Visualization system and method thereof
By establishing a user's three-dimensional model and real-time monitoring of temperature changes, the shortcomings of existing physiotherapy monitoring technologies in real-time, accuracy, personalization and visual feedback are solved, and a safe and effective physiotherapy process is achieved.
Patent Information
- Application Number
- CN202510132516.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-06
- Publication Date
- 2025-06-10
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing physical therapy monitoring technology has shortcomings in real-time, accuracy, personalization and visual feedback, making it difficult to achieve a safe and effective physical therapy process.
By establishing a user's three-dimensional model, accurately map the physiotherapy points, and using infrared thermal imaging technology to monitor temperature changes in real time, establish temperature change curves, conduct similarity analysis, and intuitively display the physiotherapy effects in the user interface through color changes.
It achieves accurate adaptation to individual differences between different users, improves the efficiency and accuracy of physical therapy point marking, ensures the personalization and accuracy of the physical therapy process, monitors and feedbacks the physical therapy effect in real time, and optimizes the physical therapy process.
Smart Images
Figure CN120126674A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of visualization, and specifically to a visualization system and method thereof. Background Art
[0002] In the field of medical rehabilitation, physiotherapy devices are widely used to treat various muscle and joint diseases. Traditional physiotherapy methods rely on the experience and manual operations of physical therapists, which are not only inefficient, but also the treatment effects are limited by individual techniques and experiences. With the development of technology, some physiotherapy devices have begun to integrate basic monitoring functions, but these devices often lack real-time and accurate status monitoring and visualization feedback mechanisms, limiting the safety and effectiveness of the physiotherapy process; Existing physiotherapy monitoring technologies mostly use contact sensors to measure the temperature changes on the body surface, but these methods may not be able to fully reflect the actual status of the physiotherapy points. In addition, due to the complexity of the human body structure, there are differences in physiotherapy points among different individuals, but existing technologies often adopt unified standards and it is difficult to achieve personalized treatment. In terms of data recording and analysis, existing systems usually lack efficient data processing capabilities and it is difficult to accurately evaluate and provide real-time feedback on the physiotherapy effects; Given the limitations of the existing technologies, there is an urgent need for a safe monitoring visualization system and method that can provide real-time monitoring and accurate feedback.
[0003] To solve the above defects, a technical solution is provided now. Summary of the Invention
[0004] The purpose of the present invention is to solve the deficiencies of the existing physiotherapy monitoring technologies in terms of real-time performance, accuracy, personalization, and visualization feedback, and to propose a visualization system and method thereof.
[0005] The purpose of the present invention can be achieved through the following technical solutions: A visualization system, comprising: A human body model establishment module, used for scanning the user's body and establishing a human body model; A storage module, used for storing the three-dimensional model data of the user and user-related information; A mapping module, used for mapping the physiotherapy points on the user's three-dimensional model to the user's entity; A monitoring module, used for monitoring the status of the physiotherapy points during the physiotherapy process of the user. The specific steps are as follows: After completing the patch installation on the user's acupoints or muscle groups, perform physiotherapy on the user's acupoints or muscle groups through electrode patches, and capture the temperature distribution on the user's body surface through an infrared thermal imager to reflect the subtle temperature changes caused by the user's muscle activity or blood flow changes; Set the temperature acquisition frequency again to capture the temperature changes of the user's acupoints or muscle groups in real time, display the temperature before physical therapy and the temperature changes during physical therapy through the user interface, and map them to different acupoints or muscle groups in the user model, so that different acupoints or muscle groups in the user model display different temperature ranges with different colors; Set the temperature threshold according to the initial temperatures of different acupoints or muscle groups of the user. When the temperature change at a certain physical therapy point during physical therapy exceeds the preset temperature threshold, map the physical therapy point to the user's three-dimensional model and display it through the user interface, and alert the operator or the user to adjust the current output or frequency of the physical therapy point; Then establish a real-time temperature change curve for the temperature changes of all physical therapy points of all users, obtain the normal physical therapy point change curve according to historical data, and compare it with the real-time temperature change range of different physical therapy points. Specifically, similarity analysis is performed by collecting the measurement parameters of the two curves to obtain a similarity evaluation value; Then compare the calculated similarity evaluation value with the preset similarity evaluation threshold. When the similarity evaluation value is greater than or equal to the similarity evaluation threshold, it is determined that the electrode physical therapy effect on this point meets the standard. When the similarity evaluation value is less than the similarity evaluation threshold, it is determined that the electrode physical therapy effect on this point does not meet the standard, and the physical therapy effects of different physical therapy points are visually displayed through different colors on different acupoints or muscle groups in the user's three-dimensional model on the user interface.
[0006] Furthermore, the specific steps for visually displaying the physical therapy effects of different physical therapy points through different colors on different acupoints or muscle groups in the user's three-dimensional model on the user interface in the monitoring module are as follows: When the similarity evaluation value XXP is less than the similarity evaluation threshold, calculate the difference between the similarity evaluation value and the similarity evaluation threshold, and record it as the deviation value; Preset several deviation value intervals and the maximum deviation value. Different color displays are respectively set for the preset several deviation value intervals. Compare the obtained deviation value interval with the several deviation value intervals to determine the deviation value interval corresponding to this physical therapy point, so as to obtain the display color of the corresponding user interface; When the deviation value is greater than the maximum deviation value, alert the specific acupoint or muscle group position of this physical therapy point through the user interface, and prompt the operator to adjust the attachment position of the electrode patch on this physical therapy point or change the current output and frequency of the physical therapy electrode to achieve the purpose of improving the physical therapy effect.
[0007] Furthermore, the specific operation steps for similarity analysis by collecting the measurement parameters of the two curves in the monitoring module are as follows: The measurement parameters include: slope, standard deviation, correlation coefficient, dynamic time warping distance, and peak and valley values; According to the importance of each measurement parameter for the similarity analysis of the two curves, a weight is assigned to each measurement parameter, and the sum of the weights is set to 1; Then, each measurement parameter is normalized to obtain a slope value, a standard deviation value, a coefficient value, a moving distance value, and a peak-valley value, which are respectively designated as xb, cb, xb, db, and fg. After normalization, they are substituted into the following formula: To obtain a similarity evaluation value XXP, where are the preset weights of the slope value, the standard deviation value, the coefficient value, the moving distance value, and the peak-valley value respectively. The calculated similarity evaluation value XXP is used as the standard for measuring the similarity of the two curves.
[0008] Furthermore, the specific operation steps for the human body model establishment module to scan the user's body and establish a human body model are as follows: First, determine the scanning technology, and then guide the user to adopt the correct posture through a preset area indication diagram, and prompt the user to keep the body parts stable and easy to scan during the scanning process; Then, use the determined scanning technology to scan the user's body to obtain specific external morphological data of the user, collect the specific external morphological data of the user, and the specific external morphological data of the user consists of several two-dimensional image sequences; Next, preprocess the collected two-dimensional images, including denoising and contrast enhancement, and then verify the integrity of the collected two-dimensional images. The specific steps are as follows: Use image processing algorithms to evaluate the quality of the scanned two-dimensional images, including evaluating the clarity, contrast, and noise level of the images. According to the evaluation results, cooperate with checking the boundary integrity of the images and identifying holes or discontinuous regions in the images to determine whether there are missing or unclear regions in the images; Then, preset an integrity threshold according to the usage requirements, compare the integrity of the images with the preset integrity threshold. When the integrity of the images is lower than the preset integrity threshold, the area needs to be scanned again. Use the algorithm to automatically mark the area that needs to be scanned again and perform visual display, so that the scanning personnel can quickly locate the user's body part and rescan the area; Fuse the data of the first scan and the second scan to form a complete data set; When the image integrity reaches the preset integrity threshold, the remaining unscanned parts are filled through a predictive algorithm; Then, verify the results of the predictive filling to ensure the accuracy and rationality of the filling. At the same time, provide a user interaction interface to allow the operator to manually adjust the filling results; Then, use 3D reconstruction software to convert the preprocessed 2D image data into a 3D model. Complete the conversion of the 3D model through image segmentation, registration, and fusion steps. Refine the reconstructed 3D model, including smoothing, hole filling, and sharpening.
[0009] Furthermore, the predictive algorithms in the human body model establishment module include: Statistical-based method: Use the statistical information of known regions to predict the characteristics of unknown regions. Model-based method: Use the human anatomy model to predict the shape and characteristics of missing regions. Deep learning-based method: Use a trained neural network model to predict and fill the missing parts of the image.
[0010] Furthermore, the specific operation steps for the storage module to store the user's 3D model data and user-related information are as follows: Save the user 3D model file to the storage module and use a standard file format. Then establish a user information database, enter the user's basic information, including name, age, gender, and contact information, and associate the user information with the corresponding 3D model file to enable the identification of the corresponding user's 3D model through the user's basic information. Integrate the model retrieval and loading functions in the user interface to quickly find the user model to be searched for by the user through search and screening, and retrieve the corresponding 3D model file from the database based on the user information or unique identifier. Before model loading, ensure that the operator has the right to access the user's model and information through a verification process for the operator to avoid the leakage of user information.
[0011] Furthermore, the specific operation steps for the mapping module to map the physiotherapy points on the user 3D model to the user entity are as follows: First, establish a standard 3D human body model, use this standard model as a reference basis, and mark all acupoints and muscle groups on the standard model. Define a general coordinate system on the standard model so that the positions of all acupoints and muscle groups are determined based on this general coordinate system, and analyze the differences between the user model and the standard model, including size, proportion, and shape. According to the differences between the user model and the standard model, calculate the size and proportion adjustment factor, use the calculated size and proportion adjustment factor to convert the coordinates of the acupoints and muscle groups on the standard model to the user model, apply the converted coordinates to the user model, and mark the corresponding positions of the acupoints and muscle groups. Compare the user's three-dimensional human body model data with the standard three-dimensional human body model data, mark the positions of the acupoints and muscle groups corresponding to the user's three-dimensional human body model, and use an automated algorithm to improve the efficiency and accuracy of the marking; Then, verify the accuracy of the positions of the acupoints and muscle groups manually, and perform position calibration according to the feedback. Integrate the model viewing and acupoint and muscle group marking functions in the user interface, allowing the user or operator to view and adjust intuitively. At the same time, provide tools for the user or operator to manually adjust the results of the automatic marking to adapt to individual differences. When the user model is updated, the markings of the acupoints and muscle groups are updated synchronously; According to the user's physical therapy needs and the preset physical therapy plan, determine the specific acupoints or muscle groups that the user needs for physical therapy. Use different visual markings on the user model to highlight these points. Map the point coordinates on the model to the actual positions on the user's body through the markings, and verify and calibrate the actual positions marked by the user; Through the augmented reality application auxiliary tool, overlay the point information on the model onto the user's physical body to facilitate accurate positioning by the operator. Attach physical therapy electrode patches to the acupoints or muscle groups on the user's body that need physical therapy based on the point information of the user's physical body. At the same time, record and associate the positions of the user's physical therapy points for the user to use in the next physical therapy.
[0012] A visualization method includes the following steps: S1: Scan the user's body and establish a three-dimensional model, including image preprocessing and integrity verification; S2: Store the three-dimensional model data, and associate the user information with the model to ensure data security; S3: Map and mark the physical therapy points on the user model, and adjust the coordinates to adapt to individual differences; S4: Monitor the physical therapy process through infrared thermal imaging, and capture and display the temperature changes in real time; S5: Analyze the temperature change curve using key parameters and calculate the similarity between the curves; S6: Evaluate the physical therapy effect based on the similarity and provide an intuitive feedback on the interface through color changes.
[0013] Compared with the prior art, the beneficial effects of the present invention are: In the present invention, by establishing a three-dimensional model of the user and accurately mapping the physical therapy points, it realizes accurate adaptation to the individual differences of different users. Using an automated algorithm combined with manual calibration, it improves the efficiency and accuracy of the marking of physical therapy points, ensuring the personalization and precision of the physical therapy process; In the present invention, the system monitors the temperature change during the physiotherapy process in real time through infrared thermal imaging technology and sets a temperature threshold warning, effectively avoiding user discomfort or injury caused by abnormal temperature changes. The establishment of the real-time temperature change curve and the similarity analysis further enhance the evaluation and monitoring of the physiotherapy effect; In the present invention, the physiotherapy effect is visually displayed in the user interface by color change. By comparing the real-time temperature change curve with historical data, the physiotherapy effect is evaluated and feedback is provided in a timely manner. This visual feedback mechanism enables the operator to quickly identify and adjust the physiotherapy plan, optimize the physiotherapy process, and improve the treatment effect. Brief Description of the Drawings
[0014] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the accompanying drawings; Figure 1 It is the system general block diagram of the present invention. Detailed Embodiments
[0016] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.
[0017] It should be understood that the terms "including" and "comprising" used in the specification and claims of this disclosure indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.
[0018] It should also be understood that the terms used in this disclosure specification are only for the purpose of describing specific embodiments and are not intended to limit this disclosure. As used in this disclosure specification and claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms. It should also be further understood that the term "and / or" used in this disclosure specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.
[0019] As Figure 1 shown, a visualization system includes a human body model establishment module, a storage module, a mapping module, and a monitoring module; The human body model establishment module is used to scan the user's body and establish a human body model; First, determine the scanning technology, including X-ray computed tomography (CT), magnetic resonance imaging (MRI), optical scanning, or structured light scanning; then, guide the user to adopt the correct posture through a preset regional indication diagram, and prompt the user to keep the body part stable and easy to scan during the scanning process; then, use the determined scanning technology to scan the user's body to obtain specific external morphological data of the user, collect the specific external morphological data of the user, and the specific external morphological data of the user consists of several two-dimensional image sequences; then, preprocess the collected two-dimensional images, including denoising and contrast enhancement, to improve the accuracy of subsequent processing, and then verify the integrity of the collected two-dimensional images. The specific steps are as follows: Use image processing algorithms to evaluate the quality of the scanned two-dimensional images, including evaluating the clarity, contrast, and noise level of the images. According to the evaluation results, cooperate with checking the boundary integrity of the images, identifying holes or discontinuous regions in the images to determine whether there are missing or unclear regions in the images. Then, preset an integrity threshold according to the usage requirements, and compare the integrity of the images with the preset integrity threshold. When the integrity of the images is lower than the preset integrity threshold, the area needs to be scanned again. Use the algorithm to automatically mark the area that needs to be scanned again and perform visual display, so that the scanning personnel can quickly locate the user's body part and rescan the area; fuse the data of the first scan and the second scan to form a complete data set; when the image integrity reaches the preset integrity threshold, fill the remaining unscanned part through a predictive algorithm, including: statistical-based method: using the statistical information of the known area to predict the characteristics of the unknown area; model-based method: using the human anatomy model to predict the shape and characteristics of the missing area; deep learning-based method: using a trained neural network model, such as a convolutional neural network (CNN), to predict and fill the missing image part; Then, verify the results of the predictive filling to ensure the accuracy and rationality of the filling. At the same time, provide a user interface that allows the operator to manually adjust the filling results when necessary; then, use 3D reconstruction software to convert the preprocessed two-dimensional image data into a 3D model, and complete the conversion of the 3D model through image segmentation, registration, and fusion steps. Refine the reconstructed 3D model, including smoothing, hole filling, and sharpening, to improve the quality of the model.
[0020] The storage module is used to store the 3D model data of the user and the user-related information; The user's 3D model file is saved in the storage module, and a standard file format is used, including STL, OBJ or PLY. Then a user information database is established, and the user's basic information, including name, age, gender and contact information, is entered. The user information is associated with the corresponding 3D model file to ensure that each user's 3D model can be accurately identified; and the model retrieval and loading functions are integrated in the user interface to provide users with a way to quickly find the user model they need through search and screening, and retrieve the corresponding 3D model file from the database based on user information or a unique identifier; before the model is loaded, a verification process is performed on the operator to ensure that the operator has the right to access the user's model and information to avoid user information leakage.
[0021] The mapping module is used to map the therapy points on the user's three-dimensional model to the user entity; First, a standard 3D human body model is established, and the standard model is used as a reference basis. All acupuncture points and muscle groups are marked on the standard model. A universal coordinate system is defined on the standard model, so that the positions of all acupuncture points and muscle groups are determined based on the universal coordinate system, and the differences between the user model and the standard model are analyzed, including size, proportion and shape. According to the difference between the user model and the standard model, the size ratio adjustment factor is calculated, and the coordinates of the acupuncture points and muscle groups on the standard model are converted to the user model by using the calculated size ratio adjustment factor. The converted coordinates are applied to the user model to mark the corresponding acupuncture points and muscle group positions; according to the comparison between the user's 3D human body model data and the standard 3D human body model data, the corresponding acupuncture points and muscle group positions of the user's 3D human body model are marked, and the automated algorithm is used to reduce manual operations and improve the efficiency and accuracy of marking; The accuracy of the acupoint and muscle group positions is then manually verified, and the positions are calibrated based on the feedback. The model viewing and acupoint and muscle group marking functions are integrated into the user interface, allowing the user or operator to intuitively view and adjust. At the same time, tools are provided for the user to allow the user or operator to manually adjust the automatic marking results to adapt to individual differences. When the user model is updated, the markings of the acupoints and muscle groups are updated synchronously. According to the user's physical therapy needs and the preset physical therapy plan, the specific acupuncture points or muscle groups that the user needs physical therapy are determined, and different visual markers are used on the user model to highlight these points. The point coordinates on the model are mapped to the actual positions on the user's body through marking, and the actual positions of the user's marks are verified and calibrated; through the augmented reality (AR) application auxiliary tools, the point information on the model is superimposed on the user's physical body to facilitate the operator's accurate positioning, and it is convenient to attach physical therapy electrodes to the acupuncture points or muscle groups on the user's body that need physical therapy. At the same time, the position of the user's physical therapy point is recorded and associated, which is convenient for the user to use for the next physical therapy.
[0022] The monitoring module is used to monitor the status of the physiotherapy point during the physiotherapy process of the user; After the patch is installed on the user's acupoint or muscle group, physiotherapy is performed on the user's acupoint or muscle group through the electrode patch, and the temperature changes of the user's physiotherapy acupoint or muscle group before and during the physiotherapy are collected. Specifically, the infrared thermal imager is used to capture the temperature distribution on the user's body surface, reflecting the subtle temperature changes caused by the user's muscle activity or blood flow changes; Then set the temperature acquisition frequency, capture the temperature changes of the user's acupoint or muscle group in real time, display the temperature before physiotherapy and the temperature changes during the physiotherapy process through the user interface. The temperature data collected before physiotherapy is used as the baseline reference and recorded as the initial temperature. During the physiotherapy process, the temperature of each acupoint or muscle group is monitored and recorded in real time. The collected temperature data is displayed on the user interface in the form of a graph or color change, and mapped to different acupoints or muscle groups in the user model, so that different acupoints or muscle groups in the user model are displayed in different colors to represent different temperature ranges; Then, according to the initial temperature of different acupoints or muscle groups of the user, set the temperature threshold warning. When the temperature change of a certain physiotherapy point during the physiotherapy process exceeds the preset temperature threshold, the physiotherapy point is mapped to the user's three-dimensional model and displayed through the user interface, and the operator or the user is warned to adjust the current output or frequency of the physiotherapy point to avoid discomfort to the user; Among them, for the current output of the physiotherapy point, the monitoring module monitors the current output of each physiotherapy point in real time, then preset different current output intervals, which represent different current output levels respectively, and assign a color to each current output level, so as to be intuitively displayed on the visualization interface. While displaying the color, the real-time current value of each physiotherapy point is provided, the color and numerical display of the interface are dynamically updated according to the current change, and the user is allowed to adjust the current output size on this interface; Then establish a real-time temperature change curve for the temperature changes of all physiotherapy points of all users, obtain the normal physiotherapy point change curve according to the historical data, and compare it with the real-time temperature change interval of different physiotherapy points. Specifically, the similarity analysis is carried out by collecting the measurement parameters of the two curves. The measurement parameters include: Slope: Reflects the rate of temperature change over time; Standard deviation: Reflects the consistency and stability of temperature change; Correlation coefficient: Measures the linear relationship between two curves; Dynamic time warping distance: Measures the similarity of two time series on different time scales; Peaks and valleys: Reflect the extreme situations of the curve, that is, the highest and lowest temperature changes; According to the importance of each measurement parameter for the similarity analysis of the two curves, a weight is assigned to each measurement parameter, and the sum of the weights is set to 1. Then, each measurement parameter is normalized to obtain the slope scale value, standard deviation scale value, coefficient scale value, moving distance scale value, and peak-valley scale value, which are respectively labeled as xb, cb, xb, db, and fg. After normalization, substitute them into the following formula: To obtain the similarity evaluation value XXP, where are the preset weights of the slope scale value, standard deviation scale value, coefficient scale value, moving distance scale value, and peak-valley scale value respectively. The calculated similarity evaluation value XXP is used as the similarity standard for measuring the two curves; Then, compare the calculated similarity evaluation value XXP with the preset similarity evaluation threshold to determine whether the similarity evaluation value XXP meets the standard of the similarity evaluation threshold. When the similarity evaluation value XXP is greater than or equal to the similarity evaluation threshold, it is determined that the electrode physiotherapy effect at this point reaches the standard. When the similarity evaluation value XXP is less than the similarity evaluation threshold, it is determined that the electrode physiotherapy effect at this point does not reach the standard; Visualize the physiotherapy effects of different physiotherapy points by different colors on different acupoints or muscle groups in the user's three-dimensional model on the user interface. When the similarity evaluation value XXP is less than the similarity evaluation threshold, calculate the difference between the similarity evaluation value and the similarity evaluation threshold, and record it as the deviation value. Preset several deviation value intervals and the maximum deviation value. Different color displays are respectively set for the preset several deviation value intervals. Compare the obtained deviation value interval with the several deviation value intervals to determine the deviation value interval corresponding to this physiotherapy point, so as to obtain the corresponding display color. When the deviation value is greater than the maximum deviation value, alert the specific acupoint or muscle group position of this physiotherapy point through the user interface, and prompt the operator to adjust the attachment position of the electrode patch at this physiotherapy point or change the current of the physiotherapy electrode to achieve the purpose of improving the physiotherapy effect.
[0023] A visualization method includes the following steps: User body scanning and three-dimensional model establishment: Use CT, MRI, optical scanning, or structured light scanning technology to scan the user's body. Guide the user to take the correct posture through a preset area indication diagram, obtain a sequence of two-dimensional images, preprocess the two-dimensional images, including denoising and contrast enhancement, verify the image integrity, and perform secondary scanning and data fusion if necessary; Human model data storage and information association: Save the three-dimensional model data in a standard format, such as STL, OBJ, or PLY. Establish a user information database, enter the user's basic information, and associate it with the corresponding three-dimensional model file; Physiotherapy Point Mapping and Marking: Establish a standard three-dimensional human body model, mark acupoints and muscle groups, adjust the coordinates of acupoints and muscle groups according to the differences between the user model and the standard model, use an automated algorithm to mark the physiotherapy points on the user model, and calibrate through manual verification; Physiotherapy Process Monitoring and Status Visualization: Install electrode patches and perform physiotherapy, capture the temperature distribution through an infrared thermal imager, monitor and record the temperature changes of the physiotherapy acupoints or muscle groups in real time, and display them through the user interface; Establishment of Temperature Change Curve and Similarity Analysis: Establish a real-time temperature change curve and compare it with historical data, collect parameters such as slope, standard deviation, correlation coefficient, dynamic time warping distance, and peak and valley values, assign weights to each parameter and perform standardization processing, and calculate the similarity evaluation value; Physiotherapy Effect Evaluation and Feedback: Compare the similarity evaluation value with a preset threshold to evaluate the physiotherapy effect. According to the evaluation result, visually display the physiotherapy effect in different colors in the user interface. If the deviation value is greater than the preset maximum deviation value, give a warning and prompt to adjust the position of the electrode patch or the current frequency; The present invention is applicable to the safety monitoring visualization of physiotherapy devices; The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not elaborate on all details and do not limit the invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.
Claims
1. A visualization system, characterized in that: include; A human body model building module is used to scan the user's body and build a human body model; A storage module, used to store the user's 3D model data and user-related information; A mapping module, used for mapping the therapy points on the user's three-dimensional model to the user entity; The monitoring module is used to monitor the status of the therapy points during the user's therapy. The specific steps are as follows: After the patch is installed on the user's acupuncture points or muscle groups, the user's acupuncture points or muscle groups are treated with the electrode patch, and the temperature distribution on the user's body surface is captured by an infrared thermal imager to reflect the subtle temperature changes caused by the user's muscle activity or blood flow changes; Then set the temperature collection frequency to capture the temperature changes of the user's acupuncture points or muscle groups in real time, display the temperature before and during physical therapy through the user interface, and map it to different acupuncture points or muscle groups in the user model, so that different acupuncture points or muscle groups in the user model display different temperature ranges through different colors; Then, according to the initial temperature of different acupuncture points or muscle groups of the user, a temperature threshold is set. When the temperature change of a certain treatment point exceeds the preset temperature threshold during the treatment, the treatment point is mapped to the user's three-dimensional model and displayed through the user interface, and the operator or user is warned to adjust the current output or frequency of the treatment point. Then, a real-time temperature change curve is established for the temperature changes of all the therapy points of all users. The normal therapy point change curve is obtained based on historical data, and compared with the real-time temperature change range of different therapy points. Specifically, the measurement parameters of the two curves are collected for similarity analysis to obtain similarity evaluations. The calculated similarity evaluation value is then compared with the preset similarity evaluation threshold. When the similarity evaluation value is greater than or equal to the similarity evaluation threshold, it is judged that the electrode therapy effect on the point has reached the standard. When the similarity evaluation value is less than the similarity evaluation threshold, it is judged that the electrode therapy effect on the point has not reached the standard. The therapy effects of different therapy points are visualized by different colors for different acupuncture points or muscle groups on the user's three-dimensional model in the user interface.
2. A visualization system according to claim 1, characterized in that: The specific steps of visually displaying the physiotherapy effects of different physiotherapy points in the monitoring module through different colors on different acupuncture points or muscle groups on the user's three-dimensional model in the user interface are as follows: When the similarity evaluation value XXP is less than the similarity evaluation threshold, the difference between the similarity evaluation value and the similarity evaluation threshold is calculated and recorded as the deviation value; Preset a number of deviation value intervals and a maximum deviation value, set different color displays for the preset several deviation value intervals, compare the obtained deviation value interval with the several deviation value intervals, determine the deviation value interval corresponding to the physiotherapy point, and obtain the corresponding user interface display color; When the deviation value is greater than the maximum deviation value, the specific acupoint or muscle group position of the therapy point will be warned through the user interface, and the operator will be prompted to adjust the attachment position of the electrode sheet on the therapy point or change the current output and frequency of the therapy electrode to achieve the purpose of improving the therapy effect.
3. A visualization system according to claim 1, characterized in that: The specific operation steps of performing similarity analysis by collecting the measurement parameters of two curves in the monitoring module are as follows: The measurement parameters include: slope, standard deviation, correlation coefficient, dynamic time warping distance, and peak and valley values; According to the importance of each measurement parameter to the similarity analysis of the two curves, a weight is assigned to each measurement parameter, and the sum of the weights is set to 1; Then, each measurement parameter is standardized to obtain the slope value, standard deviation value, coefficient value, dynamic distance value and peak-to-valley value, which are calibrated as xb, cb, xb, db and fg respectively. After normalization, they are entered into the following formula: To obtain the similarity evaluation XXP, where They are the preset weights of slope standard value, standard deviation standard value, coefficient standard value, dynamic distance standard value and peak-valley standard value respectively, and the calculated similarity evaluation value XXP is used as the standard for measuring the similarity of the two curves.
4. A visualization system according to claim 1, characterized in that: The specific operation steps of the human body model building module to scan the user's body and build a human body model are as follows: First, the scanning technique is determined, and then the user is guided to adopt the correct posture through the preset area indicator map, and the user is prompted to keep the body part stable and easy to scan during the scanning process; Then, a determined scanning technology is used to scan the user's body to obtain specific external morphological data of the user, and the specific external morphological data of the user is collected, where the specific external morphological data of the user is composed of a plurality of two-dimensional image sequences; The collected two-dimensional image is then preprocessed, including denoising and contrast enhancement, and the integrity of the collected two-dimensional image is verified. The specific steps are as follows: Use image processing algorithms to evaluate the quality of the scanned two-dimensional image, including evaluating the image clarity, contrast and noise level, and based on the evaluation results, check the image boundary integrity, identify holes or discontinuous areas in the image to determine whether there are missing or unclear areas in the image; Then, an integrity threshold is preset according to the usage requirements, and the integrity of the image is compared with the preset integrity threshold. When the integrity of the image is lower than the preset integrity threshold, the area needs to be scanned again. The algorithm is used to automatically mark the area that needs to be scanned again, and a visual display is performed to help the scanner quickly locate the user's body part and rescan the area; The data from the first scan and the second scan are merged to form a complete data set; When the image integrity reaches a preset integrity threshold, the remaining unscanned portion is filled in using a predictive algorithm; The predictive filling results are then verified to ensure the accuracy and rationality of the filling, while providing a user interaction interface to allow the operator to manually adjust the filling results; Then, the preprocessed two-dimensional image data is converted into a three-dimensional model using three-dimensional reconstruction software. The conversion of the three-dimensional model is completed through image segmentation, registration and fusion steps, and the reconstructed three-dimensional model is refined, including smoothing, hole filling and sharpening.
5. A visualization system according to claim 4, characterized in that: The predictive algorithm in the human body model building module includes: Statistical-based methods: using statistical information of known areas to predict the characteristics of unknown areas; Model-based methods: using a human anatomy model to predict the shape and features of the missing area; Deep learning based methods: Use trained neural network models to predict and fill in missing image parts.
6. A visualization system according to claim 1, characterized in that: The specific operation steps of storing the user's three-dimensional model data and user-related information in the storage module are as follows: Save the user's 3D model file to the storage module and use a standard file format; Then establish a user information database, enter the user's basic information, including name, age, gender and contact information, and associate the user information with the corresponding 3D model file to realize the recognition of the corresponding user's 3D model through the user's basic information; Integrate model retrieval and loading functions in the user interface to provide users with the ability to quickly find the user model they need through search and filtering, and retrieve the corresponding 3D model file from the database based on user information or a unique identifier; Before the model is loaded, the operator is verified to ensure that the operator has the right to access the user's model and information to avoid user information leakage.
7. A visualization system according to claim 1, characterized in that: The specific operation steps of the mapping module to map the therapy points on the user's three-dimensional model to the user entity are as follows: First, a standard three-dimensional human body model is established, which is used as a reference basis, and all acupuncture points and muscle groups are marked on the standard model; Define a universal coordinate system on the standard model so that the positions of all acupoints and muscle groups are determined based on the universal coordinate system, and analyze the differences between the user model and the standard model, including size, proportion and shape; According to the difference between the user model and the standard model, the size ratio adjustment factor is calculated. The coordinates of the acupuncture points and muscle groups on the standard model are converted to the user model using the calculated size ratio adjustment factor. The converted coordinates are applied to the user model to mark the corresponding acupuncture points and muscle group positions. According to the comparison between the user's 3D human body model data and the standard 3D human body model data, the corresponding acupuncture points and muscle group positions of the user's 3D human body model are marked, and the efficiency and accuracy of marking are improved by using an automated algorithm; The accuracy of the acupoint and muscle group positions is then manually verified, and the positions are calibrated based on the feedback. The model viewing and acupoint and muscle group marking functions are integrated into the user interface, allowing the user or operator to intuitively view and adjust. At the same time, tools are provided for the user to allow the user or operator to manually adjust the automatic marking results to adapt to individual differences. When the user model is updated, the markings of the acupoints and muscle groups are updated synchronously. According to the user's physical therapy needs and the preset physical therapy plan, the specific acupuncture points or muscle groups that the user needs physical therapy are determined, and different visual markers are used on the user model to highlight these points. The coordinates of the points on the model are mapped to the actual positions on the user's body through the markers, and the actual positions of the user's markers are verified and calibrated; Through the application of augmented reality auxiliary tools, the point information on the model is superimposed on the user's physical body to facilitate the operator's accurate positioning. The point information of the user's entity is used to attach therapeutic electrodes to the acupuncture points or muscle groups on the user's body that need therapeutic treatment. At the same time, the position of the user's therapeutic points is recorded and associated to facilitate the user's next therapeutic use.
8. A visualization method, characterized in that: The following steps are involved: S1: Scan the user's body and build a 3D model, including image preprocessing and integrity verification; S2: Stores 3D model data and associates user information with the model to ensure data security; S3: Map and mark the therapy points on the user model and adjust the coordinates to accommodate individual differences; S4: Monitor the physical therapy process through infrared thermal imaging, capturing and displaying temperature changes in real time; S5: Analyze the temperature change curve using key parameters and calculate the similarity between the curves; S6: Evaluate the therapeutic effect based on the similarity, and provide intuitive feedback on the interface through color changes.