A learning desk system
The posture detection and adjustment function of the study desk system solves the problem that traditional study desks cannot monitor and correct poor posture. It realizes accurate monitoring and active correction of the posture of teenagers and children, and improves the intelligence level and health protection effect of the study desk.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Utility models(China)
- Current Assignee / Owner
- SHANDONG GUANGMINGYUANDI CHILDRENS FURNITURE TECH CO LTD
- Filing Date
- 2025-07-24
- Publication Date
- 2026-07-14
AI Technical Summary
Traditional study desks cannot effectively monitor and correct poor posture, which affects the healthy development of teenagers and children, and cannot meet the personalized learning needs.
A study desk system was designed, which integrates a posture detection unit, a core control unit, and an reminder unit. The system monitors posture in real time through a pressure sensor array, a camera module, and a distance sensor. The core control unit controls the height adjustment mechanism and the angle adjustment mechanism to actively intervene and correct poor posture.
It enables precise monitoring and proactive correction of poor posture, adapts to the personalized needs of different users, improves the intelligence level of the study desk, and protects the health of teenagers.
Smart Images
Figure CN224483359U_ABST
Abstract
Description
Technical Field
[0001] This utility model relates to the field of smart furniture technology, and in particular to a study desk system. Background Technology
[0002] Traditional study desks have limited functionality and cannot meet the needs of modern personalized learning. Children and teenagers often exhibit poor posture and excessive screen time during study, which negatively impacts their healthy development. Parents also find it difficult to monitor their children's learning progress in real time.
[0003] Some existing smart desks may have basic functions such as height adjustment, tabletop tilt adjustment, and lighting linkage, but they cannot effectively monitor poor posture (such as slouching, leaning forward, backward, left, or right), let alone meet users' core expectation of "correcting posture." Therefore, there is an urgent need for a study desk that can effectively monitor and correct posture. Utility Model Content
[0004] To address the aforementioned technical problems, this utility model provides a study desk system that can effectively monitor sitting posture and proactively intervene to correct poor sitting posture when it is detected.
[0005] The above-mentioned objective of this utility model is achieved through the following technical solution:
[0006] A study desk system includes a study desk body, the study desk body having a height adjustment mechanism that can electrically adjust the height of the desktop and an angle adjustment mechanism that can electrically adjust the tilt angle of the desktop.
[0007] It also includes a posture detection unit, a core control unit, and a reminder unit. The signal output terminal of the posture detection unit is connected to the first signal input terminal of the core control unit, the first signal output terminal of the core control unit is connected to the signal input terminal of the reminder unit, the second signal output terminal of the core control unit is connected to the signal input terminal of the height adjustment mechanism, and the third signal output terminal of the core control unit is connected to the signal input terminal of the angle adjustment mechanism.
[0008] The sitting posture detection unit is used to detect the user's sitting posture information and transmit it to the core control unit;
[0009] The core control unit is used to control the reminder unit, height adjustment mechanism and angle adjustment mechanism according to the received posture information, so as to remind the user to adjust their posture by means of at least one of the reminder unit, height adjustment mechanism and angle adjustment mechanism when the user has poor posture.
[0010] Preferably, the posture detection unit includes a first pressure sensor array disposed on the seat and a second pressure sensor array disposed in a preset area of the tabletop. The first and second pressure sensor arrays are respectively connected to the core control unit.
[0011] The first pressure sensor array is used to detect the pressure distribution information of the user on the seat and transmit it to the core control unit;
[0012] The second pressure sensor array is used to detect the pressure distribution information of the user on the tabletop and transmit it to the core control unit.
[0013] Preferably, the second pressure sensor array is disposed in the left and right elbow support areas of the tabletop and / or the front edge of the tabletop.
[0014] Preferably, the study desk system further includes an identity recognition unit, which is connected to the core control unit, wherein...
[0015] The identity recognition unit is used to detect the identity information of the user currently using the study desk and transmit it to the core control unit.
[0016] Preferably, the identity recognition unit includes at least one of a face recognition module, a fingerprint recognition module, an RFID reader, and an NFC reader.
[0017] Preferably, the posture detection unit includes a camera module, which is connected to the core control unit, wherein...
[0018] The camera module is used to capture images of the user's sitting posture while using the study desk.
[0019] Preferably, the sitting posture detection unit includes a distance sensor, which is connected to the core control unit, wherein...
[0020] The distance sensor is used to detect the distance information between the user's chest and the front wall of the table and / or between the user's head and the table, and transmits it to the core control unit.
[0021] Preferably, the ranging sensor is a ToF sensor.
[0022] Preferably, the reminder unit includes an LED light warning device and a voice playback warning device.
[0023] Preferably, the core control unit includes an MCU, a memory, a timing module, a motor drive module, and a wireless communication module. The memory, timing module, motor drive module, and wireless communication module are respectively connected to the MCU. The posture detection unit and the reminder unit are respectively connected to the MCU. The height adjustment mechanism and the angle adjustment mechanism are respectively connected to the motor drive module.
[0024] The beneficial effects of this utility model are as follows:
[0025] This invention incorporates a posture detection unit, a core control unit, and a reminder unit. The posture detection unit detects the user's posture information, enabling effective posture monitoring. The core control unit controls the reminder unit, height adjustment mechanism, and angle adjustment mechanism based on the received posture information. When the user exhibits poor posture, at least one of these mechanisms reminds the user to adjust their posture, thus proactively intervening to correct poor posture upon detection. Attached Figure Description
[0026] To more clearly illustrate the technical solutions in the embodiments of this utility model or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this utility model. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0027] Figure 1 This is a schematic diagram of the structure of a study desk system in one embodiment of the present invention;
[0028] Figure 2 This is a schematic diagram of the structure of the study desk system in another embodiment of the present invention;
[0029] Figure 3 This is a schematic diagram of the structure of the study desk system in another embodiment of the present invention. Detailed Implementation
[0030] To enable those skilled in the art to better understand the technical solutions of this utility model, the technical solutions in the embodiments of this utility model will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this utility model, and not all of them. Based on the embodiments of this utility model, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this utility model.
[0031] In the embodiments provided by this utility model, it should be understood that the disclosed methods and systems can be implemented in other ways. The system embodiments described below are merely illustrative. For example, the division of units and modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or modules can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, and can be electrical, mechanical, or other forms.
[0032] In addition, each functional unit in the various embodiments of this utility model can be integrated into a single processor, or each unit can be a separate device, or two or more units can be integrated into a single device; each functional unit in the various embodiments of this utility model can be implemented in hardware or in the form of hardware plus software functional units.
[0033] Those skilled in the art will understand that all or part of the steps of the following method embodiments can be implemented by program instructions and related hardware. The aforementioned program instructions can be stored in a computer-readable storage medium. When the program instructions are executed, they perform the steps of the following method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), magnetic disks, or optical disks.
[0034] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this utility model, "a plurality of" or "several" means two or more, unless otherwise explicitly specified.
[0035] like Figure 1-3 As shown in the figure, this utility model embodiment provides a study desk system, which includes a study desk body, a posture detection unit 1, a core control unit 2, and a reminder unit 3.
[0036] The study desk body has an electrically adjustable height adjustment mechanism 4 and an electrically adjustable tilt mechanism 5. The height adjustment mechanism 4 can be implemented by a DC motor driving a lead screw to rotate, which in turn drives the table legs to raise or lower the desktop height. The tilt mechanism 5 can be implemented by a DC motor driving a lead screw to rotate, which in turn drives the tabletop to tilt via a connecting rod. Both the electrically adjustable height adjustment mechanism 4 and the electrically adjustable tilt mechanism 5 are existing technologies, and their detailed working principles will not be described again.
[0037] The signal output terminal of the posture detection unit 1 is connected to the first signal input terminal of the core control unit 2. The first signal output terminal of the core control unit 2 is connected to the signal input terminal of the reminder unit 3. The second signal output terminal of the core control unit 2 is connected to the signal input terminal of the height adjustment mechanism 4. The third signal output terminal of the core control unit 2 is connected to the signal input terminal of the angle adjustment mechanism 5. The posture detection unit 1 is used to detect the user's posture information and transmit it to the core control unit 2. The core control unit 2 is used to control the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5 according to the received posture information, so as to remind the user to adjust their posture by means of at least one of the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5 when the user has poor posture.
[0038] The working principle of the study desk system in this embodiment of the utility model is as follows:
[0039] When in use, the system is started, which powers on the posture detection unit 1, the core control unit 2, and the reminder unit 3. During the use of the study desk, the posture detection unit 1 detects the user's posture information in real time and transmits it to the core control unit 2. The core control unit 2 determines whether the received posture information is poor. When the user has poor posture, the core control unit 2 outputs a corresponding reminder command, reminding the user to adjust their posture through at least one of the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5.
[0040] The study desk system of this utility model embodiment is equipped with a posture detection unit 1, a core control unit 2, and a reminder unit 3. The posture detection unit 1 detects the user's posture information to achieve effective posture monitoring. The core control unit 2 controls the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5 based on the received posture information. When the user has poor posture, at least one of the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5 reminds the user to adjust their posture, thereby realizing proactive intervention to correct poor posture when poor posture is detected.
[0041] In one embodiment, such as Figure 1 As shown, the posture detection unit 1 includes a first pressure sensor array 11 disposed on the seat and a second pressure sensor array 12 disposed in a preset area of the table. The first pressure sensor array 11 and the second pressure sensor array 12 are respectively connected to the core control unit 2.
[0042] The first pressure sensor array 11 is used to detect the pressure distribution information of the user on the seat and transmit it to the core control unit 2;
[0043] The second pressure sensor array 12 is used to detect the pressure distribution information of the user on the table and transmit it to the core control unit 2.
[0044] In this embodiment, the first pressure sensor array 11 is evenly distributed on the seat surface to collect pressure data of the user's buttocks and back in contact with the seat in real time, forming a pressure distribution matrix. When the user has poor sitting postures such as hunching over, leaning to the left, leaning to the right, leaning forward or leaning back, the pressure center of the buttocks will deviate from the geometric center of the seat, so that the difference between the pressure on one side (such as the left side) and the pressure on the opposite side (such as the right side) is greater than the preset pressure difference threshold. The pressure distribution on the back will also show a unilateral concentration phenomenon, so that the core control unit 2 can determine whether poor sitting postures such as hunching over, leaning to the left, leaning to the right, leaning forward or leaning back are present based on the pressure distribution information of the seat collected by the first pressure sensor array 11.
[0045] The second pressure sensor array 12 is arranged in a preset area of the table (such as the writing area and the elbow support area) to monitor the user's arm support force and the contact pressure between the chest and the table. If the user leans on the table or leans forward, the chest will exert abnormal pressure on the edge of the table (greater than the preset value), and the pressure value in the elbow support area will also increase significantly (greater than the preset value). In this way, the core control unit 2 can determine whether there is a bad sitting posture such as leaning on the table or leaning forward based on the pressure distribution information of the user on the table collected by the second pressure sensor array 12.
[0046] The core control unit 2 can also fuse and analyze the pressure data of the seat and the table, and determine whether there is poor sitting posture through a preset sitting posture model (such as a normal pressure distribution threshold). For example, when the center of pressure of the seat shifts by more than 15% and the pressure in the elbow support area of the table exceeds 50N, it is determined to be a "leaning to the left while slouching on the table" state.
[0047] This embodiment achieves multi-dimensional posture monitoring through dual detection of pressure distribution on the seat and table. It can accurately identify various basic poor sitting postures such as hunching, leaning forward, leaning backward, leaning to the left, and leaning to the right. The non-visual detection of this embodiment avoids the privacy issues caused by cameras, making it suitable for children's use. The sensor array is hidden inside the seat and table, which does not affect the user experience. Moreover, it can be implemented using mature and low-cost thin-film pressure sensor technology, which reduces costs compared to visual detection solutions.
[0048] In one embodiment, the second pressure sensor array 12 is disposed in the left and right elbow areas and the front edge of the table.
[0049] In this embodiment, high-density pressure sensors (spaced ≤ 2cm apart) are arranged in the elbow support area on both sides of the table (10-15cm from the front edge of the table) to detect the user's elbow support position and pressure value in real time. When sitting normally, the elbow pressure is evenly distributed in the middle of the elbow support area. If the user extends one arm too far forward (such as writing with the left hand), the pressure value at the edge of the corresponding elbow support area will suddenly increase.
[0050] A strip pressure sensor is installed on the front edge of the tabletop (i.e. the side wall of the tabletop closest to the user) to detect the contact pressure between the chest and the tabletop. When the user leans forward at an angle greater than 30°, the chest will press against the side wall sensor, triggering a pressure threshold alarm.
[0051] The core control unit 2 can determine the left and right tilt by the symmetry of the pressure distribution in the elbow support area (deviation > 20%), and determine the degree of forward tilt by the pressure value at the front edge of the table (e.g., > 30N). Combined with the seat pressure data, it can realize the three-dimensional positioning of the sitting posture (X / Y / Z axis offset), thereby achieving accurate judgment of poor sitting posture.
[0052] This embodiment distinguishes between poor sitting postures such as writing with the left side tilted, the right shoulder drooping, leaning forward, and slouching by placing the second pressure sensor array 12 on the left and right elbow support areas and the front edge of the table. It judges the sitting posture by the relative change in pressure distribution, and is not affected by the user's body type (obese / thin) or height. When the pressure in the elbow support area is concentrated on the left side, the core control unit 2 can control the reminder unit 3 to output voice and / or light reminders to the user. It can also control the height adjustment mechanism 4 and / or the angle adjustment mechanism 5 to automatically raise or lower the study table or automatically tilt the table to remind the user and guide the user to restore a symmetrical sitting posture.
[0053] It should be noted that when the core control unit 2 analyzes the pressure distribution information collected by the first pressure sensor array 11 and the second pressure sensor array 12 of the posture detection unit 1, it does not involve any improvement to the computer program itself. It can be implemented using only hardware circuitry. For example, a subtractor can be used to calculate the difference between the pressure value in the left area and the pressure value in the right area of the sensor array. Then, a comparator can be used to compare the pressure difference output by the subtractor with a preset pressure difference threshold. When the pressure difference is greater than the preset pressure difference threshold (determined as poor posture), the comparator outputs a high level to at least one of the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5 to remind the user to adjust their posture.
[0054] In one embodiment, the study desk system further includes an identity recognition unit 6, which is connected to the core control unit 2.
[0055] The identity recognition unit 6 is used to detect the identity information of the user currently using the study desk and transmit it to the core control unit 2.
[0056] Specifically, in this embodiment, the identity recognition unit 6 includes at least one of a face recognition module 61, a fingerprint recognition module 62, an RFID reader 63, and an NFC reader 64. The face recognition module 61 uses an RGB-D camera to collect facial depth information and performs feature matching through a convolutional neural network (CNN) to identify the user's identity and output user identity information (such as user ID, user account, etc.); the fingerprint recognition module 62 can identify the user's identity by collecting fingerprints; the RFID reader 63 and the NFC reader 64 read the identity tag worn by the user (such as a smart bracelet or campus card), and the tag stores information such as user ID, height, and historical sitting posture data.
[0057] By setting up an identity recognition unit 6 to detect the identity information of the user currently using the study desk, the core control unit 2 can retrieve corresponding personalized setting parameters from pre-stored data based on the identity information, such as the initial desktop height (formula: height × 0.45 ± 2 cm), tilt angle preference, and posture alarm threshold, to achieve one configuration per person. When switching users, the desktop height and angle are automatically adjusted without manual settings. It can also combine the identity information with the timing module 23 to generate a weekly / monthly posture report for a single user (such as the number of times of poor posture is poor each day and the average study time), which is pushed to parents through the APP, so that parents can understand their child's posture and study situation in a timely manner.
[0058] In one embodiment, such as Figure 2 As shown, the sitting posture detection unit 1 includes a camera module 13, which is connected to the core control unit 2.
[0059] The camera module 13 is used to capture images of the user's sitting posture while using the study desk.
[0060] In this embodiment, the camera module 13 uses a 1080P wide-angle camera (30fps) and is installed 20cm above the tabletop, covering the upper body of the user. The image is grayscaled and noise is reduced to remove ambient light interference. Based on the OpenPose human posture estimation model, 18 key points (shoulders, elbows, wrists, waist, etc.) are detected in real time, and the angles of each joint are calculated. For example, when the angle between the shoulder and waist is less than 150°, it is determined as "hunchback", and when the distance between the chest and the tabletop is less than 30cm, it is determined as "slouching". The core control unit 2 updates the algorithm model regularly through the cloud server, supports the addition of new sitting posture types (such as "writing with head tilted"), and stores the most recent 500 sitting posture images locally for offline recognition.
[0061] The sitting posture detection unit 1, through the camera module 13, allows parents to view images of their child's sitting posture in real time via the parent's APP. Combined with key point annotations, parents can intuitively understand poor posture (such as highlighting hunchback in red). The algorithm can be self-optimized through user feedback (manually marking misjudged cases).
[0062] It should be noted that in this embodiment, the core control unit 2 does not involve any improvement to the computer program itself when analyzing the user's sitting posture image collected by the camera module 13 of the sitting posture detection unit 1. The analysis of the user's sitting posture image adopts existing image processing and recognition technologies such as image grayscale conversion, noise reduction processing, and OpenPose human posture estimation.
[0063] In one embodiment, such as Figure 3 As shown, the sitting posture detection unit 1 includes a distance sensor 14, which is connected to the core control unit 2.
[0064] The distance sensor 14 is used to detect the distance information between the user's chest and the front wall of the table and between the user's head and the table, and transmits it to the core control unit 2.
[0065] In this embodiment, the ranging sensor 14 is a ToF sensor.
[0066] In this embodiment, two sets of ToF sensors are set. One set of ToF sensors (Time-of-Flight sensors) is installed in the middle of the front side wall of the table, emits infrared light pulses and measures the time difference of the reflected signals, calculates the distance between the chest and the table (accuracy ±5mm), and when the distance is <25cm, it is determined as "excessive forward tilting".
[0067] Another set of ToF sensors is placed 15cm above the desktop to detect the vertical distance between the head and the desktop. When the distance is less than 30cm, it is judged as "looking too close".
[0068] This embodiment can also combine seat pressure data (such as the pressure on the buttocks shifting backward when leaning forward) with distance data, and use a Kalman filter algorithm to eliminate accidental interference (such as the instantaneous distance change when reaching for stationery), and set an alarm to be triggered only if there is a continuous abnormality for 5 seconds.
[0069] ToF sensors have strong resistance to ambient light interference (error <10mm under direct sunlight) and a response speed 3 times faster than ultrasonic sensors (50ms / time). When alarm feedback is triggered by the reminder unit 3, the distance status can be displayed via an LED light ring (green >30cm, yellow 25-30cm, red <25cm), allowing users to intuitively perceive the sitting distance.
[0070] The ToF sensor is designed to monitor "looking too close" (<33cm) which affects vision and "excessive forward tilting" which affects the spine, providing dual protection for children's health.
[0071] It should be noted that when the core control unit 2 analyzes the distance information between the user's chest and the front wall of the table and between the user's head and the table collected by the distance sensor 14 of the posture detection unit 1, it does not involve any improvement to the computer program itself. It can be implemented using only hardware circuitry. For example, a comparator can be used to compare the distance information between the user's chest and the front wall of the table output by the distance sensor 14 with a preset distance threshold. When the distance information is less than the preset distance threshold (determined as poor posture), the comparator outputs a high level to at least one of the reminder unit 3, the height adjustment mechanism 4, and the angle adjustment mechanism 5 to remind the user to adjust their posture.
[0072] In one embodiment, the alert unit 3 includes an LED light warning device 31 and a voice playback warning device 32.
[0073] Specifically, the LED light warning device 31 can be a ring-shaped LED light strip set on the edge of the table. Different bad sitting postures correspond to different light modes: hunching over → red breathing light, leaning on the table → yellow flashing light, leaning to the left / right → single-sided blue flowing light. The brightness of the light can also indicate the degree of bad sitting posture. The greater the degree of bad sitting posture, the brighter the light, so that users can understand their sitting posture more intuitively.
[0074] The voice-activated warning device 32 has a built-in 3W speaker and can store various personalized reminder voices (such as "Little one, lift your head up!" and "Little one, sit up straight to grow taller"), and supports parents to customize their own recordings. The voice reminder interval is dynamically adjusted according to the duration of poor posture (e.g., after the first reminder, it repeats every 3 minutes).
[0075] If three consecutive reminders are ineffective, the height / angle adjustment can be automatically activated. If you lean too close to the ground, the desktop height will be raised by 2cm; if you lean to the left, the desktop will be tilted upward by 3°. This physical intervention helps to correct your posture.
[0076] In this embodiment, when reminding the user to adjust their posture, a multi-sensory coordinated hierarchical reminder is used: visual (lighting) + auditory (voice) + tactile (desktop adjustment) three-dimensional stimulation, which is more effective than a single reminder method; the reminder gradually upgrades from gentle reminders to physical adjustments, avoiding excessive intervention that may affect learning focus, and balancing health protection and user experience.
[0077] In one embodiment, the core control unit 2 includes an MCU 21, a memory 22, a timing module 23, a motor drive module 24, and a wireless communication module 25. The memory 22, the timing module 23, the motor drive module 24, and the wireless communication module 25 are respectively connected to the MCU 21. The posture detection unit 1 and the reminder unit 3 are respectively connected to the MCU 21. The height adjustment mechanism 4 and the angle adjustment mechanism 5 are respectively connected to the motor drive module 24.
[0078] In this embodiment, MCU21 uses an ARM Cortex-M4 processor to process sensor data in real time and supports multi-task parallel processing (sitting posture detection, motor control, and wireless communication are performed simultaneously). Memory 22 uses a Flash memory chip + RAM cache. The Flash memory chip stores user configuration files, sitting posture model parameters, and historical data; the RAM cache stores real-time sensor data and supports fast algorithm calls. Motor drive module 24 integrates an H-bridge drive circuit, supporting DC motor forward and reverse rotation and PWM speed regulation, controlling the direction and speed of height adjustment, as well as the direction and speed of angle adjustment. Wireless communication module 25 uses a 2.4G Wi-Fi module + BLE5.0 module. The 2.4G Wi-Fi module enables data synchronization with the mobile APP, and the BLE5.0 module is used for close-range configuration (such as initial user registration). Data transmission can be encrypted using the AES-128 algorithm. The parent APP can view sitting posture data in real time, remotely adjust desktop parameters, and receive abnormal alarms (such as push notifications for 30 seconds of continuous slouching). Timing module 23 can use a high-precision RTC clock to record learning time and duration of poor sitting posture.
[0079] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.
[0080] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention.
[0081] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly using hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.
[0082] The above description of the disclosed embodiments enables those skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A study desk system, comprising a study desk body, the study desk body having a height adjustment mechanism for electrically adjusting the desktop height and an angle adjustment mechanism for electrically adjusting the desktop tilt angle, characterized in that, It also includes a posture detection unit, a core control unit, and a reminder unit. The signal output terminal of the posture detection unit is connected to the first signal input terminal of the core control unit, the first signal output terminal of the core control unit is connected to the signal input terminal of the reminder unit, the second signal output terminal of the core control unit is connected to the signal input terminal of the height adjustment mechanism, and the third signal output terminal of the core control unit is connected to the signal input terminal of the angle adjustment mechanism. The sitting posture detection unit is used to detect the user's sitting posture information and transmit it to the core control unit; The core control unit is used to control the reminder unit, height adjustment mechanism and angle adjustment mechanism according to the received posture information, so as to remind the user to adjust their posture by means of at least one of the reminder unit, height adjustment mechanism and angle adjustment mechanism when the user has poor posture.
2. The study desk system according to claim 1, characterized in that, The posture detection unit includes a first pressure sensor array mounted on the seat and a second pressure sensor array mounted in a preset area of the table. The first and second pressure sensor arrays are respectively connected to the core control unit. The first pressure sensor array is used to detect the pressure distribution information of the user on the seat and transmit it to the core control unit; The second pressure sensor array is used to detect the pressure distribution information of the user on the tabletop and transmit it to the core control unit.
3. The study desk system according to claim 2, characterized in that, The second pressure sensor array is disposed in the left and right elbow areas of the table and / or the front edge of the table.
4. The study desk system according to claim 1, characterized in that, It also includes an identity recognition unit, which is connected to the core control unit, wherein, The identity recognition unit is used to detect the identity information of the user currently using the study desk and transmit it to the core control unit.
5. The study desk system according to claim 4, characterized in that, The identity recognition unit includes at least one of a face recognition module, a fingerprint recognition module, an RFID reader, and an NFC reader.
6. The study desk system according to claim 4, characterized in that, The posture detection unit includes a camera module, which is connected to the core control unit. The camera module is used to capture images of the user's sitting posture while using the study desk.
7. The study desk system according to claim 4, characterized in that, The posture detection unit includes a distance sensor, which is connected to the core control unit. The distance sensor is used to detect the distance information between the user's chest and the front wall of the table and / or between the user's head and the table, and transmits it to the core control unit.
8. The study desk system according to claim 7, characterized in that, The ranging sensor is a ToF sensor.
9. The study desk system according to claim 1, characterized in that, The alert unit includes an LED light warning device and a voice playback warning device.
10. The study desk system according to any one of claims 1-9, characterized in that, The core control unit includes an MCU, a memory, a timing module, a motor drive module, and a wireless communication module. The memory, timing module, motor drive module, and wireless communication module are all connected to the MCU. The posture detection unit and the reminder unit are all connected to the MCU. The height adjustment mechanism and the angle adjustment mechanism are all connected to the motor drive module.