An office device control method and system having a function of preventing lumbar disease

Abstract

The application relates to the technical field of office equipment, and particularly provides an office device control method and system with a lumbar disease prevention function, which comprises the following steps: collecting user sitting posture related data; constructing a multi-dimensional health assessment model based on the preprocessed user sitting posture related data, and obtaining a health score of the current sitting posture of the user according to the multi-dimensional health assessment model; dividing the current sitting posture of the user into different grades according to the health score, and controlling the action of the office device according to the current sitting posture grade of the user to guide the user to restore a correct sitting posture. The application considers multi-dimensional factors that affect the sitting posture of the user, can control the action of the office device according to the current sitting posture grade of the user, automatically adjust the height, angle and other parameters of the office chair and the office table, guide the user to restore a correct sitting posture, is favorable for comprehensively and effectively monitoring and correcting the sitting posture of the user, and thus provides health protection for people who use computers for a long time.

Description

Technical Field

[0001] This invention relates to the field of office equipment technology, and more specifically, to a control method and system for an office device with the function of preventing lumbar spine diseases. Background Technology

[0002] In today's fast-paced life, workplace health issues are prominent, with lumbar spine problems increasingly affecting younger people. Office desks and chairs, as necessities in the workplace, play a crucial role in preventing lumbar spine diseases through their design and usage. However, in existing office environments, traditional desks and chairs often lack real-time monitoring and automatic adjustment functions for user posture, making it difficult to correct poor posture and increasing the risk of lumbar spine problems. Existing technologies, such as the Chinese invention patent application number CN202111628389.0 "A Method for Recommending Sitting Height of Adjustable Desks for Healthy Office Work" and the Chinese invention patent application number CN202410407825.9 "A Control Method and System for Office Desks and Chairs," while capable of adjusting desk and chair height based on user posture, do not comprehensively consider integrating user posture-related data to construct a multi-dimensional health assessment model, making it difficult to comprehensively and effectively monitor and correct user posture.

[0003] Given the untapped potential of sensors and mechanical devices, office systems for preventing lumbar spine disorders based on sensor network data acquisition and mechanical device assistance hold significant practical importance and application prospects. Therefore, it is necessary to develop a control method for office devices with lumbar spine disorder prevention functions to more comprehensively and effectively monitor and correct users' posture, providing health protection for people who spend long hours working on computers. Summary of the Invention

[0004] Based on this, in order to improve the efficiency of user posture monitoring and correction, the present invention provides a control method and system for an office device with the function of preventing lumbar spine diseases, the specific technical solution of which is as follows:

[0005] A method for controlling an office device with the function of preventing lumbar spine diseases includes the following steps: By deploying sensor networks on office chairs and desks, data related to user posture can be collected. The user's sitting posture data is preprocessed, a multi-dimensional health assessment model is constructed based on the preprocessed user sitting posture data, and the health score of the user's current sitting posture is obtained according to the multi-dimensional health assessment model. The system categorizes users' current sitting posture into different levels based on their health scores, and controls the operation of office equipment according to the user's current posture level to guide the user to restore the correct sitting posture.

[0006] The described office device control method with lumbar spine disease prevention function collects multi-dimensional user posture-related data by deploying a sensor network on the office chair and desk, and constructs a multi-dimensional health assessment model to obtain the user's current posture health score. It considers multiple factors affecting user posture and can control the office device's actions based on the user's current posture level, automatically adjusting parameters such as the height and angle of the office chair and desk to guide the user to restore correct posture. It overcomes the shortcomings of existing methods that do not comprehensively consider and integrate user posture-related data to construct a multi-dimensional health assessment model, making it difficult to comprehensively and effectively monitor and correct user posture. This method is conducive to comprehensively and effectively monitoring and correcting user posture, thereby providing health protection for people who use computers for long periods of time.

[0007] Preferably, the specific method for constructing a multidimensional health assessment model includes the following steps: The contact pressure between various parts of the user's body and the office chair is obtained, and a pressure distribution item is obtained based on the contact pressure to quantify the risk of the user's center of gravity shifting in the sitting posture. Obtain the user's actual spinal curvature angle, and based on the actual spinal curvature angle, obtain a static spinal deviation item to assess the static risk of the spinal curvature deviating from the ideal state; The system acquires the user's real-time neck angle and uses this angle to obtain a dynamic neck risk item for capturing the instantaneous risk of sudden neck movement. A multidimensional health assessment model is constructed based on pressure distribution, spinal static deviation, and cervical dynamic risk.

[0008] Preferably, the specific method for obtaining the pressure distribution term includes the following steps: Obtain the ideal distributed pressure, and obtain the pressure distribution deviation that reflects the degree of center of gravity shift in sitting posture based on the contact pressure and the ideal distributed pressure. Based on the Sigmoid function, the pressure distribution deviation is mapped to obtain the pressure distribution term.

[0009] Preferably, the specific method for obtaining the static deviation of the spine includes the following steps: Obtain the ideal curvature angle of the spine, and calculate the absolute deviation of the spinal angle between the ideal curvature angle and the actual curvature angle of the spine. The maximum permissible deviation of the spine is obtained. After normalizing the absolute deviation of the spine angle based on the maximum permissible deviation of the spine, the static deviation term of the spine is obtained.

[0010] Preferably, the specific method for obtaining the dynamic risk item of the neck includes the following steps: The rate of change of neck angle is obtained based on the real-time neck angle. Obtain the dynamic risk threshold for the neck, and obtain the dynamic risk item for the neck based on the rate of change of neck angle and the dynamic risk threshold for the neck.

[0011] An office device control system with a function of preventing lumbar spine diseases, used to implement the office device control method, comprising: The posture monitoring module is used to collect user posture-related data through a sensor network deployed on office chairs and desks, and transmit the user posture-related data to the central controller. The central controller is used to preprocess user posture-related data, build a multi-dimensional health assessment model based on the preprocessed user posture-related data, obtain the health score of the user's current posture according to the multi-dimensional health assessment model, classify the user's current posture into different levels according to the health score, and control the operation of office equipment according to the user's current posture level to guide the user to restore the correct posture. The mechanical adjustment module is used to respond to the office equipment control commands generated by the central controller and control the operation of the office equipment.

[0012] Preferably, the central controller includes: The pressure distribution acquisition module is used to acquire the contact pressure between various parts of the user's body and the office chair, and to acquire pressure distribution items based on the contact pressure to quantify the risk of the user's center of gravity shifting while sitting. The static deviation item acquisition module is used to acquire the user's actual spinal curvature angle and, based on the actual spinal curvature angle, acquire the spinal static deviation item used to assess the static risk of the spinal curvature deviating from the ideal state. The dynamic risk item acquisition module is used to acquire the user's real-time neck angle and acquire dynamic neck risk items based on the real-time neck angle to capture the instantaneous risk of sudden neck movement. The health assessment model building module is used to construct a multi-dimensional health assessment model based on stress distribution items, spinal static deviation items, and cervical dynamic risk items.

[0013] Preferably, the pressure distribution term acquisition module includes: The pressure distribution deviation acquisition unit is used to acquire the ideal distribution pressure and to acquire the pressure distribution deviation that reflects the degree of center of gravity shift in the sitting posture based on the contact pressure and the ideal distribution pressure. The pressure distribution mapping unit is used to map the pressure distribution deviation based on the Sigmoid function to obtain the pressure distribution term.

[0014] Preferably, the static deviation term acquisition module includes: The absolute angle deviation acquisition unit is used to acquire the ideal curvature angle of the spine and calculate the absolute angle deviation of the spine between the ideal curvature angle and the actual curvature angle of the spine. The absolute deviation normalization processing unit is used to obtain the maximum permissible deviation of the spine. After normalizing the absolute deviation of the spine angle based on the maximum permissible deviation of the spine, the static deviation term of the spine is obtained.

[0015] Preferably, the dynamic risk item acquisition module includes: Angle change rate acquisition unit, used to acquire the neck angle change rate based on the real-time neck angle; The dynamic risk item acquisition unit is used to acquire the neck dynamic risk threshold and to acquire the neck dynamic risk item based on the neck angle change rate and the neck dynamic risk threshold. Attached Figure Description

[0016] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0017] Figure 1 This is a schematic diagram of the overall process of a pet state recognition method based on motion capture and sound analysis in one embodiment of the present invention. Figure 2 This is a flowchart illustrating a specific method for obtaining an abnormal behavior index in one embodiment of the present invention. Figure 3 This is a flowchart illustrating a specific method for obtaining an emotion score in one embodiment of the present invention; Figure 4 This is a schematic diagram of the overall process of a pet state recognition method based on motion capture and sound analysis in another embodiment of the present invention; Figure 5 This is a flowchart illustrating a specific method for obtaining dynamic risk items of the neck in one embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of the invention.

[0019] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] In this invention, "first" and "second" do not represent a specific quantity or order, but are merely used to distinguish names.

[0022] Before describing the specific embodiments of the present invention, a brief introduction to the prior art will be given first.

[0023] In today's fast-paced life, workplace health issues are prominent, with lumbar spine problems increasingly affecting younger people. Office desks and chairs, as necessities in the workplace, play a crucial role in preventing lumbar spine diseases through their design and usage. However, in existing office environments, traditional desks and chairs often lack real-time monitoring and automatic adjustment functions for user posture, making it difficult to correct poor posture and increasing the risk of lumbar spine problems. Existing technologies, such as the Chinese invention patent application number CN202111628389.0 "A Method for Recommending Sitting Height of Adjustable Desks for Healthy Office Work" and the Chinese invention patent application number CN202410407825.9 "A Control Method and System for Office Desks and Chairs," while capable of adjusting desk and chair height based on user posture, do not comprehensively consider integrating user posture-related data to construct a multi-dimensional health assessment model, making it difficult to comprehensively and effectively monitor and correct user posture.

[0024] Given the untapped potential of sensors and mechanical devices, office systems for preventing lumbar spine disorders based on sensor network data acquisition and mechanical device assistance hold significant practical importance and application prospects. Therefore, it is necessary to develop a control method for office devices with lumbar spine disorder prevention functions to more comprehensively and effectively monitor and correct users' posture, providing health protection for people who spend long hours working on computers.

[0025] Furthermore, with the development of IoT technology, data synchronization and analysis have become crucial components of smart devices. Through wireless communication technologies such as Bluetooth and Wi-Fi, users can transmit health data to their phones or computers for further analysis. However, existing data analysis primarily focuses on sports and health, lacking systematic solutions for analyzing posture and providing health recommendations in the office environment. This invention will fill this gap and effectively alleviate health problems in the office environment.

[0026] In summary, the existing technology has the following drawbacks: 1. Lacks real-time posture monitoring function Traditional office chairs lack real-time posture monitoring capabilities, making it impossible to detect and correct poor posture in a timely manner. Prolonged periods of poor posture (such as leaning forward, hunching over, etc.) can easily lead to strain on the lumbar and cervical spine, increasing the risk of occupational diseases. Since they cannot prevent health problems caused by poor posture, users need to rely on self-awareness or external reminders to maintain correct posture.

[0027] 2. No automatic adjustment function Traditional office chairs cannot automatically adjust their height, angle, and other parameters based on the user's posture. Users need to manually adjust the chair, a cumbersome and inefficient process that makes precise adjustments difficult. Manual adjustments may result in chair parameters that are not ergonomically sound, which can exacerbate fatigue and discomfort with prolonged use.

[0028] 3. Insufficient application of sensor technology Traditional office chairs do not fully utilize advanced technologies such as pressure sensors and posture sensors. They cannot collect users' posture data in real time, lacking scientific analysis and feedback on posture. Users cannot understand their own posture habits and find it difficult to take targeted measures to improve their posture.

[0029] 4. Lack of data synchronization and analysis functions. Traditional office chairs lack data synchronization and analysis capabilities, making it impossible to synchronize user posture data with smart devices (such as mobile phones and computers). Users cannot understand their long-term posture habits through data analysis, nor can they obtain personalized health advice. Without data support, users struggle to develop scientific health management plans.

[0030] 5. The reminder function is limited or missing. Traditional office chairs lack effective reminder functions, failing to promptly alert users when they adopt poor posture. The reminder methods are often limited (e.g., relying solely on sound), making them easily ignored by users. Furthermore, they cannot effectively correct poor posture, potentially leading users to maintain incorrect positions for extended periods, increasing health risks.

[0031] 6. Lack of personalized adaptation Traditional office chairs are typically designed based on universal standards, making it impossible to personalize them according to users' body characteristics and habits. Different users have significantly different physical conditions (such as height, weight, and sitting posture), and a universal design cannot meet everyone's needs. Users may experience discomfort, and prolonged use can exacerbate fatigue and health problems.

[0032] One of the objectives of this invention is to improve the efficiency of user posture monitoring and correction. To this end, such as... Figure 1 As shown, an embodiment of the present invention provides a control method for an office device with the function of preventing lumbar spine diseases, comprising the following steps: S1 collects user posture-related data by deploying a sensor network on office chairs and desks.

[0033] Specifically, various sensors (such as pressure sensors, posture sensors, and head and neck posture monitors) can be placed on office chairs and desks to collect users' sitting posture data in real time and transmit it to the central controller for analysis.

[0034] S2 preprocesses user posture-related data, constructs a multi-dimensional health assessment model based on the preprocessed user posture-related data, and obtains the user's current posture health score based on the multi-dimensional health assessment model.

[0035] The central controller's built-in algorithm processes user posture data collected by the sensor network to construct a multi-dimensional health assessment model. This model comprehensively considers factors such as center of gravity position, pressure distribution, and spinal curvature to generate and categorize health scores. Through accurate data processing and health assessment, the system's effectiveness is ensured, guaranteeing that adjustments and reminders are based on scientific analysis.

[0036] S3 categorizes the user's current sitting posture into different levels based on their health score, and controls the operation of office devices according to the user's current sitting posture level to guide the user to restore the correct sitting posture.

[0037] Specifically, based on health scores, the system automatically adjusts parameters such as the height and angle of office chairs and desks using electric actuators or pneumatic pistons to adapt to the user's healthy sitting posture. This automated adjustment of chair and desk parameters improves user experience and health protection, promptly corrects poor posture, and reduces the hassle of manual adjustments.

[0038] Based on the health score H(t), the user's current sitting posture is divided into different levels: H(t) < 0.3 is good, 0.3 ≤ H(t) < 0.6 is mildly poor, and H(t) ≥ 0.6 is severely poor. Historical H(t) data can be used to generate personalized health reports.

[0039] If 0.3≤H(t)<0.6, the office equipment can be controlled to make gentle adjustments, such as slightly raising the seat cushion; if H(t)≥0.6, forced adjustments will be made, such as multi-axis linkage, simultaneously adjusting the seat cushion height, backrest angle, and desktop height.

[0040] The system can pre-set the seat height adjustment amount and backrest angle adjustment amount corresponding to different health scores, build a parameter mapping table, and then obtain the health score corresponding to the user's current sitting posture, call the parameter mapping table, and control the operation of the office device.

[0041] As a preferred technical solution, the system can also be personalized based on the user's physical characteristics and habits, providing real-time feedback and long-term health advice through reminder and feedback modules. In this way, personalized adaptation enhances the system's applicability and user experience, while the feedback mechanism helps users continuously improve their posture.

[0042] As a preferred technological solution, user posture data can also be synchronized with smart devices, generating detailed health reports and recommendations through data analysis. Data synchronization and analysis can help users understand their long-term posture habits and develop scientific health management plans.

[0043] In summary, the proposed office device control method with lumbar spine disease prevention function collects multi-dimensional user posture-related data by deploying a sensor network on the office chair and desk, and constructs a multi-dimensional health assessment model to obtain a health score for the user's current posture. It considers multiple factors affecting user posture and can control the office device's actions based on the user's current posture level, automatically adjusting parameters such as the height and angle of the office chair and desk to guide the user back to correct posture. This overcomes the shortcomings of existing methods that do not comprehensively consider and integrate user posture-related data to construct a multi-dimensional health assessment model, making it difficult to comprehensively and effectively monitor and correct user posture. This method is beneficial for comprehensively and effectively monitoring and correcting user posture, thereby providing health protection for people who use computers for long periods of time.

[0044] In one embodiment, such as Figure 2 As shown, the specific method for constructing a multi-dimensional health assessment model includes the following steps: S21, obtain the contact pressure between various parts of the user's body and the office chair, and obtain the pressure distribution item based on the contact pressure to quantify the risk of the user's center of gravity shifting while sitting.

[0045] Specifically, such as Figure 3 As shown, the specific method for obtaining the pressure distribution term includes the following steps: S211, Obtain the ideal distributed pressure, and obtain the pressure distribution deviation that reflects the degree of center of gravity shift in the sitting posture based on the contact pressure and the ideal distributed pressure.

[0046] S212, based on the Sigmoid function, maps the pressure distribution deviation to obtain the pressure distribution term.

[0047] Specifically, the contact pressure between various parts of the user's body and the office chair can be obtained through an array of pressure sensors installed on the seat cushion / backrest.

[0048] Based on the Sigmoid function, pressure distribution deviation is mapped to the 0-1 range, so that the larger the pressure distribution deviation, the higher the pressure distribution term, and the lower the corresponding health status. For example, when prolonged sitting causes concentrated pressure on the buttocks, the pressure distribution deviation increases significantly, the pressure distribution term rises, and an alarm is triggered.

[0049] S22, obtain the user's actual spinal curvature angle, and obtain a static spinal deviation term based on the actual spinal curvature angle to assess the static risk of the spinal curvature deviating from the ideal state.

[0050] Specifically, such as Figure 4 As shown, the specific method for obtaining the static deviation of the spine includes the following steps: S221, obtain the ideal curvature angle of the spine, and calculate the absolute deviation of the spine angle between the ideal curvature angle and the actual curvature angle of the spine. S222, obtain the maximum permissible deviation of the spine, and after normalizing the absolute deviation of the spine angle based on the maximum permissible deviation of the spine, obtain the static deviation term of the spine.

[0051] The actual curvature angle of the spine can be obtained through a spine-attached or seat-embedded posture sensor (accelerometer + gyroscope). The ideal curvature angle of the spine can be understood as the physiological curvature standard that conforms to ergonomics, and can be defined as a personalized benchmark value based on the user's height / weight preset.

[0052] The greater the absolute deviation of the spinal angle, the higher the value of the static deviation term of the spine. For example, in kyphosis, the actual bending angle of the spine deviates negatively, and the value of the static deviation term of the spine increases significantly.

[0053] S23, obtain the user's real-time neck angle, and obtain a dynamic neck risk item based on the real-time neck angle to capture the instantaneous risk of sudden neck movement.

[0054] Specifically, such as Figure 5 As shown, the specific method for obtaining the dynamic risk item of the neck includes the following steps: S231, obtain the rate of change of neck angle based on the real-time neck angle.

[0055] S232, Obtain the neck dynamic risk threshold, and obtain the neck dynamic risk item based on the neck angle change rate and the neck dynamic risk threshold.

[0056] Real-time neck angles can be obtained using a head and neck posture monitor, defined as the absolute angle values ​​for head tilting, head raising, and side tilting. The rate of change of neck angle is determined by calculating the time derivative of the neck angle and is used to reflect the dynamic risk of sudden forward or backward tilting of the neck.

[0057] The rate of change of neck angle reflects the intensity of the movement. When looking down at high speed, the rate of change of neck angle is <0 and the absolute value is large, and the value of this dynamic risk item of the neck increases sharply.

[0058] S24. A multi-dimensional health assessment model is constructed based on the pressure distribution item, the spinal static deviation item, and the cervical dynamic risk item.

[0059] A health score is obtained based on a multi-dimensional health assessment model to determine the user's current sitting posture. The higher the value, the higher the health risk. The health score is used to classify the sitting posture level (such as good, mildly poor, severely poor, etc.).

[0060] For example, a multidimensional health assessment model is represented as follows: .in, Indicates health score, These represent the pressure distribution term, the spinal static deviation term, and the cervical dynamic risk term, respectively. These are the weighting coefficients. The Sigmoid normalization function maps the sum of the pressure distribution term, the spinal static deviation term, and the cervical dynamic risk term to the 0-1 range.

[0061] These are the pressure sensitivity coefficient and the pressure distribution deviation, respectively. The pressure sensitivity coefficient is used to control the nonlinear effect of pressure deviation on the score. The larger the value, the more significant the effect of small deviation on the score. The typical value range is 1-5.

[0062] These are represented, in order, the actual curvature angle of the spine, the ideal curvature angle of the spine, and the maximum permissible deviation of the spine. The maximum permissible deviation of the spine is set based on clinical data and is a preset constant, generally between 15 and 20 degrees. These are the rate of change of neck angle and the dynamic risk threshold of the neck, respectively. The unit of the dynamic risk threshold of the neck is degrees / second. Actions below this value are considered safe. This can be determined experimentally, with typical values ​​of 0.5° / second to 1° / second.

[0063] For the pressure distribution item, based on the Sigmoid function, sensitivity to gradually changing poor posture can be achieved, avoiding misjudgments caused by baseline deviation. For the spinal static deviation item, based on the tanh function and combined with the maximum permissible spinal deviation, when the spinal deviation is within the safe range, its output is close to 0; when the deviation exceeds the safe range, the output approaches β as the deviation increases, which can prevent scoring from going out of control and improve the tolerance for minor deviations, reducing false alerts. For the neck dynamic risk item... This ensures that all rapid neck movements (whether tilting the head down or tilting it back) are quantified as risks. It can filter out minor, safe neck movements to avoid frequent alerts, while accurately capturing high-risk, sudden movements.

[0064] In summary, a multi-dimensional health assessment model is constructed by integrating stress distribution items, spinal static deviation items, and cervical dynamic risk items. It can identify sudden adverse movements (such as sudden forward tilting) in advance through cervical derivative items, and convert stress deviation into exponentially increasing scores through the Sigmoid function to quantify stress distribution risk.

[0065] Prolonged sitting can easily lead to chronic health risks. For example, the health risks of the same poor sitting posture differ greatly between 1 minute and 30 minutes. By quantifying the cumulative risks of prolonged sitting, the warning lag of poor sitting posture can be reduced, enabling early intervention.

[0066] As a preferred technical solution, a sitting posture duration accumulation term can be introduced. This term is used to assess the risk of the same sitting posture deviation over a longer duration. A multi-dimensional health assessment model is constructed by integrating the sitting posture duration accumulation term, pressure distribution term, spinal static deviation term, and cervical dynamic risk term. For example, the sitting posture duration accumulation term is represented as... ;in, These are represented, in order, the cumulative risk weighting coefficient, the time sensitivity coefficient, and the current sitting posture duration (in minutes). The cumulative risk weighting coefficient is adaptively adjusted according to the sitting posture duration. The time sensitivity coefficient is used to control the rate at which the duration affects the risk, and its preset constant has a typical value of 0.05-0.1. The current sitting posture duration can be accumulated based on the effective sitting posture signal detected by the sensor.

[0067] The resulting multidimensional health assessment model is represented as a Sigmoid mapping of the sum of the cumulative sitting duration, pressure distribution, spinal static deviation, and cervical dynamic risk.

[0068] An embodiment of the present invention also provides an office device control system with a function of preventing lumbar spine diseases, for implementing the office device control method, which includes a posture monitoring module, a central controller and a mechanical adjustment module.

[0069] The posture monitoring module is used to collect user posture-related data through a sensor network deployed on office chairs and desks, and transmit the user posture-related data to the central controller.

[0070] Specifically, the posture monitoring module includes: 1. Sensor Network Deployment: Various types of sensors, including pressure sensors and posture sensors (such as accelerometers and gyroscopes), are strategically placed on the seat cushions, backrests, and desks of office chairs to comprehensively collect user posture-related data. Pressure sensors detect the contact pressure between different parts of the user's body and the chair / desktop, thereby inferring the center of gravity distribution of the sitting posture. Posture sensors monitor overall body posture changes, such as forward and backward leaning, and left and right twisting. Head and neck posture monitors specifically monitor the user's head and neck posture in real time, including head tilt angle, head tilt direction, and neck flexion, providing more comprehensive data support for assessing postural health.

[0071] 2. Data Acquisition and Transmission: Data acquired by the sensors in real time is transmitted to the central controller via wired or wireless communication. Wireless communication can utilize common technologies such as Bluetooth and Wi-Fi to ensure stable and efficient data transmission. The central controller performs preliminary processing and integration of the received data for subsequent analysis.

[0072] The central controller is used to preprocess user posture-related data, build a multi-dimensional health assessment model based on the preprocessed user posture-related data, obtain the user's current posture health score according to the multi-dimensional health assessment model, classify the user's current posture into different levels according to the health score, and control the operation of office equipment according to the user's current posture level to guide the user to restore the correct posture.

[0073] The central controller's built-in data processing algorithm performs in-depth analysis of the collected sensor data. First, it processes the pressure sensor data to calculate the user's center of gravity position and pressure distribution, determining if there are any areas of excessive or insufficient pressure. If so, this indicates potential poor posture. For the posture sensor data, a posture calculation algorithm accurately calculates key posture parameters such as the user's spinal curvature and body tilt angle, comparing these parameters with preset healthy sitting posture standards.

[0074] Based on the above processing results, a multi-dimensional health assessment model was constructed. This model comprehensively considers factors such as center of gravity position, pressure distribution, spinal curvature, and body tilt angle, and calculates a health score for the current sitting posture through weighted calculation. For example, when the spinal curvature exceeds a certain value within the normal range, a certain number of points are deducted accordingly; abnormal local pressure also has a negative impact on the score. Based on the score results, sitting posture is divided into different levels, such as good, mildly poor, moderately poor, and severely poor, and relevant data are recorded for subsequent tracking and analysis.

[0075] The mechanical adjustment module is used to respond to the office equipment control commands generated by the central controller and control the operation of the office equipment.

[0076] For the office chair: the design includes adjustable seat height, seat depth, backrest height, and tilt angle. Precise adjustments to these components are achieved using electric actuators or pneumatic pistons. For example, the seat height can be adjusted to fit the user's height via an electric actuator, ensuring both feet are flat on the ground, thighs are parallel to the ground, and knees are at a 90-degree angle. The backrest features an ergonomic curve design, and its tilt angle and lumbar support height can be dynamically adjusted according to the user's posture. This stepless adjustment is achieved through a motor-driven gear transmission mechanism to maintain the natural physiological curvature of the spine.

[0077] For the desk: The design incorporates a height-adjustable desktop structure, also powered by an electric actuator. Upon detecting poor posture, the microprocessor immediately issues a control command, activating the electric actuator and other mechanical devices under the desktop for adjustment. For example, if the user is found to be leaning forward, the corresponding electric actuator will raise the desktop, prompting the user to straighten up. If the head is excessively forward, the system may automatically adjust based on the user's posture and height by pushing the chair or adjusting the desktop height, ensuring that the neck remains naturally vertical when the eyes are level with the computer screen, avoiding cervical fatigue caused by looking down or up.

[0078] The mechanical adjustment module is controlled based on the assessment results of a multi-dimensional health evaluation model. When a user's posture is detected to be slightly incorrect, the micro-adjustment program of the office chair or desk is initiated, such as making small adjustments to the seat cushion depth or desktop height to guide the user back to a correct posture. If the posture is moderately or more incorrect, the adjustment intensity is increased, such as simultaneously adjusting multiple parts of the office chair and the height of the desk, to quickly correct the poor posture. During the adjustment process, the sequence and amplitude of the actions of each drive device are precisely controlled by the central controller to ensure that the adjustment process is smooth, accurate, and conforms to ergonomic principles.

[0079] When a user's posture is consistently poor and mechanical adjustments fail to improve it, a reminder function can be activated. Reminders can be delivered via sound, message, or vibration. The system continuously monitors the user's posture; once poor posture is detected, it triggers a reminder and begins an adjustment process. Through adjustments to the desktop or adjustments to the chair, the system guides the user back to the correct posture, ensuring a comfortable and healthy posture at all times during work.

[0080] Based on users' long-term sitting posture data, personalized health reports and suggestions are generated, including posture improvement goals, daily exercise plans, and office environment optimization suggestions, helping users comprehensively improve their physical health. In addition to common body posture monitoring, head and neck posture detection functions can also be added to make sitting posture assessment more accurate and comprehensive, effectively preventing problems such as cervical fatigue, pain, and myopia caused by poor posture.

[0081] The system can also build feedback content and mechanisms, including detailed information such as specific problems with the current sitting posture, health suggestions, and improvement goals. It connects to the user's smart devices via Bluetooth or Wi-Fi to achieve real-time data synchronization and sharing, enabling users to clearly understand their sitting posture and areas for improvement. Simultaneously, this module also features user interaction capabilities, allowing users to manually input their feelings or special needs. The system can then further optimize and adjust its strategies and reminder methods based on this feedback, improving user experience and system adaptability.

[0082] In summary, the office device control system with lumbar spine disease prevention function collects multi-dimensional user posture-related data by deploying a sensor network on office chairs and desks, and constructs a multi-dimensional health assessment model to obtain a health score of the user's current posture. It considers multiple factors affecting user posture and can control the operation of the office device based on the user's current posture level, automatically adjusting parameters such as the height and angle of the office chair and desk to guide the user back to correct posture. This overcomes the shortcomings of existing systems that do not comprehensively consider and integrate user posture-related data to construct a multi-dimensional health assessment model, making it difficult to comprehensively and effectively monitor and correct user posture. Therefore, it is beneficial for comprehensively and effectively monitoring and correcting user posture, thus providing health protection for people who use computers for long periods of time.

[0083] In one embodiment, the central controller includes a pressure distribution acquisition module, a static deviation acquisition module, a dynamic risk acquisition module, and a health assessment model construction module.

[0084] The pressure distribution acquisition module is used to acquire the contact pressure between various parts of the user's body and the office chair, and to acquire pressure distribution items based on the contact pressure to quantify the risk of the user's center of gravity shifting while sitting.

[0085] Specifically, the pressure distribution item acquisition module includes: a pressure distribution deviation acquisition unit, used to acquire the ideal distribution pressure, and to acquire the pressure distribution deviation reflecting the degree of center of gravity shift in sitting posture based on the contact pressure and the ideal distribution pressure; and a pressure distribution mapping unit, used to map the pressure distribution deviation based on the Sigmoid function to acquire the pressure distribution item.

[0086] The static deviation acquisition module is used to obtain the user's actual spinal curvature angle and, based on the actual spinal curvature angle, to obtain a static deviation item for assessing the static risk of the spinal curvature deviating from the ideal state.

[0087] Specifically, the static deviation term acquisition module includes: an absolute angle deviation acquisition unit, used to acquire the ideal curvature angle of the spine and calculate the absolute deviation of the spine angle between the ideal curvature angle and the actual curvature angle of the spine; and an absolute deviation normalization processing unit, used to acquire the maximum permissible deviation of the spine, normalize the absolute deviation of the spine angle based on the maximum permissible deviation of the spine, and then acquire the static deviation term of the spine.

[0088] The dynamic risk item acquisition module is used to acquire the user's real-time neck angle and acquire dynamic risk items of the neck based on the real-time neck angle to capture the instantaneous risk of sudden neck movement.

[0089] Specifically, the dynamic risk item acquisition module includes: an angle change rate acquisition unit, used to acquire the neck angle change rate based on the real-time neck angle; and a dynamic risk item acquisition unit, used to acquire the neck dynamic risk threshold, and to acquire the neck dynamic risk item based on the neck angle change rate and the neck dynamic risk threshold.

[0090] The health assessment model building module is used to construct a multi-dimensional health assessment model based on stress distribution, spinal static deviation, and cervical dynamic risk.

[0091] For example, a multidimensional health assessment model is represented as follows: .in, Indicates health score, These represent the pressure distribution term, the spinal static deviation term, and the cervical dynamic risk term, respectively. These are the weighting coefficients. The Sigmoid normalization function maps the sum of the pressure distribution term, the spinal static deviation term, and the cervical dynamic risk term to the 0-1 range.

[0092] In summary, a multi-dimensional health assessment model is constructed by integrating stress distribution items, spinal static deviation items, and cervical dynamic risk items. It can identify sudden adverse movements (such as sudden forward tilting) in advance through cervical derivative items, and convert stress deviation into exponentially increasing scores through the Sigmoid function to quantify stress distribution risk.

[0093] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0094] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A control method for an office device with the function of preventing lumbar spine diseases, characterized in that, Includes the following steps: By deploying sensor networks on office chairs and desks, data related to user posture can be collected. The user's sitting posture data is preprocessed, a multi-dimensional health assessment model is constructed based on the preprocessed user sitting posture data, and the health score of the user's current sitting posture is obtained according to the multi-dimensional health assessment model. The system categorizes users' current sitting posture into different levels based on their health scores, and controls the operation of office equipment according to the user's current posture level to guide the user to restore the correct sitting posture.

2. The office device control method as described in claim 1, characterized in that, The specific methods for constructing a multidimensional health assessment model include the following steps: The contact pressure between various parts of the user's body and the office chair is obtained, and a pressure distribution item is obtained based on the contact pressure to quantify the risk of the user's center of gravity shifting in the sitting posture. Obtain the user's actual spinal curvature angle, and based on the actual spinal curvature angle, obtain a static spinal deviation item to assess the static risk of the spinal curvature deviating from the ideal state; The system acquires the user's real-time neck angle and uses this angle to obtain a dynamic neck risk item for capturing the instantaneous risk of sudden neck movement. A multidimensional health assessment model is constructed based on pressure distribution, spinal static deviation, and cervical dynamic risk.

3. The office device control method as described in claim 2, characterized in that, The specific method for obtaining the pressure distribution term includes the following steps: Obtain the ideal distributed pressure, and obtain the pressure distribution deviation that reflects the degree of center of gravity shift in sitting posture based on the contact pressure and the ideal distributed pressure. Based on the Sigmoid function, the pressure distribution deviation is mapped to obtain the pressure distribution term.

4. The office device control method as described in claim 3, characterized in that, The specific method for obtaining the static deviation of the spine includes the following steps: Obtain the ideal curvature angle of the spine, and calculate the absolute deviation of the spinal angle between the ideal curvature angle and the actual curvature angle of the spine. The maximum permissible deviation of the spine is obtained. After normalizing the absolute deviation of the spine angle based on the maximum permissible deviation of the spine, the static deviation term of the spine is obtained.

5. The office device control method as described in claim 4, characterized in that, The specific methods for obtaining dynamic risk items of the neck include the following steps: The rate of change of neck angle is obtained based on the real-time neck angle. Obtain the dynamic risk threshold for the neck, and obtain the dynamic risk item for the neck based on the rate of change of neck angle and the dynamic risk threshold for the neck.

6. An office device control system with a function of preventing lumbar spine diseases, used to implement the office device control method as described in any one of claims 1-5, characterized in that, include: The posture monitoring module is used to collect user posture-related data through a sensor network deployed on office chairs and desks, and transmit the user posture-related data to the central controller. The central controller is used to preprocess user posture-related data, build a multi-dimensional health assessment model based on the preprocessed user posture-related data, obtain the health score of the user's current posture according to the multi-dimensional health assessment model, classify the user's current posture into different levels according to the health score, and control the operation of office equipment according to the user's current posture level to guide the user to restore the correct posture. The mechanical adjustment module is used to respond to the office equipment control commands generated by the central controller and control the operation of the office equipment.

7. The office equipment control system as described in claim 6, characterized in that, The central controller includes: The pressure distribution acquisition module is used to acquire the contact pressure between various parts of the user's body and the office chair, and to acquire pressure distribution items based on the contact pressure to quantify the risk of the user's center of gravity shifting while sitting. The static deviation item acquisition module is used to acquire the user's actual spinal curvature angle and, based on the actual spinal curvature angle, acquire the spinal static deviation item used to assess the static risk of the spinal curvature deviating from the ideal state. The dynamic risk item acquisition module is used to acquire the user's real-time neck angle and acquire dynamic neck risk items based on the real-time neck angle to capture the instantaneous risk of sudden neck movement. The health assessment model building module is used to construct a multi-dimensional health assessment model based on stress distribution items, spinal static deviation items, and cervical dynamic risk items.

8. The office equipment control system as described in claim 7, characterized in that, The pressure distribution item acquisition module includes: The pressure distribution deviation acquisition unit is used to acquire the ideal distribution pressure and to acquire the pressure distribution deviation that reflects the degree of center of gravity shift in the sitting posture based on the contact pressure and the ideal distribution pressure. The pressure distribution mapping unit is used to map the pressure distribution deviation based on the Sigmoid function to obtain the pressure distribution term.

9. The office equipment control system as described in claim 8, characterized in that, The static deviation term acquisition module includes: The absolute angle deviation acquisition unit is used to acquire the ideal curvature angle of the spine and calculate the absolute angle deviation of the spine between the ideal curvature angle and the actual curvature angle of the spine. The absolute deviation normalization processing unit is used to obtain the maximum permissible deviation of the spine. After normalizing the absolute deviation of the spine angle based on the maximum permissible deviation of the spine, the static deviation term of the spine is obtained.

10. The office equipment control system as described in claim 9, characterized in that, The dynamic risk item acquisition module includes: Angle change rate acquisition unit, used to acquire the neck angle change rate based on the real-time neck angle; The dynamic risk item acquisition unit is used to acquire the neck dynamic risk threshold and to acquire the neck dynamic risk item based on the neck angle change rate and the neck dynamic risk threshold.

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