A method and system for adaptive control of electric wheelchair seat posture and road conditions

Abstract

The present application relates to electric wheelchair control technology, specifically, to a method and system for adaptively controlling the posture of an electric wheelchair seat according to road conditions. The method comprises: receiving a first control instruction for entering a specific posture maintenance mode; responding to the first control instruction, obtaining the current posture parameters of the electric wheelchair seat, and storing the current posture parameters as target posture parameters; monitoring disturbance parameters, which are changes in the posture parameters caused by uneven road surfaces during the electric wheelchair's travel; determining the range of the disturbance parameters, and maintaining the target posture parameters if the disturbance parameters are less than a preset disturbance suppression threshold corresponding to the specific posture maintenance mode. The method has the advantages of effectively maintaining the specific target posture set by the user, avoiding unexpected posture adjustments caused by minor road disturbances, reducing interference to the user, and improving the user experience in specific scenarios.

Description

Technical Field

[0001] The present application relates to the technical field of electric wheelchairs, and more specifically, to a method and system for adaptively controlling the seat posture and road conditions of an electric wheelchair. Background Art

[0002] As a critical assistive tool for individuals with limited mobility, electric wheelchairs are designed to provide greater autonomy and ride quality. However, in certain situations, electric wheelchair users may seek more than just universal ride comfort or postural adaptability under normal road conditions. For example, a user with a specific medical condition, such as hip or spinal surgery, may be required to maintain a specific, precisely defined body position for extended periods during the recovery period to promote wound healing or reduce pressure on specific areas. This specific body position may differ from a conventional "comfortable" sitting position but is crucial to the user's recovery goals. Alternatively, the user may have a chronic medical condition, such as a high risk of pressure ulcers, requiring the seat to maintain a position that maximizes pressure distribution across specific areas. Alternatively, the user may rely on wheelchair-mounted life support or assistive therapy devices (e.g., certain types of portable ventilators, whose tubing connections and device stability require a strict upper body position), requiring the user to maintain a relatively fixed body position and angle for proper operation.

[0003] Electric wheelchairs provide important support for people with limited mobility. However, certain health needs require users to maintain a precisely defined posture for extended periods of time, such as for postoperative recovery, pressure ulcer prevention, or to ensure the operation of assistive devices. Existing posture adaptive control systems often automatically adjust the seat posture based on general comfort algorithms when faced with minor indoor road disturbances. This can easily interfere with the user's specific posture settings, leading to discomfort, treatment disruption, or frequent manual adjustments. Enabling the system to recognize and prioritize the user's proactively set target posture has become a pressing technical challenge. Summary of the Invention

[0004] The purpose of this application is to provide an electric wheelchair seat posture road condition adaptive control method and system, which has the advantages of being able to effectively maintain the specific target posture set by the user, avoid unexpected posture adjustments caused by minor road disturbances, reduce interference to the user, and improve the user experience in specific scenarios.

[0005] In a first aspect, the present application provides a method for adaptively controlling the posture of an electric wheelchair seat according to road conditions, the method comprising:

[0006] receiving a first control instruction for entering a specific posture maintaining mode;

[0007] In response to the first control instruction, obtaining current posture parameters of the electric wheelchair seat, and storing the current posture parameters as target posture parameters;

[0008] Monitor disturbance parameters, which are changes in the posture parameters of the electric wheelchair caused by uneven road surfaces during driving;

[0009] The range of the disturbance parameter is determined. If the disturbance parameter is less than a preset disturbance suppression threshold corresponding to a specific posture maintenance mode, the target posture parameter is maintained.

[0010] Through the above solution, the specific target posture set by the user can be effectively maintained, unexpected posture adjustments caused by minor road disturbances can be avoided, interference to the user can be reduced, and the user experience in specific scenarios can be improved.

[0011] Furthermore, the present application also proposes that the disturbance parameter includes a first disturbance parameter and a second disturbance parameter, and the disturbance suppression threshold includes a first disturbance suppression threshold and a second disturbance suppression threshold;

[0012] Determine the range of the disturbance parameter. If the disturbance parameter is less than a preset disturbance suppression threshold corresponding to a specific posture maintenance mode, maintain the target posture parameter, including:

[0013] comparing the first disturbance parameter with a first disturbance rejection threshold, and comparing the second disturbance parameter with a second disturbance rejection threshold;

[0014] When the first disturbance parameter is less than a first disturbance suppression threshold, and the second disturbance parameter is less than a second disturbance suppression threshold, determining a combined disturbance risk level according to the first disturbance parameter and the second disturbance parameter;

[0015] The combined disturbance risk level is determined by comparing it with the preset risk level threshold. If the combined disturbance risk level is less than the risk level threshold, the target posture parameters are maintained.

[0016] Through the above scheme, the precision and accuracy of posture maintenance judgment are improved by introducing multiple disturbance parameters and combined risk level judgment.

[0017] Furthermore, the present application also proposes that the combined disturbance risk level is determined according to the first disturbance parameter and the second disturbance parameter, including:

[0018] Acquire adjustment information of a target posture characteristic corresponding to the target posture parameter, where the adjustment information represents, under the corresponding target posture parameter, an influence weight of the first disturbance parameter and the second disturbance parameter corresponding to posture stability or a user tolerance parameter to a combined disturbance risk level;

[0019] According to the adjustment information, respectively combining the first disturbance parameter and the second disturbance parameter to generate an adjusted disturbance factor adjusted by the impact weight or the tolerance parameter;

[0020] Based on the adjusted disturbance factor, determine the combined disturbance risk level.

[0021] Through the above scheme, the differences in the impact of target posture characteristics on different disturbance parameters or user tolerance are taken into account, making the risk level assessment more in line with actual needs.

[0022] Furthermore, the present application also proposes to obtain adjustment information of the target posture characteristics corresponding to the target posture parameters, where the adjustment information represents that under the corresponding target posture parameters, the first disturbance parameter and the second disturbance parameter respectively correspond to the influence weight of the posture stability or the user's tolerance parameter to the combined disturbance risk level, including:

[0023] Determining whether the target posture characteristic is associated with a preset specific physiological state identifier specified by the user;

[0024] If the target posture characteristic is associated with a specific physiological state identifier specified by the user, retrieving a preset baseline tolerance parameter corresponding to the specific physiological state identifier;

[0025] Adjustment information is generated according to a preset benchmark tolerance parameter, and the adjustment information is used to characterize the influence weight of the first disturbance parameter and the second disturbance parameter on the posture stability under the target posture or the user's tolerance parameter to the combined disturbance risk level.

[0026] Through the above scheme, the user's specific physiological state is associated with the adjustment information, so that the posture maintenance strategy can better adapt to the user's individual needs.

[0027] Furthermore, the present application also proposes generating adjustment information according to a preset baseline tolerance parameter, including:

[0028] Obtaining a first adjustment parameter determined by a preset reference tolerance parameter, the first adjustment parameter representing a minimum allowable tolerance level determined by the preset reference tolerance parameter;

[0029] Determining a second adjustment parameter according to the target posture characteristic, where the second adjustment parameter represents the influence of the target posture characteristic on the disturbance adaptability;

[0030] When there is a difference between the tolerance level represented by the first adjustment parameter and the disturbance adaptability represented by the second adjustment parameter, the first adjustment parameter and the second adjustment parameter are adjusted in combination according to the preset integration rule to generate adjustment information. The adjustment information reflects the comprehensive needs of the user under a specific physiological state and target posture characteristics, and the tolerance level determined by the adjustment information is not lower than the minimum allowable tolerance level.

[0031] Through the above scheme, the minimum tolerance level determined by the user's physiological state and the impact of the target posture characteristics on disturbance adaptability are comprehensively considered to generate adjustment information that more comprehensively reflects user needs.

[0032] Furthermore, the present application also proposes that, according to a preset integration rule, the first adjustment parameter and the second adjustment parameter are combined for adjustment to generate adjustment information, including:

[0033] Obtaining weight information corresponding to the first adjustment parameter and the second adjustment parameter in the integration rule;

[0034] A combination operation is performed on the first adjustment parameter and the second adjustment parameter according to the configuration weight information to generate adjustment information.

[0035] Through the above solution, a specific method of generating adjustment information through combination operation is provided, which improves the operability of the solution.

[0036] Furthermore, the present application also proposes that, based on the configuration weight information, a first adjustment parameter and a second adjustment parameter are combined and calculated to generate adjustment information, including:

[0037] Performing a weighted sum or weighted average operation on the first adjustment parameter and the second adjustment parameter according to the configuration weight information to obtain a preliminary combination result;

[0038] Determine whether the tolerance level determined by the preliminary combination results is lower than the preset minimum allowable tolerance level;

[0039] If the tolerance level determined by the preliminary combined result is lower than the minimum permissible tolerance level, the preliminary combined result is revised to the minimum permissible tolerance level to generate adjustment information;

[0040] If the tolerance level determined by the preliminary combination result is not lower than the preset minimum allowable tolerance level, the preliminary combination result is used as adjustment information.

[0041] Through the above scheme, a specific algorithm for weighted combination is provided, and it is ensured that the tolerance level determined by the final adjustment information is not lower than the minimum requirement, thereby ensuring the basic safety and comfort of users.

[0042] Furthermore, the present application also proposes that obtaining configuration weight information corresponding to the first adjustment parameter and the second adjustment parameter in the integration rule includes:

[0043] Obtaining preset priority definitions corresponding to the first adjustment parameter and the second adjustment parameter respectively from the integration rule;

[0044] According to the priority definition, first weight information corresponding to the first adjustment parameter and second weight information corresponding to the second adjustment parameter are obtained by the integration rule, and the first weight information and the second weight information reflect the priority determined by the priority definition.

[0045] Through the above scheme, the weights are determined by defining the priorities, which makes the generation process of the adjustment information more flexible and intelligent, and can reflect the importance of different factors.

[0046] Furthermore, the present application also proposes that, according to the priority definition, first weight information corresponding to the first adjustment parameter and second weight information corresponding to the second adjustment parameter are obtained by the integration rule, and the first weight information and the second weight information reflect the priority determined by the priority definition, including:

[0047] Based on the obtained priority definition, the first weight information and the second weight information are determined through the preset priority weight mapping mechanism. The preset priority weight mapping mechanism is used to convert the priority definition into the first weight information and the second weight information, so that the first weight information and the second weight information reflect the priority determined by the priority definition.

[0048] Through the above scheme, a specific implementation method for determining weights through a priority weight mapping mechanism is provided, thereby enhancing the feasibility of the scheme.

[0049] In a second aspect, the present application further proposes an electric wheelchair seat posture adaptive control system for implementing the above-mentioned electric wheelchair seat posture road condition adaptive control method, the system comprising:

[0050] An instruction receiving module, configured to receive a first control instruction for entering a specific posture maintaining mode;

[0051] a target posture setting module, configured to respond to the first control instruction, obtain the current posture parameters of the electric wheelchair seat, and store the current posture parameters as target posture parameters;

[0052] The disturbance monitoring module is used to monitor the disturbance parameters, which are the changes in the posture parameters of the electric wheelchair caused by uneven road surface during driving;

[0053] The attitude control module is used to determine the range of the disturbance parameter and maintain the target attitude parameter if the disturbance parameter is less than the preset disturbance suppression threshold corresponding to the specific attitude maintenance mode.

[0054] Through the above solution, a system for implementing the above method is provided, which provides a hardware or software carrier for solving technical problems.

[0055] From the above, it can be seen that the present application provides an electric wheelchair seat posture road condition adaptive control method and system, which can effectively maintain the specific target posture set by the user by monitoring the disturbance in a specific mode and judging whether it is less than a threshold value, avoiding unexpected posture adjustments caused by minor road disturbances, reducing interference to the user, and improving the user experience in specific scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 A flowchart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions is provided in one embodiment of the present application.

[0057] Figure 2 This is one of the flow charts of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0058] Figure 3 This is a second flow chart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0059] Figure 4 This is a third flow chart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0060] Figure 5 This is a fourth flow chart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0061] Figure 6 This is a fifth flow chart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0062] Figure 7 This is a sixth flow chart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0063] Figure 8 This is a seventh flow chart of a method for adaptively controlling the seat posture of an electric wheelchair according to road conditions provided in another embodiment of the present application.

[0064] Figure 9 FIG8 is a flow chart of an electric wheelchair seat posture adaptive road condition control method provided in another embodiment of the present application.

[0065] Figure 10 A flowchart of a control system for adaptively controlling the seat posture of an electric wheelchair according to road conditions is provided in another embodiment of the present application. DETAILED DESCRIPTION

[0066] The technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The components of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for which protection is claimed, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0067] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0068] During the research process, the present applicant discovered that conventional existing electric wheelchair seat posture adaptive road condition control systems, when responding to changes in body posture caused by uneven road surfaces, are generally designed to improve ride comfort or enhance normal driving stability by adjusting the seat posture. However, in specific scenarios where the user has precisely adjusted the seat to a target posture due to specific health needs (such as postoperative rehabilitation, pressure ulcer prevention, or stable operation of assistive devices) and expects to maintain this posture for a long time during low-speed driving, the system's compensatory fine-tuning of minor road disturbances based on general control logic may instead destroy the user's carefully set precise posture, which is contrary to the user's core intention. This unexpected posture change may cause physical discomfort to the user, affect the rehabilitation process or the effectiveness of assistive devices, and force the user to frequently make manual readjustments, increasing the operational burden.

[0069] For example, consider a user undergoing spinal surgery who requires a strict sitting posture. They've used their electric wheelchair's adjustment functions to set the seat cushion and backrest angles to the precise values ​​prescribed by their doctor. When the wheelchair moves at low speed in an indoor environment, such as a hospital corridor, and the wheels pass over floor seams or carpet edges, high-precision sensors detect the resulting subtle changes in body posture, such as slight pitch or roll. Existing adaptive control algorithms identify these minor changes as disturbances requiring compensation and instruct the seat actuators to make minute adjustments in an attempt to "correct" the body posture or "absorb" the vibration. However, even these adjustments, even small ones, can cause the actual seat posture to deviate from the user's target posture, such as a slight change in backrest angle. This can directly interfere with a user who needs to maintain a strict posture.

[0070] If these issues are not addressed, the "intelligent" adaptive function of electric wheelchairs in specific posture maintenance scenarios will not be able to effectively serve the user's individual needs, but may instead become a distraction. The system will continuously respond to minor road disturbances, causing the seat posture to fluctuate frequently around the user's target posture, making it impossible to maintain stability for long periods of time. This will weaken the practicality of electric wheelchairs as assistive tools in specific medical or rehabilitation scenarios and may increase the complexity and psychological burden of user operation.

[0071] Reference Figure 1 , this application proposes a method for adaptively controlling the posture of an electric wheelchair seat according to road conditions, the method comprising:

[0072] S100: receiving a first control instruction to enter a specific posture maintaining mode;

[0073] S200: Responding to the first control instruction, obtaining current posture parameters of the electric wheelchair seat, and storing the current posture parameters as target posture parameters;

[0074] S300: monitoring disturbance parameters, where the disturbance parameters are changes in posture parameters of the electric wheelchair caused by uneven road surfaces during travel;

[0075] S400: Determine the range of the disturbance parameter. If the disturbance parameter is less than a preset disturbance suppression threshold corresponding to a specific posture maintaining mode, maintain the target posture parameter.

[0076] In this embodiment, the specific posture maintenance mode refers to a state in which the user desires the seat to maintain a predetermined or currently set precise posture, and can be activated by a specific user operation. The first control instruction is used to trigger the specific posture maintenance mode. It can be a physical button signal, a touch screen input, a voice command, or a remote control signal. Its purpose is to inform the system that the user wants the seat to maintain its current posture.

[0077] In response to the first control command, the current posture parameters of the electric wheelchair seat are acquired and stored as target posture parameters. Posture parameters characterize the current spatial position and orientation of the electric wheelchair seat and may include seat cushion inclination, backrest angle, leg rest angle, and seat height. These parameters can be acquired through various sensors and are intended to quantify the current state of the seat. The target posture parameter refers to the seat posture that the system strives to maintain in a specific posture maintenance mode. These current posture parameters are acquired and stored upon receiving the first control command and serve as a benchmark for posture maintenance control. The method also monitors disturbance parameters, which represent changes in posture parameters caused by uneven road conditions during driving. These disturbance parameters can be calculated from data such as instantaneous posture changes, vibration amplitude, and angular velocity of the vehicle body or seat as sensed by accelerometers, gyroscopes, and inclination sensors. These parameters are intended to quantify the extent to which external road conditions affect the seat posture. The method determines the range of the disturbance parameter. If the disturbance parameter is less than a preset disturbance suppression threshold corresponding to the specific posture maintenance mode, the target posture parameter is maintained. The disturbance suppression threshold is a preset value used to determine whether the monitored disturbance parameters need to trigger attitude adjustment. This threshold is associated with a specific attitude maintenance mode and may be set according to the characteristics of the mode. Its purpose is to filter out small, unnecessary attitude adjustments and prioritize maintaining the target attitude.

[0078] The core innovation of this application lies in introducing a specific posture maintenance mode and setting a disturbance suppression threshold associated with the mode in this mode, so as to judge and filter road disturbances, thereby achieving the effect of prioritizing the maintenance of the target posture set by the user and avoiding unnecessary fine-tuning.

[0079] In one specific implementation of this embodiment, receiving the first control instruction to enter a specific posture maintenance mode can be specifically the user pressing a physical button on the wheelchair control panel, which is connected to the control unit of the wheelchair. After receiving the button signal, the control unit recognizes it as an instruction to enter a specific posture maintenance mode. In response to the first control instruction, the current posture parameters of the electric wheelchair seat are obtained, and the current posture parameters are stored as target posture parameters. Specifically, the real-time values ​​of posture parameters such as the seat cushion inclination and backrest angle can be obtained through angle sensors installed at the seat joints and tilt sensors installed under the seat cushion, and these values ​​are stored in the memory of the control unit as target posture parameters. Monitoring disturbance parameters can be specifically carried out by continuously collecting data through acceleration sensors and gyroscopes installed on the frame. The control unit calculates the instantaneous posture change rate or vibration amplitude of the vehicle body or seat based on these data as disturbance parameters. Determine the range of the disturbance parameter. If the disturbance parameter is smaller than the preset disturbance suppression threshold corresponding to the specific posture maintenance mode, maintain the target posture parameter. Specifically, the control unit compares the calculated disturbance parameter value with the disturbance suppression threshold preset in the control unit. For example, if the pitch angle change amplitude is smaller than the preset threshold and the vertical vibration acceleration peak is smaller than the preset threshold, the control unit does not send an adjustment instruction to the linear actuator or motor of the seat, thereby maintaining the seat at the position and angle determined by the stored target posture parameters.

[0080] Reference Figure 2 Further, the disturbance parameter includes a first disturbance parameter and a second disturbance parameter, the disturbance suppression threshold includes a first disturbance suppression threshold and a second disturbance suppression threshold, and step S400 includes:

[0081] S410: comparing the first disturbance parameter with the first disturbance suppression threshold, and comparing the second disturbance parameter with the second disturbance suppression threshold;

[0082] S420: When the first disturbance parameter is less than the first disturbance suppression threshold, and the second disturbance parameter is less than the second disturbance suppression threshold, determining a combined disturbance risk level according to the first disturbance parameter and the second disturbance parameter;

[0083] S430: Determine the combined disturbance risk level and a preset risk level threshold. If the combined disturbance risk level is less than the risk level threshold, maintain the target posture parameters.

[0084] The first and second disturbance parameters refer to the change in the electric wheelchair's posture in a specific direction, such as pitch angle change, roll angle change, vertical acceleration, or angular velocity. These parameters can be represented by data obtained from a posture sensor (e.g., a gyroscope or accelerometer).

[0085] The first disturbance suppression threshold and the second disturbance suppression threshold refer to the maximum values ​​allowed for the first disturbance parameter and the second disturbance parameter, respectively, and can be preset according to a specific posture maintenance mode or user requirements.

[0086] The combined disturbance risk level refers to the overall attitude stability risk level derived from a comprehensive assessment of the first and second disturbance parameters. It can be a numerical risk index or a hierarchical risk category. Its purpose is to reflect the combined risk of multiple disturbance parameters, avoiding the limitations of single-parameter judgments.

[0087] The risk level threshold is a preset limit used to determine whether the combined disturbance risk level is within an acceptable range. It can be a numerical value or a risk category. Its purpose is to establish a safety margin for overall attitude stability, which serves as the ultimate basis for determining whether the target attitude is maintained.

[0088] The solution of the present application decomposes the disturbance into at least two components, namely a first disturbance parameter and a second disturbance parameter, and sets independent tolerance limits for each component, namely a first disturbance suppression threshold and a second disturbance suppression threshold. The system compares each disturbance component with its corresponding threshold. Only when all monitored disturbance components are less than their respective thresholds is the posture considered likely to be stable and the overall risk is further assessed. At this point, the system calculates a comprehensive combined disturbance risk level based on the first and second disturbance parameters using preset rules or models. This level reflects the potential impact of the superposition of multi-directional disturbances on posture stability. Finally, the calculated combined disturbance risk level is compared with the preset risk level threshold. Only when the overall risk level is lower than the set safety threshold does the system ultimately decide to maintain the current target posture parameters. This multi-level, multi-parameter judgment mechanism overcomes the shortcomings of relying solely on a single disturbance parameter judgment and can more comprehensively and accurately assess the posture stability of electric wheelchair seats under complex road conditions, especially when there is a superposition of disturbances from multiple directions. By introducing combined risk assessment, even if a single disturbance component is small, if its combined effect leads to an increase in the overall risk, the system can identify it and take corresponding measures, thereby improving the reliability of posture maintenance.

[0089] In one specific implementation of this embodiment, the present application is specifically implemented as follows: the first disturbance parameter is set to the seat pitch angle change, and the first disturbance suppression threshold is set to 2 degrees; the second disturbance parameter is set to the seat roll angle change, and the second disturbance suppression threshold is set to 1.5 degrees. The calculation method of the combined disturbance risk level can be set as: risk level = W1*|pitch angle change|+W2*|roll angle change|, where W1 and W2 are preset weights. The risk level threshold is set to a certain value R_threshold. When the seat pitch angle change is detected to be 1 degree (less than 2 degrees) and the seat roll angle change is 1 degree (less than 1.5 degrees), the system will calculate the combined disturbance risk level based on these two parameters. If the calculated combined risk level is less than R_threshold, the system maintains the target posture parameters. For example, if the seat pitch angle is monitored to change by 1.8 degrees (less than 2 degrees) and the seat roll angle is monitored to change by 1.4 degrees (less than 1.5 degrees), although the individual disturbance parameters are less than their respective thresholds, the calculated combined disturbance risk level may be higher than R_threshold. At this time, the system determines that the target attitude parameters cannot be maintained and may need to make attitude adjustments or issue an alarm.

[0090] Reference Figure 3 Furthermore, sub-step S422 of step S420: determining the combined disturbance risk level according to the first disturbance parameter and the second disturbance parameter, includes:

[0091] S4221: Acquire adjustment information of a target posture characteristic corresponding to the target posture parameter, where the adjustment information indicates that, under the corresponding target posture parameter, the first disturbance parameter and the second disturbance parameter respectively correspond to influence weights of posture stability or user tolerance parameters to a combined disturbance risk level;

[0092] S4222: Generate an adjusted disturbance factor adjusted by the impact weight or tolerance parameter by combining the first disturbance parameter and the second disturbance parameter according to the adjustment information;

[0093] S4223: Determine the combined disturbance risk level based on the adjusted disturbance factor.

[0094] Specifically, adjustment information refers to the data or parameter set used to modify the original disturbance parameters so that they better reflect the actual risk level under a specific target posture. It can be stored in a preset lookup table or dynamically generated through a computational model based on the target posture parameters and user configuration information. Its purpose is to introduce the influence of posture characteristics and individual user differences on risk assessment. Impact weight refers to the relative importance of different disturbance parameters (such as the first disturbance parameter and the second disturbance parameter) to posture stability under specific target posture parameters. It can be a set of numerical values, such as a percentage or a proportional coefficient, used to weight each disturbance parameter when calculating the combined disturbance risk. Its purpose is to distinguish the difference in the impact of different disturbances under a specific posture. The tolerance parameter refers to the user's acceptance of the combined disturbance under specific target posture parameters. It can be a numerical value or level, reflecting the user's sensitivity to slight changes in posture or risk tolerance. Its purpose is to incorporate the user's individual needs into risk assessment. The adjusted disturbance factor refers to the new disturbance measure obtained after the original first disturbance parameter and the second disturbance parameter are corrected by adjustment information (such as influence weight or tolerance parameter). Specifically, it can be the sum of the products of the original disturbance parameters and the corresponding influence weights, or the result of the combined operation of the original disturbance parameters and the adjustment coefficients associated with the tolerance parameters. Its purpose is to provide a more indicative risk assessment basis that comprehensively considers posture characteristics and user tolerance.

[0095] The solution of this application introduces adjustment information for target posture characteristics, enabling the determination of the combined disturbance risk level to comprehensively consider the impact of the target posture parameters themselves on posture stability and the user's tolerance for disturbances in the current posture. Specifically, after the basic conditions of the first disturbance parameter being less than the first disturbance suppression threshold and the second disturbance parameter being less than the second disturbance suppression threshold are met, the system no longer simply determines or judges the combined disturbance risk level directly. Instead, it first obtains adjustment information associated with the current target posture parameters. This adjustment information can reflect the different weights of the first and second disturbance parameters on posture stability in the current posture, or the user's specific tolerance for the combined disturbance risk. Based on this adjustment information, the original first and second disturbance parameters are further processed to generate an adjusted disturbance factor. Compared to the original disturbance parameters, this adjusted disturbance factor better reflects the actual risk level because it has been modified based on the inherent characteristics of the target posture and the user's individual needs. Ultimately, the combined disturbance risk level is determined based on this adjusted disturbance factor. Because the risk level determination process incorporates considerations of posture characteristics and user tolerance, the system's risk assessment of combined disturbances becomes more refined and personalized. Consequently, the system maintains the target posture parameters only when it determines that the risk level of this more refined assessment of the combined disturbance is less than the preset risk level threshold. This approach avoids unnecessary compensatory adjustments to minor disturbances when the user requires specific posture maintenance due to a failure to fully understand the priority of that requirement. This prevents the user's carefully set target posture from being disrupted, better meeting the user's need for posture stability in specific scenarios.

[0096] In one specific implementation of this embodiment, the present application is implemented as follows: Assume that the current target posture parameter of the electric wheelchair seat corresponds to a semi-reclining posture set by the user for pressure ulcer prevention. The system first obtains adjustment information for the target posture characteristics corresponding to the semi-reclining posture. This adjustment information can be preset in a posture-adjustment parameter comparison table. For example, for the "semi-reclining + pressure ulcer prevention" posture, the adjustment information specifies that the influence weight of the pitch angle change (first disturbance parameter) is 0.7, and the influence weight of the roll angle change (second disturbance parameter) is 0.3. When the actual first disturbance parameter (e.g., a pitch angle change of 0.5 degrees) and the second disturbance parameter (e.g., a roll angle change of 0.4 degrees) are monitored, and they are respectively less than the corresponding first disturbance suppression threshold and second disturbance suppression threshold, the system generates an adjusted disturbance factor based on the obtained adjustment information and the two disturbance parameters. For example, the adjusted disturbance factor can be calculated as: 0.5 * 0.7 + 0.4 * 0.3 = 0.35 + 0.12 = 0.47. Finally, the system determines the current combined perturbation risk level based on this adjusted perturbation factor of 0.47 and the preset risk level classification criteria. For example, if the preset risk level threshold is 0.5, since 0.47 is less than 0.5, the system determines the risk level to be low and maintains the current target posture parameters.

[0097] Reference Figure 4 , further, step S4221 includes:

[0098] S42211: Determine whether the target posture characteristic is associated with a preset specific physiological state identifier specified by the user;

[0099] S42212: If the target posture characteristic is associated with a specific physiological state identifier specified by the user, retrieve a preset reference tolerance parameter corresponding to the specific physiological state identifier;

[0100] S42213: Generate adjustment information according to the preset benchmark tolerance parameter, where the adjustment information is used to characterize the influence weight of the first disturbance parameter and the second disturbance parameter on the posture stability under the target posture or the user's tolerance parameter to the combined disturbance risk level.

[0101] Among them, target posture characteristics refer to attributes related to target posture parameters that affect the user's riding experience or health needs, such as the overall shape formed by the combination of posture inclination angle, backrest angle, leg rest height, etc., or the pressure distribution of this shape on specific parts of the body such as the buttocks and back, and the impact on the respiratory or circulatory system.

[0102] Adjustment information refers to a set of parameters used to guide the subsequent determination of the combined disturbance risk level. Specifically, it can be the relative importance (influence weight) of the first disturbance parameter and the second disturbance parameter to posture stability, or the user's tolerance to different types of disturbances such as tilt and vibration in the target posture (tolerance parameter).

[0103] The user-specified preset specific physiological status identifier refers to a symbol or code entered by the user or caregiver in the system to mark the user's current health status or special needs, such as "postoperative recovery period", "high risk of pressure sores", "respiratory support equipment in use", etc. It can be obtained using preset drop-down menu options, custom text labels or by connecting to the medical and health management system.

[0104] The preset baseline tolerance parameters refer to the numerical values ​​or parameter sets that are pre-stored by the system or configured by professionals for each preset specific physiological state identifier, reflecting the user's basic tolerance level to posture disturbances in that physiological state. They can adopt a single tolerance score, a set of tolerance thresholds for different disturbance types, or a function that describes a tolerance curve.

[0105] By determining whether the target posture characteristics are associated with a preset specific physiological state identifier specified by the user, the system identifies whether the current posture is associated with the user's specific health needs. This association determination allows the system to distinguish between general and specific scenarios. When a specific physiological state identifier is identified, the system no longer relies solely on the general target posture characteristics to generate adjustment information, but instead retrieves the preset baseline tolerance parameters corresponding to the specific physiological state identifier. Retrieving the baseline parameters that reflect the user's tolerance to disturbances in this specific state allows the subsequently generated adjustment information to accurately reflect the user's individual needs. The adjustment information generated based on the preset baseline tolerance parameters is used to represent the weight of the first and second disturbance parameters on posture stability, or the user's tolerance parameter for the combined disturbance risk level, in the target posture. This allows the user's actual tolerance level in their specific physiological state to be fully considered when determining the combined disturbance risk level based on the adjustment information, thereby more accurately assessing the impact of the current disturbance on the user. Therefore, the system can more reasonably decide whether posture adjustment is needed, avoiding unnecessary fine-tuning when the user needs to strictly maintain a specific posture. This effectively solves the problem that the basic solution cannot accurately adjust the control parameters according to the user's specific physiological state, and improves the pertinence and effectiveness of posture maintenance.

[0106] In one specific implementation of this embodiment, a user needs to maintain a specific semi-recumbent posture after spinal surgery. The user adjusts the wheelchair seat to this target posture through the wheelchair control panel and selects the associated preset specific physiological state indicator, "Spinal Postoperative Recovery." Upon receiving this information, the system determines that the current target posture characteristic, such as a backrest angle set to 135 degrees, is associated with the user-specified "Spinal Postoperative Recovery" indicator. The system then searches a preset configuration table for a preset baseline tolerance parameter corresponding to the "Spinal Postoperative Recovery" indicator. For example, the parameter is set to "Extremely Sensitive to Posture Changes." Based on this preset baseline tolerance parameter, the system generates adjustment information for a parameter representing the weight of the impact of a first disturbance parameter, such as posture tilt, and a second disturbance parameter, such as vertical vibration, on posture stability, or the user's tolerance to a combined disturbance risk level. For example, the generated adjustment information may indicate that, under the current target posture, even a slight posture tilt or vertical vibration will result in a higher combined disturbance risk level, thereby incentivizing the system to maintain the current posture and avoid unnecessary adjustments.

[0107] Reference Figure 5 , further, step S42213 includes:

[0108] A1: Obtaining a first adjustment parameter determined by a preset reference tolerance parameter, where the first adjustment parameter represents a minimum allowable tolerance level determined by the preset reference tolerance parameter;

[0109] A2: Determine a second adjustment parameter based on the target posture characteristics, where the second adjustment parameter represents the impact of the target posture characteristics on the disturbance adaptability;

[0110] A3: When there is a difference between the tolerance level represented by the first adjustment parameter and the disturbance adaptability represented by the second adjustment parameter, the first adjustment parameter and the second adjustment parameter are adjusted in combination according to the preset integration rule to generate adjustment information. The adjustment information reflects the comprehensive needs of the user under a specific physiological state and target posture characteristics, and the tolerance level determined by the adjustment information is not lower than the minimum allowable tolerance level.

[0111] Among them, the first adjustment parameter refers to a parameter calculated or determined by a preset baseline tolerance parameter, which is used to set the minimum acceptable disturbance level or risk threshold of the user in a specific physiological state, and can be represented by a specific value, a range or a level identifier.

[0112] The target posture characteristics refer to the properties inherent in the target posture of the current electric wheelchair seat itself, which affect the user's adaptability or stability to external disturbances in this posture. It can be determined by a combination of posture parameters (such as tilt angle, backrest angle, leg support angle), the results of the posture stability evaluation model, or user feedback data related to the posture.

[0113] The second adjustment parameter refers to a parameter determined based on target posture characteristic analysis and used to reflect the degree of influence of the target posture itself on the user disturbance adaptability. It can be represented by a correction factor, a weight set or an adaptability level identifier.

[0114] The preset integration rule refers to a predetermined logic, algorithm or mapping relationship used to comprehensively consider the first adjustment parameter and the second adjustment parameter and generate the final adjustment information. It can be implemented using a weighted average algorithm, priority judgment logic, fuzzy reasoning system or a prediction algorithm based on a machine learning model.

[0115] The solution of the present application further refines the process of generating adjustment information by determining whether the target posture characteristics are associated with the specific physiological state identifier specified by the user and retrieving the preset baseline tolerance parameters. Specifically, the system not only obtains the first adjustment parameter determined by the preset baseline tolerance parameter, which sets the minimum allowable tolerance level of the user in a specific physiological state, ensuring basic safety and comfort. At the same time, the system also determines the second adjustment parameter based on the current target posture characteristics. This parameter reflects the impact of the target posture itself on the user's disturbance adaptability, taking into account the actual tolerance of users to disturbances in different postures. When there is a difference in the tolerance level or disturbance adaptability represented by these two parameters, the system combines and adjusts the first adjustment parameter and the second adjustment parameter according to the preset integration rules to generate the final adjustment information. This adjustment information combines the dual influence of the specific physiological state and the target posture characteristics, and more comprehensively reflects the actual needs of the user in the current specific scenario. For example, even if a lower minimum tolerance level is set for a specific physiological state, if the current target posture itself is very stable, the system may appropriately adjust its sensitivity to certain minor disturbances without falling below the minimum level. Conversely, if the target posture itself is less stable, the system may further increase its sensitivity to disturbances or reduce its tolerance based on the minimum tolerance level to prioritize posture stability. This comprehensive consideration and adjustment mechanism makes the generated adjustment information more accurate and personalized. When used to subsequently determine the combined disturbance risk level, it can more accurately assess the impact of the current disturbance on the user in a specific physiological state and target posture, thereby more intelligently determining whether the target posture needs to be maintained, avoiding unnecessary or inappropriate posture adjustments, and improving the accuracy of posture maintenance control and user experience.

[0116] In one specific implementation of this embodiment, the present application is implemented as follows: Assuming that a user specifies a specific physiological state identifier, "postoperative recovery," the system determines whether the current target posture characteristic is associated with this identifier. The system retrieves a preset baseline tolerance parameter corresponding to "postoperative recovery." For example, this parameter indicates that the user has a low tolerance for both vertical vibration and horizontal sway. Based on this preset baseline tolerance parameter, the system obtains a first adjustment parameter, for example, determining the minimum allowable tolerance level to be "Level 2" (higher levels indicate less tolerance). Simultaneously, the system analyzes the current target posture characteristic, for example, a seat with the backrest tilted 45 degrees and the seat cushion tilted forward 10 degrees. Based on this posture characteristic, the system determines a second adjustment parameter. For example, if the analysis finds that in this posture, the user is particularly sensitive to vertical vibration but relatively insensitive to horizontal sway, the system determines that the second adjustment parameter represents "high vertical sensitivity, low horizontal sensitivity." The system determines that there is a difference between the first adjustment parameter (minimum tolerance level 2) and the second adjustment parameter (high vertical sensitivity, low horizontal sensitivity). Based on a preset integration rule, such as a lookup table based on posture type and physiological state, the system combines the first and second adjustment parameters for adjustment. The lookup table may indicate that in the "post-operative recovery" and "backrest tilted 45 degrees" posture, the vertical disturbance influence weight should be set to 0.7 and the horizontal disturbance influence weight should be set to 0.3, while ensuring that the final tolerance level is not lower than level 2. Based on this rule, the system generates adjustment information, which is specifically characterized by a vertical disturbance influence weight of 0.7 and a horizontal disturbance influence weight of 0.3. The system checks whether the tolerance level determined by this adjustment information (for example, the risk level threshold calculated by weighted combination of disturbance parameters) is lower than the minimum allowable tolerance level of level 2. If it is lower, the adjustment information is modified to make its tolerance level exactly level 2; if it is not lower, the adjustment information is directly adopted. The final generated adjustment information is used to subsequently determine the combined disturbance risk level and guide posture maintenance control.

[0117] Reference Figure 6 Furthermore, according to the preset integration rule, sub-step A32 in step A3: combining the first adjustment parameter and the second adjustment parameter to perform adjustment to generate adjustment information, the steps include:

[0118] A321: Obtaining configuration weight information corresponding to the first adjustment parameter and the second adjustment parameter in the integration rule;

[0119] A322: Perform a combination operation on the first adjustment parameter and the second adjustment parameter according to the configuration weight information to generate adjustment information.

[0120] Specifically, in this embodiment, configuration weight information refers to the numerical values ​​or indicators assigned to the first and second adjustment parameters in the integration rule, which are used to indicate their relative importance in the combination operation. This information can be stored and retrieved using a numerical array, an association list, or a structured data format. The combination operation refers to the mathematical or logical operation performed on the first and second adjustment parameters based on the configuration weight information to obtain the final adjustment information. This operation can be implemented using weighted summation, weighted averaging, or other forms of weighted combination algorithms.

[0121] Adjustment information is generated by obtaining the configuration weights corresponding to the first and second adjustment parameters within the integration rule and combining the two parameters based on this weight information. This process ensures that when integrating the first adjustment parameter (representing the minimum allowable tolerance level determined by a preset baseline tolerance parameter) and the second adjustment parameter (representing the impact of the target posture characteristics on disturbance adaptability), the impact of the two can be more finely balanced according to preset priorities or importance. Through this weighted combination, the generated adjustment information more accurately reflects the user's comprehensive needs under specific physiological conditions and target posture characteristics, avoiding the bias that may be caused by simple superposition or averaging. This more accurate adjustment information, when subsequently used to determine the combined disturbance risk level, can make risk assessments more realistic, thereby guiding the system to make more appropriate posture maintenance or adjustment decisions. This effectively solves the problem of how to effectively integrate these two parameters to reflect the user's specific physiological needs while taking into account the impact of the target posture characteristics on disturbance adaptability, while ensuring that the generated adjustment information accurately reflects the user's comprehensive needs.

[0122] In one specific implementation of this embodiment, specifically, the system can first obtain preset priority definitions corresponding to the first adjustment parameter and the second adjustment parameter from the integration rule. Then, based on these priority definitions, the integration rule obtains first weight information corresponding to the first adjustment parameter and second weight information corresponding to the second adjustment parameter through a preset priority weight mapping mechanism. These weight information reflects the priority order determined by the priority definitions. Next, based on the obtained configuration weight information, the first adjustment parameter and the second adjustment parameter are weighted summed or averaged to obtain a preliminary combination result. Subsequently, it is determined whether the tolerance level determined by the preliminary combination result is lower than the preset minimum allowable tolerance level. If the tolerance level determined by the preliminary combination result is lower than the minimum allowable tolerance level, the preliminary combination result is corrected to the minimum allowable tolerance level to generate adjustment information. If the tolerance level determined by the preliminary combination result is not lower than the preset minimum allowable tolerance level, the preliminary combination result is used as the adjustment information.

[0123] Reference Figure 7, further, step A322 includes:

[0124] A3221: Perform a weighted sum or weighted average operation on the first adjustment parameter and the second adjustment parameter based on the configuration weight information to obtain a preliminary combination result;

[0125] A3222: Determine whether the tolerance level determined by the preliminary combined results is lower than the preset minimum allowable tolerance level;

[0126] A3223: If the tolerance level determined by the preliminary combined result is less than the minimum allowable tolerance level, the preliminary combined result is revised to the minimum allowable tolerance level to generate adjustment information;

[0127] A3224: If the tolerance level determined by the preliminary combination result is not lower than the preset minimum allowable tolerance level, the preliminary combination result will be used as adjustment information.

[0128] Specifically, a weighted summation or weighted average operation refers to a mathematical operation that linearly combines multiple values ​​according to their corresponding weights. This can be implemented using the formulas: Result = Weight1 * Parameter1 + Weight2 * Parameter2 + ... or Result = (Weight1 * Parameter1 + Weight2 * Parameter2 + ...) / (Weight1 + Weight2 + ...). A preliminary combination result refers to the intermediate value or indicator obtained by performing a weighted summation or weighted average operation on the first adjustment parameter and the second adjustment parameter based on the configured weight information. It reflects the comprehensive adjustment recommendations before a safety check is performed. The preset minimum allowable tolerance level refers to the lower limit of the tolerance level set by the system to ensure basic user safety and comfort. It can be represented by a fixed numerical threshold, a minimum level, or a safety indicator. Correction refers to the operation of adjusting the value of the preliminary combination result to the minimum allowable tolerance level when the tolerance level determined by the preliminary combination result is lower than the preset minimum allowable tolerance level. This can be implemented using a simple assignment operation.

[0129] By introducing a safety check and correction mechanism in the process of integrating the first adjustment parameter and the second adjustment parameter to generate the adjustment information, it is ensured that the final adjustment information will not cause the tolerance level to be lower than the preset minimum allowable tolerance level. Specifically, after performing a weighted summation or weighted average operation on the first adjustment parameter and the second adjustment parameter based on the configuration weight information to obtain a preliminary combination result, the system will determine whether the tolerance level determined by the preliminary combination result meets the minimum safety requirements, that is, whether it is lower than the preset minimum allowable tolerance level. If the judgment result is lower than the minimum allowable tolerance level, the system will not directly adopt the preliminary combination result, but will correct it to the minimum allowable tolerance level to generate the final adjustment information. This correction operation ensures that even when personalized needs conflict with the minimum safety standards, the safety standards can be met first. If the tolerance level determined by the preliminary combination result is not lower than the preset minimum allowable tolerance level, it indicates that the preliminary result has met the safety requirements. At this time, the preliminary combination result can be directly used as adjustment information without additional correction. This process design, based on the generation of adjustment information through combination operations, adds security verification and mandatory correction links to the combination results, so that the generated adjustment information can not only reflect the user's comprehensive needs under specific physiological states and target posture characteristics, but also strictly abide by the minimum safety threshold, avoiding the safety risks or discomfort that may be caused by excessive pursuit of personalized adjustments.

[0130] In one specific implementation of this embodiment, the first adjustment parameter (tolerance determined based on a specific physiological state) is assumed to be a numerical value ranging from 0 to 10, with higher values ​​indicating greater tolerance. The second adjustment parameter (disturbance adaptability determined based on target posture characteristics) is also assumed to be a numerical value ranging from 0 to 10, with higher values ​​indicating greater adaptability. The configured weight information includes a weight w1 for the first adjustment parameter and a weight w2 for the second adjustment parameter, where w1 + w2 = 1. The preset minimum allowable tolerance level corresponds to a numerical threshold, for example, set to 3. For example, assuming the value of the first adjustment parameter is 2 (indicating low user tolerance) and the value of the second adjustment parameter is 8 (indicating good current posture adaptability), the configured weight information is w1 = 0.7 and w2 = 0.3 (indicating greater consideration of the user's physiological state). A weighted sum operation is performed based on the configured weight information, resulting in a preliminary combination result = w1 * first adjustment parameter + w2 * second adjustment parameter = 0.7 * 2 + 0.3 * 8 = 1.4 + 2.4 = 3.8. Determine whether the tolerance level determined by the preliminary combination result 3.8 is lower than the preset minimum allowable tolerance level of 3. In this example, 3.8 is not lower than 3. Therefore, the preliminary combination result 3.8 is used as the adjustment information. For another example, assume that the value of the first adjustment parameter is 2, the value of the second adjustment parameter is 5, and the configuration weight information is w1 = 0.7, w2 = 0.3. Perform a weighted sum operation based on the configuration weight information to obtain the preliminary combination result = 0.7 * 2 + 0.3 * 5 = 1.4 + 1.5 = 2.9. Determine whether the tolerance level determined by the preliminary combination result 2.9 is lower than the preset minimum allowable tolerance level of 3. In this example, 2.9 is lower than 3. Therefore, the preliminary combination result 2.9 is corrected to the minimum allowable tolerance level of 3 to generate the adjustment information. The tolerance level determined by the final adjustment information is 3.

[0131] Reference Figure 8 , further, step A3221 includes:

[0132] A32211: Obtaining preset priority definitions corresponding to the first adjustment parameter and the second adjustment parameter, respectively, from the integration rule;

[0133] A32212: According to the priority definition, the first weight information corresponding to the first adjustment parameter and the second weight information corresponding to the second adjustment parameter are obtained by the integration rule. The first weight information and the second weight information reflect the priority determined by the priority definition.

[0134] Among them, the priority definition refers to a rule or identifier pre-set in the integration rule for determining the relative importance of the first adjustment parameter and the second adjustment parameter, which can be represented by an enumerated value, a flag or a sorted list. Among them, the first weight information refers to a numerical value or factor used to measure the degree of influence of the first adjustment parameter in the combination operation, which can be represented by a percentage, a proportional coefficient or a grade value. Among them, the second weight information refers to a numerical value or factor used to measure the degree of influence of the second adjustment parameter in the combination operation, which can be represented by a percentage, a proportional coefficient or a grade value. Among them, the priority determined by the priority definition refers to the relative order relationship between the first adjustment parameter and the second adjustment parameter in importance or influence determined according to the priority definition, and its purpose is to guide the configuration of weight information to ensure that parameters with high importance obtain higher weights.

[0135] The solution of this application solves the problem of obtaining reasonable configuration weight information by introducing a priority definition to guide the configuration of weight information. Specifically, the integration rule first obtains preset priority definitions corresponding to the first and second adjustment parameters. This means that before the system configures weights, it has already determined which of the first and second adjustment parameters is more important or should be given priority in the current specific scenario. Pre-setting this priority definition provides a clear basis and direction for subsequent weight configuration. Based on this obtained priority definition, the integration rule obtains the first weight information corresponding to the first adjustment parameter and the second weight information corresponding to the second adjustment parameter. The first and second weight information reflect the priority order determined by the priority definition. This means that if the priority definition indicates that the first adjustment parameter is more important, the obtained first weight information will be higher than the second weight information, and vice versa. This priority-based weight acquisition method ensures the rationality and targetedness of weight configuration and avoids arbitrary or empirical weight setting. Precisely because reasonable weight information reflecting the order of priority has been obtained, when this weight information is used to perform a combination operation on the first and second adjustment parameters, the higher-priority parameter is given a greater weight in the resulting combination, allowing the generated adjustment information to more accurately reflect the user's comprehensive needs under specific physiological conditions and target posture characteristics. In particular, it ensures that the final tolerance level is no less than the minimum allowable tolerance level determined by the preset baseline tolerance parameters. This method of using priorities to guide weight acquisition and, in turn, influence the combination operation, makes the entire adjustment information generation process more intelligent and user-oriented, effectively solving the problem of how to obtain reasonable weights to generate accurate adjustment information.

[0136] In one specific implementation of this embodiment, the integration rules can be stored in a configuration file containing multiple entries, each corresponding to a specific target posture characteristic or associated physiological state indicator. Each entry, in addition to potentially containing other configuration parameters, also explicitly defines the priority of the first adjustment parameter and the second adjustment parameter. For example, for a target posture associated with the specific physiological state indicator "postoperative recovery period," the priority definition in the configuration file may be set to "lowest tolerance level first," meaning that the first adjustment parameter determined by the preset baseline tolerance parameter should have a higher priority. The system reads the configuration file and obtains the priority definition for "lowest tolerance level first." Based on this priority definition, the system then retrieves specific weight information by searching a priority-weight mapping table in the configuration file. For example, the mapping table may specify that "lowest tolerance level first" corresponds to a first weight of 0.8 and a second weight of 0.2. The obtained first weight of 0.8 and second weight of 0.2 reflect the priority of the lowest tolerance level over posture adaptability. This weight information is then used to perform a weighted combination operation on the first and second adjustment parameters to generate the final adjustment information.

[0137] Reference Figure 9 , further, step A32212 includes:

[0138] A322121: Based on the obtained priority definition, the first weight information and the second weight information are determined through a preset priority weight mapping mechanism. The preset priority weight mapping mechanism is used to convert the priority definition into the first weight information and the second weight information, so that the first weight information and the second weight information reflect the priority determined by the priority definition.

[0139] By introducing a priority definition and a priority-weight mapping mechanism, the problem of determining the weights of the first and second adjustment parameters based on actual conditions when integrating them is solved. Specifically, a pre-defined priority definition is first obtained, which specifies the relative importance of the first adjustment parameter (e.g., based on the user's physiological state) and the second adjustment parameter (e.g., based on the target posture characteristics) when generating adjustment information. Then, based on the obtained priority definition, a pre-defined priority-weight mapping mechanism is used to convert this qualitative priority relationship into quantitative first and second weight information. For example, if the priority definition specifies that the first adjustment parameter has a higher priority, the mapping mechanism generates a weight combination that makes the first weight information greater than the second weight information. This weight information is then used to perform a combination operation (e.g., weighted summation or weighted average) on the first and second adjustment parameters to generate the final adjustment information. This generated adjustment information more accurately reflects the user's comprehensive needs under a specific physiological state and target posture, making subsequent adjustments to the perturbation parameter impact weights or user tolerance parameters more reasonable. This priority-based weight determination method enables the entire posture control system to more intelligently balance the impact of different factors in a specific posture maintenance mode, prioritizing the user's most critical needs, thereby improving the system's adaptability and user experience.

[0140] In one specific implementation of this embodiment, the first weight information and the second weight information are determined based on the acquired priority definition through a preset priority weight mapping mechanism. For example, the priority definition can be set as "physiological state priority is higher than posture characteristic priority". The preset priority weight mapping mechanism can be a simple lookup table: if the priority is defined as "physiological state priority is higher than posture characteristic priority", the mapping mechanism outputs the first weight information as 0.7 and the second weight information as 0.3; if the priority is defined as "posture characteristic priority is higher than physiological state priority", the first weight information is output as 0.3 and the second weight information is output as 0.7; if the priority is defined as "physiological state and posture characteristic priority are the same", the first weight information is output as 0.5 and the second weight information is output as 0.5. After the system obtains the current priority definition, it consults the mapping table to determine the first weight information and the second weight information used for the combination operation.

[0141] Through the above technical solution, a priority definition and priority weight mapping mechanism are introduced, so that when the first adjustment parameter and the second adjustment parameter are integrated to generate adjustment information, the first weight information and the second weight information can be dynamically or pre-determined according to a preset priority definition. This allows the generated adjustment information to more reasonably reflect the comprehensive needs of the user under a specific physiological state and target posture, thereby more effectively adjusting the influence weight of the first disturbance parameter and the second disturbance parameter on posture stability or the user's tolerance parameter for the combined disturbance risk level, thereby improving the adaptability and user experience of the posture control system.

[0142] Reference Figure 10 , the present application further proposes an electric wheelchair seat posture adaptive control system, the system comprising:

[0143] An instruction receiving module, configured to receive a first control instruction for entering a specific posture maintaining mode;

[0144] a target posture setting module, configured to respond to the first control instruction, obtain the current posture parameters of the electric wheelchair seat, and store the current posture parameters as target posture parameters;

[0145] The disturbance monitoring module is used to monitor the disturbance parameters, which are the changes in the posture parameters of the electric wheelchair caused by uneven road surface during driving;

[0146] The attitude control module is used to determine the range of the disturbance parameter and maintain the target attitude parameter if the disturbance parameter is less than the preset disturbance suppression threshold corresponding to the specific attitude maintenance mode.

[0147] Among them, the instruction receiving module refers to a unit for receiving external input control signals, which can be implemented by a wired or wireless communication interface, such as connecting to the wheelchair main controller through a CAN bus, or receiving instructions from the user operation panel or remote control through wireless methods such as Bluetooth and Wi-Fi; the target posture setting module refers to a unit for obtaining and recording the current posture state of the electric wheelchair seat, which can be implemented by an interface circuit connected to a posture sensor (such as an inertial measurement unit IMU) and a data storage unit (such as RAM, EEPROM); the disturbance monitoring module refers to a unit for real-time perception and quantification of the impact of external interference on the seat posture of the electric wheelchair during driving, which can be implemented by a data acquisition and processing circuit connected to sensors such as accelerometers and gyroscopes; the posture control module refers to a unit for deciding whether the seat posture needs to be adjusted to maintain the target state based on the monitored disturbance parameters, which can be implemented by a microcontroller, digital signal processor or dedicated control chip, and connected to the seat actuator (such as a motor controller).

[0148] The solution of the present application is to implement the electric wheelchair seat posture road condition adaptive control method in the form of a system module. After the instruction receiving module receives the first control instruction to enter the specific posture maintenance mode, the target posture setting module responds to this instruction, obtains the current posture parameter of the electric wheelchair seat, and stores this parameter as the target posture parameter to be maintained. During the driving process of the electric wheelchair, the disturbance monitoring module continuously monitors the changes in posture parameters caused by uneven road surface and generates disturbance parameters. The posture control module receives the disturbance parameters and compares them with the preset disturbance suppression threshold corresponding to the current specific posture maintenance mode. If the monitored disturbance parameter is less than the threshold, the posture control module maintains the target posture parameter, that is, does not issue an adjustment instruction or issues an instruction to maintain the current state to the seat actuator. This way of implementing the method steps through hardware modularization can provide faster response speed and higher control accuracy compared to pure software implementation, thereby more effectively suppressing the impact of small road disturbances on specific postures and ensuring the stability of the seat posture.

[0149] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for adaptively controlling the posture of an electric wheelchair seat according to road conditions, characterized in that: The method comprises: receiving a first control instruction for entering a specific posture maintaining mode; In response to the first control instruction, obtaining current posture parameters of the electric wheelchair seat, and storing the current posture parameters as target posture parameters; Monitoring disturbance parameters, wherein the disturbance parameters are changes in the posture parameters caused by uneven road surfaces during the travel of the electric wheelchair; Determining the range of the disturbance parameter, and if the disturbance parameter is less than a preset disturbance suppression threshold corresponding to the specific posture maintaining mode, maintaining the target posture parameter; The determining the range of the disturbance parameter, and maintaining the target posture parameter if the disturbance parameter is less than a preset disturbance suppression threshold corresponding to the specific posture maintaining mode, includes: comparing the first disturbance parameter with a first disturbance rejection threshold, and comparing the second disturbance parameter with a second disturbance rejection threshold; When the first disturbance parameter is less than the first disturbance suppression threshold, and the second disturbance parameter is less than the second disturbance suppression threshold, determining a combined disturbance risk level according to the first disturbance parameter and the second disturbance parameter; Determining the combined disturbance risk level and a preset risk level threshold, and if the combined disturbance risk level is less than the risk level threshold, maintaining the target posture parameter; The determining of the combined disturbance risk level according to the first disturbance parameter and the second disturbance parameter includes: Acquire adjustment information of a target posture characteristic corresponding to the target posture parameter, the adjustment information representing, under the corresponding target posture parameter, influence weights of the first disturbance parameter and the second disturbance parameter corresponding to posture stability or a user tolerance parameter to the combined disturbance risk level; generating, according to the adjustment information, a disturbance factor adjusted by the influence weight or the tolerance parameter, by combining the first disturbance parameter and the second disturbance parameter respectively; The combined disturbance risk level is determined based on the adjusted disturbance factor.

2. The method for adaptively controlling the seat posture of an electric wheelchair according to claim 1, characterized in that: The obtaining of adjustment information of the target posture characteristic corresponding to the target posture parameter, wherein the adjustment information represents, under the corresponding target posture parameter, influence weights of the first disturbance parameter and the second disturbance parameter corresponding to posture stability or a user tolerance parameter to the combined disturbance risk level, including: Determining whether the target posture characteristic is associated with a preset specific physiological state identifier specified by a user; If the target posture characteristic is associated with the specific physiological state identifier specified by the user, retrieving a preset reference tolerance parameter corresponding to the specific physiological state identifier; The adjustment information is generated according to the preset benchmark tolerance parameter, and the adjustment information is used to characterize the influence weight of the first disturbance parameter and the second disturbance parameter on the posture stability under the target posture or the user's tolerance parameter to the combined disturbance risk level.

3. The method for adaptively controlling the seat posture of an electric wheelchair according to claim 2, characterized in that: The generating the adjustment information according to the preset reference tolerance parameter includes: Obtaining a first adjustment parameter determined by the preset reference tolerance parameter, wherein the first adjustment parameter represents a minimum allowable tolerance level determined by the preset reference tolerance parameter; determining a second adjustment parameter according to the target posture characteristic, where the second adjustment parameter represents an influence of the target posture characteristic on disturbance adaptability; When there is a difference between the tolerance level represented by the first adjustment parameter and the disturbance adaptability represented by the second adjustment parameter, the first adjustment parameter and the second adjustment parameter are adjusted in combination according to the preset integration rule to generate the adjustment information, which reflects the comprehensive needs of the user under the specific physiological state and the target posture characteristics, and the tolerance level determined by the adjustment information is not lower than the minimum allowable tolerance level.

4. The method for adaptively controlling the seat posture of an electric wheelchair according to claim 3, characterized in that: The adjusting, based on a preset integration rule, in combination with the first adjustment parameter and the second adjustment parameter to generate the adjustment information includes: Obtaining weight information corresponding to the first adjustment parameter and the second adjustment parameter in the integration rule; The first adjustment parameter and the second adjustment parameter are combined and calculated according to the configuration weight information to generate the adjustment information.

5. The method for adaptively controlling the seat posture of an electric wheelchair according to claim 4, characterized in that: The performing a combined operation on the first adjustment parameter and the second adjustment parameter according to the configuration weight information to generate the adjustment information includes: performing a weighted sum or weighted average operation on the first adjustment parameter and the second adjustment parameter according to the configuration weight information to obtain a preliminary combination result; determining whether the tolerance level determined by the preliminary combination result is lower than a preset minimum allowable tolerance level; If the tolerance level determined by the preliminary combination result is lower than the minimum allowable tolerance level, correcting the preliminary combination result to the minimum allowable tolerance level to generate the adjustment information; If the tolerance level determined by the preliminary combination result is not lower than the preset minimum allowable tolerance level, the preliminary combination result is used as the adjustment information.

6. The method for adaptively controlling the seat posture of an electric wheelchair according to claim 4, characterized in that: The acquiring, within the integration rule, configuring weight information corresponding to the first adjustment parameter and the second adjustment parameter includes: Obtaining preset priority definitions corresponding to the first adjustment parameter and the second adjustment parameter respectively from the integration rule; According to the priority definition, the integration rule obtains first weight information corresponding to the first adjustment parameter and second weight information corresponding to the second adjustment parameter, and the first weight information and the second weight information reflect the priority determined by the priority definition.

7. The method for adaptively controlling the seat posture of an electric wheelchair according to claim 6, characterized in that: According to the priority definition, obtaining, by the integration rule, first weight information corresponding to the first adjustment parameter and second weight information corresponding to the second adjustment parameter, wherein the first weight information and the second weight information reflect a priority determined by the priority definition, includes: Based on the obtained priority definition, the first weight information and the second weight information are determined through a preset priority weight mapping mechanism. The preset priority weight mapping mechanism is used to convert the priority definition into the first weight information and the second weight information, so that the first weight information and the second weight information reflect the priority determined by the priority definition.

8. An electric wheelchair seat posture adaptive control system, used to implement the electric wheelchair seat posture road condition adaptive control method according to claim 1, characterized in that: The system includes: An instruction receiving module, configured to receive a first control instruction for entering a specific posture maintaining mode; a target posture setting module, configured to respond to the first control instruction, obtain current posture parameters of the electric wheelchair seat, and store the current posture parameters as target posture parameters; A disturbance monitoring module is used to monitor disturbance parameters, wherein the disturbance parameters are changes in the posture parameters caused by uneven road surface during the travel of the electric wheelchair; The posture control module is used to determine the range of the disturbance parameter and maintain the target posture parameter if the disturbance parameter is less than a preset disturbance suppression threshold corresponding to the specific posture maintenance mode.

Images