A control system and control method of an intelligent foot inversion orthosis

Abstract

The application discloses a control system and a control method of an intelligent foot inversion orthosis, and the system comprises a data acquisition module, an analysis module, a gait acquisition module and a correction analysis module. The analysis module is used for acquiring relationship expressions in three directions respectively. The gait acquisition module is used for determining a plurality of sub-periods sorted according to time, standard characteristic parameters corresponding to each sub-period and electric auxiliary tension values in three directions, and determining current values corresponding to each sub-period. The correction analysis module is used for determining a sub-period corresponding to a current moment, and determining a corresponding current value output by the foot inversion orthosis based on the sub-period corresponding to the current moment. In the application, the corresponding current value is adjusted in real time according to different walking postures during walking of a patient, so that the problem that the electric auxiliary tension values generated by muscles of the orthosis during walking are the same due to the use of the same current value, and the orthosis cannot adapt to a changeable walking process is avoided, and the adaptability of the orthosis is improved.

Description

Technical Field

[0001] This application relates to the field of orthotic control technology, and more specifically, to a control system and control method for an intelligent clubfoot orthosis. Background Technology

[0002] Symptoms of foot inversion often include: abnormal foot posture and uncoordinated gait during walking. In severe cases, it can also cause compensatory damage to the knee and hip joints. Foot inversion orthoses can improve foot posture and gait incoordination during walking. Therefore, the degree of matching between the control process of the foot inversion orthoses and the walking process is directly related to the stability of walking.

[0003] However, the control process of existing foot inversion orthotics still has the following problems: On the one hand, most systems divide gait intervals based on changes in a single directional muscle group or plantar pressure signal, and adjust the corresponding parameters for each gait interval. However, during the patient's walking process, data such as stride length, cadence, and pressure are based on real-time changes in the environment, making it impossible to accurately capture changes in the patient's walking process. This results in a low degree of matching between parameter adjustment and the patient's walking process, and low adaptability during use. On the other hand, the parameters obtained by existing technologies cannot be accurately correlated one-to-one with the divided sub-cycles. The sub-cycle error matching is large during the single orthotics process, resulting in low timeliness and accuracy of electric-assisted correction.

[0004] Therefore, existing technologies have shortcomings and urgently need improvement. Summary of the Invention

[0005] In view of the above problems, the purpose of this invention is to provide a control system and control method for an intelligent foot inversion orthosis, so as to solve the problem that in the existing technology, patients with stroke, cerebral palsy and lower limb muscle injury rehabilitation patients often have foot inversion symptoms during the rehabilitation process. During the walking process, patients often have strange foot postures and uncoordinated gait. In severe cases, it can also cause compensatory damage to the knee joint, hip joint and other joints, which seriously affects the patient's rehabilitation progress and mood. Therefore, the treatment process of foot inversion is also an extremely important process.

[0006] However, the control process of existing foot inversion orthoses still has the following problems: On the one hand, most systems divide gait intervals based on changes in a single directional muscle group or plantar pressure signal, and adjust the corresponding parameters for each gait interval. However, during the patient's walking process, data such as stride length, cadence, and pressure are based on real-time changes in the environment, making it impossible to accurately capture changes in the patient's walking process. This results in a low degree of matching between parameter adjustments and the patient's walking process, leading to low adaptability during use. On the other hand, the parameters obtained by existing technologies cannot be precisely correlated one-to-one with the divided sub-cycles. The sub-cycle error matching is large during the single-piece orthodontic process, resulting in low timeliness and accuracy of electric-assisted correction.

[0007] On one hand, the present invention provides a control system for an intelligent foot inversion orthosis, comprising: The data acquisition module is used to acquire the tension values ​​of the patient's muscle groups in three directions; The analysis module is used to obtain the relationship expressions between the current value and the electrical assist pulling force value of the muscle groups in three directions after the patient wears the orthosis. The gait acquisition module is used to acquire the voluntary pulling force values ​​of the patient's muscle groups in three directions during the natural walking phase after the patient wears the orthosis. Based on the voluntary pulling force values ​​of the patient's muscle groups in three directions, it determines several sub-cycles ordered by time, the standard feature parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions. Based on the electrically assisted pulling force values ​​in the three directions and the corresponding relational expressions in the three directions, it determines the current value corresponding to each sub-cycle. The correction analysis module is used to determine characteristic parameters based on the voluntary pulling force values ​​generated by the patient's muscle groups in three directions during the correction phase, compare the characteristic parameters with the standard characteristic parameters to determine the sub-cycle corresponding to the current moment, and determine the corresponding current value output by the foot inversion orthosis based on the sub-cycle corresponding to the current moment. The three directions include: the coronal plane direction, the sagittal plane direction, and the horizontal plane direction.

[0008] As a preferred technical solution for the control system of the intelligent foot inversion orthosis, the analysis module gradually increases the current value to obtain the corresponding muscle tension value. In response to the muscle tension value no longer increasing with the current, the range formed by the current being zero and the current value at this time is recorded as the preset current range.

[0009] As a preferred technical solution for the control system of an intelligent foot inversion orthosis, the analysis module acquires the relationship expressions between the current values ​​and the electrically assisted pulling force values ​​of muscle groups in three directions, including: For a muscle group in a single direction, the analysis module traverses a preset current range with a preset step size to obtain several data sets, and then splits the data sets into training sets and validation sets. Based on the training set, a linear fit is performed to obtain an expression. The fit degree between the expression and the validation set is calculated. If the fit degree between the expression and some training data is less than the preset fit degree, the length of the preset step size is reduced and this step is repeated. In response to a fit degree greater than or equal to the preset fit degree, the expression is determined to be accurate and the relational expression corresponding to the muscle group in this direction is output. The calculation is repeated to obtain the relational expressions corresponding to the muscle groups in other directions. Each data set includes a current value and a corresponding electric auxiliary pulling force value.

[0010] As a preferred technical solution for the control system of an intelligent foot inversion orthosis, the gait acquisition module determines several sub-cycles ordered by time, standard characteristic parameters corresponding to each sub-cycle, and electrically assisted pulling values ​​in the three directions based on the patient's voluntary pulling force values ​​in three directions, including: Establish a coordinate system with time on the horizontal axis and voluntary pulling force value on the vertical axis. Input the voluntary pulling force value data in the three directions into the coordinate system to obtain a three-dimensional muscle force time series curve. Based on the changing trend of the difference in the vertical coordinates of the two curves in the three-directional muscle force time-series curve, several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrical assist pulling force values ​​in the three directions are determined. The complete gait cycle is defined as follows: the cycle begins when the heel of one side of the patient touches the ground and ends when the heel of the same side of the patient touches the ground again.

[0011] As a preferred technical solution for the control system of an intelligent foot inversion orthosis, the gait acquisition module, based on the changing trend of the vertical coordinate difference between the pairwise curves in the three-directional muscle force time-series curve, determines several sub-cycles ordered by time, standard characteristic parameters corresponding to each sub-cycle, and electrically assisted pulling force values ​​in three directions, including: Based on the aforementioned triaxial muscle strength time-series curve, two groups of curves in the triaxial muscle strength time-series curve are randomly selected to form several sets of curve pairing relationships, and the curve pairing relationships are sorted to form a pairing sequence. Calculate the time difference between the ordinates of each pair of curves in the three-dimensional muscle force time-series curve graph, and plot the time difference curves corresponding to each pair of curves based on the time difference values. The derivative of the difference curves corresponding to each pair of curves is calculated to obtain the temporal difference derivative curves corresponding to each pair of curves. A straight line parallel to the y-axis is moved from left to right. The positive and negative values ​​of the ordinates of the intersection points of the straight line and the temporal difference derivative curves are obtained according to the pairing sequence. The complete gait cycle is divided into several sub-cycles according to the different positive and negative value combinations. The sub-cycles are mapped to the three-dimensional muscle force time-series curve. The average value of the voluntary pulling force in the three directions is calculated in the three-dimensional muscle force time-series curve corresponding to each sub-cycle. The required electric assist pulling force value in each direction is calculated based on the average value of the voluntary pulling force in the three directions. The pairing sequence and the positive and negative value combination corresponding to each sub-period are denoted as standard feature parameters.

[0012] As a preferred technical solution for the control system of an intelligent foot inversion orthosis, the gait acquisition module calculates the required electrically assisted pulling force value in each direction based on the average value of the autonomous pulling force in three directions, including: Obtain the standard tension values ​​required by the muscle groups in three directions when the patient's foot is in a neutral position; Calculate the difference between the standard pulling force required by the muscle groups in each of the three directions and the average value of the corresponding voluntary pulling force, and record it as the electric assist pulling force required in each direction.

[0013] As a preferred technical solution for the control system of an intelligent inversion orthosis, the gait acquisition module, before establishing a coordinate system with time as the horizontal axis and autonomous pulling force value as the vertical axis, also includes: filtering and noise reduction processing of the autonomous pulling force value data in the three directions.

[0014] As a preferred technical solution for the control system of an intelligent foot inversion orthosis, the initial value range of the preset step length is 0.5 to 1.0 mA.

[0015] On the other hand, the present invention provides a control method for an intelligent foot inversion orthosis, comprising: Step S1: Obtain the tension values ​​of the patient's muscle groups in three directions; Step S2: After the patient wears the orthosis, obtain the relationship expression between the current value and the electrical assist pulling force value of the muscle groups in three directions; Step S3: During the natural walking phase after the patient wears the orthosis, obtain the voluntary pulling force values ​​of the patient's muscle groups in three directions. Based on the voluntary pulling force values ​​of the patient's muscle groups in three directions, determine several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions. Based on the electrically assisted pulling force values ​​in the three directions and the corresponding relational expressions, determine the current value corresponding to each sub-cycle. Step S4: During the orthopedic phase, characteristic parameters are determined based on the voluntary pulling force values ​​generated by the patient's muscle groups in three directions. The characteristic parameters are compared with the standard characteristic parameters to determine the sub-cycle corresponding to the current moment. The corresponding current value output by the foot inversion orthosis is determined based on the sub-cycle corresponding to the current moment.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention obtains the relationship expression between current and electrically assisted pulling force. When the patient wears the orthosis, the corresponding current value is determined through the current value and the relationship expression. The patient's relationship expression is then obtained. During walking, the voluntary pulling force values ​​generated by muscle groups in three directions during natural walking are acquired. Ignoring the specific pulling force values, the entire gait cycle of the patient is divided into several sub-intervals based solely on the changing trend of the difference in the ordinates of the pairwise curves. Each sub-interval corresponds to a specific combination of positive and negative values, allowing the patient to obtain the voluntary pulling force values ​​in real time during walking. The acquired data is analyzed to obtain a specific code. Based on this code, the current sub-cycle of the patient can be accurately determined. Each sub-cycle corresponds to a current value. This current value enables muscle contraction to generate a certain electrical assist pulling force, achieving adaptive adjustment of the orthotic output current value. This improves the matching degree between the orthotic and the patient's walking posture, allowing the current value to be adjusted in real time according to different walking postures during the patient's walking process. This avoids the problem of the orthotic not being able to adapt to the changing walking process due to the same electrical assist pulling force generated by the muscles during walking when the same current value is used, thus increasing the adaptability of the orthotic. Attached Figure Description

[0017] Figure 1 This invention provides a structural block diagram of the control system of an intelligent foot inversion orthosis. Figure 2 A flowchart illustrating the steps of the control method for the intelligent inversion orthosis provided by the present invention is shown. Detailed Implementation

[0018] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0019] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0020] Figure 1 The diagram shows a structural block diagram of the control system of an intelligent foot inversion orthosis provided by the present invention.

[0021] like Figure 1 As shown, this invention discloses a control system for an intelligent foot inversion orthosis, comprising: The data acquisition module is used to acquire the tension values ​​of the patient's muscle groups in three directions; The analysis module is used to obtain the relationship expressions between the current value and the electrical assist pulling force value of the muscle groups in three directions after the patient wears the orthosis. The gait acquisition module is used to acquire the voluntary pulling force values ​​of the patient's muscle groups in three directions during the natural walking phase after the patient wears the orthosis. Based on the voluntary pulling force values ​​of the patient's muscle groups in three directions, it determines several sub-cycles ordered by time, the standard feature parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions. Based on the electrically assisted pulling force values ​​in the three directions and the corresponding relational expressions in the three directions, it determines the current value corresponding to each sub-cycle. The correction analysis module is used to determine characteristic parameters based on the voluntary pulling force values ​​generated by the patient's muscle groups in three directions during the orthopedic stage, compare the characteristic parameters with standard characteristic parameters to determine the sub-cycle corresponding to the current moment, and determine the corresponding current value output by the foot inversion orthosis based on the sub-cycle corresponding to the current moment. The three directions include: the coronal plane, the sagittal plane, and the horizontal plane.

[0022] It should be noted that, in the embodiments of the present invention, the muscle group corresponding to the coronal plane is the peroneal muscle group, the muscle group corresponding to the sagittal plane is the tibialis anterior and the triceps surae, and the muscle group corresponding to the horizontal plane is the hip abductor and the hip adductor data acquisition module. Furthermore, this invention first selects independent muscle groups in the coronal, sagittal, and horizontal directions based on the patient's leg muscles. Electrode pads and three independent tension acquisition sensors are applied to the corresponding positions of these muscle groups, respectively attached to the corresponding clusters. The acquired electromyographic signals are then converted into tension values ​​through an electromyographic-tension mapping model after analog-to-digital conversion. After the patient's orthosis is worn, the analysis module acquires the current and electrically assisted tension values ​​of the corresponding muscle groups in the three directions while the patient is relaxed. The acquired data is preprocessed to remove outliers, and a tension relationship expression is obtained by fitting the acquired data. The gait acquisition module acquires the tension generated by the patient's own muscle contraction during walking after the orthosis is worn (i.e., the voluntary tension value in this invention). Based on the voluntary tension data, the gait cycle is determined and divided into several sub-cycles. The division of sub-cycles is not based on specific numerical values, but only on the trend of tension changes between pairs of the three directions. The electrically assisted tension value and current value corresponding to each sub-cycle are calculated. The correction analysis module provides corresponding electrical assistance based on the determined electrical assist force and current values ​​for each sub-cycle. Specific currents are output through electrodes attached to the corresponding muscles, causing the patient's muscles to contract. This contraction, combined with the patient's voluntary pulling force in three directions, balances the three forces, thus orthodontically aligning the patient's foot. As the patient walks, the voluntary pulling force value continuously changes. The patient's voluntary pulling force value is obtained by subtracting the electrical assist force value from the actual measured pulling force value. Corresponding characteristic parameters are continuously acquired based on these voluntary pulling force values. Changes in these parameters indicate the start of the next sub-cycle, and current is output based on the corresponding current value for the next sub-cycle. With continuous walking and passive electrical assistance, the patient's muscles gradually strengthen. Periodic reviews and re-performance updates the relevant parameters, achieving dynamic adaptation of the orthotic control parameters.

[0023] In detail, the beneficial effect of the present invention is that when the patient wears the orthosis, the corresponding current value is determined by the current value and the relational expression, and the patient's relational expression is obtained. During the walking process, parameters such as cadence and stride length are constantly changing. Therefore, simply correcting foot inversion based on parameters such as cadence, stride length, and tension value cannot adapt to the changing walking process in actual walking. However, the relative changes in the tension of the muscle groups in the three directions remain unchanged. The embodiments of the present invention take this characteristic into consideration. By obtaining the voluntary tension values ​​generated by the muscle groups in the three directions during the patient's natural walking process, ignoring the specific tension values, and only using the changing trend of the difference in the vertical coordinates of the two pairs of curves, the complete gait cycle of the patient is divided into several sub-intervals. Each sub-interval corresponds to a specific code (i.e., The technical solution of this invention establishes a correspondence between the positive and negative values ​​of the ordinates of the intersection points of the paired sequence and the curve of the time difference derivative. This allows the patient to obtain a specific code through real-time data analysis during walking. Based on this specific code, the current sub-cycle of the patient can be accurately determined. Each sub-cycle corresponds to a current value, which enables muscle contraction to generate a certain electrical assist pulling force. This achieves adaptive adjustment of the orthotic output current value, improving the matching degree between the orthotic and the patient's walking posture. During the patient's walking process, the corresponding current value is adjusted in real time according to different walking postures. This avoids the problem of the orthotic failing to adapt to the changing walking process due to the same electrical assist pulling force generated by the muscles during walking, caused by using the same current value, thus increasing the adaptability of the orthotic.

[0024] Furthermore, the analysis module gradually increases the current value to obtain the corresponding muscle tension value. In response to the muscle tension value no longer increasing with the current, the range formed by the current being zero and the current value at this time is recorded as the preset current range.

[0025] Those skilled in the art will understand that when the current is between 5 and 10 mA, human muscles will contract slightly, and when the current is between 10 and 30 mA, human muscles will produce stable functional contractions. That is, 5 to 30 mA is the safe current value for the human body. When gradually increasing the current value, the current should not exceed 30 mA. The specific value is determined according to the actual situation. In this embodiment of the invention, the maximum value of gradually increasing the current value is 20 mA. If no increase in muscle tension is detected after the current value reaches 20 mA, then 20 mA is set as the maximum value of the preset current range.

[0026] Furthermore, the analysis module obtains the relationship expressions between the current values ​​and the electrically assisted pulling force values ​​of the muscle groups in three directions, including: For a muscle group in a single direction, the analysis module traverses a preset current range with a preset step size to obtain several data sets, and then splits the data sets into training sets and validation sets. The expression is obtained by linear fitting based on the training group. The goodness of fit between the expression and the validation group is calculated. If the goodness of fit between the expression and some training data is less than the preset goodness of fit, the length of the preset step size is reduced and this step is repeated. In response to a fit greater than or equal to a preset fit, the expression is determined to be accurate and the relational expression corresponding to the muscle group in this direction is output. The calculation is repeated to obtain the relational expressions corresponding to the muscle groups in other directions. Each data set includes the current value and the corresponding electric auxiliary pulling force value.

[0027] It should be noted that the higher the current value, the stronger the muscle contraction force, indicating a certain linear relationship between the current value and the muscle contraction force. Based on this, by acquiring data, splitting it into a dataset and a training set, performing linear fitting on the dataset to obtain a linear expression, and verifying the goodness of fit on the training set, these are conventional techniques used by those skilled in the art and will not be elaborated upon here. A higher goodness of fit results in a more accurate expression, and consequently, a more accurate electrically assisted pulling force value. Therefore, the goodness of fit should be determined based on factors such as the patient's actual needs and the data processing capabilities of the intelligent foot inversion orthosis. In this embodiment, the preset goodness of fit is 99%. The reduction in the preset step length is determined according to the actual situation. In this embodiment, the reduced step length is half of the preset step length.

[0028] In detail, by obtaining the relationship expression between the patient's current value and the electric assist pulling force value, the present invention can provide an accurate data basis for subsequent technical solutions that provide different electric assist pulling force values ​​according to different needs of sub-cycles during walking.

[0029] Furthermore, the gait acquisition module determines several sub-cycles ordered by time, standard feature parameters corresponding to each sub-cycle, and electrically assisted pulling force values ​​in the three directions based on the patient's voluntary pulling force values ​​in the three directions, including: Establish a coordinate system with time on the horizontal axis and voluntary pulling force value on the vertical axis. Input the voluntary pulling force value data in the three directions into the coordinate system to obtain a three-dimensional muscle force time series curve. Based on the changing trend of the difference in the vertical coordinates of the two curves in the three-directional muscle force time-series curve, several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrical assist pulling force values ​​in the three directions are determined.

[0030] Furthermore, the gait acquisition module, based on the changing trends of the ordinate differences between pairs of curves in the three-directional muscle force time-series curve, determines several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions, including: Based on the triaxial muscle strength time series curve, two groups of curves in the triaxial muscle strength time series curve are randomly selected to form several groups of curve pairing relationships, and the curve pairing relationships are sorted to form a pairing sequence. Calculate the time difference between the ordinates of each pair of curves in the three-dimensional muscle force time-series curve graph, and plot the time difference curves corresponding to each pair of curves based on the time difference values. Differentiate the difference curves corresponding to each pair of curves to obtain the temporal difference derivative curves corresponding to each pair of curves. Move a straight line parallel to the y-axis from left to right. Obtain the positive and negative combinations (++-) of the ordinates of the intersection points of the straight line and the temporal difference derivative curves according to the pairing sequence (12, 13, 23). Divide the complete gait cycle into several sub-cycles according to the different positive and negative combinations. The complete gait cycle is: the cycle that starts when the patient's heel touches the ground on one side and ends when the patient's heel touches the ground again on the same side. Several sub-cycles are mapped to the three-dimensional muscle force time-series curve. The average value of the voluntary pulling force in the three directions is calculated in the three-dimensional muscle force time-series curve corresponding to each sub-cycle. The required electric assist pulling force value in each direction is calculated based on the average value of the voluntary pulling force in the three directions. The paired sequence and the combination of positive and negative values ​​corresponding to each sub-cycle are denoted as standard feature parameters.

[0031] It should be noted that by randomly selecting any two groups of curves from the three-dimensional muscle strength time-series curve graph to form several sets of curve pairing relationships, and labeling the three curves in the three-dimensional muscle strength time-series curve graph as 1, 2, 3, etc., the resulting pairing relationships can be obtained in different orders such as 12, 13, 23 or 13, 12, 23... The order of the pairing relationships is the pairing sequence in this embodiment of the invention. Since the time difference curve graph corresponds to the time difference of the ordinate of each pair of curves, by differentiating the time difference curve graph, we can determine whether the time difference of the ordinate of each pair of curves is increasing or decreasing (a positive derivative indicates an increase in the time difference of the ordinate of each pair of curves, and a negative derivative indicates a decrease in the time difference of the ordinate of each pair of curves). (The time difference on the y-axis decreases). Although the patient's cadence, stride length, speed, and other parameters change continuously during walking, this relative change relationship remains unchanged. Based on this, and based on the above-mentioned pairing sequence (e.g., the current pairing sequence is 12, 13, 23), there is a line parallel to the y-axis and a time difference derivative curve. The derivative of the time difference derivative curve between curves 1 and 2 is positive, the derivative of the time difference derivative curve between curves 1 and 3 is positive, and the derivative of the time difference derivative curve between curves 2 and 3 is negative. Then, the positive and negative value combination corresponding to the pairing sequence is (++-). This correspondence between the pairing sequence and the positive and negative value combination is the standard feature parameter in the embodiment of this invention. As the straight line parallel to the y-axis moves from left to right, the vertical coordinates of the three curves in the three-dimensional muscle force time-series curve are constantly changing. Taking the moment of switching between positive and negative value combinations as the critical point, the complete gait cycle can be divided into several sub-intervals. If the number of sub-intervals exceeds the number that can be specified by the positive and negative value combinations (++-), the corresponding sub-cycle can also be determined by the temporal sequence of the positive and negative value combinations within the complete gait cycle. For example, the positive and negative value combination of the previous cycle (++-) and the current positive and negative value combination (-+-). This temporal sequence of (++-) (-+-) can also be used as a way to determine the sub-cycle. After the above explanation, those skilled in the art should be able to understand this part, and it will not be elaborated here. Thus, the electric assist pulling force value corresponding to each sub-interval is calculated.

[0032] In detail, this invention divides sub-cycles by pairing three-dimensional muscle force time-series curves, calculating the difference in the vertical coordinate of each pair of curves, and combining the changes in the combination of positive and negative values ​​over time. The correspondence between the paired sequences and the combination of positive and negative values ​​is used as a feature parameter, thereby enabling the rapid determination of the corresponding sub-cycle during the patient's walking process. This allows for the application of different current values ​​to different walking states during the patient's walking process, thereby improving the matching degree between the orthosis and the patient's walking posture.

[0033] Furthermore, the gait acquisition module calculates the required electrically assisted pulling force value in each direction based on the average value of the autonomous pulling force in the three directions, including: Obtain the standard tension values ​​required by the muscle groups in three directions when the patient's foot is in a neutral position; Calculate the difference between the standard pulling force required by the muscle groups in each of the three directions and the average value of the corresponding voluntary pulling force, and record it as the electric assist pulling force required in each direction.

[0034] It should be noted that when the patient's foot is in a neutral position, the standard tension values ​​required by the muscle groups in the three directions can be determined by manually adjusting the patient's foot to the correct position and measuring the actual values, by calculating based on a model of the human skeleton, or by other methods. No specific method of obtaining these values ​​is specified here.

[0035] Furthermore, before establishing a coordinate system with time as the horizontal axis and autonomous pulling force value as the vertical axis, the gait acquisition module also includes filtering and noise reduction processing of the autonomous pulling force value data in the three directions.

[0036] Those skilled in the art will understand that methods for filtering and denoising data include, but are not limited to, moving average filtering, low-pass digital filtering, etc. The specific method is determined according to the actual situation, as long as it can achieve the effect of filtering out abnormal data caused by walking jitter, sensor interference, and sudden changes in posture. In this embodiment of the invention, low-pass digital filtering is used for filtering and denoising.

[0037] Furthermore, the initial value range of the preset step size is 0.5 to 1.0 mA.

[0038] This invention also provides a control method for an intelligent foot inversion orthosis, comprising: Step S1: Obtain the tension values ​​of the patient's muscle groups in three directions; Step S2: After the patient wears the orthosis, obtain the relationship expression between the current value and the electrical assist pulling force value of the muscle groups in three directions; Step S3: During the natural walking phase after the patient wears the orthosis, obtain the voluntary pulling force values ​​of the patient's muscle groups in three directions. Based on the voluntary pulling force values ​​of the patient's muscle groups in three directions, determine several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions. Based on the electrically assisted pulling force values ​​in the three directions and the corresponding relational expressions, determine the current value corresponding to each sub-cycle. Step S4: During the orthopedic phase, characteristic parameters are determined based on the voluntary pulling force values ​​generated by the patient's muscle groups in three directions. The characteristic parameters are compared with standard characteristic parameters to determine the sub-cycle corresponding to the current moment. The corresponding current value output by the foot inversion orthosis is determined based on the sub-cycle corresponding to the current moment.

[0039] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple modules or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or modules can be electrical, mechanical, or other forms.

[0040] The modules described above as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules. They may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of this embodiment according to actual needs.

[0041] In addition, in the various embodiments of the present invention, all functional modules can be integrated into one processing module, or each module can be a separate module, or two or more modules can be integrated into one module; the integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0042] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0043] Alternatively, if the integrated modules of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

Claims

1. A control system for an intelligent foot inversion orthosis, characterized in that, include: The data acquisition module is used to acquire the tension values ​​of the patient's muscle groups in three directions; The analysis module is used to obtain the relationship expressions between the current value and the electrical assist pulling force value of the muscle groups in three directions after the patient wears the orthosis. The gait acquisition module is used to acquire the voluntary pulling force values ​​of the patient's muscle groups in three directions during the natural walking phase after the patient wears the orthosis. Based on the voluntary pulling force values ​​of the patient's muscle groups in three directions, it determines several sub-cycles ordered by time, the standard feature parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions. Based on the electrically assisted pulling force values ​​in the three directions and the corresponding relational expressions in the three directions, it determines the current value corresponding to each sub-cycle. The correction analysis module is used to determine characteristic parameters based on the voluntary pulling force values ​​generated by the patient's muscle groups in three directions during the correction phase, compare the characteristic parameters with the standard characteristic parameters to determine the sub-cycle corresponding to the current moment, and determine the corresponding current value output by the foot inversion orthosis based on the sub-cycle corresponding to the current moment. The three directions include: the coronal plane direction, the sagittal plane direction, and the horizontal plane direction.

2. The control system of the intelligent foot inversion orthosis according to claim 1, characterized in that, The analysis module gradually increases the current value to obtain the corresponding muscle tension value. When the muscle tension value no longer increases with the current, the range between zero current and the current value at that time is recorded as the preset current range.

3. The control system of the intelligent foot inversion orthosis according to claim 2, characterized in that, The analysis module obtains the relationship expressions between the current values ​​and the electrically assisted pulling force values ​​of the muscle groups in three directions, including: For a muscle group in a single direction, the analysis module traverses a preset current range with a preset step size to obtain several data sets, and then splits the data sets into training sets and validation sets. Based on the training set, a linear fit is performed to obtain an expression. The fit degree between the expression and the validation set is calculated. If the fit degree between the expression and some training data is less than the preset fit degree, the length of the preset step size is reduced and this step is repeated. In response to a fit degree greater than or equal to the preset fit degree, the expression is determined to be accurate and the relational expression corresponding to the muscle group in this direction is output. The calculation is repeated to obtain the relational expressions corresponding to the muscle groups in other directions. Each data set includes a current value and a corresponding electric auxiliary pulling force value.

4. The control system of the intelligent foot inversion orthosis according to claim 1, characterized in that, The gait acquisition module determines several sub-cycles ordered by time, standard feature parameters corresponding to each sub-cycle, and electrically assisted pulling values ​​in the three directions based on the patient's voluntary pulling force values ​​in the three directions, including: Establish a coordinate system with time on the horizontal axis and voluntary pulling force value on the vertical axis. Input the voluntary pulling force value data in the three directions into the coordinate system to obtain a three-dimensional muscle force time series curve. Based on the changing trend of the difference in the vertical coordinates of the two curves in the three-directional muscle force time-series curve, several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrical assist pulling force values ​​in the three directions are determined.

5. The control system of the intelligent foot inversion orthosis according to claim 4, characterized in that, The gait acquisition module, based on the changing trends of the ordinate differences between pairs of curves in the three-directional muscle force time-series curve, determines several sub-cycles ordered by time, standard characteristic parameters corresponding to each sub-cycle, and electrically assisted pulling force values ​​in three directions, including: Based on the aforementioned triaxial muscle strength time-series curve, two groups of curves in the triaxial muscle strength time-series curve are randomly selected to form several sets of curve pairing relationships, and the curve pairing relationships are sorted to form a pairing sequence. Calculate the time difference between the ordinates of each pair of curves in the three-dimensional muscle force time-series curve graph, and plot the time difference curves corresponding to each pair of curves based on the time difference values. Differentiate the difference curves corresponding to each pair of curves to obtain the temporal difference derivative curves corresponding to each pair of curves. Move a straight line parallel to the y-axis from left to right. Obtain the positive and negative value combinations of the ordinates of the intersection points of the straight line and the temporal difference derivative curves according to the pairing sequence. Divide the complete gait cycle into several sub-cycles according to the different positive and negative value combinations. The complete gait cycle is: a cycle that starts when the patient's heel touches the ground on one side and ends when the patient's heel on the same side touches the ground again. The sub-cycles are mapped to the three-dimensional muscle force time-series curve. The average value of the voluntary pulling force in the three directions is calculated in the three-dimensional muscle force time-series curve corresponding to each sub-cycle. The required electric assist pulling force value in each direction is calculated based on the average value of the voluntary pulling force in the three directions. The pairing sequence and the positive and negative value combination corresponding to each sub-period are denoted as standard feature parameters.

6. The control system of the intelligent foot inversion orthosis according to claim 5, characterized in that, The gait acquisition module calculates the required electrically assisted pulling force value in each direction based on the average value of the autonomous pulling force in three directions, including: Obtain the standard tension values ​​required by the muscle groups in three directions when the patient's foot is in a neutral position; Calculate the difference between the standard pulling force required by the muscle groups in each of the three directions and the average value of the corresponding voluntary pulling force, and record it as the electric assist pulling force required in each direction.

7. The control system of the intelligent foot inversion orthosis according to claim 4, characterized in that, Before establishing a coordinate system with time as the horizontal axis and autonomous pulling force value as the vertical axis, the gait acquisition module also includes filtering and noise reduction processing of the autonomous pulling force value data in the three directions.

8. The control system of the intelligent foot inversion orthosis according to claim 3, characterized in that, The initial value range of the preset step size is 0.5 to 1.0 mA.

9. A control method for an intelligent foot inversion orthosis, used to implement the control system of the intelligent foot inversion orthosis as described in any one of claims 1-8, characterized in that, include: Step S1: Obtain the tension values ​​of the patient's muscle groups in three directions; Step S2: After the patient wears the orthosis, obtain the relationship expression between the current value and the electrical assist pulling force value of the muscle groups in three directions; Step S3: During the natural walking phase after the patient wears the orthosis, obtain the voluntary pulling force values ​​of the patient's muscle groups in three directions. Based on the voluntary pulling force values ​​of the patient's muscle groups in three directions, determine several sub-cycles ordered by time, the standard characteristic parameters corresponding to each sub-cycle, and the electrically assisted pulling force values ​​in the three directions. Based on the electrically assisted pulling force values ​​in the three directions and the corresponding relational expressions, determine the current value corresponding to each sub-cycle. Step S4: During the orthopedic phase, characteristic parameters are determined based on the voluntary pulling force values ​​generated by the patient's muscle groups in three directions. The characteristic parameters are compared with the standard characteristic parameters to determine the sub-cycle corresponding to the current moment. The corresponding current value output by the foot inversion orthosis is determined based on the sub-cycle corresponding to the current moment.

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