Intelligent bed control method and device based on gesture recognition, equipment and medium

Abstract

The invention relates to the technical field of smart home, and provides a gesture recognition-based smart bed control method, device and equipment and a medium, which can detect whether a wake-up gesture exists in real time by using a gesture recognition sensor deployed in a configuration area so as to prevent misoperation caused by unconscious actions in sleep of a user. When the wake-up gesture is detected, the gesture recognition sensor is used for capturing the three-dimensional space position, form and motion trail of the hand of the user in real time to serve as hand motion data, so that silent hand motion capturing is achieved, and other people are prevented from being disturbed; the hand motion data is analyzed by utilizing the gesture library to obtain the target control mode, and the target intelligent bed is controlled based on the target control mode, so that the intelligent bed is conveniently and accurately controlled.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and in particular to a smart bed control method, device, equipment and medium based on gesture recognition. Background Technology

[0002] With the development of technology, smart beds have entered more and more homes. Currently, the mainstream control methods for smart beds include the following: (1) Controlled via a physical remote control, meaning the user needs to use a dedicated remote control to control the smart bed. This method has the following main drawbacks: 1) Physical remote control is easy to lose: Physical remote control is small and easy to lose when placed on the bed or bedside table, especially at night when the light is dim.

[0003] 2) Inconvenient operation: When users are drowsy, they need to fumble and identify the buttons if they want to operate the physical remote control. If the button font is small or unclear, it will be inconvenient for the elderly to operate.

[0004] 3) Battery dependency: The battery needs to be replaced regularly, otherwise it will not work.

[0005] (2) Mobile App (Application) Control: Control is achieved by installing an App or Mini Program on a smartphone. This method has the following main drawbacks: 1) Cumbersome steps: Users need to find their phones first, and then perform operations such as unlocking, opening the APP or mini-program, and connecting the device in sequence. The whole process interrupts the rest state and affects the user's ability to fall asleep again.

[0006] 2) Light interference: The bright light from the mobile phone screen can be very dazzling at night, which may affect the sleep of the user or their partner.

[0007] (3) Voice control: Controlled via voice commands. This method has the following main drawbacks: 1) Disturbing others: Sending voice commands late at night may disturb your partner in bed.

[0008] 2) Recognition rate issues: The recognition success rate will decrease when there is environmental noise (such as fan, air conditioner, or even snoring) or when the user's voice is soft, unclear, uses different dialects, or has non-standard pronunciation.

[0009] 3) Privacy concerns: Some users may feel uneasy about having a device that continuously picks up sound in their bedroom.

[0010] As can be seen from the problems existing in the above-mentioned mainstream smart bed control methods, current smart bed control methods generally suffer from technical issues such as cumbersome operation, lack of intuitiveness, and potential disturbance to others in core usage scenarios such as nighttime and bedtime, resulting in a need for improved user experience. Therefore, there is an urgent need for a more intuitive, silent, and convenient smart bed control method. Summary of the Invention

[0011] In view of the above, it is necessary to provide a smart bed control method, device, equipment and medium based on gesture recognition, in order to solve the problems of inconvenient and inaccurate control of smart beds, and the ease with which they may disturb others.

[0012] A smart bed control method based on gesture recognition, the smart bed control method based on gesture recognition includes: In response to control commands to the target smart bed, gesture recognition sensors deployed in the configuration area are used to detect in real time whether a wake-up gesture is present; When the wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data. The hand movement data is analyzed using a gesture library to obtain the target control mode; The target smart bed is controlled based on the target control mode.

[0013] A gesture recognition-based smart bed control device, the gesture recognition-based smart bed control device comprising: The detection unit, in response to control commands to the target smart bed, uses gesture recognition sensors deployed in the configuration area to detect in real time whether a wake-up gesture exists; The capture unit is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data using the gesture recognition sensor when the wake-up gesture is detected. The parsing unit is used to parse the hand movement data using a gesture library to obtain the target control mode; A control unit is used to control the target smart bed based on the target control mode.

[0014] A computer device, the computer device comprising: Memory, storing at least one instruction; and The processor executes instructions stored in the memory to implement the gesture recognition-based smart bed control method.

[0015] A computer-readable storage medium storing at least one instruction, which is executed by a processor in a computer device to implement the gesture recognition-based smart bed control method.

[0016] As can be seen from the above technical solutions, the present invention can utilize gesture recognition sensors deployed in the configuration area to detect the presence of wake-up gestures in real time, thereby preventing accidental operation caused by unconscious movements of the user during sleep; when a wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape, and movement trajectory of the user's hand in real time as hand movement data, thereby achieving silent hand movement capture and avoiding disturbing others; the hand movement data is analyzed using a gesture library to obtain the target control mode, and the target smart bed is controlled based on the target control mode, thereby achieving convenient and accurate control of the smart bed. Attached Figure Description

[0017] Figure 1 This is a flowchart of a preferred embodiment of the smart bed control method based on gesture recognition of the present invention.

[0018] Figure 2 This is a functional block diagram of a preferred embodiment of the smart bed control device based on gesture recognition of the present invention.

[0019] Figure 3 This is a schematic diagram of the structure of a computer device that implements a preferred embodiment of the intelligent bed control method based on gesture recognition according to the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0021] like Figure 1 The diagram shown is a flowchart of a preferred embodiment of the smart bed control method based on gesture recognition according to the present invention. The order of the steps in this flowchart can be changed, and some steps can be omitted, depending on different requirements.

[0022] The gesture recognition-based smart bed control method is applied to one or more computer devices. The computer device is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions. Its hardware includes, but is not limited to, microprocessors, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), embedded devices, etc.

[0023] The computer device can be any electronic product that can interact with the user, such as a personal computer, tablet computer, smartphone, personal digital assistant (PDA), game console, interactive network television (IPTV), smart wearable device, etc.

[0024] The computer equipment may also include network equipment and / or user equipment. The network equipment includes, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of hosts or network servers.

[0025] The server can be a standalone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0026] Artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0027] Foundational technologies for artificial intelligence generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interactive systems, and mechatronics. AI software technologies mainly encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0028] The network in which the computer device is located includes, but is not limited to, the Internet, wide area network, metropolitan area network, local area network, and virtual private network (VPN).

[0029] S10, in response to control commands to the target smart bed, uses gesture recognition sensors deployed in the configuration area to detect in real time whether a wake-up gesture is present.

[0030] In this embodiment, the target smart bed may have functions such as adjusting the bed posture (e.g., raising the back, legs, etc.), adjusting the firmness, massage, heating, and monitoring sleep.

[0031] In this embodiment, the wake-up gesture can be customized according to user habits to facilitate user operation.

[0032] For example, the wake-up gesture can be: placing the palm flat within the sensing area and holding it for 2 seconds.

[0033] The wake-up gesture can activate the gesture control function according to the user's actual operation needs, so as to prevent the user's unconscious movements during sleep from causing accidental triggering.

[0034] In this embodiment, before using a gesture recognition sensor deployed in the configuration area to detect the presence of a wake-up gesture in real time, the method further includes: When a user is detected lying on the target smart bed, the system determines that the control command has been received and controls the target smart bed to enter standby mode. When the target smart bed enters the standby state, it does not respond to gestures other than the wake-up gesture.

[0035] The above embodiments can further avoid the problem of accidental triggering caused by unconscious movements of users during sleep.

[0036] In this embodiment, the configuration area is used to cover the space where the user's hands can move naturally when lying on the target smart bed.

[0037] For example, the configuration area may include, but is not limited to, the sides of the headboard, the sides of the mattress, or a separate bedside device (such as a bedside table).

[0038] In this embodiment, the gesture recognition sensor includes a millimeter-wave radar sensor that can penetrate non-metallic obstructions and is unaffected by light, and / or a time-of-flight (TOF) camera or an infrared structured light camera capable of working at night.

[0039] Among them, the millimeter-wave radar sensor can penetrate non-metallic obstructions such as blankets to accurately sense minute hand movements, speed and direction, and is not affected by light, thus perfectly matching the use scenario in bed.

[0040] Among them, since the time-of-flight depth camera and the infrared structured light camera have the ability to work at night, they can also be used in bed.

[0041] This embodiment uses the millimeter-wave radar sensor, the time-of-flight depth camera, or the infrared structured light camera to accurately capture user gestures even when there is obstruction or low light, providing an accurate foundation for subsequent gesture recognition.

[0042] S11, when the wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data.

[0043] In this embodiment, the movement trajectory of the gesture can be identified more accurately through the three-dimensional spatial position.

[0044] In this embodiment, the shape may include, but is not limited to: finger shape (such as fingers open or clenched into a fist) and palm shape (closed or open).

[0045] In this embodiment, the motion trajectory is used to reflect the movement state of the hand, such as waving up and down, waving forward and backward, etc.

[0046] In the above embodiments, the user's gestures within the preset sensing area can be captured and recognized in real time and without contact, thereby comprehensively capturing multi-dimensional hand movement data for use in subsequent pattern analysis.

[0047] In this embodiment, after using the gesture recognition sensor to capture the three-dimensional spatial position, shape, and movement trajectory of the user's hand in real time as hand movement data, the method further includes: If no hand movement data is detected within a preset time period, or if a locking gesture is detected, the target smart bed is controlled to enter the standby state.

[0048] The preset duration can be configured according to actual needs, such as 30 minutes.

[0049] For example, if no gesture operation is detected within 30 minutes after activating the gesture control function, it means that the user has fallen asleep or does not need gesture control. In this case, in order to save resources, the target smart bed can be controlled to enter the standby state.

[0050] The locking gesture can be customized according to user habits to facilitate user operation.

[0051] For example, the locking gesture could be: quickly clenching your fist twice.

[0052] The locking gesture allows the user to control the target smart bed to enter the standby state according to their actual operating needs, thereby avoiding accidental operation.

[0053] S12, the hand movement data is analyzed using a gesture library to obtain the target control mode.

[0054] In this embodiment, the gesture library is used to store various gestures for controlling the target smart bed.

[0055] In this embodiment, the step of parsing the hand movement data using a gesture library to obtain the target control mode includes: The hand movement data is used to perform matching in the gesture library; When a target gesture corresponding to the hand movement data is matched in the gesture library, the hand movement data is determined to be valid. Obtain a mapping table used to record the correspondence between gestures and control modes; The mapping table is traversed using the target gesture; The control pattern that is traversed and corresponds to the target gesture is determined as the target control pattern.

[0056] Specifically, a CNN (Convolutional Neural Network) model or template matching algorithm based on deep learning can be used to match the hand movement data stream to the specific gestures predefined in the gesture library in real time.

[0057] The gesture library includes dynamic gestures and static gestures; The dynamic gestures are used to control the function modes, which include posture adjustment mode, airbag adjustment mode, and auxiliary function mode. For example, the dynamic gestures may include, but are not limited to: (1) Wave your hand up or down: Used to control the raising or lowering of the back of the bed.

[0058] (2) Wave your hand forward or backward, or wave your hand to the left or right: to control the raising or lowering of the bed legs.

[0059] (3) Clockwise or counterclockwise circular motion: used to turn the massage function on or off, or to switch massage modes.

[0060] (4) Spread your fingers or clench your fist: Used to turn the reading light on or off.

[0061] The static gestures are used for gear control, confirmation control, saving to memory mode, and pause control.

[0062] For example, the static gestures may include, but are not limited to: (1) Extend different numbers of fingers (e.g., extend 1 finger, extend 2 fingers, extend 3 fingers): used to adjust the massage intensity or the speed of bed lifting.

[0063] (2) "OK" gesture: used to confirm execution or save as a memory mode.

[0064] (3) "Pause" gesture (i.e., palm facing forward): used to stop all actions in an emergency.

[0065] S13, control the target smart bed based on the target control mode.

[0066] In this embodiment, controlling the target smart bed based on the target control mode includes: The target control mode is sent to the corresponding target driver in the target smart bed; The target driver is used to drive the corresponding hardware in the target smart bed to execute the target control mode.

[0067] For example, the target control mode may include, but is not limited to: (1) Posture adjustment mode: controls the back, legs, etc. of the motor lifting bed.

[0068] (2) Massage or vibration mode: controls the start / stop, mode and intensity of the massage motor.

[0069] (3) Airbag adjustment mode: controls the inflation and deflation of airbags in different areas and the mode adjustment.

[0070] (4) Reading mode: controls the on / off switch and brightness of the reading light.

[0071] (5) Under-bed ambient light mode: controls the on / off state and brightness of the under-bed ambient light.

[0072] (6) Heating mode: controls the start and stop of the zoned temperature control system in the smart bed, heating intensity, heating area and heating mode.

[0073] Through the above embodiments, it is possible to achieve accurate and silent control of the smart bed without disturbing others by combining gesture recognition.

[0074] In this embodiment, after controlling the target smart bed based on the target control mode, the method further includes: Obtain the control results of the target smart bed; A feedback signal is generated based on the control result; The feedback signal informs the user whether the target smart bed control is successful or failed through vibrations below a preset intensity or changes in indicator light brightness below a configured brightness.

[0075] For example, subtle vibrations or gentle indicator light changes can provide users with feedback on whether the operation was successful or failed, allowing them to promptly confirm the control results and improving the user experience.

[0076] In this embodiment, when controlling the smart bed based on gesture recognition, users do not need to search for any external devices; they can control it simply by raising their hand. The actions and functions correspond intuitively, with a low learning curve, truly achieving "blind operation." The entire interaction process is silent, making it ideal for nighttime use without waking up those nearby, ensuring the sleep quality of cohabitants. The gesture recognition sensor is unaffected by light or darkness and can penetrate blankets, enabling all-weather, highly reliable gesture recognition, ensuring usability and accuracy in various bed scenarios. Non-contact operation avoids the risk of cross-infection, improving hygiene. Furthermore, the ability to set lock and emergency stop gestures enhances safety. This novel interaction method greatly enhances the product's technological sophistication and high-end positioning, bringing users an unprecedented smart living experience.

[0077] For example: When user A wakes up in the middle of the night feeling stomach discomfort and wants to raise the back of the bed to relieve the discomfort, the following steps can be taken in sequence: (1) User A extends his right hand out from under the blanket, places his palm flat and holds it for 2 seconds in the sensing area near the headboard (i.e., wake-up gesture). A faint LED (Light Emitting Diode) indicator light on the headboard changes from off to a soft blue, indicating that the smart bed gesture control mode has been activated.

[0078] (2) User A slowly waves his palm upwards. The gesture recognition sensor (such as a millimeter-wave radar sensor or an infrared structured light camera) captures this dynamic gesture and recognizes it as a mode control command of "raising back".

[0079] (3) The drive motor slowly and smoothly raises the back of the smart bed. During the process, user A keeps his hands raised and the back of the bed continues to rise until a comfortable angle is reached. Then user A lowers his hands.

[0080] (4) When the gesture disappears, the control command will stop being sent. At this time, the headboard of the smart bed will stop in the current position.

[0081] (5) If user A wants to lower the headboard a little further, simply make a downward waving gesture. After adjustment, if there is no further operation within 30 seconds, it will automatically enter sleep mode and the LED light will turn off.

[0082] Through the above embodiments, the smart bed can be accurately adjusted in posture silently through gesture recognition, thereby assisting users in adjusting their sleeping position.

[0083] As can be seen from the above technical solutions, the present invention can utilize gesture recognition sensors deployed in the configuration area to detect the presence of wake-up gestures in real time, thereby preventing accidental operation caused by unconscious movements of the user during sleep; when a wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape, and movement trajectory of the user's hand in real time as hand movement data, thereby achieving silent hand movement capture and avoiding disturbing others; the hand movement data is analyzed using a gesture library to obtain the target control mode, and the target smart bed is controlled based on the target control mode, thereby achieving convenient and accurate control of the smart bed.

[0084] like Figure 2 The diagram shown is a functional block diagram of a preferred embodiment of the gesture recognition-based smart bed control device of the present invention. The gesture recognition-based smart bed control device 11 includes a detection unit 110, a capture unit 111, a parsing unit 112, and a control unit 113. The module / unit referred to in this invention is a series of computer program segments that can be executed by a processor and perform a fixed function, stored in memory. In this embodiment, the functions of each module / unit will be described in detail in subsequent embodiments.

[0085] The detection unit 110 is used to detect in real time whether a wake-up gesture exists in response to a control command for the target smart bed; The capturing unit 111 is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data when the wake-up gesture is detected by the gesture recognition sensor. The parsing unit 112 is used to parse the hand movement data using a gesture library to obtain the target control mode; The control unit 113 is used to control the target smart bed based on the target control mode.

[0086] As can be seen from the above technical solutions, the present invention can utilize gesture recognition sensors deployed in the configuration area to detect the presence of wake-up gestures in real time, thereby preventing accidental operation caused by unconscious movements of the user during sleep; when a wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape, and movement trajectory of the user's hand in real time as hand movement data, thereby achieving silent hand movement capture and avoiding disturbing others; the hand movement data is analyzed using a gesture library to obtain the target control mode, and the target smart bed is controlled based on the target control mode, thereby achieving convenient and accurate control of the smart bed.

[0087] like Figure 3 The diagram shown is a schematic diagram of the structure of a computer device that implements a preferred embodiment of the smart bed control method based on gesture recognition according to the present invention.

[0088] The computer device 1 may include a memory 12, a processor 13, and a bus (the arrow in the figure represents the bus), and may also include a computer program stored in the memory 12 and executable on the processor 13, such as a smart bed control program based on gesture recognition.

[0089] Those skilled in the art will understand that the schematic diagram is merely an example of computer device 1 and does not constitute a limitation on computer device 1. Computer device 1 can be either a bus topology or a star topology. Computer device 1 may also include more or fewer other hardware or software than shown in the diagram, or different component arrangements. For example, computer device 1 may also include input / output devices, network access devices, etc.

[0090] It should be noted that the computer device 1 described is merely an example. Other existing or future electronic products that are adaptable to this invention should also be included within the scope of protection of this invention and are incorporated herein by reference.

[0091] The memory 12 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 12 can be an internal storage unit of the computer device 1, such as a portable hard drive of the computer device 1. In other embodiments, the memory 12 can be an external storage device of the computer device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the computer device 1. Furthermore, the memory 12 can include both internal and external storage units of the computer device 1. The memory 12 can be used not only to store application software and various types of data installed on the computer device 1, such as the code of a smart bed control program based on gesture recognition, but also to temporarily store data that has been output or will be output.

[0092] In some embodiments, the processor 13 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits packaged with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 13 is the control unit of the computer device 1, connecting various components of the computer device 1 via various interfaces and lines. It executes programs or modules stored in the memory 12 (e.g., executing a gesture-based smart bed control program) and calls data stored in the memory 12 to perform various functions of the computer device 1 and process data.

[0093] The processor 13 executes the operating system of the computer device 1 and various installed applications. The processor 13 executes these applications to implement the steps in the various embodiments of the gesture recognition-based smart bed control method described above, for example... Figure 1 The steps are shown.

[0094] For example, the computer program may be divided into one or more modules / units, which are stored in the memory 12 and executed by the processor 13 to complete the present invention. The one or more modules / units may be a series of computer-readable instruction segments capable of performing a specific function, which describe the execution process of the computer program in the computer device 1. For example, the computer program may be divided into a detection unit 110, a capture unit 111, a parsing unit 112, and a control unit 113.

[0095] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium. This software functional module, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute portions of the gesture recognition-based smart bed control method described in the various embodiments of this invention.

[0096] If the modules / units integrated in the computer device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware devices. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above.

[0097] The computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory, etc.

[0098] Furthermore, the computer-readable storage medium may primarily include a stored program area and a stored data area, wherein the stored program area may store the operating system, an application program required for at least one function, etc.; and the stored data area may store data created based on the use of blockchain nodes, etc.

[0099] The blockchain referred to in this invention is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, a blockchain is a decentralized database, a chain of data blocks linked together using cryptographic methods. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-counterfeiting) and generate the next block. A blockchain can include an underlying blockchain platform, a platform product service layer, and an application service layer.

[0100] The bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, in... Figure 3 The bus is represented by only one straight line, but this does not mean that there is only one bus or one type of bus. The bus is configured to enable communication between the memory 12 and at least one processor 13, etc.

[0101] Although not shown, the computer device 1 may also include a power supply (such as a battery) to power various components. Preferably, the power supply can be logically connected to the at least one processor 13 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The computer device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0102] Furthermore, the computer device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the computer device 1 and other computer devices.

[0103] Optionally, the computer device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the computer device 1 and to display a visual user interface.

[0104] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0105] It will be understood by those skilled in the art that Figure 3 The structure shown does not constitute a limitation on the computer device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0106] Combination Figure 1 The memory 12 in the computer device 1 stores multiple instructions to implement a smart bed control method based on gesture recognition, and the processor 13 can execute the multiple instructions to achieve the following: In response to control commands to the target smart bed, gesture recognition sensors deployed in the configuration area are used to detect in real time whether a wake-up gesture is present; When the wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data. The hand movement data is analyzed using a gesture library to obtain the target control mode; The target smart bed is controlled based on the target control mode.

[0107] Specifically, the processor 13's implementation method for the above instructions can be found in [reference needed]. Figure 1 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0108] It should be noted that all data involved in this case was legally obtained. Software tools or components not belonging to this company that appear in the embodiments of this application are merely illustrative examples and do not represent actual use.

[0109] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0110] This invention can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This invention can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0111] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0112] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0113] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0114] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within the invention. No appended diagram markings in the claims should be construed as limiting the scope of the claims.

[0115] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices described in this invention can also be implemented by a single unit or device through software or hardware. Terms such as "first," "second," etc., are used to indicate names and do not indicate any specific order.

[0116] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A smart bed control method based on gesture recognition, characterized in that, The smart bed control method based on gesture recognition includes: In response to control commands to the target smart bed, gesture recognition sensors deployed in the configuration area are used to detect in real time whether a wake-up gesture is present; When the wake-up gesture is detected, the gesture recognition sensor is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data. The hand movement data is analyzed using a gesture library to obtain the target control mode; The target smart bed is controlled based on the target control mode.

2. The smart bed control method based on gesture recognition as described in claim 1, characterized in that, Before utilizing the gesture recognition sensor deployed in the configuration area to detect the presence of a wake-up gesture in real time, the method further includes: When a user is detected lying on the target smart bed, the system determines that the control command has been received and controls the target smart bed to enter standby mode. When the target smart bed enters the standby state, it does not respond to gestures other than the wake-up gesture.

3. The smart bed control method based on gesture recognition as described in claim 1, characterized in that, The configuration area is designed to cover the space where the user's hands can move naturally when lying on the target smart bed.

4. The smart bed control method based on gesture recognition as described in claim 1, characterized in that, The gesture recognition sensor includes a millimeter-wave radar sensor that can penetrate non-metallic obstructions and is unaffected by light, and / or a time-of-flight depth camera or an infrared structured light camera capable of working at night.

5. The smart bed control method based on gesture recognition as described in claim 2, characterized in that, After using the gesture recognition sensor to capture the three-dimensional spatial position, shape, and movement trajectory of the user's hand in real time as hand movement data, the method further includes: If no hand movement data is detected within a preset time period, or if a locking gesture is detected, the target smart bed is controlled to enter the standby state.

6. The smart bed control method based on gesture recognition as described in claim 1, characterized in that, The step of parsing the hand movement data using a gesture library to obtain the target control mode includes: The hand movement data is used to perform matching in the gesture library; When a target gesture corresponding to the hand movement data is matched in the gesture library, the hand movement data is determined to be valid. Obtain a mapping table used to record the correspondence between gestures and control modes; The mapping table is traversed using the target gesture; The control pattern that is traversed and corresponds to the target gesture is determined as the target control pattern.

7. The smart bed control method based on gesture recognition as described in claim 6, characterized in that: The gesture library includes dynamic gestures and static gestures; The dynamic gestures are used to control the function modes, which include posture adjustment mode, airbag adjustment mode, and auxiliary function mode. The static gestures are used for gear control, confirmation control, saving to memory mode, and pause control.

8. The smart bed control method based on gesture recognition as described in claim 1, characterized in that, The control of the target smart bed based on the target control mode includes: The target control mode is sent to the corresponding target driver in the target smart bed; The target driver is used to drive the corresponding hardware in the target smart bed to execute the target control mode.

9. The smart bed control method based on gesture recognition as described in claim 1, characterized in that, After controlling the target smart bed based on the target control mode, the method further includes: Obtain the control results of the target smart bed; A feedback signal is generated based on the control result; The feedback signal informs the user whether the target smart bed control was successful or failed through vibrations below a preset intensity or changes in indicator light brightness below a configured brightness.

10. A smart bed control device based on gesture recognition, characterized in that, The gesture recognition-based smart bed control device includes: The detection unit, in response to control commands to the target smart bed, uses gesture recognition sensors deployed in the configuration area to detect in real time whether a wake-up gesture exists; The capture unit is used to capture the three-dimensional spatial position, shape and movement trajectory of the user's hand in real time as hand movement data using the gesture recognition sensor when the wake-up gesture is detected. The parsing unit is used to parse the hand movement data using a gesture library to obtain the target control mode; A control unit is used to control the target smart bed based on the target control mode.

11. A computer device, characterized in that, The computer device includes: Memory, storing at least one instruction; and The processor executes instructions stored in the memory to implement the gesture recognition-based smart bed control method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, which is executed by a processor in a computer device to implement the gesture recognition-based smart bed control method as described in any one of claims 1 to 9.

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