Mattress control method and device, intelligent mattress and storage medium

Abstract

The embodiment of the application discloses a mattress control method and device, an intelligent mattress and a storage medium. The method comprises the following steps: receiving body data of a target user sent by a body fat detection device; determining first mattress shape data of an intelligent mattress according to the body data and historical sleep quality data of the target user, and adjusting the shape of the intelligent mattress according to the first mattress shape data; when it is detected that the target user enters a sleep state, determining a sleep posture of the target user; determining second mattress shape data corresponding to the intelligent mattress according to the sleep posture and the first mattress shape data, and adjusting the shape of the intelligent mattress according to the second mattress shape data. The embodiment can improve the sleep quality of the user and meet the needs of the user's body.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home, in particular to a mattress control method and device, a smart mattress and a storage medium. BACKGROUND

[0002] At present, special groups such as overweight people, children and the elderly have higher requirements for mattresses. Not only the sleep quality of these special groups needs to be ensured, but also their specific needs for bones, weight and body development need to be considered. In order to more accurately solve the problems of these special groups, they usually need to manually input specific body data, but the operation is relatively cumbersome and easy to miss filling, and the accuracy of the body data cannot be guaranteed, so that the mattress cannot meet the needs of the user's body. Therefore, how to improve the sleep quality of the user and meet the needs of the user's body has become a problem to be solved. SUMMARY

[0003] The embodiments of the present application disclose a mattress control method and device, a smart mattress and a storage medium, which can improve the sleep quality of the user and meet the needs of the user's body.

[0004] The embodiments of the present application disclose a mattress control method applied to a smart mattress, the method comprising:

[0005] receiving body data of a target user sent by a body fat detection device;

[0006] determining first mattress shape data of the smart mattress according to the body data and historical sleep quality data of the target user, and adjusting the shape of the smart mattress according to the first mattress shape data;

[0007] when it is detected that the target user enters a sleep state, determining a sleep posture of the target user;

[0008] determining second mattress shape data corresponding to the smart mattress according to the sleep posture and the first mattress shape data, and adjusting the shape of the smart mattress according to the second mattress shape data.

[0009] In one embodiment, the body data includes historical body data corresponding to the target user in a historical time period; and the determination of the first mattress shape data of the smart mattress according to the body data and the historical sleep quality data of the target user comprises:

[0010] determining a user body change condition according to the historical body data; the user body change condition includes a user body development condition or a user body aging condition;

[0011] According to the user body change condition and the historical sleep quality data of the target user in the historical time period, first mattress shape data of the smart mattress is determined.

[0012] In one embodiment, the determining of the first mattress shape data of the smart mattress according to the user body change condition and the historical sleep quality data of the target user in the historical time period comprises:

[0013] Obtaining body target data corresponding to the target user; the body target data is used to indicate data that the body data of the target user needs to reach after a preset time;

[0014] According to the user body change condition, body prediction data after the preset time is predicted;

[0015] Determining a difference between the body prediction data and the body target data;

[0016] According to the difference, the user body change condition and the historical sleep quality data, the first mattress shape data of the smart mattress is determined.

[0017] In one embodiment, the determining of the first mattress shape data of the smart mattress according to the difference, the user body change condition and the historical sleep quality data comprises:

[0018] If the difference is less than or equal to a difference threshold value, a weight corresponding to the body change condition is determined as a first weight, a weight corresponding to the historical sleep quality is determined as a second weight, and the user body change condition and the historical sleep quality data are weighted and calculated based on the first weight and the second weight to determine the first mattress shape data of the smart mattress;

[0019] If the difference is greater than the difference threshold value, a weight corresponding to the body change condition is determined as a third weight, a weight corresponding to the historical sleep quality is determined as a fourth weight, and the user body change condition and the historical sleep quality data are weighted and calculated based on the third weight and the fourth weight to determine the first mattress shape data of the smart mattress;

[0020] Wherein, the first weight is less than the third weight, and the second weight is greater than the fourth weight.

[0021] In one embodiment, the determining of the second mattress shape data corresponding to the smart mattress according to the sleep posture and the first mattress shape data comprises:

[0022] Determining a mattress shape optimization parameter corresponding to the sleep posture;

[0023] According to the mattress shape optimization parameter, the first mattress shape data is optimized to obtain second mattress shape data corresponding to the smart mattress.

[0024] In one embodiment, after the body data of the target user sent by the body fat detection device is received, the method further comprises:

[0025] Obtaining a plurality of historical bed-in times of the target user;

[0026] Determining a bed-in time range according to the plurality of historical bed-in times;

[0027] If it is determined that the current time is within the bed-in time range, the step of determining the first mattress shape data of the smart mattress according to the body data and historical sleep quality data of the target user, and adjusting the shape of the smart mattress according to the first mattress shape data is executed.

[0028] In one embodiment, the body data includes one or more of body weight, body fat, height, bone mass, and body age.

[0029] Embodiments of the present application disclose a mattress control device applied to a smart mattress, the device comprising:

[0030] A data receiving module configured to receive body data of a target user sent by a body fat detection device;

[0031] A first adjusting module configured to determine first mattress shape data of the smart mattress according to the body data and historical sleep quality data of the target user, and adjust the shape of the smart mattress according to the first mattress shape data;

[0032] A posture determining module configured to determine a sleep posture of the target user when it is detected that the target user enters a sleep state;

[0033] A second adjusting module configured to determine second mattress shape data corresponding to the smart mattress according to the sleep posture and the first mattress shape data, and adjust the shape of the smart mattress according to the second mattress shape data.

[0034] In one embodiment, the first adjusting module is further configured to determine a user body change condition according to the historical body data, wherein the user body change condition includes a user body development condition or a user body aging condition; and determine the first mattress shape data of the smart mattress according to the user body change condition and historical sleep quality data of the target user corresponding to the historical time period.

[0035] In an embodiment, the first adjusting module is further configured to acquire body target data corresponding to the target user, wherein the body target data is used to indicate data that the body data of the target user needs to reach after a preset time; predict body prediction data after the preset time according to the body change condition of the user; determine a difference between the body prediction data and the body target data; and determine first mattress shape data of the smart mattress according to the difference, the body change condition of the user, and the historical sleep quality data.

[0036] In an embodiment, the first adjusting module is further configured to, if the difference is less than or equal to a difference threshold, determine that a weight corresponding to the body change condition is a first weight, and a weight corresponding to the historical sleep quality is a second weight, and perform weighted calculation on the body change condition of the user and the historical sleep quality data based on the first weight and the second weight to determine the first mattress shape data of the smart mattress; if the difference is greater than the difference threshold, determine that a weight corresponding to the body change condition is a third weight, and a weight corresponding to the historical sleep quality is a fourth weight, and perform weighted calculation on the body change condition of the user and the historical sleep quality data based on the third weight and the fourth weight to determine the first mattress shape data of the smart mattress; wherein the first weight is less than the third weight, and the second weight is greater than the fourth weight.

[0037] In an embodiment, the second adjusting module is further configured to determine mattress shape optimization parameters corresponding to the sleep posture; and optimize the first mattress shape data according to the mattress shape optimization parameters to obtain second mattress shape data corresponding to the smart mattress.

[0038] In an embodiment, the mattress control device further includes a time determining module configured to acquire a plurality of historical bed-in times of the target user; determine a bed-in time range according to the plurality of historical bed-in times; and if it is determined that a current time is within the bed-in time range, perform the steps of determining the first mattress shape data of the smart mattress according to the body data and the historical sleep quality data of the target user, and adjusting the shape of the smart mattress according to the first mattress shape data.

[0039] In an embodiment, the body data includes one or more of body weight, body fat, height, bone mass, and body age.

[0040] Embodiments of the present application disclose a smart mattress, which includes:

[0041] a memory storing executable program codes;

[0042] a processor coupled to the memory.

[0043] The processor invokes the executable program code stored in the memory to execute the method described in any of the above embodiments.

[0044] The embodiment of the present application discloses a computer readable storage medium, which stores a computer program, wherein the computer program causes the processor to execute the method described in any of the above embodiments when executed by the processor.

[0045] By the bed mattress control method and device, the intelligent bed mattress and the storage medium disclosed by the embodiment of the present application, the intelligent bed mattress can receive the body data of the target user sent by the body fat detection equipment, determine the first bed mattress shape data of the intelligent bed mattress according to the body data and the historical sleep data of the target user, and preliminarily adjust the shape of the intelligent bed mattress according to the first bed mattress shape data, so as to provide moderate support and comfort to ensure that the target user obtains preliminary relaxation after getting into bed. The intelligent bed mattress can also determine the sleep posture of the target user when detecting that the target user enters the sleep state, determine the second bed mattress shape data of the intelligent bed mattress in combination with the sleep posture of the target user and the first bed mattress shape data determined before, and adjust the shape of the intelligent bed mattress again according to the second bed mattress shape data. The secondary adjustment ensures that the intelligent bed mattress can provide appropriate support for different sleep postures, thereby improving the sleep experience of the user and improving the sleep quality of the user. In addition, since the preliminary adjustment is performed according to the first bed mattress shape data, the needs of the user's body can be met, the sleep experience of the user is customized, and the comfort and sleep quality of the user are further improved. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0047] Figure 1 is an application scenario diagram of a bed mattress control method disclosed by the embodiment of the present application;

[0048] Figure 2 is a flowchart of a bed mattress control method disclosed by the embodiment of the present application;

[0049] Figure 3 is a flowchart of another bed mattress control method disclosed by the embodiment of the present application;

[0050] Figure 4is a flowchart of a method for determining first mattress shape data of a smart mattress according to body data and historical sleep quality data of a target user, disclosed by embodiments of the present application.

[0051] Figure 5 is a modular schematic diagram of a mattress control device, disclosed by embodiments of the present application.

[0052] Figure 6 is an electronic block diagram of a smart mattress, disclosed by embodiments of the present application. DETAILED DESCRIPTION

[0053] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0054] It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present application are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to the process, method, product or device.

[0055] It can be understood that the terms "first", "second" and the like used in the present application can be used herein to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from another element. For example, without departing from the scope of the present application, the first mattress shape data can be referred to as the second mattress shape data, and similarly, the second mattress shape data can be referred to as the first mattress shape data. The first mattress shape data and the second mattress shape data are both mattress shape data, but they are not the same mattress shape data.

[0056] The embodiments of the present application disclose a mattress control method and device, a smart mattress and a storage medium, which can improve the sleep quality of a user and meet the needs of the user's body.

[0057] The following will be described in detail with reference to the drawings.

[0058] As Figure 1 shown, Figure 1This is a schematic diagram illustrating an application scenario of a mattress control method disclosed in an embodiment of this application. The application scenario may include a smart mattress 110, a body fat detection device 120, and a target user 130. The smart mattress 110 can detect whether the user on it is asleep. The smart mattress 110 can also adjust its shape to make the target user 130 more comfortable. The body fat detection device 120 may include a body fat scale, body fat analyzer, etc., and is not limited thereto. The body fat detection device 120 can detect the body data of the target user 130. The body fat detection device 120 and the smart mattress 110 are communicatively connected for information exchange.

[0059] Specifically, when the body fat detection device 120 detects the body data of the target user 130, the body fat detection device 120 can send the body data to the smart mattress 110. The smart mattress 110 can receive the body data of the target user 130 sent by the body fat detection device 110, and determine the first mattress shape data of the smart mattress 110 based on the body data and the target user 130's historical sleep quality data, and adjust the shape of the smart mattress 110 according to the first mattress shape data. When the smart mattress 110 detects that the target user 130 has entered a sleep state, it can determine the sleeping posture of the target user 130, and then determine the second mattress shape data corresponding to the smart mattress 110 based on the sleeping posture and the first mattress shape data, and adjust the shape of the smart mattress 110 according to the second mattress shape data.

[0060] like Figure 2 As shown, Figure 2 This is a flowchart illustrating a mattress control method disclosed in an embodiment of this application. This mattress control method can be applied to the smart mattress described in the above embodiment and may include the following steps:

[0061] Step 210: Receive the target user's body data sent by the body fat detection device.

[0062] The smart mattress can receive body data from a body fat detection device sent to the target user. This body data can include one or more of the following: weight, body fat percentage, height, bone mass, and biological age. Bone mass refers to the content of bone tissue and bone matrix per unit volume. Bone tissue includes calcium and phosphorus, while bone matrix includes collagen, protein, and inorganic salts. It's important to understand that the body data can be any data detected by the body fat detection device; weight and body fat percentage are just examples. This body data can also include the target user's historical body data within a specific time period, which can refer to a recently preset historical period, such as the target user's historical body data for the past month.

[0063] Optionally, in order to protect the data security of the target user and avoid data leakage during data transmission, the body fat detection device can also send part of the detected body data to the smart mattress, wherein the body fat detection device can determine whether each detected body data has an impact on the user's sleep, and send the body data that can have an impact on the user's sleep to the smart mattress.

[0064] In one embodiment, the smart mattress can receive the body data sent by the body fat detection device, determine the user identity of the target user according to the detection sensor arranged around the body fat detection device, and then take the received body data as the body data of the target user for subsequent processing. The detection sensor arranged around the body fat detection device can include but is not limited to an image sensor, an iris sensor, etc. When the smart mattress receives the body data sent by the body fat detection device, it can send a data collection instruction to the detection sensor. The detection sensor collects user data corresponding to the target user on the body fat detection device (such as an image containing the user's face, a user's iris image, etc.) according to the data collection instruction, and sends it to the smart mattress. The smart mattress identifies the user identity of the target user according to the user data collected by the detection sensor. For example, the image containing the user's face can be subjected to face recognition, the face contained in the image can be extracted, and the extracted face can be matched with the pre-recorded face in the database to determine the pre-recorded face matched with the extracted face, and the user identity corresponding to the matched pre-recorded face can be determined as the user identity of the target user. By implementing this embodiment, when the body fat detection device cannot identify the user, other detection sensors can be used to identify the target user together, and through the cooperation between various devices, the accuracy of the target user corresponding to the body data is improved.

[0065] As an optional implementation, after receiving the body data of the target user, the smart mattress can compare the body data with the historical body data of the target user detected last time to determine whether the received body data this time is normal. If the received body data this time is normal, the subsequent step 220 is executed. If the received body data this time is not normal, it means that the user identity of the target user identified currently is wrong. The smart mattress can re-identify the user identity of the target user through the detection sensor in the above embodiment or through the body fat detection device.

[0066] Further, the smart mattress can calculate a first difference between the current received body data and the last detected historical body data, and calculate a time difference between the current time and the time of the last detection, determine a data variation range corresponding to the time difference, the data variation range being used to represent a normal variation range of the body data under the time difference. If the first difference is within the data variation range, it is determined that the body data received by the smart mattress is normal, and if the first difference is not within the data variation range, it is determined that the body data received by the smart mattress is abnormal. Taking the weight in the body data as an example, the time difference is 24 hours, and the data variation range can be -3 kg (kilogram) to 3 kg, i.e. the range of weight loss of 3 kg to weight gain of 3 kg, whether the weight difference between the current received weight and the last detected weight is within the range of -3 kg to 3 kg can be determined, if yes, it is determined that the current received weight is normal, if not, it is determined that the current received weight is abnormal. By implementing this embodiment, the accuracy of the body data is further ensured by verifying the body data.

[0067] In step 220, first mattress shape data of the smart mattress is determined according to the body data and the historical sleep quality data of the target user, and the shape of the smart mattress is adjusted according to the first mattress shape data.

[0068] The smart mattress can determine the first mattress shape data of the smart mattress according to the body data and the historical sleep quality data of the target user, wherein the historical sleep quality data can refer to the related data generated by the target user in the past sleep cycle, and the historical sleep quality data can include one or more of sleep duration, wake-up times, sleep depth, etc. Optionally, the smart mattress can include a plurality of mattress areas, and the mattress shape data can include the height, curvature, inclination, hardness, etc. of each mattress area to adapt to the body data of the target user and provide better human contact points, which is not limited. Optionally, the shape determination model can be pre-stored in the smart mattress, and the shape determination model is pre-trained according to training data, and the training data can include sample body data and sample sleep quality data of a plurality of sample users. The smart mattress can input the body data and the historical sleep quality data of the target user into the shape determination model to obtain the first mattress shape data of the smart mattress.

[0069] In an embodiment, the historical sleep quality data of the target user can include a plurality of sets of sleep quality data, each set of sleep quality data corresponding to a plurality of historical mattress shape data and a plurality of historical body data, each set of sleep quality data can include sleep duration, wake-up times, sleep depth of the target user in the case of corresponding historical mattress shape data, the smart mattress can analyze each set of sleep quality data of the target user, the corresponding historical mattress shape data and the corresponding historical body data, determine the data correlation between the body data, the mattress shape data and the sleep quality data, and determine the first mattress shape data of the smart mattress according to the data correlation and the body data currently received by the body fat detection device, so that the target user obtains better sleep quality.

[0070] The smart mattress can adjust the shape of the smart mattress according to the first mattress shape data. Wherein, the smart mattress can adjust the shape in multiple ways, optionally, the smart mattress can be built-in air bags, and the air bags of different mattress regions are controlled to inflate or deflate according to the first mattress shape data, so as to adjust the inflation degree of the air bags of different mattress regions, thereby changing the hardness and shape of the mattress regions. Optionally, the inside of the smart mattress can be integrated with mechanical elements, which are adjustable, for example, adjustable springs or brackets, the smart mattress can adjust the mechanical elements according to the first mattress shape data, so as to change the curvature, inclination, height, etc. of each mattress region of the smart mattress. Optionally, the smart mattress can also include materials that can respond to external pressure, such as shape memory foam, the smart mattress can make the smart mattress adaptively deform through heat or pressure according to the first mattress shape data.

[0071] Step 230, when it is detected that the target user enters a sleep state, the sleep posture of the target user is determined.

[0072] Optionally, the smart mattress can monitor the motion data of the target user through the sensor arranged inside the smart mattress, the motion data can refer to the data of the motion generated by the user's body, such as turning over, moving, etc. When the target user enters a sleep state, the body activity of the target user will gradually decrease until it stops, therefore, the smart mattress can compare the motion data of the target user with a preset motion threshold, if the motion data of the target user is lower than the motion threshold and maintains for a preset time, the smart mattress determines that the target user enters a sleep state.

[0073] Optionally, the smart mattress can also be provided with a biological sensor, through which the smart mattress can monitor the heart rate and breathing frequency of the target user. When the target user enters a sleep state, the heart rate and breathing will become more stable, therefore, the smart mattress can analyze the change of the heart rate and the change of the breathing frequency to determine whether the target user enters a sleep state.

[0074] Optionally, the smart mattress can also be provided with an EEG (Electroencephalogram) sensor, which can monitor the brain waves of the target user, so as to monitor the brain activity of the target user. The smart mattress can obtain the brain waves monitored by the EEG sensor, and compare the brain waves with characteristic brain waves of different sleep stages, so as to determine whether the target user enters a sleep state.

[0075] Optionally, the smart mattress can also detect the breathing sound of the target user through the sound sensor, and determine whether the user enters a sleep state through the breathing sound.

[0076] It can be understood that the above method of detecting whether the target user enters a sleep state can be used alone or in combination, and the embodiments of the present application do not limit this.

[0077] When it is detected that the target user enters a sleep state, the smart mattress can determine the sleep posture of the target user. The smart mattress can include a plurality of pressure sensors for monitoring the pressure distribution of the target user on the smart mattress. The smart mattress can determine the sleep posture of the target user according to the pressure distribution detected by the plurality of pressure sensors. The sleep posture can include a supine posture, a lateral posture, a prone posture, and a curled posture. Optionally, the smart mattress can determine the sleep posture of the target user according to the pressure of a plurality of predetermined specific areas corresponding to a plurality of body parts of the target user. For example, in a supine posture, the pressure of the target user is mainly concentrated on the hips of the target user, and the hips of the user can correspond to a first specific area. When the pressure of the first specific area exceeds a first pressure threshold, it can be determined that the sleep posture of the target user is a supine posture. For example, in a lateral posture, the pressure of the target user is mainly concentrated on the hips and shoulders of the target user, and the shoulders of the user can correspond to a second specific area. When the pressure of the second specific area exceeds a second pressure threshold, and the pressure of the first specific area exceeds a third pressure threshold and is less than the first pressure threshold, it can be determined that the sleep posture of the target user is a lateral posture.

[0078] In step 240, according to the sleep posture and the first mattress shape data, the second mattress shape data corresponding to the smart mattress is determined, and the shape of the smart mattress is adjusted according to the second mattress shape data.

[0079] In one embodiment, the smart mattress can determine mattress shape optimization parameters corresponding to a sleeping posture. Based on these parameters, it optimizes first mattress shape data to obtain second mattress shape data. The mattress shape optimization parameters can be preset and correspond to the sleeping posture. Since the pressure distribution in each sleeping posture is relatively fixed, preset mattress shape optimization parameters can improve the speed of determining the second mattress shape data. These parameters include optimization parameter values ​​for each mattress area to optimize the first mattress shape data for each area, resulting in the second mattress shape data and providing the target user with a better sleep experience. For example, in a supine position, the optimization parameter values ​​for the mattress area where the target user's back is located are used to increase the height of that area, providing more support for the user's back.

[0080] In this embodiment, the smart mattress can receive body data of the target user sent by a body fat detection device. Based on this body data and the target user's historical sleep data, it determines the first mattress shape data and initially adjusts the shape of the smart mattress according to the first mattress shape data to provide appropriate support and comfort, ensuring that the target user achieves initial relaxation after getting into bed. The smart mattress can also determine the target user's sleeping posture when it detects that the target user has entered a sleep state. Combining the target user's sleeping posture with the previously determined first mattress shape data, it determines the second mattress shape data and adjusts the shape of the smart mattress again according to the second mattress shape data. This secondary adjustment ensures that the smart mattress can provide appropriate support for different sleeping postures, thereby improving the user's sleep experience and sleep quality. Furthermore, since this initial adjustment is based on the first mattress shape data, it can meet the user's physical needs, tailoring a sleep experience for the user and further enhancing the user's comfort and sleep quality.

[0081] like Figure 3 As shown, Figure 3 This is a flowchart illustrating another mattress control method disclosed in an embodiment of this application. This mattress control method can be applied to the smart mattress in the above embodiment, and the mattress control method may include the following steps:

[0082] Step 310: Receive the target user's body data sent by the body fat detection device.

[0083] Step 320: Obtain multiple historical bedtimes of the target user.

[0084] It can be understood that although more users will use the body fat detection device to detect body data before going to bed, the target user does not necessarily go to bed every time when the body fat detection device is used to detect body data. Therefore, the smart mattress can obtain multiple historical bed times of the target user to determine whether the user will go to bed in the subsequent step. Optionally, the smart mattress can save the time of the target user going to bed this time as the historical bed time when the target user stays on the smart mattress for a preset sleep duration.

[0085] Step 330, determining a bed time range according to the multiple historical bed times.

[0086] The smart mattress can select an abnormal historical bed time from the multiple historical bed times, the average value of the difference between the abnormal historical bed time and other historical bed times being greater than an abnormal threshold. Then, the smart mattress can determine the earliest historical bed time and the latest historical bed time from the multiple historical bed times after removing the abnormal historical bed time. The smart mattress can determine the bed time range according to the earliest historical bed time and the latest historical bed time, for example, the bed time range can be 23:30 to 24:00. After determining the bed time range, the smart mattress can determine whether the current time is within the bed time range. If it is determined that the current time is within the bed time range, step 340 can be performed. If it is determined that the current time is not within the bed time range, it can be determined that the target user only detects body data and does not intend to go to bed. The smart mattress can also determine the first mattress shape data of the smart mattress according to the body data and the historical sleep quality data of the target user after detecting that the target user goes to bed and the duration of the smart mattress reaches the sleep required duration, and adjust the shape of the smart mattress according to the first mattress shape data.

[0087] Optionally, if the user inputs a preset bed time range in advance, the smart mattress can compare the bed time range determined according to the multiple historical bed times with the preset bed time range to obtain a new bed time range. Optionally, the smart mattress can take the intersection of the bed time range and the preset bed time range as the new bed time range. Optionally, the smart mattress can take the union of the bed time range and the preset bed time range as the new bed time range.

[0088] Step 340, if it is determined that the current time is within the bed time range, determining the first mattress shape data of the smart mattress according to the body data and the historical sleep quality data of the target user, and adjusting the shape of the smart mattress according to the first mattress shape data.

[0089] Step 350, determining the sleep posture of the target user when detecting that the target user enters a sleep state.

[0090] Step 360: Based on the sleeping posture and the shape data of the first mattress, determine the shape data of the second mattress corresponding to the smart mattress, and adjust the shape of the smart mattress according to the shape data of the second mattress.

[0091] In this embodiment, after receiving the target user's body data sent by the body fat detection device, the smart mattress can obtain multiple historical bedtimes of the target user, determine the bedtime range based on the multiple historical bedtimes, and only execute the subsequent steps of controlling mattress deformation when it is determined that the current time is within the bedtime range. This can accurately control the smart mattress and reduce the power consumption of the smart mattress.

[0092] like Figure 4 As shown, Figure 4 This is a flowchart illustrating a method for determining the first mattress shape data of a smart mattress based on body data and the target user's historical sleep quality data, as disclosed in an embodiment of this application. This method can be applied to the smart mattress in the above embodiment and may include the following steps:

[0093] Step 410: Determine the changes in the user's physical condition based on the target user's historical physical data within the historical time period.

[0094] A smart mattress can determine changes in a user's body based on their body data. These changes include changes in the user's physical development or aging process. These changes refer to how the user's body data has changed over a historical period.

[0095] Here, "user's physical development status" refers to changes in a user's physical data over a historical period, such as a 2cm increase in height or an increase in body fat. "User's physical aging status" refers to changes in a user's physical data over a historical period, such as a 2-year increase in biological age or a decrease in bone mass. It's understood that "user's physical development status" could be an increase or decrease in one metric, and "user's physical aging status" could also be an increase or decrease in one metric; there are no restrictions on this.

[0096] Step 420: Determine the first mattress shape data of the smart mattress based on the user's physical changes and the target user's historical sleep quality data in the historical time period.

[0097] The intelligent mattress can determine the first mattress shape data of the intelligent mattress according to the user body change condition and the historical sleep quality data of the target user in the historical time period, so that the first mattress shape data can adapt to the development or aging of the user body and improve the sleep quality of the user. Optionally, the training data of the shape determination model in the above embodiment can also include the sample body change condition of the sample user, and the intelligent terminal can input the user body change condition and the historical sleep quality data into the shape determination model in the above embodiment to obtain the first mattress shape data.

[0098] In the embodiments of the present application, the intelligent mattress can determine the user body change condition according to the historical body data of the target user in the historical time period, and determine the first mattress shape data of the intelligent mattress according to the user body change condition and the historical sleep quality data of the target user in the historical time period, which can improve the accuracy of the first mattress shape data.

[0099] In one embodiment, the intelligent mattress can obtain the body target data corresponding to the target user, and predict the body prediction data after the preset time according to the user body change condition, and then determine the difference between the body prediction data and the body target data. The intelligent mattress can determine the first mattress shape data of the intelligent mattress according to the difference, the user body change condition and the historical sleep quality data.

[0100] The body target data is used to indicate the data that the body data of the target user needs to reach after the preset time, for example, the height of the target user needs to increase by 5 cm in half a year, and the user body change condition represents the change condition of the body data of the target user after the historical time period, for example, the height of the target user has increased by 1 cm in the last month. The intelligent mattress can predict the body prediction data after the preset time according to the user body change condition of the target user in the historical time period, for example, the body prediction data after the preset time can be that the height of the target user increases by 6 cm in half a year. The intelligent mattress can subtract the body prediction data from the body target data to obtain the difference between the body prediction data and the body target data, which can include positive and negative values. The positive value can represent that the body prediction data does not reach the body target data, and the negative value can represent that the body prediction data exceeds the body target data.

[0101] In the embodiment, the smart mattress obtains body prediction data based on the body change of the user, compares the body prediction data with the body target data, obtains a difference between the body prediction data and the body target data, and determines the first mattress shape data of the smart mattress based on the difference, the body change of the user and the historical sleep quality data, so as to further improve the first mattress shape data, thereby improving the balance between meeting the needs of the user and improving the sleep quality of the user.

[0102] As an optional implementation, the step of determining the first mattress shape data of the smart mattress based on the difference, the body change of the user and the historical sleep quality data can include: if the difference is less than or equal to a difference threshold, determining that a weight corresponding to the body change is a first weight, and a weight corresponding to the historical sleep quality is a second weight, and performing weighted calculation on the body change of the user and the historical sleep quality data based on the first weight and the second weight to determine the first mattress shape data of the smart mattress; if the difference is greater than the difference threshold, determining that a weight corresponding to the body change is a third weight, and a weight corresponding to the historical sleep quality is a fourth weight, and performing weighted calculation on the body change of the user and the historical sleep quality data based on the third weight and the fourth weight to determine the first mattress shape data of the smart mattress.

[0103] When the difference is less than or equal to the difference threshold, it indicates that the body prediction data is close to or has reached the body target data, and the smart mattress can take the sleep quality as the adjustment focus of the mattress shape, and improve the sleep quality of the user in the case that the target user can reach the body target data after a preset time. When the difference is greater than the difference threshold, it indicates that the body prediction data has not reached the body target data and the difference is large, and the smart mattress can take the body change as the adjustment focus of the mattress shape, and reduce the importance of the sleep quality in the case that the target user cannot reach the body target data after a preset time, and preferentially make the mattress shape help the user to reach the body target data after a preset time. Therefore, the first weight can be less than the third weight, and the second weight can be greater than the fourth weight.

[0104] Optionally, the smart mattress can input the weight corresponding to the body change, the weight corresponding to the historical sleep quality, the body change of the user and the historical sleep quality data into the shape determination model in the above embodiment to obtain the first mattress shape data. The weight corresponding to the body change and the weight corresponding to the historical sleep quality can be used as parameters in the model for model calculation.

[0105] According to the embodiment, the intelligent mattress adjusts the shape of the intelligent mattress according to the first mattress shape data, which can improve the sleep quality of the user and help the user to reach the body target data after the preset time length, and further improve the balance between meeting the physical needs of the user and improving the sleep quality of the user.

[0106] As shown in Figure 5 , Figure 5 is a modular schematic diagram of a mattress control device disclosed by an embodiment of the present application. The mattress control device 500 is applied to the intelligent mattress in the above embodiment. The mattress control device can include a data receiving module 510, a first adjusting module 520, a posture determining module 530, and a second adjusting module 540, wherein:

[0107] The data receiving module 510 is configured to receive the body data of the target user sent by the body fat detection device.

[0108] The first adjusting module 520 is configured to determine the first mattress shape data of the intelligent mattress according to the body data and the historical sleep quality data of the target user, and adjust the shape of the intelligent mattress according to the first mattress shape data.

[0109] The posture determining module 530 is configured to determine the sleep posture of the target user when it is detected that the target user enters a sleep state.

[0110] The second adjusting module 540 is configured to determine the second mattress shape data corresponding to the intelligent mattress according to the sleep posture and the first mattress shape data, and adjust the shape of the intelligent mattress according to the second mattress shape data.

[0111] In one embodiment, the first adjusting module 520 is further configured to determine the body change condition of the user according to the historical body data, wherein the body change condition of the user includes the body development condition of the user or the body aging condition of the user; and determine the first mattress shape data of the intelligent mattress according to the body change condition of the user and the historical sleep quality data of the target user in the historical time period.

[0112] In one embodiment, the first adjusting module 520 is further configured to obtain the body target data corresponding to the target user, wherein the body target data is used to indicate the data that the body data of the target user needs to reach after a preset time; predict the body prediction data after the preset time according to the body change condition of the user; determine the difference between the body prediction data and the body target data; and determine the first mattress shape data of the intelligent mattress according to the difference, the body change condition of the user, and the historical sleep quality data.

[0113] In an embodiment, the first adjusting module 520 is further configured to: if the difference value is less than or equal to a difference value threshold, determine that a weight corresponding to the body change condition is a first weight, and a weight corresponding to the historical sleep quality is a second weight, and perform weighted calculation on the body change condition and the historical sleep quality data of the target user based on the first weight and the second weight to determine the first mattress shape data of the smart mattress; if the difference value is greater than the difference value threshold, determine that the weight corresponding to the body change condition is a third weight, and the weight corresponding to the historical sleep quality is a fourth weight, and perform weighted calculation on the body change condition and the historical sleep quality data of the target user based on the third weight and the fourth weight to determine the first mattress shape data of the smart mattress; wherein the first weight is less than the third weight, and the second weight is greater than the fourth weight.

[0114] In an embodiment, the second adjusting module 540 is further configured to: determine a mattress shape optimization parameter corresponding to the sleep posture; and optimize the first mattress shape data based on the mattress shape optimization parameter to obtain the second mattress shape data corresponding to the smart mattress.

[0115] In an embodiment, the mattress control device further includes a time determining module configured to: obtain a plurality of historical bed-in times of the target user; determine a bed-in time range based on the plurality of historical bed-in times; and if it is determined that the current time is within the bed-in time range, execute the steps of: determining the first mattress shape data of the smart mattress based on the body data and the historical sleep quality data of the target user, and adjusting the shape of the smart mattress according to the first mattress shape data.

[0116] In an embodiment, the body data includes one or more of body weight, body fat, height, bone mass, and body age.

[0117] In an embodiment, the smart mattress can receive the body data of the target user sent by the body fat detection device, determine the first mattress shape data of the smart mattress based on the body data and the historical sleep data of the target user, and preliminarily adjust the shape of the smart mattress based on the first mattress shape data, so as to provide moderate support and comfort to ensure that the target user obtains preliminary relaxation after getting into bed. The smart mattress can further determine the sleep posture of the target user when detecting that the target user enters a sleep state, determine the second mattress shape data of the smart mattress based on the sleep posture of the target user and the previously determined first mattress shape data, and adjust the shape of the smart mattress again based on the second mattress shape data, so as to ensure that the smart mattress can provide appropriate support for different sleep postures, thereby improving the sleep experience of the user and increasing the sleep quality of the user. In addition, since the preliminary adjustment is performed based on the first mattress shape data, the sleep experience of the user can be customized according to the user's body, and the comfort and sleep quality of the user are further improved.

[0118] As Figure 6 shown in one embodiment, an intelligent mattress can be provided, which can include:

[0119] a memory 610 storing executable program codes;

[0120] a processor 620 coupled with the memory 610;

[0121] The processor 620 invokes the executable program codes stored in the memory 610 to implement the mattress control method provided in each of the above embodiments.

[0122] The memory 610 can include a random access memory (RAM) and can also include a read-only memory (ROM). The memory 610 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 610 can include a program storage area and a data storage area, wherein the program storage area can store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing each of the above method embodiments, etc. The data storage area can also store data created by the intelligent mattress in use, etc.

[0123] The processor 620 can include one or more processing cores. The processor 620 connects various parts within the entire intelligent mattress through various interfaces and lines, and performs various functions of the intelligent mattress and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 610, and invoking data stored in the memory 610. Optionally, the processor 620 can be implemented in at least one of a hardware form of a digital signal processing (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA). The processor 620 can integrate a combination of one or more of a central processing unit (CPU), a graphics processor (GPU) and a modem, etc. Among them, the CPU is mainly used to process operating systems, user interfaces and application programs, etc.; the GPU is used to be responsible for rendering and drawing display content; and the modem is used to process wireless communication. It can be understood that the above-mentioned modem can also not be integrated into the processor 620, but can be implemented by a separate communication chip.

[0124] It can be understood that the smart mattress can include more or less structural elements than the above structural block diagram, for example, including a power module, a physical button, a WiFi (Wireless Fidelity) module, a speaker, a Bluetooth module, a sensor, etc., which are not limited herein.

[0125] The embodiments of the present application disclose a computer readable storage medium storing a computer program, wherein the computer program causes a computer to execute the method described in the above embodiments.

[0126] In addition, the embodiments of the present application further disclose a computer program product, when the computer program product runs on a computer, causes the computer to execute all or part of the steps in any one of the mattress control methods described in the above embodiments.

[0127] A person of ordinary skill in the art can understand that all or part of the steps in the above embodiments can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer readable storage medium, including a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically-Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical disk memories, magnetic disk memories, magnetic tape memories, or any other computer readable medium capable of carrying or storing data.

[0128] The above describes in detail the mattress control method, the device, the smart mattress and the storage medium disclosed by the embodiments of the present application. The principles and implementation manners of the present application are described by applying specific examples in this paper. The above embodiment is only used to help understand the method and the core idea of the present application. Meanwhile, for a person of ordinary skill in the art, according to the idea of the present application, the specific implementation manner and the application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A mattress control method, characterized in that, Applied to a smart mattress, the method includes: The system receives body data of the target user sent by the body fat detection device, the body data including the target user's historical body data corresponding to a historical time period; Based on the body data and the target user's historical sleep quality data, the first mattress shape data of the smart mattress is determined, and the shape of the smart mattress is adjusted according to the first mattress shape data; When the target user is detected to have entered a sleep state, the sleep posture of the target user is determined; Based on the sleeping posture and the first mattress shape data, determine the second mattress shape data corresponding to the smart mattress, and adjust the shape of the smart mattress according to the second mattress shape data; The step of determining the first mattress shape data of the smart mattress based on the body data and the target user's historical sleep quality data includes: Based on the historical physical data, the user's physical changes are determined; the user's physical changes include the user's physical development or the user's physical aging. Obtain the target body data corresponding to the target user; the target body data is used to indicate the data that the target user's body data needs to reach after a preset time. Based on the changes in the user's physical condition, predict the body prediction data after the preset time. Determine the difference between the predicted body data and the target body data; Based on the difference, the user's physical changes, and the historical sleep quality data, the first mattress shape data of the smart mattress is determined.

2. The method according to claim 1, characterized in that, The step of determining the first mattress shape data of the smart mattress based on the difference, the user's physical changes, and the historical sleep quality data includes: If the difference is less than or equal to the difference threshold, the weight corresponding to the physical changes is determined as the first weight, and the weight corresponding to the historical sleep quality is determined as the second weight. The user's physical changes and the historical sleep quality data are weighted and calculated based on the first weight and the second weight to determine the first mattress shape data of the smart mattress. If the difference is greater than the difference threshold, the weight corresponding to the physical changes is determined as the third weight, and the weight corresponding to the historical sleep quality is determined as the fourth weight. The user's physical changes and historical sleep quality data are weighted and calculated based on the third weight and the fourth weight to determine the first mattress shape data of the smart mattress. Wherein, the first weight is less than the third weight, and the second weight is greater than the fourth weight.

3. The method according to claim 1, characterized in that, The step of determining the second mattress shape data corresponding to the smart mattress based on the sleeping posture and the first mattress shape data includes: Determine the mattress shape optimization parameters corresponding to the sleep posture; Based on the mattress shape optimization parameters, the first mattress shape data is optimized to obtain the second mattress shape data corresponding to the smart mattress.

4. The method according to claim 1, characterized in that, After receiving the body data of the target user sent by the body fat detection device, the method further includes: Obtain multiple historical bedtimes of the target user; The range of bedtimes is determined based on the aforementioned multiple historical bedtimes; If it is determined that the current time is within the time range for going to bed, then the steps of determining the first mattress shape data of the smart mattress based on the body data and the target user's historical sleep quality data, and adjusting the shape of the smart mattress according to the first mattress shape data are executed.

5. The method according to any one of claims 1 to 4, characterized in that, The body data includes one or more of the following: weight, body fat percentage, height, bone mass, and body age.

6. A mattress control device, characterized in that, The device, used in a smart mattress, includes: The data receiving module is used to receive the body data of the target user sent by the body fat detection device. The body data includes the historical body data of the target user in a historical time period. The first adjustment module is used to determine the first mattress shape data of the smart mattress based on the body data and the target user's historical sleep quality data, and adjust the shape of the smart mattress according to the first mattress shape data. The posture determination module is used to determine the sleep posture of the target user when the target user is detected to have entered a sleep state; The second adjustment module is used to determine the second mattress shape data corresponding to the smart mattress based on the sleeping posture and the first mattress shape data, and adjust the shape of the smart mattress according to the second mattress shape data; The first adjustment module is further configured to: determine the user's physical changes based on the historical physical data; the user's physical changes include the user's physical development or the user's physical aging; acquire the target physical data corresponding to the target user; the target physical data is used to indicate the data that the target user's physical data needs to reach after a preset time; predict the predicted physical data after the preset time based on the user's physical changes; determine the difference between the predicted physical data and the target physical data; and determine the first mattress shape data of the smart mattress based on the difference, the user's physical changes, and the historical sleep quality data.

7. A smart mattress, characterized in that, include: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein, when executed by a processor, the computer program causes the processor to perform the method according to any one of claims 1 to 5.

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