Self-adaptive supporting intelligent office chair system based on dynamic posture perception

Abstract

The invention discloses a self-adaptive supporting intelligent office chair system based on dynamic posture perception. Comprising a multi-source posture sensing module, an intelligent decision-making module and a self-adaptive supporting execution module, and the multi-source posture sensing module is used for continuously collecting sensing data such as pressure distribution, posture change and continuous sitting duration in the sitting process of a user; the intelligent decision-making module performs fusion analysis on the sensing data, identifies the sitting posture state of the user, and constructs a sedentariness risk assessment result for representing the waist load change trend based on the sitting posture state and the sitting duration; the self-adaptive supporting execution module automatically adjusts the supporting state of the supporting part of the office chair according to the sedentariness risk assessment result without active operation of the user, and dynamically intervenes and guides the sitting posture of the user, so that a closed-loop self-adaptive supporting control mechanism based on perception-assessment-execution is formed. The timeliness and pertinence of supporting and adjusting of the office chair can be improved, and the office chair is suitable for long-time office scenes.

Description

Technical Field

[0001] This invention relates to the field of intelligent office furniture technology, and in particular to an adaptive support intelligent office chair system based on dynamic posture perception. Background Technology

[0002] With the continuous improvement of office automation and informatization, prolonged sitting has become a common work style. Office workers often need to maintain a seated posture for several hours at a time during their daily work, resulting in uneven stress on the lower back and causing fatigue, soreness, and other discomfort. To improve the experience of prolonged sitting, various office chair products with adjustable support functions have emerged in the current technology.

[0003] Most existing office chairs provide lumbar, backrest, or seat support through fixed structures or manual adjustments, requiring users to actively adjust the support position and intensity based on their own comfort. However, due to significant differences in body shape among users, and the fact that the same user's posture changes continuously over time during actual use, single or fixed adjustments cannot consistently match the user's real-time posture, easily leading to problems such as insufficient or excessive support.

[0004] To further improve the ease of adjustment, some existing technologies propose to use an electric adjustment structure to drive the lumbar support or backrest. However, such solutions usually still rely on the user to actively trigger the adjustment operation, lacking the ability to perceive changes in the user's sitting posture in real time. They cannot respond in time when the user unconsciously slumps their back, leans forward, or sits for a long time, and the actual use effect is still limited.

[0005] In addition, although some existing technologies have attempted to introduce sensors to collect sitting posture or pressure information, they are mostly limited to monitoring a single parameter and fail to comprehensively analyze multi-dimensional information such as pressure distribution, posture changes and sitting time. They also lack a quantitative assessment mechanism for the trend of lumbar load changes during prolonged sitting, making it difficult to form an effective proactive intervention strategy.

[0006] Therefore, existing office chair technologies generally have the following shortcomings: First, they lack the ability to dynamically and continuously perceive the user's sitting posture, making it difficult to accurately reflect the real state of sitting posture changes over time; second, they lack a systematic assessment mechanism for the risks of prolonged sitting, making it impossible to determine when support adjustment is needed; and third, support adjustment relies heavily on the user's active operation, making it difficult to achieve automatic and continuous posture guidance and intervention, and overall, a closed-loop control system based on the collaborative work of perception, assessment, and execution has not yet been formed.

[0007] Therefore, existing technologies still need to be improved. Summary of the Invention

[0008] In view of the shortcomings of the prior art, this invention provides an adaptive support intelligent office chair system based on dynamic posture perception. By continuously sensing and comprehensively analyzing the user's sitting posture and continuous sitting behavior, the system automatically adjusts the support state of the office chair without the user's active intervention, thereby proactively responding to changes in posture and the risks of prolonged sitting. This technical solution can form a closed-loop support control mechanism based on the collaborative work of perception, evaluation, and execution during natural user use, thereby improving the targeting and continuity of support adjustment and enhancing the user experience in prolonged seated office scenarios.

[0009] The technical solution of the present invention is as follows: This invention provides an adaptive support smart office chair system based on dynamic posture perception, comprising: The multi-source posture sensing module is configured to continuously collect sensing data to characterize the user's sitting posture during the user's sitting process. The sensing data includes at least the pressure distribution data of the seat cushion and / or backrest area, posture angle data reflecting the relative posture change of the chair back, and user continuous sitting time data. The intelligent decision-making module is signal-connected to the multi-source posture perception module and is configured to perform fusion analysis on the perception data, identify the user's current sitting posture, and construct a sedentary risk assessment result based on the sitting posture and continuous sitting time to characterize the trend of lumbar load changes. An adaptive support execution module, connected to the intelligent decision module, is configured to automatically adjust the support state of at least one support part of the office chair based on the sedentary risk assessment results without requiring active user operation, so as to dynamically intervene and guide the user's sitting posture. The multi-source attitude perception module, intelligent decision-making module, and adaptive support execution module work together to form a closed-loop adaptive support control system based on "perception-evaluation-execution".

[0010] In one embodiment, the multi-source posture sensing module includes an array of pressure sensors arranged inside the seat cushion and backrest, used to collect force distribution information of the user's buttocks and back in a spatially distributed manner, and to determine the center of gravity offset characteristics of the user's sitting posture based on the force distribution information.

[0011] In one embodiment, the multi-source attitude sensing module further includes an inertial measurement unit disposed in the chair back structure, used to collect the tilt angle of the chair back and its change information, and to work in conjunction with the pressure distribution information to determine the bending trend of the user's spinal region.

[0012] In one embodiment, the intelligent decision-making module includes a posture state recognition unit, which classifies the user's sitting posture based on the perceived data. The sitting posture state includes at least one or more of the following: standard sitting posture, forward-leaning sitting posture, backward-leaning sitting posture, and slumped sitting posture.

[0013] In one embodiment, the intelligent decision-making module further includes a sedentary risk assessment unit, which is configured to generate a sedentary risk index that reflects the cumulative trend of lumbar load by comprehensively considering the degree of poor posture and the duration of continuous sitting. The sedentary risk index increases with the duration of poor posture.

[0014] In one embodiment, the intelligent decision-making module is configured to compare the sedentary risk index with at least one preset risk threshold, and generate a corresponding adaptive support adjustment instruction when the preset conditions are met, so as to determine the adjustment timing and adjustment range of the adaptive support execution module.

[0015] In one embodiment, the adaptive support execution module includes an adjustable lumbar support assembly having at least vertical and horizontal degrees of freedom and being configured to change its spatial position under the control of the adaptive support adjustment command, thereby providing dynamic support to the user's lumbar region.

[0016] In one embodiment, the adaptive support execution module further includes a zoned controllable support unit disposed inside the seat cushion. The zoned controllable support unit is configured to periodically adjust the support intensity of different areas of the seat cushion when the user is in a prolonged sitting state, so as to cause the center of force on the user's buttocks to shift slowly.

[0017] In one embodiment, the intelligent decision-making module is configured to learn support preference parameters corresponding to different users based on users' historical usage data, and to prioritize the adoption of personalized support control strategies that match the current user in subsequent use.

[0018] In one embodiment, the system further includes a human-computer interaction module configured to output prompts to the user related to sitting posture or the risk of prolonged sitting, and / or receive mode selection instructions from the user for the adaptive support control strategy.

[0019] In summary, this invention, by introducing a technical approach combining multi-source posture sensing, risk assessment, and adaptive support adjustment, transforms the traditional support adjustment method in office chairs, which relies on user subjective feelings and manual operation, into an automatic response mechanism based on objective sitting posture and prolonged sitting behavior. The system continuously senses changes in posture and force during the user's natural sitting process and assesses the trend of lumbar load changes based on continuous sitting time. It proactively adjusts the support status of the support parts without user intervention, thereby dynamically guiding against poor posture and the risks of prolonged sitting. Through the coordinated cooperation between sensing, assessment, and execution, this invention forms a stable and continuous closed-loop adaptive support control method. This not only improves the timeliness and targeting of office chair support adjustment but also provides a support experience that better meets the actual needs of different users in long-term office scenarios, demonstrating good practicality and promotional value.

[0020] Compared with existing office chair solutions that rely on fixed structures or manual adjustments, this invention achieves a fundamental change in the way office chairs are adjusted by constructing a closed-loop adaptive support control mechanism based on multi-source posture perception and prolonged sitting risk assessment, resulting in technical effects that are difficult to predict in the prior art.

[0021] First, this invention does not merely judge and adjust a sitting posture at a single instant. Instead, through continuous collection and fusion analysis of multi-dimensional information such as pressure distribution, posture changes, and continuous sitting duration, it reflects the dynamic process of changes in the user's sitting posture over time, thereby assessing the cumulative trend of lumbar load. This control method based on "changing trends" rather than single-point states allows the system to intervene before poor posture significantly worsens, avoiding the passive mode of "adjusting after discomfort is detected" in existing technologies, and has a significant proactive effect.

[0022] Secondly, this invention introduces the results of a sedentary risk assessment as the trigger for support adjustment, so that support adjustment no longer depends on the user's subjective feelings or operational intentions, but is automatically completed based on objective conditions. The resulting effect is not simply "more convenient," but rather, it achieves continuous and gentle adjustments to the support state without the user's noticeable perception, making the posture guidance process more natural and significantly reducing the interference of frequent or abrupt adjustments on the user experience. This is something that existing solutions, which are mainly based on manual or semi-automatic adjustments, are difficult to achieve.

[0023] Furthermore, this invention combines posture recognition results with sedentary risk assessment, enabling targeted rather than mechanical support adjustments. For example, the system can generate different support adjustment strategies under different sitting postures or different periods of prolonged sitting, thus avoiding the insufficient adaptability problem caused by "uniform parameters and uniform actions" in existing technologies. This method of support adjustment based on state differences ensures that the office chair maintains a good support matching effect when facing different users and the same user at different times, improving the overall applicability of the system.

[0024] Furthermore, this invention establishes a stable closed-loop control without requiring active user intervention, enabling continuous collaboration between perception, evaluation, and execution. This closed-loop mechanism not only improves the timeliness and continuity of support adjustments but also provides the foundation for long-term system optimization based on historical usage, offering technical space for subsequent personalized support control. This comprehensive effect is difficult to anticipate with traditional office chair structures or single-function improvement solutions.

[0025] In summary, this invention is not a simple superposition or replacement of existing office chair support structures or adjustment methods. Instead, by introducing an adaptive control approach centered on risk assessment, it achieves synergistic improvements in aspects such as posture perception depth, adjustment trigger logic, and support guidance methods, thus significantly improving the overall effectiveness of support adjustment technology in sedentary scenarios. Attached Figure Description

[0026] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 A structural block diagram of an adaptive support intelligent office chair system based on dynamic posture perception provided by the present invention; Figure 2 The present invention provides a system structure diagram of a multi-source posture sensing module for an adaptive support intelligent office chair system based on dynamic posture perception. Figure 3 The present invention provides a system structure diagram of the intelligent decision-making module of an adaptive support intelligent office chair system based on dynamic posture perception; Figure 4 The present invention provides a system structure diagram of the adaptive support execution module of an adaptive support intelligent office chair system based on dynamic posture perception; Figure 5 This invention provides an overall system structure diagram of an adaptive support intelligent office chair system based on dynamic posture perception. Detailed Implementation

[0027] To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention is further described in detail below. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The embodiments of the invention are described below in conjunction with the accompanying drawings.

[0028] This invention provides an adaptive support smart office chair system based on dynamic posture perception. Please refer to [link to relevant documentation]. Figures 1-5 ,include: The multi-source posture sensing module 1 is configured to continuously collect sensing data to characterize the user's sitting posture during the user's sitting process. The sensing data includes at least the pressure distribution data of the seat cushion and / or backrest area, the posture angle data reflecting the relative posture change of the chair back, and the user's continuous sitting time data. The intelligent decision-making module 2 is signal-connected to the multi-source posture perception module 1 and is configured to perform fusion analysis on the perception data, identify the user's current sitting posture, and construct a sedentary risk assessment result based on the sitting posture and continuous sitting time to characterize the trend of lumbar load changes. The adaptive support execution module 3 is connected to the intelligent decision module 2 and is configured to automatically adjust the support state of at least one support part of the office chair according to the sedentary risk assessment results without the need for active user operation, so as to dynamically intervene and guide the user's sitting posture. The multi-source attitude perception module 1, the intelligent decision-making module 2, and the adaptive support execution module 3 work together to form a closed-loop adaptive support control system based on "perception-evaluation-execution".

[0029] In one specific embodiment, the adaptive support intelligent office chair system based on dynamic posture perception described in this invention is integrated into the office chair body, and the system is continuously operational during the user's natural sitting and use. The multi-source posture perception module 1 automatically activates after the user sits down, continuously collecting multi-dimensional perception data reflecting the user's posture throughout the sitting process. Specifically, perception units located in the seat cushion and backrest areas acquire the force distribution of the user's buttocks and back at different positions, thus reflecting the user's current center of gravity distribution characteristics. Simultaneously, posture perception units arranged inside the chair back structure collect posture change information of the chair back relative to a reference position, reflecting the tilting trend of the user's body as the sitting posture changes. Furthermore, the system continuously determines whether the user is seated and records the duration of continuous sitting, supplementing the information on changes in posture status over time. Through these methods, the multi-source posture perception module 1 can continuously output perception data characterizing the user's posture without relying on any active user operation.

[0030] The intelligent decision-making module 2 maintains a signal connection with the multi-source posture sensing module 1. After acquiring the sensed data, it fuses the data from different sources. Based on the sensed force distribution characteristics, posture change information, and continuous sitting time, the intelligent decision-making module 2 comprehensively judges the user's current sitting posture, thereby distinguishing whether the user is in a relatively stable sitting posture or has a significant posture deviation. Furthermore, the intelligent decision-making module 2 does not rely solely on the sitting posture at a single moment but combines the changes in the sitting posture during continuous sitting to assess the trend of lumbar load changes, forming an assessment result that reflects the degree of risk associated with prolonged sitting. This assessment result reflects the trend of lumbar load accumulation over time during the current usage phase, providing a basis for subsequent support adjustments.

[0031] The adaptive support execution module 3 maintains a control connection with the intelligent decision-making module 2. Upon receiving an adjustment command generated based on the sedentary risk assessment results, it automatically adjusts at least one support component of the office chair. This adjustment process is completed without any active adjustment by the user, ensuring that the change in support status matches the user's posture and the risk of prolonged sitting. Through dynamic adjustment of the support status of the support components, the adaptive support execution module 3 guides the user's posture, gradually returning the user to a more reasonable support state during continuous sitting, thereby preventing the continuous accumulation of lumbar load under poor posture.

[0032] Through the coordinated operation of the multi-source posture perception module 1, intelligent decision-making module 2, and adaptive support execution module 3, this embodiment forms a closed-loop adaptive support control mechanism based on "perception-evaluation-execution". The system can continuously sense changes in posture, assess the risks of prolonged sitting, and automatically adjust support as the user naturally uses the office chair, allowing the chair's support state to dynamically change according to the user's actual usage, thereby achieving proactive response to posture changes and the risks of prolonged sitting.

[0033] In a further embodiment, the multi-source posture sensing module 1 includes a pressure sensor array disposed inside the seat cushion and backrest, used to collect the force distribution information of the user's buttocks and back in a spatial distribution form, and to determine the center of gravity offset characteristics of the user's sitting posture based on the force distribution information.

[0034] Specifically, in this embodiment, in one specific implementation, the multi-source posture sensing module 1 includes a pressure sensor array deployed inside the seat cushion and backrest of the office chair. The pressure sensor array consists of multiple distributed sensing units, each used to collect pressure information at a corresponding location, thereby forming pressure distribution data reflecting the overall force distribution state of the user's buttocks and back. By analyzing the pressure magnitude and spatial distribution relationship in different areas, the system can obtain the concentrated force area and its changes under the user's current sitting posture, providing basic data support for judging sitting posture.

[0035] In actual use, when the user maintains a relatively standard sitting posture, the pressure distribution collected by the pressure sensor array is usually relatively even. However, when the user leans forward, backward, or shifts their body to the left or right, the pressure values ​​in local areas of the seat cushion and backrest will change significantly. By continuously collecting the above pressure distribution data, the multi-source posture sensing module 1 can reflect the dynamic changes in the force distribution during the user's sitting process and determine the center of gravity shift trend of the user's sitting posture, thereby avoiding errors caused by judging based on single-point pressure data.

[0036] Furthermore, by analyzing the changes in pressure distribution over time, the multi-source posture perception module 1 can distinguish between normal posture adjustments made by users in a short period of time and poor sitting postures maintained for a long period of time, thus enabling subsequent posture recognition and risk assessment based on pressure distribution data to have higher stability and continuity.

[0037] In a further embodiment, the multi-source attitude sensing module 1 further includes an inertial measurement unit disposed in the chair back structure, used to collect the tilt angle of the chair back and its change information, and to work in conjunction with the pressure distribution information to determine the bending trend of the user's spinal region.

[0038] Specifically, in this embodiment, the multi-source posture sensing module 1 further includes an inertial measurement unit disposed inside the chair back structure. The inertial measurement unit is used to collect the tilt angle and its change information of the chair back during user use, supplementing the perceived data of the user's sitting posture from the perspective of posture angle. By monitoring the posture change of the chair back relative to its initial position in real time, the system can obtain posture angle information reflecting the user's posture changes such as leaning forward or backward.

[0039] In this embodiment, the attitude angle data collected by the inertial measurement unit and the pressure distribution data collected by the pressure sensor array are output in parallel and provided to the intelligent decision-making module 2 by the multi-source attitude perception module 1 for subsequent analysis. By co-analyzing the information on the change in chair back posture with the force distribution of the seat cushion and backrest, the system can more accurately distinguish between the posture change caused by the user actively adjusting the chair back angle and the force shift caused by the change in the user's body posture itself, thereby improving the accuracy of the sitting posture judgment.

[0040] Furthermore, by continuously monitoring the trend of posture angle changes collected by the inertial measurement unit, the system can reflect the changes in the curvature trend of the user's spine during sitting. When a user is in a poor sitting posture such as slouching or leaning forward for a long time, the posture angle of the chair back and the pressure distribution often show consistent change characteristics. The multi-source posture perception module 1 continuously outputs the above-mentioned multi-dimensional perception data, providing a more complete and reliable data foundation for the subsequent decision-making process based on posture state recognition and sedentary risk assessment.

[0041] In a further embodiment, the intelligent decision-making module 2 includes a posture state recognition unit, which classifies the user's sitting posture based on the perceived data. The sitting posture state includes at least one or more of the following: standard sitting posture, forward-leaning sitting posture, backward-leaning sitting posture, and slumped sitting posture.

[0042] In this embodiment, the intelligent decision-making module 2 includes a posture state recognition unit. This posture state recognition unit is configured to receive pressure distribution data, posture angle data, and continuous sitting time data collected by the multi-source posture perception module 1, and to preprocess and extract features from the data. In the specific implementation process, the posture state recognition unit first analyzes the force concentration areas and spatial offset of the user's buttocks and back based on the pressure distribution in the seat cushion and backrest areas, thereby obtaining pressure characteristic parameters that can reflect the stability and symmetry of the user's sitting posture. At the same time, combined with the backrest tilt angle and its changing trend collected by the inertial measurement unit in the backrest structure, the posture changes of the user's upper body relative to the backrest are characterized.

[0043] Based on this, the posture recognition unit comprehensively analyzes the pressure feature parameters and posture angle feature parameters, and identifies and classifies the user's current sitting posture according to preset sitting posture judgment rules or trained posture classification models. The sitting posture includes at least one or more of the following: standard sitting posture, forward-leaning sitting posture, backward-leaning sitting posture, and slumped sitting posture. Slumped sitting posture can be determined by a significant decrease in pressure on the lower backrest and a slow change in the backrest angle, while forward-leaning sitting posture can be determined by an increase in pressure at the front edge of the seat cushion and a decrease in the backrest angle. Through this method, the posture recognition unit can continuously and dynamically update the current sitting posture recognition results during the user's natural sitting process, providing a reliable posture basis for subsequent sedentary risk assessment.

[0044] In a further embodiment, the intelligent decision-making module 2 also includes a sedentary risk assessment unit, which is configured to generate a sedentary risk index that reflects the cumulative trend of lumbar load by comprehensively considering the degree of poor posture and the duration of continuous sitting. The sedentary risk index increases with the duration of poor posture.

[0045] More specifically, in this embodiment, the intelligent decision-making module 2 further includes a sedentary risk assessment unit. This unit is configured to, based on the sitting posture results output by the posture recognition unit, further quantify the cumulative risk of lumbar load on the user by considering the user's continuous sitting duration. Specifically, the sedentary risk assessment unit first determines the severity weight of the identified sitting posture. Different sitting postures correspond to different base risk weight values; for example, a standard sitting posture corresponds to a lower weight, while a slumped posture or a prolonged forward-leaning posture corresponds to a higher weight.

[0046] Subsequently, the sedentary risk assessment unit combines the weights of the degree of poor posture with the length of time the user maintains this sitting posture continuously to generate a sedentary risk index that reflects the cumulative trend of lumbar load. The sedentary risk index increases with the duration of poor posture and decreases or resets when the user's posture improves or they briefly leave their seat. By introducing the time dimension of continuous sitting time, frequent misjudgments caused by judging solely based on instantaneous posture are avoided, making the sedentary risk assessment results more consistent with the physiological load changes of users in real-world office scenarios.

[0047] In a further embodiment, the intelligent decision-making module 2 is configured to compare the sedentary risk index with at least one preset risk threshold, and generate a corresponding adaptive support adjustment instruction when the preset conditions are met, so as to determine the adjustment timing and adjustment range of the adaptive support execution module 3.

[0048] Specifically, the intelligent decision-making module 2 is configured to compare the sedentary risk index output by the sedentary risk assessment unit with at least one preset risk threshold to determine whether to trigger adaptive support adjustment. In practice, multiple risk threshold ranges can be preset to distinguish different levels of sedentary risk. When the sedentary risk index does not reach the preset risk threshold, the system maintains the current support state. When the sedentary risk index reaches or exceeds the first risk threshold, the intelligent decision-making module 2 generates an adaptive support adjustment command for prompting or slight adjustment. When the sedentary risk index further reaches a higher risk threshold, an adaptive support adjustment command corresponding to a more significant support adjustment is generated.

[0049] The adaptive support adjustment command includes at least the adjustment trigger timing and adjustment range information. The adjustment trigger timing is used to indicate the time node when the adaptive support execution module 3 starts to perform support adjustment, and the adjustment range is used to limit the intensity range of support adjustment. By comparing the sedentary risk index with a risk threshold in a graded manner, the system can trigger support adjustment step by step and gradually according to the actual degree of change in the user's sedentary risk, thereby avoiding support actions that are too abrupt or frequent, and improving the user's comfort and acceptance during long-term use.

[0050] In a further embodiment, the adaptive support execution module 3 includes an adjustable lumbar support assembly having at least vertical and horizontal adjustment degrees of freedom, and is configured to change its spatial position under the control of the adaptive support adjustment command, thereby providing dynamic support to the user's lumbar region.

[0051] Specifically, the adaptive support execution module 3 includes an adjustable lumbar support assembly, which is disposed inside the backrest of the office chair, located in the area corresponding to the user's lumbar spine. Its structure forms a support relationship with the main body of the backrest that allows for relative movement. The adjustable lumbar support assembly has at least two degrees of freedom of adjustment in the vertical and horizontal directions, wherein the vertical adjustment is used to match the lumbar spine position of users of different heights, and the horizontal adjustment is used to change the degree of fit of the lumbar support.

[0052] In its implementation, the adjustable lumbar support assembly may include a support plate, a drive mechanism, and a guide structure for limiting the range of motion. Upon receiving an adaptive support adjustment command generated by the intelligent decision module 2, the drive mechanism drives the support plate to shift in the corresponding direction, thereby changing the spatial position of the lumbar support assembly relative to the chair back. When the sedentary risk index is in a low range, the lumbar support assembly maintains basic support. When the sedentary risk index reaches a preset risk threshold and a support adjustment command is generated, the lumbar support assembly gradually moves forward or undergoes fine-tuning of its height without causing significant discomfort to the user, thus providing enhanced support to the user's lumbar region.

[0053] In this way, the adjustable lumbar support component can dynamically adjust according to the user's sitting posture and changes in the risk of prolonged sitting without the user's active operation. This transforms the lumbar support from passive, fixed support to active, responsive support, thereby reducing the accumulation of lumbar fatigue caused by prolonged poor sitting posture.

[0054] The adaptive support execution module 3 also includes a zoned controllable support unit disposed inside the seat cushion. The zoned controllable support unit is configured to periodically adjust the support intensity of different areas of the seat cushion when the user is in a prolonged sitting state, so as to cause the center of force on the user's buttocks to shift slowly.

[0055] The adaptive support execution module 3 also includes a zoned controllable support unit disposed inside the seat cushion. The zoned controllable support unit divides the seat cushion into multiple independent support zones along the front-back direction and / or left-right direction. Each support zone can independently adjust its support intensity under the control of the intelligent decision module 2. The zoned controllable support unit can achieve differentiated support for different pressure areas of the user's buttocks by changing the elastic support characteristics or support height of the corresponding zone.

[0056] When a user is in a sedentary state, the intelligent decision-making module 2, based on the sedentary risk index and its changing trend, periodically sends support adjustment commands to the zoned controllable support units. This causes the support intensity of different cushion areas to change slowly according to a preset strategy, thereby prompting the center of pressure on the user's buttocks to shift between the various support areas. This shift process is continuous and gradual, avoiding significant disturbance to the user caused by abrupt changes in support status, while effectively alleviating discomfort caused by prolonged pressure on localized areas.

[0057] By introducing zoned controllable support units that work in conjunction with adjustable lumbar support components, the office chair can achieve dynamic intervention in the lateral force distribution level on the basis of longitudinal lumbar support adjustment. This creates a multi-dimensional adaptive support system covering the lumbar spine and hip area, improving the overall comfort and health support effect of the system in long-term seated office scenarios.

[0058] In a further embodiment, the intelligent decision-making module 2 is configured to learn support preference parameters corresponding to different users based on users' historical usage data, and to prioritize the adoption of personalized support control strategies that match the current user in subsequent use.

[0059] Specifically, the intelligent decision-making module 2 is configured to learn and update support preference parameters for different users based on historical usage data during long-term user operation. The historical usage data includes at least information such as the adjustment trigger frequency and adjustment amplitude of the adaptive support execution module 3 under different sitting postures, as well as the duration of continuous sitting after adjustment. Through statistical analysis of the aforementioned historical data, the intelligent decision-making module 2 can extract user preferences for support intensity and adjustment rhythm.

[0060] In its implementation, when the system identifies the same user sitting down again, the intelligent decision-making module 2 prioritizes calling the support preference parameters matched to that user. It then adjusts the relationship between the prolonged sitting risk index and preset risk thresholds, for example, fine-tuning the risk threshold that triggers support adjustment or individually limiting the rate of change in support adjustment amplitude. Through this approach, different users can obtain support responses that better suit their body type and usage habits when using the same office chair system, avoiding over- or under-support caused by a uniform control strategy. This improves the system's adaptability and comfort in multi-user scenarios.

[0061] In a further embodiment, the system further includes a human-computer interaction module 4, which is configured to output prompt information related to sitting posture or the risk of prolonged sitting to the user, and / or receive mode selection instructions from the user for the adaptive support control strategy.

[0062] The system also includes a human-computer interaction module 4, which is communicatively connected to the intelligent decision-making module 2. The human-computer interaction module 4 is configured to output prompts to the user related to the current sitting posture or the risk of prolonged sitting, and / or receive user commands for selecting modes of the adaptive support control strategy. The prompts may take at least one form, such as visual, tactile, or auditory, to provide appropriate posture reminders or health tips as the risk of prolonged sitting gradually accumulates.

[0063] In its implementation, the human-computer interaction module 4 can provide multiple support control modes for users to choose from, such as a conservative, gentle support mode or a more proactive, enhanced support mode. After the user inputs the corresponding mode selection command through the human-computer interaction module 4, the intelligent decision-making module 2 adjusts the support adjustment strategy according to the selected mode. By introducing the human-computer interaction module 4, the system maintains its automated and adaptive support adjustment capabilities while preserving the user's right to know and choose the support behavior, thereby increasing the user's acceptance and trust in the system for long-term use.

[0064] In summary, this invention introduces a system architecture combining multi-source posture sensing, intelligent decision-making, and adaptive support execution into an office chair. This allows the chair to continuously sense changes in posture and assess the risk of prolonged sitting during natural user use, dynamically adjusting the lumbar and seat cushion support without requiring active user intervention. The system uses the user's actual sitting posture as input and the results of the prolonged sitting risk assessment as the basis for decision-making. Through the coordinated operation of the adjustable lumbar support component and the zoned controllable support unit, it achieves proactive intervention and guidance of the user's posture.

[0065] Meanwhile, by learning from users' historical usage data and cooperating with the human-computer interaction module, the system maintains its automated support and adjustment capabilities while taking into account individual differences and usage preferences among different users. This allows it to develop a support strategy that better meets user needs over long-term use. The above technical solution improves the support response in prolonged seated office scenarios without increasing the user's operational burden, enhancing the overall performance of office chairs in terms of comfort, adaptability, and health support. It demonstrates good engineering feasibility and application value.

[0066] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A dynamically posture-aware based adaptive support intelligent office chair system, characterized in that, The method comprises the following steps: A multi-source posture perception module is configured to continuously collect perception data for representing the user's sitting posture during the user's sitting process, the perception data at least including pressure distribution data of the seat cushion and / or the backrest area, posture angle data reflecting the relative posture change of the chair back, and continuous sitting duration data of the user; An intelligent decision module is in signal connection with the multi-source posture perception module and is configured to perform fusion analysis on the perception data, identify the user's current sitting posture, and construct a sedentary risk assessment result for representing the waist load change trend based on the sitting posture and the continuous sitting duration; An adaptive support execution module is in control connection with the intelligent decision module and is configured to automatically adjust the support state of at least one support part of the office chair based on the sedentary risk assessment result without the user's active operation, so as to dynamically intervene and guide the user's sitting posture. The multi-source posture perception module, the intelligent decision module, and the adaptive support execution module cooperatively constitute a closed-loop adaptive support control system based on "perception-evaluation-execution".

2. The self-adapting support intelligent office chair system according to claim 1, wherein, The multi-source posture perception module comprises a pressure sensor array arranged in the seat cushion and the backrest, which is used to collect the force distribution information of the user's hips and back in a spatial distribution form, and determine the center of gravity deviation characteristics of the user's sitting posture based on the force distribution information.

3. The self-adapting support intelligent office chair system according to claim 1 or 2, characterized in that, The multi-source posture perception module further comprises an inertial measurement unit arranged in the chair back structure, which is used to collect the inclination angle and change information of the chair back, and cooperates with the pressure distribution information to determine the bending trend of the user's spine region.

4. The self-adapting support intelligent office chair system according to any one of claims 1 to 3, characterized in that, The intelligent decision module comprises a posture state recognition unit, which classifies the user's sitting posture based on the perception data, and the sitting posture at least includes one or more of a standard sitting posture, a forward-leaning sitting posture, a backward-leaning sitting posture, and a hunched sitting posture.

5. The self-adapting support intelligent office chair system according to claim 4, wherein, The intelligent decision module further comprises a sedentary risk assessment unit, which is configured to generate a sedentary risk index reflecting the cumulative trend of the waist load by comprehensively considering the adverse degree corresponding to the user's sitting posture and the continuous sitting duration, and the sedentary risk index increases with the increase of the continuous time of the adverse sitting posture.

6. The self-adapting support intelligent office chair system according to claim 5, wherein, The intelligent decision module is configured to compare the sedentary risk index with at least one preset risk threshold, and generate a corresponding adaptive support adjustment instruction when the preset condition is met, so as to determine the adjustment time and adjustment amplitude of the adaptive support execution module.

7. The self-adapting support intelligent office chair system according to any one of claims 1 to 6, wherein, The adaptive support execution module comprises an adjustable lumbar support assembly, which has at least adjustment degrees in the upward-downward direction and the forward-backward direction, and is configured to change its spatial position under the control of the adaptive support adjustment instruction, thereby providing dynamic support for the user's lumbar region.

8. The self-adapting support intelligent office chair system according to any one of claims 1 to 7, characterized in that, The adaptive support execution module further comprises a partition controllable support unit arranged in the seat cushion, which is configured to periodically adjust the support strength of different seat cushion regions when the user is in a sedentary state, so as to cause the force center of the user's hips to slowly migrate.

9. The self-adapting support intelligent office chair system according to any one of claims 1 to 8, wherein, The intelligent decision module is configured to learn support preference parameters corresponding to different users based on user historical use data, and to preferentially adopt a personalized support control strategy matching the current user in a subsequent use process.

10. The self-adapting support intelligent office chair system according to any one of claims 1 to 9, wherein, The system further comprises a human-computer interaction module configured to output prompt information related to a sitting posture state or a sedentary risk to a user, and / or receive a mode selection instruction of the adaptive support control strategy from the user.

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