Office chair self-adapting adjustment method and system based on ergonomics data

Abstract

This invention relates to the field of adaptive control technology and proposes an adaptive adjustment method and system for office chairs based on ergonomic data. The method includes: acquiring initial human contact characteristic data; matching initial adjustment parameters from a preset adjustment strategy library, the initial adjustment parameters including seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters, and using the initial adjustment parameters as the first output; extracting pressure distribution characteristic indicators from a dynamic pressure distribution sequence, comparing the pressure distribution characteristic indicators with the corresponding thresholds of a preset standard pressure distribution template, and determining whether the current support state meets the preset ergonomic support requirements; when the determination result is that the ergonomic support requirements are not met, generating compensation adjustment parameters based on the deviation between the pressure distribution characteristic indicators and the corresponding thresholds of the standard pressure distribution template, and using the compensation adjustment parameters as the second output to complete the final adjustment; this invention can improve the efficiency of adaptive adjustment of office chairs.

Description

Technical Field

[0001] This invention relates to the field of adaptive control technology, and in particular to an adaptive adjustment method and system for office chairs based on ergonomic data. Background Technology

[0002] Existing office chair adjustment methods only preset a limited number of positions to achieve a single adjustment process for the longitudinal displacement of the seat cushion and the tilt angle of the backrest. During the operation of the equipment, it does not collect data on the distribution of the reference points of the buttocks in the seat cushion area and the contour shape of the back contact surface in the backrest area after the user sits down in real time. It cannot fully capture the unique sitting posture characteristics of different users. The adjustment parameters output by the fixed positions cannot adapt to the differentiated contact shapes of the buttocks and backs of various groups of people. After the initial adjustment of the chair, there are obvious individual adaptation defects in the support and fit of the seat cushion and backrest to the human torso.

[0003] The existing office chair adjustment logic only performs one round of parameter output operation and then ends the adjustment process. It does not collect dynamic pressure distribution information of the seat cushion and backrest after the initial adjustment. It cannot extract support status characteristics such as pressure center offset, effective contact area, and pressure gradient. It lacks a step to compare and verify the actual pressure characteristics with the standard ergonomic support template. It cannot actively identify the working condition of unbalanced pressure distribution in the support area, nor does it have a closed-loop adjustment mechanism to generate compensatory adjustment actions based on pressure deviation. As a result, the ergonomic support effect of the chair is difficult to consistently meet the standards during long-term use. Summary of the Invention

[0004] This invention provides an adaptive adjustment method and system for office chairs based on ergonomic data to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides an adaptive adjustment method for office chairs based on ergonomic data, comprising: Pt.1. Obtain the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface; Pt.2. Based on the buttock reference point position information and the back contact surface contour feature information, match the corresponding initial adjustment parameters from the preset adjustment strategy library. The initial adjustment parameters include seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters. Use the initial adjustment parameters as the first output. Pt.3. Obtain the dynamic pressure distribution sequence after the first output action, extract pressure distribution feature indicators from the dynamic pressure distribution sequence, compare the pressure distribution feature indicators with the corresponding threshold of the preset standard pressure distribution template, and determine whether the current support state meets the preset ergonomic support requirements based on the comparison result. Pt.4 When the judgment result is that the ergonomic support requirements are not met, a compensation adjustment parameter is generated based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template. The compensation adjustment parameter is used as the second output to complete the final adjustment.

[0006] In a preferred embodiment, the acquisition of the user's initial human body contact feature data, which includes hip reference point location information and back contact surface contour feature information, includes: Obtain the buttock reference point position information, which includes the position of the pressure extreme point and the position of the pressure center point in the seat area when the user is seated. The pressure extreme point position and the pressure center point position together determine the buttock reference point position information. Extract back contact surface contour feature information, which includes the longitudinal contact depth distribution and contact surface morphology features of the backrest area when the user is seated. The longitudinal contact depth distribution and the contact surface morphology features together determine the back contact surface contour feature information. The position information of the buttock reference point is fused with the contour feature information of the back contact surface to form the initial human body contact feature data.

[0007] In a preferred embodiment, acquiring the user's initial human contact characteristic data further includes: In response to the seat's activation signal, the contact pressure field distribution of the buttock seating area is captured via the seat cushion partition. Deformation characteristic parameters and pressure transmission characteristic parameters of the seat cushion area are extracted from the contact pressure field distribution. The position information of the buttock reference point is determined by the deformation characteristic parameters and the pressure transmission characteristic parameters. The contact depth field distribution of the back seat area is captured by backrest partitioning. The load distribution boundary and contact curvature change features of the backrest area are extracted from the contact depth field distribution. The back contact surface contour feature information is determined by the load distribution boundary and the contact curvature change features. The initial human contact feature data of the seat are obtained by spatiotemporally associating the position information of the buttock reference point with the contour feature information of the back contact surface.

[0008] In a preferred embodiment, the step of matching corresponding initial adjustment parameters from a preset adjustment strategy library based on the hip reference point position information and the back contact surface contour feature information includes: Based on the spatial orientation relationship between the extreme pressure point and the center pressure point in the hip reference point location information, a hip posture feature vector is constructed. The hip posture feature vector is used to characterize the user's hip sitting orientation features. Based on the longitudinal contact depth distribution and contact surface morphology features in the back contact surface contour feature information, a back posture feature vector is constructed, which is used to characterize the user's back leaning morphology features. The buttocks posture feature vector and the back posture feature vector are concatenated to generate a comprehensive posture feature vector; Using the comprehensive body posture feature vector as the query index of the strategy library, the matching target strategy entry is located in the preset adjustment strategy library. The strategy entry is associated with a corresponding body posture feature interval and adjustment parameter group. The adjustment parameter group includes seat cushion longitudinal displacement parameter and backrest tilt angle adjustment parameter. The seat cushion longitudinal displacement parameter and the backrest tilt angle adjustment parameter in the adjustment parameter group are used together as the initial adjustment parameters.

[0009] In a preferred embodiment, the step of using the initial adjustment parameter as the first output includes: The initial adjustment parameters are deconstructed to separate the seat cushion longitudinal displacement parameter and the backrest tilt angle adjustment parameter. The longitudinal displacement parameters of the seat cushion are assigned a longitudinal displacement physical semantic, which represents the displacement value of the seat cushion in the longitudinal direction. The backrest tilt angle adjustment parameters are assigned tilt angle adjustment physical semantics, which characterize the tilt angle value of the backrest relative to the vertical direction; The longitudinal displacement parameters of the seat cushion and the tilt angle adjustment parameters of the backrest are serialized according to the output data format to obtain the first output.

[0010] In a preferred embodiment, obtaining the dynamic pressure distribution sequence after the first output action and extracting pressure distribution feature indicators from the dynamic pressure distribution sequence includes: The dynamic pressure distribution sequence is decomposed along a time axis to determine that the dynamic pressure distribution sequence consists of pressure frames of the seat area and pressure frames of the backrest area arranged along the time axis, and each pressure frame contains the regional pressure distribution of the corresponding area. Features are extracted from the pressure distribution in the region to obtain pressure distribution characteristic indicators, which include pressure center offset, contact area distribution parameters, and contact pressure gradient variation amplitude.

[0011] In a preferred embodiment, comparing the pressure distribution characteristic index with the corresponding threshold of a preset standard pressure distribution template, and determining whether the current support state meets the preset ergonomic support requirements based on the comparison result, includes: A threshold space decomposition is performed on a preset standard pressure distribution template to separate template threshold sequences corresponding to each sub-index in the pressure distribution feature index. The pressure distribution characteristic index is dimensionally split, and the actual distribution values ​​of the pressure center offset characterization quantity, contact area distribution parameter, and contact pressure gradient change amplitude are extracted from the pressure distribution characteristic index. The actual distribution value is compared with the judgment boundary value in the template threshold sequence to establish a correspondence between the actual distribution value and the judgment boundary value on a per-index dimension. The feature comparison process includes identifying the deviation direction and degree between each actual distribution value and the corresponding judgment boundary value. A state-space decision is made on the feature comparison results. When all the actual distribution values ​​are within the compliance range defined by the decision boundary value, a support requirement compliance signal is output. When the actual distribution value of any indicator dimension is outside the compliance range defined by the judgment boundary value, a support requirement failure signal is output.

[0012] In a preferred embodiment, generating compensation adjustment parameters based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template, and using the compensation adjustment parameters as a second output, includes: Based on the dimensions of each sub-indicator in the pressure distribution characteristic index, the deviation amount is decomposed into a deviation vector to obtain a deviation component sequence. The deviation component sequence includes the deviation direction indicator and the deviation degree value in each dimension. The deviation values ​​in the deviation component sequence are mapped to compensation values, and the deviation values ​​are converted into compensation adjustment components in that dimension according to a preset compensation mapping relationship. The compensation mapping relationship is used to map the deviation values ​​to the compensation adjustment amplitude of the corresponding dimension. The compensation adjustment components are integrated according to the original dimensional arrangement order of each sub-index in the pressure distribution characteristic index to generate compensation adjustment parameters, which include compensation adjustment sub-parameters corresponding to each dimension. The compensation adjustment parameters are encapsulated according to the output data format to generate a second output.

[0013] In a preferred embodiment, the step of using the compensation adjustment parameter as a second output to complete the final adjustment includes: The compensation adjustment parameters and the adjustment object identifiers corresponding to each compensation adjustment sub-parameter are recovered from the second output. The adjustment object identifiers are used to indicate the adjustment object to which each compensation adjustment sub-parameter acts. The compensation adjustment sub-parameters are mapped and latched with the adjustment object identifier to generate a mapping latch relationship sequence, which contains the corresponding mapping between each compensation adjustment sub-parameter and its adjustment object; According to the mapping latch relationship sequence, the ready verification of each compensation adjustment sub-parameter is performed to confirm that each compensation adjustment sub-parameter has completed the process of being extracted from the second output and mapped to its adjustment object identifier, and a compensation adjustment ready signal corresponding to each adjustment object is generated. Collect all the aforementioned compensation adjustment ready signals, perform comprehensive arbitration on all the aforementioned compensation adjustment ready signals, and generate the final adjustment completion signal.

[0014] To address the above problems, the present invention also provides an adaptive adjustment system for office chairs based on ergonomic data, the system comprising: The feature acquisition module is used to acquire the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface. The initial parameter matching module is used to match the corresponding initial adjustment parameters from the preset adjustment strategy library based on the buttock reference point position information and the back contact surface contour feature information. The initial adjustment parameters include seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters, and the initial adjustment parameters are used as the first output. The pressure judgment module is used to obtain the dynamic pressure distribution sequence after the first output action, extract pressure distribution feature indicators from the dynamic pressure distribution sequence, compare the pressure distribution feature indicators with the corresponding threshold of the preset standard pressure distribution template, and determine whether the current support state meets the preset ergonomic support requirements based on the comparison result. The compensation parameter adjustment module is used to generate compensation adjustment parameters based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template when the judgment result is that the ergonomic support requirements are not met. The compensation adjustment parameters are then used as the second output to complete the final adjustment.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention can simultaneously collect the complete buttock reference point position information of the seat cushion area and the back contact surface contour feature information of the backrest area when seated. After performing feature fusion and spatiotemporal correlation processing on the two types of raw contact data, a unique comprehensive body posture feature vector is constructed. This feature vector is used as a retrieval index to retrieve the matching initial adjustment parameters of the seat cushion longitudinal displacement and backrest tilt angle in the adjustment strategy library. After completing parameter serialization, standardized control commands are output. Relying on the initial adjustment logic that conforms to the user's own body shape characteristics, the basic position and tilt angle of the seat cushion and backrest can match the individual's unique buttock pressure point and back contact surface, establishing a highly adapted basic fit relationship between the seat support structure and the human torso from the initial adjustment stage.

[0016] 2. This invention establishes a closed-loop adaptive control logic that runs from beginning to end. It continuously collects the continuous dynamic pressure distribution sequence generated by the seat cushion and backrest after the initial adjustment. It decomposes and purifies the time-series pressure frames to obtain multi-dimensional pressure distribution feature indicators such as pressure center offset, contact area, and pressure gradient. It compares all feature indicators with the built-in threshold of the standard pressure distribution template to complete the support status judgment. For the support substandard working conditions, it performs vector decomposition of the pressure deviation and maps it to generate corresponding compensation adjustment parameters. After encapsulating the compensation parameters, it sends out to execute a secondary fine-tuning action to continuously correct the force distribution of the seat support surface. Throughout the process, the pressure on the buttocks and back is evenly distributed, and the balanced support effect that meets the ergonomic judgment standard is stably maintained. Attached Figure Description

[0017] Figure 1 A flowchart illustrating an embodiment of the adaptive adjustment method for an office chair based on ergonomic data provided by the present invention; Figure 2 A functional block diagram of an office chair adaptive adjustment system based on ergonomic data provided in an embodiment of the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0018] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0019] This application provides an adaptive adjustment method for office chairs based on ergonomic data. The executing entity of this ergonomic data-based adaptive adjustment method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the ergonomic data-based adaptive adjustment method for office chairs can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0020] Reference Figure 1 The diagram shown is a flowchart illustrating an adaptive adjustment method for an office chair based on ergonomic data, according to an embodiment of the present invention. In this embodiment, the adaptive adjustment method for an office chair based on ergonomic data includes: Pt.1. Obtain the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface; In this embodiment of the invention, the acquisition of the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface, includes: Obtain the buttock reference point position information, which includes the position of the pressure extreme point and the position of the pressure center point in the seat area when the user is seated. The pressure extreme point position and the pressure center point position together determine the buttock reference point position information. Extract back contact surface contour feature information, which includes the longitudinal contact depth distribution and contact surface morphology features of the backrest area when the user is seated. The longitudinal contact depth distribution and the contact surface morphology features together determine the back contact surface contour feature information. The position information of the buttock reference point is fused with the contour feature information of the back contact surface to form the initial human body contact feature data.

[0021] The acquisition of the user's initial human contact characteristic data also includes: In response to the seat's activation signal, the contact pressure field distribution of the buttock seating area is captured via the seat cushion partition. Deformation characteristic parameters and pressure transmission characteristic parameters of the seat cushion area are extracted from the contact pressure field distribution. The position information of the buttock reference point is determined by the deformation characteristic parameters and the pressure transmission characteristic parameters. The contact depth field distribution of the back seat area is captured by backrest partitioning. The load distribution boundary and contact curvature change features of the backrest area are extracted from the contact depth field distribution. The back contact surface contour feature information is determined by the load distribution boundary and the contact curvature change features. The initial human contact feature data of the seat are obtained by spatiotemporally associating the position information of the buttock reference point with the contour feature information of the back contact surface.

[0022] After the seat receives the ready signal generated by the device startup, the built-in sensing unit of the seat cushion continuously collects all the pressure field data generated in the entire area of ​​the seat cushion when the user is fully seated. After the collection is completed, the point with the highest pressure value is locked as the pressure extreme point. Then, the pressure coverage of all sensing points of the seat cushion is taken as the complete statistical range. The pressure data collected from all points are integrated to delineate the central area of ​​concentrated pressure distribution. The coordinates of the center point of this area are the pressure center point location.

[0023] The coordinates of the sensor points corresponding to the locked pressure extreme point and the coordinates of the sensor points corresponding to the pressure center point are uniformly stored in the same set of data storage units. The complete set of coordinate data is fixedly named the buttock reference point position information.

[0024] The backrest is equipped with a built-in depth sensing unit that synchronously collects the contact surface indentation depth values ​​corresponding to each vertical height of the backrest when the user is fully leaning back. A set of contact depth values ​​is recorded at fixed standard height intervals along the vertical direction of the backrest. The depth values ​​corresponding to all heights are summarized to form the longitudinal contact depth distribution. The data of the boundary range of contact between all sensing points of the backrest and the human back, as well as the point data corresponding to the surface undulation changes, are collected simultaneously. All boundary and surface point data are integrated to form the contact surface morphology characteristics.

[0025] The complete set of numerical data on longitudinal contact depth distribution and the complete set of point data on contact surface morphology are collected and stored in the same independent data storage unit. The complete set of backrest data collected in this group is fixedly named as back contact surface contour feature information.

[0026] The complete set of coordinate data of the buttock reference point position information and the complete set of sensor data of the back contact surface contour feature information are retrieved from the storage unit. All point information contained in the two types of data is processed in a unified format. The standard for the processing is to uniformly adopt the coordinate recording specification preset by the seat sensor hardware at the factory. After the format is completed, the two types of data are merged and stored in the same total storage data package. The integrated total storage data package is fixedly named the initial human body contact feature data.

[0027] After the seat control motherboard receives the seat start signal generated by the hardware trigger, all pressure sensing units inside the seat cushion section start synchronously and continuously collect data. The collection period is uniformly set to the factory-preset 50-millisecond single collection interval. The real-time pressure values ​​of all sensing points on the seat cushion surface are completely recorded. All pressure values ​​are integrated and summarized to generate a complete pressure field distribution of the buttocks seating area.

[0028] The pressure values ​​recorded at each sensing point within the contact pressure field distribution are compared with the unloaded reference pressure value of the cushion when there is no human contact. Based on the recorded values ​​of the sensing points deviating from the unloaded reference after being pressed, the range of points corresponding to the indentation and expansion of the cushion material is recorded. All indentation and expansion points are summarized to form the deformation characteristic parameters of the cushion area. Based on the pressure value transmission changes between adjacent sensing points along the horizontal and vertical plane of the cushion, the coverage range of pressure transmission between the points is recorded. All transmission coverage points are summarized to form the pressure transmission characteristic parameters of the cushion area.

[0029] The complete set of data points for deformation characteristic parameters of the seat area and pressure transmission characteristic parameters of the seat area are stored in the same independent storage unit. The complete set of data integrated in this storage unit is fixedly named the buttock reference point location information.

[0030] All depth sensing units within the backrest partition simultaneously activate continuous data acquisition at fixed 50-millisecond intervals, fully recording the indentation depth values ​​generated by the human backrest when leaning against all sensing points in the vertical and horizontal directions of the backrest. The depth values ​​of all points are then aggregated to generate a complete contact depth field distribution of the backrest seating area.

[0031] All sensor points with depth values ​​greater than the no-load zero contact depth threshold of 0.2 mm within the contact depth field distribution are defined as effective contact points on the human back. The outer boundary points of all effective contact points are integrated and collected to form the load distribution boundary of the backrest area. The indentation depth difference corresponding to all sensor points in each segment is extracted sequentially at a fixed 1 cm vertical interval along the backrest. All segmented depth difference values ​​are recorded, summarized, and collected to form the contact curvature change characteristics of the backrest area.

[0032] The complete set of data points on the load distribution boundary of the backrest area, the contact curvature variation characteristics of the backrest area, and the complete set of depth difference data are stored in the same independent storage unit. The complete set of data integrated in this storage unit is fixedly named the back contact surface contour feature information.

[0033] The complete hip reference point position information and back contact surface contour feature information are retrieved from the storage unit. The 50-millisecond acquisition timestamp of the two types of data is used as the association matching benchmark. The hip point data and back depth point data generated under the same timestamp are bound and stored one by one. After binding, they are uniformly converted into the standard coordinate storage format preset by the seat sensing system. After binding and format unification, the spatiotemporal association processing is completed. The complete set of integrated data generated after spatiotemporal association processing is fixedly named as the initial human body contact feature data of the seat.

[0034] Pt.2. Based on the buttock reference point position information and the back contact surface contour feature information, match the corresponding initial adjustment parameters from the preset adjustment strategy library. The initial adjustment parameters include seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters. Use the initial adjustment parameters as the first output. In this embodiment of the invention, the step of matching corresponding initial adjustment parameters from a preset adjustment strategy library based on the hip reference point position information and the back contact surface contour feature information includes: Based on the spatial orientation relationship between the extreme pressure point and the center pressure point in the hip reference point location information, a hip posture feature vector is constructed. The hip posture feature vector is used to characterize the user's hip sitting orientation features. Based on the longitudinal contact depth distribution and contact surface morphology features in the back contact surface contour feature information, a back posture feature vector is constructed, which is used to characterize the user's back leaning morphology features. The buttocks posture feature vector and the back posture feature vector are concatenated to generate a comprehensive posture feature vector; Using the comprehensive body posture feature vector as the query index of the strategy library, the matching target strategy entry is located in the preset adjustment strategy library. The strategy entry is associated with a corresponding body posture feature interval and adjustment parameter group. The adjustment parameter group includes seat cushion longitudinal displacement parameter and backrest tilt angle adjustment parameter. The seat cushion longitudinal displacement parameter and the backrest tilt angle adjustment parameter in the adjustment parameter group are used together as the initial adjustment parameters.

[0035] The step of using the initial adjustment parameter as the first output includes: The initial adjustment parameters are deconstructed to separate the seat cushion longitudinal displacement parameter and the backrest tilt angle adjustment parameter. The longitudinal displacement parameters of the seat cushion are assigned a longitudinal displacement physical semantic, which represents the displacement value of the seat cushion in the longitudinal direction. The backrest tilt angle adjustment parameters are assigned tilt angle adjustment physical semantics, which characterize the tilt angle value of the backrest relative to the vertical direction; The longitudinal displacement parameters of the seat cushion and the tilt angle adjustment parameters of the backrest are serialized according to the output data format to obtain the first output.

[0036] The complete buttock reference point position information is retrieved from the storage unit. The sensor coordinate points corresponding to the extreme pressure points and the pressure center points are separated. The global coordinate system preset by the cushion sensing hardware is used as the spatial orientation determination reference. The horizontal and vertical interval values ​​of the two sets of coordinate points are recorded. The two sets of interval values ​​and the relative orientation information of the points are entered into a dedicated data storage queue in a fixed storage order according to the system. The complete content recorded in this queue is fixedly named the buttock posture feature vector. The buttock posture feature vector fully carries the buttock orientation features after the user sits down.

[0037] Retrieve complete back contact surface contour feature information from the storage unit, and separate the longitudinal contact depth distribution into all segmented depth recording data and the contact surface morphology feature of all boundary surface point recording data. The depth values ​​and effective contact boundary point coordinates collected in 1 cm longitudinal segments of the backrest are entered into a dedicated data storage queue in a fixed entry order. The complete record content of this queue is fixedly named the back posture feature vector. The back posture feature vector fully carries the back posture features when the user leans against it.

[0038] Retrieve the dedicated data storage queues for the buttocks posture feature vector and the back posture feature vector, and follow the system's preset fixed splicing order of first entering all the contents of the buttocks queue and then entering all the contents of the back queue. Continuously integrate all the recorded data in the two queues into the same new storage queue, and name the newly integrated storage queue "Comprehensive Posture Feature Vector".

[0039] The entire record content in the comprehensive body feature vector storage queue is used as the unified query index standard. All stored entries in the preset adjustment strategy library in the local storage device are traversed line by line. Each target strategy entry in the adjustment strategy library is pre-bound with a fixed range of body feature intervals and a matching adjustment parameter group. During the traversal, the fixed threshold for matching is that all records of the comprehensive body feature vector completely fall into a single body feature interval. After the retrieval is completed, the only set of content that completely meets the judgment conditions is locked as the target strategy entry.

[0040] The control data corresponding to the longitudinal displacement of the seat cushion and the control data corresponding to the backrest tilt angle are extracted from the built-in matching adjustment parameter group of the target strategy entry. The two sets of split control data are uniformly stored in the same output storage unit. The complete set of control data stored in this unit is fixedly named the initial adjustment parameter.

[0041] Read the initial adjustment parameters stored in the storage unit as a whole, and complete the parameter deconstruction operation according to the data splitting and separation mark preset by the system as the distinction benchmark. Based on the fixed data belonging range corresponding to the separation mark, separate the complete data segment of seat cushion longitudinal displacement parameter and the complete data segment of backrest tilt angle adjustment parameter from the initial adjustment parameters. After the two types of data segments are split, they are stored in two independent temporary storage partitions respectively.

[0042] Retrieve the complete data segment of the longitudinal displacement parameter of the seat cushion and bind it to the preset longitudinal displacement physical semantic identifier of the seat hardware control system. This identifier is uniformly matched with the millimeter measurement standard corresponding to the forward and backward movement hardware travel scale of the seat cushion. After the longitudinal displacement physical semantic binding is completed, the range of hardware execution travel corresponding to the longitudinal displacement value of the seat cushion carried by the longitudinal displacement parameter can be clearly interpreted.

[0043] Retrieve the complete data segment of the backrest tilt angle adjustment parameters and bind it to the preset tilt angle adjustment physical semantic identifier of the seat hardware control system. This identifier is uniformly matched with the angle measurement standard corresponding to the vertical zero angle reference of the backrest rotation mechanism. After the tilt angle adjustment physical semantic binding is completed, the hardware rotation travel range corresponding to the tilt angle value of the backrest relative to the vertical direction carried by the backrest tilt angle adjustment parameters can be clearly interpreted.

[0044] The system retrieves the semantically bound seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters. Following the system's preset output data format, it first enters the complete data of the seat cushion longitudinal displacement parameters and then enters the complete data of the backrest tilt angle adjustment parameters to complete the parameter serialization process. The standardized complete set of transmission data packets generated after serialization is fixedly named as the first output.

[0045] Pt.3. Obtain the dynamic pressure distribution sequence after the first output action, extract pressure distribution feature indicators from the dynamic pressure distribution sequence, compare the pressure distribution feature indicators with the corresponding threshold of the preset standard pressure distribution template, and determine whether the current support state meets the preset ergonomic support requirements based on the comparison result. In this embodiment of the invention, obtaining the dynamic pressure distribution sequence after the first output action and extracting pressure distribution feature indicators from the dynamic pressure distribution sequence includes: The dynamic pressure distribution sequence is decomposed along a time axis to determine that the dynamic pressure distribution sequence consists of pressure frames of the seat area and pressure frames of the backrest area arranged along the time axis, and each pressure frame contains the regional pressure distribution of the corresponding area. Features are extracted from the pressure distribution in the region to obtain pressure distribution characteristic indicators, which include pressure center offset, contact area distribution parameters, and contact pressure gradient variation amplitude.

[0046] The step of comparing the pressure distribution characteristic index with the corresponding threshold of a preset standard pressure distribution template, and determining whether the current support state meets the preset ergonomic support requirements based on the comparison result, includes: A threshold space decomposition is performed on a preset standard pressure distribution template to separate template threshold sequences corresponding to each sub-index in the pressure distribution feature index. The pressure distribution characteristic index is dimensionally split, and the actual distribution values ​​of the pressure center offset characterization quantity, contact area distribution parameter, and contact pressure gradient change amplitude are extracted from the pressure distribution characteristic index. The actual distribution value is compared with the judgment boundary value in the template threshold sequence to establish a correspondence between the actual distribution value and the judgment boundary value on a per-index dimension. The feature comparison process includes identifying the deviation direction and degree between each actual distribution value and the corresponding judgment boundary value. A state-space decision is made on the feature comparison results. When all the actual distribution values ​​are within the compliance range defined by the decision boundary value, a support requirement compliance signal is output. When the actual distribution value of any indicator dimension is outside the compliance range defined by the judgment boundary value, a support requirement failure signal is output.

[0047] After the seat actuator fully executes all the internal control commands of the first output and completes the hardware adjustment actions of the seat cushion longitudinal displacement and backrest tilt angle, the seat cushion and backrest partition pressure sensing units continuously collect pressure data according to the hardware preset 50-millisecond acquisition interval. All time-series pressure acquisition data packets are uniformly summarized and stored to form a dynamic pressure distribution sequence.

[0048] The complete stored dynamic pressure distribution sequence is retrieved. The 50-millisecond acquisition timestamp of the data packet within the sequence is used as the time axis decomposition judgment benchmark. All data packets are split according to the inherent arrangement order of the timestamps from smallest to largest. After splitting, each group of independent time-series data packets is fixedly defined as a pressure frame. All pressure frames are divided into two groups for storage according to the acquisition time: seat area pressure frames and backrest area pressure frames. Each group of seat area pressure frames completely contains the real-time pressure record content of the sensor points throughout the seat area. Each group of backrest area pressure frames completely contains the real-time pressure record content of the sensor points throughout the backrest area. The total pressure record content contained in a single pressure frame is fixedly named as the area pressure distribution.

[0049] The complete sensor point records of regional pressure distribution stored in each group of seat cushion area pressure frames and backrest area pressure frames are retrieved in sequence. All effective pressure sensor points are screened using the system's preset no-load pressure of 0 Pa as the effective contact judgment threshold. Based on the selected effective point coordinate records, the coordinates of the current human body force center point are locked. The coordinate difference between this coordinate and the standard force center point coordinate of the seat is recorded. This difference record is fixedly named the pressure center offset characterization quantity.

[0050] The total number of sensor points within the statistical area pressure distribution that meet the effective contact judgment threshold of 0 Pa is used to calculate the effective contact range between the human body and the seat by combining the fixed standard collection area of ​​a single sensor unit. This range record is fixedly named the contact area distribution parameter.

[0051] Pressure values ​​corresponding to adjacent sensing points are extracted sequentially from fixed interval points along the horizontal and vertical sides of the seat cushion and fixed interval points along the vertical segments of the backrest. The difference between pressure values ​​between adjacent points is recorded completely. All segmented differences are summarized to form a complete set of records, which is fixedly named the contact pressure gradient change amplitude.

[0052] The pressure center offset, contact area distribution parameters, and contact pressure gradient change amplitude extracted from the same time-series pressure frame are uniformly stored in the same independent storage unit. The complete set of integrated records in this unit is fixedly named as pressure distribution characteristic index.

[0053] Retrieve the complete standard pressure distribution template pre-stored in the local storage device, classify and store it according to the three categories of sub-indicators preset in the template to complete the threshold space decomposition operation, and extract the complete set of boundary record data matching the pressure center offset characterization quantity, contact area distribution parameter, and contact pressure gradient change amplitude according to the partition identifier built into the template. The complete set of boundary record data corresponding to each category of sub-indicators is stored independently to form a unique template threshold sequence.

[0054] Retrieve complete pressure distribution characteristic indicators from the storage unit, and perform dimensional splitting operation according to the three types of sub-indicators preset by the system. Based on the data belonging range defined by the splitting indicator, extract complete records of coordinate difference corresponding to pressure center offset, complete records of effective contact range corresponding to contact area distribution parameter, and complete records of point pressure difference corresponding to contact pressure gradient change amplitude. The extracted records of the three types are uniformly named as the actual distribution value of the corresponding sub-indicator.

[0055] Retrieve the actual distribution value corresponding to the same sub-index and all judgment boundary values ​​within the template threshold sequence. Use the pre-set lower and upper judgment boundary values ​​within the template threshold sequence as a unified comparison benchmark. Complete the comparison record of the actual distribution value of a single sub-index with the judgment boundary value of the same category one by one. During the comparison, mark the coordinates or numerical orientation of the actual distribution value relative to the lower and upper judgment boundary values ​​as the deviation direction. Record the complete difference between the actual distribution value and the two judgment boundary values ​​as the degree of deviation. Establish a binding correspondence between the actual distribution value and the corresponding judgment boundary value for each sub-index independently. Complete the feature comparison operation of all three sub-indexes.

[0056] After collecting all three types of sub-indicators and completing feature comparison, the binding correspondence records generated are used to carry out state space judgment operations. The judgment conditions are uniformly set as follows: the actual distribution value of the pressure center offset characterization quantity falls within the upper and lower judgment boundary value range of the corresponding template threshold sequence; the actual distribution value of the contact area distribution parameter falls within the upper and lower judgment boundary value range of the corresponding template threshold sequence; and the actual distribution value of the contact pressure gradient change amplitude falls within the upper and lower judgment boundary value range of the corresponding template threshold sequence. When all three types of sub-indicators meet the judgment conditions, the hardware control unit generates a support requirement compliance signal in a fixed level format and transmits it to the seat adjustment execution module.

[0057] After collecting all three types of sub-indicators and completing feature comparison, the binding correspondence records generated are used to carry out state space judgment operations. The judgment conditions are uniformly set as follows: the actual distribution value of the pressure center offset characterization quantity falls within the upper and lower judgment boundary value range of the corresponding template threshold sequence; the actual distribution value of the contact area distribution parameter falls within the upper and lower judgment boundary value range of the corresponding template threshold sequence; and the actual distribution value of the contact pressure gradient change amplitude falls within the upper and lower judgment boundary value range of the corresponding template threshold sequence. If any type of sub-indicator fails to meet the judgment condition, the hardware control unit generates a support requirement non-compliance signal that is different from the standard signal level format and transmits it to the seat compensation adjustment control module.

[0058] Pt.4 When the judgment result is that the ergonomic support requirements are not met, a compensation adjustment parameter is generated based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template. The compensation adjustment parameter is used as the second output to complete the final adjustment.

[0059] In this embodiment of the invention, the step of generating a compensation adjustment parameter based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template, and using the compensation adjustment parameter as a second output, includes: Based on the dimensions of each sub-indicator in the pressure distribution characteristic index, the deviation amount is decomposed into a deviation vector to obtain a deviation component sequence. The deviation component sequence includes the deviation direction indicator and the deviation degree value in each dimension. The deviation values ​​in the deviation component sequence are mapped to compensation values, and the deviation values ​​are converted into compensation adjustment components in that dimension according to a preset compensation mapping relationship. The compensation mapping relationship is used to map the deviation values ​​to the compensation adjustment amplitude of the corresponding dimension. The compensation adjustment components are integrated according to the original dimensional arrangement order of each sub-index in the pressure distribution characteristic index to generate compensation adjustment parameters, which include compensation adjustment sub-parameters corresponding to each dimension. The compensation adjustment parameters are encapsulated according to the output data format to generate a second output.

[0060] The step of using the compensation adjustment parameter as a second output to complete the final adjustment includes: The compensation adjustment parameters and the adjustment object identifiers corresponding to each compensation adjustment sub-parameter are recovered from the second output. The adjustment object identifiers are used to indicate the adjustment object to which each compensation adjustment sub-parameter acts. The compensation adjustment sub-parameters are mapped and latched with the adjustment object identifier to generate a mapping latch relationship sequence, which contains the corresponding mapping between each compensation adjustment sub-parameter and its adjustment object; According to the mapping latch relationship sequence, the ready verification of each compensation adjustment sub-parameter is performed to confirm that each compensation adjustment sub-parameter has completed the process of being extracted from the second output and mapped to its adjustment object identifier, and a compensation adjustment ready signal corresponding to each adjustment object is generated. Collect all the aforementioned compensation adjustment ready signals, perform comprehensive arbitration on all the aforementioned compensation adjustment ready signals, and generate the final adjustment completion signal.

[0061] Retrieve the complete deviation records corresponding to all sub-indicators, and divide them into three independent dimensions based on the pressure center offset, contact area distribution parameters, and contact pressure gradient change amplitude. Separately split the corresponding deviation records according to each independent dimension. During the splitting process, simultaneously enter the deviation direction identifier and complete deviation degree value matched for that dimension. After all dimensions are split, store them in a unified and orderly manner to form a set of records. This set of orderly records is fixedly named the deviation component sequence.

[0062] The complete deviation component sequence is retrieved from the storage unit. The deviation value carried by each record in the sequence is read line by line. The pre-fixed compensation mapping relationship lookup table in the local storage is retrieved. The deviation value of each fixed interval in the lookup table is bound to a specific compensation adjustment amplitude. The matching criterion is that the deviation value falls completely into a single fixed interval in the lookup table. The compensation adjustment amplitude corresponding to this dimension is retrieved. After the retrieval and matching are completed, a single-dimensional matching adjustment record is generated. This single-dimensional matching adjustment record is fixedly named compensation adjustment component.

[0063] Retrieve all the compensation and adjustment components generated across all dimensions. Following the original dimensional arrangement order of storing the pressure distribution characteristic indicators, first store the data corresponding to the pressure center offset, then the data corresponding to the contact area distribution parameters, and finally the data corresponding to the contact pressure gradient change amplitude. Then, sequentially store all the compensation and adjustment components into the same independent storage partition. After storage, the complete set of records within the partition is uniformly divided into three independent sub-items. Each independent sub-item is fixedly named the compensation and adjustment sub-parameter, and the complete set of data formed by integrating all sub-items is fixedly named the compensation and adjustment parameter.

[0064] Retrieve the complete stored compensation adjustment parameters, read the standard output data format specification preset by the seat transmission link. The specification stipulates that the seat cushion longitudinal compensation data and backrest tilt angle compensation data have fixed segmentation identifiers and storage order. According to the specification, add segmentation identifiers to all compensation adjustment sub-parameters inside the compensation adjustment parameters and sort them in a unified manner. After the sorting is completed, package it into a set of standardized transmission data packets. The packaged standardized transmission data packets are fixedly named the second output.

[0065] The second output transmission data packet, which is fully encapsulated within the storage link, is retrieved. Based on the preset data segmentation identifier inside the data packet, the data packet encapsulation structure is disassembled layer by layer. From the disassembled data packet, the complete record content of all compensation adjustment sub-parameters is separated one by one. Simultaneously, the adjustment object identifier bound to each compensation adjustment sub-parameter is extracted. The adjustment object identifier has two types of fixed character codes built in: seat cushion longitudinal actuator and backrest tilt actuator. The encoded content can accurately point to the adjustment object that the corresponding compensation adjustment sub-parameter needs to drive.

[0066] The complete record of a single set of compensation adjustment sub-parameters and its corresponding extracted adjustment object code identifier are stored in the same set of binding storage units. All bound units are arranged in the order of the original dimensions of the sub-indicators and stored in a unified storage queue. This ordered storage queue completely records the one-to-one binding content of all compensation adjustment sub-parameters and adjustment object identifiers. This queue is fixedly named the mapping latch relationship sequence.

[0067] Each group of bound storage units within the mapping latch relationship sequence is read one by one. The unit is checked to see if it simultaneously stores complete and unmissing compensation adjustment sub-parameter records and corresponding adjustment object identification codes. The verification criteria are set as complete extraction of compensation adjustment sub-parameters and no missing characters in the adjustment object identification code. When a single group of bound units meets the criteria, the seat control main board generates a dedicated fixed-level compensation adjustment ready signal. Each type of adjustment object independently generates a dedicated compensation adjustment ready signal and caches it separately in the signal storage partition.

[0068] The system retrieves all dedicated compensation adjustment ready signals for the adjustment objects cached in the signal storage partition. The comprehensive arbitration judgment standard is set so that the compensation adjustment ready signals corresponding to the seat cushion longitudinal actuator and the compensation adjustment ready signals corresponding to the backrest tilt actuator are simultaneously in an effective level state. After all signals meet the effective level judgment standard, the seat control motherboard outputs a final adjustment completion signal in a unified level format. The final adjustment completion signal is sent to all actuators of the seat, and the entire adaptive adjustment process is completed.

[0069] like Figure 2 The diagram shown is a functional block diagram of an office chair adaptive adjustment system based on ergonomic data provided in an embodiment of the present invention.

[0070] The ergonomic data-based adaptive adjustment system for office chairs described in this invention can be installed in electronic devices. Depending on the functions implemented, the ergonomic data-based adaptive adjustment system may include a feature acquisition module, an initial parameter matching module, a pressure optimization module, and a compensation parameter adjustment module. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and perform a fixed function, stored in the memory of the electronic device.

[0071] In this embodiment, the functions of each module / unit are as follows: The feature acquisition module is used to acquire the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface. The initial parameter matching module is used to match the corresponding initial adjustment parameters from the preset adjustment strategy library based on the buttock reference point position information and the back contact surface contour feature information. The initial adjustment parameters include seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters, and the initial adjustment parameters are used as the first output. The pressure judgment module is used to obtain the dynamic pressure distribution sequence after the first output action, extract pressure distribution feature indicators from the dynamic pressure distribution sequence, compare the pressure distribution feature indicators with the corresponding threshold of the preset standard pressure distribution template, and determine whether the current support state meets the preset ergonomic support requirements based on the comparison result. The compensation parameter adjustment module is used to generate compensation adjustment parameters based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template when the judgment result is that the ergonomic support requirements are not met. The compensation adjustment parameters are then used as the second output to complete the final adjustment.

[0072] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0073] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0074] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0075] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0076] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An adaptive adjustment method for office chairs based on ergonomic data, characterized in that: The method includes: Pt.

1. Obtain the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface; Pt.

2. Based on the buttock reference point position information and the back contact surface contour feature information, match the corresponding initial adjustment parameters from the preset adjustment strategy library. The initial adjustment parameters include seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters. Use the initial adjustment parameters as the first output. Pt.

3. Obtain the dynamic pressure distribution sequence after the first output action, extract pressure distribution feature indicators from the dynamic pressure distribution sequence, compare the pressure distribution feature indicators with the corresponding threshold of the preset standard pressure distribution template, and determine whether the current support state meets the preset ergonomic support requirements based on the comparison result. Pt.4 When the judgment result is that the ergonomic support requirements are not met, a compensation adjustment parameter is generated based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template. The compensation adjustment parameter is used as the second output to complete the final adjustment.

2. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 1, characterized in that, The initial human body contact feature data of the user is obtained, which includes the position information of the buttock reference point and the contour feature information of the back contact surface, including: Obtain the buttock reference point position information, which includes the position of the pressure extreme point and the position of the pressure center point in the seat area when the user is seated. The pressure extreme point position and the pressure center point position together determine the buttock reference point position information. Extract back contact surface contour feature information, which includes the longitudinal contact depth distribution and contact surface morphology features of the backrest area when the user is seated. The longitudinal contact depth distribution and the contact surface morphology features together determine the back contact surface contour feature information. The position information of the buttock reference point is fused with the contour feature information of the back contact surface to form the initial human body contact feature data.

3. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 2, characterized in that, The acquisition of the user's initial human contact characteristic data also includes: In response to the seat's activation signal, the contact pressure field distribution of the buttock seating area is captured via the seat cushion partition. Deformation characteristic parameters and pressure transmission characteristic parameters of the seat cushion area are extracted from the contact pressure field distribution. The position information of the buttock reference point is determined by the deformation characteristic parameters and the pressure transmission characteristic parameters. The contact depth field distribution of the back seat area is captured by backrest partitioning. The load distribution boundary and contact curvature change features of the backrest area are extracted from the contact depth field distribution. The back contact surface contour feature information is determined by the load distribution boundary and the contact curvature change features. The initial human contact feature data of the seat are obtained by spatiotemporally associating the position information of the buttock reference point with the contour feature information of the back contact surface.

4. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 1, characterized in that, The step of matching corresponding initial adjustment parameters from a preset adjustment strategy library based on the hip reference point position information and the back contact surface contour feature information includes: Based on the spatial orientation relationship between the extreme pressure point and the center pressure point in the hip reference point location information, a hip posture feature vector is constructed. The hip posture feature vector is used to characterize the user's hip sitting orientation features. Based on the longitudinal contact depth distribution and contact surface morphology features in the back contact surface contour feature information, a back posture feature vector is constructed, which is used to characterize the user's back leaning morphology features. The buttocks posture feature vector and the back posture feature vector are concatenated to generate a comprehensive posture feature vector; Using the comprehensive body posture feature vector as the query index of the strategy library, the matching target strategy entry is located in the preset adjustment strategy library. The strategy entry is associated with a corresponding body posture feature interval and adjustment parameter group. The adjustment parameter group includes seat cushion longitudinal displacement parameter and backrest tilt angle adjustment parameter. The seat cushion longitudinal displacement parameter and the backrest tilt angle adjustment parameter in the adjustment parameter group are used together as the initial adjustment parameters.

5. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 4, characterized in that, The step of using the initial adjustment parameter as the first output includes: The initial adjustment parameters are deconstructed to separate the seat cushion longitudinal displacement parameter and the backrest tilt angle adjustment parameter. The longitudinal displacement parameters of the seat cushion are assigned a longitudinal displacement physical semantic, which represents the displacement value of the seat cushion in the longitudinal direction. The backrest tilt angle adjustment parameters are assigned tilt angle adjustment physical semantics, which characterize the tilt angle value of the backrest relative to the vertical direction; The longitudinal displacement parameters of the seat cushion and the tilt angle adjustment parameters of the backrest are serialized according to the output data format to obtain the first output.

6. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 1, characterized in that, The step of obtaining the dynamic pressure distribution sequence after the first output action, and extracting pressure distribution feature indicators from the dynamic pressure distribution sequence, includes: The dynamic pressure distribution sequence is decomposed along a time axis to determine that the dynamic pressure distribution sequence consists of pressure frames of the seat area and pressure frames of the backrest area arranged along the time axis, and each pressure frame contains the regional pressure distribution of the corresponding area. Features are extracted from the pressure distribution in the region to obtain pressure distribution characteristic indicators, which include pressure center offset, contact area distribution parameters, and contact pressure gradient variation amplitude.

7. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 6, characterized in that, The step of comparing the pressure distribution characteristic index with the corresponding threshold of a preset standard pressure distribution template, and determining whether the current support state meets the preset ergonomic support requirements based on the comparison result, includes: A threshold space decomposition is performed on a preset standard pressure distribution template to separate template threshold sequences corresponding to each sub-index in the pressure distribution feature index. The pressure distribution characteristic index is dimensionally split, and the actual distribution values ​​of the pressure center offset characterization quantity, contact area distribution parameter, and contact pressure gradient change amplitude are extracted from the pressure distribution characteristic index. The actual distribution value is compared with the judgment boundary value in the template threshold sequence to establish a correspondence between the actual distribution value and the judgment boundary value on a per-index dimension. The feature comparison process includes identifying the deviation direction and degree between each actual distribution value and the corresponding judgment boundary value. A state-space decision is made on the feature comparison results. When all the actual distribution values ​​are within the compliance range defined by the decision boundary value, a support requirement compliance signal is output. When the actual distribution value of any indicator dimension is outside the compliance range defined by the judgment boundary value, a support requirement failure signal is output.

8. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 1, characterized in that, The step of generating compensation adjustment parameters based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template, and using the compensation adjustment parameters as a second output, includes: Based on the dimensions of each sub-indicator in the pressure distribution characteristic index, the deviation amount is decomposed into a deviation vector to obtain a deviation component sequence. The deviation component sequence includes the deviation direction indicator and the deviation degree value in each dimension. The deviation values ​​in the deviation component sequence are mapped to compensation values, and the deviation values ​​are converted into compensation adjustment components in that dimension according to a preset compensation mapping relationship. The compensation mapping relationship is used to map the deviation values ​​to the compensation adjustment amplitude of the corresponding dimension. The compensation adjustment components are integrated according to the original dimensional arrangement order of each sub-index in the pressure distribution characteristic index to generate compensation adjustment parameters, which include compensation adjustment sub-parameters corresponding to each dimension. The compensation adjustment parameters are encapsulated according to the output data format to generate a second output.

9. The adaptive adjustment method for office chairs based on ergonomic data as described in claim 8, characterized in that, The step of using the compensation adjustment parameter as a second output to complete the final adjustment includes: The compensation adjustment parameters and the adjustment object identifiers corresponding to each compensation adjustment sub-parameter are recovered from the second output. The adjustment object identifiers are used to indicate the adjustment object to which each compensation adjustment sub-parameter acts. The compensation adjustment sub-parameters are mapped and latched with the adjustment object identifier to generate a mapping latch relationship sequence, which contains the corresponding mapping between each compensation adjustment sub-parameter and its adjustment object; According to the mapping latch relationship sequence, the ready verification of each compensation adjustment sub-parameter is performed to confirm that each compensation adjustment sub-parameter has completed the process of being extracted from the second output and mapped to its adjustment object identifier, and a compensation adjustment ready signal corresponding to each adjustment object is generated. Collect all the aforementioned compensation adjustment ready signals, perform comprehensive arbitration on all the aforementioned compensation adjustment ready signals, and generate the final adjustment completion signal.

10. An office chair adaptive adjustment system based on ergonomic data, characterized in that: For implementing the ergonomic data-based adaptive adjustment method for office chairs as described in claim 1, the system comprises: The feature acquisition module is used to acquire the user's initial human body contact feature data, which includes the position information of the buttock reference point and the contour feature information of the back contact surface. The initial parameter matching module is used to match the corresponding initial adjustment parameters from the preset adjustment strategy library based on the buttock reference point position information and the back contact surface contour feature information. The initial adjustment parameters include seat cushion longitudinal displacement parameters and backrest tilt angle adjustment parameters, and the initial adjustment parameters are used as the first output. The pressure judgment module is used to obtain the dynamic pressure distribution sequence after the first output action, extract pressure distribution feature indicators from the dynamic pressure distribution sequence, compare the pressure distribution feature indicators with the corresponding threshold of the preset standard pressure distribution template, and determine whether the current support state meets the preset ergonomic support requirements based on the comparison result. The compensation parameter adjustment module is used to generate compensation adjustment parameters based on the deviation between the pressure distribution characteristic index and the corresponding threshold of the standard pressure distribution template when the judgment result is that the ergonomic support requirements are not met. The compensation adjustment parameters are then used as the second output to complete the final adjustment.

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