Bed heating device with mattress heating function and bed frame apparatus provided with same

Abstract

The present disclosure relates to a bed heating device with a mattress heating function, and includes an air heating module provided in a lower space of a frame supporting a bed mattress; a temperature controller configured to control a temperature of the air heating module; and a control module configured to control the air heating module to operate according to the temperature set by the temperature controller.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] A claim for priority under 35 U.S.C. § 119 is made to Korean Patent Application No. 10-2025-0003465 filed on Jan. 9, 2025 in the Korean Intellectual Property Office, the entire contents of which are hereby incorporated by reference.BACKGROUND1. Technical Field

[0002] The present disclosure relates to a bed heating device with a mattress heating function and a bed frame apparatus provided with the same.2. Description of Related Art

[0003] The conventional heating method is to raise the temperature of the floor of the room or to heat the air.

[0004] This heating method is suitable for sleeping on the floor, but has the disadvantage of having a little heating effect on the bed mattress.

[0005] To solve this problem, there has been an attempt to provide a heating effect by providing an air heating device inside the bed mattress, but there is a problem that there is not enough space inside the bed mattress, which causes damage to the mattress.

[0006] Accordingly, it is needed a device that can provide the heating effect to the bed mattress without damaging it, but this technology is not currently available.SUMMARY

[0007] The embodiment disclosed in the present disclosure is to provide a bed heating device capable of providing a heating effect to a bed mattress.

[0008] In addition, the embodiment disclosed in the present disclosure is to provide a heating effect to a bed mattress by heating the air in a lower space of a bed frame.

[0009] In addition, the embodiment disclosed in the present disclosure is to provide a bed heating device capable of providing different heating effects to upper and lower bodies of a user sleeping in a bed.

[0010] Technical problems of the inventive concept are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

[0011] In an aspect of the present disclosure, a bed heating device according to an embodiment of the present disclosure includes an air heating module provided in a lower space of a frame supporting a bed mattress; a temperature controller configured to control a temperature of the air heating module; and a control module configured to control the air heating module to operate according to the temperature set by the temperature controller.

[0012] Furthermore, the device may further include a partitioner for partitioning a first lower space corresponding to an upper body part of a user using the bed and a second lower space corresponding to a lower body part of the user.

[0013] Furthermore, the device may further include a first air heating module for heating air in the first lower space; and a second air heating unit for heating air in the second lower space.

[0014] Furthermore, the device may further include an angle adjustment device capable of adjusting a direction of hot air discharged from the air heating module, and the control module may be configured to control the angle adjustment device according to a temperature settings of the upper and lower bodies respectively input through the temperature controller.

[0015] Furthermore, the device may further include a sliding rail that allows the partitioner to move.

[0016] Furthermore, the control module may be configured to calculate a position of the partitioner based on a sleeping posture and body information of the user, and move the partitioner to the calculated position.

[0017] Furthermore, the control module may be configured to calculate a position of the partitioner based on a head position of the user during sleep, a height of the user, and an upper and lower body ratio of the user, and move the partitioner to the calculated position.

[0018] Furthermore, the control module may be configured to receive data related to the user's sleep sensed through a radar, analyze a temperature of the mattress and a movement of the user during sleep according to an operation of the air heating module based on the received data, determine the temperature of the mattress for the user's deep sleep based on the analyzed result, and determine a control method of the air heating module based on the determined result.

[0019] Furthermore, the control module may be configured to control an output of the air heating module based on a room temperature and the temperature set.

[0020] In another aspect of the present disclosure, a bed frame including a bed heating device according to an embodiment of the present disclosure includes an upper frame supporting a bed mattress; a lower frame placed on a floor surface to support the upper frame, and having a space formed therein; an air heating module provided in the space formed in the lower frame; a temperature controller configured to control a temperature of the air heating module; and a control module configured to control the air heating module to operate according to the temperature set by the temperature controller.

[0021] Furthermore, a computer program stored in a computer-readable recording medium for executing a method for implementing the present disclosure may be further provided.

[0022] Furthermore, a computer-readable recording medium recording a computer program for executing a method for implementing the present disclosure may be further provided.BRIEF DESCRIPTION OF THE FIGURES

[0023] FIG. 1 is a schematic diagram of a bed heating device according to an embodiment of the present disclosure.

[0024] FIG. 2 is a block diagram illustrating the configurations of a bed heating device according to an embodiment of the present disclosure.

[0025] FIG. 3 is a diagram illustrating a partitioner provided in a lower space of a bed frame.

[0026] FIG. 4 is a diagram illustrating a lower space of a bed frame divided into two.

[0027] FIG. 5 is a diagram illustrating a case where two air hearting modules are provided to provide heating effects of different temperatures to the user's upper and lower bodies, respectively.

[0028] FIG. 6 and FIG. 7 are diagrams illustrating a case where the position of the partitioner is changed to provide a heating effect by considering the user's body characteristics and sleeping posture.

[0029] FIGS. 8 and 9 are diagrams illustrating an example of an air hearting module in the form of a heater rod and including a heat-radiating insulation plate.

[0030] FIG. 10 is a diagram illustrating an example of the heat-radiating insulation plate of FIG. 8.DETAILED DESCRIPTION

[0031] In the drawings, the same reference numeral refers to the same element. This disclosure does not describe all elements of embodiments, and general contents in the technical field to which the present disclosure belongs or repeated contents of the embodiments will be omitted. The terms, such as “unit, module, member, and block” may be embodied as hardware or software, and a plurality of “units, modules, members, and blocks” may be implemented as one element, or a unit, a module, a member, or a block may include a plurality of elements.

[0032] Throughout this specification, when a part is referred to as being “connected” to another part, this includes “direct connection” and “indirect connection”, and the indirect connection may include connection via a wireless communication network.

[0033] Furthermore, when a certain part “includes” a certain element, other elements are not excluded unless explicitly described otherwise, and other elements may in fact be included.

[0034] In the entire specification of the present disclosure, when any member is located “on” another member, this includes a case in which still another member is present between both members as well as a case in which one member is in contact with another member.

[0035] The terms “first,”“second,” and the like are just to distinguish an element from any other element, and elements are not limited by the terms.

[0036] The singular form of the elements may be understood into the plural form unless otherwise specifically stated in the context.

[0037] Identification codes in each operation are used not for describing the order of the operations but for convenience of description, and the operations may be implemented differently from the order described unless there is a specific order explicitly described in the context.

[0038] The operating principle and embodiments of the present disclosure are described below with reference to the attached drawings.

[0039] In this specification, the term ‘bed heating device according to the present disclosure’ includes all of various devices that can perform computational processing and provide results to the user. For example, the device may include all of a computer, a server device, and a portable terminal, or may be in the form of one of them.

[0040] Here, the computer may include, for example, a notebook, a desktop, a laptop, a tablet PC, a slate PC, and the like mounted with a web browser.

[0041] The server device is a server that communicates with an external device to process information, and may include an application server, a computing server, a database server, a file server, a mail server, a proxy server, and a web server.

[0042] A portable terminal is a wireless communication device that ensures portability and mobility, and may include all kinds of handheld-based wireless communication devices such as PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminal, a smart phone, and the like, and a wearable device such as at least one of a watch, a ring, bracelets, anklets, a necklace, glasses, contact lenses, or a head-mounted device (HMD).

[0043] The function related to artificial intelligence according to the present disclosure operates through a processor and a memory. The processor may be composed of one or more processors. At this time, the one or more processors may be a general-purpose processor such as a CPU, an AP, a DSP (Digital Signal Processor), a graphics-only processor such as a GPU, a VPU (Vision Processing Unit), or an artificial intelligence-only processor such as an NPU. The one or more processors control input data to be processed according to a predefined operation rule or artificial intelligence model stored in the memory. Alternatively, in the case that the one or more processors are artificial intelligence-only processors, the artificial intelligence-only processor may be designed as a hardware structure specialized for processing a specific artificial intelligence model.

[0044] The predefined operation rule or artificial intelligence model may be created through learning. Here, being created through learning means that a basic artificial intelligence model is learned by using a plurality of learning data by a learning algorithm, thereby creating a predefined operation rule or artificial intelligence model set to perform a desired characteristic (or, purpose). Such learning may be performed on the device itself in which the artificial intelligence according to the present disclosure is performed, or may be performed through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0045] The artificial intelligence model may include a plurality of neural network layers. Each of the plurality of neural network layers has a plurality of weights, and performs neural network operations through operations between the operation results of the previous layer and the plurality of weights. The plurality of weights of the plurality of neural network layers may be optimized by the learning results of the artificial intelligence model. For example, the plurality of weights may be updated so that the loss value or cost value acquired by the artificial intelligence model is reduced or minimized during the learning process. The artificial neural network may include a deep neural network (DNN), for example, a convolutional neural network (CNN), a deep neural network (DNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), or a deep Q-network, but is not limited to the examples described above.

[0046] According to an exemplary embodiment of the present disclosure, the processor may implement artificial intelligence. Artificial intelligence refers to a machine learning method based on an artificial neural network that imitates human neurons (biological neurons) to enable a machine to learn. The artificial intelligence methodology may be divided into supervised learning in which input data and output data are provided together as training data according to a learning method so that the answer (output data) to a problem (input data) is determined, unsupervised learning in which only input data is provided without output data so that the answer (output data) to a problem (input data) is not determined, and reinforcement learning in which a reward is given from an external environment whenever an action is taken in a current state (State), and learning is performed in a direction to maximize this reward. In addition, the methodology of artificial intelligence can be classified according to the architecture, which is the structure of the learning model. The architecture of widely used deep learning technology can be classified into convolutional neural network (CNN), recurrent neural network (RNN), transformer, and generative adversarial network (GAN).

[0047] The present device and system may include an artificial intelligence model. The artificial intelligence model may be one artificial intelligence model or may be implemented as multiple artificial intelligence models. The artificial intelligence model may be composed of a neural network (or artificial neural network) and may include a statistical learning algorithm that mimics the neurons of biology in machine learning and cognitive science. A neural network may mean an overall model that has problem-solving capabilities by changing the strength of the synapse connection through learning by forming a network with artificial neurons (nodes) that combine synapses. The neurons of the neural network may include a combination of weights or biases. The neural network may include one or more layers composed of one or more neurons or nodes. For example, the device may include an input layer, a hidden layer, and an output layer. The neural network constituting the device can infer a desired result (output) from an arbitrary input (input) by changing the weights of neurons through learning.

[0048] The processor may generate a neural network, train (or learn) a neural network, perform a calculation based on received input data, generate an information signal based on the result of the calculation, or retrain the neural network. The models of the neural network may include various types of models such as CNN (Convolution Neural Network) such as GoogleNet, AlexNet, VGG Network, R-CNN (Region with Convolution Neural Network), RPN (Region Proposal Network), RNN (Recurrent Neural Network), S-DNN (Stacking-based deep Neural Network), S-SDNN (State-Space Dynamic Neural Network), Deconvolution Network, DBN (Deep Belief Network), RBM (Restrcted Boltzman Machine), Fully Convolutional Network, LSTM (Long Short-Term Memory) Network, Classification Network, and the like, but are not limited thereto. The processor may include one or more processors for performing calculations according to the models of the neural network. For example, a neural network may include a deep neural network.

[0049] The neural network may include CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), percept, multilayer perceptron, FF (Feed Forward), RBF (Radial Basis Network), DFF (Deep Feed Forward), LSTM (Long Short Term Memory), Gated Recurrent Unit (GRU), Auto Encoder (AE), Variational Auto Encoder (VAE), Denoising Auto Encoder (DAE), Sparse Auto Encoder (SAE), Markov Chain (MC), Hopfield Network (HN), Boltzmann Machine (BM), Restricted Boltzmann Machine (RBM), Depp Belief Network (DBN), Deep Convolutional Network (DCN), Deconvolutional Network (DN), Deep Convolutional Inverse Graphics Network (DCIGN), Generative Adversarial Network (GAN), Liquid State Machine (LSM), Extreme Learning Machine (ELM), Echo State Network (ESN), Deep Residual Network (DRN), Differentiable Neural Computer (DNC), Neural Turning Machine (NTM), Capsule Network (CN), Kohonen Network (KN), and Attention Network (AN), but not limited thereto, and it will be understood by those skilled in the art that any neural network may be included.

[0050] According to an exemplary embodiment of the present disclosure, the processor may use various artificial intelligence structures and algorithms such as CNN (Convolution Neural Network), R-CNN (Region with Convolution Neural Network), RPN (Region Proposal Network), RNN (Recurrent Neural Network), S-DNN (Stacking-based deep Neural Network), S-SDNN (State-Space Dynamic Neural Network), Deconvolution Network, DBN (Deep Belief Network), RBM (Restricted Boltzmann Machine), Fully Convolutional Network, LSTM (Long Short-Term Memory) Network, Classification Network, Generative Modeling, eXplainable AI, Continual AI, Representation Learning, and AI for Material Design such as GoogleNet, AlexNet, VGG Network, BERT, SP-BERT, MRC / QA, Text Analysis, Dialog System, GPT-3, and GPT-4 for natural language processing, Visual Analytics, Visual Understanding, Video Synthesis for vision processing, Anomaly Detection, Prediction, Time-Series Forecasting, Optimization, and Recommendation for algorithms ResNet for data intelligence, but not limited thereto. Hereinafter, the embodiment of the present disclosure will be described in detail.

[0051] FIG. 1 is a schematic diagram of a bed heating device according to an embodiment of the present disclosure.

[0052] Referring to FIG. 1, a bed heating device 100 is illustrated, and an air hearting module 140 is installed in a lower space 186 of a frame 180 that supports a bed mattress 190.

[0053] In addition, it is illustrated that air heated by the air hearting module 140 circulates in the lower space 186.

[0054] In this way, the air heated by the air hearting module 140 provides a heating effect to the bed mattress 190, and provides a mattress warming effect to a user sleeping in the bed.

[0055] Hereinafter, the bed heating device according to an embodiment of the present disclosure will be described in more detail with reference to other drawings.

[0056] FIG. 2 is a block diagram illustrating the configurations of a bed heating device according to an embodiment of the present disclosure.

[0057] FIG. 3 is a diagram illustrating a partitioner provided in a lower space of a bed frame.

[0058] FIG. 4 is a diagram illustrating a lower space of a bed frame divided into two.

[0059] FIG. 5 is a diagram illustrating a case where two air hearting modules are provided to provide heating effects of different temperatures to the user's upper and lower bodies, respectively.

[0060] FIG. 6 and FIG. 7 are diagrams illustrating a case where the position of the partitioner is changed to provide a heating effect by considering the user's body characteristics and sleeping posture.

[0061] Referring to FIG. 2, the bed heating device according to an embodiment of the present disclosure includes a control module 110, a communication module 120, a memory 130, an air heating module 140, a temperature controller 150, an angle adjustment device 160, and a rail 170.

[0062] However, in some embodiments, the bed heating device may include fewer or more components than the components illustrated in FIG. 2.

[0063] Referring to FIGS. 2 to 6, the bed heating device 100 according to the embodiment of the present disclosure will be described.

[0064] The control module 110 is connected to components that may be controlled by electrical signals among the components of the bed heating device, and is a subject that controls these components. The control module 110 may include at least one processor.

[0065] The processor may be implemented as a storage module storing data for an algorithm for controlling the operation of components within the device or a program that reproduces the algorithm, and at least one processor that performs the above-described operation using the data stored in the storage module. At this time, the storage module and the processor may be implemented as separate chips. Alternatively, the storage module and the processor may be implemented as a single chip.

[0066] In addition, the processor may control one or more of the components discussed above in combination to implement various embodiments of the present disclosure described in the diagrams below on the device.

[0067] In addition to the operation related to the application program, the processor may typically control the overall operation of the device. The processor may process signals, data, information, and the like input or output through the components discussed above, or may operate an application program stored in the storage module, thereby providing or processing appropriate information or functions to the user.

[0068] In addition, the processor may control at least some of the components of the device in order to operate the application program stored in the storage module. In addition, the processor may operate at least two or more of the components included in the device in combination to drive the application program.

[0069] The processor may be implemented as one or more. Hereinafter, even in the case that the processor is expressed as a singular number, it may be considered as plural. The processor may control the configurations of the bed heating device. The processor may mean a data processing device built into hardware that has a physically structured circuit to perform a function expressed by a code or command included in a program. As such, the processor may encompass processing devices such as a microprocessor, a central processing unit (CPU), a processor core, a multiprocessor, an application-specific integrated circuit (ASIC), and a field programmable gate array (FPGA), as an example of a data processing device built into hardware, but the scope of the present invention is not limited thereto. The processor may separately have a learning processor for performing artificial intelligence operations, or may have a learning processor on its own.

[0070] In various embodiments, the processor may include one or more of a central processing unit (CPU), an application processor (AP), or a communication processor (CP). At least a portion of the processor may be hardware, access memory, and perform functions related to instructions stored in the memory.

[0071] The communication module 120 may include one or more modules that connect the bed heating device 100 to one or more networks.

[0072] The communication module 120 may include one or more components that enable communication with an external device, and may include, for example, at least one of a broadcast reception module, a wired communication module, a wireless communication module, a short-range communication module, or a location information module.

[0073] The wired communication module may include various wired communication modules such as a Local Area Network (LAN) module, a Wide Area Network (WAN) module, or a Value Added Network (VAN) module, as well as various cable communication modules such as a Universal Serial Bus (USB), a High Definition Multimedia Interface (HDMI), a Digital Visual Interface (DVI), RS-232 (recommended standard232), power line communication, or plain old telephone service (POTS).

[0074] The wireless communication module may include a wireless communication module that supports various wireless communication methods such as a WiFi module, a WiBro (Wireless broadband) module, GSM (Global System for Mobile Communication), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), UMTS (Universal Mobile Telecommunications System), TDMA (Time Division Multiple Access), LTE (Long Term Evolution), 4G, 5G, and 6G.

[0075] The wireless communication module may include a wireless communication interface that includes an antenna and a transmitter that transmits a communication signal. In addition, the wireless communication module may further include a signal conversion module that modulates a digital control signal output from a processor through the wireless communication interface into an analog wireless signal under the control of the processor.

[0076] The short-range communication module is for short-range communication, and may support short-range communication by using at least one of Bluetooth, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra-Wideband), ZigBee, NFC (Near Field Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, or Wireless USB (Wireless Universal Serial Bus) technology.

[0077] The communication module 120 may also use the term of a communication interface.

[0078] The communication interface may establish communication between an electronic device and an external device. For example, the communication interface can communicate with the external device through wireless communication (e.g., Wi-Fi (Wireless Fidelity), Bluetooth, NFC (Near Field Communication), MST (magnetic stripe transmission), etc.) or wired communication.

[0079] The communication module 120 is connected to the temperature controller 150 and may receive a control signal input to the temperature controller 150 and transmit the control signal to the control module 110.

[0080] The communication module 120 may be connected to the user's terminal for communication, and the control module 110 may control the bed heating device 100 according to the control signal received from the terminal.

[0081] The memory 130 may store data supporting various functions of the device. The memory may store a plurality of application programs (or applications) driven by the device, data for the operation of the device, and commands. At least some of these application programs may exist for the basic functions of the device. Meanwhile, the application program may be stored in the memory, installed in the device, and driven to perform an operation (or function) by the processor.

[0082] The memory 130 may store data supporting various functions of the device and a program for the operation of the processor, input / output data (e.g., music files, still images, moving images, etc.) may be stored, and a plurality of application programs (or applications) run on the device, data for the operation of the device, and commands can be stored. At least some of these application programs may be downloaded from an external server via wireless communication.

[0083] The memory 130 may include at least one type of storage medium among a flash memory type, a hard disk type, an SSD (Solid State Disk type), an SDD (Silicon Disk Drive) type, a multimedia card micro type, a card type memory (for example, an SD or XD memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk. In addition, the memory may be a database that is separate from the device but connected by wire or wirelessly.

[0084] The memory 130 may be electrically connected to the processor and may store at least one code executed in the processor. The memory may refer to various types of storage devices. The memory may store information necessary for performing operations using artificial intelligence, machine learning, and artificial neural networks.

[0085] The memory 130 may store various learning models. The learning models stored in the memory may infer result values for new input data that are not learning data, and the inferred values may be used as a basis for judgment to perform a certain operation. The learning models stored in the memory may perform learning based on label information, and various backpropagation algorithms may be applied so that the loss function has a target value in order to increase the accuracy of learning.

[0086] The air hearting module 140 is provided in a lower space 181 of the frame 180 that supports the bed mattress.

[0087] The air hearting module 140 may be applied with a device such as a hot air blower that may heat the air in the lower space to increase the temperature of the lower space.

[0088] The air hearting module 140 is controlled by the control module 110 and may include functions such as overheating prevention and leakage prevention.

[0089] FIG. 3 is a diagram of FIG. 1 with the bed mattress 190 excluded.

[0090] Referring to FIG. 3, the air hearting module 140 is provided on one side of the lower space 181 of the frame 180 that supports the bed mattress, and blows heated air to the other side to circulate the heated air in the lower space 181.

[0091] In FIG. 3, the air hearting module 140 is provided on one side of the lower space 181 of the frame 180 supporting the bed mattress, but the installation location is not limited thereto, and the number is not limited to one.

[0092] In the embodiment of the present disclosure, one side of the bed heating device 100 means the direction in which the user's feet are located, and the other side means the direction in which the user's head is located.

[0093] The temperature controller 150 is a means for controlling the temperature of the air hearting module 140, and the user may directly set the temperature. The temperature controller 150 may input the temperature directly or the degree of the temperature.

[0094] In one embodiment, the communication module 120 may be connected to the user's terminal for communication, and may receive a temperature control signal from the terminal.

[0095] In one embodiment, the temperature controller 150 may provide functions such as on-time reservation and off-time reservation.

[0096] The angle adjustment device 160 may adjust the direction of hot air discharged from the air hearting module.

[0097] The angle adjustment device 160 may be installed near an outlet where air is discharged from the air hearting module 140 to enable this function.

[0098] The control module 110 may control the angle adjustment device according to the temperature settings of each of the upper and lower bodies input through the temperature controller 150.

[0099] Referring to FIG. 4, the air hearting module 140 is installed on the side of the lower space 181, and the lower space 181 of the bed frame 180 is divided into two lower spaces 182 and 183.

[0100] In addition, it is exemplified that a partitioner is installed in the center of the lower space 181 of the frame 180.

[0101] The bed heating device 100 divides the lower space 181 into a first lower space 182 and a second lower space 183 through the partitioner.

[0102] The control module 110 controls the angle adjustment device 160 to control the amount of hot air introduced into the first lower space 182 and the second lower space 183, thereby controlling the temperatures of the first lower space 182 and the second lower space 183 to be different.

[0103] In addition, this configuration may provide the effect of different temperatures at the positions of the mattress 190 corresponding to the user's upper and lower bodies.

[0104] Referring to FIG. 5, the bed heating device 100 is exemplified as including a plurality of air hearting modules 140.

[0105] More specifically, the bed heating device 100 includes a first air hearting module 141 installed on the side of the first lower space 182 and a second air hearting module 142 installed on the side of the second lower space 183.

[0106] The control module 110 may control the temperatures of the first lower space 182 and the second lower space 183 by independently controlling the first air hearting module 141 and the second air hearting module 142.

[0107] The bed heating device 100 may be controlled independently because the air circulating in the first lower space 182 and the second lower space 183 is not moved to other lower spaces by the partitioner.

[0108] Referring to FIG. 6 and FIG. 7, the bed heating device 100 may further include a sliding rail 170 of a predetermined length to enable the partitioner to move in the lower space 181.

[0109] The rail 170 may include a member such as a step so that the partitioner may be fixed at a plurality of different positions.

[0110] The rail 170 may include a moving means so that the partitioner may move under the control of the control module 110.

[0111] The control module 110 may control the moving means so that the position of the partitioner changes according to a control signal received from the temperature controller 150 or the terminal.

[0112] The control module 110 may calculate the position of the partitioner based on the user's sleeping posture and the user's body information. In addition, the control module 110 may control the partitioner to move to the calculated position.

[0113] At this time, the user's sleeping posture may mean the user's head position when sleeping. The user's body information may mean the user's height and body ratio (upper and lower body ratio).

[0114] The control module 110 may calculate the appropriate position of the partitioner based on the user's head position when sleeping, the user's height, and the user's upper and lower body ratio.

[0115] FIG. 6 exemplifies an example in which the partitioner is moved to one side and the area of the first lower space 182 is expanded, and FIG. 7 exemplifies an example in which the partitioner is moved to the other side and the area of the second lower space 183 is expanded.

[0116] The control module 110 may control the output of the heating module based on the temperature set through the indoor temperature and the temperature controller 150.

[0117] In one embodiment, the control module 110 may receive an image captured during the user's sleep through the communication module 120. The control module 110 may analyze the temperature of the mattress 190 and the user's movement during sleep based on the operation of the air hearting module 140 based on the received image, and may determine / calculate the mattress temperature for the user's deep sleep based on the analyzed result.

[0118] At this time, the control module 110 may analyze the user's sleep state based on the user's movement sensed through a radar.

[0119] In addition, the control module 110 may determine a control method of the air hearting module 140 based on the determined result. In this case, the control method of the air hearting module 140 means determining an output value of the air hearting module 140.

[0120] In one embodiment, the control module 110 may determine a control method of the air hearting module 140 based on at least one of the user's movement, the user's sleep state, and the user's health state sensed through radar. Here, the control method may mean the operation or non-operation of the air hearting module 140 and the operating temperature.

[0121] In one embodiment, the control module 110 may determine at least one of the user's sleep stage, sleep efficiency, or sleep delay time based on data sensed through radar.

[0122] In one embodiment, the control method of the air hearting module 140 may include the output value of the air hearting module 140 according to the user's sleep time zone.

[0123] In one embodiment, the bed heating device 100 may provide an optimized bed heating service using a thermal image measurement result and an artificial intelligence model.

[0124] The artificial intelligence model learns in advance about the mattress temperature suitable for a person's sleep according to the indoor temperature. At this time, the person's age and gender may be additionally included as learning data.

[0125] The control module 110 may calculate / output the mattress temperature suitable for the user's deep sleep based on the thermal image measurement result during the user's sleep using the artificial intelligence model.

[0126] At this time, the artificial intelligence model may generate a control signal for controlling the first air hearting module 141 and the second air hearting module 142 in order to provide the mattress temperature suitable for the user's deep sleep.

[0127] The control module 110 may control the first air hearting module 141 and the second air hearting module 142 according to the control signal obtained from the artificial intelligence model, thereby providing the user with the optimal mattress heating effect for deep sleep.

[0128] In the case that the above-described configurations are commonly applied to users, as an extended embodiment, the bed heating device 100 may apply the artificial intelligence model to each individual user as follows.

[0129] The artificial intelligence model may learn the mattress temperature optimized for each individual user by analyzing the user's movement while sleeping and the mattress temperature and the user's movement while sleeping.

[0130] FIGS. 8 and 9 are diagrams illustrating an example of an air hearting module in the form of a heater rod and including a heat-radiating insulation plate.

[0131] FIG. 10 is a diagram illustrating an example of the heat-radiating insulation plate of FIG. 8.

[0132] Referring to FIG. 8 and FIG. 9, the bed heating device 100 may include the air hearting module 140 in the form of a heater rod.

[0133] For example, the air hearting module 140 in the form of a heater rod may be provided in the longitudinal direction at the center of the bed frame 180.

[0134] Referring to FIG. 8, a plurality of air hearting modules 140 in the form of a heater rod may be provided, and as shown in the diagram, the air hearting module 140 may include a first air hearting module 143 in the first lower space 182 and a second air hearting module 144 in the second lower space 183.

[0135] In addition, the air hearting module 140 in the form of a heater rod may include a heat-radiating insulation plate 145 on both sides.

[0136] The heat-radiating insulation plate 140 is installed at a predetermined angle 10° to 30° with the lower part of the frame 180, and by effectively transferring the heat generated from the air hearting module 140 to the mattress installed at the upper part of the frame 180 by the angle and the heat-radiating function at the lower part and the heat-radiating function at the upper part, the heat generated from the air hearting module 140 may be effectively transferred to the mattress installed at the upper part of the frame 180, thereby providing an efficient temperature increase effect to the user using the bed.

[0137] In one embodiment, the heat-radiating insulation plate 140 may be configured to form a predetermined angle with the lower surface, and the lower surface may mean the lower or bottom surface of the frame 180.

[0138] Referring to FIG. 9, the air hearting module 140 in the form of a heater rod may be provided on top of two heat-radiating insulation plates 140.

[0139] However, it is not limited thereto, and one heat-radiating insulation plate 140 may be formed in a form in which the middle is bent.

[0140] Referring to FIG. 8, the first air hearting module 143 and a first heat-radiating insulation plate 146 may be provided in the first lower space 182, and a second air hearting module 144 and a second heat-radiating insulation plate 147 may be provided in the second lower space 183.

[0141] Referring to FIG. 10, the heat-radiating insulation plate 145 may be configured such that the upper part has a heat-radiating function and the lower part has an insulation function.

[0142] In one embodiment, the heat-radiating insulation plate 145 may include an upper heat-radiating plate 145a and a lower heat-radiating plate 145b.

[0143] In one embodiment, the bed heating device 100 may analyze the user's sleep state and health state using a radar sensor device, and the embodiment will be described in detail below.

[0144] The radar may include at least one radar sensor or radar sensor module.

[0145] The radar may sense the user's movement and collect data on the user's breathing, heartbeat, and the like.

[0146] The control module 110 may control the radar to measure / sensing data related to the user's sleep.

[0147] The data related to the user's sleep may be the user's breathing state, a video of the user's sleeping posture, or biometric information measured about the user.

[0148] The control module 110 may receive and process data for analyzing the user's sleep and health state collected by the radar. The result of the processing may be transmitted to the server 300 or / and the terminal.

[0149] The control module 110 may process data collected by the radar and generate a control signal based on the analysis result of the data collected by the radar.

[0150] The control module 110 may collect and store various data unrelated to the user's sleep movement to remove noise from the user's sleep movement sensing data according to the present disclosure, including only meaningful data related to the health status, including breathing and heart conditions during sleep.

[0151] The control module 110 processes the user's movement data collected through radar, filters only the data related to the user's breathing and health state during sleep, and processes the filtered data so that it may be analyzed separately. For convenience, the data related to health state will be described below using heart condition data as an example.

[0152] The control module 110 may remove noise when the user's movement data during sleep is received. The data from which the noise has been removed may be converted into a frequency domain by FFT (Fast Fourier Transform) processing. The control module 110 may separate the user's movement data during sleep converted into a frequency domain by FFT processing into frequency domain units, and individually process the data of each separated domain to generate data for analyzing breathing during sleep and data for analyzing health state.

[0153] The control module 110 may first convert the user's movement data during sleep into a frequency domain by FFT processing without filtering it, and filter the data converted into the frequency domain to extract only the breathing activity waveform and the heartbeat waveform during sleep. The filtering may be, for example, one of a low-pass filter, a high-pass filter, or a band-pass filter depending on the noise. The subsequent operations may refer to the above-mentioned contents.

[0154] The control module 110 may analyze the user's sleep quality and health state by comparing the respiratory activity waveform and heartbeat waveform by calling the corresponding respiratory activity waveform and heartbeat waveform from the memory 207.

[0155] The reference data may include, for example, at least one of the following: the respiratory activity waveform and heartbeat waveform of the user for a given period of time; the respiratory activity waveform and heartbeat waveform of the user when he or she is healthy and when he or she is not healthy; the respiratory activity waveform and heartbeat waveform of the user by sleep start time; the respiratory activity waveform and heartbeat waveform of the user by total sleep time; the respiratory activity waveform and heartbeat waveform of the user by day of the week; the respiratory activity waveform and heartbeat waveform of the user by weather during sleep; the respiratory activity waveform and heartbeat waveform of the user by sleep position; the respiratory activity waveform and heartbeat waveform of the user by sleep posture; the respiratory activity waveform and heartbeat waveform received from an external medical institution database server in each of the above cases; the respiratory activity waveform and heartbeat waveform of a generally healthy person or a person suffering from a given disease from an external medical institution database server, and the like.

[0156] The reference data may have different priorities or weights set during sleep analysis. The priorities or weights may also vary depending on the analysis time. For example, in the case that is Wednesday and it is rainy, the user's sleep start time is 12 midnight, and the total sleep time is 6 hours, then the reference data corresponding to Wednesday, rain, 12 midnight, and 6 hours may be given higher priorities or weights. Therefore, when analyzing the user's breathing activity waveform and heartbeat waveform during sleep by applying multiple reference data simultaneously or sequentially, the user's health state may be analyzed by referring to the priorities or weights, and the guide including recommended data or content may be provided differently accordingly.

[0157] The control module 110 may process critical breathing activity waveform and heartbeat waveform for health and health abnormality in advance and store them in the memory 130.

[0158] The control module 110 may determine whether to perform secondary processing on the respiratory activity waveform and heartbeat waveform information obtained by applying the critical respiratory activity waveform and heartbeat waveform when the user's sleep-related respiratory activity waveform and heartbeat waveform information are first acquired.

[0159] For example, the control module 110 may set additional health state determination candidate data in the case that it determines that secondary processing is necessary due to a problem in the user's sleep-related respiratory activity waveform and heartbeat waveform information based on the first critical respiratory activity waveform and heartbeat waveform information.

[0160] When the control module 110 sets additional health state determination candidate data, the control module 110 may skip the primary processing process and directly perform the secondary processing process on subsequent data.

[0161] The control module 110 may be shown to compare and analyze the respiratory activity waveform and the heartbeat waveform more accurately by calling and comparing at least one candidate data as a secondary processing process, thereby determining the user's health condition.

[0162] Afterwards, in the case that the control module 110 determines that there is no problem with the health condition for a predetermined number of times for example, three times or more, it may switch back to the primary processing priority application procedure.

[0163] When the control module 110 first performs the secondary processing process, it determines the health condition by applying only a predetermined number of the highest priority reference data according to the priority or weight, but in the case that the health condition is continuously determined to be abnormal, it may use additional reference data to determine the accurate health condition.

[0164] The control module 110 may ignore and not process the respiratory activity waveform and heartbeat waveform for a predetermine period of times or a predetermined number of times in the case that the analysis result of the user's sleep breathing activity waveform and heartbeat waveform is determined to be in a healthy state for a predetermined period of times or a predetermined number of times.

[0165] For example, when analyzing a waveform in units of time, the control module 110 may skip the waveforms for the next hour for the next 1 hour and process the waveforms for the next hour between the next 1 hour and 2 hours.

[0166] In the above case, when analyzing a waveform in units of time, in the case that the analysis result from the waveforms for the first 10 minutes is determined to be in a good health state, the analysis term may be increased. For example, the analysis term may be adjusted from analyzing a waveform in units of 1 minute to units of 5 minutes, 10 minutes, 20 minutes, or 30 minutes. Or, in the case that the waveform analysis result for the first 10 minutes is good, the waveform for the remaining 50 minutes may not be analyzed.

[0167] The control module 110 may generate a signal including recommended information according to the analysis result, and transmit the generated signal.

[0168] Here, the recommended information may include, for example, recommended music content, recommended video content, and the like.

[0169] In the case that the intensity of the received signal of the radar is below a threshold, the control module 110 may control the radar to move along the rail to a point where the intensity of the received signal is above the threshold.

[0170] A predetermined space in which the radar may be positioned or arranged may be formed within a topper. In the case that the radar is in the form of a rail, the radar may move along the rail or may be arranged at a position close to the position of the user's lungs or heart estimated based on the user's sleep movement data.

[0171] The control module 110 may separate the independent respiratory activity waveform and heartbeat waveform for each user, and analyze the respiratory activity waveform and heartbeat waveform for each user by distinguishing them.

[0172] To this end, the control module 110 may operate each radar simultaneously, but may control them to operate independently or alternately at different times to increase accuracy and reduce processing time.

[0173] The bed heating device 100 may include an artificial intelligence (AI) engine (not shown).

[0174] The artificial intelligence engine may learn using sleep data respiratory activity waveform, heartbeat waveform, and the like collected from the user or an external device as a training data set, and generate a learning model. The learning model generated in this way may function to replace some of the operations of the control module 110.

[0175] The terminal may communicate with the control module 110 of the topper and / or the server 300, and may receive and output the results of analyzing the data on sleep and health state collected through the radar of the topper. Here, the results may also include guide data such as health recommendations based on the analysis, such as (a) or (b) of FIG. 7.

[0176] The terminal may be a terminal owned by the user or a terminal of a user registered in the topper or the server 300. Such a terminal may be a fixed terminal such as a PC or TV, or a mobile terminal such as a smartphone, tablet PC, or laptop.

[0177] The terminal may also manually control the radar in the topper to collect data for analyzing the user's sleep and health state.

[0178] In the embodiment of the present disclosure, the bed heating device 100 may perform the following process.

[0179] The operation process of the bed heating device 100 may include a process of storing reference data, a process of acquiring the user's movement data during sleep using radar, a process of converting the acquired user's movement data during sleep into a frequency domain to acquire respiratory activity waveform and heartbeat waveform data, a step of analyzing the acquired respiratory and heartbeat waveform data by comparing it with the stored reference data, and a process of generating and transmitting guide data including recommended content based on the analysis results.

[0180] The control module 110 may collect the user's sleep data.

[0181] The control module 110 may process and analyze the user's sleep data.

[0182] The control module 110 may generate a learning and artificial intelligence model for sleep analysis of the corresponding user.

[0183] The control module 110 may store the user's sleep analysis data and the generated model in the memory 207.

[0184] The control module 110 may receive a radar sensor signal.

[0185] The control module 110 may extract respiratory and heartbeat movement data, that is, respiratory activity waveform and heartbeat waveform, from the radar sensor signal.

[0186] The control module 110 may extract data of corresponding user from the memory 207.

[0187] The control module 110 may compare the two data described above to determine whether the user has entered a sleep state.

[0188] In the case that the control module 110 determines that the user has entered a sleep state as a result of the determination, the control module 110 may analyze the user's sleep state and health state.

[0189] The control module 110 may generate and provide a guide by reflecting the analysis result.

[0190] According to the present disclosure described above, the heating effect may be provided to a bed mattress.

[0191] In addition, according to the present disclosure, it is possible to provide the heating effect to the bed mattress by heating the air in the lower space of the bed frame.

[0192] In addition, according to the present disclosure, it is possible to provide different heating effects to the upper and lower bodies of a user sleeping in the bed.

[0193] The method according to one embodiment of the present disclosure described above may be implemented as a program or application and stored in a medium to be executed in combination with a hardware server.

[0194] The program described above may include a code coded in a computer language, such as C, C++, JAVA, or machine language, that may be read by the processor CPU of the computer through the device interface of the computer so that the computer reads the program and executes the methods implemented as the program. Such code may include functional code related to functions that define the necessary functions for executing the above methods, and may include control code related to execution procedures necessary for the processor of the computer to execute the functions according to a predetermined procedure. In addition, such code may further include memory reference-related code regarding which location address of the internal or external memory of the computer should be referenced for additional information or media necessary for the processor of the computer to execute the functions. In addition, if the processor of the computer needs to communicate with any other computer or server located remotely in order to execute the functions, the code may further include communication-related code regarding how to communicate with any other computer or server located remotely using the communication module of the computer, and what information or media should be sent and received during the communication.

[0195] The above-mentioned storage medium means a medium that stores data semi-permanently and may be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specifically, examples of the above-mentioned storage medium include, but are not limited to, ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. That is, the above-mentioned program may be stored in various recording media on various servers that the above-mentioned computer may access, or in various recording media on the user's above-mentioned computer. In addition, the above-mentioned medium may be distributed to computer systems connected to a network, so that a computer-readable code may be stored in a distributed manner.

[0196] The steps of the method or algorithm described in relation to the embodiments of the present disclosure may be implemented directly in hardware, implemented as a software module executed by hardware, or implemented by a combination of these. The software module may reside in a random access memory (RAM), a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, a CD-ROM, or any other form of computer readable recording medium well known in the art to which the present disclosure pertains.

[0197] Although the embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art will understand that the present disclosure may be implemented in other specific forms without changing the technical spirit or essential characteristics thereof. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

Claims

1. A bed heating device comprising:an air heating module provided in a lower space of a frame supporting a bed mattress;a temperature controller configured to control a temperature of the air heating module; anda control module configured to control the air heating module to operate according to the temperature set by the temperature controller.

2. The device according to claim 1, further comprising a partitioner for partitioning a first lower space corresponding to an upper body part of a user using the bed and a second lower space corresponding to a lower body part of the user.

3. The device according to claim 2, further comprising:a first air heating module for heating air in the first lower space; anda second air heating module for heating air in the second lower space.

4. The device according to claim 2, further comprising an angle adjustment device capable of adjusting a direction of hot air discharged from the air heating module,wherein the control module is configured to control the angle adjustment device according to a temperature settings of the upper and lower bodies respectively input through the temperature controller.

5. The device according to claim 2, further comprising a sliding rail that allows the partitioner to move.

6. The device according to claim 5, wherein the control module is configured to:calculate a position of the partitioner based on a sleeping posture and body information of the user, andmove the partitioner to the calculated position.

7. The device according to claim 5, wherein the control module is configured to:calculate a position of the partitioner based on a head position of the user during sleep, a height of the user, and an upper and lower body ratio of the user, andmove the partitioner to the calculated position.

8. The device according to claim 1, wherein the control module is configured to:receive data related to the user's sleep sensed through a radar,analyze a temperature of the mattress and a movement of the user during sleep according to an operation of the air heating module based on the received data,determine the temperature of the mattress for the user's deep sleep based on the analyzed result, anddetermine a control method of the air heating module based on the determined result.

9. The device according to claim 1, wherein the control module is configured to:control an output of the air heating module based on a room temperature and the temperature set.

10. A bed frame including a bed heating device, comprising:an upper frame supporting a bed mattress;a lower frame placed on a floor surface to support the upper frame, and having a space formed therein;an air heating module provided in the space formed in the lower frame;a temperature controller configured to control a temperature of the air heating module; anda control module configured to control the air heating module to operate according to the temperature set by the temperature controller.

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