Intelligent rhythm mattress control method and system based on comfort analysis and medium

Abstract

The embodiment of the invention provides an intelligent rhythm mattress control method and system based on comfort analysis and a medium. The method comprises the steps of collecting physiological feature data and body pressure distribution data of sleep of a user, performing processing according to the physiological feature data and the body pressure distribution data to obtain a sleep comfort index, obtaining a sleep stage level according to the sleep comfort index, and performing processing in combination with rhythm preference data to obtain mattress rhythm control data, the mattress is regulated and controlled according to the mattress rhythm control data, the effect after regulation and control is checked, processing is carried out according to historical sleep data and historical sleep comfort degree indexes of a user, sleep rhythm effect data are obtained, the mattress rhythm regulation effect is evaluated, and the mattress rhythm regulation effect is obtained through comfort degree analysis, rhythm control generation, rhythm execution and dynamic regulation. Intelligent matching and dynamic optimization of rhythm and user comfort are realized, and the sleep comfort of the user is improved.

Description

Technical Field

[0001] This application relates to the field of smart home and health monitoring technology, and more specifically, to a rhythmic smart mattress control method, system, and readable storage medium based on comfort analysis. Background Technology

[0002] As people place increasing emphasis on sleep quality and healthy lifestyles, smart mattresses are gradually becoming an important part of home health products. Current smart mattresses primarily focus on basic functions such as temperature regulation, posture adjustment, and basic sleep monitoring, lacking the ability to dynamically sense and proactively adjust to user comfort. In particular, the rhythm function often uses fixed patterns, failing to personalize adjustments based on the user's real-time physiological state and physical comfort, resulting in poor rhythm effects and potentially even reducing sleep quality.

[0003] Therefore, relevant technical solutions are urgently needed to address the above problems. Summary of the Invention

[0004] The purpose of this application is to provide a rhythmic smart mattress control method, system, and readable storage medium based on comfort analysis, which can enhance the personalization and intelligence of mattress control and improve user experience.

[0005] This application also provides a rhythmic smart mattress control method based on comfort analysis, including the following steps: Collect physiological characteristics and body pressure distribution data of users' sleep; The sleep comfort index is obtained by processing the physiological characteristic data and body pressure distribution data. Sleep stage levels are obtained based on the sleep comfort index, and mattress rhythm control data is obtained by combining rhythm preference data processing. The mattress is adjusted based on the mattress rhythm control data, and the effect of the adjustment is verified. By processing users' historical sleep data and historical sleep comfort index, sleep rhythm effectiveness data is obtained to evaluate the effectiveness of mattress rhythm adjustment.

[0006] Optionally, in the rhythmic smart mattress control method based on comfort analysis described in the embodiments of this application, the collection of physiological characteristic data and body pressure distribution data of user sleep includes: The system collects physiological data on the user's sleep through a pre-set first device, including changes in heart rate, respiratory rate, skin conductivity, and body temperature. The second device is used to collect body pressure distribution data of the mattress, including pressure distribution, center of gravity offset, and pressure change frequency.

[0007] Optionally, in the rhythmic smart mattress control method based on comfort analysis described in the embodiments of this application, the step of processing the physiological characteristic data and body pressure distribution data to obtain a sleep comfort index includes: Based on the physiological characteristic data and body pressure distribution data, heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity are obtained respectively. The sleep comfort index is obtained by weighting the heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity.

[0008] Optionally, in the rhythmic smart mattress control method based on comfort analysis described in the embodiments of this application, the step of obtaining the sleep stage level according to the sleep comfort index and obtaining mattress rhythmic control data by combining rhythmic preference data processing includes: The sleep comfort index is compared with a preset sleep quality threshold to obtain the sleep stage level; The user's preset rhythm preference data is obtained and combined with the sleep stage level to obtain mattress rhythm control data; The sleep stages include light sleep, deep sleep, and REM sleep.

[0009] Optionally, in the rhythmic smart mattress control method based on comfort analysis described in the embodiments of this application, the step of adjusting the mattress according to the mattress rhythmic control data and verifying the effect after adjustment includes: The mattress rhythm control data includes rhythm parameters and rhythm patterns; The rhythm parameters include frequency, amplitude, waveform type, region, and duration; The rhythmic patterns include wave-like, breathing-like, pulse-like, and soothing patterns.

[0010] The mattress is adjusted based on the mattress rhythm control data. The physiological characteristics and body pressure distribution data of the user's sleep after adjustment are collected and processed to obtain the sleep comfort index after adjustment. The sleep comfort index after regulation is compared with the sleep comfort index before regulation, and the regulation effect is verified based on the comparison results.

[0011] Optionally, in the rhythmic smart mattress control method based on comfort analysis described in this application embodiment, the step of processing the user's historical sleep data and historical sleep comfort index to obtain sleep rhythm effectiveness data and evaluate the mattress rhythm adjustment effectiveness includes: Acquire multiple historical sleep data of users within a preset historical time period, including the duration of sleep onset, light sleep stage, deep sleep stage, and REM sleep stage for a single historical sleep node; The historical sleep data of the individual historical sleep node and the corresponding sleep comfort index are processed to obtain sleep season rhythm effect data. The sleep rhythm effect data of multiple historical sleep nodes are aggregated to obtain sleep rhythm effect data within a preset historical time period; The effectiveness of mattress rhythm regulation was evaluated based on the sleep rhythm effectiveness data.

[0012] Secondly, embodiments of this application provide a rhythmic intelligent mattress control system based on comfort analysis. The system includes a memory and a processor. The memory includes a program for a rhythmic intelligent mattress control method based on comfort analysis. When the program for the rhythmic intelligent mattress control method based on comfort analysis is executed by the processor, it implements the following steps: Collect physiological characteristics and body pressure distribution data of users' sleep; The sleep comfort index is obtained by processing the physiological characteristic data and body pressure distribution data. Sleep stage levels are obtained based on the sleep comfort index, and mattress rhythm control data is obtained by combining rhythm preference data processing. The mattress is adjusted based on the mattress rhythm control data, and the effect of the adjustment is verified. By processing users' historical sleep data and historical sleep comfort index, sleep rhythm effectiveness data is obtained to evaluate the effectiveness of mattress rhythm adjustment.

[0013] Optionally, in the rhythmic intelligent mattress control system based on comfort analysis described in the embodiments of this application, the collection of physiological characteristic data and body pressure distribution data of user sleep includes: The system collects physiological data on the user's sleep through a pre-set first device, including changes in heart rate, respiratory rate, skin conductivity, and body temperature. The second device is used to collect body pressure distribution data of the mattress, including pressure distribution, center of gravity offset, and pressure change frequency.

[0014] Optionally, in the rhythmic intelligent mattress control system based on comfort analysis described in this application embodiment, the step of processing the physiological characteristic data and body pressure distribution data to obtain a sleep comfort index includes: Based on the physiological characteristic data and body pressure distribution data, heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity are obtained respectively. The sleep comfort index is obtained by weighting the heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity.

[0015] Thirdly, embodiments of this application also provide a computer-readable storage medium, which includes a rhythmic smart mattress control method program based on comfort analysis. When the rhythmic smart mattress control method program based on comfort analysis is executed by a processor, it implements the steps of the rhythmic smart mattress control method based on comfort analysis as described in any of the above claims.

[0016] As can be seen from the above, the rhythmic smart mattress control method, system, and readable storage medium based on comfort analysis provided in this application collects physiological characteristic data and body pressure distribution data of the user's sleep, processes the physiological characteristic data and body pressure distribution data to obtain a sleep comfort index, obtains the sleep stage level based on the sleep comfort index, and obtains mattress rhythmic control data by combining rhythmic preference data. The mattress is adjusted based on the mattress rhythmic control data, and the effect of the adjustment is tested. The user's historical sleep data and historical sleep comfort index are processed to obtain sleep rhythmic effectiveness data, and the effectiveness of mattress rhythmic adjustment is evaluated. Through comfort analysis, rhythmic control generation, rhythmic execution, and dynamic adjustment, intelligent matching and dynamic optimization of rhythm and user comfort are achieved, thereby improving the user's sleep comfort.

[0017] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing embodiments of this application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart of a rhythmic smart mattress control method based on comfort analysis provided in an embodiment of this application.

[0020] Figure 2 A flowchart illustrating the sleep data acquisition process of the rhythmic smart mattress control method based on comfort analysis provided in this application embodiment.

[0021] Figure 3 A flowchart illustrating the comfort analysis process of the rhythmic smart mattress control method based on comfort analysis provided in this application embodiment. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0023] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0024] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a rhythmic smart mattress control method based on comfort analysis in some embodiments of this application. This method is used in terminal devices such as mobile phones and computers. The method includes the following steps: S11. Collect physiological characteristic data and body pressure distribution data of the user's sleep; S12. Process the physiological characteristic data and body pressure distribution data to obtain the sleep comfort index; S13. Obtain the sleep stage level based on the sleep comfort index, and obtain mattress rhythm control data by combining rhythm preference data processing. S14. Adjust the mattress according to the mattress rhythm control data and check the effect after adjustment; S15. Process the user's historical sleep data and historical sleep comfort index to obtain sleep rhythm effectiveness data and evaluate the effectiveness of mattress rhythm adjustment.

[0025] This process involves collecting physiological characteristic data and body pressure distribution data of the user's sleep, processing this data to obtain a sleep comfort index, determining the sleep stage level based on the sleep comfort index, and combining this with rhythm preference data to obtain mattress rhythm control data. The mattress is then adjusted based on this rhythm control data, and the effect of the adjustment is verified. Finally, historical sleep data and historical sleep comfort indices of the user are processed to obtain sleep rhythm effectiveness data, evaluating the effectiveness of mattress rhythm adjustment. Through comfort analysis, rhythm control generation, rhythm execution, and dynamic adjustment, intelligent matching and dynamic optimization of rhythm and user comfort are achieved, thereby improving the user's sleep comfort.

[0026] Please refer to Figure 2 , Figure 2 This is a flowchart illustrating the sleep data acquisition process of a rhythmic smart mattress controlled based on comfort analysis, as described in some embodiments of this application. According to embodiments of the present invention, the acquisition of the user's physiological characteristics and body pressure distribution data during sleep specifically includes: S21. Collect physiological characteristic data of the user's sleep through a preset first device, including heart rate changes, respiratory rate, skin conductivity and body temperature changes; S22. Collect body pressure distribution data of the mattress through a preset second device, including pressure distribution, center of gravity offset and pressure change frequency.

[0027] The system collects real-time physiological data of the user's sleep, including heart rate, body temperature, and respiratory sensors, through a first preset device such as the user's sleep wearable device. This data includes heart rate changes, respiratory rate, skin conductivity, and body temperature changes. The system also collects body pressure distribution data of the mattress through a second preset device such as multi-point sensors deployed on the mattress surface. This data includes pressure distribution, center of gravity shift, and pressure change frequency. The data collection frequency is once per minute or higher to ensure the accuracy of the captured dynamic change data.

[0028] Please refer to Figure 3 , Figure 3 This is a flowchart illustrating the comfort analysis process of a rhythmic smart mattress control system based on comfort analysis in some embodiments of this application. According to an embodiment of the present invention, the step of processing the physiological characteristic data and body pressure distribution data to obtain a sleep comfort index specifically involves: S31. Process the physiological characteristic data and body pressure distribution data to obtain heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity, respectively. S32. The sleep comfort index is obtained by weighting the heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity.

[0029] The process involves processing heart rate changes and respiratory rate based on physiological characteristic data and body pressure distribution data, as well as pressure distribution and pressure change frequency. Heart rate fluctuation data is calculated based on the standard deviation of heart rate changes over a period of time, and respiratory rate stability is calculated based on the standard deviation of respiratory rate over a period of time. Effective pressure (e.g., by setting a threshold of 0.5 kPa), the proportion of effective pressure points, and the deviation of each effective pressure point from the set target uniform pressure are selected through a preset screening method based on pressure distribution and pressure change frequency. The number of points with pressure values ​​within the range of "P×(1-ε) - P×(1+ε)" (ε is the allowable deviation, such as ε=10%) is counted. Then, the pressure distribution uniformity = (number of points within the range / total number of points) × 100%. The closer the value is to 100%, the higher the uniformity. Finally, the sleep comfort index C is obtained by weighted calculation based on heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity. The comfort index can be used to diagnose the user's sleep stage.

[0030] According to an embodiment of the present invention, obtaining the sleep stage level based on the sleep comfort index and obtaining mattress rhythm control data by combining rhythm preference data processing specifically includes: The sleep comfort index is compared with a preset sleep quality threshold to obtain the sleep stage level; The user's preset rhythm preference data is obtained and combined with the sleep stage level to obtain mattress rhythm control data; The sleep stages include light sleep, deep sleep, and REM sleep.

[0031] The process involves comparing the sleep comfort index with a preset sleep quality threshold. The corresponding sleep stage level is determined based on the range within which the threshold comparison results fall. Then, the user's preset rhythm preference data, including rhythm frequency and amplitude, is acquired and processed using a rhythm control recognition model in conjunction with the sleep stage level to obtain mattress rhythm control data. This rhythm control recognition model is a neural network model trained on rhythm frequency, amplitude, and sleep stage level to obtain mattress rhythm control data. The sleep stage levels include light sleep, deep sleep, and REM sleep. For example, in this embodiment, if the calculated sleep comfort index is 0.3, its corresponding sleep quality distribution threshold range is [0.25, 0.35), corresponding to a light sleep stage. In the light sleep stage, the rhythm frequency and amplitude are adjusted first to help the user enter deep sleep faster. In the deep sleep stage, rhythm adjustments are reduced, with fine-tuning only performed when problems such as uneven pressure distribution or high heart rate occur.

[0032] According to an embodiment of the present invention, adjusting the mattress based on the mattress rhythm control data and verifying the effect after adjustment includes: The mattress rhythm control data includes rhythm parameters and rhythm patterns; The rhythm parameters include frequency, amplitude, waveform type, region, and duration; The rhythmic patterns include wave-like, breathing-like, pulse-like, and soothing patterns.

[0033] The mattress is adjusted based on the mattress rhythm control data. The physiological characteristics and body pressure distribution data of the user's sleep after adjustment are collected and processed to obtain the sleep comfort index after adjustment. The sleep comfort index after regulation is compared with the sleep comfort index before regulation, and the regulation effect is verified based on the comparison results.

[0034] The mattress rhythm control data includes rhythm parameters and rhythm modes. Rhythm parameters include frequency, amplitude, waveform type, region, and duration. Rhythm modes include wave-like, breathing-like, pulse-like, and soothing modes. The mattress is adjusted based on the rhythm control data. Then, the user's physiological characteristics and body pressure distribution data after adjustment are collected and processed to obtain a sleep comfort index. The sleep comfort index after adjustment is compared with the sleep comfort index before mattress adjustment. If the index increases, the mattress adjustment is effective. Subsequently, the mattress rhythm strategy is continuously and dynamically adjusted based on the sleep comfort index to achieve a precise match between the rhythm and the user's physiological state, thereby continuously improving sleep comfort.

[0035] According to an embodiment of the present invention, the step of processing the user's historical sleep data and historical sleep comfort index to obtain sleep rhythm effectiveness data and evaluating the effectiveness of mattress rhythm adjustment specifically includes: Acquire multiple historical sleep data of users within a preset historical time period, including the duration of sleep onset, light sleep stage, deep sleep stage, and REM sleep stage for a single historical sleep node; The historical sleep data of the individual historical sleep node and the corresponding sleep comfort index are processed to obtain sleep season rhythm effect data. The sleep rhythm effect data of multiple historical sleep nodes are aggregated to obtain sleep rhythm effect data within a preset historical time period; The effectiveness of mattress rhythm regulation was evaluated based on the sleep rhythm effectiveness data.

[0036] This process involves acquiring multiple historical sleep data points from a user within a preset historical time period, including the duration of sleep onset, light sleep, deep sleep, and REM sleep at individual historical sleep nodes. The historical sleep data for each individual node is processed along with its corresponding sleep comfort index. A weight is assigned to each sleep node, and a weighted average method is used to calculate the sleep rhythm effect data based on the duration of each node. Deep sleep and REM sleep have relatively high weights because they have a greater impact on sleep quality. The sleep rhythm effect data from multiple historical sleep nodes are aggregated to obtain sleep rhythm effectiveness data for the preset historical time period. The effectiveness of mattress rhythm adjustment is evaluated based on this sleep rhythm effectiveness data, optimizing the mattress's personalized rhythm strategy to better suit the user's current physical state and different users' sleep preferences, forming a closed-loop continuous optimization mechanism for the rhythm strategy.

[0037] This invention also discloses a rhythmic intelligent mattress control system based on comfort analysis, including a memory and a processor. The memory includes a program for a rhythmic intelligent mattress control method based on comfort analysis. When the processor executes the program for the rhythmic intelligent mattress control method based on comfort analysis, it performs the following steps: Collect physiological characteristics and body pressure distribution data of users' sleep; The sleep comfort index is obtained by processing the physiological characteristic data and body pressure distribution data. Sleep stage levels are obtained based on the sleep comfort index, and mattress rhythm control data is obtained by combining rhythm preference data processing. The mattress is adjusted based on the mattress rhythm control data, and the effect of the adjustment is verified. By processing users' historical sleep data and historical sleep comfort index, sleep rhythm effectiveness data is obtained to evaluate the effectiveness of mattress rhythm adjustment.

[0038] This process involves collecting physiological characteristic data and body pressure distribution data of the user's sleep, processing this data to obtain a sleep comfort index, determining the sleep stage level based on the sleep comfort index, and combining this with rhythm preference data to obtain mattress rhythm control data. The mattress is then adjusted based on this rhythm control data, and the effect of the adjustment is verified. Finally, historical sleep data and historical sleep comfort indices of the user are processed to obtain sleep rhythm effectiveness data, evaluating the effectiveness of mattress rhythm adjustment. Through comfort analysis, rhythm control generation, rhythm execution, and dynamic adjustment, intelligent matching and dynamic optimization of rhythm and user comfort are achieved, thereby improving the user's sleep comfort.

[0039] According to an embodiment of the present invention, the collection of physiological characteristic data and body pressure distribution data of user sleep specifically includes: The system collects physiological data on the user's sleep through a pre-set first device, including changes in heart rate, respiratory rate, skin conductivity, and body temperature. The second device is used to collect body pressure distribution data of the mattress, including pressure distribution, center of gravity offset, and pressure change frequency.

[0040] The system collects real-time physiological data of the user's sleep, including heart rate, body temperature, and respiratory sensors, through a first preset device such as the user's sleep wearable device. This data includes heart rate changes, respiratory rate, skin conductivity, and body temperature changes. The system also collects body pressure distribution data of the mattress through a second preset device such as multi-point sensors deployed on the mattress surface. This data includes pressure distribution, center of gravity shift, and pressure change frequency. The data collection frequency is once per minute or higher to ensure the accuracy of the captured dynamic change data.

[0041] According to an embodiment of the present invention, the step of processing the physiological characteristic data and body pressure distribution data to obtain the sleep comfort index specifically involves: Based on the physiological characteristic data and body pressure distribution data, heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity are obtained respectively. The sleep comfort index is obtained by weighting the heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity.

[0042] The process involves processing heart rate changes and respiratory rate based on physiological characteristic data and body pressure distribution data, as well as pressure distribution and pressure change frequency. Heart rate fluctuation data is calculated based on the standard deviation of heart rate changes over a period of time, and respiratory rate stability is calculated based on the standard deviation of respiratory rate over a period of time. Effective pressure (e.g., by setting a threshold of 0.5 kPa), the proportion of effective pressure points, and the deviation of each effective pressure point from the set target uniform pressure are selected through a preset screening method based on pressure distribution and pressure change frequency. The number of points with pressure values ​​within the range of "P×(1-ε) - P×(1+ε)" (ε is the allowable deviation, such as ε=10%) is counted. Then, the pressure distribution uniformity = (number of points within the range / total number of points) × 100%. The closer the value is to 100%, the higher the uniformity. Finally, the sleep comfort index C is obtained by weighted calculation based on heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity. The comfort index can be used to diagnose the user's sleep stage.

[0043] According to an embodiment of the present invention, obtaining the sleep stage level based on the sleep comfort index and obtaining mattress rhythm control data by combining rhythm preference data processing specifically includes: The sleep comfort index is compared with a preset sleep quality threshold to obtain the sleep stage level; The user's preset rhythm preference data is obtained and combined with the sleep stage level to obtain mattress rhythm control data; The sleep stages include light sleep, deep sleep, and REM sleep.

[0044] The process involves comparing the sleep comfort index with a preset sleep quality threshold. The corresponding sleep stage level is determined based on the range within which the threshold comparison results fall. Then, the user's preset rhythm preference data, including rhythm frequency and amplitude, is acquired and processed using a rhythm control recognition model in conjunction with the sleep stage level to obtain mattress rhythm control data. This rhythm control recognition model is a neural network model trained on rhythm frequency, amplitude, and sleep stage level to obtain mattress rhythm control data. The sleep stage levels include light sleep, deep sleep, and REM sleep. For example, in this embodiment, if the calculated sleep comfort index is 0.3, its corresponding sleep quality distribution threshold range is [0.25, 0.35), corresponding to a light sleep stage. In the light sleep stage, the rhythm frequency and amplitude are adjusted first to help the user enter deep sleep faster. In the deep sleep stage, rhythm adjustments are reduced, with fine-tuning only performed when problems such as uneven pressure distribution or high heart rate occur.

[0045] According to an embodiment of the present invention, adjusting the mattress based on the mattress rhythm control data and verifying the effect after adjustment includes: The mattress rhythm control data includes rhythm parameters and rhythm patterns; The rhythm parameters include frequency, amplitude, waveform type, region, and duration; The rhythmic patterns include wave-like, breathing-like, pulse-like, and soothing patterns.

[0046] The mattress is adjusted based on the mattress rhythm control data. The physiological characteristics and body pressure distribution data of the user's sleep after adjustment are collected and processed to obtain the sleep comfort index after adjustment. The sleep comfort index after regulation is compared with the sleep comfort index before regulation, and the regulation effect is verified based on the comparison results.

[0047] The mattress rhythm control data includes rhythm parameters and rhythm modes. Rhythm parameters include frequency, amplitude, waveform type, region, and duration. Rhythm modes include wave-like, breathing-like, pulse-like, and soothing modes. The mattress is adjusted based on the rhythm control data. Then, the user's physiological characteristics and body pressure distribution data after adjustment are collected and processed to obtain a sleep comfort index. The sleep comfort index after adjustment is compared with the sleep comfort index before mattress adjustment. If the index increases, the mattress adjustment is effective. Subsequently, the mattress rhythm strategy is continuously and dynamically adjusted based on the sleep comfort index to achieve a precise match between the rhythm and the user's physiological state, thereby continuously improving sleep comfort.

[0048] According to an embodiment of the present invention, the step of processing the user's historical sleep data and historical sleep comfort index to obtain sleep rhythm effectiveness data and evaluating the effectiveness of mattress rhythm adjustment specifically includes: Acquire multiple historical sleep data of users within a preset historical time period, including the duration of sleep onset, light sleep stage, deep sleep stage, and REM sleep stage for a single historical sleep node; The historical sleep data of the individual historical sleep node and the corresponding sleep comfort index are processed to obtain sleep season rhythm effect data. The sleep rhythm effect data of multiple historical sleep nodes are aggregated to obtain sleep rhythm effect data within a preset historical time period; The effectiveness of mattress rhythm regulation was evaluated based on the sleep rhythm effectiveness data.

[0049] This process involves acquiring multiple historical sleep data points from a user within a preset historical time period, including the duration of sleep onset, light sleep, deep sleep, and REM sleep at individual historical sleep nodes. The historical sleep data for each individual node is processed along with its corresponding sleep comfort index. A weight is assigned to each sleep node, and a weighted average method is used to calculate the sleep rhythm effect data based on the duration of each node. Deep sleep and REM sleep have relatively high weights because they have a greater impact on sleep quality. The sleep rhythm effect data from multiple historical sleep nodes are aggregated to obtain sleep rhythm effectiveness data for the preset historical time period. The effectiveness of mattress rhythm adjustment is evaluated based on this sleep rhythm effectiveness data, optimizing the mattress's personalized rhythm strategy to better suit the user's current physical state and different users' sleep preferences, forming a closed-loop continuous optimization mechanism for the rhythm strategy.

[0050] A third aspect of the present invention provides a readable storage medium including a rhythmic smart mattress control method program based on comfort analysis, wherein when the rhythmic smart mattress control method program based on comfort analysis is executed by a processor, it implements the steps of the rhythmic smart mattress control method based on comfort analysis as described in any of the preceding claims.

[0051] This invention discloses a rhythmic intelligent mattress control method, system, and readable storage medium based on comfort analysis. It collects physiological characteristic data and body pressure distribution data of the user's sleep, processes this data to obtain a sleep comfort index, determines the sleep stage level based on the index, and combines this with rhythmic preference data to obtain mattress rhythmic control data. The mattress is then adjusted based on this data, and the effect of the adjustment is verified. Furthermore, historical sleep data and historical sleep comfort indices of the user are processed to obtain sleep rhythmic effectiveness data, evaluating the effectiveness of the mattress rhythmic adjustment. Through comfort analysis, rhythmic control generation, rhythmic execution, and dynamic adjustment, intelligent matching and dynamic optimization of rhythm and user comfort are achieved, thereby improving user sleep comfort.

[0052] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0053] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units. They may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0054] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0055] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0056] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A rhythmic intelligent mattress control method based on comfort analysis, characterized in that, Includes the following steps: Collect physiological characteristics and body pressure distribution data of users' sleep; The sleep comfort index is obtained by processing the physiological characteristic data and body pressure distribution data. Sleep stage levels are obtained based on the sleep comfort index, and mattress rhythm control data is obtained by combining rhythm preference data processing. The mattress is adjusted based on the mattress rhythm control data, and the effect of the adjustment is verified. By processing users' historical sleep data and historical sleep comfort index, sleep rhythm effectiveness data is obtained to evaluate the effectiveness of mattress rhythm adjustment.

2. The rhythmic intelligent mattress control method based on comfort analysis according to claim 1, characterized in that, The collected physiological characteristic data and body pressure distribution data of user sleep include: The system collects physiological data on the user's sleep through a pre-set first device, including changes in heart rate, respiratory rate, skin conductivity, and body temperature. The second device is used to collect body pressure distribution data of the mattress, including pressure distribution, center of gravity offset, and pressure change frequency.

3. The rhythmic intelligent mattress control method based on comfort analysis according to claim 2, characterized in that, The process of processing the physiological characteristic data and body pressure distribution data to obtain the sleep comfort index includes: Based on the physiological characteristic data and body pressure distribution data, heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity are obtained respectively. The sleep comfort index is obtained by weighting the heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity.

4. The rhythmic intelligent mattress control method based on comfort analysis according to claim 1, characterized in that, The process of obtaining sleep stage levels based on the sleep comfort index and processing rhythm preference data to obtain mattress rhythm control data includes: The sleep comfort index is compared with a preset sleep quality threshold to obtain the sleep stage level; The user's preset rhythm preference data is obtained and combined with the sleep stage level to obtain mattress rhythm control data; The sleep stages include light sleep, deep sleep, and REM sleep.

5. The rhythmic intelligent mattress control method based on comfort analysis according to claim 1, characterized in that, The step of adjusting the mattress based on the mattress rhythm control data and verifying the effect after adjustment includes: The mattress rhythm control data includes rhythm parameters and rhythm patterns; The rhythm parameters include frequency, amplitude, waveform type, region, and duration; The rhythmic patterns include wave-like, breathing-like, pulse-like, and soothing patterns. The mattress is adjusted based on the mattress rhythm control data. The physiological characteristics and body pressure distribution data of the user's sleep after adjustment are collected and processed to obtain the sleep comfort index after adjustment. The sleep comfort index after regulation is compared with the sleep comfort index before regulation, and the regulation effect is verified based on the comparison results.

6. The rhythmic intelligent mattress control method based on comfort analysis according to claim 1, characterized in that, The process involves processing the user's historical sleep data and historical sleep comfort index to obtain sleep rhythm effectiveness data, and evaluating the mattress's rhythm adjustment effectiveness, including: Acquire multiple historical sleep data of users within a preset historical time period, including the duration of sleep onset, light sleep stage, deep sleep stage, and REM sleep stage for a single historical sleep node; The historical sleep data of the individual historical sleep node and the corresponding sleep comfort index are processed to obtain sleep season rhythm effect data. The sleep rhythm effect data of multiple historical sleep nodes are aggregated to obtain sleep rhythm effect data within a preset historical time period; The effectiveness of mattress rhythm regulation was evaluated based on the sleep rhythm effectiveness data.

7. A rhythmic intelligent mattress control system based on comfort analysis, characterized in that, The system includes a memory and a processor. The memory contains a program for a rhythmic intelligent mattress control method based on comfort analysis. When the program for the rhythmic intelligent mattress control method based on comfort analysis is executed by the processor, it performs the following steps: Collect physiological characteristics and body pressure distribution data of users' sleep; The sleep comfort index is obtained by processing the physiological characteristic data and body pressure distribution data. Sleep stage levels are obtained based on the sleep comfort index, and mattress rhythm control data is obtained by combining rhythm preference data processing. The mattress is adjusted based on the mattress rhythm control data, and the effect of the adjustment is verified. By processing users' historical sleep data and historical sleep comfort index, sleep rhythm effectiveness data is obtained to evaluate the effectiveness of mattress rhythm adjustment.

8. The rhythmic intelligent mattress control system based on comfort analysis according to claim 7, characterized in that, The collected physiological characteristic data and body pressure distribution data of user sleep include: The system collects physiological data on the user's sleep through a pre-set first device, including changes in heart rate, respiratory rate, skin conductivity, and body temperature. The second device is used to collect body pressure distribution data of the mattress, including pressure distribution, center of gravity offset, and pressure change frequency.

9. The rhythmic intelligent mattress control system based on comfort analysis according to claim 8, characterized in that, The process of processing the physiological characteristic data and body pressure distribution data to obtain the sleep comfort index includes: Based on the physiological characteristic data and body pressure distribution data, heart rate fluctuation data, respiratory rate stability and pressure distribution uniformity are obtained respectively. The sleep comfort index is obtained by weighting the heart rate fluctuation data, respiratory rate stability, and pressure distribution uniformity.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a rhythmic smart mattress control method program based on comfort analysis. When the rhythmic smart mattress control method program based on comfort analysis is executed by a processor, it implements the steps of the rhythmic smart mattress control method based on comfort analysis as described in any one of claims 1 to 6.

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