Intelligent mattress temperature control method and intelligent mattress temperature control device

Abstract

The invention relates to the technical field of temperature control, and discloses an intelligent mattress temperature control method and an intelligent mattress temperature control device, which are characterized in that a recommended temperature value suitable for a user is accurately calculated by acquiring user portrait information and an environment temperature value, and a mattress is controlled to adjust the temperature according to the recommended temperature value. According to individual differences of different users and real-time environment temperature changes, personalized accurate adjustment of the temperature of the mattress can be realized, so that the problem of sleep quality reduction caused by uncomfortable temperature of the mattress can be effectively avoided, a more comfortable and suitable sleep environment is provided for the user, the user can fall asleep more quickly, and the sleep quality of the user is improved. And the sleep depth and quality are improved, so that the body rest and recovery are better promoted, and the sleep experience and life quality of the user are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of temperature control technology, and in particular to a smart mattress temperature control method and a smart mattress temperature control device. Background Technology

[0002] As people's living standards improve, their demands for sleep quality are also increasing. As a crucial component of sleep, the mattress has a significant impact on sleep quality. A comfortable sleep environment not only helps people fall asleep faster but also improves sleep depth and quality, allowing the body to rest and recover better.

[0003] Currently, although traditional smart mattresses have temperature regulation functions, they cannot personalize the temperature according to different users and ambient temperatures, which may cause users to have their sleep quality affected by the uncomfortable mattress temperature during sleep.

[0004] Therefore, developing an intelligent control method that can personalize mattress temperature adjustment based on different users and ambient temperatures is of significant practical importance.

[0005] The above information is provided as background information only to aid in understanding the present invention, and does not constitute an assertion or admission that any of the above content can be used as prior art relative to the present invention. Summary of the Invention

[0006] This invention provides a method and device for intelligent mattress temperature control, enabling personalized temperature adjustment and improving users' sleep quality.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] In a first aspect, the present invention provides a method for intelligent temperature control of a mattress, the method comprising:

[0009] S101. Obtain user profile information and ambient temperature value;

[0010] S102. Calculate and determine the recommended temperature value based on the user profile information and the ambient temperature value;

[0011] S103. Control the mattress to adjust the temperature according to the recommended temperature value.

[0012] Furthermore, in the intelligent mattress temperature control method, the user profile information includes gender, age, BMI, and temperature preference type;

[0013] The types of cold and heat preferences include those who are sensitive to cold, those who are neutral, and those who are sensitive to heat.

[0014] Furthermore, in the intelligent mattress temperature control method, step S102 includes:

[0015] S1021. Based on the user profile information and the ambient temperature value, the recommended temperature value is calculated and determined according to the following formula:

[0016] ;

[0017] in, Recommended temperature value, To maintain a fixed temperature value, The values ​​corresponding to gender are: The values ​​corresponding to age. The value corresponding to BMI. The values ​​corresponding to the warm / cold preference type. The values ​​corresponding to the ambient temperature are... , , , , These are the corresponding weighting coefficients.

[0018] Furthermore, in the intelligent mattress temperature control method, after step S102, the method further includes:

[0019] S102.5 Determine whether the recommended temperature value is within the preset temperature constraint range; if not, execute S102.6 first, then execute S103; if yes, execute S103 directly.

[0020] S102.6 Update the recommended temperature value to the value closest to the upper and lower limits of the temperature constraint range.

[0021] Furthermore, in the intelligent mattress temperature control method, step S103 includes:

[0022] S1031. Collect the user's physiological data in real time, identify the sleep stage based on the physiological data, and determine the temperature regulation amount based on the sleep stage;

[0023] S1032. Calculate and determine the target temperature value based on the recommended temperature value and the temperature adjustment amount;

[0024] S1033. Control the mattress to adjust the temperature according to the target temperature value.

[0025] Furthermore, in the intelligent mattress temperature control method, step S1031 includes:

[0026] S10311. Real-time collection of user physiological data;

[0027] S10312. The physiological data is sampled using a sliding time window of a preset time length;

[0028] S10313. Input the physiological data within the sliding time window into the sleep stage segmentation model to segment the sleep stages according to a preset time resolution and obtain a sleep stage sequence.

[0029] S10314. Determine whether the sleep stage sequence meets the stability judgment condition; the stability judgment condition is that the stage transition does not exceed the preset number of times, or the continuous proportion of the same stage is greater than the preset percentage; if yes, then execute S10315; if no, then return to execute S10311.

[0030] S10315. Determine the temperature regulation amount based on the sleep stage sequence and LSTM model.

[0031] Furthermore, in the intelligent mattress temperature control method, step S10315 includes:

[0032] S103151. Obtain the temperature value of the bedding;

[0033] S103152. Input the sleep stage sequence, physiological data, user profile information and bed temperature value into the LSTM model to determine the temperature regulation amount.

[0034] Furthermore, in the intelligent mattress temperature control method, after step S1031, the method further includes:

[0035] S1031.5. Summate the temperature adjustment amount with the temperature adjustment amount determined each time within the preset time period;

[0036] S1031.6 Determine whether the summation result is greater than the first preset constraint threshold; if yes, then execute S1031.7; if no, then execute S1032.

[0037] S1031.7, No temperature adjustment is performed.

[0038] Furthermore, in the intelligent mattress temperature control method, after step S1032, the method further includes:

[0039] S1032.5. Calculate the difference between the target temperature value and the target temperature value determined in the first calculation;

[0040] S1032.6 Determine whether the difference result is greater than the second preset constraint threshold; if yes, then execute S1032.7; if no, then execute S1033.

[0041] S1032.7, No temperature adjustment is performed.

[0042] Furthermore, in the intelligent mattress temperature control method, step S1032 includes:

[0043] S10321. Based on the recommended temperature value and the temperature adjustment amount, the target temperature value is calculated and determined according to the following formula:

[0044] ;

[0045] in, The target temperature value, Recommended temperature value, This refers to the temperature regulation amount.

[0046] In a second aspect, the present invention provides a smart mattress temperature control device, the device comprising:

[0047] The acquisition module is used to acquire user profile information and ambient temperature values;

[0048] The calculation module is used to calculate and determine the recommended temperature value based on the user profile information and the ambient temperature value;

[0049] The temperature control module is used to control the mattress to adjust the temperature according to the recommended temperature value.

[0050] Furthermore, in the intelligent mattress temperature control device, the user profile information includes gender, age, BMI, and temperature preference type;

[0051] The types of cold and heat preferences include those who are sensitive to cold, those who are neutral, and those who are sensitive to heat.

[0052] Furthermore, in the intelligent mattress temperature control device, the calculation module is specifically used for:

[0053] Based on the user profile information and the ambient temperature value, the recommended temperature value is calculated and determined according to the following formula:

[0054] ;

[0055] in, Recommended temperature value, To maintain a fixed temperature value, The values ​​corresponding to gender are: The values ​​corresponding to age. The value corresponding to BMI. The values ​​corresponding to the warm / cold preference type. The values ​​corresponding to the ambient temperature are... , , , , These are the corresponding weighting coefficients.

[0056] Furthermore, in the intelligent mattress temperature control device, after step S102, the device further includes a constraint judgment module, used for:

[0057] After the calculation module performs the step of calculating and determining the recommended temperature value based on the user profile information and the ambient temperature value, it determines whether the recommended temperature value is within a preset temperature constraint range. If not, the constraint determination module first updates the recommended temperature value to the value closest to the upper and lower limits of the temperature constraint range, and then the temperature control module performs the step of controlling the mattress to adjust the temperature based on the recommended temperature value. If yes, the temperature control module directly performs the step of controlling the mattress to adjust the temperature based on the recommended temperature value.

[0058] Furthermore, in the intelligent mattress temperature control device, the temperature control module is specifically used for:

[0059] The system collects the user's physiological data in real time, identifies the sleep stage based on the physiological data, and determines the temperature regulation amount based on the sleep stage.

[0060] The target temperature value is calculated and determined based on the recommended temperature value and the temperature adjustment amount;

[0061] The mattress is controlled to adjust its temperature based on the target temperature value.

[0062] Furthermore, in the intelligent mattress temperature control device, the steps of the temperature control module performing real-time collection of the user's physiological data, identifying the sleep stage based on the physiological data, and determining the temperature adjustment amount based on the sleep stage specifically include:

[0063] Real-time collection of users' physiological data;

[0064] The physiological data are sampled using a sliding time window of a preset duration;

[0065] The physiological data within the sliding time window is input into the sleep stage segmentation model to divide the sleep stages according to a preset time resolution, thereby obtaining a sleep stage sequence.

[0066] Determine whether the sleep stage sequence meets the stability judgment condition; the stability judgment condition is that the stage transition does not exceed the preset number of times, or the continuous proportion of the same stage is greater than the preset percentage; if yes, then execute the step of determining the temperature regulation amount based on the sleep stage sequence and the LSTM model; if no, then return to the step of real-time collection of the user's physiological data.

[0067] Furthermore, in the intelligent mattress temperature control device, the step of determining the temperature adjustment amount based on the sleep stage sequence and the LSTM model, executed by the temperature control module, specifically includes:

[0068] Get the temperature value of the bed;

[0069] The sleep stage sequence, physiological data, user profile information, and bed temperature value are input into the LSTM model to determine the temperature regulation amount.

[0070] Furthermore, in the aforementioned intelligent mattress temperature control device, the temperature control device is also specifically used for:

[0071] After performing the steps of collecting the user's physiological data in real time, identifying the sleep stage based on the physiological data, and determining the temperature regulation amount based on the sleep stage, the temperature regulation amount is summed with the temperature regulation amount determined each time in the preset time period.

[0072] Determine whether the summation result is greater than a first preset constraint threshold; if yes, no temperature adjustment is performed; if no, the step of calculating and determining the target temperature value based on the recommended temperature value and the temperature adjustment amount is executed.

[0073] Furthermore, in the intelligent mattress temperature control device, the temperature control module is also specifically used for:

[0074] After performing the step of calculating and determining the target temperature value based on the recommended temperature value and the temperature adjustment amount, the difference between the target temperature value and the target temperature value determined in the first calculation is calculated.

[0075] Determine whether the difference result is greater than the second preset constraint threshold; if yes, do not adjust the temperature; if no, execute the step of controlling the mattress to adjust the temperature according to the target temperature value.

[0076] Furthermore, in the intelligent mattress temperature control device, the step of calculating and determining the target temperature value based on the recommended temperature value and the temperature adjustment amount, performed by the temperature control module, specifically includes:

[0077] Based on the recommended temperature value and the temperature adjustment amount, the target temperature value is calculated and determined according to the following formula:

[0078] ;

[0079] in, The target temperature value, Recommended temperature value, This refers to the temperature regulation amount.

[0080] Compared with the prior art, the present invention has the following beneficial effects:

[0081] This invention provides a smart mattress temperature control method and device. By acquiring user profile information and ambient temperature values, it accurately calculates a recommended temperature value suitable for the user and controls the mattress temperature accordingly. This allows for personalized and precise adjustment of the mattress temperature based on individual differences among users and real-time changes in ambient temperature. This effectively avoids sleep quality decline caused by uncomfortable mattress temperature, providing users with a more comfortable and suitable sleep environment. It helps users fall asleep faster, improves sleep depth and quality, and thus better promotes physical rest and recovery, significantly enhancing the user's sleep experience and quality of life.

[0082] The present invention has other features and advantages, which will be apparent from or will be set forth in detail in the accompanying drawings and the following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description

[0083] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0084] Figure 1 This is one of the flowcharts of the intelligent mattress temperature control method provided in Embodiment 1 of the present invention;

[0085] Figure 2 This is the second flowchart of the intelligent mattress temperature control method provided in Embodiment 1 of the present invention;

[0086] Figure 3 This is one of the detailed process diagrams of S103 provided in Embodiment 1 of the present invention;

[0087] Figure 4 This is a further detailed flowchart of S1031 provided in Embodiment 1 of the present invention;

[0088] Figure 5 This is a further detailed flowchart of S10315 provided in Embodiment 1 of the present invention;

[0089] Figure 6 This is a further detailed flowchart of S103 provided in Embodiment 1 of the present invention;

[0090] Figure 7 This is the third detailed flowchart of S103 provided in Embodiment 1 of the present invention;

[0091] Figure 8 This is a schematic diagram of the functional modules of the intelligent mattress temperature control device provided in Embodiment 2 of the present invention.

[0092] Figure label:

[0093] Acquisition module 201, calculation module 202, temperature control module 203. Detailed Implementation

[0094] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0095] Example 1

[0096] Please refer to Figure 1 This is a flowchart illustrating a smart mattress temperature control method according to Embodiment 1 of the present invention. This method is applicable to scenarios where users sleep on a smart mattress. The method is executed by a smart mattress temperature control system, which can be implemented by software and / or hardware and integrated within the mattress. The method specifically includes the following steps:

[0097] S101. Obtain user profile information and ambient temperature value;

[0098] It should be noted that the user profile information can generally be entered by the user through a terminal APP.

[0099] The user profile information includes gender, age, BMI (Body Mass Index), and temperature preference type; the temperature preference type includes cold-sensitive, neutral, and heat-sensitive; among them, neutral means that the user has no obvious preference for mattress temperature, and is neither particularly cold-sensitive nor particularly heat-sensitive.

[0100] There are two main ways to obtain ambient temperature values. One way is to collect ambient temperature data in real time by strategically placing various sensors around or inside the mattress; the other way is to use positioning technology to obtain ambient temperature information for the corresponding location from the network.

[0101] S102. Calculate and determine the recommended temperature value based on the user profile information and the ambient temperature value;

[0102] It should be noted that the recommended temperature value takes into account various factors such as the user's own physiological characteristics, temperature preferences, and the temperature of the current environment, so as to provide the user with a personalized and most suitable sleep temperature.

[0103] S103. Control the mattress to adjust the temperature according to the recommended temperature value.

[0104] It's important to note that after calculating the recommended temperature, the system immediately sends a control command to the mattress's temperature control device, instructing the mattress to adjust its temperature according to this recommended value. Upon receiving the command, the mattress's temperature control device quickly activates the heating or cooling function, adjusting the operation of the internal heating or cooling elements to gradually reach and stabilize the mattress temperature near the recommended value. Throughout the adjustment process, the system monitors the mattress's temperature changes in real time to ensure the accuracy and stability of temperature regulation, preventing the temperature from becoming too high or too low.

[0105] This invention comprehensively acquires user profile information and real-time ambient temperature values, and accurately calculates a recommended temperature value suitable for the user based on this information. Then, it intelligently adjusts the mattress temperature according to this recommended value. This method fully considers individual differences among users, such as gender, age, body mass index, and temperature preferences, while also responding promptly to real-time changes in ambient temperature, achieving personalized and precise mattress temperature adjustment. This precise temperature adjustment effectively avoids user discomfort caused by excessively high or low mattress temperatures, thus preventing decreased sleep quality. It creates a more comfortable and suitable sleep environment for users, helping them fall asleep faster, improving sleep depth and quality, and allowing the body to get more rest and recovery. Ultimately, it significantly improves the user's sleep experience and quality of life, providing strong support for the user's healthy life.

[0106] In one embodiment of this example, step S102 can be further refined to include the following steps:

[0107] S1021. Based on the user profile information and the ambient temperature value, the recommended temperature value is calculated and determined according to the following formula:

[0108] ;

[0109] in, The recommended temperature value is the final result calculated in this step. This value will guide the temperature adjustment of the mattress to ensure that the user receives the most suitable sleeping temperature.

[0110] The fixed temperature value is a pre-set base temperature parameter. For example, in this embodiment, it is set to 28, which provides a basic starting point for the entire temperature calculation, and all subsequent adjustments to the parameters will be based on this.

[0111] The values ​​are assigned to genders because different genders have certain differences in physiological characteristics and temperature perception, thus requiring different values ​​for each. For example, the value for males is -0.3, and the value for females is +0.5. This differentiated value better takes into account the influence of gender factors on temperature requirements.

[0112] The values ​​are assigned to different age groups, as people of different ages have varying physical functions and metabolic levels, resulting in different abilities to adapt to temperature. The value range is set from -0.2 to +0.8; for example, a 22-year-old would have a value of 0.2. This age-based value setting method allows for more precise satisfaction of the temperature needs of users in different age groups.

[0113] The value corresponds to BMI, which reflects a person's degree of obesity, and obesity affects the body's ability to dissipate heat and retain heat. Its range is -0.8 to +0.6; for example, when the BMI is 18.5 kg / m², the corresponding value is 0.2. This value setting takes into account the influence of body mass on temperature perception, making temperature regulation more personalized.

[0114] The values ​​assigned to different temperature preferences directly influence users' mattress temperature needs. For example, a user who is sensitive to cold has a value of +1.2, meaning they require a relatively high mattress temperature; a neutral user has a value of 0, indicating they don't have a strong preference for any particular temperature; and a user who is sensitive to heat has a value of -0.8, meaning they prefer a lower mattress temperature. This categorization method fully respects users' individual preferences.

[0115] This value corresponds to the ambient temperature. Changes in ambient temperature directly affect human comfort, so it needs to be considered in temperature calculations. Its range is -0.3 to +0.5; for example, when the ambient temperature is 25 degrees Celsius, the corresponding value is 0.1. By incorporating this ambient temperature value, the mattress temperature can be dynamically adjusted according to changes in the external environment.

[0116] , , , , The corresponding parameters are ( , , , , The weighting coefficients are used to adjust the proportion of each parameter in the final recommended temperature value calculation. Different weighting coefficient settings reflect the different degrees of influence of each parameter on the recommended temperature value. For example, if it is believed that gender has a relatively small impact on temperature requirements, then... The value of will be relatively small; conversely, if it is believed that the type of preference for warmth or coldness has a greater impact on temperature requirements, then The value of this will be relatively large. By reasonably setting these weighting coefficients, the calculated recommended temperature value can be more in line with the actual situation and user needs.

[0117] Through the detailed settings of the above formula and various parameters, S1021 can comprehensively consider multiple factors such as the user's gender, age, BMI, preference for warm or cold temperatures, and ambient temperature, and accurately calculate the recommended temperature value suitable for the current user, providing a scientific and accurate basis for subsequent mattress temperature adjustment.

[0118] Please refer to Figure 2 In one embodiment of this example, in Figure 1 Based on S102, the method further includes:

[0119] S102.5 Determine whether the recommended temperature value is within the preset temperature constraint range; if not, execute S102.6 first, then execute S103; if yes, execute S103 directly.

[0120] It should be noted that the preset temperature constraint range is generally set after comprehensive consideration of factors such as human comfort, the safe operation requirements of the mattress equipment, and the actual use scenario. Under normal circumstances, the preset temperature constraint range is set to 13 ~ 35℃.

[0121] During the judgment process, there are two possible outcomes:

[0122] If the recommended temperature value is within the preset temperature constraint range: This indicates that the calculated recommended temperature value meets the established reasonable range and no additional adjustment is required. At this time, the system will directly execute S103, that is, control the mattress to adjust the temperature according to the recommended temperature value to ensure a suitable sleep temperature environment for the user.

[0123] If the recommended temperature value is not within the preset temperature constraint range: This means that the calculated recommended temperature value exceeds a reasonable range. Directly adjusting the temperature according to this value may cause discomfort to the user or even damage the mattress. Therefore, in this case, the system needs to first execute S102.6 to adjust the recommended temperature value, and then execute S103 after the adjustment is completed to ensure the rationality and safety of temperature adjustment.

[0124] S102.6 Update the recommended temperature value to the value closest to the upper and lower limits of the temperature constraint range.

[0125] It should be noted that when the calculated recommended temperature value exceeds the preset temperature constraint range, the recommended temperature value needs to be adjusted to bring it back within the temperature constraint range. Specifically, the adjustment method involves updating the recommended temperature value to the upper or lower limit of the temperature constraint range, specifically the value closest to the original recommended temperature value. The purpose of this is to ensure that the recommended temperature value returns to a reasonable range while minimizing the deviation from the original recommended temperature value, thus more closely reflecting the user's actual temperature needs.

[0126] For example, assuming the temperature constraint range is 20℃ to 30℃, the calculated recommended temperature value is 32℃. Since 32℃ exceeds the upper limit of the temperature constraint range (30℃), and the upper limit of the temperature constraint range is 30℃ while the lower limit is 20℃, 32℃ is closer to 30℃ (a difference of 2℃) and farther from 20℃ (a difference of 12℃). Therefore, the recommended temperature value is updated to 30℃, which is the upper limit of the temperature constraint range.

[0127] Furthermore, suppose that the calculated recommended temperature value is 18℃: 18℃ is lower than the lower limit of the temperature constraint range of 20℃, and 18℃ is closer to 20℃ (the difference is 2℃), but farther from 30℃ (the difference is 12℃), then the recommended temperature value will be updated to 20℃, which is the lower limit of the temperature constraint range.

[0128] In summary, the core objective of this embodiment, through the settings described in S102.5 and S102.6, is to ensure that the recommended temperature value always remains within a reasonable temperature constraint range. When the recommended temperature value exceeds this range, the nearest range boundary value (upper or lower limit) is selected as the new recommended temperature value. This effectively avoids improper mattress temperature adjustment caused by unreasonable recommended temperature values, thereby ensuring the rationality and safety of mattress temperature adjustment and providing users with a more stable and comfortable sleep temperature environment.

[0129] Please refer to Figure 3 In one embodiment of this example, S103 includes:

[0130] S1031. Collect the user's physiological data in real time, identify the sleep stage based on the physiological data, and determine the temperature regulation amount based on the sleep stage;

[0131] It should be noted that the system continuously and in real-time collects a wide range of user-related body data using various sensors installed on the mattress or related accessories, such as temperature sensors, heart rate sensors, and accelerometers. This data covers several key physiological indicators, including but not limited to:

[0132] Body temperature: In addition to monitoring the user's surface temperature, core body temperature is also monitored. Surface temperature directly reflects the heat exchange between the body and the external environment, while core body temperature better reflects the body's internal metabolic state. Combining the two provides a more comprehensive understanding of the user's body temperature trends.

[0133] Heart rate: Accurately records the number of times a user's heart beats per minute. Heart rate is one of the important indicators reflecting the body's physiological state. Heart rate exhibits different characteristics in different sleep stages. For example, during light sleep, heart rate may fluctuate to some extent, while during deep sleep, heart rate is usually relatively stable and slower.

[0134] Respiratory rate: Accurately counts the number of breaths a user takes per minute. Respiratory rate is also closely related to sleep state; during sleep, it changes with sleep depth. For example, during REM sleep, the respiratory rate may be relatively fast and irregular.

[0135] These sensors monitor the aforementioned physiological data in real time, and the data is continuously updated to ensure that the system can obtain the user's latest physiological status information in a timely and accurate manner, providing a reliable basis for subsequent sleep stage identification and temperature regulation.

[0136] The system incorporates a data analysis algorithm that performs in-depth analysis and processing of real-time collected physiological data. Through comprehensive analysis of data such as body temperature, heart rate, and respiratory rate, it can accurately identify the user's current sleep stage. Generally, sleep stages are mainly divided into light sleep, deep sleep, and REM (rapid eye movement) sleep, each with its unique physiological characteristics. For example, during light sleep, the user's body is relatively relaxed but easily awakened by external disturbances. At this time, body temperature may drop slightly, and heart rate and respiratory rate are relatively stable but slightly higher than during deep sleep. Deep sleep is a crucial period for the body's recovery and repair; the user's body is in a state of deep relaxation, body temperature further decreases, and heart rate and respiratory rate reach a low and stable level. REM sleep is associated with dream activity; the brain is more active during this time, body temperature may rise slightly, and heart rate and respiratory rate are relatively fast and irregular.

[0137] After accurately identifying the user's sleep stage, the system determines the appropriate temperature regulation based on the characteristics of different sleep stages and individual user differences, combined with pre-set rules and models. Different sleep stages have different temperature requirements. For example, during light sleep, users are more sensitive to temperature changes, so the temperature regulation may be relatively small to avoid waking the user due to excessive temperature fluctuations. During deep sleep, the user's metabolism is relatively slow, and a slightly lower temperature may be needed to promote recovery, so the temperature regulation may be appropriately increased. During REM sleep, due to brain activity, the body may generate more heat, and the temperature regulation may need to be adjusted according to the actual situation to maintain a comfortable sleep temperature.

[0138] S1032. Calculate and determine the target temperature value based on the recommended temperature value and the temperature adjustment amount;

[0139] It should be noted that after obtaining the recommended temperature value and temperature adjustment amount, the system will use simple mathematical operations to combine the two to determine the final target temperature value.

[0140] Specifically, the target temperature value can be calculated using the following formula:

[0141] ;

[0142] in, The target temperature value, Recommended temperature value, This refers to the temperature regulation amount.

[0143] In this way, the system can fully consider the user's basic temperature requirements (recommended temperature value) as well as the specific needs of the current sleep stage (temperature adjustment), ensuring that the target temperature value more accurately matches the user's actual sleep temperature requirements.

[0144] S1033. Control the mattress to adjust the temperature according to the target temperature value.

[0145] It's important to note that once the target temperature is determined, the system immediately sends a control command to the mattress's temperature control device. Upon receiving the command, the device quickly and accurately adjusts the mattress temperature based on the target value. For example, if the target temperature is higher than the current mattress temperature, the device will activate the heating function to gradually raise the mattress temperature to the target value; if the target temperature is lower than the current mattress temperature, the device will activate the cooling function to lower the mattress temperature to the target value. Throughout the temperature adjustment process, the system continuously monitors the actual mattress temperature and compares it with the target temperature in real time. Based on any deviations, the system promptly adjusts the temperature control device's operation to ensure the mattress temperature is stably and accurately maintained near the target value, providing the user with a consistently comfortable sleeping environment.

[0146] In summary, through the synergistic effect of steps S1031, S1032, and S1033, this embodiment can dynamically and precisely adjust the mattress temperature according to the user's real-time changing physiological state and sleep stage, creating a personalized and comfortable sleep environment for the user and effectively improving the user's sleep quality.

[0147] Please refer to Figure 4 In one embodiment of this example, S1031 includes:

[0148] S10311. Real-time collection of user physiological data;

[0149] S10312. The physiological data is sampled using a sliding time window of a preset time length;

[0150] It should be noted that this is a method for processing the collected physiological data. This dynamic sampling method ensures the accuracy of the temporal locality analysis of the data, and also achieves continuous tracking of changes in the user's physiological state through window sliding, avoiding the lag effect caused by a fixed window. Specifically:

[0151] Preset time length: This is a fixed, predefined time period, such as 1 minute, 5 minutes, or 10 minutes. This time period determines the data range for each sampling analysis.

[0152] Sliding time window: This is a dynamic data sampling method. Imagine a time window continuously moving forward (sliding) on ​​the timeline. After each movement, the data within the window is resampled and analyzed.

[0153] For example, assuming the preset time length is 5 minutes, the step size of the sliding time window is 1 minute:

[0154] Starting at time t0, the window covers a time range from t0 to t0+5 minutes, and the system will analyze the physiological data within these 5 minutes.

[0155] One minute later (time point t1), the window slides forward one minute, and the new time range is from t1 to t1+5 minutes. The system then analyzes the physiological data within these 5 minutes again.

[0156] This process continues, with data being sampled and analyzed each time the window is moved.

[0157] S10313. Input the physiological data within the sliding time window into the sleep stage segmentation model to segment the sleep stages according to a preset time resolution and obtain a sleep stage sequence.

[0158] It should be noted that this step involves inputting the processed physiological data into a pre-trained model to analyze the user's sleep stages:

[0159] Sleep stage segmentation model: This is a pre-trained algorithm model that can determine which sleep stage a user is in based on physiological data. Common sleep stages include light sleep, deep sleep, and rapid eye movement (REM) sleep.

[0160] Preset time resolution: This is the time precision of the model's output, such as every minute, every 5 minutes, etc. This means that the model will output the user's sleep stage information at this time interval.

[0161] Sleep stage sequence: The model outputs a time series based on physiological data within a sliding time window, representing the user's sleep stages at different time points.

[0162] For example, assuming the preset time length is 5 minutes, the sliding time window step size is 1 minute, and the preset time resolution is 1 minute:

[0163] Starting at time point t0, the window covers a time range from t0 to t0+5 minutes. The system analyzes the physiological data within these 5 minutes and inputs it into the sleep stage segmentation model.

[0164] The model outputs a sequence of sleep stages over these 5 minutes, for example:

[0165] t0 to t0+1 minutes: light sleep;

[0166] t0+1 to t0+2 minutes: light sleep;

[0167] t0+2 to t0+3 minutes: Deep sleep;

[0168] t0+3 to t0+4 minutes: REM;

[0169] t0+4 to t0+5 minutes: Deep sleep;

[0170] One minute later (time point t1), the window slides forward one minute, and the new time range is from t1 to t1+5 minutes. The system analyzes the physiological data within these 5 minutes again and outputs a new sleep stage sequence.

[0171] This process continues until a complete time series of sleep stages is generated, which is used to analyze the user's sleep quality.

[0172] S10314. Determine whether the sleep stage sequence meets the stability judgment condition; the stability judgment condition is that the stage transition does not exceed the preset number of times, or the continuous proportion of the same stage is greater than the preset percentage; if yes, then execute S10315; if no, then return to execute S10311.

[0173] It should be noted that the purpose of this step is to assess whether the user's sleep stage sequence is stable enough to determine whether to continue temperature regulation. Specifically:

[0174] Stage transitions did not exceed the preset number: This means that within a certain period of time, the number of times the user's sleep stages change does not exceed a set threshold. For example, if the preset number is 3, then within a certain period of time (such as 5 minutes), the number of times the user's sleep stages change cannot exceed 3.

[0175] The consecutive percentage of the same sleep stage exceeds a preset percentage: This means that within a certain time period, the proportion of a certain sleep stage's continuous duration to the total time exceeds a set threshold. For example, if the preset percentage is 40%, then within 5 minutes, the consecutive percentage of a certain sleep stage (such as light sleep) needs to exceed 40%. Taking the sleep stage sequence of light sleep, light sleep, deep sleep, REM sleep, and deep sleep within 5 minutes as an example, the consecutive percentage of light sleep is 40%, but it does not exceed 40%.

[0176] If the sleep stage sequence meets any of the above stability conditions, proceed to the next step (i.e., S10315). If not, return to S10311, recollect physiological data, and continue monitoring.

[0177] S10315. Determine the temperature regulation amount based on the sleep stage sequence and LSTM model.

[0178] It should be noted that the purpose of this step is to determine the mattress temperature regulation level using an LSTM model based on the user's sleep stage sequence. Specifically:

[0179] LSTM (Long Short-Term Memory) is a special type of recurrent neural network (RNN) capable of processing and predicting long-term dependencies in time-series data. In sleep monitoring, LSTM models can learn a user's sleep patterns and predict the most suitable mattress temperature based on these patterns.

[0180] For example, if a user is currently in a deep sleep phase, the model may suggest lowering the mattress temperature to help the user maintain a comfortable and stable sleep state.

[0181] This deep learning-based time series prediction method can dynamically adapt to subtle changes in a user's sleep state, achieving a precise match between temperature regulation and sleep needs.

[0182] In summary, through the synergistic effect of the above steps, this embodiment achieves a complete closed-loop control from physiological data acquisition to temperature regulation determination. This ensures the scientific accuracy and stability of sleep stage identification, and enables personalized and dynamic calculation of temperature regulation through an intelligent model. Ultimately, it provides users with a comfortable sleep temperature environment that adapts to their sleep throughout the entire process, significantly improving sleep quality and recovery effects.

[0183] Please refer to Figure 5 In one embodiment of this example, step S10315 can be further refined to include the following steps:

[0184] S103151. Obtain the temperature value of the bedding;

[0185] It should be noted that the system collects temperature data inside the bed in real time through an array of temperature sensors deployed inside the mattress or close to the user's body.

[0186] The collected bed temperature values ​​will serve as dynamic environmental parameters, complementing the user's physiological data and providing a more comprehensive input basis for subsequent model calculations. For example, when the bed temperature is already at a relatively high level (e.g., 28°C), even if the user is in a deep sleep stage (which usually requires a lower temperature), the model may appropriately reduce the cooling rate to avoid excessive cooling that could cause user discomfort.

[0187] Understandably, temperature can be collected by placing sensors at at least three temperature measurement points under the covers (such as the areas corresponding to the chest, waist, and legs) to eliminate the impact of local temperature deviations on the overall judgment.

[0188] S103152. Input the sleep stage sequence, physiological data, user profile information and bed temperature value into the LSTM model to determine the temperature regulation amount.

[0189] It should be noted that the system achieves accurate prediction of temperature regulation by inputting four types of data—sleep stage sequences, physiological data, user profile information, and bed temperature values—into a trained LSTM model.

[0190] Through this multimodal data fusion and intelligent decision-making mechanism, the system can dynamically adapt to subtle changes in the user's sleep state and environmental disturbances, achieving precise temperature regulation tailored to each individual, and significantly improving sleep comfort and recovery.

[0191] Please refer to Figure 6 In one embodiment of this example, in Figure 3 Building upon step S1031, this embodiment introduces a cumulative temperature regulation constraint mechanism. By dynamically monitoring the total temperature regulation within a short period, it avoids drastic fluctuations in bed temperature caused by frequent or large-scale adjustments, thereby ensuring user sleep comfort. This mechanism specifically includes the following three new steps, S1031.5 to S1031.7, forming a closed-loop control with the original process:

[0192] S1031.5. Summate the temperature adjustment amount with the temperature adjustment amount determined each time within the preset time period;

[0193] It should be noted that the preset time period is a pre-defined time range. For example, it could be 5 minutes. Within this time period, there will be multiple temperature adjustment operations, and each time a corresponding temperature adjustment amount will be determined. This step is to add the currently determined temperature adjustment amount to the temperature adjustment amounts determined in each previous operation within the preset time period to obtain a total.

[0194] For example, if three adjustments have been made in the past 5 minutes (ΔT1=+0.2℃, ΔT2=-0.3℃, ΔT3=+0.1℃), and a new adjustment ΔT4=+0.4℃ is generated, then the cumulative sum is:

[0195] ΣΔT=0.2-0.3+0.1+0.4=0.4℃.

[0196] S1031.6 Determine whether the summation result is greater than the first preset constraint threshold; if yes, then execute S1031.7; if no, then execute S1032.

[0197] It should be noted that the system compares the accumulated sum ΣΔT with a first preset constraint threshold (Th1), which is set based on user comfort experiments, for example, 2℃ (i.e., the temperature change within 5 minutes does not exceed 2℃). The judgment logic is as follows:

[0198] If |ΣΔT|>Th1: This indicates that the temperature adjustment range is too large in the short term, which may cause user discomfort (such as frequent alternation between hot and cold or sudden temperature changes), and the constraint mechanism needs to be triggered.

[0199] If |ΣΔT|≤Th1: This indicates that the adjustment range is within a safe range, and subsequent operations can continue.

[0200] Example: If Th1 = 0.5℃ and the current ΣΔT = 0.4℃ (≤ 0.5℃), then the condition is met, and S1032 (normal adjustment) is executed; if ΣΔT = +0.6℃ (> 0.5℃), then the constraint is triggered, and S1031.7 is executed.

[0201] S1031.7, No temperature adjustment is performed.

[0202] In summary, by introducing this mechanism, the system can improve the smoothness and safety of temperature regulation while ensuring the accuracy of sleep stage recognition, making it particularly suitable for users who are sensitive to temperature or have high requirements for sleep quality.

[0203] Please refer to Figure 7 In one embodiment of this example, in Figure 3 or Figure 5 On the basis of (in order to) Figure 3 Taking the existing system as an example, after step S1032, the system introduces a constraint mechanism for the maximum change in target temperature. This mechanism limits the maximum adjustment range during the entire sleep period by comparing the current target temperature value with the target temperature value determined in the first calculation, ensuring that the temperature does not change significantly. The specific new steps are as follows, forming a closed-loop control with the original process:

[0204] S1032.5. Calculate the difference between the target temperature value and the target temperature value determined in the first calculation;

[0205] For example, assuming the current target temperature is 28℃, and the first calculated target temperature is 20℃, then the difference is 8℃.

[0206] S1032.6 Determine whether the difference result is greater than the second preset constraint threshold; if yes, then execute S1032.7; if no, then execute S1033.

[0207] It should be noted that, continuing with the above example, the system will compare the calculated difference, i.e., 8℃, with the second preset constraint threshold (e.g., 6℃) to determine whether the constraint condition is triggered. In fact, 8℃ > 6℃, which means that this temperature adjustment has exceeded the maximum allowable adjustment range during the entire sleep period, which may cause user discomfort, and S1032.7 needs to be executed.

[0208] Similarly, if the temperature does not exceed the limit, it means that the temperature change is within a reasonable range, and the original process S1033 can be executed.

[0209] S1032.7, No temperature adjustment is performed.

[0210] In summary, by introducing a constraint mechanism for the maximum variation range of the target temperature, this embodiment further improves the reliability and user comfort of the system while ensuring accurate identification of the sleep stage and intelligent temperature regulation.

[0211] Although this invention uses terms such as user profile information and ambient temperature values ​​extensively, the possibility of using other terms is not excluded. These terms are used merely for the convenience of describing and explaining the essence of this invention; interpreting them as any additional limitation would contradict the spirit of this invention.

[0212] Example 2

[0213] Please refer to Figure 8 Embodiment 2 of the present invention provides a smart mattress temperature control device, the device comprising:

[0214] The acquisition module 201 is used to acquire user profile information and ambient temperature values;

[0215] Calculation module 202 is used to calculate and determine a recommended temperature value based on the user profile information and the ambient temperature value;

[0216] The temperature control module 203 is used to control the mattress to adjust the temperature according to the recommended temperature value.

[0217] Optionally, in the intelligent mattress temperature control device, the user profile information includes gender, age, BMI, and temperature preference type;

[0218] The types of cold and heat preferences include those who are afraid of cold, those who are neutral, and those who are afraid of heat.

[0219] Optionally, in the intelligent mattress temperature control device, the calculation module 202 is specifically used for:

[0220] Based on the user profile information and the ambient temperature value, the recommended temperature value is calculated and determined according to the following formula:

[0221] ;

[0222] in, Recommended temperature value, To maintain a fixed temperature value, The values ​​corresponding to gender are... The values ​​corresponding to age. The value corresponding to BMI. The values ​​corresponding to the warm / cold preference type. The value corresponding to the ambient temperature. , , , , These are the corresponding weighting coefficients.

[0223] Optionally, in the intelligent mattress temperature control device, after step S102, the device further includes a constraint judgment module, used for:

[0224] After the calculation module 202 executes the step of calculating and determining the recommended temperature value based on the user profile information and the ambient temperature value, it determines whether the recommended temperature value is within a preset temperature constraint range. If not, the constraint determination module first updates the recommended temperature value to the value closest to the upper and lower limits of the temperature constraint range, and then the temperature control module 203 executes the step of controlling the mattress to adjust the temperature based on the recommended temperature value. If yes, the temperature control module 203 directly executes the step of controlling the mattress to adjust the temperature based on the recommended temperature value.

[0225] Optionally, in the intelligent mattress temperature control device, the temperature control module 203 is specifically used for:

[0226] The system collects the user's physiological data in real time, identifies the sleep stage based on the physiological data, and determines the temperature regulation amount based on the sleep stage.

[0227] The target temperature value is calculated and determined based on the recommended temperature value and the temperature adjustment amount;

[0228] The mattress is controlled to adjust its temperature based on the target temperature value.

[0229] Optionally, in the intelligent mattress temperature control device, the steps performed by the temperature control module 203—real-time collection of the user's physiological data, identification of sleep stages based on the physiological data, and determination of the temperature adjustment amount based on the sleep stages—specifically include:

[0230] Real-time collection of users' physiological data;

[0231] The physiological data are sampled using a sliding time window of a preset duration;

[0232] The physiological data within the sliding time window is input into the sleep stage segmentation model to divide the sleep stages according to a preset time resolution, thereby obtaining a sleep stage sequence.

[0233] Determine whether the sleep stage sequence meets the stability judgment condition; the stability judgment condition is that the stage transition does not exceed the preset number of times, or the continuous proportion of the same stage is greater than the preset percentage; if yes, then execute the step of determining the temperature regulation amount based on the sleep stage sequence and the LSTM model; if no, then return to the step of real-time collection of the user's physiological data.

[0234] Optionally, in the intelligent mattress temperature control device, the step of determining the temperature adjustment amount based on the sleep stage sequence and the LSTM model executed by the temperature control module 203 specifically includes:

[0235] Get the temperature value of the bed;

[0236] The sleep stage sequence, physiological data, user profile information, and bed temperature value are input into the LSTM model to determine the temperature regulation amount.

[0237] Optionally, in the intelligent mattress temperature control device, the temperature control device is further specifically used for:

[0238] After performing the steps of collecting the user's physiological data in real time, identifying the sleep stage based on the physiological data, and determining the temperature regulation amount based on the sleep stage, the temperature regulation amount is summed with the temperature regulation amount determined each time in the preset time period.

[0239] Determine whether the summation result is greater than a first preset constraint threshold; if yes, no temperature adjustment is performed; if no, the step of calculating and determining the target temperature value based on the recommended temperature value and the temperature adjustment amount is executed.

[0240] Optionally, in the intelligent mattress temperature control device, the temperature control module 203 is further specifically used for:

[0241] After performing the step of calculating and determining the target temperature value based on the recommended temperature value and the temperature adjustment amount, the difference between the target temperature value and the target temperature value determined in the first calculation is calculated.

[0242] Determine whether the difference result is greater than the second preset constraint threshold; if yes, do not adjust the temperature; if no, execute the step of controlling the mattress to adjust the temperature according to the target temperature value.

[0243] Optionally, in the intelligent mattress temperature control device, the step of calculating and determining the target temperature value based on the recommended temperature value and the temperature adjustment amount, performed by the temperature control module 203, specifically includes:

[0244] Based on the recommended temperature value and the temperature adjustment amount, the target temperature value is calculated and determined according to the following formula:

[0245] ;

[0246] in, The target temperature value, Recommended temperature value, This refers to the temperature regulation amount.

[0247] Finally, it should be noted that although the above embodiments have been described in the description and drawings of this invention, this should not limit the scope of patent protection of this invention. Any technical solutions that are based on the essential concept of this invention, utilize the content described in the description and drawings of this invention to make equivalent structural or procedural substitutions or modifications, as well as the direct or indirect application of the technical solutions of the above embodiments to other related technical fields, are all included within the scope of patent protection of this invention.

Claims

1. A method for intelligent temperature control of a mattress, characterized in that, The method comprises: S101, acquiring user portrait information and an ambient temperature value; S102, calculating a recommended temperature value according to the user portrait information and the ambient temperature value; S103, controlling a mattress to perform temperature adjustment according to the recommended temperature value.

2. The mattress temperature intelligent control method of claim 1, wherein, The user portrait information comprises gender, age, BMI, and a cold-warm preference type; The cold-warm preference type comprises a cold-phobic type, a neutral type, and a heat-phobic type.

3. The mattress temperature intelligent control method of claim 2, wherein, The S102 comprises: S1021, calculating a recommended temperature value according to the user portrait information and the ambient temperature value according to the following formula: ； wherein, is a recommended temperature value, is a fixed temperature value, is a value corresponding to gender, is a value corresponding to age, is a value corresponding to BMI, is a value corresponding to a cold-warm preference type, is a value corresponding to an environmental temperature value, , , , , are respective weight coefficients.

4. The mattress temperature intelligent control method of claim 1, wherein, After the S102, the method further comprises: S102.5, judging whether the recommended temperature value is within a preset temperature constraint interval; if not, performing S102.6 first and then performing the S103; if yes, performing the S103 directly; S102.6, updating the recommended temperature value to the value closest to the upper limit value and the lower limit value of the temperature constraint interval.

5. The bed mattress temperature intelligent control method according to claim 1 or 4, characterized in that, The S103 comprises: S1031, collecting physiological data of a user in real time, identifying a sleep stage according to the physiological data, and determining a temperature adjustment amount according to the sleep stage; S1032, calculating a target temperature value according to the recommended temperature value and the temperature adjustment amount; S1033, controlling a mattress to perform temperature adjustment according to the target temperature value.

6. The mattress temperature intelligent control method of claim 5, wherein, The S1031 comprises: S10311, collecting physiological data of a user in real time; S10312, sampling the physiological data by using a preset time length of a sliding time window; S10313, inputting the physiological data in the sliding time window into a sleep stage division model to divide a sleep stage according to a preset time resolution, and obtaining a sleep stage sequence; S10314, judging whether the sleep stage sequence satisfies a stability judgment condition; the stability judgment condition is that a stage transition does not exceed a preset number of times, or a continuous proportion of a same stage is greater than a preset percentage; if yes, performing S10315; if not, returning to perform S10311; S10315, determining a temperature adjustment amount according to the sleep stage sequence and an LSTM model.

7. The mattress temperature intelligent control method of claim 6, wherein, The S10315 comprises: S103151, acquiring a nest temperature value; S103152, inputting the sleep stage sequence, physiological data, user portrait information, and nest temperature value into an LSTM model to determine a temperature adjustment amount.

8. The mattress temperature intelligent control method of claim 5, wherein, After the S1031, the method further comprises: S1031.5, summing the temperature adjustment amount and a temperature adjustment amount determined each time in a preset time period before; S1031.6, judging whether the sum result is greater than a first preset constraint threshold; if yes, performing S1031.7; if not, performing the S1032; S1031.7, not performing temperature adjustment.

9. The mattress temperature intelligent control method of claim 5, wherein, After the S1032, the method further comprises: S1032.5, calculating a difference between the target temperature value and a target temperature value determined for the first time; S1032.6, judging whether the difference result is greater than a second preset constraint threshold; if yes, performing S1032.7; if not, performing S1033; S1032.7, not performing temperature adjustment.

10. The bed mattress temperature intelligent control method of claim 5, wherein, The S1032 comprises: S10321, calculating and determining a target temperature value according to the recommended temperature value and the temperature adjustment amount according to the following formula: ; wherein is a target temperature value, is a recommended temperature value, is a temperature adjustment amount.

11. A bed mattress temperature intelligent control device, characterized in that, The device comprises: An acquisition module, configured to acquire user portrait information and an ambient temperature value; A calculation module, configured to calculate and determine a recommended temperature value according to the user portrait information and the ambient temperature value; A temperature control module, configured to control a mattress to perform temperature adjustment according to the recommended temperature value.

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