User relaxation state evaluation-based rhythm control method, and system and mattress using same

Abstract

The present invention relates to a user relaxation state evaluation-based rhythm control method, and a system and mattress using same. The use experience of existing rhythm components is not so good. The present invention collects user information to obtain basic parameters for guiding the operation of a rhythm component, ensures that the basic parameters are matched with user's own condition so as to ensure that the physical rhythm experience provided by the operation of the rhythm component under the guidance of the basic parameters can have a better relaxation effect and sleep aid effect on the user, and further measures real-time physiological data of the lying user to rate a user state and thus to adaptively modify the basic parameters, so that the basic parameters can be associated with the real-time state of the user, ensuring that the rhythm experience output by the rhythm component satisfies the real-time demand of the user, and effectively improving the use experience. The present invention collects user information to select basic parameters matched therewith, and then collects real-time physiological data to modify the basic parameters, so as to ensure that users obtain individual rhythm experience associated with themselves and to effectively promote relaxation and sleep, thus improving the use effect.

Description

A rhythmic control method based on user relaxation state assessment, and a system and mattress using it. Technical Field

[0001] This invention relates to the field of sleep, and more specifically to a rhythm control method, a system using the same, and a mattress. Background Technology

[0002] To enhance the user's sleep experience and comfort, smart mattresses are equipped with a rhythmic component. By inflating and deflating the air springs within this component, a rhythmic sensation is applied to the user, promoting relaxation and faster sleep. The operating parameters of this rhythmic component are adjustable, allowing users to obtain differentiated rhythmic experiences. However, existing smart mattresses can only implement rhythmic movements according to preset programs. This means the mattress operates solely based on these programs and cannot adaptively adjust to the user's actual needs, resulting in a rhythmic experience that fails to meet the user's specific requirements and negatively impacting the overall user experience. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a rhythm control method based on user relaxation state assessment, as well as a system and mattress using the method. By collecting user information, the method obtains basic parameters to guide the operation of the rhythm components. By detecting real-time physiological data of the user, the method rates the user's state and adjusts the basic parameters accordingly, so that the rhythm experience meets the user's actual needs and effectively improves the user experience.

[0004] This invention is achieved through the following method: a rhythmic control method based on user relaxation state assessment for controlling rhythmic components, the method being implemented through the following steps:

[0005] The first step is to collect user information and compare it with the basic database to obtain the basic parameters used to control the rhythm component;

[0006] The second step involves monitoring and collecting heart rate and respiratory rate data during the user's transition from a quiet state to a deep relaxation state, and then calculating a set of relaxation parameters.

[0007] The third step is to intermittently monitor the user during the relaxation process to obtain the user's real-time heart rate and respiratory rate data, and calculate the relaxation index through the relaxation parameter set.

[0008] The fourth step is to set multiple relaxation thresholds and rate the relaxation index, and adjust the operating mode of the rhythm component according to the rating results.

[0009] In the fifth step, the rhythm component completes its action in the selected running mode and then proceeds to the third step until the preset total running time is reached and then it closes.

[0010] By collecting user information to obtain the basic parameters guiding the operation of the rhythm component, it is ensured that the basic parameters match the user's own situation. This ensures that the rhythmic sensations provided by the component under the guidance of the basic parameters can have a good relaxation and sleep-inducing effect on the user. Furthermore, by detecting the user's real-time physiological data while lying down, the user's state is rated, and the basic parameters are then adjusted accordingly. This ensures that the basic parameters are correlated with the user's real-time state, ensuring that the rhythmic experience output by the component meets the user's real-time needs and effectively improves the user experience. By collecting user information to select matching basic parameters, and then collecting real-time physiological data to adjust the basic parameters, it is ensured that the user receives a personalized rhythmic experience that is relevant to them, effectively promoting relaxation and sleep, and improving the user effect. The main reason why heart rate variability increases in a relaxed state is based on the regulatory mechanism of the autonomic nervous system, especially the activity of the parasympathetic nervous system. Heart rate variability (HRV) refers to the degree of change in the interval between heartbeats, which reflects the heart's ability to respond to environmental and internal bodily changes. In a relaxed state, the parasympathetic nervous system is dominant, and the signals it releases help to lower the heart rate, making cardiac activity more stable and gentle. This stability is not static, but rather manifests as a rhythmic, natural fluctuation. This fluctuation causes the heart rate interval to vary within a certain time period, and the differences in these variations are relatively large, thus increasing heart rate variability. To explain this numerically, suppose a person in a state of tension has a heart rate that remains at 90 beats per minute, and the heart rate interval is relatively fixed with little variation. However, in a relaxed state, although the average heart rate may still be close to 90 beats per minute, the heart rate interval will fluctuate significantly, for example, sometimes 0.65 seconds, sometimes 0.7 seconds, sometimes 0.6 seconds, etc. This fluctuation leads to increased heart rate variability. Respiratory variability parameters also have the same functional orientation as heart rate variability parameters; combining heart rate variability parameters and respiratory variability parameters can more accurately reflect the user's relaxation state.

[0011] Preferably, in the first step, the basic database includes several data sets. Each data set includes user information and corresponding basic parameters. The basic database obtains the corresponding data sets and thus the corresponding basic parameters by collecting the user information. The basic database stores several sets of corresponding user information and basic parameters, facilitating the retrieval of corresponding basic data through user information. This ensures that the rhythm component achieves a rhythmic experience closely resembling the user's needs, and by reducing the subsequent correction magnitude of the basic data, ensures that the rhythmic experience meets the user's personalized requirements.

[0012] Preferably, the user information includes the user's gender, age, height, and weight. The basic database collects and categorizes a large amount of sample data, enabling users to obtain corresponding basic data based on their own information. This effectively shortens the time required for users to obtain the corresponding basic data, thereby reducing the need for corrections to the basic data and improving the matching between the basic data and the user.

[0013] Preferably, the basic parameters include the maximum air pressure of the rhythmic component, the area of ​​motion, the preset lifting height, the basic frequency, and the duration of the movement. These basic parameters encompass multiple dimensions, ensuring that the rhythmic component generates diverse rhythmic stimulation to meet the user's relaxation and sleep-aiding needs.

[0014] Preferably, in the second step, the relaxation parameter set includes the maximum heart rate variability (HRV_max) and the minimum heart rate variability (HRV_min), obtained through the following steps: First, heart rate data is collected during the transition process; then, the transition process is divided into multiple time units, and the time interval between adjacent heartbeats within each time unit is statistically analyzed to form a unit heart rate dataset; next, the data within the unit heart rate dataset is sequentially subjected to cumulative average calculation, variance calculation, and standard deviation calculation to obtain the unit heart rate variability parameters; finally, the calculated unit heart rate variability parameters are compared to obtain the maximum heart rate variability (HRV_max) and the minimum heart rate variability (HRV_min). Obtaining the maximum heart rate variability (HRV_max) and the minimum heart rate variability (HRV_min) provides a reference for the real-time heart rate variability average obtained from subsequent real-time monitoring, thereby determining the degree of relaxation based on the user's physiological condition and preventing situations where the user's relaxation level cannot be accurately determined due to the original data being irrelevant to the user.

[0015] Preferably, in the second step, the relaxation parameter set includes a maximum respiratory rate (RF_max) and a minimum respiratory rate (RF_min), obtained through the following steps: First, respiratory data is collected during the transition process; then, the transition process is divided into multiple time units, and the respiratory rate within each time unit is statistically analyzed to form a unit respiratory dataset; next, the data within the unit respiratory dataset are summed and averaged to obtain the unit respiratory rate parameter; finally, the calculated unit respiratory rate parameters are compared to obtain the maximum respiratory rate (RF_max) and the minimum respiratory rate (RF_min). Obtaining the maximum and minimum respiratory rate (RF_min) provides a reference for the subsequent real-time average respiratory rate obtained from real-time monitoring, thereby determining the degree of relaxation based on the user's physiological condition and preventing situations where the user's relaxation level cannot be accurately determined due to the original data being irrelevant to the user.

[0016] Preferably, in the third step, a unit monitoring duration and a stoppage duration between adjacent unit monitoring durations are set to perform intermittent monitoring of the user. Each monitoring duration includes at least two consecutive unit time periods. Real-time heart rate and respiratory rate data are collected within each unit time period, and the mean real-time heart rate variability (HRV_current) and mean real-time respiratory rate (RF_current) are calculated respectively. These are then converted into a relaxation index (RELAX) corresponding to the unit monitoring duration. By intermittently monitoring the user's real-time physiological data, effective monitoring of the user's sleep at various stages is achieved. The relaxation index for each time period is then used to assess the user's relaxation level. Intermittent monitoring also reduces the amount of data processing and ensures that changes in the user's relaxation level are detected promptly, providing a basis for adjusting baseline parameters. The real-time monitored physiological data includes real-time heart rate and real-time respiratory rate data. The mean real-time heart rate variability (HRV_current) and mean real-time respiratory rate (RF_current) are calculated from this data, and the relaxation index (RELAX) is then calculated, creating a deep correlation between the relaxation index (RELAX) and the user's real-time heart rate and respiratory rate data.

[0017] Preferably, the relaxation index RELAX is calculated using the following formula:

[0018] RELAX=(HRV_current-HRV_min) / (HRV_max-HRV_min) +(RF_max-RF_current) / (RF_max-RF_min);

[0019] The position of the real-time mean heart rate variability (HRV_current) between the maximum and minimum HRV values, and the position of the real-time mean respiratory rate (RF_current) between the maximum and minimum respiratory rates, are calculated to obtain the relaxation index RELAX, which reflects the user's level of relaxation. On one hand, the more relaxed the user, the larger the real-time mean HRV_current, and the larger the difference between HRV_current and HRV_min, thus ensuring an increase in the RELAX. On the other hand, the more relaxed the user, the smaller the real-time mean respiratory rate (RF_current), and the larger the difference between RF_current and RF_max, thus ensuring an increase in the RELAX. By appropriately setting the formula to ensure that heart rate variability and respiratory rate both align with relaxation-friendly characteristics, the RELAX will increase, thus reflecting the user's relaxation.

[0020] Preferably, the time interval between adjacent heartbeats in the real-time heart rate data within a unit time period is statistically analyzed, and the cumulative average, variance, and standard deviation are calculated sequentially to obtain the real-time unit heart rate variability parameter. The real-time unit heart rate variability parameter is obtained by cumulative averaging to obtain the real-time variability mean HRV_current. When the real-time unit heart rate variability parameter is greater than the maximum heart rate variability HRV_max, the real-time unit heart rate variability parameter is corrected to the maximum heart rate variability HRV_max. When the real-time unit heart rate variability parameter is less than the minimum heart rate variability HRV_min, the real-time unit heart rate variability parameter is corrected to the minimum heart rate variability HRV_min. To prevent excessive deviations in some data, the calculated average real-time heart rate variability (HRV_current) with excessive deviations is corrected. HRV_current values ​​exceeding the preset range are corrected to either the minimum HRV_min or the maximum HRV_max. This ensures that the relaxation index (RELAX) changes accordingly by increasing data fluctuation, and also prevents the accuracy of the RELAX from being affected by excessive deviations in individual data points during subsequent operation by limiting the fluctuation range.

[0021] Preferably, the real-time unit respiratory rate parameter is obtained by averaging the real-time respiratory rate data within the unit time period. This real-time unit respiratory rate parameter is then averaged to obtain the real-time respiratory rate average RF_current. When the real-time unit respiratory rate parameter is greater than the maximum respiratory rate RF_max, it is corrected to the maximum respiratory rate RF_max; when the real-time unit respiratory rate parameter is less than the minimum heart rate variability HRV_min, it is corrected to the minimum respiratory rate RF_min. To prevent excessive deviations in some data, the calculated real-time respiratory rate average RF_current with excessive deviations is corrected. Real-time respiratory rate averages RF_current exceeding a preset range are corrected to either the maximum respiratory rate RF_max or the minimum heart rate variability HRV_min. This not only ensures that the relaxation index RELAX changes accordingly by increasing data fluctuation, but also prevents the accuracy of the relaxation index RELAX from being affected by excessive deviations in individual data points by limiting the fluctuation range.

[0022] Preferably, in the fourth step, the rhythmic component includes a second air spring layer and a first air spring layer completely covering the second air spring layer. The multi-level relaxation threshold includes a progressively increasing first-level relaxation threshold TH1_relax and a second-level relaxation threshold TH2_relax. When RELAX < TH1_relax, the rhythmic component is controlled to operate in mode one; when TH1_relax ≤ RELAX < TH2_relax, the rhythmic component is controlled to operate in mode two; and when TH2_relax ≤ RELAX, the rhythmic component is controlled to operate in mode three. By setting the first-level relaxation threshold TH1_relax and the second-level relaxation threshold TH2_relax, the relaxation index RELAX is evaluated. Based on this, the basic parameters are adjusted, and different modes of rhythmic stimulation are applied to the user to ensure that the user receives rhythmic stimulation that matches their real-time condition and relaxes and falls asleep as quickly as possible. By setting reasonable primary relaxation thresholds TH1_relax and TH2_relax as the basis for the rhythm component to switch between different modes, and by making differentiated adjustments to the basic parameters in each mode, the system ensures that users receive rhythmic stimulation that matches their own situation, thereby improving relaxation and sleep-inducing effects.

[0023] Preferably, in Mode 1, the first and second air spring layers inflate and deflate simultaneously. The first air spring layer rises and falls between 0% and 100% of its preset lifting height, while the air pressure of the second air spring layer rises and falls between 8 kPa and 20 kPa above standard atmospheric pressure. The inflation and deflation frequency is the base frequency, the movement corresponds to the user's waist and back, and the duration is 10%-30% of the movement duration. If the user is not lying down, the upper limit of the lifting height of the first air spring layer is reduced by 50%, and the upper limit of the air pressure of the second air spring layer is reduced by 50%. When RELAX < TH1_relax, the user's relaxation level is low, requiring greater rhythmic stimulation to alleviate fatigue. Simultaneous inflation and deflation of the first and second air spring layers increases the relaxation stimulation, using rhythm to relax muscles and effectively provide a relaxation effect.

[0024] Preferably, in Mode 2, the first air spring layer alternates between 0-80% of the preset lifting height. The inflation / deflation frequency of the first air spring layer is 100%-110% of the average real-time breathing rate RF_current. The second air spring layer maintains a constant pressure state at an air pressure 15 kPa higher than standard atmospheric pressure. The movement corresponds to the user's shoulders, hips, waist, and back, and the duration is 10%-30% of the movement duration. The rhythmic amplitude gradually decreases from 80% to 50% of the preset lifting height. If the user is not lying down, the upper limit of the lifting height of the first air spring layer is reduced by 50%. When TH1_relax ≤ RELAX < TH2_relax, the user's relaxation level is moderate, and the rhythmic stimulation can be appropriately reduced. This allows the user's breathing structure to be adjusted through rhythm, and muscles to be soothed and relaxed, facilitating the user's transition to sleep in a relaxed state.

[0025] Preferably, in Mode 3, the first air spring layer is closed, and the air pressure of the second air spring layer fluctuates within a range of 8-20 kPa above standard atmospheric pressure. The inflation / deflation frequency of the first air spring layer is 90%-100% of the average real-time respiratory rate RF_current, with the movement corresponding to the user's shoulders, hips, legs, waist, and back, and the duration of the movement being 10%-30% of the total movement duration. If the user is not lying down, the upper limit of the air pressure of the second air spring layer is reduced by 50%. When TH2_relax≤RELAX, the user is in a relaxed state, and gentle rhythmic stimulation is provided to guide the user to fall asleep quickly, preventing the user from waking up due to receiving strong rhythmic stimulation.

[0026] A system includes a user data acquisition module, a physiological data acquisition module, a rhythm module, a data storage module, a pressure detection module, and a processing module. The user data acquisition module collects user information and transmits it to the processing module; the physiological data acquisition module collects the user's physiological data and transmits it to the processing module, including heart rate and respiratory data; the rhythm module receives and executes instructions from the processing module; the data storage module stores a basic database, the maximum respiratory rate (RF_max), the minimum respiratory rate (RF_min), the maximum heart rate variability (HRV_max), the minimum heart rate variability (HRV_min), the average real-time respiratory rate (RF_current), the average real-time heart rate variability (HRV_current), multi-level relaxation thresholds, and the conversion methods of the rhythm component for the basic parameters in each mode; the pressure detection module monitors the pressure conditions in each region and transmits pressure change data for each region to the processing module to assist the processing module in calculating the user's posture; the processing module compares the user information provided by the user data acquisition module with the corresponding basic parameters in the basic database, calculates the relaxation index based on the physiological data provided by the physiological data acquisition module, and sends instructions for the corresponding mode to the rhythm module after comparing it with the multi-level relaxation thresholds. The system obtains basic data that meets user experience needs from the basic database by collecting user information. During system operation, it monitors the user's physiological data in real time and calculates a relaxation index. The relaxation index is compared with a multi-level relaxation threshold to select the operating mode of the rhythm component. This ensures that the system can adjust the rhythm component in real time according to the user's real-time state, thereby improving the system's relaxation and sleep aid effect.

[0027] A mattress includes a mattress body and a control box. The mattress body houses a rhythmic component, which comprises a first air spring layer and a second air spring layer stacked sequentially from top to bottom. The control box controls the independent operation of the first and second air spring layers, allowing the rhythmic component to switch between various modes. By configuring independently operable first and second air spring layers, and through their cooperation, multiple rhythmic modes can be switched. This provides diverse rhythmic experiences to meet differentiated user needs, ensuring that real-time physiological data of the user is correlated with the operating status of the rhythmic component, thereby enhancing relaxation and sleep-inducing effects.

[0028] Preferably, the vertical projections of the first air spring layer and the second air spring layer overlap, so that each area on the top surface of the mattress can obtain corresponding rhythmic stimulation through the coordinated operation of the first air spring layer and the second air spring layer, thereby enhancing the diversity of rhythmic stimulation and meeting the personalized needs of users.

[0029] Preferably, the top surface of the first air spring layer is completely covered by the first comfort layer. The first comfort layer not only serves to shield the top surface of the first air spring and reduce the feeling of foreign objects, but also uses its own deformation to conform to the user's surface and improve the user's lying comfort.

[0030] Preferably, the top surface of the second air spring layer is completely covered by the second comfort layer. The second comfort layer not only serves to shield the top surface of the second air spring, reducing the feeling of foreign objects, but also improves support comfort.

[0031] Preferably, a pressure detection layer is located below the first air spring layer. The pressure detection layer is used to detect the pressure status of different areas of the mattress, which helps to determine the user's sleeping posture and provides a reference for adjusting the operation of the vibration components.

[0032] Preferably, a physiological data monitor is provided between the first air spring layer and the second air spring layer. The physiological data monitor is used to detect the user's physiological data in real time and provide data support for calculating the relaxation index RELAX.

[0033] The key advantages of this invention are: by collecting user information to obtain the basic parameters guiding the operation of the rhythm component, ensuring that these parameters match the user's individual situation, and thus ensuring that the rhythmic sensations provided by the component under the guidance of these parameters have a good relaxing and sleep-inducing effect on the user. Furthermore, by detecting real-time physiological data while the user is lying down to rate the user's state, and then adjusting the basic parameters accordingly, the basic parameters can be correlated with the user's real-time state, ensuring that the rhythmic experience output by the component meets the user's real-time needs, effectively improving the user experience. By collecting user information to select matching basic parameters, and then adjusting these parameters by collecting real-time physiological data, the invention ensures that the user receives a personalized rhythmic experience that is relevant to them, effectively promoting relaxation and sleep, and improving the overall user experience. Attached Figure Description

[0034] Figure 1 is a schematic diagram of the logic structure of the rhythm control method described in Embodiment 1;

[0035] Figure 2 is a schematic diagram of the system described in Embodiment 2;

[0036] Figure 3 is a schematic diagram of the disassembly structure of the mattress described in Example 3;

[0037] In the diagram: 1. Control box, 2. First air spring layer, 3. Second air spring layer, 4. First comfort layer, 5. Second comfort layer, 6. Pressure detection layer, 7. Physiological data detector. Modes for Carrying Out the Invention

[0038] The essential features of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0039] Example 1:

[0040] This embodiment provides a rhythm control method based on user relaxation state assessment.

[0041] Figure 1 illustrates a rhythm control method based on user relaxation state assessment, used to control a rhythm component. The method is implemented through the following steps:

[0042] The first step is to collect user information and compare it with the basic database to obtain the basic parameters used to control the rhythm component.

[0043] Specifically, the basic database includes several data groups, each containing user information and corresponding basic parameters. The basic database obtains the corresponding data groups and thus the corresponding basic parameters from the collected user information. Establishing the basic database facilitates the acquisition of corresponding data groups from user information, thereby forming the basic parameters used to control the operation of the rhythm component.

[0044] Specifically, when establishing the basic database, a large amount of sample information is collected and summarized to form data groups that correspond one-to-one with user information and basic parameters. Big data analysis is used to obtain basic parameters suitable for specific user information, which makes it easier for users to find the corresponding basic parameters and provides users with matching rhythmic stimulation.

[0045] Specifically, the user information includes the user's gender, age, height, and weight. In addition, the types and quantities of user information can be increased or decreased as needed, which should also be considered as a specific implementation method of this embodiment.

[0046] Specifically, the basic parameters include the maximum air pressure of the rhythm component, the movement part, the preset lifting height, the basic frequency, and the movement duration. The types and number of basic parameters must not only correspond to the user's needs but also match the movement characteristics of the rhythm component to ensure that the rhythm component forms a rhythmic stimulus that meets the user's needs under the guidance of the basic parameters, thereby facilitating the user's relaxation and sleep.

[0047] The second step involves monitoring and collecting heart rate and respiratory rate data during the user's transition from a resting state to a deep relaxation state, and calculating a relaxation parameter set. This step monitors and collects physiological data from the user's transition from a resting state to a deep relaxation state, and uses this data to form the relaxation parameter set for evaluation and correction of subsequently collected real-time physiological data. The relaxation parameter set includes the maximum heart rate variability (HRV_max), minimum heart rate variability (HRV_min), maximum respiratory rate (RF_max), and minimum respiratory rate (RF_min). The relaxation parameter set can be reused after a single standardized collection, eliminating the need for repeated collections and effectively simplifying the operation. Regular, standardized collection also improves data accuracy.

[0048] Specifically, during the monitoring process, the user's state is assessed by monitoring changes in heart rate or brain waves, thereby facilitating the monitoring of heart rate and respiratory rate data as the user transitions from a quiet state to a state of deep relaxation.

[0049] Specifically, the maximum and minimum heart rate variability (HRV_max and HRV_min) are obtained through the following steps: First, heart rate data is collected during the transition process, with the collection duration determined by the duration of the user's transition from a resting state to a deeply relaxed state. Next, the transition process is divided into multiple time units. The time interval between adjacent heartbeats within each time unit is statistically analyzed to form a unit heart rate dataset. The heart rate data within each time unit is represented by a heart rate graph. The time interval between the peaks of adjacent heartbeats forms the unit heart rate dataset. The number of unit heart rate datasets corresponds to the number of time units, and there are differences between the data within each unit heart rate dataset, facilitating the calculation of heart rate variability parameters. Then, the data within each unit heart rate dataset is sequentially subjected to cumulative average calculation, variance calculation, and standard deviation calculation to obtain the unit heart rate variability parameters. This calculation not only standardizes the data but also effectively removes individual biased data, improving data accuracy. Finally, the calculated unit heart rate variability parameters are compared to obtain the maximum and minimum heart rate variability (HRV_max and HRV_min).

[0050] For example, firstly, the unit time period is set to 1 minute, and it takes 10 minutes for the user to change from a quiet state to a deep relaxation state. The heart rate data collected by monitoring can be divided into 10 units of heart rate data.

[0051] Next, the heartbeat data within the unit heart rate dataset is processed, the time intervals between adjacent heartbeats are statistically analyzed, and a unit heart rate dataset including R1, R2...Rx is obtained.

[0052] Next, calculate the average value M = (R1 + R2 + R3 + ... + Rx) / x;

[0053] Calculate the variance V = [(R1-M)² + (R2-M)² + (R3-M)² + (R4-M)² + ... + (Rx-M)²] / x;

[0054] The standard deviation is S, calculated using the formula S²=V.

[0055] The standard deviation S is obtained through the above calculation, and the standard deviation S is used as the unit heart rate variability parameter. The unit heart rate variability parameter corresponding to each unit heart rate dataset is obtained by repeated calculation.

[0056] Finally, the heart rate variability parameters of the 10 unit datasets are compared, and the largest unit heart rate variability parameter is taken as the maximum heart rate variability HRV_max, and the smallest unit heart rate variability parameter is taken as the minimum heart rate variability HRV_min.

[0057] Specifically, the maximum respiratory rate (RF_max) and minimum respiratory rate (RF_min) are obtained through the following steps: First, respiratory data are collected during the transition process; then, the transition process is divided into multiple time units, and the respiratory rate within each time unit is statistically analyzed to form a unit respiratory dataset; next, the data within the unit respiratory dataset are summed and averaged to obtain the unit respiratory rate parameter; finally, the calculated unit respiratory rate parameters are compared to obtain the maximum respiratory rate (RF_max) and minimum respiratory rate (RF_min).

[0058] The third step involves intermittent monitoring of the user during the relaxation process to obtain real-time heart rate and respiratory rate data. A relaxation index is then calculated using a set of relaxation parameters. Since relaxation takes time, intermittent monitoring allows for timely understanding of the user's relaxation status while effectively reducing computational workload and thus lowering the hardware requirements.

[0059] Specifically, a unit monitoring duration and a stoppage duration between adjacent unit monitoring durations are set to perform intermittent monitoring of the user. Each monitoring session includes at least two consecutive unit time periods. Real-time heart rate and respiratory rate data are collected within each unit time period, and the average real-time heart rate variability (HRV_current) and average real-time respiratory rate (RF_current) are calculated respectively. These are then converted into a relaxation index (RELAX) corresponding to the unit monitoring duration. The relaxation index (RELAX) is calculated using the following formula:

[0060] RELAX=(HRV_current-HRV_min) / (HRV_max-HRV_min) +(RF_max-RF_current) / (RF_max-RF_min).

[0061] The relaxation index RELAX is calculated using the above formula, ensuring a deep correlation between RELAX and the real-time average respiratory rate RF_current and the real-time average heart rate variability HRV_current. It also ensures that RELAX is correlated with the maximum and minimum heart rate variability HRV_max, the maximum and minimum respiratory rate RF_max, and the minimum respiratory rate RF_min. Furthermore, by reasonably setting the formula structure, it ensures that the heart rate variability and respiratory rate after the user relaxes can cause the relaxation index RELAX to increase, thereby improving the accuracy of the correlation between RELAX and the user's degree of relaxation.

[0062] Specifically, the time intervals between adjacent heartbeats in the real-time heart rate data within a unit time period are statistically analyzed, and then the cumulative average, variance, and standard deviation are calculated sequentially to obtain the real-time unit heart rate variability parameter. This real-time unit heart rate variability parameter is then averaged to obtain the real-time heart rate variability mean, HRV_current. The real-time heart rate data is used to calculate the real-time heart rate variability mean, HRV_current, following the same calculation process as the unit heart rate variability parameter. When the real-time unit heart rate variability parameter is greater than the maximum heart rate variability value, HRV_max, it is corrected to the maximum heart rate variability value, HRV_max. Conversely, when the real-time unit heart rate variability parameter is less than the minimum heart rate variability value, HRV_min, it is corrected to the minimum heart rate variability value, HRV_min. This process removes data with significant deviations and improves data accuracy.

[0063] Specifically, the real-time respiratory rate data within a unit time period are averaged to obtain the real-time unit respiratory rate parameter. This real-time unit respiratory rate parameter is then averaged to obtain the real-time respiratory rate average, RF_current. The real-time respiratory rate average RF_current is calculated from the real-time respiratory rate data, following the same calculation process as the unit respiratory rate parameter. When the real-time unit respiratory rate parameter is greater than the maximum respiratory rate RF_max, it is corrected to the maximum respiratory rate RF_max. When the real-time unit respiratory rate parameter is less than the minimum heart rate variability HRV_min, it is corrected to the minimum respiratory rate RF_min. This process removes data with significant deviations and improves data accuracy.

[0064] The fourth step involves setting multi-level relaxation thresholds and rating the relaxation index. Based on the rating results, the operating mode of the rhythm component is adjusted. The multi-level relaxation thresholds include a progressively increasing first-level relaxation threshold (TH1_relax) and a second-level relaxation threshold (TH2_relax). These multi-level thresholds are used to rate the relaxation index (RELAX), and after selecting a suitable operating mode, the basic parameters are adjusted to ensure that the rhythmic stimulation generated by the rhythm component meets the user's relaxation and sleep-inducing needs.

[0065] Specifically, when RELAX < TH1_relax, the control rhythm component operates in mode one. In mode one, the first air spring layer 2 and the second air spring layer 3 inflate and deflate simultaneously. The first air spring layer 2 rises and falls between 0% and 100% of the preset lifting height, while the air pressure of the second air spring layer 3 rises and falls within the range of 8 kPa-20 kPa higher than the standard atmospheric pressure. The inflation and deflation frequency is the base frequency, the movement parts correspond to the user's waist and back, and the duration is 10%-30% of the movement duration. When a single part is inflated to the maximum height, it is held for a period of body stretching before slowly deflation. This rhythmic inflation and deflation cycle is maintained to slowly stretch the spinal muscles and promote relaxation. If the user is not in a lying position, the upper limit of the lifting height of the first air spring layer 2 is reduced by 50%, and the first air spring layer 2 rises and falls between 0% and 50% of the preset lifting height. The upper limit of the air pressure of the second air spring layer 3 is reduced by 50%, and the air pressure of the second air spring layer 3 rises and falls within the range of 8 kPa-10 kPa higher than the standard atmospheric pressure.

[0066] Specifically, when TH1_relax≤RELAX<TH2_relax, the control rhythm component operates in mode two: In mode two, the first air spring layer 2 switches between 0-80% of the preset lifting height, the inflation / deflation frequency of the first air spring layer 2 is 100%-110% of the real-time average breathing rate RF_current, the second air spring layer 3 maintains a constant pressure state at an air pressure 15 kPa higher than the standard atmospheric pressure, the movement parts correspond to the user's shoulders, hips, waist and back, the duration is 10%-30% of the movement duration, the rhythm amplitude gradually decreases from 80% to 50% of the preset lifting height until the inflation height reaches 50% of the maximum height, and maintains this maximum height for cyclic inflation and deflation, gradually guiding the user into a deep relaxation state; if the user is not in a lying position, the upper limit of the lifting height of the first air spring layer 2 is reduced by 50%, and the first air spring layer 2 switches between 0-40% of the preset lifting height.

[0067] Specifically, when TH2_relax≤RELAX, the control rhythm component operates in mode three: In mode three, the first air spring layer 2 is closed, and the air pressure of the second air spring layer 3 rises and falls within the range of 8kpa-20kpa above the standard atmospheric pressure. The inflation and deflation frequency of the first air spring layer 2 is 90%-100% of the average real-time breathing frequency RF_current. The movement parts correspond to the user's shoulders, hips, legs, waist, and back, and the duration is 10%-30% of the movement duration. By simulating the whole-body wave rhythm of a single part similar to the user's breathing frequency, the user is gradually brought into a sleep state. If the user is not lying down, the upper limit of the air pressure of the second air spring layer 3 is reduced by 50%, and the air pressure of the second air spring layer 3 rises and falls within the range of 8kpa-10kpa above the standard atmospheric pressure.

[0068] In the fifth step, after the rhythm component completes its movements in the selected operating mode, it transitions to the third step until the preset total running time is reached, at which point it shuts down. By switching to the third step, the system monitors the user's real-time physiological data and adjusts the operating mode of the rhythm component to meet the differentiated rhythmic needs of the user at different times due to varying degrees of relaxation.

[0069] Example 2:

[0070] Compared to Embodiment 1, this embodiment provides a system.

[0071] As shown in Figure 2, a system using the aforementioned rhythm control method includes a user data acquisition module, a physiological data acquisition module, a rhythm module, a data storage module, a stress detection module, and a processing module. The system obtains basic data that meets the user's experience needs from a basic database by collecting user information. During system operation, the system monitors the user's physiological data in real time and calculates a relaxation index. The system uses the relaxation index to compare with multi-level relaxation thresholds to select the operating mode of the rhythm component, ensuring that the system can adjust the rhythm component in real time according to the user's real-time state, thereby improving the system's relaxation and sleep-aiding effect.

[0072] In this embodiment, the user data acquisition module is used to collect user information and transmit it to the processing module. The user sends user information to the processing module through human-computer interaction, so that the processing module can find the corresponding basic parameters in the basic database based on the user information.

[0073] In this embodiment, the physiological data acquisition module is used to collect the user's physiological data and transmit it to the processing module. The physiological data includes heart rate data and respiratory data, including but not limited to wristbands, watches or other physiological monitoring devices, all of which should be considered as specific implementations of this embodiment.

[0074] In this embodiment, the rhythm module receives and executes instructions sent by the processing module. The rhythm module includes a rhythm component and an inflation / deflation component that drives the rhythm component to move, so that the rhythm component forms a rhythmic stimulus applied to the user under the drive of the inflation / deflation component.

[0075] In this embodiment, the data storage module is used to store the basic database, the maximum value of the inhalation frequency RF_max, the minimum value of the respiratory frequency RF_min, the maximum value of the heart rate variability HRV_max, the minimum value of the heart rate variability HRV_min, the average real-time respiratory rate RF_current, the average real-time heart rate variability HRV_current, the multi-level relaxation threshold, the conversion method of the basic parameters by the rhythm component in each mode, and the program required to run the method.

[0076] In this embodiment, the pressure detection module monitors the pressure conditions in each area and transmits the pressure change data of each area to the processing module to assist the processing module in calculating the user's posture, thereby adjusting and correcting the basic parameters in each mode and effectively improving the user experience.

[0077] In this embodiment, the processing module obtains the corresponding basic parameters by comparing the user information provided by the user data acquisition module in the basic database, calculates the relaxation index based on the physiological data provided by the physiological data acquisition module, and sends the corresponding mode instruction to the rhythm module after comparing it with the multi-level relaxation threshold.

[0078] The other features and effects of the rhythm control method described in this embodiment are the same as those in Embodiment 1, and will not be repeated here.

[0079] Example 3

[0080] Compared to Embodiment 1, this embodiment provides a mattress.

[0081] As shown in Figure 3, a mattress using the aforementioned rhythmic control method includes a mattress body and a control box 1. The mattress body houses a rhythmic component, which comprises a first air spring layer 2 and a second air spring layer 3 stacked sequentially from top to bottom. The control box 1 controls the independent operation of the first air spring layer 2 and the second air spring layer 3, allowing the rhythmic component to switch between various modes. The second air spring layer 3 and the first air spring layer 2 are stacked to form the rhythmic component. The control box 1 controls the coordinated movement of the first air spring layer 2 and the second air spring layer 3 to apply rhythmic stimulation to the user in a specified mode.

[0082] In this embodiment, the top surface of the first air spring layer 2 is completely covered by the first comfort layer 4, and the top surface of the second air spring layer 3 is completely covered by the second comfort layer 5. The first comfort layer 4, the first air spring layer 2, the second comfort layer 5, and the second air spring layer 3 are stacked sequentially from top to bottom. The vertical projections of the first comfort layer 4, the first air spring layer 2, the second comfort layer 5, and the second air spring layer 3 overlap, so that each area of ​​the mattress has the same structure, ensuring that each area can achieve rhythmic coordination as needed.

[0083] In this embodiment, the top surface of the mattress is divided into several zones. The first air spring layer 2 and the second air spring layer 3 can be independently inflated and deflated to the areas corresponding to each zone, ensuring that each zone achieves rhythmic coordination and provides differentiated rhythmic stimulation to the user.

[0084] In this embodiment, the pressure detection layer 6 is disposed between the first air spring layer 2 and the second comfort layer 5 to detect the force on each area of ​​the mattress, thereby facilitating the identification of the user's sleeping posture.

[0085] In this embodiment, a physiological data detector 7 is provided between the first air spring layer 2 and the second air spring layer 3. The physiological data detector 7 is located between the second comfort layer 5 and the first air spring layer 2, and its position corresponds vertically to the user's chest position. By shortening the distance between the detector and the user's heart, the monitoring accuracy is improved, thus enhancing the accuracy of the monitoring data.

[0086] The other features and effects of the rhythm control method described in this embodiment are the same as those in Embodiment 1, and will not be repeated here.

Claims

1. A rhythmic control method based on user relaxation state assessment, used to control a rhythmic component, characterized in that, The method is implemented through the following steps: The first step is to collect user information and compare it with the basic database to obtain the basic parameters used to control the rhythm component; The second step involves monitoring and collecting heart rate and respiratory rate data during the user's transition from a quiet state to a deep relaxation state, and then calculating a set of relaxation parameters. The third step is to intermittently monitor the user during the relaxation process to obtain the user's real-time heart rate and respiratory rate data, and calculate the relaxation index through the relaxation parameter set. The fourth step is to set multiple relaxation thresholds and rate the relaxation index, and adjust the operating mode of the rhythm component according to the rating results. In the fifth step, the rhythm component completes its action in the selected running mode and then proceeds to the third step until the preset total running time is reached and then it closes.

2. The rhythmic control method based on user relaxation state assessment according to claim 1, characterized in that, In the first step, the basic database includes several data groups, each including user information and corresponding basic parameters. The basic database obtains the corresponding data groups and then the corresponding basic parameters by collecting user information. Alternatively, the user information includes the user's gender, age, height, and weight. Or, the basic parameters include the maximum air pressure of the rhythm component, the movement part, the preset lifting height, the basic frequency, and the movement duration.

3. The rhythmic control method based on user relaxation state assessment according to claim 1, characterized in that, In the second step, the relaxation parameter set includes the maximum heart rate variability (HRV_max) and the minimum heart rate variability (HRV_min), which are obtained through the following steps: First, heart rate data is collected during the transition process; then, the transition process is divided into multiple time units, and the time interval between adjacent heartbeats within each time unit is statistically analyzed to form a unit heart rate dataset; next, the data within the unit heart rate dataset is sequentially subjected to cumulative average calculation, variance calculation, and standard deviation calculation to obtain the unit heart rate variability parameters; finally, the calculated unit heart rate variability parameters are compared to obtain the maximum heart rate variability (HRV_max) and the minimum heart rate variability (HRV_min). The minimum variability value is HRV_min; or, in the second step, the relaxation parameter set includes the maximum respiratory rate RF_max and the minimum respiratory rate RF_min, which are obtained through the following steps: First, collect respiratory data during the transition process; then, divide the transition process into multiple unit time periods, statistically analyze the respiratory rate within each unit time period, and form a unit respiratory dataset; next, calculate the cumulative average of the data within the unit respiratory dataset to obtain the unit respiratory rate parameter; finally, compare the calculated unit respiratory rate parameters to obtain the maximum respiratory rate RF_max and the minimum respiratory rate RF_min.

4. A rhythmic control method based on user relaxation state assessment according to any one of claims 1-3, characterized in that, In the third step, the unit monitoring duration and the downtime between adjacent unit monitoring durations are set to perform intermittent monitoring of the user. The single monitoring duration includes at least two consecutive set unit time periods. Real-time heart rate data and real-time respiratory rate data are collected in each unit time period and the average real-time heart rate variability HRV_current and the average real-time respiratory rate RF_current are calculated respectively. The results are then converted into a relaxation index RELAX corresponding to the unit monitoring duration.

5. The rhythmic control method based on user relaxation state assessment according to claim 4, characterized in that, The relaxation index RELAX is calculated using the following formula: RELAX=(HRV_current-HRV_min) / (HRV_max-HRV_min) +(RF_max-RF_current) / (RF_max-RF_min); Alternatively, the real-time unit heart rate variability parameter can be obtained by statistically analyzing the time interval between adjacent heartbeats in the real-time heart rate data within a unit time period and then performing cumulative average, variance, and standard deviation calculations in sequence. The real-time unit heart rate variability parameter is used to obtain the real-time heart rate variability mean HRV_current through cumulative average. When the real-time unit heart rate variability parameter is greater than the maximum heart rate variability HRV_max, the real-time unit heart rate variability parameter is corrected to the maximum heart rate variability HRV_max. When the real-time unit heart rate variability parameter is less than the minimum heart rate variability HRV_min, the real-time unit heart rate variability parameter is corrected to the minimum heart rate variability HRV_min. Alternatively, the real-time unit respiratory rate parameter can be obtained by averaging the real-time respiratory rate data within a unit time period. The real-time unit respiratory rate parameter is averaged to obtain the real-time respiratory rate average RF_current. When the real-time unit respiratory rate parameter is greater than the maximum respiratory rate RF_max, the real-time unit respiratory rate parameter is corrected to the maximum respiratory rate RF_max. When the real-time unit respiratory rate parameter is less than the minimum heart rate variability HRV_min, the real-time unit respiratory rate parameter is corrected to the minimum respiratory rate RF_min.

6. The rhythmic control method based on user relaxation state assessment according to claim 4, characterized in that, In the fourth step, the rhythm component includes a second air spring layer (3) and a first air spring layer (2) that completely covers the second air spring layer (3). The multi-level relaxation threshold includes a first-level relaxation threshold TH1_relax and a second-level relaxation threshold TH2_relax that increase step by step. When RELAX < TH1_relax, the rhythm component is controlled to operate in mode one. When TH1_relax ≤ RELAX < TH2_relax, the rhythm component is controlled to operate in mode two. When TH2_relax ≤ RELAX, the rhythm component is controlled to operate in mode three.

7. The rhythmic control method based on user relaxation state assessment according to claim 6, characterized in that, In mode one, the first air spring layer (2) and the second air spring layer (3) are inflated and deflated simultaneously. The first air spring layer (2) rises and falls between 0% and 100% of the preset lifting height. The air pressure of the second air spring layer (3) rises and falls within the range of 8 kPa to 20 kPa higher than the standard atmospheric pressure. The inflation and deflation frequency is the basic frequency. The action parts correspond to the user's waist and back. The duration is 10% to 30% of the action duration. If the user is not lying down, the upper limit of the lifting height of the first air spring layer (2) is reduced by 50%, and the upper limit of the air pressure of the second air spring layer (3) is reduced by 50%. Alternatively, in mode two, the first air spring layer (2) switches between 0-80% of the preset lifting height. The inflation and deflation frequency of the first air spring layer (2) is the average real-time breathing frequency RF_current of 100%-110%. The second air spring layer (3) maintains a constant pressure state at an air pressure 15 kPa higher than the standard atmospheric pressure. The movement parts correspond to the user's shoulders, hips, waist and back. The duration is 10%-30% of the movement duration. The rhythm amplitude gradually decreases from 80% to 50% of the preset lifting height. If the user is not lying down, the upper limit of the lifting height of the first air spring layer (2) is reduced by 50%. Alternatively, in mode three, the first air spring layer (2) is closed, and the air pressure of the second air spring layer (3) rises and falls within the range of 8 kPa-20 kPa higher than the standard atmospheric pressure. The inflation and deflation frequency of the first air spring layer (2) is 90%-100% of the average real-time breathing frequency RF_current. The movement part corresponds to the user's shoulder, hip, leg, waist and back, and the duration is 10%-30% of the movement duration. If the user is not lying down, the upper limit of the air pressure of the second air spring layer (3) is reduced by 50%.

8. A system using the rhythm control method of any one of claims 1-7, characterized in that, include: The user data collection module is used to collect user information and transmit it to the processing module. The physiological data acquisition module is used to collect the user's physiological data and transmit it to the processing module. The physiological data includes heart rate data and respiratory data. The rhythm module receives and executes instructions sent by the processing module. The data storage module is used to store the basic database, the maximum value of the inhalation frequency RF_max, the minimum value of the respiratory frequency RF_min, the maximum value of the heart rate variability HRV_max, the minimum value of the heart rate variability HRV_min, the average real-time respiratory rate RF_current, the average real-time heart rate variability HRV_current, the multi-level relaxation threshold, and the conversion method of the basic parameters by the rhythm component in each mode. The pressure detection module monitors the pressure in each area and transmits the pressure change data of each area to the processing module to assist the processing module in calculating the user's posture. The processing module compares the user information provided by the user data acquisition module with the basic database to obtain the corresponding basic parameters, calculates the relaxation index based on the physiological data provided by the physiological data acquisition module, and sends the corresponding mode instruction to the rhythm module after comparing it with the multi-level relaxation threshold.

9. A mattress using the rhythmic control method of any one of claims 1-7, comprising a mattress body and a control box (1), characterized in that, The pad is equipped with a rhythm component, which includes a first air spring layer (2) and a second air spring layer (3) stacked from top to bottom. The control box (1) controls the first air spring layer (2) and the second air spring layer (3) to operate independently, so that the rhythm component can switch between various modes.

10. A mattress according to claim 9, characterized in that, The vertical projections of the first air spring layer (2) and the second air spring layer (3) are completely overlapped; or, the top surface of the first air spring layer (2) is completely covered by the first comfort layer (4); or, the top surface of the second air spring layer (3) is completely covered by the second comfort layer (5); or, a pressure detection layer (6) is provided below the first air spring layer (2); or, a physiological data detector (7) is provided between the first air spring layer (2) and the second air spring layer (3).

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