A gait assessment method, system and intelligent terminal based on 3D simulation

Abstract

The present invention relates to a gait evaluation method, system and intelligent terminal based on three-dimensional simulation, belonging to the technical field of gait evaluation, and includes: obtaining image detection information of a patient's leg; analyzing and determining the detection strip inspection shape information of a detection strip preset on the patient's leg according to the image detection information; establishing a three-dimensional model based on the detection strip inspection shape information to form leg simulation model information; analyzing the changes between the leg simulation model information at different times to form leg change situation information; inputting the leg change situation information into a preset gait evaluation neural network model to form gait evaluation result information, and outputting the gait evaluation result information to a display terminal. The present invention has the effect of improving the accuracy of the gait evaluation result.

Description

Technical Field

[0001] The present invention relates to the technical field of gait assessment, and in particular, to a gait assessment method, system and intelligent terminal based on three-dimensional simulation. Background Art

[0002] Gait assessment is a method for evaluating gait characteristics and body balance when people walk. It evaluates an individual's motor function and health status by analyzing the movement patterns during walking, including muscle contraction, bone movement, joint activity, and the coordination and control of the nervous system.

[0003] Currently, when performing gait assessment on patients with leg paralysis, marker points are pre-placed on the joints of the patients, and high-speed cameras or infrared cameras are used to capture the movement trajectories of these marker points, so as to accurately record the positions and movement states of each joint of the human body, and analyze the kinematic characteristics such as joint angles, speeds, and accelerations of the patients based on the movement trajectories of the marker points, and then determine the gait characteristics of the patients to perform gait assessment on the patients.

[0004] Since marker points are placed on the joints of the patients during current gait assessment, when the posture of the patients during walking has been deformed, etc., the movement trajectories of the joint positions are not easy to accurately reflect, resulting in inaccurate gait assessment results. Summary of the Invention

[0005] In order to improve the accuracy of gait assessment results, the present invention provides a gait assessment method, system and intelligent terminal based on three-dimensional simulation.

[0006] In the first aspect, the present invention provides a gait assessment method based on three-dimensional simulation, adopting the following technical solution:

[0007] A gait assessment method based on three-dimensional simulation includes:

[0008] Obtaining image detection information of a patient's leg;

[0009] Analyzing and determining the inspection shape information of a detection strip preset on the patient's leg according to the image detection information;

[0010] Based on the inspection shape information of the detection strip, establishing a three-dimensional model to form leg simulation model information;

[0011] Analyzing the changes between the leg simulation model information at different times to form leg change situation information;

[0012] Inputting the leg change situation information into a preset gait assessment neural network model to form gait assessment result information, and outputting the gait assessment result information to a display terminal.

[0013] Optionally, the method for determining the inspection shape information of the detection strip includes:

[0014] Retrieve the lateral reflection information and the frontal reflection information based on the reflection image detection information;

[0015] Retrieve the lateral reflection intensity value based on the lateral reflection information;

[0016] Determine the lateral inspection shape information according to the judgment result of the lateral reflection intensity value and the preset reflection reference intensity value;

[0017] Analyze the frontal reflection information to determine the frontal inspection shape information;

[0018] Combine the lateral inspection shape information and the frontal inspection shape information to form the inspection comprehensive shape information, and use the inspection comprehensive shape information as the detection strip inspection shape information.

[0019] Optionally, the method for determining the lateral inspection shape information includes:

[0020] Retrieve the lateral reflection shape information based on the lateral reflection information;

[0021] Determine the initial lateral inspection shape information corresponding to the lateral reflection shape information according to the corresponding relationship between the lateral reflection shape information and the preset initial lateral inspection shape;

[0022] Judge whether the lateral reflection intensity values are all greater than the preset reflection reference intensity value;

[0023] If so, use the initial lateral inspection shape information as the lateral inspection shape information;

[0024] If not, retrieve the position points corresponding to the lateral reflection intensity values not greater than the preset reflection reference intensity value based on the lateral reflection information and use them as the reflection abnormal position points;

[0025] Analyze the reflection abnormal position points and the initial lateral inspection shape information to determine the reflection abnormal shape influence information;

[0026] Combine the initial lateral inspection shape information and the reflection abnormal shape influence information to determine the lateral inspection shape adjustment information, and use the lateral inspection shape adjustment information as the lateral inspection shape information.

[0027] Optionally, the method for determining the reflection abnormal shape influence information includes:

[0028] Determine the initial shape area information corresponding to the initial lateral inspection shape information according to the corresponding relationship between the initial lateral inspection shape information and the preset initial shape area information;

[0029] Retrieve the contour position points of the initial shape region based on the initial shape region information;

[0030] Analyze based on the reflection anomaly position points and the contour position points of the initial shape region to determine the information on the relative contour position of the anomaly;

[0031] Based on the corresponding relationship between the information on the relative contour position of the anomaly and the preset relative position influence information, determine the relative position influence information corresponding to the information on the relative contour position of the anomaly, and use the relative position influence information as the reflection anomaly shape influence information.

[0032] Optionally, the method for determining the information on the relative contour position of the anomaly includes:

[0033] When and only when the number corresponding to the reflection anomaly position points is less than the preset reference value of the number of anomaly positions, select the contour position points of the initial shape region with the closest distance based on the reflection anomaly position points and use them as the anomaly closest contour position points;

[0034] Calculate the distance between the reflection anomaly position points and the anomaly closest contour position points and use it as the anomaly contour distance value;

[0035] Analyze based on the reflection anomaly position points and the contour position points of the initial shape region to determine the relative direction information of the anomaly contour;

[0036] Calculate the angular values between the relative direction information of each anomaly contour and use it as the relative direction included angle value;

[0037] Judge whether the relative direction included angle value is all within the preset same-direction reference included angle interval;

[0038] If so, combine the anomaly contour distance value with the preset relative position information outside the contour to form the information on the relative contour position of the anomaly;

[0039] If not, analyze based on the anomaly contour distance value to determine the relative position information inside the contour, and use the relative position information inside the contour as the information on the relative contour position of the anomaly.

[0040] Optionally, the method for determining the relative position information inside the contour includes:

[0041] Select the contour position points of the initial shape region corresponding to those not within the preset same-direction reference included angle interval based on the relative direction included angle value and use them as the included angle contour position points;

[0042] Analyze based on the included angle contour position points and the reflection anomaly position points to determine the anomaly contour distance reference value;

[0043] Judge whether the anomaly contour distance value is greater than the anomaly contour distance reference value;

[0044] If it is yes, output the preset reference position information within the contour and use it as the relative position information within the contour;

[0045] If it is no, combine the abnormal contour distance value with the preset relative reference position information within the contour to form the relative position information within the contour.

[0046] Optionally, the method for determining the abnormal contour distance reference value includes:

[0047] Analyze according to the included angle contour position points to determine the length reference direction information;

[0048] According to the corresponding relationship between the length reference direction information and the preset width reference direction information, determine the width reference direction information corresponding to the length reference direction information;

[0049] Based on the reflected abnormal position points, select the initial shape area contour position points on the width reference direction information and use them as the width contour position points;

[0050] Calculate the distance between the width contour position points and use it as the width distance value;

[0051] According to the corresponding relationship between the width distance value and the preset abnormal contour distance reference value, determine the abnormal contour distance reference value corresponding to the width distance value.

[0052] Optionally, the method for determining the front inspection shape information includes:

[0053] Retrieve the front reflection position points based on the front reflection information;

[0054] Perform curve analysis according to the front reflection position points to form a front reflection curve;

[0055] According to the corresponding relationship between the front reflection curve and the preset initial front inspection shape information, determine the initial front inspection shape information corresponding to the front reflection curve;

[0056] Obtain the pressure detection information on the detection strip;

[0057] According to the deviation situation between the pressure detection information and the preset pressure detection reference information, determine the pressure deviation influence information;

[0058] Combine the initial front inspection shape information and the pressure deviation influence information to form the front inspection shape adjustment information, and use the front inspection shape adjustment information as the front inspection shape information.

[0059] In a second aspect, the present invention provides a gait evaluation system based on 3D simulation, adopting the following technical solutions:

[0060] A gait assessment system based on 3D simulation, comprising:

[0061] An acquisition module, configured to acquire image detection information and pressure detection information;

[0062] A memory, configured to store a program of the gait assessment method based on 3D simulation as described in the first aspect;

[0063] A processor, configured to load and execute the program in the memory and implement the gait assessment method based on 3D simulation as described in the first aspect.

[0064] In a third aspect, the present invention provides an intelligent terminal, adopting the following technical solution:

[0065] An intelligent terminal, comprising a memory and a processor, wherein a computer program capable of being loaded and executed by the processor and implementing the gait assessment method based on 3D simulation as described in the first aspect is stored on the memory.

[0066] In summary, the present invention includes at least one of the following beneficial technical effects:

[0067] 1. By acquiring and analyzing the image detection information to determine the inspection shape information of the detection strip, then establishing a 3D model based on the inspection shape information of the detection strip to form leg simulation model information, and analyzing to form leg change situation information, and inputting the leg change situation information into a preset gait assessment neural network model to form gait assessment result information and outputting it to a display terminal, so as to evaluate the gait through the transformation of the entire leg, thereby improving the accuracy of the gait assessment result;

[0068] 2. By retrieving the lateral reflection information and the front reflection information from the reflected image detection information, retrieving the lateral reflection intensity value through the lateral reflection information, then analyzing the judgment result of the lateral reflection intensity value and a preset reflection reference intensity value to determine the lateral inspection shape information, analyzing to determine the front inspection shape information through the front reflection information, then combining the lateral inspection shape information and the front inspection shape information to form inspection comprehensive shape information, and using the inspection comprehensive shape information as the inspection shape information of the detection strip, thereby improving the accuracy of the obtained inspection shape information of the detection strip;

[0069] 3. Retrieve the lateral reflection shape information through the lateral reflection information, query and determine the initial lateral inspection shape information based on the lateral reflection shape information, and determine whether the lateral reflection intensity values are all greater than the preset reflection reference intensity value. When it is greater, use the initial lateral inspection shape information as the lateral inspection shape information. When it is not greater, retrieve the reflection abnormal position points through the lateral reflection information, and analyze and determine the reflection abnormal shape influence information based on the reflection abnormal position points and the initial lateral inspection shape information. Then, combine the initial lateral inspection shape information with the reflection abnormal shape influence information to determine the lateral inspection shape adjustment information, and use the lateral inspection shape adjustment information as the lateral inspection shape information, thereby improving the accuracy of the obtained lateral inspection shape information. Brief Description of the Drawings

[0070] Figure 1 is the flowchart of the method for gait assessment based on 3D simulation according to an embodiment of the present application;

[0071] Figure 2 is the flowchart of the method for determining the inspection strip inspection shape information according to an embodiment of the present application;

[0072] Figure 3 is the flowchart of the method for determining the lateral inspection shape information according to an embodiment of the present application;

[0073] Figure 4 is the flowchart of the method for determining the reflection abnormal shape influence information according to an embodiment of the present application;

[0074] Figure 5 is the flowchart of the method for determining the abnormal relative contour position information according to an embodiment of the present application;

[0075] Figure 6 is the flowchart of the method for determining the relative position information within the contour according to an embodiment of the present application;

[0076] Figure 7 is the flowchart of the method for determining the abnormal contour distance reference value according to an embodiment of the present application;

[0077] Figure 8 is the flowchart of the method for determining the front inspection shape information according to an embodiment of the present application. Detailed Description of the Embodiment

[0078] The present invention will be further described in detail below in conjunction with the drawings and embodiments.

[0079] A gait evaluation method based on three-dimensional simulation, which acquires image detection information and pressure detection information, analyzes and determines the inspection shape information of the detection strip, establishes a three-dimensional model to form leg simulation model information, analyzes and forms leg change information, inputs it into a preset gait evaluation neural network model to form gait evaluation result information, and outputs it to a display terminal, so as to evaluate the gait through the transformation of the entire leg, thereby improving the accuracy of the gait evaluation result.

[0080] An embodiment of the present invention discloses a gait evaluation method based on three-dimensional simulation. Refer to Figure 1 , a gait evaluation method based on three-dimensional simulation includes:

[0081] Refer to Figure 1 , a gait evaluation method based on three-dimensional simulation includes:

[0082] Step S100: Acquire the image detection information of the patient's leg.

[0083] Among them, the image detection information refers to the image information collected and detected for the patient's leg. The image detection information is obtained by a camera preset at the collection position when the patient stands at the required detection position. The collection position is located around the position where the patient stands for detection, so as to facilitate image collection and detection of the patient's leg.

[0084] Step S200: Analyze and determine the inspection shape information of the detection strip preset on the patient's leg according to the image detection information.

[0085] Among them, the inspection shape information of the detection strip refers to the shape information of the detection strip when the patient is walking. The detection strip is preset on the patient's leg through an elastic band and can change its own shape under force to measure the changes of the leg when the patient is walking. The detection strip is provided on both the thigh and the calf of the patient's leg, and four detection strips are provided on both the thigh and the calf and are distributed around. There are various specifications for the length of the detection strip, so as to facilitate the selection of detection strips suitable for the lengths of the thigh and calf of the patient's leg. The detection strip can emit light by itself or be made of a reflective material, and after the light is irradiated onto the detection strip by an irradiation device preset around the position where the patient stands for detection, it reflects light, so as to facilitate the detection of the detection strip. In this embodiment, the detection strip is made of a reflective material, and after the light is irradiated onto the detection strip by an irradiation device preset around the position where the patient stands for detection, it reflects light.

[0086] By using the preset detection strip features to identify the image detection information, the inspection shape information of the detection strip is determined, which is convenient for subsequent use. The detection strip features refer to the appearance and parameter features corresponding to detection strips of different specifications and sizes, and the detection strip features are obtained after being pre-input by the operator.

[0087] Step S200: Based on the shape information checked by the detection strip, a three-dimensional model is established to form leg simulation model information.

[0088] Among them, the leg simulation model information refers to the model information after three-dimensional model simulation of the patient's leg. The leg simulation model information is obtained by inputting the shape information checked by the detection strip into the three-dimensional model simulation software.

[0089] Step S400: Analyze the changes between the leg simulation model information at different times to form leg change situation information.

[0090] Among them, the leg change situation information refers to the change situation information corresponding to the changes that occur in the patient's leg during walking. The leg change situation information is formed by analyzing the changes between the leg simulation model information at different times, which is convenient for subsequent use.

[0091] Step S500: Input the leg change situation information into a preset gait evaluation neural network model to form gait evaluation result information, and output the gait evaluation result information to a display terminal.

[0092] Among them, the gait evaluation result information refers to the result information for evaluating the gait corresponding to the patient during walking. The gait evaluation neural network model is a neural network model used to analyze the leg change situation information to form the gait evaluation result. The gait evaluation neural network model is obtained by the operator pre-inputting a large amount of leg change situation information for neural network training. By inputting the leg change situation information into the preset gait evaluation neural network model to form the gait evaluation result information and outputting the gait evaluation result information to the display terminal, the gait is evaluated based on the changes in the entire leg, thereby improving the accuracy of the gait evaluation result.

[0093] Furthermore, to facilitate the patient's rehabilitation training, after step S500, the following steps are also included.

[0094] Step S600: According to the correspondence between the gait evaluation result information and the preset gait adjustment prompt information, determine the gait adjustment prompt information corresponding to the gait evaluation result information, and output the gait adjustment prompt information to the display terminal.

[0095] Among them, the gait adjustment prompt information refers to the prompt information used to prompt the patient to adjust the gait. The gait adjustment prompt information is obtained by querying from a database storing the correspondence between gait evaluation result information and gait adjustment prompt information, and the database is obtained through pre-input by the operator. The gait adjustment prompt information is determined by querying the gait evaluation result information and output to the display terminal, so as to prompt the patient to adjust the gait in time, and then facilitate the patient's rehabilitation training.

[0096] In Figure 1 In the step S200 shown, in order to further ensure the rationality of the detection strip inspection shape information, it is necessary to perform a further separate analysis and calculation on the detection strip inspection shape information, specifically through Figure 2 the steps shown for detailed description.

[0097] Referring to Figure 2 , the method for determining the detection strip inspection shape information includes the following steps:

[0098] Step S210: Retrieve the lateral reflection information and the front reflection information based on the reflection image detection information.

[0099] Among them, the lateral reflection information refers to the reflection situation information corresponding to the detection strips located on both sides of the patient, and the front reflection information refers to the reflection situation information of the detection strip in front of the patient. Retrieving the lateral reflection information and the front reflection information through the reflection image detection information facilitates subsequent use.

[0100] Step S220: Retrieve the lateral reflection intensity value based on the lateral reflection information.

[0101] Among them, the lateral reflection intensity value refers to the intensity value of the reflected light brightness of the detection strips on both sides of the patient. Retrieving the lateral reflection intensity value through the lateral reflection information facilitates subsequent use.

[0102] Step S230: Determine the lateral inspection shape information according to the judgment result of the lateral reflection intensity value and the preset reflection reference intensity value.

[0103] Among them, the reflection reference intensity value refers to the minimum intensity value corresponding to the brightness when the detection strips on both sides of the patient are normally reflected by light, and the reflection reference intensity value is obtained through pre-input by the operator. The lateral inspection shape information refers to the shape information corresponding to the detection strips on both sides of the patient. By analyzing the judgment result of the lateral reflection intensity value and the preset reflection reference intensity value, the lateral inspection shape information is determined to facilitate subsequent use.

[0104] Step S240: Analyze according to the front reflection information to determine the front inspection shape information.

[0105] Among them, the frontal inspection shape information refers to the shape information corresponding to the detection strips on the front of the patient. By analyzing the frontal reflection information, the frontal inspection shape information is determined to facilitate subsequent use.

[0106] Step S250: Combine the lateral inspection shape information and the frontal inspection shape information to form comprehensive inspection shape information, and use the comprehensive inspection shape information as the detection strip inspection shape information.

[0107] Among them, the comprehensive inspection shape information refers to the comprehensive shape information of the detection strips on the patient's legs when walking. By combining the lateral inspection shape information and the frontal inspection shape information to form the comprehensive inspection shape information, and using the comprehensive inspection shape information as the detection strip inspection shape information, the accuracy of the obtained detection strip inspection shape information is improved.

[0108] In Figure 2 In step S230 shown, in order to further ensure the rationality of the lateral inspection shape information, it is necessary to perform a further separate analysis and calculation on the lateral inspection shape information. Specifically, it is described in detail through the Figure 3 steps shown.

[0109] Referring to Figure 3 , the method for determining the lateral inspection shape information includes the following steps:

[0110] Step S231: Retrieve the lateral reflection shape information based on the lateral reflection information.

[0111] Among them, the lateral reflection shape information refers to the shape information of the area covered by the detection strips on both sides of the patient after reflecting light. By retrieving the lateral reflection shape information through the lateral reflection information, it is convenient for subsequent use.

[0112] Step S232: Determine the initial lateral inspection shape information corresponding to the lateral reflection shape information according to the correspondence between the lateral reflection shape information and the preset initial lateral inspection shape.

[0113] Among them, the initial lateral inspection shape information refers to the initial shape information corresponding to the detection strips on both sides of the patient based on the lateral reflection shape. The initial lateral inspection shape information is obtained by querying a database that stores the correspondence between the lateral reflection shape information and the initial lateral inspection shape information, which is obtained through pre-input by the operator. Determining the initial lateral inspection shape information through querying the lateral reflection shape information is convenient for subsequent use.

[0114] Step S233: Determine whether the lateral reflection intensity values are all greater than the preset reflection reference intensity value. If yes, execute step S234. If no, execute step S235.

[0115] Among them, by determining whether the lateral reflection intensity values are all greater than a preset reflection reference intensity value, it is judged whether there is a position with abnormal reflection on the test strip.

[0116] Step S234: Use the initial lateral inspection shape information as the lateral inspection shape information.

[0117] Among them, when the lateral reflection intensity values are all greater than the preset reflection reference intensity value, it indicates that there is no position with abnormal reflection on the test strip at this time. Therefore, the initial lateral inspection shape information is used as the lateral inspection shape information, thereby improving the accuracy of the obtained lateral inspection shape information.

[0118] Step S235: Based on the lateral reflection information, retrieve the position points corresponding to the lateral reflection intensity values that are not greater than the preset reflection reference intensity value and use them as abnormal reflection position points.

[0119] Among them, the abnormal reflection position point refers to the position point where the position with abnormal reflection on the test strip is located. When the lateral reflection intensity values are not all greater than the preset reflection reference intensity value, it indicates that there is a position with abnormal reflection on the test strip at this time. Therefore, through the lateral reflection information, the position points corresponding to the lateral reflection intensity values that are not greater than the preset reflection reference intensity value are retrieved and used as abnormal reflection position points, thereby facilitating subsequent use.

[0120] Step S236: Analyze based on the abnormal reflection position points and the initial lateral inspection shape information to determine the abnormal reflection shape influence information.

[0121] Among them, the abnormal reflection shape influence information refers to the influence information on the shape of the test strip caused by the position with abnormal reflection on the test strip. By analyzing the abnormal reflection position points and the initial lateral inspection shape information, the abnormal reflection shape influence information is determined, facilitating subsequent use.

[0122] Step S237: Combine the initial lateral inspection shape information and the abnormal reflection shape influence information to determine the lateral inspection shape adjustment information, and use the lateral inspection shape adjustment information as the lateral inspection shape information.

[0123] Among them, the lateral inspection shape adjustment information refers to the adjustment information for adjusting the shape of the test strips on both sides of the patient. By combining the initial lateral inspection shape information and the abnormal reflection shape influence information to determine the lateral inspection shape adjustment information, and using the lateral inspection shape adjustment information as the lateral inspection shape information, the accuracy of the obtained lateral inspection shape information is improved.

[0124] In Figure 3In step S236 shown above, in order to further ensure the rationality of the information on the influence of the abnormal reflection shape, it is necessary to perform further separate analysis and calculation on the information on the influence of the abnormal reflection shape. Specifically, it is described in detail through Figure 4 the steps shown below.

[0125] Referring to Figure 4 , the method for determining the information on the influence of the abnormal reflection shape includes the following steps:

[0126] Step S2361: Determine the initial shape area information corresponding to the initial shape information of the side inspection according to the corresponding relationship between the initial shape information of the side inspection and the preset initial shape area information.

[0127] Among them, the initial shape area information refers to the area information corresponding to the initial shape of the detection strip. The initial shape area information is obtained by querying from a database storing the corresponding relationship between the initial shape information of the side inspection and the initial shape area information. This database is obtained through pre-input by the operator. Querying and determining the initial shape area information through the initial shape information of the side inspection facilitates subsequent use.

[0128] Step S2362: Retrieve the contour position points of the initial shape area based on the initial shape area information.

[0129] Among them, the contour position points of the initial shape area refer to the contour position points of the area corresponding to the initial shape of the detection strip. Retrieving the contour position points of the initial shape area through the initial shape area information facilitates subsequent use.

[0130] Step S2363: Analyze based on the abnormal reflection position points and the contour position points of the initial shape area to determine the information on the relative contour position of the abnormality.

[0131] Among them, the information on the relative contour position of the abnormality refers to the information indicating the relative position between the abnormal position of the detection strip and the contour of the detection strip. By analyzing the abnormal reflection position points and the contour position points of the initial shape area, the information on the relative contour position of the abnormality is determined, which facilitates subsequent use.

[0132] Step S2364: Determine the relative position influence information corresponding to the information on the relative contour position of the abnormality according to the corresponding relationship between the information on the relative contour position of the abnormality and the preset relative position influence information, and use the relative position influence information as the information on the influence of the abnormal reflection shape.

[0133] Among them, the relative position influence information refers to the influence information on the shape of the detection strip caused by the relative position between the abnormal position of the detection strip and the contour of the detection strip. The relative position influence information is obtained by querying from a database storing the correspondence between the abnormal relative contour position information and the relative position influence information, and this database is obtained through pre-input by the operator. The relative position influence information is determined by querying through the abnormal relative contour position information, and the relative position influence information is used as the reflection abnormal shape influence information, thereby improving the accuracy of the obtained reflection abnormal shape influence information.

[0134] In Figure 4 In the step S2363 shown, in order to further ensure the rationality of the abnormal relative contour position information, it is necessary to perform a further separate analysis and calculation on the abnormal relative contour position information, specifically through Figure 5 the steps shown for detailed description.

[0135] Referring to Figure 5 , the method for determining the abnormal relative contour position information includes the following steps:

[0136] Step S23631: When and only when the number corresponding to the reflection abnormal position points is less than the preset abnormal position reference value, select the initial shape region contour position points with the closest distance based on the reflection abnormal position points and use them as the abnormal closest contour position points.

[0137] Among them, the abnormal position reference value refers to the maximum reference value that the detection strip can tolerate when there are abnormalities, and the abnormal position reference value is obtained through pre-input by the operator. When the number corresponding to the reflection abnormal position points is not less than the preset abnormal position reference value, it indicates that there are multiple abnormalities on the detection strip at this time, and there may be situations such as detection strip damage or incorrect installation of the detection strip. At this time, output the preset detection strip abnormal warning information for warning. The detection strip abnormal warning information refers to the warning information used to warn of abnormalities on the detection strip, and the detection strip abnormal warning information is obtained through pre-input by the operator. When and only when the number corresponding to the reflection abnormal position points is less than the preset abnormal position reference value, it indicates that the detection strip is normal at this time. Select the initial shape region contour position points with the closest distance through the reflection abnormal position points and use them as the abnormal closest contour position points for subsequent use.

[0138] Step S23632: Calculate the distance between the reflection abnormal position points and the abnormal closest contour position points and use it as the abnormal contour distance value.

[0139] Among them, the abnormal contour distance value refers to the distance value between the abnormal position and the closest contour, and the distance between the reflection abnormal position points and the abnormal closest contour position points is calculated and used as the abnormal contour distance value.

[0140] Step S23633: Analyze based on the reflection anomaly position points and the initial shape area contour position points to determine the relative direction information of the abnormal contour.

[0141] Among them, the relative direction information of the abnormal contour refers to the relative direction information of the abnormal position on the detection strip with respect to the contour points of the detection strip shape. By analyzing the reflection anomaly position points and the initial shape area contour position points, the relative direction information of the abnormal contour is determined according to the angle value between the straight line corresponding to the reflection anomaly position points and the initial shape area contour position points and a preset reference straight line, which is convenient for subsequent use.

[0142] Step S23634: Calculate the angle values between the relative direction information of each abnormal contour and use them as the relative direction included angle values.

[0143] Among them, the relative direction included angle value refers to the included angle value between the directions formed by the abnormal position on the detection strip and each position point on the detection strip shape contour. By calculating the angle values between the relative direction information of each abnormal contour and using them as the relative direction included angle values, it is convenient for subsequent use.

[0144] Step S23635: Determine whether the relative direction included angle values are all within a preset same-direction reference included angle interval. If yes, execute Step S23636; if no, execute Step S23637.

[0145] Among them, the same-direction reference included angle interval refers to the reference included angle interval used to indicate that the directions formed by the abnormal position on the detection strip and each position point on the detection strip shape contour are in the same direction. The same-direction reference included angle interval is obtained by querying from a database storing the same-direction reference included angle interval. By judging whether the relative direction included angle values are all within the preset same-direction reference included angle interval, it is thus judged whether the abnormal position on the detection strip is inside the detection strip shape contour.

[0146] Step S23636: Combine the abnormal contour distance value with the preset relative reference position information outside the contour to form the abnormal relative contour position situation information.

[0147] Among them, the relative reference position information outside the contour refers to the reference position situation information used to indicate that the abnormal position on the detection strip is outside the detection strip shape contour. The relative reference position information outside the contour is obtained through pre-input by the operator. When the relative direction included angle values are all within the preset same-direction reference included angle interval, it indicates that the abnormal position on the detection strip is outside the detection strip shape contour at this time. Therefore, the abnormal contour distance value is combined with the preset relative reference position information outside the contour to form the abnormal relative contour position situation information, thereby improving the accuracy of the obtained abnormal relative contour position situation information.

[0148] Step S23637: Analyze according to the abnormal contour distance value to determine the relative position information inside the contour, and use the relative position information inside the contour as the abnormal relative contour position information.

[0149] Among them, the relative position information inside the contour refers to the position information when the abnormal position on the detection strip is inside the shape contour of the detection strip. When the relative direction angle values are not all within the preset same-direction reference angle interval, it indicates that the abnormal position on the detection strip is inside the shape contour of the detection strip at this time. Therefore, by analyzing the abnormal contour distance value, the relative position information inside the contour is determined, and the relative position information inside the contour is used as the abnormal relative contour position information, thereby improving the accuracy of the obtained abnormal relative contour position information.

[0150] In Figure 5 the shown Step S23637, in order to further ensure the rationality of the relative position information inside the contour, it is necessary to perform a further separate analysis and calculation on the relative position information inside the contour, specifically through Figure 6 the shown steps for detailed description.

[0151] Referring to Figure 6 , the method for determining the relative position information inside the contour includes the following steps:

[0152] Step S236371: Based on the relative direction angle value, select the initial shape area contour position points corresponding to those not within the preset same-direction reference angle interval and use them as the angle contour position points.

[0153] Step S236372: Analyze according to the angle contour position points and the reflected abnormal position points to determine the abnormal contour distance reference value.

[0154] Among them, the abnormal contour distance reference value refers to the minimum reference distance value corresponding to the situation where the distance between the abnormal position and the contour position has no influence. By analyzing the angle contour position points and the reflected abnormal position points, the abnormal contour distance reference value is determined for convenient subsequent use.

[0155] Step S236373: Judge whether the abnormal contour distance value is greater than the abnormal contour distance reference value. If yes, execute Step S236374; if no, execute Step S236375.

[0156] Among them, by judging whether the abnormal contour distance value is greater than the abnormal contour distance reference value, it is judged whether the distance between the abnormal position and the contour position will affect the subsequent shape.

[0157] Step S236374: Output the preset relative position information inside the contour and use it as the relative position information inside the contour.

[0158] Among them, the reference position information within the contour refers to the reference position information that will not have an impact within the contour, and the reference position information within the contour is retrieved from the database storing the reference position information within the contour. When the abnormal contour distance value is greater than the abnormal contour distance reference value, it indicates that the distance between the abnormal position and the contour position at this time will not affect the subsequent shape. Therefore, the preset reference position information within the contour is output and used as the relative position information within the contour, thereby improving the accuracy of the obtained relative position information within the contour.

[0159] Step S236375: Combine the abnormal contour distance value with the preset relative reference position information within the contour to form the relative position information within the contour.

[0160] Among them, the relative reference position information within the contour refers to the relative reference position information when the abnormality is within the contour, and the relative reference position information within the contour is obtained through pre-input by the operator. When the abnormal contour distance value is not greater than the abnormal contour distance reference value, it indicates that the distance between the abnormal position and the contour position at this time will affect the subsequent shape. Therefore, the abnormal contour distance value is combined with the preset relative reference position information within the contour to form the relative position information within the contour, thereby improving the accuracy of the obtained relative position information within the contour.

[0161] In Figure 6 In step S236372 shown, in order to further ensure the rationality of the abnormal contour distance reference value, it is necessary to perform a further separate analysis and calculation on the abnormal contour distance reference value, specifically through Figure 7 the steps shown for detailed description.

[0162] Referring to Figure 7 , the method for determining the abnormal contour distance reference value includes the following steps:

[0163] Step S2363721: Analyze based on the included angle contour position points to determine the length reference direction information.

[0164] Among them, the length reference direction information refers to the reference direction information of the length of the detection strip. By sorting the relative direction included angle values not within the preset same-direction reference included angle interval from large to small, and performing distance vector calculation on the initial shape area contour position points corresponding to the first sorted relative direction included angle value, the length reference direction information is determined for convenient subsequent use.

[0165] Step S2363722: Determine the width reference direction information corresponding to the length reference direction information according to the correspondence between the length reference direction information and the preset width reference direction information.

[0166] Among them, the width reference direction information refers to the reference direction information of the width of the detection strip. The width reference direction information is obtained by querying from a database storing the correspondence between the length reference direction information and the width reference direction information, and this database is obtained through pre-input by the operator. Querying and determining the width reference direction information based on the length reference direction information facilitates subsequent use.

[0167] Step S2363723: Select the initial shape region contour position points on the width reference direction information based on the reflection anomaly position points and use them as the width contour position points.

[0168] Among them, the width contour position points refer to the position points where the reflection anomaly position points intersect the contour in the width direction. By using the reflection anomaly position points to select the initial shape region contour position points on the width reference direction information and using them as the width contour position points, it facilitates subsequent use.

[0169] Step S2363724: Calculate the distance between the width contour position points and use it as the width distance value.

[0170] Among them, the width distance value refers to the distance value between two width contour position points of the reflection anomaly position points in the width direction. By calculating the distance between the width contour position points and using it as the width distance value, it facilitates subsequent use.

[0171] Step S2363725: Determine the abnormal contour distance reference value corresponding to the width distance value according to the correspondence between the width distance value and the preset abnormal contour distance reference value.

[0172] Among them, the abnormal contour distance reference value refers to the reference distance value that can tolerate the distance between the abnormal position and the contour based on the width of the detection strip. The abnormal contour distance reference value is obtained by querying from a database storing the correspondence between the width distance value and the abnormal contour distance reference value, and this database is obtained through pre-input by the operator. Querying and determining the abnormal contour distance reference value based on the width distance value facilitates subsequent use.

[0173] In Figure 2 shown in step S240, in order to further ensure the rationality of the front inspection shape information, it is necessary to perform a further separate analysis and calculation on the front inspection shape information, specifically through Figure 8 the steps shown for detailed description.

[0174] Referring to Figure 8 , the determination method of the front inspection shape information includes the following steps:

[0175] Step S241: Retrieve the front reflection position points based on the front reflection information.

[0176] Among them, the front reflection position point refers to the position point corresponding to the reflected light of the test strip on the front of the patient, and the front reflection position point is obtained by querying from a database storing the front reflection position points.

[0177] Step S242: Perform curve analysis based on the front reflection position points to form a front reflection curve.

[0178] Among them, the front reflection curve refers to the curve formed by the reflection positions of the test strip on the front of the patient. By performing curve analysis on the front reflection position points, a front reflection curve is formed, which is convenient for subsequent use.

[0179] Step S243: Determine the initial front inspection shape information corresponding to the front reflection curve according to the correspondence between the front reflection curve and the preset initial front inspection shape information.

[0180] Among them, the initial front inspection shape information refers to the initial shape information of the test strip on the front of the patient. The initial front inspection shape information is obtained by querying from a database storing the correspondence between the front reflection curve and the initial front inspection shape information, and this database is obtained through pre-input by the operator. Querying and determining the initial front inspection shape information through the front reflection curve is convenient for subsequent use.

[0181] Step S244: Obtain the pressure detection information on the test strip.

[0182] Among them, the pressure detection information refers to the pressure information detected on the side of the test strip close to the patient, and the pressure detection information is detected and obtained by a pressure detection device preset on the test strip.

[0183] Step S245: Determine the pressure deviation influence information according to the deviation between the pressure detection information and the preset pressure detection reference information.

[0184] Among them, the pressure detection reference information refers to the reference detection information of the pressure when the test strip is normally pressed tightly against the patient. The pressure detection reference information is obtained by querying from a database storing the pressure detection reference information. By analyzing the deviation between the pressure detection information and the preset pressure detection reference information, and taking the deviation between the pressure detection information and the preset pressure detection reference information as the pressure detection deviation information, according to the correspondence between the pressure detection deviation information and the preset pressure deviation influence information, the pressure deviation influence information corresponding to the pressure detection deviation information is determined, so as to be convenient for subsequent use. The pressure deviation influence information is obtained by querying from a database storing the correspondence between the pressure detection deviation information and the pressure deviation influence information, and this database is obtained through pre-input by the operator.

[0185] Step S246: Combine the initial frontal inspection shape information and the pressure deviation influence information to form the frontal inspection shape adjustment information, and use the frontal inspection shape adjustment information as the frontal inspection shape information.

[0186] Among them, the frontal inspection shape adjustment information refers to the adjustment information after adjusting the shape of the detection strip on the patient's front. By combining the initial frontal inspection shape information and the pressure deviation influence information to form the frontal inspection shape adjustment information, and using the frontal inspection shape adjustment information as the frontal inspection shape information, the accuracy of the obtained frontal inspection shape information can be improved.

[0187] In Figure 8 In the shown step S246, in order to further ensure the rationality of the frontal inspection shape information, it is necessary to perform further separate analysis and calculation after using the frontal inspection shape adjustment information as the frontal inspection shape information, which is specifically described in detail through the following steps.

[0188] The steps after using the frontal inspection shape adjustment information as the frontal inspection shape information include the following steps:

[0189] Step S2461: When the lateral reflection intensity values are not all greater than the preset reflection reference intensity value, according to the correspondence between the abnormal relative contour position situation information and the preset abnormal relative contour position reference influence value, determine the abnormal relative contour position reference influence value corresponding to the abnormal relative contour position situation information.

[0190] Among them, the abnormal relative contour position reference influence value refers to the reference influence degree value when the relative position between the abnormal position and the contour position has an impact. The abnormal relative contour position reference influence value is obtained by querying from a database storing the correspondence between the abnormal relative contour position situation information and the abnormal relative contour position reference influence value, and this database is obtained through pre-input by the operator. When the lateral reflection intensity values are not all greater than the preset reflection reference intensity value, it indicates that there is an abnormal position at this time. By querying with the abnormal relative contour position situation information to determine the abnormal relative contour position reference influence value, it is convenient for subsequent use.

[0191] Step S2462: Calculate the difference between the lateral reflection intensity value and the reflection reference intensity value and use it as the lateral reflection intensity deviation value.

[0192] Among them, the lateral reflection intensity deviation value refers to the deviation value when the lateral reflection intensity value has a deviation. By calculating the difference between the lateral reflection intensity value and the reflection reference intensity value and using it as the lateral reflection intensity deviation value, it is convenient for subsequent use.

[0193] Step S2463: Calculate the product value between the lateral reflection intensity deviation value and the abnormal relative contour position reference influence value, and use it as the lateral reflection intensity influence value.

[0194] Among them, the lateral reflection intensity influence value refers to the influence degree value when the lateral reflection intensity deviation value has an impact. By calculating the product value between the lateral reflection intensity deviation value and the abnormal relative contour position reference influence value and using it as the lateral reflection intensity influence value, it is convenient for subsequent use.

[0195] Step S2464: According to the correspondence between the lateral reflection intensity influence value and the preset reflection intensity shape influence information, determine the reflection intensity shape influence information corresponding to the lateral reflection intensity influence value, and add the reflection intensity shape influence information to the front inspection shape information to form new front inspection shape information.

[0196] Among them, the reflection intensity shape influence information refers to the influence information when the intensity of the reflected light brightness has an impact on the shape. The reflection intensity shape influence information is obtained by querying from a database storing the correspondence between the lateral reflection intensity influence value and the reflection intensity shape influence information, and this database is obtained through pre-input by the operator. By querying the lateral reflection intensity influence value to determine the reflection intensity shape influence information and adding the reflection intensity shape influence information to the front inspection shape information to form new front inspection shape information, the accuracy of the obtained front inspection shape information is improved.

[0197] Based on the same inventive concept, an embodiment of the present invention provides a gait evaluation system based on three-dimensional simulation, including:

[0198] An acquisition module, configured to acquire image detection information and pressure detection information;

[0199] A memory, configured to store a program of the gait evaluation method based on three-dimensional simulation as described in any one of Figures 1 to 8 ;

[0200] A processor, configured to load and execute the program in the memory and implement the gait evaluation method based on three-dimensional simulation as described in any one of Figures 1 to 8 ;

[0201] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, and a computer program capable of being loaded and executed by the processor as described in any one of Figures 1 to 8 ;

[0202] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be allocated to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. For the specific working processes of the systems, devices, and units described above, reference can be made to the corresponding processes in the foregoing method embodiments, which will not be elaborated herein.

[0203] The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art, several improvements and refinements made without departing from the principle of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. A gait assessment method based on three-dimensional simulation, characterized in that: include: Acquire image detection information of the patient's legs; Determine the inspection shape information of the inspection strip preset on the patient's leg according to the image inspection information analysis; A three-dimensional model is established based on the shape information of the detection strip inspection to form leg simulation model information; Analyze the changes between the leg simulation model information at different times to form leg change information; Inputting the leg change information into a preset gait assessment neural network model to form gait assessment result information, and outputting the gait assessment result information to a display terminal; The method for determining the shape information of the test strip includes: Retrieving side reflection information and front reflection information based on the reflection image detection information; Retrieving the side reflection intensity value based on the side reflection information; Determine the side inspection shape information according to the judgment result of the side reflection intensity value and the preset reflection reference intensity value; Analyze the front reflection information to determine the front inspection shape information; Combining the side inspection shape information with the front inspection shape information to form comprehensive inspection shape information, and using the comprehensive inspection shape information as the detection strip inspection shape information; Methods for determining side inspection shape information include: Retrieving side reflection shape information based on the side reflection information; According to the correspondence between the side reflection shape information and the preset side inspection initial shape, the side inspection initial shape information corresponding to the side reflection shape information is determined; Determine whether the side reflection intensity values ​​are all greater than a preset reflection reference intensity value; If yes, the side inspection initial shape information is used as the side inspection shape information; If not, then based on the side reflection information, retrieve the position point corresponding to the side reflection intensity value not greater than the preset reflection reference intensity value and use it as the reflection abnormality position point; Analyze the abnormal reflection location and the initial shape information from the side to determine the influence information of the abnormal reflection shape; The side inspection shape adjustment information is determined based on the combination of the side inspection initial shape information and the reflection abnormality shape influence information, and the side inspection shape adjustment information is used as the side inspection shape information.

2. The gait assessment method based on three-dimensional simulation according to claim 1, characterized in that: Methods for determining information on the influence of reflection abnormal shape include: According to the correspondence between the initial shape information of the side inspection and the preset initial shape area information, the initial shape area information corresponding to the initial shape information of the side inspection is determined; Retrieving the initial shape area contour position points based on the initial shape area information; Analyze the reflection anomaly position points and the initial shape area contour position points to determine the anomaly relative contour position information; According to the correspondence between the abnormal relative contour position information and the preset relative position influence information, the relative position influence information corresponding to the abnormal relative contour position information is determined, and the relative position influence information is used as the reflection abnormal shape influence information.

3. The gait assessment method based on three-dimensional simulation according to claim 2, characterized in that: The method for determining the abnormal relative contour position information includes: If and only if the number of the reflection abnormal position points is less than the preset abnormal position reference number, the initial shape area contour position point with the closest position distance is selected based on the reflection abnormal position points and used as the abnormal closest contour position point; Calculate the distance between the reflection anomaly position point and the nearest contour position point of the anomaly and use it as the anomaly contour distance value; Analyze the reflection anomaly position points and the initial shape area contour position points to determine the relative direction information of the anomaly contour; Calculate the angle between the relative direction information of each abnormal contour and use it as the relative direction angle value; Determine whether the relative direction angle values ​​are all within the preset same-direction reference angle range; If yes, then combining the abnormal contour distance value with the preset relative reference position information outside the contour to form abnormal relative contour position information; If not, an analysis is performed based on the abnormal contour distance value to determine the relative position information within the contour, and the relative position information within the contour is used as the abnormal relative contour position situation information.

4. The gait assessment method based on three-dimensional simulation according to claim 3, characterized in that: The method for determining the relative position information within the contour includes: Based on the relative direction angle value, the initial shape area contour position point corresponding to the initial shape area contour position point that is not within the preset same-direction reference angle interval is selected as the angle contour position point; Analyze the angle contour position points and the reflection anomaly position points to determine the abnormal contour distance reference value; Determine whether the abnormal contour distance value is greater than the abnormal contour distance reference value; If yes, the preset reference position information within the contour is output as the relative position information within the contour; If not, then the relative position information within the contour is formed by combining the abnormal contour distance value with the preset relative reference position information within the contour.

5. The gait assessment method based on three-dimensional simulation according to claim 4, characterized in that: Methods for determining the distance between abnormal contours and reference values ​​include: Analyze the angle contour position points to determine the length reference direction information; According to the correspondence between the length reference direction information and the preset width reference direction information, the width reference direction information corresponding to the length reference direction information is determined; Based on the reflection abnormality position point, the initial shape area contour position point on the width reference direction information is selected as the width contour position point; Calculate the distance between the width contour position points and use it as the width distance value; According to the corresponding relationship between the width distance value and the preset abnormal contour distance reference value, the abnormal contour distance reference value corresponding to the width distance value is determined.

6. The gait assessment method based on three-dimensional simulation according to claim 2, characterized in that: Methods for determining the front inspection shape information include: Retrieve the front reflection position point based on the front reflection information; Performing a curve analysis according to the front reflection position points to form a front reflection curve; According to the correspondence between the front reflection curve and the preset front inspection initial shape information, the front inspection initial shape information corresponding to the front reflection curve is determined; Get the pressure test information on the test strip; According to the deviation between the pressure detection information and the preset pressure detection reference information, the pressure deviation impact information is determined; The front inspection shape adjustment information is formed based on the combination of the front inspection initial shape information and the pressure deviation influence information, and the front inspection shape adjustment information is used as the front inspection shape information.

7. A gait assessment system based on three-dimensional simulation, characterized in that: include: An acquisition module, used to acquire image detection information and pressure detection information; A memory, used to store a program of the gait assessment method based on three-dimensional simulation according to any one of claims 1 to 6; A processor is configured to load and execute a program in a memory and implement a gait assessment method based on three-dimensional simulation as described in any one of claims 1 to 6.

8. An intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes the gait assessment method based on three-dimensional simulation as described in any one of claims 1 to 6.

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