Motion sensing shoe based on plantar pressure monitoring and motion trend analysis method

Abstract

The invention relates to the technical field of intelligent wearable equipment, and discloses a motion sensing shoe based on plantar pressure monitoring and a motion trend analysis method. According to the motion sensing shoe, various types of sensors can be adopted to work in a combined mode, state trajectory tracking and pressure change condition collection of the foot are achieved, the problem that the data size is limited due to a single sensor is effectively solved by means of multi-modal data of foot pressure and foot postures, and stability and robustness are improved; real-time data of all the modules are comprehensively analyzed, potential information in the exercise data is fully mined, analysis of the exercise trend is achieved, and therefore more valuable exercise guidance and health suggestions are provided for users.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent wearable devices, and in particular to a sports sensing shoe based on plantar pressure monitoring and a sports trend analysis method. Background Art

[0002] In today's era of increasing health awareness, exercise has become an indispensable part of people's lives. Accurately and in real time, understanding one's own exercise status and trends is essential for optimizing sports performance, preventing sports injuries, and developing personalized exercise plans. Sports sensing devices based on plantar pressure have emerged. Such devices can obtain rich sports information by sensing changes in plantar pressure, providing strong support for sports analysis and health management.

[0003] At present, there are still some problems with traditional motion sensing devices. On the one hand, most traditional motion sensing devices use a single sensor, such as an accelerometer or a gyroscope, which can only obtain limited motion information and cannot fully and accurately reflect the motion state. For example, an accelerometer can only measure the acceleration of the movement and cannot obtain key information such as plantar pressure, which limits the accuracy of motion analysis. On the other hand, some motion sensing devices based on plantar pressure have problems such as low sensor accuracy and poor reliability. Since the changes in plantar pressure are very complex, the accuracy and reliability of the sensor are required to be high. Some existing devices are prone to sensor drift and inaccurate data after long-term use, which affects the effect of motion analysis. In addition, most of the existing motion trend analysis methods are based on simple statistical models, which cannot fully explore the potential information in the motion data. Most of them are based on offline processing and cannot analyze and feedback the motion state in real time. Therefore, it is urgent to develop a motion sensing shoe and a motion trend analysis method based on plantar pressure monitoring to solve the above problems. Summary of the invention

[0004] In view of this, the present application provides a sports sensing shoe and a sports trend analysis method based on plantar pressure monitoring, which can fully tap the potential information in the sports data and analyze the sports status in real time, thereby providing users with valuable sports guidance and health advice.

[0005] Specifically, the following technical solutions are included: In a first aspect, the present application provides a motion sensing shoe based on plantar pressure monitoring, the motion sensing shoe comprising a shoe, and further comprising: The plantar pressure sensing module is fitted on the insole of the shoe to collect the pressure of various parts of the user's sole; Two inertial measurement modules, embedded in the toe and rear upper of the shoe, are used to obtain the acceleration, angular velocity and angle of the foot when walking; Two curvature measurement modules are respectively embedded in the corresponding positions of the first metatarsal and the fifth metatarsal in the forefoot area of ​​the insole to obtain the curvature of the foot when walking; The main control module is embedded in the tongue of the shoe and is used to integrate pressure, acceleration, angular velocity, angle and curvature; The mobile terminal is used to perform fusion analysis on the integrated pressure, acceleration, angular velocity, angle and curvature to determine the user's gait pattern and motion trend analysis results.

[0006] In some embodiments, the plantar pressure sensing module is an array composed of multiple pressure sensors, and the plantar pressure sensing module includes three partitions, which are the first to fifth metatarsal projection areas, the arch projection area and the calcaneal load-bearing projection area. The first to fifth metatarsal projection areas include at least twelve evenly arranged pressure sensors, the arch projection area includes at least six evenly arranged pressure sensors, and the calcaneal load-bearing projection area includes at least thirty evenly arranged pressure sensors.

[0007] In some embodiments, the mobile terminal is specifically used for: Preprocessing the integrated pressure, acceleration, angular velocity, angle and curvature, including: synchronizing the ROS timestamps of the pressure of the left and right feet in the pressure, correcting the pressure after the timestamp synchronization, denoising the integrated acceleration, angular velocity and angle, and converting the integrated curvature; The angular velocity, angle and curvature are fused and analyzed with the pre-processed pressure and acceleration to determine the motion parameters including the trajectory of the plantar pressure center, gait stability, pressure distribution and change in the plantar area, gait cycle, step frequency, step length, step width, foot deviation angle, impact impulse during the contact period and plantar flexion torque; Based on the motion parameters, the user's gait pattern and motion trend analysis results are determined. The motion trend analysis results include trend charts, risk indexes, risk inducements, exercise suggestions and warning information. The trend charts are used to display the change curves of impact impulse and ankle joint stability. The risk index is used to quantify the risk level of overuse of each joint and muscle group. The risk inducements are used to provide inducement descriptions for the risk index. The exercise suggestions are used to recommend exercise assessment and intensity adjustment plans for users. The warning information is used to remind users to pay attention to their abnormal gait.

[0008] In some embodiments, the motion sensing shoe further comprises: A data transceiver module is used to send the integrated and processed pressure, acceleration, angular velocity, angle and curvature to a mobile terminal; The power supply module is used to supply power to each module.

[0009] In a second aspect, the present application provides a motion trend analysis method, which is applied to a motion sensing shoe based on plantar pressure monitoring as described in the first aspect above, and the method comprises: Obtain the pressure at various locations on the sole of the foot, the acceleration, angular velocity and angle of the foot when walking, and the bending of the foot when walking; Integrate pressure, acceleration, angular velocity, angle and curvature; The integrated pressure, acceleration, angular velocity, angle and curvature are fused and analyzed to determine the user's gait pattern and motion trend analysis results.

[0010] In some embodiments, before performing fusion analysis on the integrated pressure, acceleration, angular velocity, angle and curvature, the method further comprises: The integrated pressure, acceleration, angular velocity, angle and curvature are preprocessed, including: ROS timestamp synchronization of the pressure of the left and right feet in the pressure, correction processing of the pressure after timestamp synchronization, denoising processing of the integrated acceleration, angular velocity and angle through a Butterworth filter, and conversion processing of the integrated curvature.

[0011] In some embodiments, the pressure after the timestamp synchronization is corrected according to the following formula: In the formula, For the The pressure after the pressure sensor is calibrated, For the The average pressure of a pressure sensor without external force over a period of time. Indicates A pressure sensor is not subjected to external force at a certain moment during this period of time. Indicates the time mark, Indicates the total number of moments; The pressure of the pressure sensor in each partition is interpolated.

[0012] In some embodiments, the integrated pressure, acceleration, angular velocity, angle, and curvature are subjected to fusion analysis to determine the user's gait pattern and motion trend analysis results, including: The integrated pressure, acceleration, angular velocity, angle and curvature are analyzed to determine the user's gait pattern and motion trend analysis results, including the trajectory of the plantar pressure center, gait stability, pressure distribution and changes in the plantar area, gait cycle, step frequency, step length, step width, foot deflection angle, impact impulse during contact period and plantar flexion torque. Based on the motion parameters, the user's gait pattern and motion trend analysis results are determined. The motion trend analysis results include trend charts, risk indexes, risk inducements, exercise suggestions and warning information. The trend charts are used to display the change curves of impact impulse and ankle joint stability. The risk index is used to quantify the risk level of overuse of each joint and muscle group. The risk inducements are used to provide inducement descriptions for the risk index. The exercise suggestions are used to recommend exercise assessment and intensity adjustment plans for users. The warning information is used to remind users to pay attention to their abnormal gait.

[0013] In some embodiments, the plantar pressure center coordinates are determined according to the following formula: , ): in, For the i The pressure of the pressure sensor, and For the i The position coordinates of the pressure sensors, is the partition weight coefficient; connect the center coordinates of the plantar pressure within a period of time in chronological order ( , ) obtain the trajectory of the user's plantar pressure center during this period; The migration rate of the plantar pressure center coordinates is calculated by the sliding window difference method to obtain the quantified gait stability. According to the following formula, the pressure of the pressure sensors in different partitions is weighted and calculated to determine the pressure distribution in the plantar area: in, For the sole A Regional pressure distribution, for A In the region j The pressure of the pressure sensor, is the weight coefficient; The z-axis acceleration collected by the inertial measurement module based on the rear upper of the shoe is greater than the acceleration threshold, which meets the heel touchdown condition; the direction and amplitude of the y-axis angular velocity collected by the inertial measurement module of the rear upper of the shoe meet the eversion and inversion conditions when the heel touches the ground; the x-axis angular velocity of the inertial measurement module of the shoe toe meets the toe-off condition when it changes from positive to negative; the curvature obtained by the curvature measurement module drops to 20% of the baseline value to meet the toe-off condition. Toe-off is a landmark event that marks the end of the support phase and the beginning of the swing phase. By accurately identifying the time point of toe-off, these two core phases can be clearly distinguished to determine the gait cycle. The gait cycle is the time taken for the continuous process from the toe leaving the ground on one side of the user to the toe leaving the ground on the same side; According to the following formula, the migration rate of the plantar pressure center trajectory between the two feet is dynamically adjusted to obtain the support phase ratio: : in, is the trajectory of the plantar pressure center of the current supporting foot, For the heel-strike moment, The toes leave the ground moment; According to the following state equation and observation equation, based on the data obtained by the two inertial measurement modules, the extended Kalman filter formula reconstructs the three-dimensional motion trajectory: in, is the state vector, The data obtained by the inertial measurement module, and are process and observation noise, respectively; The step length L is calculated by trajectory integration according to the following formula: in, , They represent the velocity components in the horizontal and vertical directions of the plantar pressure center trajectory respectively; Calculating cadence by toe lift F : in, For the n The toe-off moment, For the n+1 The moment when the toes leave the ground.

[0014] In some embodiments, the maximum lateral deviation Δ based on the center of pressure of the two feet Step width; The foot deflection angle is calculated by the angle between the magnetometer heading and the direction of the plantar pressure center trajectory according to the following formula: : in, , They represent the abscissa increment and ordinate increment of the plantar pressure center trajectory respectively; According to the following formula, calculate the impact impulse during the contact period W : In the formula, represents the pressure of the pressure sensor in the calcaneal load-bearing projection area, h is the number of pressure sensors in the calcaneal load-bearing projection area, and M is the total number of pressure sensors in the calcaneal load-bearing projection area; The plantar flexion moment is calculated according to the following formula: : in, k is the stiffness coefficient of the bending measurement module 3, d is the length of the lever arm, I is the moment of inertia, represents the step size change, Indicates A curvature measurement module 3 curvature.

[0015] The beneficial effects of the technical solution provided by the embodiments of the present application include at least: The embodiment of the present application provides a motion sensing shoe and motion trend analysis method based on plantar pressure monitoring, the motion sensing shoe includes a plantar pressure sensing module for collecting pressure at various parts of the user's sole, an inertial measurement module for obtaining the acceleration, angular velocity and angle of the foot when walking, a curvature measurement module for obtaining the curvature of the foot when walking, a main control module for integrating pressure, acceleration, angular velocity, angle and curvature, and a fusion analysis of the integrated pressure, acceleration, angular velocity, angle and curvature to determine the user's gait pattern and motion trend analysis results. The motion sensing shoe can use multiple types of sensors to work together to achieve tracking of the state trajectory of the foot and collection of pressure changes. It uses multi-modal data of foot pressure and foot posture to effectively reduce the data volume limitation problem caused by a single sensor and improve stability and robustness; comprehensive analysis of real-time data of each module, fully mining the potential information in the motion data, and realizing the analysis of motion trends, thereby providing users with more valuable sports guidance and health advice. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A schematic diagram of the structure of a sports sensing shoe based on plantar pressure monitoring provided in an embodiment of the present application; Figure 2A schematic diagram of the structure of a plantar pressure sensing module in a sports sensing shoe based on plantar pressure monitoring provided in an embodiment of the present application.

[0018] The reference numerals in the figures represent respectively: 1-plantar pressure sensing module, 2-inertial measurement module, 3-curvature measurement module, 4-main control module, 5-data transceiver module, 6-power supply module. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] In order to make the technical solutions and advantages of the present application more clear, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0021] In a first aspect, the present application provides a motion sensing shoe based on plantar pressure monitoring, the motion sensing shoe comprising a shoe, and further comprising: The sole pressure sensing module 1 is fitted on the insole of the shoe and is used to collect the pressure of various parts of the sole of the user.

[0022] In some embodiments, the plantar pressure sensing module 1 is an array composed of multiple pressure sensors, and the plantar pressure sensing module 1 includes three partitions, which are the first to fifth metatarsal projection areas, the arch projection area, and the calcaneal load-bearing projection area. The first to fifth metatarsal projection areas include at least twelve uniformly arranged pressure sensors, the arch projection area includes at least six uniformly arranged pressure sensors, and the calcaneal load-bearing projection area includes at least thirty uniformly arranged pressure sensors. Multiple pressure sensors are evenly arranged according to the partitions, so as to fully perceive the pressure conditions at various locations on the sole of the user's foot.

[0023] In some embodiments, Figure 2 As shown, the plantar pressure sensing module 1 may include 48 pressure sensors, 12 pressure sensors are evenly arranged in the projection areas of the first to fifth metatarsal bones, 6 pressure sensors are evenly arranged in the projection area of ​​the arch of the foot, and 30 pressure sensors are evenly arranged in the weight-bearing projection area of ​​the calcaneus.

[0024] In some embodiments, the sensing type of the pressure sensor may be piezoresistive, the single-point measuring range may be 0-70 kg, and hemispherical micro-bumps are provided on the surface of the base to enhance the sensitivity of the local pressure concentration response.

[0025] Two inertial measurement modules 2 are embedded in the toe and rear upper of the shoe to obtain the acceleration, angular velocity and angle of the foot when walking.

[0026] Two curvature measurement modules 3 are respectively embedded in the corresponding positions of the first metatarsal and the fifth metatarsal in the forefoot area of ​​the insole, and are used to obtain the curvature of the foot when walking, so as to capture the dynamic deformation of foot flexion and dorsiflexion, and quantify the arch bending angle during the gait propulsion phase.

[0027] In some embodiments, the initial positions of the two curvature measurement modules 3 may be positions corresponding to the first metatarsophalangeal joint and the fifth metatarsal base in the forefoot region of the insole, respectively.

[0028] The pressure at various parts of the sole of the foot obtained by the sole pressure sensing module 1 can reflect the path of the user's movement center of gravity transfer. By analyzing the pressure changes of a single foot, it is possible to analyze whether there is any abnormality in the user's foot. By analyzing the pressure symmetry of both feet, it is possible to determine whether the user's walking is stable. The inertial measurement module 2 can sense the movement of a specific position of the user's foot in space when the user is walking. The acceleration of the foot when walking can reflect the user's movement acceleration habits, and can analyze the user's rhythm and strength when walking or running. The frequency of the acceleration data can be used to determine whether the user has potential movement risks. The angular velocity and angle can reflect the user's movement posture and help predict the user's movement posture change trend. The curvature of the foot when walking can reflect the user's movement gait characteristics, including step length, step width and arch flexibility, and then determine whether the user is adapted to the current exercise intensity and method.

[0029] The main control module 4 is embedded in the tongue of the shoe and is used for integrating and processing pressure, acceleration, angular velocity, angle and curvature.

[0030] The integrated processing of the main control module 4 can achieve time synchronization of pressure, acceleration, angular velocity, angle and curvature to ensure that various data are consistent at the same time point.

[0031] The mobile terminal is used to perform a fusion analysis on the integrated pressure, acceleration, angular velocity, angle and curvature to determine the user's gait pattern and motion trend analysis results, thereby comprehensively analyzing the real-time data of each module and realizing the analysis of motion trends, so as to provide users with more valuable exercise guidance and health suggestions.

[0032] In some embodiments, the mobile terminal is specifically used for: (1) Preprocessing the integrated pressure, acceleration, angular velocity, angle and curvature, including: synchronizing the ROS timestamps of the pressure of the left and right feet in the pressure, correcting the pressure after the timestamp synchronization, denoising the integrated acceleration, angular velocity and angle, and converting the integrated curvature.

[0033] The timestamp synchronization of ROS can synchronize the pressure of the left and right feet to ensure the coordination of the pressure of the left and right feet. Correcting the pressure after the timestamp synchronization can compensate for the nonlinear characteristics of the sensor and error factors such as temperature drift. De-noising the acceleration, angular velocity and angle after integration can improve the data measurement accuracy and data reliability. Converting the curvature after integration can convert the data into a more universal format, which is convenient for subsequent analysis and calculation.

[0034] (2) The angular velocity, angle and curvature are integrated and analyzed with the pre-processed pressure and acceleration to determine the motion parameters including the trajectory of the plantar pressure center, gait stability, pressure distribution and changes in the plantar area, gait cycle, step frequency, step length, step width, foot deflection angle, impact impulse during contact phase and plantar flexion torque, thereby providing a basis for analyzing the user's motion trends.

[0035] (3) Based on the motion parameters, the user's gait pattern and motion trend analysis results are determined. The motion trend analysis results include trend charts, risk indexes, risk factors, exercise recommendations and warning information. The trend charts are used to display the changing curves of impact impulse and ankle joint stability. The risk index is used to quantify the overuse risk level of each joint and muscle group. The risk factors are used to provide inducement explanations for the risk index. The exercise recommendations are used to recommend exercise assessment and intensity adjustment plans for users. The warning information is used to remind users to pay attention to their abnormal gait.

[0036] The user's gait pattern and motion trend analysis results are obtained, thereby analyzing the user's motion trend and providing the user with more valuable exercise guidance and health advice.

[0037] In some embodiments, the motion sensing shoe further comprises: The data transceiver module 5 is used to send the integrated pressure, acceleration, angular velocity, angle and curvature to the mobile terminal.

[0038] In some embodiments, the data transceiver module 5 may be an integrated BLE 5.0 Bluetooth unit and a UWB dual-mode radio frequency unit, wherein the BLE 5.0 Bluetooth unit is used for conventional data stream transmission, and the UWB dual-mode radio frequency unit provides an auxiliary positioning signal.

[0039] In some embodiments, the data transceiver module 5 has an overall packaging structure, achieves IP67 level waterproofing through a silicone potting process, and a thermally conductive graphite sheet is provided at the bottom of the cavity to ensure heat dissipation stability during long-term operation.

[0040] The power supply module 6 is used to supply power to each module.

[0041] In some embodiments, the sports sensing shoes adopt a bionic ergonomic shoe last design, and achieve a comfortable and fitting wearing experience through a flexible upper and an adaptive arch support structure. Each module is embedded in the shoe body in a concealed layout to avoid interference with normal movement. The sole adopts a zoned cushioning design: a honeycomb hollow structure is set in the forefoot area to improve bending flexibility, and a high-rebound EVA material is installed in the heel area to absorb impact energy, ensuring that the sensor can stably collect data during intense exercise. Users can use mobile terminals to obtain gait patterns and movement trend analysis results.

[0042] In summary, the embodiment of the present application provides a kind of sports sensing shoe based on plantar pressure monitoring. The sports sensing shoe can use multiple types of sensors to work together to realize the tracking of foot state trajectory and the collection of pressure change conditions. It uses multimodal data of foot pressure and foot posture to effectively reduce the data volume limitation problem caused by a single sensor and improve the stability and robustness of the system. It comprehensively analyzes the real-time data of each module, fully explores the potential information in the motion data, and realizes the analysis of motion trends, thereby providing users with more valuable sports guidance and health suggestions.

[0043] In a second aspect, an embodiment of the present application provides a motion trend analysis method, which is applied to a motion sensing shoe based on plantar pressure monitoring as in the first aspect above, and the method comprises: Step 301, obtaining the pressure at various locations on the sole of the foot, the acceleration, angular velocity and angle of the foot when walking, and the curvature of the foot when walking.

[0044] The pressure changes at various parts of the sole of the foot can reflect the path of the user's movement center of gravity transfer. By analyzing the pressure changes on one foot, it is possible to analyze whether there are abnormalities in the user's foot. By analyzing the pressure symmetry of both feet, it is possible to determine whether the user's walking is stable. The acceleration of the foot when walking can reflect the user's movement acceleration habits, which is convenient for analyzing the user's rhythm and strength when walking or running. The frequency of the acceleration data can be used to determine whether the user has potential movement risks. The angular velocity and angle can reflect the user's movement posture and help predict the user's movement posture change trend. The curvature of the foot when walking can reflect the user's movement gait characteristics, including step length, step width and arch flexibility, which can determine whether the user is adapting to the current exercise intensity and method.

[0045] In some embodiments, the pressure at each part of the sole of the foot can be expressed as , Indicates the number of the pressure sensor in the plantar pressure sensing module 1, and the inertial measurement module 2 t The data collected at all times can be expressed as , , which is composed of three-dimensional acceleration, three-dimensional angular velocity and three-dimensional angle. The curvature measurement module 3 t The curvature of the foot collected at all times during walking can be expressed as .

[0046] Step 302, integrating the pressure, acceleration, angular velocity, angle and curvature.

[0047] The integrated processing can synchronize the pressure, acceleration, angular velocity, angle and bending in time to ensure that the various data are consistent at the same time point.

[0048] In some embodiments, before performing fusion analysis on the integrated pressure, acceleration, angular velocity, angle, and curvature, the method further comprises: The integrated pressure, acceleration, angular velocity, angle and curvature are preprocessed, including: ROS timestamp synchronization of the pressure of the left and right feet in the pressure, correction processing of the pressure after timestamp synchronization, denoising processing of the integrated acceleration, angular velocity and angle through a Butterworth filter, and conversion processing of the integrated curvature.

[0049] The timestamp synchronization of ROS can synchronize the pressure of the left and right feet to ensure the coordination of the pressure of the left and right feet. The correction processing of the pressure after the timestamp synchronization can compensate for the nonlinear characteristics of the sensor and error factors such as temperature drift. The denoising processing of the acceleration, angular velocity and angle after the integration processing can improve the data measurement accuracy and data reliability. The conversion processing of the curvature after the integration processing can make the data into a more universal format, which is convenient for subsequent analysis and calculation.

[0050] In some embodiments, the pressure of the left and right feet is synchronized by ROS timestamps. The specific implementation method is as follows: (1) The pressure of the left and right feet is segmented to ensure the integrity of each segment of data. (2) The segmented data is sent to the ROS topic for data integration: read the current ROS timestamp, put the timestamp and data into the queue in the form of a tuple; take out the oldest data from the queue and make a synchronization judgment. If the difference between the two timestamps is less than the threshold, the data is considered to be synchronized, and the larger timestamp is selected as the alignment timestamp, and the pressure of the left and right feet is integrated into one piece of data. The selection of the specific threshold is determined by the sampling frequency of the sports sensing shoe and the transmission rate of the Bluetooth protocol.

[0051] In some embodiments, the pressure after the timestamp synchronization is corrected according to the following formula: In the formula, For the The pressure after the pressure sensor is calibrated, For the The average pressure of a pressure sensor without external force over a period of time. Indicates A pressure sensor is not subjected to external force at a certain moment during this period of time. Indicates the time mark, Indicates the total number of moments; The pressure of the pressure sensor in each partition is interpolated to enrich the data, providing richer and more accurate data support for subsequent movement trend analysis based on plantar pressure.

[0052] In some embodiments, interpolating the pressure of the pressure sensor in each partition specifically includes: performing bicubic interpolation on the pressure of the pressure sensor in each partition, that is, first performing one-dimensional cubic interpolation on each row, and then performing one-dimensional cubic interpolation on each column.

[0053] For a certain dimensional data, one-dimensional cubic interpolation is performed, and there are data points , , …, , in each subinterval Construct a cubic polynomial on : , , , The value of is determined by multiple conditions, including: (1) function condition, that is, the value of the interpolation function is equal to the value of the known data point; (2) first-order derivative continuity condition, that is, the first-order derivative is continuous at the connection point of adjacent subintervals; (3) second-order derivative continuity condition, that is, the second-order derivative is continuous at the connection point of adjacent subintervals; (4) boundary condition, the second-order derivative of the two end points is zero. The interpolation function is determined by the above conditions to achieve more detailed data acquisition of foot data.

[0054] It should be noted that for The analog transfer function of the Butterworth filter is for: Among them, the extreme The calculation formula is: in, is the cutoff frequency of the analog filter, .

[0055] For the second-order Butterworth filter, the analog filter is converted to a digital filter and the design parameters are as follows: In some embodiments, the acceleration, angular velocity, and angle after integration are de-noised using a Butterworth filter according to the following formula:

[0056] In the formula, is the acceleration filtering data at time t, is the original acceleration data at time t, is the angular velocity filtering data at time t, is the original data of angular velocity at time t, is the angle filtering data at time t, is the original angle data at time t.

[0057] In some embodiments, the integrated curvature is converted according to the following formula: in, For the The initial angle of the bending measurement module 3 is The curvature, For the The initial angle of the bending measurement module 3 is The curvature.

[0058] Step 303, performs a fusion analysis on the integrated pressure, acceleration, angular velocity, angle and curvature to determine the user's gait pattern and motion trend analysis results, thereby comprehensively analyzing the real-time data of each module and realizing the analysis of motion trends to provide users with more valuable exercise guidance and health advice.

[0059] In some embodiments, the integrated pressure, acceleration, angular velocity, angle, and curvature are subjected to fusion analysis to determine the user's gait pattern and motion trend analysis results, including: (1) The integrated pressure, acceleration, angular velocity, angle and curvature are analyzed to determine the motion parameters including the trajectory of the plantar pressure center, gait stability, pressure distribution and change in the plantar area, gait cycle, step frequency, step length, step width, foot deflection angle, impact impulse during contact phase and plantar flexion torque, so as to provide a basis for analyzing the user's motion trend.

[0060] In some embodiments, the plantar pressure center coordinates are determined according to the following formula: , ): in, For the i The pressure of the pressure sensor, and For the i The position coordinates of the pressure sensors (defined according to the set position of the pressure sensors, and the specific coordinate values ​​of different shoe sizes are scaled by the shoe size conversion table), is the partition weight coefficient (the first to fifth metatarsal projection area is 0.6, the arch projection area is 0.2, and the calcaneal load-bearing projection area is 0.2), Represents the number of pressure sensors, connecting the center coordinates of the plantar pressure over a period of time in chronological order ( , ) can get the trajectory of the user's plantar pressure center during this period of time.

[0061] The migration rate of the plantar pressure center coordinates was calculated using the sliding window difference method to obtain the quantified gait stability.

[0062] In some embodiments, the pressure distribution of the plantar area is determined by weighted calculation of the pressures of the pressure sensors in different partitions according to the following formula: in, For the sole A Regional pressure distribution, for A In the region j The pressure of the pressure sensor, is the weight coefficient, the closer to the center of the area, the higher the weight coefficient, and the sum of the weight coefficients is 1. Since each area has different functions in foot movement, the pressure distribution characteristics can intuitively reflect the force characteristics and state of the area during movement.

[0063] In some embodiments, the gait cycle is determined based on the z-axis acceleration collected by the inertial measurement module 2 of the rear upper of the shoe being greater than the acceleration threshold to meet the heel touchdown condition, the direction and amplitude of the y-axis angular velocity collected by the inertial measurement module 2 of the rear upper of the shoe meeting the eversion and inversion conditions when the heel touches the ground, and the x-axis angular velocity of the inertial measurement module 2 of the toe of the shoe meeting the toe-off condition when it changes from positive to negative, and the curvature obtained by the curvature measurement module 3 drops to 20% of the baseline value to meet the toe-off condition. .

[0064] The z-axis acceleration of the inertial measurement module 2 of the rear upper of the shoe is greater than the acceleration threshold and meets the heel touchdown condition, indicating that the heel touches the ground and has an instantaneous impact. If it exceeds the acceleration threshold, it is preliminarily determined to be a heel touchdown. The y-axis angular velocity and amplitude meet the eversion and inversion conditions when the heel touches the ground, indicating that the user's heel has a small angular velocity fluctuation. The z-axis acceleration combined with the y-axis angular velocity is used to double-verify the touchdown to obtain the user's heel touchdown judgment result, avoiding misjudgment caused by interference such as shoe vibration; when the x-axis angular velocity of the inertial measurement module 2 of the shoe toe changes from positive to negative, it indicates that the user's toes are off the ground. The curvature obtained by the curvature measurement module 3 drops to 20% of the baseline value to cross-verify the toe off the ground, thereby obtaining a more accurate toe off judgment result. The time used in the continuous process from the toe off the ground on one side of the user to the toe off the ground on the same side, that is, the gait cycle of a single step. is the time difference between adjacent touchdown events, and the proportion of support phase It is obtained by dynamically adjusting the migration rate of the plantar pressure center trajectory between the two feet. The formula is as follows: in, is the trajectory of the plantar pressure center of the current supporting foot, It is the moment when the heel touches the ground, marking the starting point of the stance phase in the gait cycle. It is the moment when the toes leave the ground, marking the end of the stance phase and the beginning of the swing phase in the gait cycle.

[0065] In some embodiments, an extended Kalman filter (EKF) reconstructs the three-dimensional motion trajectory based on the data acquired by the two inertial measurement modules 2 according to the following state equation and observation equation: in, is the state vector (i.e. the position data, velocity data, and attitude data corresponding to the current state), The data obtained by the inertial measurement module 2, and are process and observation noise.

[0066] The step length L is calculated by trajectory integration according to the following formula: in, , They represent the velocity components in the horizontal and vertical directions of the plantar pressure center trajectory respectively; Calculating cadence by toe lift F : in, For the n The toe-off moment, For the n+1 The moment when the toes leave the ground.

[0067] In some embodiments, the maximum lateral deviation Δ based on the center of pressure of the two feet Step width; The foot deflection angle is calculated by the angle between the magnetometer heading and the direction of the plantar pressure center trajectory according to the following formula: : in, , They respectively represent the horizontal and vertical increments of the plantar pressure center trajectory.

[0068] In some embodiments, the impact impulse during the contact period is calculated according to the following formula: W : In the formula, represents the pressure of the pressure sensor in the calcaneal load-bearing projection area, h is the number of pressure sensors in the calcaneal load-bearing projection area, and M is the total number of pressure sensors in the calcaneal load-bearing projection area.

[0069] In some embodiments, the plantar flexion moment is calculated according to the following formula: : in, k is the stiffness coefficient of the bending measurement module 3, d is the length of the lever arm, I is the moment of inertia, represents the step size change, Indicates A curvature measurement module 3 curvature.

[0070] (2) Based on the motion parameters, the user's gait pattern and motion trend analysis results are determined. The motion trend analysis results include trend charts, risk indexes, risk factors, exercise recommendations and warning information. The trend charts are used to display the changing curves of impact impulse and ankle joint stability. The risk index is used to quantify the overuse risk level of each joint and muscle group. The risk factors are used to provide inducement explanations for the risk index. The exercise recommendations are used to recommend exercise assessment and intensity adjustment plans for users. The warning information is used to remind users to pay attention to their abnormal gait.

[0071] In some embodiments, the motion parameters are jointly analyzed through the API large model to obtain the gait pattern; the API large model can be based on the Transformer-CNN hybrid architecture, integrate multi-source sensor data and biomechanical parameters, dynamically weight key features through a multi-head attention mechanism, and output classification results and confidence levels. The gait pattern may include normal gait, gait to be trained, and abnormal gait. The judgment conditions for normal gait may be a step length of 0.6-0.8 meters, a step frequency of 100-120 steps / minute, an ankle dorsiflexion angle contact period of 10°-15°, and a plantar pressure distribution that conforms to a dynamic balance of 30%-40% of the calcaneus / 40%-50% of the forefoot body weight. Abnormal gaits include Parkinson's gait and foot drop gait after stroke. The criteria for determining Parkinson's gait in the API large model may be that the step length is less than 0.6m, the step frequency is greater than 130 steps / minute, and the forefoot propulsion force is less than 30% of the user's body weight; the criteria for determining the post-stroke foot drop gait in the API large model may be that the ankle dorsiflexion angle is less than 5, the heel touchdown delay is greater than 50ms, and the classification confidence is above 0.95.

[0072] In some embodiments, the gait to be trained indicates that the user's gait is slightly different from the normal gait, and gait training is required through motion sensing shoes. The gait to be trained may include ankle postoperative gait and nerve injury rehabilitation gait. The judgment condition of ankle postoperative gait in the API large model can be that the improvement rate of the gait symmetry index SI is less than 1% for 3 consecutive days. The nerve injury rehabilitation gait can be judged by the covariance of the arch energy storage efficiency and the plantar flexion torque.

[0073] In some embodiments, the motion parameters are jointly analyzed through the API big model to obtain motion trend analysis results, which may include: aggregating continuous motion parameters by day, week, and month dimensions to build a time series database; performing deep feature extraction and nonlinear relationship modeling on the aggregated multidimensional data through the API big model; and the output results of the big model are processed by a visualization engine to generate motion trend analysis results.

[0074] For example, exercise recommendations may include "reduce running mileage by 20% in the next two weeks" and "increase arch strengthening training". Warning information may include "there is an acute injury risk (the plantar flexion torque in a single exercise exceeds 120% of the personal historical peak and the ground hardness is greater than 80HB (Brnell hardness))", "there is a chronic cumulative risk (the average daily impact impulse integral exceeds the safety threshold for 30 consecutive days, and the monthly decrease in joint stability index is greater than 5%)", and "there is a risk of athletic ability decline (the slope of the step length-cadence relationship curve continues to shift negatively for six weeks)". In summary, the embodiment of the present application provides a motion trend analysis method, which can process various types of sensor data, realize the tracking of foot state trajectory and the collection of pressure changes, and utilize multimodal data of foot pressure and foot posture to effectively reduce the data volume limitation problem caused by a single sensor and improve the stability and robustness of the system; comprehensive analysis of real-time data of each module can realize the prediction and correction of motion trends, thereby providing users with more valuable exercise guidance and health advice.

[0075] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the present application disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only.

[0076] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A sports sensing shoe based on plantar pressure monitoring, comprising a shoe, characterized in that: Also includes: A sole pressure sensing module (1) is fitted on the insole of a shoe and is used to collect pressure at various locations on the sole of a user; Two inertial measurement modules (2), respectively embedded in the toe and rear upper of the shoe, for obtaining the acceleration, angular velocity and angle of the foot when walking; Two curvature measurement modules (3) are respectively embedded in corresponding positions of the first metatarsal bone and the fifth metatarsal bone in the forefoot area of ​​the insole, and are used to obtain the curvature of the foot when walking; A main control module (4) is embedded in the tongue of the shoe and is used to integrate and process pressure, acceleration, angular velocity, angle and curvature; The mobile terminal is used to perform fusion analysis on the integrated pressure, acceleration, angular velocity, angle and curvature to determine the user's gait pattern and motion trend analysis results.

2. The sports sensing shoe based on plantar pressure monitoring according to claim 1, characterized in that: The plantar pressure sensing module (1) is an array composed of a plurality of pressure sensors. The plantar pressure sensing module (1) comprises three partitions, the three partitions being respectively the first to fifth metatarsal projection areas, the arch projection area and the calcaneal load-bearing projection area. The first to fifth metatarsal projection areas include at least twelve uniformly arranged pressure sensors, the arch projection area includes at least six uniformly arranged pressure sensors, and the calcaneal load-bearing projection area includes at least thirty uniformly arranged pressure sensors.

3. The sports sensing shoe based on plantar pressure monitoring according to claim 1, characterized in that: The mobile terminal is specifically used for: Preprocessing the integrated pressure, acceleration, angular velocity, angle and curvature, including: synchronizing the ROS timestamps of the pressure of the left and right feet in the pressure, correcting the pressure after the timestamp synchronization, denoising the integrated acceleration, angular velocity and angle, and converting the integrated curvature; The angular velocity, angle and curvature are fused and analyzed with the pre-processed pressure and acceleration to determine the motion parameters including the trajectory of the plantar pressure center, gait stability, pressure distribution and change in the plantar area, gait cycle, step frequency, step length, step width, foot deviation angle, impact impulse during the contact period and plantar flexion torque; Based on the motion parameters, the user's gait pattern and motion trend analysis results are determined. The motion trend analysis results include trend charts, risk indexes, risk inducements, exercise suggestions and warning information. The trend charts are used to display the change curves of impact impulse and ankle joint stability. The risk index is used to quantify the risk level of overuse of each joint and muscle group. The risk inducements are used to provide inducement descriptions for the risk index. The exercise suggestions are used to recommend exercise assessment and intensity adjustment plans for users. The warning information is used to remind users to pay attention to their abnormal gait.

4. The sports sensing shoe based on plantar pressure monitoring according to claim 1, characterized in that: The motion sensing shoe also includes: A data transceiver module (5) is used to send the integrated pressure, acceleration, angular velocity, angle and curvature to a mobile terminal; The power supply module (6) is used to supply power to each module.

5. A motion trend analysis method, characterized in that: Applied to a sports sensing shoe based on plantar pressure monitoring as claimed in any one of claims 1 to 4, the method comprises: Obtain the pressure at various locations on the sole of the foot, the acceleration, angular velocity and angle of the foot when walking, and the bending of the foot when walking; Integrate pressure, acceleration, angular velocity, angle and curvature; The integrated pressure, acceleration, angular velocity, angle and curvature are fused and analyzed to determine the user's gait pattern and motion trend analysis results.

6. The motion trend analysis method according to claim 5, characterized in that: Before performing fusion analysis on the integrated pressure, acceleration, angular velocity, angle and curvature, the method further includes: The integrated pressure, acceleration, angular velocity, angle and curvature are preprocessed, including: ROS timestamp synchronization of the pressure of the left and right feet in the pressure, correction processing of the pressure after timestamp synchronization, denoising processing of the integrated acceleration, angular velocity and angle through a Butterworth filter, and conversion processing of the integrated curvature.

7. The motion trend analysis method according to claim 5, characterized in that: According to the following formula, the pressure after timestamp synchronization is corrected: In the formula, For the The pressure after the pressure sensor is calibrated, For the The average pressure of a pressure sensor without external force over a period of time. Indicates A pressure sensor is not subjected to external force at a certain moment during this period of time. Indicates the time mark, Indicates the total number of moments; The pressure of the pressure sensor in each partition is interpolated.

8. The motion trend analysis method according to claim 5, characterized in that: The integrated pressure, acceleration, angular velocity, angle and curvature are analyzed to determine the user's gait pattern and motion trend analysis results, including: The integrated pressure, acceleration, angular velocity, angle and curvature are analyzed to determine the motion parameters including the trajectory of the plantar pressure center, gait stability, pressure distribution and change in the plantar area, gait cycle, step frequency, step length, step width, foot deviation angle, impact impulse during contact period and plantar flexion moment; Based on the motion parameters, the user's gait pattern and motion trend analysis results are determined. The motion trend analysis results include trend charts, risk indexes, risk inducements, exercise suggestions and warning information. The trend charts are used to display the change curves of impact impulse and ankle joint stability. The risk index is used to quantify the risk level of overuse of each joint and muscle group. The risk inducements are used to provide inducement descriptions for the risk index. The exercise suggestions are used to recommend exercise assessment and intensity adjustment plans for users. The warning information is used to remind users to pay attention to their abnormal gait.

9. The motion trend analysis method according to claim 8, characterized in that: According to the following formula, determine the coordinates of the plantar pressure center ( , ): in, For the i The pressure of the pressure sensor, and For the i The position coordinates of the pressure sensors, is the partition weight coefficient; connect the center coordinates of the plantar pressure within a period of time in chronological order ( , ) obtain the trajectory of the user's plantar pressure center during this period; The migration rate of the plantar pressure center coordinates is calculated by the sliding window difference method to obtain the quantified gait stability. According to the following formula, the pressure of the pressure sensors in different partitions is weighted and calculated to determine the pressure distribution in the plantar area: in, For the sole A Regional pressure distribution, for A In the region j The pressure of the pressure sensor, is the weight coefficient; The gait cycle is determined based on the z-axis acceleration collected by the inertial measurement module (2) of the rear upper of the shoe being greater than the acceleration threshold, satisfying the heel touchdown condition; the direction and amplitude of the y-axis angular velocity collected by the inertial measurement module (2) of the rear upper of the shoe satisfying the eversion and inversion conditions when the heel touches the ground; the x-axis angular velocity of the inertial measurement module (2) of the toe of the shoe satisfying the toe-off condition when it changes from positive to negative; and the curvature obtained by the curvature measurement module (3) drops to 20% of the baseline value, satisfying the toe-off condition. The gait cycle is the time taken for the continuous process from the toe leaving the ground on one side of the user to the toe leaving the ground on the same side; According to the following formula, the migration rate of the plantar pressure center trajectory between the two feet is dynamically adjusted to obtain the support phase ratio: : in, is the trajectory of the plantar pressure center of the current supporting foot, For the heel-strike moment, The toes leave the ground moment; According to the following state equation and observation equation, based on the data obtained by the two inertial measurement modules (2), the extended Kalman filter formula reconstructs the three-dimensional motion trajectory: in, is the state vector, The data obtained by the inertial measurement module (2) and are process and observation noise respectively; The step length L is calculated by trajectory integration according to the following formula: in, , They represent the velocity components in the horizontal and vertical directions of the plantar pressure center trajectory respectively; Calculating cadence by toe lift F : in, For the n The toe-off moment, For the n+1 The moment when the toes leave the ground.

10. The motion trend analysis method according to claim 9, characterized in that: The maximum lateral deviation based on the pressure center of both feet Δ Step width; The foot deflection angle is calculated by the angle between the magnetometer heading and the direction of the plantar pressure center trajectory according to the following formula: : in, , They represent the abscissa increment and ordinate increment of the plantar pressure center trajectory respectively; According to the following formula, calculate the impact impulse during the contact period W : In the formula, represents the pressure of the pressure sensor in the calcaneal load-bearing projection area, h is the number of pressure sensors in the calcaneal load-bearing projection area, and M is the total number of pressure sensors in the calcaneal load-bearing projection area; The plantar flexion moment is calculated according to the following formula: : in, k is the stiffness coefficient of the bending measurement module (3), d is the length of the lever arm, I is the moment of inertia, represents the step size change, Indicates A curvature measurement module (3) curvature.

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