Kinesio application assisting method and related equipment

Abstract

The invention discloses a kinesio application assisting method and related equipment. The method comprises the following steps: acquiring treatment purpose information of a target patient; acquiring biological characteristic information of the target patient; and recommended patch shape data and recommended patch size data are analyzed and determined based on the physiological sign information and the treatment purpose information, so that an execution device is controlled to cut a pre-stored patch based on the recommended patch shape data and the recommended patch size data to obtain a target patch. The problems that in the actual operation process of the kinesio, an operator needs to have rich experience and high skills, the patch cannot be flatly attached to the skin, and wrinkles, bubbles and the like occur easily can be solved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of smart medical care. More specifically, the present invention relates to a kinesiology tape application assistance method and related equipment. Background Art

[0002] Kinesio taping has been widely used in rehabilitation medicine and sports medicine for its remarkable effectiveness in relieving pain, improving muscle function, and promoting blood circulation. However, in practice, it presents numerous operational difficulties, especially for beginners. Firstly, because the shapes, sizes, and functional requirements of various taping areas vary, cutting the kinesio tape to the appropriate shape and size is challenging, often requiring extensive experience and skill. Secondly, to achieve the desired therapeutic effect, the kinesio tape must be applied smoothly to the skin, avoiding wrinkles and air bubbles. However, achieving a perfect fit is extremely challenging when taping irregular areas such as joints. These operational limitations not only compromise the therapeutic effectiveness of kinesio taping but also lead to significant time waste, limiting the widespread application of this technology in clinical practice. Summary of the Invention

[0003] The Summary of the Invention introduces a series of simplified concepts that will be further described in the Detailed Description of the Invention. The Summary of the Invention is not intended to limit the key features and essential features of the claimed technical solution, nor is it intended to determine the scope of protection of the claimed technical solution.

[0004] To address the issues of Kinesio Taping requiring extensive experience and high skill, and the tendency for the patch to not adhere smoothly to the skin, resulting in wrinkles and bubbles, the present invention provides, in a first aspect, a Kinesio Taping application assistance method, comprising:

[0005] Obtain information on treatment goals for target patients;

[0006] Obtaining biometric information of the target patient;

[0007] Recommended patch shape data and recommended patch size data are determined based on the physiological sign information and treatment purpose information, so as to control the execution device to cut the pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain the target patch.

[0008] Optionally, also include:

[0009] The target taping site is determined based on the analysis of the physiological sign information and the treatment purpose information.

[0010] Optionally, also include:

[0011] Generate a request to obtain the image of the target taping part,

[0012] When receiving the target taping part image in response to the acquisition request, adding an auxiliary taping mark to the target taping part image based on the recommended taping shape data and the recommended taping size data;

[0013] The target taping part image with the auxiliary taping mark is displayed to prompt the user to perform taping.

[0014] Optionally, the target patch includes a fixing section and a treatment section, and the method further includes:

[0015] Generate a request to obtain the image of the target taping part,

[0016] Upon receiving the target taping site image in response to the acquisition request, the length of the fixed segment is determined based on the taping site type, taping site size and taping site skin condition indicated by the target taping site image, wherein the taping site skin condition includes skin smoothness and / or skin temperature.

[0017] Optionally, before the step of generating a request for acquiring an image of the target taping site, the method further includes:

[0018] Determining an ideal posture for the taping site based on the treatment purpose information analysis, wherein the image acquisition request includes the ideal posture for the taping site;

[0019] When the target taping part image matches the ideal taping part preparation posture, an auxiliary taping mark is added to the target taping part image based on the recommended patch shape data and the recommended patch size data; otherwise, a posture adjustment prompt message is generated.

[0020] Optionally, also include:

[0021] Determining the ideal posture for preparing the taping site based on the treatment purpose information analysis;

[0022] When the user holds the user smart terminal device, the actual posture of the taping part preparation is determined based on the acceleration sensor and gyroscope of the user smart terminal device;

[0023] When the actual taping position preparation posture matches the ideal taping position preparation posture, an auxiliary taping mark is added to the target taping position image based on the recommended patch shape data and the recommended patch size data; otherwise, a posture adjustment prompt message is generated.

[0024] In a second aspect, the present invention further provides a Kinesio Tape application assistive device, comprising:

[0025] An acquisition unit, used for acquiring items to be examined from a target patient;

[0026] An analyzing unit, configured to analyze the relationship type between the items to be inspected based on the inspection item knowledge graph when there are at least two items to be inspected;

[0027] A planning unit is used to determine the inspection priorities of the at least two items to be inspected based on the relationship type, so as to generate an inspection sequence recommendation.

[0028] In a third aspect, an electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of any one of the kinesiology tape application assistance methods of the first aspect when executing the computer program stored in the memory.

[0029] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the kinesiology taping application assistance method according to any one of the above items in the first aspect is implemented.

[0030] In summary, the Kinesio taping application assistance method proposed in this application obtains treatment objective information from a target patient; obtains biometric information of the target patient; and determines recommended patch shape data and recommended patch size data based on the physiological sign information and treatment objective information. The method then controls an execution device to cut a pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain a target patch. This method accurately matches the patient's body part characteristics, avoiding blind experience-based cutting. This improves the fit and enhances the patch's functional effectiveness (e.g., better fixation and higher elasticity). Pre-cutting optimizes the shape to accommodate irregular areas and reduces the risk of wrinkles and bubbles. The patch edges are more easily aligned with the surface, improving patient comfort and application time. Novice users can rely on recommendations and pre-cutting, reducing the learning curve and application time. The standardized process facilitates widespread adoption and is suitable for use in hospitals, sports rehabilitation institutions, and self-help settings at home. Because both patient information collection and patch cutting are automatically performed by the system, novice users can complete professional-level Kinesio taping based on recommended data without having to master complex patch cutting techniques. Precisely matching the size and shape of the patient's target area avoids patch waste or poor treatment results due to improper cutting, ensuring the patch adheres smoothly to curved and irregular areas without wrinkles or bubbles, extending the application time. The entire process is highly automated, reducing manual operation time and facilitating large-scale application in hospital rehabilitation departments, sports teams, and community health centers. It is particularly suitable for the rapid deployment of standardized rehabilitation services.

[0031] The Kinesio tape application assisting method of the present invention, and other advantages, objectives, and features of the present invention will be partially reflected in the following description and partially understood by those skilled in the art through study and practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present description. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0033] Figure 1 A schematic flow chart of a Kinesio Tape application assistance method provided in an embodiment of the present application;

[0034] Figure 2 A schematic diagram of the structure of a Kinesio taping application assisting device provided in an embodiment of the present application;

[0035] Figure 3 This is a schematic diagram of the structure of an electronic device assisting with the application of Kinesio Tape provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the embodiments described are only part of the embodiments of the present application, not all of the embodiments.

[0037] In order to solve the problem that the actual operation of Kinesio Tape requires the operator to have rich experience and high skills, and it is easy for the patch to not fit smoothly on the skin, and wrinkles and bubbles may appear, please refer to Figure 1 , is a flow chart of a Kinesio Tape application assistance method provided in an embodiment of the present application, which may specifically include: steps S110 to S130.

[0038] S110, obtaining treatment purpose information of the target patient.

[0039] S120: Obtain biometric information of the target patient.

[0040] S130, determining recommended patch shape data and recommended patch size data based on the physiological sign information and treatment purpose information, and controlling the execution device to cut the pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain a target patch.

[0041] As can be understood, this method, based on personalized medicine and intelligent-assisted cutting technology, collects information about the patient's treatment objectives and biometrics, uses an analytical model to automatically recommend the best kinesiology tape shape and size for the patient's needs. The actuator then performs high-precision automatic cutting based on the recommended data. This method aims to address issues inherent in traditional kinesiology taping, such as insufficient manual cutting experience, shape mismatches, and uneven application. It aims to improve operational efficiency and the clinical efficacy of the tape, achieving a standardized and personalized kinesiology taping application model.

[0042] For example, the system first obtains information about the specific treatment goals that the patient hopes to achieve through kinesiology taping through self-filling by the patient or input by medical staff. Specific methods include providing a set of standardized guidance questionnaires or electronic forms, covering common treatment purpose options, such as muscle pain relief, joint support, sports performance improvement, or blood circulation promotion, etc., and can also customize special needs. The system will record the target area (such as neck, shoulder, knee), symptom description (such as pain level, muscle stiffness) and treatment goals in detail. Taking the athlete Xiao Zhang as an example, he chose "Relieve right shoulder muscle tension and reduce pain" during the filling process, and marked the key application area as the levator scapulae. The accurate collection of this information provides a clear basis for the treatment direction for the subsequent recommendation of the type of tape and the cutting shape.

[0043] For example, next, the system needs to obtain detailed biometric information of the patient's target part. In terms of specific operation, a portable 3D scanner or camera equipment can be used to perform high-precision surface scanning of the patient's designated part to obtain the surface size (length, width, circumference), surface contour morphology (whether there are obvious curves, irregular protrusions, etc.) and local skin characteristics (such as skin elasticity, muscle tension) of the part. In addition, in order to further enhance personalized data, auxiliary features such as the patient's daily exercise frequency and range of joint motion can also be obtained synchronously through historical health records or wearable devices. Taking Xiao Zhang as an example, after the device scanned the scapular area of ​​his right shoulder, it was recognized that the part had an arc-shaped contour, with a size of approximately 12cm×15cm, and there was a muscle bulge area on the surface. It was appropriate to focus on the curvature and flatness of the patch.

[0044] Exemplarily, the system analyzes the treatment purpose information and biometric information collected in the first two steps, calls the built-in patch morphology and function model database, and intelligently matches the most suitable patch cutting plan. Specifically, the system first determines the appropriate patch type based on the patient's treatment purpose. For example, Y-type or I-type patches are usually recommended for pain relief, while X-type or fan-shaped patches are often used for joint support. Secondly, based on the morphological characteristics of the target area, the system uses an algorithm to calculate the appropriate patch length, width, bifurcation length, and patch edge shape to ensure that the patch can cover the required area and conform to the skin surface contour to avoid wrinkles, pulling, or unstable adhesion due to size mismatch. For example, Xiao Zhang's needs are matched with "Y-type patches to relieve shoulder muscle tension." The system combines its shoulder scan data to automatically generate a recommended patch size of 25cm×5cm, a bifurcation length of 10cm, and appropriately trims the edges to accommodate the curvature of the scapular area, forming a complete cutting instruction.

[0045] Exemplarily, the system sends the generated recommended patch shape data and size data to the execution device, controlling it to automatically complete the patch cutting process. The execution device usually includes an automatic feeding device, an intelligent cutting module and a discharging system, equipped with high-precision CNC blades, which can achieve precise cutting within the millimeter error range according to the received instructions. The patch storage roll is pre-loaded with conventional patch materials, and the system automatically selects the corresponding roll material according to the required type. In Xiao Zhang's example, after the device received the recommended parameters for the Y-type patch, the execution module automatically cuts out a 25cm×5cm Y-type patch with smooth and symmetrical bifurcations and clean and neat edges. The cut patch is then output, supplemented by screen prompts for application method suggestions (such as patch stretch percentage, fitting direction, etc.), which greatly simplifies the manual cutting steps.

[0046] In summary, the kinesio taping application assistance method provided in the embodiments of the present application obtains treatment objective information from a target patient, obtains biometric information from the target patient, and determines recommended patch shape data and recommended patch size data based on the physiological sign information and treatment objective information. This allows the execution device to cut a pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain a target patch. This precisely matches the patient's body part characteristics, avoiding blind, empirical cutting. This improves the fit and enhances the patch's functional effectiveness (e.g., better fixation and greater elasticity). Pre-cutting optimizes the shape to accommodate irregular areas, reducing the risk of wrinkles and bubbles. The patch's edges are more easily aligned with the surface, improving patient comfort and application time. Novice users can rely on recommendations and pre-cutting, reducing the learning curve and application time. The standardized process facilitates widespread adoption and is suitable for use in hospitals, sports rehabilitation institutions, and self-help settings at home. Because both patient information collection and patch cutting are automatically performed by the system, novice users can complete professional-level kinesio taping based on recommended data without having to master complex patch cutting techniques. Precisely matching the size and shape of the patient's target area avoids patch waste or poor treatment results due to improper cutting, ensuring the patch adheres smoothly to curved and irregular areas without wrinkles or bubbles, extending the application time. The entire process is highly automated, reducing manual operation time and facilitating large-scale application in hospital rehabilitation departments, sports teams, and community health centers. It is particularly suitable for the rapid deployment of standardized rehabilitation services.

[0047] For example, after analyzing the purpose of self-treatment, physiological signs, biometrics, images and posture, the system automatically generates a taping prescription. Each taping step is equipped with: image-assisted markings, such as marking the starting point, direction, and stretching method of the taping in the uploaded image; video prompts, such as a standard operation video showing the taping step (which can be a model animation or a real-life demonstration); voice guidance, such as the system can read out: "Please stand, relax your shoulders naturally, align the Y-shaped tape under the acromion, apply it inward and downward, and stretch it 30%." Combined with image recognition or posture sensing, it determines whether the user has taped it in the correct position; if it is not taped correctly, the system will give a real-time prompt: "The starting point of the taping is too high, please move it down 2cm and try again." At the end of each taping prescription, the system will push personalized care suggestions and rehabilitation guidance, such as "Prepare the skin before applying the patch. It must not be damp or coated with oily substances", "Do not rub the patch after application", "It is not recommended to keep the patch on for more than 72 hours. If redness, swelling or itching occurs, remove it immediately", "If blisters or hydrolysis occur, please take a photo and upload it. The system will automatically determine whether to continue using it", "Please use a shower and immediately absorb the moisture on the surface with a towel or paper towel afterwards". In addition, rehabilitation movement suggestions and dietary suggestions are pushed in combination with the purpose of taping, such as "Do 2 sets of scapular adduction exercises daily, 10 times each set, to help relax the shoulder muscles", and "Reduce the intake of cold foods to avoid muscle tension."

[0048] According to some embodiments, the biometric information includes limb parameters, and obtaining the biometric information of the target patient includes:

[0049] The biometric information of the target patient is predicted based on the age and gender of the target patient.

[0050] It's understandable that data models can be used to analyze and recommend patch shapes and sizes using patient treatment objectives and biometric information. This information can then be precisely tailored by an intelligent actuator, ultimately achieving a combination of standardized and personalized patch effects. In particular, the introduction of methods to predict limb parameters based on the patient's age and gender during the biometric information acquisition process allows for reasonable recommendations based on big data models even when scanning equipment is lacking or clinical conditions are limited, ensuring the system's broad applicability and efficiency.

[0051] For example, the system collects treatment goal information from target patients through guided questionnaires, form input, or electronic health records. This information includes specific needs such as pain relief, joint support, improved blood circulation, and enhanced athletic ability. It also specifies the target application site (such as shoulder, waist, knee, etc.) and a description of the treatment need (such as "relieve right shoulder pain and stabilize the joint"). For example, patient Ms. Li filled in "relieve pain in the front of the left knee and strengthen joint support" as the treatment goal.

[0052] If actual measurement is not possible under clinical conditions or at home, the system predicts the patient's biometric information based on age and gender data. The system pre-establishes a large number of population statistical models, and extracts the average limb parameters (such as circumference, width) and standard deviation of specific parts (shoulders, knees, waist, etc.) based on data sets classified by different age groups, genders, and body shapes. Input the patient's basic information: age, gender, height, weight (at least one of them); match the corresponding parameter intervals through the model and output the estimated parameters of the target part. For example, a 35-year-old female with a height of 165cm and a weight of 60kg is predicted to have a knee circumference range of 36cm to 39cm and a width of about 12cm. If the patient has a brief description of his body shape (such as thin or strong), the model can further adjust the predicted parameters; at the same time, it supports patients to customize the recommended parameters. For example, Ms. Li, 35 years old, female, 165cm tall, the system automatically predicts that her left knee circumference is 38cm and the width is 12cm. Combined with the purpose of "joint support", it recommends X Type of patch, 30cm long, 5cm wide, with the cross angle adjusted to adapt to the knee motion curve. Based on the acquired treatment purpose information and biometric information (direct measurement or predicted results), the system calls the functional model library to complete the patch recommendation. The patch type can be matched according to functional requirements. For example, X-shaped or fan-shaped patches are recommended for support needs; I-type and Y-type are recommended for pain relief. The total length, width, and bifurcation length of the patch can be reasonably allocated in combination with the surface size data of the part. For example, for front support of the knee joint, it is recommended that the bifurcation length cover the muscles around the knee joint to improve the stability of the patch. Generate adaptive cutting plans, such as adjusting the curvature of the patch edge; if the predicted data is used, the system The size adjustment coefficient can be set to allow the operator to make fine adjustments based on clinical observations. After the recommended patch data is generated, it is transmitted to the execution device control system. For example, the pre-stored patch roll can be automatically called; the CNC tool cuts according to the recommended size and shape data; supports fast switching of common shapes (I type, Y type, X type, fan shape); after completion, it is output and accompanied by a visual application guide to ensure that the operator can easily master the application method. In the case of Ms. Li's knee joint, the system automatically cut out an X-shaped patch with a length of 30cm and a width of 5cm. The bifurcation angle fits the knee and guides it to be applied according to the prompts without manual cutting or experience accumulation. Thus, the biological data is obtained by measuring and predicting the dual channels. The data-driven recommendation ensures that each patient receives a personalized patch shape and size, avoiding the inefficiency and poor results of traditional "one-size-fits-all" cutting. Therefore, whether it is a high-end 3D scanning site or a basic medical environment, only basic information needs to be entered to complete an effective recommendation. Novice operators only need to enter information and apply the recommended patch without having to master complex cutting techniques.By combining prediction and measurement, we ensure that the patch size is perfectly matched to the patient's area, reducing the risk of wrinkles and bubbles and improving application stability. This standardized closed-loop process of patch recommendation, cutting, and application is suitable for promotion in various scenarios, including hospital rehabilitation departments, sports teams, and community and family rehabilitation.

[0053] According to some embodiments, the biometric information includes limb parameters, and obtaining the biometric information of the target patient includes:

[0054] The biometric information of the target patient is determined based on the image information of the target patient.

[0055] It is understood that by obtaining the patient's treatment goal information and biometric information, a recommended patch shape and size data can be generated based on an analytical model, and precise cutting can be performed using an intelligent execution device. Biometric information includes limb parameters, which can be obtained in a variety of flexible ways, including direct measurement, predictive calculation, and extraction based on patient image information, ensuring the method's broad applicability and intelligence. In particular, identifying the patient's limb parameters through image information enables convenient, efficient, and non-invasive data collection, suitable for self-photography by patients or in telemedicine environments.

[0056] For example, patients can fill in or select treatment purpose information through mobile APP, hospital terminal or manual entry, and clarify the specific parts and needs that need to relieve symptoms and improve functions. The information covers pain relief, joint support, muscle function enhancement, blood circulation improvement, etc., and can be accompanied by symptom descriptions (such as pain level, duration, etc.). For example, the patient Mr. Zhang filled in "Relieve pain in the front of the right knee and strengthen support" as the treatment purpose. Obtaining the biometric information of the target patient supports multiple acquisition methods. For example, when conditions permit, 3D scanners, measuring tools, etc. are used to directly obtain the limb parameters of the target part. The collected data includes the length, width, circumference, surface contour morphology and muscle tension of the target part. For example, after scanning Mr. Zhang's knee, the circumference of the knee is 40cm, and the front surface of the knee is relatively flat, which is suitable for the use of a support patch. If there are no scanning conditions, the system calls the pre-trained model through the patient's basic information (such as age, gender, height, and weight) to predict the typical limb parameter range of the target part. For example, Mr. Zhang, a 45-year-old male with a height of 175 cm, was predicted by the system to have a right knee circumference of approximately 39 cm to 42 cm. Based on the treatment objectives, the system generated taping parameters suitable for a medium-sized X-shaped taping. In scenarios such as home-based telerehabilitation, primary healthcare, or patient self-care, image acquisition can be used. For example, the patient uses a mobile phone, tablet, or hospital equipment to capture a set of standardized images of the target area. The system guides the shooting angle (such as front, side, and overhead) to ensure image clarity and lighting conditions. The system denoises, enhances, and corrects distortion of the images. Pose estimation algorithms and object detection models can be used to automatically locate key points of the captured area. Trained convolutional neural networks or other deep learning models can be used to extract key parameters such as limb contour, length, width, and circumference. Image scale can be calibrated using known reference objects (such as standard cards or ruler stickers) or ratios of human physiological characteristics to improve measurement accuracy. The system calculates the actual dimensions of the target area. For example, image analysis of Mr. Zhang's right knee shows a circumference of 40.5 cm and a width of 12.5 cm. The surface is smooth and has a well-defined curvature, making it suitable for standard X-shaped tape cutting. The system integrates the patient's treatment objective information with acquired biometric information (including direct measurement, prediction, or image recognition), and calls upon a built-in tape function model to determine the tape type: for example, Y-shaped or I-shaped tape is recommended for pain relief, while X-shaped or fan-shaped tape is recommended for joint support. The system also calculates the dimensions and bifurcation length: for example, if the knee circumference is 40 cm, an X-shaped tape with a length of 30 cm and a bifurcation angle that accommodates joint flexion and extension is recommended. Edge morphology is also optimized, specifically fine-tuning the tape edges based on the skin surface curve identified in the image data to prevent wrinkling. This recommended data is transmitted to the actuator control system, which automatically selects the appropriate tape roll. CNC tools precisely cut the tape based on the recommended data, including length, width, and contours. Upon completion, the tape is discharged with an application guide to guide the patient or operator in proper application.Taking Mr. Zhang as an example, the system cuts out an X-shaped patch that fits his right knee. The bifurcation angle is fine-tuned according to the knee image data, with high cutting accuracy and excellent fitting effect. Through image information + AI recognition technology, the patient's limb parameters are obtained quickly and contactlessly, greatly improving the efficiency and applicability of biometric data collection. Flexible switching is achieved by combining predictive models and direct measurements to ensure that the data acquisition method adapts to different clinical environments and form diversified acquisition channels. The image recognition part uses mature image processing and deep learning algorithms to ensure high-precision extraction of dimensional parameters. At the same time, it can be combined with surface markers (such as standard reference stickers) for scale calibration.

[0057] In some examples, this also includes:

[0058] The target taping site is determined based on the analysis of the physiological sign information and the treatment purpose information.

[0059] It is understood that based on the patient's treatment objectives and physiological signs, a data analysis model can be used to intelligently determine the most appropriate target taping site. Based on the biometric information of that site (which can be obtained through measurement, image recognition, or prediction), the optimal patch shape and size can be recommended, and the execution device can perform high-precision automatic cutting to achieve both standardized and personalized taping. In particular, by combining the patient's physiological sign data (such as muscle tension, pain area, movement posture analysis, etc.) with treatment needs, the optimal taping site can be automatically determined, reducing human judgment errors and improving efficacy.

[0060] For example, the system guides patients or medical staff to fill in treatment needs, including pain relief, joint support, improved blood circulation, etc., and allows vague descriptions or unspecified specific taping locations. For example, the patient Mr. Wang only described that he "felt sore in his left shoulder and upper back and wanted to improve it" and selected "relieve shoulder muscle fatigue." Methods for obtaining physiological sign information include but are not limited to the following: muscle tension detection equipment (such as surface electromyographs) detect muscle tension in the target area; thermal imaging of painful areas identifies abnormal temperature areas and indirectly determines blood flow and inflammation points; motion posture monitoring (such as wearable sensors or posture recognition systems) collects movement patterns and finds abnormal posture load locations; and the patient's medical history and physical examination data are automatically retrieved. For example, Mr. Wang underwent surface electromyograph testing and found that his left levator scapulae and trapezius muscles were overactive in electromyographic activity. At the same time, posture analysis showed that his shoulders were tilted forward. The system uses a preset physiological sign-location association model and a treatment purpose-location matching model to comprehensively analyze and derive recommended taping locations. This can include establishing a physiological sign-to-site mapping database, associating common muscle electrical signal abnormalities, temperature abnormalities, and postural abnormalities with specific locations. For example, if levator scapulae hypertonicity is present, taping of the suprascapular region is recommended; if lumbar muscle tension is present, taping of the paraspinal muscles is recommended. Site recommendations can be optimized based on the treatment objective. For example, for pain relief, the system prioritizes areas of abnormal hypertonicity and inflammation; for support, the system prioritizes joints and connective muscle groups; and for blood flow improvement, the system prioritizes areas of poor circulation. Multiple sites can be prioritized. If multiple abnormalities are detected, the system recommends the preferred taping site based on symptom severity and the degree of physiological abnormality, and may also provide secondary recommendations. For example, Mr. Wang detected abnormalities in both the levator scapulae and trapezius muscles. Based on the objective of "relieving shoulder muscle fatigue," the system automatically identified the suprascapular region and medial scapular border of his left shoulder as target taping sites, and also recommended supplementary taping of the upper back. Once the target taping site is determined, the system then acquires biometric information for that site. The system then uses the identified target taping site and biometric information to determine the optimal taping site. Combined with the muscle direction and functional requirements of the part, the type of patch is matched (such as Y-shaped to relieve local muscle tension). The total length, width, and bifurcation length of the patch are calculated to ensure that key parts are covered and adapted to the surface contour. Refine the edge cutting so that the patch fits smoothly on curved parts such as the suprascapular area. In Mr. Wang's case, the system recommended a Y-shaped patch with a length of 30cm, a width of 5cm, and a bifurcation of 12cm, covering the levator scapulae and the inner edge of the scapula. Therefore, by integrating physiological sign information with treatment purpose information, the target taping site is intelligently determined, avoiding errors in site selection caused by unclear patient descriptions or doctor's empirical judgment; especially for patients with complex symptoms or pain in multiple parts, the system can prioritize the application areas based on sign analysis to ensure maximum therapeutic effect.

[0061] In some examples, this also includes:

[0062] Generate a request to obtain the image of the target taping part,

[0063] When receiving the target taping part image in response to the acquisition request, adding an auxiliary taping mark to the target taping part image based on the recommended taping shape data and the recommended taping size data;

[0064] The target taping part image with the auxiliary taping mark is displayed to prompt the user to perform taping.

[0065] It is understandable that the most appropriate target taping site, patch shape, and size can be recommended through intelligent analysis of the patient's treatment objectives, physiological signs, and biometric information. At the same time, to lower the operator's technical threshold and avoid application errors, this method has added a function that automatically generates auxiliary taping marks based on the image of the target taping site. Combined with visual image prompts, it guides the user to accurately complete the taping operation, achieving a fully closed-loop operation process from intelligent recommendation to cutting to intuitive guidance to application.

[0066] For example, the system comprehensively analyzes and determines the optimal target taping site, such as the levator scapulae area and the erector spinae area of ​​the lumbar spine. Multiple sites can be ranked by severity. Direct measurement, image recognition, or prediction methods can be used to obtain site dimensions and contour information for use in recommending taping parameters. The taping shape (e.g., Y-shaped, X-shaped), dimensions, and bifurcation length are determined, and cropping data is generated. After determining the target taping site, the system can automatically generate an image acquisition request, prompting the user to capture a clear image or video of that area. This can be achieved by displaying a prompt on the mobile app / terminal interface: "Please capture a frontal image of the suprascapular area of ​​your left shoulder." Shooting instructions (e.g., recommended angles and lighting) and reference comparison images are provided to ensure that the image meets the requirements. Once the system receives the target site image uploaded by the user, it automatically corrects the image angle, removes noise, and enhances the contours. A trained model is then used to identify key points of the target site contour in the captured image, such as the shoulder contour and knee curve. The previously analyzed recommended taping shape and dimensions are overlaid onto the corresponding image area as a visual layer. Markings can include: a tape shape outline (clearly depicting the area covered by the tape); taping direction arrows (to guide the direction of tape stretching); dotted lines at the bifurcation locations (e.g., for a Y-shaped bifurcation area); and markers for the tape's starting and ending points. Optionally, a tape stretching intensity prompt (e.g., "30% stretch recommended") can be displayed. For example, after a patient uploads an image of their left shoulder, the system overlays a translucent Y-shaped tape outline on the image, marking the starting point below the acromion and the two bifurcations along the medial edge of the scapula. Arrows indicate the stretching direction, and dotted lines mark the end points. Finally, the system visually displays the image with auxiliary taping markers on the patient's app interface or hospital terminal, guiding the operator to apply the tape according to the visual prompts in the image, ensuring accurate tape placement, correct direction, standardized bifurcation and edge positioning, and a clear degree of stretch. The system can also include animated or voice prompts for the application steps to enhance the user experience. Based on the recommended tape data, the cutting device is controlled to cut the tape, and the user applies the tape according to the auxiliary markings. This allows the user to directly reference the image with auxiliary taping markers to avoid issues with tape position, direction, and bifurcation deviations. Even beginners and patients can easily and accurately apply the patch themselves, reducing reliance on professional rehabilitation staff. Each taping process is visually standardized to ensure consistent efficacy and facilitate adoption in hospitals, communities, and homes. Intuitive and easy-to-understand instructions reduce operational confusion and shorten application preparation time.

[0067] In some examples, the targeting patch includes a fixation segment and a treatment segment, and the method further includes:

[0068] Generate a request to obtain the image of the target taping part,

[0069] Upon receiving the target taping site image in response to the acquisition request, the length of the fixed segment is determined based on the taping site type, taping site size and taping site skin condition indicated by the target taping site image, wherein the taping site skin condition includes skin smoothness and / or skin temperature.

[0070] It is understood that the length of the fixed segment is dynamically adjusted according to the epidermal characteristics of the target taping site (such as smoothness and temperature) to ensure that the patch can achieve good fixation and therapeutic effects under various skin conditions. This function uses AI to analyze the epidermal state of the taping area by acquiring images of the target taping site, and intelligently adjusts the cutting parameters to prevent the patch from falling off or not being firmly fixed due to factors such as greasy skin, sweating, and rough surface.

[0071] It is understandable that in order to further improve the stability of the Kinesio patch under different patient skin conditions, the target patch is subdivided into two parts: a fixed segment and a treatment segment. The fixed segment is located at the starting and ending ends of the patch, and is used to achieve a stable attachment of the patch to the skin surface; while the treatment segment is located between the fixed segments and undertakes therapeutic functions such as supporting, relaxing, and correcting the patient's local muscles, joints, or soft tissues. In actual application, based on the differences in individual patient skin surface conditions, the system dynamically adjusts the length of the fixed segment through image recognition technology to ensure that the patch has good adhesion under various skin conditions and avoid the problem of the patch edge curling or falling off.

[0072] Exemplarily, after determining the patient's target taping site, the system generates an image acquisition request, prompting the user or operator to use a mobile device or terminal to take a clear image of the target site, ensuring that the image fully displays the contours and surface conditions of the target site. After receiving the image of the target taping site in response to the acquisition request, the system activates the image processing module and extracts the following key data based on a pre-trained image recognition model: taping site type, such as shoulder, knee, waist, etc.; taping site dimensions, including geometric parameters such as the length, width, and circumference of the target site; and the epidermal condition of the taping site, which can specifically include epidermal finish. The system determines whether the skin surface is smooth, oily, or rough based on image brightness, reflectivity, and surface texture characteristics. And epidermal temperature. Local skin surface temperature data is acquired using a compatible thermal imaging device or a synchronous temperature measurement module. Based on a comprehensive analysis of the extracted information, the system dynamically adjusts the length of the fixed segment. When the finish is high (greasy skin, smooth surface), the patch is prone to sliding or warping. The system will appropriately extend the standard length of the fixed segment (such as 5cm), for example, to 7cm or 8cm, to expand the contact area between the patch and the skin, enhance friction, and improve adhesion. When the epidermal temperature is high (for example, the local temperature is detected to be over 37°C), the system will identify it as a state of excessive sweating and high skin temperature. The adhesive layer of the patch is temperature-sensitive. As the skin surface temperature rises, the temperature of the adhesive layer rises synchronously, and the colloid may soften, resulting in a decrease in overall viscosity. Especially during exercise or high temperature environments, the patch is easy to fall off. Therefore, the system will automatically extend the length of the fixed segment by 1-3cm based on the temperature data to ensure a larger area of ​​fixation and improve overall adhesion. While determining the length of the fixed segment, the system will update the complete patch design data, including the overall length, width, specific distribution of the fixed segment and treatment segment, and transmit it to the automatic cutting device to complete high-precision patch cutting. Based on the recommended patch parameters, the system overlays visual markers on the image of the target taping area, clearly indicating the starting and ending points of the fixed segment and the treatment area covered. The system also displays a prompt: "The fixed segment length has been automatically adjusted to X cm based on skin smoothness and temperature. Please apply according to the markers." Skin smoothness directly affects the friction between the patch and the skin. Oilier or smoother the skin, the more likely the patch edge will lift or slip, requiring a longer fixed segment to increase the friction area. Skin temperature affects the temperature of the patch's adhesive layer. Adhesive softens in high temperatures, reducing adhesion. High temperatures, coupled with sweating, further impair adhesion. Therefore, the system extends the fixed segment to increase the fixed area and visually prompts the user to cleanse or cool the skin. Automatically adjusting the fixed segment length based on skin smoothness and temperature prevents the patch from peeling or lifting. Extending the fixed segment effectively stabilizes the treatment area, ensuring long-term treatment without interruption due to patch shedding. Fixed segment length adjustments are intuitively indicated in the image, eliminating the need for specialized skin analysis experience.Whether in hospital, sports rehabilitation or home self-help, it can be intelligently adapted according to the user's skin condition to improve universality.

[0073] In some examples, before the step of generating a target taping site image acquisition request, the method further includes:

[0074] Determining an ideal posture for the taping site based on the treatment purpose information analysis, wherein the image acquisition request includes the ideal posture for the taping site;

[0075] When the target taping part image matches the ideal taping part preparation posture, an auxiliary taping mark is added to the target taping part image based on the recommended patch shape data and the recommended patch size data; otherwise, a posture adjustment prompt message is generated.

[0076] Exemplarily, after obtaining the patient's treatment purpose information, the system first calls the built-in treatment purpose-posture matching model to analyze and determine the preparatory ideal posture suitable for the current taping site. The system queries the built-in database based on the treatment purpose (such as shoulder muscle relaxation, lumbar support, knee joint stabilization) and the target taping site type, and matches the corresponding standardized ideal posture data. The ideal posture data may include: body position requirements (such as standing, sitting, prone, supine, etc.), site angles (such as shoulders relaxed and drooping, knees bent 15 degrees), and key point angle data (such as shoulder, elbow, and knee joint angle ranges). For example, for the treatment purpose of "relieving right shoulder pain and stabilizing the shoulder joint", the system determines the preparatory ideal posture as: shoulders naturally drooping, head slightly lowered, and standing in a relaxed state. When generating a target taping site image acquisition request, the system adds the above-mentioned preparatory ideal posture data to the image acquisition request. On the user interface or terminal interface, an image acquisition prompt pops up, and the corresponding ideal posture reference image / animation is displayed at the same time. The user is explicitly prompted: "Please maintain the following posture to capture the image of the target area." For example, "Stand naturally and relax, shoulders lowered, head slightly lowered, back straight." This ensures that the user clearly understands the specific posture they need to adopt before capturing the image, ensuring the accuracy of subsequent analysis. After the user captures and uploads an image of the target taping area, the system performs contour recognition on the image to locate the location and shape of the taping area. It then performs posture recognition, using image posture estimation algorithms (such as keypoint detection and posture regression models) to extract the patient's current body posture data. The system compares the actual posture data identified in the image with the previously generated ideal posture data to determine whether the current posture meets the requirements. If a match is found, the system confirms that the user has maintained the standard ideal posture and proceeds to the next steps. Based on the recommended tape shape and size data, auxiliary taping markers are superimposed on the image to clearly indicate the tape start and end points, fixation segments, treatment segment divisions, and stretching direction. If a match is found, the system automatically generates a posture adjustment prompt to inform the user of the specific points that need to be adjusted. For example, "Please relax your shoulders and lower your head slightly" or "Bend your knees slightly 15°." It can also be accompanied by a posture diagram or dynamic animation to guide the user to readjust. After the user adjusts the posture, he or she takes a photo and uploads the image again. The system will re-match it until it meets the standard posture and then enter the taping auxiliary prompt step. Therefore, various treatment needs and taping sites correspond to different standardized postures. The system ensures that the starting state of treatment is scientific and reasonable through matching. The user knows clearly what posture to maintain before taking the photo, avoiding subsequent recognition errors due to non-standard shooting. Through posture estimation technology, the patient's actual posture is identified in real time, accurately compared, and the optimal taping environment is ensured. The taping operation is always completed in the recommended posture to ensure that the stretching direction and coverage position of the patch are consistent with the muscle direction. The user does not need to judge whether the posture is correct or not. The system recognizes and prompts in real time, reducing the difficulty of operation.Verify posture during the photo session, reducing the risk of patch cutting or application failure due to incorrect posture during the taping process. Suitable for hospitals, rehabilitation institutions, sports rehabilitation settings, and patients can also use it for self-service.

[0077] In some examples, this also includes:

[0078] Determining the ideal posture for preparing the taping site based on the treatment purpose information analysis;

[0079] When the user holds the user smart terminal device, the actual posture of the taping part preparation is determined based on the acceleration sensor and gyroscope of the user smart terminal device;

[0080] When the actual taping position preparation posture matches the ideal taping position preparation posture, an auxiliary taping mark is added to the target taping position image based on the recommended patch shape data and the recommended patch size data; otherwise, a posture adjustment prompt message is generated.

[0081] To further ensure the accuracy of Kinesio taping application placement and angle and enhance its effectiveness, the system, upon receiving the patient's treatment objective, not only determines the taping location and recommended taping parameters, but also analyzes the ideal preparatory posture for taping that area based on the treatment objective. The system incorporates a database of treatment objective-posture matching, with standardized ideal postures corresponding to different treatment needs and taping locations. For example, for levator scapulae relaxation, the patient is recommended to slightly lower their head and naturally lower their shoulders; for lumbar support, the patient is recommended to stand or lie flat with their back straight; and for knee stabilization support, the patient is recommended to naturally bend their knees 15° and relax their leg muscles. Based on the user's input treatment objective, the system automatically matches the ideal posture for the corresponding taping location and displays it to the user via a diagram or animation on the terminal interface. During the actual taping process, the user typically holds a smart terminal device such as a mobile phone or tablet (e.g., using an app to capture an image of the target taping location). The system then uses the device's accelerometer and gyroscope to detect the user's current posture in real time. Built-in sensors in the device capture the user's hand and torso movement data, inferring changes in angle and acceleration along each axis during the taping process. The system compares this real-time data with pre-set ideal posture feature values ​​to determine whether the user's current posture matches the recommended posture. If the pre-set posture of the current taping area matches the ideal posture, the system confirms the posture is correct and proceeds to the next step. The previously analyzed and recommended tape shape and size data are overlaid on the captured image of the target taping area to generate clear and intuitive auxiliary taping markers, indicating the user's starting and ending positions, stretching direction, and the division between fixed and treatment sections. If a deviation between the actual and ideal posture is detected, the system identifies the specific deviation (e.g., shoulders not relaxed, knees not bent enough) based on sensor data. A posture adjustment prompt is automatically generated and pushed to the user's terminal interface, providing clear and specific adjustment suggestions such as "Please let your shoulders hang naturally" or "Slightly bend your knees." The system can also display posture diagrams or animations to guide the user through the correct posture adjustment. When the system detects that the user has adjusted to the recommended ideal posture, it will again superimpose the auxiliary taping mark on the target taping area image to ensure that the patch cutting and application operations are carried out under optimal posture conditions, avoiding inaccurate patch positioning or reduced application effect due to improper posture. Therefore, the functional effects of the kinesiology tape (such as support, relaxation, and correction) are dependent on the patient's posture. Maintaining the correct posture helps the tape to exert force accurately. The system standardizes the ideal posture through the treatment purpose and posture database. It makes full use of the accelerometer and gyroscope of the smart terminal, does not add additional equipment burden, monitors the user's current posture in real time, and improves the interactive experience. When the posture does not match, the system promptly pushes adjustment suggestions to reduce application errors. Ensure that the patch is applied when the patient maintains the correct posture to avoid position and angle deviations that affect the support or relaxation effect.The system automatically guides patients in adjusting their posture, eliminating the need for manual intervention from rehabilitation staff. It's suitable for self-taping by patients or at primary rehabilitation centers. Real-time posture detection and dynamic prompts ensure users are clearly informed of each step, enhancing confidence. Auxiliary taping markings are generated only after posture confirmation, ensuring accurate marking and minimizing rework and taping failures.

[0082] For example, before applying the patch, the unit can automatically clean the skin surface at the application site, removing grease, dirt, and impurities, providing a better foundation for the patch to adhere. Cleaning can be done by spraying with a mild cleanser combined with wiping with a soft cloth, ensuring a safe, comfortable, and effective cleaning process.

[0083] For example, moderately heating the Kinesio patch can improve its adhesion, making it easier to adhere to the skin. The temperature control unit can precisely control the heating temperature and time based on the patch material and the patient's skin tolerance, preventing skin damage caused by excessive temperatures.

[0084] For example, during the patch application process, the pressure-applying unit can evenly apply pressure to the patch according to a preset pressure distribution pattern, helping to expel air between the patch and the skin, effectively reducing wrinkles and bubbles. For irregular areas such as joints, the pressure-applying unit can also adjust the intensity and direction of pressure in real time according to the instructions of the intelligent control system to achieve a perfect fit between the patch and the skin surface.

[0085] See also Figure 2 In the embodiments of the present application, an embodiment of the auxiliary device for applying the kinesiology tape may include:

[0086] A first acquiring unit 21 is used to acquire treatment purpose information of a target patient;

[0087] A second acquiring unit 22 is configured to acquire biometric information of the target patient;

[0088] The analyzing unit 23 is configured to determine recommended patch shape data and recommended patch size data based on the physiological sign information and the treatment purpose information, so as to control the executing device to cut the pre-stored patch based on the recommended patch shape data and recommended patch size data.

[0089] In summary, the kinesio patch application assistance device provided in the embodiment of the present application obtains the treatment purpose information of the target patient; obtains the biometric information of the target patient; and determines the recommended patch shape data and recommended patch size data based on the physiological sign information and the treatment purpose information, so as to control the execution device to cut the pre-stored patch based on the recommended patch shape data and the recommended patch size data to obtain the target patch. In this way, the characteristics of the patient's body parts are accurately matched to avoid blind experience-based cutting. The fitting effect is improved and the functional effectiveness of the patch is enhanced (such as better fixation and higher elastic auxiliary effect). The shape is optimized by pre-cutting to adapt to irregular parts and reduce the risk of wrinkles and bubbles. The edge of the patch is easier to fit smoothly with the surface, which improves the patient's comfort and application time. Novices can rely on recommendations and pre-cutting to reduce the learning curve and operation time. The standardized process is easy to promote and is suitable for scenarios such as hospitals, sports rehabilitation institutions, and family self-help.

[0090] like Figure 3 As shown, an embodiment of the present application further provides an electronic device 300, including a memory 310, a processor 320, and a computer program 311 stored in the memory 320 and executable on the processor. When the processor 320 executes the computer program 311, the steps of any of the above-mentioned methods for assisting the application of kinesiology tape are implemented:

[0091] Obtain information on treatment goals for target patients;

[0092] Obtaining biometric information of the target patient;

[0093] Recommended patch shape data and recommended patch size data are determined based on the physiological sign information and treatment purpose information, so as to control the execution device to cut the pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain the target patch.

[0094] Since the electronic device introduced in this embodiment is a device used to implement a kinesiology tape application auxiliary device in the embodiment of this application, based on the method introduced in the embodiment of this application, those skilled in the art can understand the specific implementation of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of this application will not be described in detail here. As long as the device used by those skilled in the art to implement the method in the embodiment of this application falls within the scope of protection to be provided by this application.

[0095] In the specific implementation process, the computer program 311 can be implemented when executed by the processor Figure 1 Any implementation manner in the corresponding embodiment:

[0096] Obtain information on treatment goals for target patients;

[0097] Obtaining biometric information of the target patient;

[0098] Recommended patch shape data and recommended patch size data are determined based on the physiological sign information and treatment purpose information, so as to control the execution device to cut the pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain the target patch.

[0099] It should be noted that, in the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0100] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0101] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0102] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0103] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0104] The present application also provides a computer program product, which includes computer software instructions. When the computer software instructions are executed on a processing device, the processing device is caused to execute the following Figure 1 This corresponds to the kinesiology tape application assistance process in the embodiment.

[0105] A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0106] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0107] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0108] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0109] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0110] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0111] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A Kinesio taping application assisting method, characterized in that: include: Obtain information on treatment goals for target patients; Obtaining biometric information of the target patient; Recommended patch shape data and recommended patch size data are determined based on the physiological sign information and treatment purpose information, so as to control the execution device to cut the pre-stored patch based on the recommended patch shape data and recommended patch size data to obtain the target patch.

2. The method according to claim 1, wherein The biometric information package includes limb parameters, and obtaining the biometric information of the target patient includes: Predicting the biometric information of the target patient based on the age and gender of the target patient; and / or, The biometric information of the target patient is determined based on the image information of the target patient.

3. The method according to claim 1, wherein Also includes: The target taping site is determined based on the analysis of the physiological sign information and the treatment purpose information.

4. The method according to claim 3, wherein Also includes: Generate a request to obtain the image of the target taping part, When receiving the target taping part image in response to the acquisition request, adding an auxiliary taping mark to the target taping part image based on the recommended taping shape data and the recommended taping size data; The target taping part image with the auxiliary taping mark is displayed to prompt the user to perform taping.

5. The method according to claim 3, wherein The target patch includes a fixing section and a treatment section, and the method further includes: Generate a request to obtain the image of the target taping part, Upon receiving the target taping site image in response to the acquisition request, the length of the fixed segment is determined based on the taping site type, taping site size and taping site skin condition indicated by the target taping site image, wherein the taping site skin condition includes skin smoothness and / or skin temperature.

6. The method according to claim 4, wherein Before the step of generating a target taping site image acquisition request, the method further includes: Determining an ideal posture for the taping site based on the treatment purpose information analysis, wherein the image acquisition request includes the ideal posture for the taping site; When the target taping part image matches the ideal taping part preparation posture, an auxiliary taping mark is added to the target taping part image based on the recommended patch shape data and the recommended patch size data; otherwise, a posture adjustment prompt message is generated.

7. The method according to claim 3, wherein Also includes: Determining the ideal posture for preparing the taping site based on the treatment purpose information analysis; When the user holds the user smart terminal device, the actual posture of the taping part preparation is determined based on the acceleration sensor and gyroscope of the user smart terminal device; When the actual taping position preparation posture matches the ideal taping position preparation posture, an auxiliary taping mark is added to the target taping position image based on the recommended patch shape data and the recommended patch size data; otherwise, a posture adjustment prompt message is generated.

8. A kinesiology tape application assisting device, characterized in that: include: a first acquiring unit, configured to acquire treatment purpose information of a target patient; a second acquiring unit, configured to acquire biometric information of the target patient; The analyzing unit is configured to determine recommended patch shape data and recommended patch size data based on the physiological sign information and the treatment purpose information, so as to control the executing device to cut the pre-stored patch based on the recommended patch shape data and the recommended patch size data.

9. An electronic device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor is configured to implement the steps of the kinesiology tape application assisting method according to any one of claims 1 to 7 when executing the computer program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the kinesiology tape application assistance method according to any one of claims 1 to 7 is implemented.

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