Gait analysis system

Abstract

The invention is suitable for the technical field of medical equipment, and provides a gait analysis system which comprises a first pressure sensor module, a second pressure sensor module, an FPGA processor module and an upper computer module.The first pressure sensor module is used for collecting first pressure data generated when a user walks on a first sensor array, and the second pressure sensor module is used for collecting second pressure data generated when the user walks on a second sensor array; the second pressure sensor module is used for collecting second pressure data generated when the user walks by wearing a second sensor array, and the FPGA processor module is used for receiving the first pressure data and the second pressure data at the same time. The first pressure module is used for receiving first pressure data and second pressure data, converting the first pressure data and the second pressure data into target data according to a target protocol and transmitting the target data to the upper computer module, and the upper computer module is used for processing the target data to obtain gait analysis data. The use conditions of gait analysis can be reduced, and the accuracy of gait analysis is improved.

Description

Technical Field

[0001] This application belongs to the technical field of medical devices, and particularly relates to a gait analysis system. Background Art

[0002] Gait analysis refers to the analysis of the behavioral characteristics of walking to examine the walking state. Since the control of walking is very complex, including central commands, body balance, and coordination control, etc., gait analysis can assist in clinical diagnosis, efficacy evaluation, etc. For example, peripheral nerve injury, central nerve injury, etc. may all lead to abnormal gait, and gait analysis can help patients with abnormal gait improve and restore their walking ability.

[0003] Currently, gait analysis is mainly divided into two categories: qualitative analysis (visual inspection) and quantitative analysis. Among them, qualitative analysis is mainly carried out by medical staff through visual observation, which is affected by subjective factors and inaccurate; quantitative analysis requires arranging auxiliary devices (such as digital detectors or high-speed cameras, etc.) in the test site, and the person to be tested wears multiple types of wearable devices in the test site for gait analysis. The auxiliary devices are expensive and the test preparation is cumbersome. Summary of the Invention

[0004] The embodiments of this application provide a gait analysis system, which can reduce the usage conditions of gait analysis and improve the accuracy of gait analysis.

[0005] The embodiments of this application provide a gait analysis system, including a first pressure sensor module, a second pressure sensor module, an FPGA processor module, and a host computer module, where:

[0006] The first pressure sensor module is used to collect first pressure data generated when a user walks on a first sensor array;

[0007] The second pressure sensor module is used to collect second pressure data generated when the user wears a second sensor array and walks;

[0008] The FPGA processor module is used to simultaneously receive the first pressure data and the second pressure data, convert the first pressure data and the second pressure data into target data according to a target protocol, and transmit the target data to the host computer module;

[0009] The host computer module is used to process the target data to obtain gait analysis data.

[0010] Optionally, the first pressure sensor module further includes a first analog-to-digital conversion module and a first analog switch module, where:

[0011] The first analog switch module is configured to receive a first data acquisition instruction sent by the FPGA processor module and switch sensor elements in the first sensor array according to the first data acquisition instruction.

[0012] The first analog-to-digital conversion module is configured to acquire first pressure data generated when a user walks while wearing the first sensor array according to the first data acquisition instruction.

[0013] Optionally, the first sensor array is composed of sensor elements arranged in m rows and n columns, where both m and n are integers greater than 1. Sensor elements in the same row of the first sensor array share a common row lead wire, and sensor elements in the same column of the first sensor array share a common column lead wire.

[0014] Optionally, the first pressure sensor module is specifically configured to:

[0015] The first analog switch module receives a first data acquisition instruction sent by the FPGA processor module, where the first data acquisition instruction includes a set sampling frequency.

[0016] The first analog switch module switches the column lead wires in the first sensor array according to the sampling frequency.

[0017] When the column lead wires are switched, the first analog-to-digital conversion module performs parallel data acquisition on all row lead wires in the first sensor array.

[0018] When all column lead wires in the first sensor array have been traversed, the first analog-to-digital conversion module aggregates all the acquired data to obtain the first pressure data.

[0019] Optionally, the sensor element density of the first sensor array is less than that of the second sensor array.

[0020] Optionally, the FPGA processor module includes a data alignment module and a protocol conversion module, where:

[0021] The data alignment module is configured to align data according to the transmission times of the first pressure data and the second pressure data.

[0022] The protocol conversion module is configured to convert the aligned first pressure data and second pressure data into the target data according to the target protocol.

[0023] Optionally, the protocol conversion module is specifically configured to:

[0024] Convert the aligned first pressure data and second pressure data into the target data according to the data type configuration information and data storage configuration information in the target protocol, where the target data includes a pressure data frame or a pressure data array.

[0025] Optionally, the host computer module includes a data preprocessing module, a first data feature extraction module, a second data feature extraction module, and a multi-feature fusion analysis module, where:

[0026] The data preprocessing module is used to filter out environmental noise in the target data;

[0027] The first data feature extraction module is used to extract gait cycle features according to the pressure data frame or the pressure data array;

[0028] The second data feature extraction module is used to extract gait spatio-temporal features according to the pressure data frame or the pressure data array;

[0029] The multi-feature fusion analysis module is used to perform feature fusion analysis on the gait cycle features and the gait spatio-temporal features according to a trained multi-feature fusion classification model to obtain the gait analysis data.

[0030] Optionally, the first data feature extraction module is specifically used for:

[0031] Determine the time points when the states of different parts of the sole change according to the distribution positions of the pressures in the pressure data frame or the pressure data array; where the state changes of different parts of the sole include heel strike, heel off, toe strike, and toe off;

[0032] Calculate the gait cycle features according to the time points; where the gait cycle features include at least one of the features corresponding to the stance phase and the swing phase.

[0033] Optionally, the second data feature extraction module is specifically used for:

[0034] Determine the position coordinates of different parts of the sole according to the distribution positions of the pressures in the pressure data frame or the pressure data array;

[0035] Determine the duration of the state change of different parts of the sole according to the time points when the states of different parts of the sole change;

[0036] Calculate the gait spatio-temporal features according to the position coordinates of different parts of the sole and the duration of the state change of different parts of the sole; where the gait spatio-temporal features include at least one of the features corresponding to step length, step width, stride, walking speed, and step frequency.

[0037] The beneficial effects of the embodiments of the present application compared with the prior art are as follows:

[0038] Through the pressure data collected by the first pressure sensor module and the second pressure sensor module, the present application can perform gait analysis on the user, achieving simple and accurate gait analysis. Specifically, since the first pressure sensor module collects the first pressure data generated by the user walking on the first sensor array, and the second pressure sensor module collects the second pressure data generated by the user wearing the second sensor array while walking, more abundant plantar pressure information can be obtained, thereby improving the accuracy of gait analysis. At the same time, collecting plantar pressure information through the first pressure sensor module and the second pressure sensor module means that there is no need to wear multiple types of wearable devices, which can reduce the usage conditions of gait analysis and improve the applicability of gait analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0040] Figure 1 is a functional architecture diagram of a gait analysis system provided by an embodiment of the present application;

[0041] Figure 2 is a schematic structural diagram of an insole provided by an embodiment of the present application;

[0042] Figure 3 is a schematic side view structural diagram of an insole provided by an embodiment of the present application;

[0043] Figure 4 is a functional architecture diagram of the first pressure sensor module provided by an embodiment of the present application;

[0044] Figure 5 is a functional architecture diagram of the FPGA processor module provided by an embodiment of the present application;

[0045] Figure 6 is a functional architecture diagram of the host computer module provided by an embodiment of the present application;

[0046] Figure 7 is a system structure diagram of the gait analysis system provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system architectures, technologies, etc. are presented to provide a thorough understanding of the embodiments of the present application. However, those skilled in the art should understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from obscuring the description of the present application.

[0048] It should be understood that when used in the specification and the appended claims of the present application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0049] It should also be understood that the term "and / or" as used in the specification and the appended claims of the present application refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0050] As used in the specification and the appended claims of the present application, the term "if" can be interpreted as "when" or "once" or "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]" depending on the context.

[0051] In addition, in the description of the specification and the appended claims of the present application, the terms "first", "second", "third", etc. are only used for differentiating descriptions and cannot be understood as indicating or implying relative importance.

[0052] The reference to "one embodiment" or "some embodiments" or the like described in the specification of the present application means that a specific feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the present application. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0053] Currently, when using quantitative analysis methods to perform gait analysis on patients with abnormal gaits, in order to improve the accuracy of gait analysis, different types of wearable devices, detection devices, etc. often need to cooperate with each other to complete the examination. For example, when performing gait analysis on Parkinson's patients, the patient needs to wear different types of wearable devices such as acceleration sensors, gyro sensors, and ranging sensors to collect gait data, and cooperate with auxiliary devices (such as digital detectors or high-speed cameras, etc.) to perform gait analysis. Since such auxiliary devices are expensive and the test preparations (such as usage conditions, usage steps) are too cumbersome, the applicability of gait analysis is poor.

[0054] In order to improve the applicability of gait analysis, the present application provides a gait analysis system based on pressure sensors.

[0055] Figure 1 The functional architecture diagram of a gait analysis system provided by an embodiment of the present application is shown. In this embodiment, the gait analysis system 1 includes a first pressure sensor module 101, a second pressure sensor module 102, an FPGA processor module 103, and a host computer module 104, which are described in detail as follows:

[0056] The first pressure sensor module 101 is used to collect first pressure data generated when a user walks on a first sensor array.

[0057] In some embodiments, the above-mentioned first sensor array may be a pressure sensor array provided in a floor mat. The above-mentioned first pressure sensor module may be installed in the floor mat and is used to collect first pressure data generated by the first sensor array when the user walks on the floor mat. Since the first pressure sensor module 101 collects the first pressure data generated by the first sensor array, it means that there is no need for the user to wear it, and the above-mentioned first sensor array is provided in the floor mat, which is convenient for curling and carrying, has better mobility, and can be used in more venues.

[0058] The second pressure sensor module 102 is used to collect second pressure data generated when the user wears a second sensor array and walks.

[0059] In some embodiments, the above-mentioned second sensor array may be a pressure sensor array provided in an insole. The above-mentioned second pressure sensor module may be installed in the insole and is used to collect second pressure data generated by the second sensor array when the user wears the above-mentioned insole and walks.

[0060] It should be noted that the above-mentioned insole may be a split external insole, that is, the above-mentioned insole can be fixed outside the tester's shoes, so as to adapt to different testers. Refer to Figure 2 As shown, it is a structural schematic diagram of the insole. Among them, the above-mentioned insole can be divided into a forefoot part and a heel part, and is fixed to the tester's shoe sole through a fixing clip. Refer toFigure 3 As shown in the figure, it is a schematic structural diagram of the insole in side view. Among them, the forefoot part and the heel part both include a circuit layer and a sponge. The circuit layer is equipped with pressure sensors (i.e., the second sensor array) at the pressure sensing areas of the toe and the heel positions. The rest of the circuit layer contains a battery slot, a microprocessor, a memory, a wireless signal transmitting part, etc. Since the split external insole has the characteristics of simple wearing and convenient disassembly, it can better adapt to different testers and at the same time better sense the force conditions of different parts (such as the toe, the heel, etc.).

[0061] The above-mentioned FPGA processor module 103 is used to simultaneously receive the first pressure data and the second pressure data, convert the first pressure data and the second pressure data into target data according to the target protocol, and transmit the target data to the host computer module.

[0062] In some embodiments, the above-mentioned FPGA processor module can be installed in a Field Programmable Gate Array (FPGA) chip and is used to convert the first pressure data and the second pressure data into target data according to the target protocol. Among them, the above-mentioned target protocol refers to a specific protocol used to convert data from different sources into the same format standard.

[0063] The above-mentioned host computer module 104 is used to process the target data to obtain gait analysis data.

[0064] In some embodiments, the above-mentioned host computer module 104 can be installed in a host computer. The above-mentioned host computer is a computer or other digital device used to control or monitor another device or multiple devices (such as sensors, actuators, controllers, etc.), for example, a computer, a mobile phone, etc.

[0065] This application can perform gait analysis on the user through the pressure data collected by the first pressure sensor module and the second pressure sensor module, and can achieve simple and accurate gait analysis. Specifically, since the first pressure sensor module collects the first pressure data generated when the user walks on the first sensor array, and the second pressure sensor module collects the second pressure data generated when the above-mentioned user wears the second sensor array and walks, more abundant plantar pressure information can be obtained, thereby improving the accuracy of gait analysis. At the same time, collecting plantar pressure information through the first pressure sensor module and the second pressure sensor module means that there is no need to wear multiple types of wearable devices, so that the usage conditions of gait analysis can be reduced and the applicability of gait analysis can be improved.

[0066] In the embodiments of this application, referring to Figure 4 As shown in the figure, the above-mentioned first pressure sensor module 101 further includes a first analog switch module 1011 and a first analog-to-digital conversion module 1012, where:

[0067] The first analog switch module 1011 is configured to receive a first data acquisition instruction sent by the FPGA processor module 103, and switch the sensor elements in the first sensor array according to the first data acquisition instruction.

[0068] The first analog-to-digital conversion module 1012 is configured to acquire first pressure data generated when a user wears the first sensor array and walks according to the first data acquisition instruction.

[0069] In some embodiments, the above-mentioned first analog switch module 1011 can be installed in an analog switch (MUX) chip to switch the sensor elements in the first sensor array according to a first data acquisition instruction sent by the FPGA processor module 103. The above-mentioned first analog-to-digital conversion module 1012 can be installed in an analog-to-digital converter (ADC) to convert the analog voltage signal collected by the sensor array into a digital signal and transmit it to the above-mentioned FPGA processor module 103.

[0070] In an alternative embodiment of the present application, the above-mentioned first sensor array is composed of sensor elements arranged in m rows and n columns, where m and n are both integers greater than 1. The sensor elements in the same row of the first sensor array share a row lead wire, and the sensor elements in the same column of the first sensor array share a column lead wire.

[0071] It should be noted that since the above-mentioned first sensor array is arranged in the floor mat, the number of sensor elements in the above-mentioned first sensor array will change according to the number of floor mats spliced. For example, assuming that the size of each floor mat is 1m * 1m and it contains a layer of pressure sensor array (100 * 100), if 10 floor mats are spliced into a size of 1m * 10m, the corresponding first pressure sensor array is 1000 * 100. At the same time, the sensor elements in each row or column are connected by the same wire to facilitate data acquisition of the entire row or column of sensor elements.

[0072] Further, the above-mentioned first pressure sensor module 101 is specifically configured to:

[0073] The first analog switch module 1011 receives a first data acquisition instruction sent by the FPGA processor module 103, where the first data acquisition instruction includes a set sampling frequency;

[0074] The first analog switch module 1011 switches the column lead wires in the first sensor array according to the sampling frequency;

[0075] When the column lead wire is switched, the first analog-to-digital conversion module 1012 performs parallel data acquisition on all row lead wires in the first sensor array;

[0076] When all column lead wires in the first sensor array are traversed, the first analog-to-digital conversion module 1012 aggregates all the acquired data to obtain the first pressure data.

[0077] In some embodiments, when using a floor mat for gait analysis, different numbers of floor mats are spliced in the column direction according to the actual measurement site or other requirements. Therefore, in order to improve the efficiency of data acquisition, column scanning can be used for data acquisition. For example, the above-mentioned FPGA processor module 103 controls the above-mentioned first analog switch module 1011 to switch different column lead wires through a first data acquisition instruction. Each time a column lead wire is switched, the above-mentioned first analog-to-digital conversion module 1012 performs a parallel data acquisition on all row lead wires. When all column lead wires are traversed, the signals of all sensor elements in the sensor array are acquired. Assuming that the sampling frequency set by the host computer module is 100 Hz, the above-mentioned first analog switch module needs to be switched 100 times per second.

[0078] In the embodiments of the present application, the sensor element density of the first sensor array is less than that of the second sensor array.

[0079] In some embodiments, in order to improve the efficiency of data acquisition and avoid excessive amount of acquired data, the sensor element density of the sensor array in the insole can be set to be greater than that of the sensor array in the floor mat. Since the area of the floor mat is large, a smaller sensor element density in the floor mat can avoid excessive amount of data acquisition and improve the efficiency of data acquisition; while the area of the insole is small, a larger sensor element density in the insole can improve the accuracy of the acquired data without overly affecting the efficiency of data acquisition.

[0080] It should be noted that the composition structure and data acquisition method of the second sensor array in the insole are similar to those of the floor mat, and will not be elaborated here.

[0081] In an alternative embodiment of the present application, referring to Figure 5 As shown, the above-mentioned FPGA processor module 103 includes a data alignment module 1031 and a protocol conversion module 1032, where:

[0082] The data alignment module 1031 is used to perform data alignment according to the sending times of the first pressure data and the second pressure data;

[0083] The protocol conversion module 1032 is configured to convert the aligned first pressure data and second pressure data into the target data according to a target protocol.

[0084] In some embodiments, due to the separability of the insole and the spliceability of the floor mat, the above-mentioned first pressure data and second pressure data are from different sensor arrays. To avoid large errors in data processing, the data alignment module 1031 uses the transmission times of the first pressure data and the second pressure data to unify the first pressure data and the second pressure data to the same time node, or makes the difference between the time nodes of the first pressure data and the second pressure data less than a preset time threshold.

[0085] In the embodiments of the present application, the protocol conversion module 1032 is specifically configured to:

[0086] Convert the aligned first pressure data and second pressure data into the target data according to the data type configuration information and data storage configuration information in the target protocol, where the target data includes a pressure data frame or a pressure data array.

[0087] In some embodiments, the above-mentioned data type configuration information is used to configure different data types for different data. The above-mentioned data storage configuration information is used to configure the data storage format. Assuming that in the case of splicing 10 floor mats (i.e., splicing 10 arrays), the time stamp is first stored in the int32 data type, and then the data of 1000 row leads in the first column is stored in the int16 data type, and then the data of 1000 row leads in the second column, and so on, until the data of 1000 rows in the 100th column. These data form a complete data frame or pressure data array (i.e., the target data). If the sampling rate is 100 Hz, it means that each second of data contains 100 such data frames.

[0088] In the embodiments of the present application, referring to Figure 6 As shown, the above-mentioned host computer module 104 includes a data preprocessing module 1041, a first data feature extraction module 1042, a second data feature extraction module 1043, and a multi-feature fusion analysis module 1044, where:

[0089] The data preprocessing module 1041 is configured to filter out environmental noise in the target data;

[0090] The first data feature extraction module 1042 is configured to extract gait cycle features according to the pressure data frame or the pressure data array;

[0091] The second data feature extraction module 1043 is configured to extract gait spatio-temporal features according to the pressure data frame or the pressure data array;

[0092] The multi-feature fusion analysis module 1044 is configured to perform feature fusion analysis on the gait cycle features and the gait spatio-temporal features according to the trained multi-feature fusion classification model to obtain the gait analysis data.

[0093] In some embodiments, the above data preprocessing module 1041 may filter out environmental noise in the target data through a preset signal filtering method. Among them, the above preset signal filtering method may be one of a median filtering method, a moving average filtering method, a Kalman filtering method, etc. The above gait cycle feature is a feature reflecting the process of a user's walking, from when the heel of the same foot leaves the ground and steps out, to when the heel touches the ground again. The above gait spatio-temporal feature refers to some features related to the movement time and movement distance during the user's walking process. The above trained multi-feature fusion classification model may be a trained multi-layer perceptron (MLP) or a convolutional neural network (CNN). For example, the training steps of the above multi-feature fusion classification model may include: collecting gait feature data with labels in a public database, and at the same time using internally and clinically collected data, calculating their gait features, and having them expert-annotated; inputting the above two types of data into an initial model (multi-layer perceptron (MLP) or convolutional neural network (CNN)); constructing a cost function of the model using the model parameters, and using the method of softmax regression to gradually adjust the model parameters to reduce the cost function; when the cost function reaches the minimum value, the model parameters at this time are the optimal model parameters, and the above multi-feature fusion classification model is obtained. Through the above multi-feature fusion classification model, gait analysis data can be directly obtained. When evaluating a user's movement disorder, the above gait analysis data may include a movement disorder evaluation result, and the above movement disorder evaluation result includes one of normal movement disorder, mild movement disorder, moderate movement disorder, and severe movement disorder.

[0094] In the embodiments of the present application, the above first data feature extraction module 1042 is specifically configured to:

[0095] Determine the time points when the states of different parts of the sole change according to the distribution positions of the pressures in the pressure data frame or the pressure data array; wherein, the state changes of different parts of the sole include heel strike, heel off, toe strike, and toe off;

[0096] Calculate the gait cycle features according to the time points; wherein, the gait cycle features include at least one of the features corresponding to the stance phase and the swing phase.

[0097] In some embodiments, since the sensor data is transmitted to the host computer in the form of a data frame (or matrix), the time points of state changes in different parts of the sole can be determined according to the distribution positions of the pressures in the above data frame (or matrix), including heel strike, heel lift, toe off, etc. For example, assuming a sampling rate of 100 Hz, the pressure data of all sensor elements in the 99th frame shows 0, and the pressure data in the 100th frame is that the pressure of the sensor elements at the heel is 1 and the pressures of the elements at other parts are 0. Then it indicates that at the 1st second, the heel starts to touch the ground, and the time point at this time is recorded as the time point when the heel starts to touch the ground.

[0098] In an alternative embodiment of the present application, taking the gait cycle characteristics of the right foot as an example, the early stance phase represents the time from the first contact of the right foot with the ground to the left toe off; the mid stance phase represents the time from the moment of left toe off to the right heel lift; the late stance phase represents the time from the right heel lift to the left foot contact with the ground; the early swing phase represents the time from the first contact of the left foot with the ground to the right toe off; the late swing phase represents the time from the right toe off to the first contact of the right foot with the ground.

[0099] In the embodiment of the present application, the above second data feature extraction module 1043 is specifically configured to:

[0100] Determine the position coordinates of different parts of the sole according to the distribution positions of the pressures in the pressure data frame or the pressure data array;

[0101] Determine the duration of state changes in different parts of the sole according to the time points of state changes in different parts of the sole;

[0102] Calculate the gait spatio-temporal characteristics according to the position coordinates of different parts of the sole and the duration of state changes in different parts of the sole; wherein, the gait spatio-temporal characteristics include at least one of the characteristics corresponding to step length, step width, stride, walking speed, and walking frequency.

[0103] Among them, the above step length can be determined according to the longitudinal straight-line distance from the heel contact point of one foot to the heel contact point of the other foot; the above stride can be determined according to the longitudinal straight-line distance between two consecutive heel contact points of the same side; the above step width can be determined according to the lateral distance between the midpoints of the heels of the left and right feet; the above walking speed can be determined by the straight-line distance of walking and the walking time; the above walking frequency can be determined by 60 / average step time.

[0104] In some embodiments, the position of the state change of different parts of the sole and the duration of each step can be determined according to the distribution position of the pressure in the above data frame (or matrix). For example, in the case of a sampling rate of 100 Hz, the first frame of data is that the sensor elements with coordinates (0, 10) and (10, 10) detect the left heel and the right heel respectively, and the 101st frame of data is that the sensor element with coordinates (10, 110) detects the right heel again, which means that after 1 second, the right foot has moved forward by the length of 100 sensor elements. If the distance between sensor elements is 5 mm and the size of the sensor element itself is also 5 mm, the corresponding stride is 10 mm * 100 = 100 cm. Other gait spatio-temporal characteristics can be calculated according to a similar method, which will not be elaborated here.

[0105] In an alternative embodiment of the present application, the system structure diagram of the above gait analysis system can be referred to Figure 7 as shown. Among them, Array 1, Array 2, and Array 3 represent the pressure sensor arrays in three floor mats. At the same time, the three floor mats are spliced in the column direction. The column lead wires of the floor mat array are connected to the analog switch (MUX) chipset. The FPGA controls the MUX to switch different column lead wires to be connected to the supply voltage (Volt Current Condenser, VCC); the row lead wires are connected to a voltage dividing resistor and then grounded. One end of the voltage dividing resistor connected to the row lead wire is connected to the ADC chipset. The ADC chip converts the analog voltage signal into a digital signal and transmits it to the FPGA. After being integrated by the FPGA, the data is uploaded to the PC host computer. The composition structure of the insole array is similar to that of the floor mat. The data of the insole is transmitted to the FPGA in real time via Bluetooth and then transmitted to the PC host computer after being integrated by the FPGA.

[0106] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0107] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0108] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the module embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other can be through some interfaces, and the indirect couplings or communication connections of devices or units can be in electrical, mechanical or other forms.

[0109] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0110] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A gait analysis system, characterized in that, it includes a first pressure sensor module, a second pressure sensor module, an FPGA processor module and a host computer module, wherein: The first pressure sensor module is used to collect first pressure data generated when a user walks on a first sensor array; The second pressure sensor module is used to collect second pressure data generated when the user walks while wearing a second sensor array; The FPGA processor module is used to simultaneously receive the first pressure data and the second pressure data, convert the first pressure data and the second pressure data into target data according to a target protocol, and transmit the target data to the host computer module; The host computer module is used to process the target data to obtain gait analysis data.

2. The gait analysis system according to claim 1, characterized in that, The first pressure sensor module further includes a first analog-to-digital conversion module and a first analog switch module, wherein: The first analog switch module is used to receive a first data acquisition instruction sent by the FPGA processor module, and switch sensor elements in the first sensor array according to the first data acquisition instruction; The first analog-to-digital conversion module is used to collect first pressure data generated when the user walks while wearing the first sensor array according to the first data acquisition instruction.

3. The gait analysis system according to claim 2, characterized in that, The first sensor array is composed of sensor elements arranged in m rows and n columns, where m and n are both integers greater than 1. The sensor elements in the same row of the first sensor array share a row lead wire, and the sensor elements in the same column of the first sensor array share a column lead wire.

4. The gait analysis system according to claim 3, characterized in that, The first pressure sensor module is specifically used for: The first analog switch module receives a first data acquisition instruction sent by the FPGA processor module, where the first data acquisition instruction includes a set sampling frequency; The first analog switch module switches the column lead wires in the first sensor array according to the sampling frequency; The first analog-to-digital conversion module performs parallel data acquisition on all row lead wires in the first sensor array when the column lead wires are switched; The first analog-to-digital conversion module summarizes all the collected data to obtain the first pressure data when all the column lead wires in the first sensor array have been traversed.

5. The gait analysis system according to any one of claims 1-4, characterized in that, The sensor element density of the first sensor array is less than the sensor element density of the second sensor array.

6. The gait analysis system according to any one of claims 1-4, characterized in that, The FPGA processor module includes a data alignment module and a protocol conversion module, wherein: The data alignment module is used to perform data alignment according to the sending times of the first pressure data and the second pressure data; The protocol conversion module is used to convert the aligned first pressure data and second pressure data into the target data according to the target protocol.

7. The gait analysis system according to claim 6, wherein, the protocol conversion module is specifically used for: converting the aligned first pressure data and second pressure data into the target data according to the data type configuration information and data storage configuration information in the target protocol, wherein the target data includes a pressure data frame or a pressure data array.

8. The gait analysis system according to claim 7, wherein, the host computer module includes a data preprocessing module, a first data feature extraction module, a second data feature extraction module, and a multi-feature fusion analysis module, wherein: the data preprocessing module is used to filter out environmental noise in the target data; the first data feature extraction module is used to extract gait cycle features according to the pressure data frame or the pressure data array; the second data feature extraction module is used to extract gait spatio-temporal features according to the pressure data frame or the pressure data array; the multi-feature fusion analysis module is used to perform feature fusion analysis on the gait cycle features and the gait spatio-temporal features according to a trained multi-feature fusion classification model to obtain the gait analysis data.

9. The gait analysis system according to claim 8, wherein, the first data feature extraction module is specifically used for: determining the time points when the states of different parts of the sole change according to the distribution positions of the pressures in the pressure data frame or the pressure data array; wherein the state changes of different parts of the sole include heel strike, heel off, toe strike, and toe off; calculating the gait cycle features according to the time points; wherein the gait cycle features include at least one of the features corresponding to the stance phase and the swing phase.

10. The gait analysis system according to claim 9, wherein, the second data feature extraction module is specifically used for: determining the position coordinates of different parts of the sole according to the distribution positions of the pressures in the pressure data frame or the pressure data array; determining the duration of the state change of different parts of the sole according to the time points when the state of different parts of the sole changes; calculating the gait spatio-temporal features according to the position coordinates of different parts of the sole and the duration of the state change of different parts of the sole; wherein the gait spatio-temporal features include at least one of the features corresponding to step length, step width, stride length, walking speed, and walking frequency.

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