A data processing method, device and equipment based on a smart mattress and a medium

Abstract

Embodiments of the present application disclose a data processing method and device based on a smart mattress, equipment and medium. Among them, the method comprises: obtaining the initial air pressure data of the target mattress; extracting the effective air pressure data from the initial air pressure data based on the preset threshold; determining the feature information according to the effective air pressure data; determining the action state of the target user according to the feature information; wherein the action state includes any one of the following: getting into bed, turning over and getting out of bed. The technical scheme can identify the action state of the target user, improve the real-time and accuracy, and reduce the missed detection rate and delay.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, and in particular to a data processing method and device based on a smart mattress, equipment and a medium. BACKGROUND

[0002] In today's era of popularization of artificial intelligence and the Internet of Things, more and more products are developing towards intelligence, including the mattress we sleep on every day. The smart mattress is a mattress designed by combining traditional mattresses with modern technology, aiming at human sleep habits.

[0003] The smart mattress can be used to detect various states of the user when sleeping, and the air bag is used to monitor the air pressure of the user getting out of bed. The smart mattress can determine the state of the user getting out of bed according to the change of the air pressure of the air bag.

[0004] At present, the smart mattress determines the state of getting out of bed based on the air pressure threshold and the number of channels, but there may be missed detection or detection delay, such as a user with a lighter weight or a smaller individual, which may result in missed detection of getting into bed, missed detection of getting out of bed, or delayed detection of getting into bed and delayed detection of getting out of bed, thereby affecting the use experience of the smart mattress. SUMMARY

[0005] The present application provides a data processing method and device based on a smart mattress, which can identify the action state of a target user, improve real-time performance and accuracy, and reduce the rate of missed detection and delay.

[0006] According to an aspect of the present application, a data processing method based on a smart mattress is provided, comprising:

[0007] obtaining initial air pressure data of a target mattress; wherein the initial air pressure data carries time point information;

[0008] extracting effective air pressure data from the initial air pressure data based on a preset threshold;

[0009] determining feature information according to the effective air pressure data;

[0010] determining the action state of a target user according to the feature information; wherein the action state includes any one of the following: getting into bed, turning over and getting out of bed.

[0011] Optionally, the initial air pressure data carries time point information; and the preset threshold includes a first threshold and a second threshold.

[0012] Optionally, extracting effective air pressure data from the initial air pressure data based on a preset threshold comprises:

[0013] determining a starting time point according to the first threshold and the initial air pressure data;

[0014] determining an ending time point according to the second threshold and the initial air pressure data;

[0015] determining the initial air pressure data falling between the starting time point and the ending time point as valid air pressure data.

[0016] Optionally, determining the initial air pressure data falling between the starting time point and the ending time point as valid air pressure data comprises:

[0017] determining a valid duration according to the starting time point and the ending time point;

[0018] determining the initial air pressure data falling between the starting time point and the ending time point as valid air pressure data if the valid duration is greater than a set time threshold.

[0019] Optionally, determining a starting time point according to the first threshold and the initial air pressure data comprises:

[0020] filtering the initial air pressure data to obtain filtered air pressure data;

[0021] determining time point information corresponding to any one of the at least two continuous air pressure data as the starting time point if the filtered air pressure data is greater than the first threshold.

[0022] Correspondingly, determining an ending time point according to the second threshold and the initial air pressure data comprises:

[0023] determining time point information corresponding to any one of the at least two continuous air pressure data as the ending time point if the filtered air pressure data is less than the second threshold.

[0024] Optionally, the feature information comprises a change rate of the valid air pressure data and an air pressure difference value, wherein the air pressure difference value is a difference between the valid air pressure data corresponding to the ending time point and the starting time point.

[0025] Optionally, determining the action state of the target user according to the feature information comprises:

[0026] determining the action state of the target user as a getting-into-bed action if the air pressure difference value is positive and the change rate is greater than a first preset change rate.

[0027] If the air pressure difference value is positive, and the change rate is greater than the second preset change rate and less than the first preset change rate, it is determined that the action state of the target user is a turning-over action.

[0028] If the air pressure difference value is negative, and the change rate is negative, it is determined that the action state of the target user is a bed-leaving action.

[0029] According to another aspect of the present application, a data processing apparatus based on a smart mattress is provided, comprising:

[0030] An initial air pressure data acquisition module is configured to acquire initial air pressure data of a target mattress; wherein the initial air pressure data carries time point information.

[0031] An effective air pressure data extraction module is configured to extract effective air pressure data from the initial air pressure data based on a preset threshold.

[0032] A feature information determination module is configured to determine feature information according to the effective air pressure data.

[0033] An action state determination module is configured to determine an action state of a target user according to the feature information; wherein the action state comprises any one of the following: a getting-into-bed action, a turning-over action, and a bed-leaving action.

[0034] According to another aspect of the present application, an electronic device is provided, comprising:

[0035] at least one processor; and

[0036] a memory in communication connection with the at least one processor; wherein,

[0037] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the data processing method based on a smart mattress according to any one of the embodiments of the present application.

[0038] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to execute the data processing method based on a smart mattress according to any one of the embodiments of the present application.

[0039] The technical scheme of the embodiment of the present application comprises the following steps: obtaining initial air pressure data of a target mattress; extracting effective air pressure data from the initial air pressure data based on a preset threshold; determining feature information according to the effective air pressure data; determining a motion state of a target user according to the feature information; wherein the motion state comprises any one of the following: a getting-into-bed motion, a turning-over motion and a getting-out-of-bed motion. The technical scheme can identify the motion state of the target user, improve real-time performance and accuracy, and reduce the missed detection rate and delay.

[0040] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. 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.

[0042] Figure 1 is a flow chart of a data processing method based on a smart mattress according to an embodiment of the present application;

[0043] Figure 2 is a flow chart of a data processing method based on a smart mattress according to an embodiment of the present application;

[0044] Figure 3 is a structural schematic diagram of a data processing device based on a smart mattress according to an embodiment of the present application;

[0045] Figure 4 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to enable those skilled in the art to better understand the present application scheme, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0047] It should be noted that the terms "first", "second", and the like in the description and claims of the application and the above drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0048] Embodiment one

[0049] Figure 1 It is a flowchart of a data processing method based on a smart mattress according to embodiment one of the application. The embodiment can be applicable to the determination of the action state of the user based on the smart mattress. The method can be executed by a data processing device based on a smart mattress. The data processing device based on a smart mattress can be realized in the form of hardware and / or software, and can be configured in an electronic device with data processing capability. As shown in the figure, the method comprises: Figure 1

[0050] S110, obtaining initial air pressure data of a target mattress.

[0051] In this embodiment, the smart mattress can be provided with at least one air bag whose inflation and deflation can be controlled. The initial air pressure data can be understood as the initial air pressure data currently collected by the target mattress. The initial air pressure data can include a lot of air pressure data of the target mattress. The initial air pressure data in this embodiment can carry time point information, wherein the time point information can be understood as the corresponding time when the air pressure data of the target mattress is collected. In this embodiment, the initial air pressure data of the target mattress obtained can all carry corresponding time point information, so as to determine the specific time of collection. The technical solution of this embodiment can be directly used in embedded terminal, and the air pressure data of the target mattress can be collected through the mattress interface connected to the computer terminal to obtain the initial air pressure data of the target mattress.

[0052] Further, the initial air pressure data in this embodiment can not carry time point information, and can be marked by using a count point marking method for each collected initial air pressure data, so as to determine the count point marking information corresponding to the initial air pressure data.

[0053] ​S120, extract valid air pressure data from the initial air pressure data based on a preset threshold.

[0054] The preset threshold can be a preset threshold. The preset threshold includes a first threshold and a second threshold. The first threshold can be understood as a starting threshold of the valid air pressure data. The second threshold can be understood as an ending threshold of the valid air pressure data. Specifically, the first threshold and the second threshold can be determined by collecting data of various action states and different users. Different users can be different in body size or body mass index (BMI), etc. The valid air pressure data can be understood as air pressure data of an effective activity segment; the valid air pressure data can be used to determine the air pressure data of the action state of the user. In this embodiment, the valid air pressure data can be extracted from the initial air pressure data based on the preset threshold.

[0055] S130, determining feature information according to the valid air pressure data.

[0056] The feature information can include a change rate of the valid air pressure data and an air pressure difference value; the air pressure difference value is the difference between the valid air pressure data corresponding to the ending time point and the starting time point. The ending time point can be understood as the ending time point of the valid air pressure data. The starting time point can be understood as the starting time point of the valid air pressure data. The change rate in this embodiment can be understood as the slope information of the valid air pressure data. The feature information can be understood as information used to determine the action state of the target user. In this embodiment, the feature information can be determined according to the valid air pressure data.

[0057] S140, determining the action state of the target user according to the feature information.

[0058] The action state includes any one of the following: getting-into-bed action, turning-over action, and getting-out-of-bed action. In this embodiment, the getting-into-bed action, turning-over action, and getting-out-of-bed action of the target user can be determined according to the change rate and air pressure difference value of the valid air pressure data. In this embodiment, the continuous getting-out-of-bed state of the target user can be obtained according to the action state of the target user.

[0059] In this embodiment, optionally, determining the action state of the target user according to the feature information includes: if the air pressure difference value is positive and the change rate is greater than a first preset change rate, determining that the action state of the target user is the getting-into-bed action; if the air pressure difference value is positive and the change rate is greater than a second preset change rate and less than the first preset change rate, determining that the action state of the target user is the turning-over action; and if the air pressure difference value is negative and the change rate is negative, determining that the action state of the target user is the getting-out-of-bed action.

[0060] The first preset change rate can be preset. For example, the first preset change rate in the embodiment can be 0.5. The second preset change rate can be preset. For example, the second preset change rate in the embodiment can be -0.5. The first preset change rate and the second preset change rate in the embodiment can be obtained based on data analysis of the collected air pressure data, or can be set according to actual requirements.

[0061] If the obtained air pressure difference value is positive and the change rate is greater than the first preset change rate, it is determined that the action state of the target user is a getting-into-bed action. If the air pressure difference value is positive, the change rate is greater than the second preset change rate and less than the first preset change rate, it is determined that the action state of the target user is a turning-over action. If the air pressure difference value is negative and the change rate is also negative, it can be determined that the action state of the target user is a getting-out-of-bed state. In the embodiment, through such a setting, the action state of the target user can be accurately determined through the change rate of the air pressure data and the air pressure difference, and the real-time performance is strong and the accuracy is high.

[0062] The technical scheme of the embodiment of the application comprises the following steps: obtaining initial air pressure data of a target mattress; extracting effective air pressure data from the initial air pressure data based on a preset threshold; determining feature information according to the effective air pressure data; determining an action state of a target user according to the feature information; and the action state comprises any one of a getting-into-bed action, a turning-over action and a getting-out-of-bed action. The technical scheme can identify the action state of the target user, improve the real-time performance and the accuracy, and reduce the missed detection rate and the delay.

[0063] Embodiment two

[0064] Figure 2 is a flowchart of a data processing method based on an intelligent mattress according to the embodiment two of the application. The embodiment is optimized based on the above-mentioned embodiment. The specific optimization is that the effective air pressure data is extracted from the initial air pressure data based on a preset threshold, which comprises the following steps: determining a starting time point according to the first threshold and the initial air pressure data; determining an ending time point according to the second threshold and the initial air pressure data; and determining the initial air pressure data falling between the starting time point and the ending time point as the effective air pressure data. As shown in Figure 2 the method comprises the following steps:

[0065] S210, obtaining initial air pressure data of a target mattress.

[0066] S220, determining a starting time point according to the first threshold and the initial air pressure data.

[0067] The starting time point can be understood as a starting time point corresponding to the effective air pressure data. In this embodiment, the starting time point can be determined according to the first threshold value and the initial air pressure data through a setting mode.

[0068] In this embodiment, optionally, determining the starting time point according to the first threshold value and the initial air pressure data includes: performing filtering processing on the initial air pressure data to obtain filtered air pressure data; and if at least two continuous air pressure data of the filtered air pressure data are greater than the first threshold value, determining time point information corresponding to any one of the at least two continuous air pressure data as the starting time point.

[0069] The filtering processing can be understood as an operation of filtering processing on the initial air pressure data. In this embodiment, high-pass filtering of a certain size hertz can be performed on the initial air pressure data. The size can be set according to actual needs, and the size hertz in this embodiment can be 10 Hz. In this embodiment, the at least two continuous air pressure data can be air pressure data of at least two continuous windows. In this embodiment, high-pass filtering can be performed on the initial air pressure data to obtain filtered air pressure data. If the at least two continuous window air pressure data of the filtered air pressure data are greater than the first threshold value, the starting time point can be determined according to the time point corresponding to any one of the at least two continuous window air pressure data.

[0070] Specifically, the starting time point is determined according to time point information corresponding to the at least two continuous air pressure data. If the starting time point is determined according to time point information corresponding to two continuous air pressure data, any one of the two air pressure data can be taken as the starting time point. For example, the time point information corresponding to the last air pressure data of the two window air pressure data can be taken as the starting time point. In this embodiment, the starting time point of the effective air pressure data is determined according to the preset threshold value, which facilitates determination of the effective air pressure data.

[0071] S230, determining an ending time point according to the second threshold value and the initial air pressure data.

[0072] The ending time point can be understood as an ending time point corresponding to the effective air pressure data. In this embodiment, the ending time point can be determined according to the preset second threshold value and the initial air pressure data through a setting mode.

[0073] In this embodiment, optionally, correspondingly, determining the ending time point according to the second threshold value and the initial air pressure data includes: if at least two continuous air pressure data of the filtered air pressure data are less than the second threshold value, determining time point information corresponding to any one of the at least two continuous air pressure data as the ending time point.

[0074] In this embodiment, the at least two continuous air pressure data can be air pressure data of at least two continuous windows. In this embodiment, if the filtered air pressure data is less than the second threshold value for at least two continuous air pressure data, any one of the at least two air pressure data can be determined as the end time point. For example, the last air pressure data of the at least two continuous air pressure data can be determined as the end time point. In this embodiment, by setting the first threshold value and the second threshold value, the start time point and the end time point of the effective air pressure data can be determined, which facilitates the determination of the effective air pressure data.

[0075] S240, determining the initial air pressure data falling between the start time point and the end time point as the effective air pressure data.

[0076] In this embodiment, the duration between the start time point and the end time point can be determined first, and then the effective air pressure data of the corresponding period can be determined by judging whether the duration is valid.

[0077] In this embodiment, the initial air pressure data falling between the start time point and the end time point is determined as the effective air pressure data, including: determining an effective duration according to the start time point and the end time point; if the effective duration is greater than a set time threshold value, determining the initial air pressure data falling between the start time point and the end time point as the effective air pressure data.

[0078] In this embodiment, the effective duration can be understood as the duration between the start time point and the end time point. The effective duration in this embodiment can be obtained by the difference between the end time point and the start time point. In addition, if the obtained initial air pressure data does not carry time point information, but is marked by a set count point, the determination of the duration can be obtained by dividing the difference between the end point corresponding point and the start point corresponding point by the sampling rate. The sampling rate can be directly obtained according to the hardware device.

[0079] The set time threshold can be preset. The set time threshold in the embodiment can be obtained by data analysis according to the acquired air pressure data of different users, or can be set according to actual needs. In the embodiment, the effective duration between the start time point and the end time point can be determined, if the effective duration is greater than the set time threshold, the initial air pressure data between the start time point and the end time point can be determined as effective air pressure data; if the effective duration is not greater than the set time threshold, it can be considered that the air pressure data in this period is invalid. In the embodiment, by setting the time threshold to judge the effective duration, whether the air pressure data corresponding to the period is effective can be determined, which can avoid detecting the in-bed situation caused by the increase of pressure amplitude due to short-term abnormal situation.

[0080] In addition, in the embodiment, the initial air pressure data can be subjected to median filtering processing operation or other filtering processing that can make the data smoother before determining the effective air pressure data, so that the data can be smoother and more conducive to determining the effective air pressure data.

[0081] S250, determining feature information according to the effective air pressure data.

[0082] S260, determining the action state of the target user according to the feature information.

[0083] The technical scheme of the embodiment of the application comprises the following steps: acquiring initial air pressure data of a target mattress; determining a start time point according to a first threshold and the initial air pressure data; determining an end time point according to a second threshold and the initial air pressure data; determining initial air pressure data between the start time point and the end time point as effective air pressure data; determining feature information according to the effective air pressure data; determining the action state of the target user according to the feature information; wherein the action state comprises any one of the following: getting-into-bed action, turning-over action and getting-out-of-bed action. The technical scheme can identify the action state of the target user, further improve the real-time performance and accuracy, and reduce the missed detection rate and delay.

[0084] Embodiment three

[0085] Figure 3 is a structural schematic diagram of a data processing device based on an intelligent mattress according to the embodiment three of the application. As shown in the figure, Figure 3 The device comprises:

[0086] An initial air pressure data acquisition module 310 is configured to acquire initial air pressure data of a target mattress.

[0087] An effective air pressure data extraction module 320 is configured to extract effective air pressure data from the initial air pressure data based on a preset threshold.

[0088] determine feature information according to the effective air pressure data;

[0089] determine an action state of the target user according to the feature information; wherein the action state comprises any one of a getting-into-bed action, a turning action and a getting-out-of-bed action.

[0090] Optionally, the initial air pressure data carries time point information; and the preset threshold comprises a first threshold and a second threshold.

[0091] Optionally, the effective air pressure data extraction module 320 comprises:

[0092] a start time point determination unit configured to determine a start time point according to the first threshold and the initial air pressure data;

[0093] an end time point determination unit configured to determine an end time point according to the second threshold and the initial air pressure data;

[0094] an effective air pressure data determination unit configured to determine the initial air pressure data falling between the start time point and the end time point as effective air pressure data.

[0095] Optionally, the effective air pressure data determination unit is specifically configured to:

[0096] determine an effective duration according to the start time point and the end time point;

[0097] if the effective duration is greater than a set time threshold, determine the initial air pressure data falling between the start time point and the end time point as effective air pressure data.

[0098] Optionally, the start time point determination unit is specifically configured to:

[0099] perform filtering processing on the initial air pressure data to obtain filtered air pressure data;

[0100] if at least two continuous air pressure data of the filtered air pressure data are greater than the first threshold, determine time point information corresponding to any one of the at least two continuous air pressure data as the start time point;

[0101] Correspondingly, the end time point determination unit is specifically configured to:

[0102] if at least two continuous air pressure data of the filtered air pressure data are less than the second threshold, determine time point information corresponding to any one of the at least two continuous air pressure data as the end time point.

[0103] Optionally, the feature information comprises a change rate of the effective air pressure data and an air pressure difference value; wherein the air pressure difference value is a difference value between the effective air pressure data corresponding to the end time point and the start time point.

[0104] Optionally, the action state determination module 340 is specifically configured to:

[0105] If the air pressure difference value is positive and the change rate is greater than a first preset change rate, it is determined that the action state of the target user is a getting-into-bed action.

[0106] If the air pressure difference value is positive and the change rate is greater than a second preset change rate and less than the first preset change rate, it is determined that the action state of the target user is a turning-over action.

[0107] If the air pressure difference value is negative and the change rate is negative, it is determined that the action state of the target user is a getting-out-of-bed action.

[0108] The data processing apparatus based on the smart mattress provided in the embodiment of the application can execute the data processing method based on the smart mattress provided in any embodiment of the application, and has the corresponding function modules and beneficial effects of the execution method.

[0109] Embodiment Four

[0110] Figure 4 is a structural schematic diagram of an electronic device according to the embodiment four of the application. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (such as headsets, glasses, watches, etc.), and other similar computing devices. The components shown here, their connections, and their functions, as described above, are meant to be examples only, and are not intended to limit the implementations of the application described and / or claimed in this document.

[0111] As Figure 4As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer programs stored in the read-only memory (ROM) 12 or loaded into the random access memory (RAM) 13 from the storage unit 18. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0112] Various components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, a speaker, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0113] The processor 11 can be various general and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the smart mattress based data processing method.

[0114] In some embodiments, the smart mattress based data processing method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the smart mattress based data processing method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the smart mattress based data processing method by any other appropriate means, such as by means of firmware.

[0115] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a load programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0116] Computer programs used to implement the processes of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, can cause instructions defined in the flow charts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a standalone software package and partially on a remote machine or entirely on a remote machine or server.

[0117] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0118] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0119] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0120] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0121] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the present disclosure are achieved, and the present disclosure is not limited herein.

[0122] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A data processing method based on a smart mattress, characterized in that, include: Obtain the initial air pressure data of the target mattress; Effective air pressure data is extracted from the initial air pressure data based on a preset threshold. Characteristic information is determined based on the effective air pressure data; The target user's action state is determined based on the aforementioned feature information; wherein, the action state includes any one of the following: getting into bed, turning over, and getting out of bed; The initial air pressure data carries time point information; the preset threshold includes a first threshold and a second threshold; the first threshold is the starting threshold of the effective air pressure data; the second threshold is the ending threshold of the effective air pressure data; The step of extracting effective air pressure data from the initial air pressure data based on a preset threshold includes: The starting time point is determined based on the first threshold and the initial air pressure data; The end time point is determined based on the second threshold and the initial air pressure data; The effective duration is determined based on the start time point and the end time point; if the effective duration is greater than a set time threshold, the initial air pressure data falling between the start time point and the end time point is determined as the effective air pressure data. The process of determining the start time point based on the first threshold and the initial air pressure data, and determining the end time point based on the second threshold and the initial air pressure data, specifically includes: The initial air pressure data is filtered to obtain filtered air pressure data; If at least two consecutive pressure data points of the filtered air pressure data are greater than the first threshold, then the time point information corresponding to any one of the two consecutive pressure data points is determined as the start time point; if at least two consecutive pressure data points of the filtered air pressure data are less than the second threshold, then the time point information corresponding to any one of the two consecutive pressure data points is determined as the end time point.

2. The method according to claim 1, characterized in that, The feature information includes the rate of change of the effective air pressure data and the air pressure difference; wherein, the air pressure difference is the difference between the effective air pressure data corresponding to the end time point and the start time point.

3. The method according to claim 2, characterized in that, Determining the target user's action state based on the feature information includes: If the air pressure difference is positive and the rate of change is greater than the first preset rate of change, then the target user's action state is determined to be getting into bed. If the air pressure difference is positive, and the rate of change is greater than the second preset rate of change and less than the first preset rate of change, then the target user's action state is determined to be a rolling action. If the air pressure difference is negative and the rate of change is negative, then the target user's action state is determined to be an out-of-bed action.

4. A data processing device based on a smart mattress, characterized in that, include: The initial air pressure data acquisition module is used to acquire the initial air pressure data of the target mattress. An effective air pressure data extraction module is used to extract effective air pressure data from the initial air pressure data based on a preset threshold. The feature information determination module is used to determine feature information based on the effective air pressure data; An action state determination module is used to determine the action state of the target user based on the feature information; wherein, the action state includes any one of the following: getting into bed, turning over, and getting out of bed; The initial air pressure data carries time point information; the preset threshold includes a first threshold and a second threshold; the first threshold is the starting threshold of the effective air pressure data; the second threshold is the ending threshold of the effective air pressure data; The extraction of effective air pressure data from the initial air pressure data based on a preset threshold specifically includes: The starting time point is determined based on the first threshold and the initial air pressure data; The end time point is determined based on the second threshold and the initial air pressure data; The effective duration is determined based on the start time point and the end time point; if the effective duration is greater than a set time threshold, the initial air pressure data falling between the start time point and the end time point is determined as the effective air pressure data. The process of determining the start time point based on the first threshold and the initial air pressure data, and determining the end time point based on the second threshold and the initial air pressure data, specifically includes: The initial air pressure data is filtered to obtain filtered air pressure data; If at least two consecutive pressure data points of the filtered air pressure data are greater than the first threshold, then the time point information corresponding to any one of the two consecutive pressure data points is determined as the start time point; if at least two consecutive pressure data points of the filtered air pressure data are less than the second threshold, then the time point information corresponding to any one of the two consecutive pressure data points is determined as the end time point.

5. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the data processing method based on a smart mattress as described in any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the data processing method based on a smart mattress as described in any one of claims 1-3.

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