A method and system for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery

Abstract

The present invention belongs to the field of queue data management, and provides a method and system for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery, including: obtaining patient data to be acupunctured, and submitting the acupuncture patient data to the RedCap database; determining the queue data recording time according to the patient data to be acupunctured; prompting the acupuncture time according to the queue data recording time; performing acupuncture operation according to the acupuncture time; recording the operation image of the acupuncture operation; identifying the acupuncture point of the acupuncture operation according to the operation image; and submitting the acupuncture point and the corresponding acupuncture operation time to the RedCap database. The above scheme can automatically submit acupuncture queue data, thereby improving ease of use.

Description

Technical Field

[0001] The present invention belongs to the field of queue data management, and in particular relates to a method and system for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery. Background Art

[0002] Postoperative intestinal obstruction after abdominal tumor surgery refers to intestinal obstruction that occurs after abdominal tumor surgery. Abdominal tumor surgery usually involves the removal, repair or movement of abdominal organs or tissues, which may affect the normal structure and function of the digestive tract. Postoperative intestinal obstruction may be caused by postoperative tissue adhesion, intestinal stenosis, postoperative bleeding, intestinal scar formation, etc.

[0003] Postoperative intestinal obstruction is a common complication after abdominal tumor surgery, which can cause nausea, vomiting, abdominal pain, bloating, cessation of defecation and flatulence, etc. Due to the high incidence and mortality of postoperative intestinal obstruction after abdominal tumor surgery, the poor targeting of Western medicine treatment and obvious side effects, and the need for another surgery in severe cases, the specific treatment of postoperative intestinal obstruction after abdominal tumor surgery has always been the focus of attention and debate.

[0004] At present, studies have reported that acupuncture is effective in treating postoperative intestinal obstruction, safe and without side effects, but the number of related studies on abdominal tumor surgery is small and the quality is not high, which affects the promotion and application of acupuncture in this field. Therefore, it is necessary to use patients with postoperative intestinal obstruction of abdominal tumors as research subjects, and conduct a cohort study on optimizing acupuncture treatment regimen and conventional treatment through a prospective, randomized controlled design.

[0005] Existing technologies usually use REDCap (https: / / projectredcap.org / ) to establish a prospective cohort study database, such as "How to Use REDCap to Establish a Prospective Cohort Study Database" published by David et al., but acupuncture treatment requires recording many data items, especially the need to record acupuncture points, time, etc. When there are many acupuncture points, the record is complicated, resulting in cumbersome cohort data entry operations, and a more efficient and automated data management method is needed. Summary of the invention

[0006] In order to solve the problems in the prior art, the present invention provides a method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery, the method comprising: acquiring patient data to be acupunctured, and submitting the acupuncture patient data to a RedCap database; determining a queue data recording time according to the patient data to be acupunctured; prompting acupuncture time according to the queue data recording time; performing acupuncture operation according to the acupuncture time; recording an operation image of the acupuncture operation; identifying acupoints for acupuncture operation according to the operation image; and submitting the acupoints and corresponding acupuncture operation times to the RedCap database.

[0007] Furthermore, submitting the acupuncture patient data to the RedCap database includes: analyzing the HTML structure and form fields of the data submission page of the RedCap webpage; writing a crawler program to simulate the user's operation of submitting data based on the webpage structure; before submitting the data, including login credentials or Cookie in the HTTP request; using the crawler program to submit the data by simulating the user filling in the form fields on the webpage; processing the server response to check whether the data is successfully submitted, and handling any errors or abnormal situations; setting the crawler program to execute periodically, and automatically submitting the data to the RedCap database when the data is updated.

[0008] Furthermore, the method of identifying acupuncture points for acupuncture operation based on the operation image includes: establishing a standard virtual three-dimensional human body model with human acupuncture points; before acupuncture, marking the acupuncture points on the human body with a fluorescent pen; performing acupuncture treatment at the fluorescent marked points; acquiring operation process images from at least two angles; establishing a human body three-dimensional model including fluorescent marks based on the images from at least two angles; scaling the standard virtual three-dimensional human body model to the same size as the human body three-dimensional model, and making the scaled quasi-virtual three-dimensional human body model overlap with the human body three-dimensional model; calculating the distance between the fluorescent point and the acupuncture point on the virtual three-dimensional human body model, and determining the acupuncture point with the smallest distance to the fluorescent point.

[0009] Furthermore, the method of establishing a three-dimensional human body model including fluorescent markers based on images from at least two angles includes: writing a program to collect photos or videos of the patient's body; selecting a cloud-based three-dimensional reconstruction service, and determining the API provided by the selected service based on its API documentation or developer documentation; writing a program to upload the collected photos or videos to the selected three-dimensional reconstruction service platform, using the API or SDK provided by the service, and following the instructions in its documentation; using the service's API or SDK, writing a program to start the three-dimensional reconstruction process, and after the three-dimensional reconstruction process is completed, writing a program to obtain the generated three-dimensional model.

[0010] Furthermore, scaling the standard virtual three-dimensional human body model to the same size as the human body three-dimensional model and making the scaled quasi-virtual three-dimensional human body model overlap with the human body three-dimensional model includes: using three-dimensional modeling software or a library to load the standard virtual three-dimensional human body model and the human body three-dimensional model; using a feature detection algorithm or a pattern matching algorithm to determine a point in the two models as a reference point; calculating the scaling ratio and translation vector between the two models based on the position of the reference point; and applying the calculated scaling ratio and translation vector to one of the models to align it with the other model.

[0011] Another aspect of the present invention also discloses a data management system for acupuncture queues for intestinal obstruction after abdominal tumor surgery, the system comprising:

[0012] A data management module, used for obtaining data of patients to be acupunctured and submitting the data of patients to the RedCap database;

[0013] A prompting module is used to determine the queue data recording time according to the patient data to be acupunctured; prompt the acupuncture time according to the queue data recording time; and perform acupuncture operation according to the acupuncture time;

[0014] A recording module, used for recording the operation image of the acupuncture operation;

[0015] A recognition module, used for recognizing acupoints for acupuncture operation according to the operation image;

[0016] The submission module is used to submit the acupoints and the corresponding acupuncture operation time to the RedCap database.

[0017] Furthermore, submitting the acupuncture patient data to the RedCap database includes: analyzing the HTML structure and form fields of the data submission page of the RedCap webpage; writing a crawler program to simulate the user's operation of submitting data based on the webpage structure; before submitting the data, including login credentials or Cookie in the HTTP request; using the crawler program to submit the data by simulating the user filling in the form fields on the webpage; processing the server response to check whether the data is successfully submitted, and handling any errors or abnormal situations; setting the crawler program to execute periodically, and automatically submitting the data to the RedCap database when the data is updated.

[0018] Furthermore, the method of identifying acupuncture points for acupuncture operation based on the operation image includes: establishing a standard virtual three-dimensional human body model with human acupuncture points; before acupuncture, marking the acupuncture points on the human body with a fluorescent pen; performing acupuncture treatment at the fluorescent marked points; acquiring operation process images from at least two angles; establishing a human body three-dimensional model including fluorescent marks based on the images from at least two angles; scaling the standard virtual three-dimensional human body model to the same size as the human body three-dimensional model, and making the scaled quasi-virtual three-dimensional human body model overlap with the human body three-dimensional model; calculating the distance between the fluorescent point and the acupuncture point on the virtual three-dimensional human body model, and determining the acupuncture point with the smallest distance to the fluorescent point.

[0019] Furthermore, the method of establishing a three-dimensional human body model including fluorescent markers based on images from at least two angles includes: writing a program to collect photos or videos of the patient's body; selecting a cloud-based three-dimensional reconstruction service, and determining the API provided by the selected service based on its API documentation or developer documentation; writing a program to upload the collected photos or videos to the selected three-dimensional reconstruction service platform, using the API or SDK provided by the service, and following the instructions in its documentation; using the service's API or SDK, writing a program to start the three-dimensional reconstruction process, and after the three-dimensional reconstruction process is completed, writing a program to obtain the generated three-dimensional model.

[0020] Furthermore, scaling the standard virtual three-dimensional human body model to the same size as the human body three-dimensional model and making the scaled quasi-virtual three-dimensional human body model overlap with the human body three-dimensional model includes: using three-dimensional modeling software or a library to load the standard virtual three-dimensional human body model and the human body three-dimensional model; using a feature detection algorithm or a pattern matching algorithm to determine a point in the two models as a reference point; calculating the scaling ratio and translation vector between the two models based on the position of the reference point; and applying the calculated scaling ratio and translation vector to one of the models to align it with the other model.

[0021] The present invention can produce the following beneficial effects through the above technical solution:

[0022] Automated processes can reduce the time spent on manual operations and manual data entry, thereby improving work efficiency. Medical staff can focus more on patient care and treatment instead of spending too much time on data entry and management.

[0023] Automated processes can reduce the occurrence of human errors and improve data accuracy and consistency. Through automated data transmission and recording, data errors caused by human negligence or mistakes can be avoided.

[0024] Automated processes can ensure that data is recorded and managed according to predefined standards, thereby improving the quality and reliability of data. The consistency and accuracy of data are crucial for subsequent analysis and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0026] Figure 1 is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0027] Below, the invention is preferably described in conjunction with the accompanying drawings and specific implementation methods.

[0028] This embodiment solves the above problem through the following steps:

[0029] In one embodiment, reference Figure 1 The present invention provides a method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery.

[0030] Abdominal tumor surgery is a surgical procedure performed on tumors located in the abdomen. Abdominal tumors can include many types, such as liver cancer, stomach cancer, colon cancer, intestinal tumors, ovarian cancer, etc.

[0031] Intestinal obstruction after abdominal tumor surgery is a postoperative complication, which refers to the situation where the intestines are obstructed after abdominal tumor surgery. Intestinal obstruction means that the intestinal contents cannot pass through the normal intestinal passage, resulting in increased pressure in the intestine and causing symptoms. Abdominal tumor surgery may cause intestinal adhesions, stenosis, postoperative bleeding, intestinal wall damage, etc., thereby increasing the risk of intestinal obstruction.

[0032] This example uses patients with intestinal obstruction after abdominal tumor surgery as the research subjects. Through a prospective, randomized, controlled design, the optimized acupuncture treatment plan for intestinal obstruction after abdominal tumor surgery was applied, and the optimized acupuncture treatment plan was compared with conventional treatment (enhanced recovery after surgery). A special disease cohort of patients with acupuncture-induced intestinal obstruction after abdominal tumor surgery was established. Indicators were collected based on "patient-reported outcomes", and patients were managed using an intelligent clinical research implementation platform. Relevant indicators were collected to evaluate the clinical efficacy of acupuncture treatment for intestinal obstruction after abdominal tumor surgery, so as to generate high-quality evidence-based evidence.

[0033] In order to achieve the above purpose, the present embodiment first obtains the data of patients to be acupunctured, and submits the data of patients to the RedCap database.

[0034] In order to obtain detailed cohort data, we first need to create a file for the patient and obtain the data of the surgical patients. The patient data can usually be obtained from the hospital's HIS (Hospital Information System). Specific data information may include:

[0035] Personal information: including basic information such as name, age, gender, and contact information, so as to identify and contact the patient.

[0036] Medical history: including past medical history, family medical history, allergy history, surgical history, etc. This information is crucial for evaluating the effectiveness of acupuncture.

[0037] Physical examination: including physiological indicators such as height, weight, body temperature, blood pressure, pulse, respiration, and detailed examination results of specific parts or systems, such as heart and lung auscultation and abdominal palpation.

[0038] Laboratory tests: including blood tests (routine blood tests, biochemical indicators, coagulation function, etc.), urine tests, imaging tests (X-ray, CT scan, MRI, etc.), electrocardiogram (ECG), etc.

[0039] Surgery-related information: including surgery type, surgery date, surgery site, and detailed records of the surgery process to facilitate acupuncture analysis after acupuncture.

[0040] RedCap (Research Electronic Data Capture) is a web-based electronic data capture tool used to support the management of clinical research and investigation data. It provides a user-friendly interface that allows researchers to design, build and manage customized electronic questionnaires and databases.

[0041] Researchers can use RedCap's interface to design customized data collection forms, including various types of fields (text, numbers, dates, selection boxes, etc.) to meet the needs of specific studies. Data can be entered manually through the web interface or imported by uploading data files in batches. RedCap provides data validation to ensure data integrity and accuracy. It can automatically check the format, range, and logical relationship of the data and provide error prompts. RedCap can also be used to manage data, including operations such as adding, editing, deleting, and finding data.

[0042] The data queue of this embodiment is managed using RedCap. First, it is necessary to establish a queue database in the RedCap database. The specific establishment method can refer to "How to use REDCap to establish a prospective cohort study database" published by David et al. The entries of the database can refer to the above reference documents and the aforementioned patient information. The specific entries and form contents are not the focus of discussion of this embodiment. Those skilled in the art can design them according to specific circumstances when implementing this embodiment.

[0043] RedCap is a web-based electronic data capture tool. Furthermore, in order to facilitate automated data management, this embodiment automatically submits information within the system through a computer program. Specifically:

[0044] First, analyze the web page structure of RedCap, especially the HTML structure and form fields of the data submission page.

[0045] According to the structure of the web page, write a crawler program to simulate the operation of users submitting data. You can use programming languages ​​such as Python and combine third-party libraries (such as Beautiful Soup and Requests) to send HTTP requests, parse web page content, and fill in form fields.

[0046] Before submitting data, authentication is required. You can include login credentials or cookies in the HTTP request.

[0047] Use a crawler to extract patient data and submit the data by simulating a user filling out form fields on a web page.

[0048] Process the server response to check whether the data was submitted successfully and handle any errors or exceptions.

[0049] Set the crawler to run periodically to automatically submit data to the RedCap database when the data is updated.

[0050] By establishing patient data through the above method and automatically submitting it to the RedCap database, the operation process of medical staff can be reduced and ease of use can be improved.

[0051] The research process of this embodiment needs to follow the preset time regulations. For example, multiple acupuncture treatments are required from 0 to 3 days, and follow-up is required on the 10th day. In order to prevent forgetting, this embodiment needs to determine the queue data recording time based on the patient data to be acupunctured.

[0052] Specifically, the operation time of the patient is first determined from the patient data to be acupunctured, and the acupuncture treatment time and follow-up time are calculated based on the patient's operation time. For example, if the patient has surgery at 9:00 on January 4, 2024, and acupuncture treatment needs to be performed at 12 hours, 24 hours, 48 ​​hours, or 72 hours after surgery, the acupuncture time is calculated to be 21:00 on January 4, 2024, 21:00 on January 5, 2024, 21:00 on January 6, 2024, and 21:00 on January 7, 2024.

[0053] The above calculation can be automatically realized by using a computer program. After setting the time required for acupuncture treatment after surgery in the system in advance, the calculation can be automatically calculated based on the operation time. The above method can improve the calculation efficiency and reduce the manual workload.

[0054] In order to provide treatment prompts to medical staff, the present embodiment further prompts the acupuncture time according to the queue data recording time.

[0055] When implementing the prompt, you can choose to use an integrated development environment such as Android Studio (for Android application development) or Xcode (for iOS application development). Develop an Android or iOS application that connects to the RedCap database to obtain the patient's basic information and acupuncture treatment time.

[0056] Implement the reminder function in the application, including setting the reminder time, reminder method (such as sound, vibration, notification, etc.), reminder content, etc. You can use the reminder function provided by the system (such as Android's ArmManager or iOS's UI Local Notification), or you can use a third-party library to implement the reminder function.

[0057] Through the above reminder scheme, medical staff can be reminded to perform acupuncture treatment in a timely manner to prevent forgetting, resulting in missing cohort data and affecting the analysis of cohort data.

[0058] After receiving the reminder, the acupuncture operation is performed according to the acupuncture time.

[0059] During the acupuncture treatment, the operation video of the acupuncture operation is recorded. In order to facilitate subsequent operations, the present embodiment preferably obtains the operation video from at least two viewing angles.

[0060] Identifying acupoints for acupuncture operation according to the operation video specifically includes:

[0061] First, a standard virtual three-dimensional human body model with acupuncture points is established.

[0062] Collect data on human anatomy, including the names, locations, depths, etc. of acupuncture points. This data can come from authoritative sources such as anatomy textbooks, academic papers, and clinical guidelines.

[0063] This embodiment can use common 3D modeling software, such as BlueDer, Maya, 3ds Max, etc. Medical image processing software, such as Mimics, 3D Slicer, etc. can also be used. Create a standard human body model, or use a ready-made human body model as a basis and modify and adjust it. Determine the exact location of each acupoint on the human body model based on the collected human anatomy data. Use a marker or marking system to mark the location of the acupoint on the human body model.

[0064] Before acupuncture, use a highlighter pen to mark the acupuncture points on the human body.

[0065] Before marking, the acupuncturist or doctor can determine the acupuncture points to be needled according to the patient's condition and treatment plan. Use a highlighter to mark the acupuncture points on the patient's skin. When marking, make sure that the mark is accurate, clearly visible, and does not cause discomfort or pain to the patient. Choose a bright highlighter, preferably a bright color such as red, green or orange, to ensure the clarity and easy identification of the mark. The color of the highlighter should contrast clearly with the background and not be easily distracted or confused.

[0066] By using a highlighter to mark points on the human body, on the one hand, it ensures that the acupuncturist or doctor can accurately find the acupuncture points, and on the other hand, it can help the software to more easily identify and locate the marked points, thereby realizing automated image processing and analysis.

[0067] Perform acupuncture treatment at the fluorescent marked area. Choose the appropriate acupuncture technique according to the patient's condition and treatment needs. Commonly used acupuncture techniques include straight puncture, rotary puncture, and Bo Luo needle. You can choose the most suitable acupuncture technique according to your needs.

[0068] Furthermore, in order to facilitate the subsequent modeling process, the patient needs to receive treatment in the same posture as the standard virtual three-dimensional human body model.

[0069] The operation process images are acquired from at least two angles, and a three-dimensional human body model including fluorescent markers is established based on the videos from at least two angles.

[0070] By integrating information from multiple angles, the shape, structure and texture of the object can be captured more accurately. This helps to improve the accuracy and authenticity of modeling, making the generated three-dimensional model more accurate. Therefore, this embodiment obtains operation process images from at least two angles.

[0071] The image can be obtained by a camera fixed to an operating table or bed, and the camera switch is turned on when the medical staff starts acupuncture treatment to obtain the image. It can also be obtained by a handheld device such as a mobile phone, a camera, etc. The specific acquisition means is not specifically limited in this embodiment.

[0072] When performing three-dimensional modeling, any method in the prior art may be selected.

[0073] In one embodiment, a cloud-based 3D reconstruction service is used, such as Photoscan, RealityCapture, Meshroom, etc. These services allow uploading photos or videos and automatically process them to generate a 3D model.

[0074] First, write a program to collect photos or videos of the patient's body. This can be done by calling the camera or reading image or video files from the local file system.

[0075] Choose a suitable cloud-based 3D reconstruction service, such as Photoscan, RealityCapture, or Meshroom. Determine the API provided by the selected service based on its API documentation or developer documentation.

[0076] Write a program to upload the collected photos or videos to the selected 3D reconstruction service platform. Use the API or SDK provided by the service and follow the instructions in its documentation.

[0077] Using the service's API or SDK, write a program to start the 3D reconstruction process. Once the 3D reconstruction process is complete, write a program to obtain the resulting 3D model. Download the result file from the service's website.

[0078] In this step, the 3D model is automatically generated by calling the API of the cloud 3D model generation service through a computer program, which can reduce manual intervention and improve generation efficiency.

[0079] Since special fluorescent colors are used to mark the patient's acupuncture points, the fluorescent spots can be easily preserved in the 3D model.

[0080] The standard virtual three-dimensional human body model is scaled to be consistent with the size of the three-dimensional human body model, and the scaled quasi-virtual three-dimensional human body model is made to overlap with the three-dimensional human body model. The specific steps are as follows:

[0081] The standard virtual three-dimensional human body model and the three-dimensional human body model are loaded using three-dimensional modeling software or a library.

[0082] Determine a point in the two models as the reference point. Feature detection algorithms such as Harris corner detection, SI FT, SURF, etc. can be used to detect some significant feature points in the model image. Filter the detected feature points and select some representative points as candidate reference points. In addition, pattern matching algorithms such as template matching, Hough transform, etc. can be used to match areas similar to predefined patterns from the model image, such as head, hands, etc. Design a pattern to represent the reference point and match it with the model image to find the area that best matches the expected features.

[0083] Based on the location of the reference point, the scale and translation vector between the two models are calculated. This step can be achieved using mathematical calculations or computer vision techniques.

[0084] Apply the calculated scale and translation vector to one of the models to align it with the other. This can be done using 3D transform operations such as scaling, translating, etc.

[0085] After the two models are overlapped, the patient's acupuncture points correspond to the acupuncture points of the standard model, so the distance between the fluorescent point and the acupuncture point on the virtual three-dimensional human body model can be calculated, and the acupuncture point with the smallest distance to the fluorescent point is determined as the acupuncture point. Specifically:

[0086] The coordinate information of the fluorescent points and acupuncture points is extracted from the model data. Each point can be represented as a coordinate in three-dimensional space.

[0087] For each fluorescent point, calculate the distance between it and each acupuncture point. The distance between two points can be calculated using the Euclidean distance formula.

[0088] Find the acupuncture point that is closest to the fluorescent point. Traverse all acupuncture points and find the acupuncture point that makes the distance the smallest, which is the acupuncture point corresponding to the fluorescent point.

[0089] The acupoints and the corresponding acupuncture operation times are submitted to the RedCap database.

[0090] In the aforementioned steps, acupuncture points are identified, and during the identification process, acupuncture operations are automatically recorded by a program. Thereafter, the corresponding acupuncture points and operation times can be submitted to the RedCap database. For specific submission methods, reference can be made to the aforementioned automated submission method by a computer program.

[0091] Through the above technical means, the automated process can reduce the time of manual operation and manual entry, thereby improving work efficiency. Medical staff can focus more on patient care and treatment instead of spending too much time on data entry and management.

[0092] Automated processes can reduce the occurrence of human errors and improve data accuracy and consistency. Through automated data transmission and recording, data errors caused by human negligence or mistakes can be avoided.

[0093] Automated processes can ensure that data is recorded and managed according to predefined standards, thereby improving the quality and reliability of data. The consistency and accuracy of data are crucial for subsequent analysis and decision-making.

[0094] On the other hand, the present invention also provides a data management system for acupuncture queues for intestinal obstruction after abdominal tumor surgery, comprising:

[0095] A data management module, used for obtaining data of patients to be acupunctured and submitting the data of patients to the RedCap database;

[0096] A prompting module is used to determine the queue data recording time according to the patient data to be acupunctured; prompt the acupuncture time according to the queue data recording time; and perform acupuncture operation according to the acupuncture time;

[0097] A recording module, used for recording the operation image of the acupuncture operation;

[0098] A recognition module, used for recognizing acupoints for acupuncture operation according to the operation image;

[0099] The submission module is used to submit the acupoints and the corresponding acupuncture operation time to the RedCap database.

[0100] Furthermore, the specific implementation methods of the above-mentioned acupuncture queue data management system for intestinal obstruction after abdominal tumor surgery are the same as a method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery, and all further technical solutions in a method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery are fully introduced into acupuncture queue data management system for intestinal obstruction after abdominal tumor surgery.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

[0102] The present invention does not particularly specify the structure of some modules, which shall be subject to the contents recorded in the prior art. The prior art mentioned in the above background technology section and the specific embodiment section of the present invention can be used as part of the present invention to understand the meaning of some technical features or parameters. The scope of protection of the present invention shall be subject to the contents actually recorded in the claims.

Claims

1. A method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery, characterized in that The method comprises: Acquire data of patients to be treated with acupuncture, and submit the data to the RedCap database; Determining a queue data recording time according to the patient data to be acupunctured; Prompt acupuncture time according to the queue data recording time; Perform acupuncture operation according to the acupuncture time; recording an operation image of the acupuncture operation; identifying acupuncture points according to the operation image; Submit the acupuncture points and corresponding acupuncture operation times to the RedCap database; Submitting the acupuncture patient data to the RedCap database includes: Analyze the HTML structure and form fields of the data submission page of the RedCap website; According to the structure of the web page, write a crawler program to simulate the operation of users submitting data; Include login credentials or cookies in HTTP requests before submitting data; Use a crawler to submit data by simulating a user filling out form fields on a web page; Process the server response to check if the data was successfully submitted and handle any errors or exceptions; Set the crawler to run periodically to automatically submit data to the RedCap database when the data is updated; The step of identifying acupuncture points according to the operation image comprises: Establish a standard virtual three-dimensional human body model with human acupuncture points; Before acupuncture, use a highlighter pen to mark the acupuncture points on the body; Perform acupuncture treatment at the fluorescent marked area; Acquire images of the operation process from at least two angles; Establishing a three-dimensional model of the human body including fluorescent markers based on images from at least two angles; Scaling the standard virtual three-dimensional human body model to be consistent with the size of the three-dimensional human body model, and making the scaled quasi-virtual three-dimensional human body model overlap with the three-dimensional human body model; The distance between the fluorescent point and the acupuncture point on the virtual three-dimensional human body model is calculated, and the acupuncture point with the smallest distance to the fluorescent point is determined as the acupuncture point.

2. The method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery according to claim 1 is characterized in that The method of establishing a three-dimensional human body model including fluorescent markers based on images from at least two angles comprises: Write a program to collect photos or videos of the patient's body; Select a cloud-based 3D reconstruction service and determine the API provided by the service according to its API documentation or developer documentation. Write a program to upload the collected photos or videos to the selected 3D reconstruction service platform, using the API or SDK provided by the service and following the instructions in its documentation; Use the service's API or SDK to write a program to start the 3D reconstruction process. After the 3D reconstruction process is completed, write a program to obtain the generated 3D model.

3. The method for managing acupuncture queue data for intestinal obstruction after abdominal tumor surgery according to claim 2 is characterized in that Scaling the standard virtual three-dimensional human body model to be consistent with the size of the three-dimensional human body model, and making the scaled quasi-virtual three-dimensional human body model overlap with the three-dimensional human body model includes: Load the standard virtual three-dimensional human body model and the three-dimensional human body model using three-dimensional modeling software or library; Using a feature detection algorithm or a pattern matching algorithm, a point in the two models is determined as a reference point; Based on the position of the reference point, the scaling ratio and translation vector between the two models are calculated; Apply the calculated scale and translation vector to one of the models to align it with the other.

4. A data management system for acupuncture queues for intestinal obstruction after abdominal tumor surgery, characterized in that The system comprises: A data management module, used for obtaining data of patients to be acupunctured and submitting the data of patients to the RedCap database; A prompting module is used to determine the queue data recording time according to the patient data to be acupunctured; prompt the acupuncture time according to the queue data recording time; and perform acupuncture operation according to the acupuncture time; A recording module, used for recording the operation image of the acupuncture operation; A recognition module, used for recognizing acupoints for acupuncture operation according to the operation image; A submission module, for submitting the acupoints and corresponding acupuncture operation times to the RedCap database; Submitting the acupuncture patient data to the RedCap database includes: Analyze the HTML structure and form fields of the data submission page of the RedCap website; According to the structure of the web page, write a crawler program to simulate the operation of users submitting data; Include login credentials or cookies in HTTP requests before submitting data; Use a crawler to submit data by simulating a user filling out form fields on a web page; Process the server response to check if the data was successfully submitted and handle any errors or exceptions; Set the crawler to run periodically to automatically submit data to the RedCap database when the data is updated; The step of identifying acupuncture points according to the operation image comprises: Establish a standard virtual three-dimensional human body model with human acupuncture points; Before acupuncture, use a highlighter pen to mark the acupuncture points on the body; Perform acupuncture treatment at the fluorescent marked area; Acquire images of the operation process from at least two angles; Establishing a three-dimensional model of the human body including fluorescent markers based on images from at least two angles; Scaling the standard virtual three-dimensional human body model to be consistent with the size of the three-dimensional human body model, and making the scaled quasi-virtual three-dimensional human body model overlap with the three-dimensional human body model; The distance between the fluorescent point and the acupuncture point on the virtual three-dimensional human body model is calculated, and the acupuncture point with the smallest distance to the fluorescent point is determined as the acupuncture point.

5. The acupuncture queue data management system for intestinal obstruction after abdominal tumor surgery according to claim 4 is characterized in that The method of establishing a three-dimensional human body model including fluorescent markers based on images from at least two angles comprises: Write a program to collect photos or videos of the patient's body; Select a cloud-based 3D reconstruction service and determine the API provided by the service according to its API documentation or developer documentation. Write a program to upload the collected photos or videos to the selected 3D reconstruction service platform, using the API or SDK provided by the service and following the instructions in its documentation; Use the service's API or SDK to write a program to start the 3D reconstruction process. After the 3D reconstruction process is completed, write a program to obtain the generated 3D model.

6. The acupuncture queue data management system for intestinal obstruction after abdominal tumor surgery according to claim 5 is characterized in that Scaling the standard virtual three-dimensional human body model to be consistent with the size of the three-dimensional human body model, and making the scaled quasi-virtual three-dimensional human body model overlap with the three-dimensional human body model includes: Load the standard virtual three-dimensional human body model and the three-dimensional human body model using three-dimensional modeling software or library; Using a feature detection algorithm or a pattern matching algorithm, a point in the two models is determined as a reference point; Based on the position of the reference point, the scaling ratio and translation vector between the two models are calculated; Apply the calculated scale and translation vector to one of the models to align it with the other.

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