental stress relief organization. The stress relief mechanism provides users with personalized stress relief operations based on the personalized stress relief instructions output. The assessment of the user's mental stress state based on acquired physiological parameters, characteristic parameters, and sleep parameters includes: A mental stress state assessment algorithm model is established through a data processor. Physiological parameters, characteristic parameters, and sleep parameters are input into the mental stress state assessment algorithm model. The output parameters of the mental stress state assessment algorithm model include the user's mental stress state type and severity parameters. The process of analyzing the user's mental stress state and outputting personalized stress relief instructions to the mental stress relief organization includes: The data processor establishes a recommendation algorithm model for stress relief methods. The model is input with physiological parameters, feature parameters, sleep parameters, stress state type and severity parameters. The output parameters of the model include personalized stress relief methods and different levels of relief. The personalized stress relief methods include music meditation recommendations or airbag fluctuations, with different levels of relief including meditation time, airbag fluctuation frequency, and amplitude.

2. The stress relief method based on sleep monitoring according to claim 1, characterized in that, The physiological parameters include one or more of sex, height, weight, heart rate, respiration, body movement, or heart rate variability; and / or, the characteristic parameters include time domain or frequency domain.

3. The stress relief method based on sleep monitoring according to claim 1, characterized in that, The sleep parameters include one or more of the following: sleep latency, sleep duration, sleep onset time, or percentage of deep sleep.

4. The stress relief method based on sleep monitoring according to claim 1, characterized in that, The types of mental stress states include normal, tense, anxious, excited, or depressed; the severity includes mild, moderate, or severe.

5. The stress relief method based on sleep monitoring according to claim 1, characterized in that, The stress relief devices mentioned include smart mattresses, massage chairs, or sleep aid apps.

6. A stress relief device based on sleep monitoring, used to perform the method according to any one of claims 1-5, characterized in that, include: Monitoring devices are used to acquire users' physiological parameters, characteristic parameters, and sleep parameters; The data processor is used to assess the user's mental stress state based on the acquired physiological parameters, characteristic parameters, and sleep parameters; and to analyze the user's mental stress state and output personalized stress relief instructions to the mental stress relief institution. A stress relief organization is used to provide users with personalized stress relief operations based on the personalized stress relief instructions output.

7. A computer device comprising a memory, a data processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the data processor executes the computer program, it implements the method as described in any one of claims 1-5.

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