Medical health intelligent analysis system

Abstract

The invention relates to a medical health intelligent analysis system which comprises a successive generation device, a directional shooting device, a data analysis device, an information extraction device, a blood vessel detection device, a blood drawing identification mechanism and a signal mapping mechanism. The medical health intelligent analysis system is compact in structure and intelligent to control.

Description

Technical Field

[0001] The present invention relates to the field of smart medicine, and in particular to a smart medical health analysis system. Background Art

[0002] Healthcare has become a focal point for people. With rising living standards and heightened health awareness, people's demands for medical services are becoming increasingly diverse. In this era fraught with both challenges and opportunities, Ping An Healthcare, with its exceptional strength and innovative philosophy, has become a leader in the healthcare sector. We are committed to providing comprehensive, high-quality medical services, focusing on health management and disease prevention, safeguarding people's health and creating a better future. Our healthcare system boasts an extensive network of medical resources and has established close partnerships with numerous renowned medical institutions both domestically and internationally. By integrating high-quality medical resources, we provide patients with comprehensive medical services, including expert consultations, telemedicine, and referral services. Regardless of their location, patients can enjoy first-class medical care.

[0003] CN119157508A discloses a real-time monitoring device for medical health supervision and a monitoring method thereof, comprising a support mechanism, the support mechanism comprising a support base, the top of the support base being provided with three groups of No. 1 monitoring mechanisms slidingly arranged in a circular array, the movement path of the three groups of No. 1 monitoring mechanisms being from the circumference of the support base to its center, and a No. 2 monitoring mechanism being fixedly connected to the center of the top of the support base. This technology has the advantages of flexible adjustment and accurate monitoring, solving the problems of the above-mentioned device requiring the user to manually adjust the position of monitoring components, such as seats, pedals, and blood pressure monitoring sleeves, which may lead to inaccurate adjustments and affect measurement results, and the lack of intelligent adjustment functions, which makes it impossible to automatically adjust the position of monitoring components according to the user's height and body shape; and the lack of effective buffering and limiting design, which leads to vibration and lateral offset during use, affecting the stability and accuracy of the measurement.

[0004] CN119092155A discloses a remote medical health consultation and management platform, comprising a user monitoring terminal, a user terminal, a health management platform backend server, and an intelligent question-and-answer terminal. The user monitoring terminal first collects physical indicator data and receives a text description of the consultation question. This information is stored and managed by the health management platform backend server. The intelligent question-and-answer terminal then uses the collected data to provide users with customized answers based on their individual health status and specific questions, thereby enabling instant generation of consultation answer texts and providing more personalized consultation services. Summary of the Invention

[0005] In order to solve technical problems in related fields, the present invention provides a medical health intelligent analysis system, which can use an artificial intelligence model with a customized structure to intelligently identify the width of the thickest part of the blood vessel in the arm of an on-site patient based on multiple targeted selected visual data, and when the width of the thickest part of the blood vessel in the arm of the on-site patient identified by the intelligent identification is less than or equal to a preset width threshold, a blood drawing difficulty signal is issued; otherwise, a blood drawing easy signal is issued, thereby replacing the naked eyes of medical staff to complete the preliminary identification of whether the current patient is easy to draw blood.

[0006] According to the present invention, a medical health intelligence analysis system is provided, the system comprising: A successive generation device is used to perform training operations on the Hoffet neural network to obtain the Hoffet neural network after each training operation and output it as an intelligent recognition model, wherein the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional imaging device; A directional shooting device is used to perform a shooting operation facing the arm of a patient on site who is about to have blood drawn, so as to obtain and output a corresponding on-site shooting image; a data analysis device connected to the directional shooting device, configured to analyze the received on-site shot image based on the standard imaging contour of the human arm to obtain a sub-image corresponding to the on-site patient's arm and output the sub-image as a reference sub-image; an information extraction device connected to the data analysis device, for extracting the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the reference sub-image and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image; A blood vessel detection device is used to obtain the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of a standard human blood vessel and output them as color association information corresponding to the standard human blood vessel; a blood drawing identification mechanism, connected to the successive generation device, the information extraction device, and the blood vessel detection device, respectively, for intelligently identifying the width of the thickest portion of a blood vessel in the arm of a live patient using an intelligent identification model based on color association information corresponding to the standard human blood vessels, each horizontal coordinate value and each vertical coordinate value of each pixel point of the reference sub-image, and each red and green component value, each black and white component value, and each yellow and blue component value of each pixel point of the reference sub-image; a signal mapping mechanism connected to the blood drawing identification mechanism, configured to issue a blood drawing difficulty signal when the width of the thickest part of the blood vessel in the arm of the on-site patient is less than or equal to a preset width threshold, and further configured to issue a blood drawing ease signal when the width of the thickest part of the blood vessel in the arm of the on-site patient is greater than the preset width threshold; Among them, the successive generation device is used to perform each training operation on the Hoffet neural network to obtain the Hoffet neural network after each training operation and output it as an intelligent recognition model. The number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional shooting device, including: the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the horizontal resolution of the directional shooting device and is monotonically positively correlated with the vertical resolution of the directional shooting device.

[0007] Therefore, the present invention has the following three outstanding technical effects: First, the Hoffet neural network is trained multiple times to obtain a Hoffet neural network after each training operation and output as an intelligent recognition model. The number of training operations performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional imaging device. Specifically, the number of training operations performed by the Hoffet neural network is monotonically positively correlated with the horizontal resolution of the directional imaging device and monotonically positively correlated with the vertical resolution of the directional imaging device, thereby completing the targeted design of the intelligent recognition model for subsequent intelligent identification of blood vessel width. Second, a directional imaging device is used to perform an imaging operation directed at the arm of a patient on-site whose blood is to be drawn, thereby obtaining and outputting a corresponding on-site image. Based on the standard imaging contours of a human arm, a sub-image corresponding to the patient's arm is parsed from the on-site image to serve as a reference sub-image. The horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point in the reference sub-image, as well as the red and green component values, black and white component values, and yellow and blue component values ​​of each pixel point in the reference sub-image, are then used to perform targeted selection of visual data for subsequent intelligent identification of blood vessel width. Third: A signal mapping mechanism is introduced for intelligent identification. When the width of the thickest part of the blood vessel in the arm of the patient on site is less than or equal to the preset width threshold, a blood drawing difficulty signal is issued; otherwise, a blood drawing easy signal is issued, thereby replacing the naked eye of medical staff to complete the preliminary identification of whether the current patient is easy to draw blood.

[0008] The medical health intelligent analysis system of the present invention boasts a compact structure and intelligent operation. It utilizes a custom-designed artificial intelligence model to intelligently identify the width of the thickest blood vessels in a patient's arm based on targeted visual data. When the width of the thickest blood vessel is less than or equal to a preset width threshold, a blood drawing difficulty signal is issued, thereby replacing the medical staff's visual assessment of whether blood drawing is easy for the patient. DETAILED DESCRIPTION

[0009] Blood drawing is one of the most common physical examination items in the medical and health field. However, the thickness of blood vessels in the arms of different people varies. Relying solely on manual experience to make judgments is obviously too rough. It is hoped that an electronic and intelligent detection mechanism for the thickness of blood vessels in the arms of different people can provide reliable and critical reference data for whether blood drawing can be completed in the arm before the human body is drawn. Obviously, there is currently a lack of corresponding mature technical solutions.

[0010] The following is a detailed description of an embodiment of the medical health intelligence analysis system of the present invention.

[0011] Example 1

[0012] The medical health intelligence analysis system according to the first embodiment of the present invention includes: A successive generation device is used to perform training operations on the Hoffet neural network to obtain the Hoffet neural network after each training operation and output it as an intelligent recognition model, wherein the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional imaging device; For example, a successive generation device is used to perform each training operation on the Hoffet neural network to obtain the Hoffet neural network after each training operation and output it as an intelligent recognition model, wherein the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional imaging device, including: using a numerical conversion formula to express the numerical conversion relationship of the monotonically positive correlation between the number of each training operation performed by the Hoffet neural network and the resolution of the directional imaging device; A directional shooting device is used to perform a shooting operation facing the arm of a patient on site who is about to have blood drawn, so as to obtain and output a corresponding on-site shooting image; a data analysis device connected to the directional shooting device, configured to analyze the received on-site shot image based on the standard imaging contour of the human arm to obtain a sub-image corresponding to the on-site patient's arm and output the sub-image as a reference sub-image; an information extraction device connected to the data analysis device, for extracting the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the reference sub-image and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image; A blood vessel detection device is used to obtain the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of a standard human blood vessel and output them as color association information corresponding to the standard human blood vessel; a blood drawing identification mechanism, connected to the successive generation device, the information extraction device, and the blood vessel detection device, respectively, for intelligently identifying the width of the thickest portion of a blood vessel in the arm of a live patient using an intelligent identification model based on color association information corresponding to the standard human blood vessels, each horizontal coordinate value and each vertical coordinate value of each pixel point of the reference sub-image, and each red and green component value, each black and white component value, and each yellow and blue component value of each pixel point of the reference sub-image; a signal mapping mechanism connected to the blood drawing identification mechanism, configured to issue a blood drawing difficulty signal when the width of the thickest part of the blood vessel in the arm of the on-site patient is less than or equal to a preset width threshold, and further configured to issue a blood drawing ease signal when the width of the thickest part of the blood vessel in the arm of the on-site patient is greater than the preset width threshold; wherein the successive generation device is used to perform each training operation on the Hoffet neural network to obtain the Hoffet neural network after each training operation and output it as an intelligent recognition model, wherein the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional imaging device, including: the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the horizontal resolution of the directional imaging device and is monotonically positively correlated with the vertical resolution of the directional imaging device; And wherein, using an intelligent recognition model to intelligently identify the width of the thickest part of the blood vessels in the arm of the patient on site based on the color association information corresponding to the standard human blood vessels, the horizontal coordinate values ​​and the vertical coordinate values ​​of each pixel point of the reference sub-image, and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image includes: synchronously inputting the color association information corresponding to the standard human blood vessels, the horizontal coordinate values ​​and the vertical coordinate values ​​of each pixel point of the reference sub-image, and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image into the intelligent recognition model.

[0013] Example 2

[0014] The medical health intelligence analysis system according to the second embodiment of the present invention may further include: a numerical analysis mechanism, connected to the blood drawing identification mechanism, the successive generation device, the information extraction device, and the blood vessel detection device, respectively, for measuring the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device, and the blood vessel detection device; Wherein, the numerical analysis mechanism is respectively connected with the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to respectively measure the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the numerical analysis mechanism includes a plurality of height measurement units, which are respectively connected with the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device to complete the measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device; Wherein, the numerical analysis mechanism includes a plurality of height measurement units, which are used to be respectively connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device to complete the respective measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the plurality of height measurement units are a plurality of height sensors, which are used to be respectively connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device to complete the respective measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device; Wherein, the plurality of height measurement units are a plurality of height sensors, which are used to be connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively, so as to complete the respective measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the structures of the plurality of height sensors are the same; Among them, the multiple height measurement units are multiple height sensors, which are used to be connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively, so as to complete the separate measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device. It also includes: the multiple height sensors have the same height measurement upper limit value and height measurement lower limit value.

[0015] Example 3

[0016] The medical health intelligence analysis system shown in the third embodiment of the present invention may further include: a real-time display mechanism, connected to the plurality of height sensors of the blood drawing identification mechanism, the successive generation device, the information extraction device, and the blood vessel detection device, respectively, for synchronously playing the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device, and the blood vessel detection device; Wherein, the instant display mechanism is respectively connected to a plurality of height sensors of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to synchronously play the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively, including: the instant display mechanism is a character display device; And wherein, the real-time display mechanism is respectively connected to multiple height sensors of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to synchronously play the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the real-time display mechanism is a voice playback device.

[0017] In addition, in the medical health intelligent analysis system, the intelligent recognition model is used to intelligently identify the blood vessel width at the thickest point of the blood vessel in the arm of the on-site patient based on the color association information corresponding to the standard human blood vessels, the horizontal coordinate values ​​and the vertical coordinate values ​​of each pixel point of the reference sub-image, and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image, which also includes: executing the intelligent recognition model to obtain the blood vessel width at the thickest point of the blood vessel in the arm of the on-site patient as output.

[0018] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A medical health intelligence analysis system, characterized in that: The system includes: A successive generation device is used to perform training operations on the Hoffet neural network to obtain the Hoffet neural network after each training operation and output it as an intelligent recognition model, wherein the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional imaging device, including: the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the horizontal resolution of the directional imaging device and the vertical resolution of the directional imaging device; A directional shooting device is used to perform a shooting operation facing the arm of a patient on site who is about to have blood drawn, so as to obtain and output a corresponding on-site shooting image; A data analysis device is connected to the directional shooting device and is used to analyze the received on-site shot image based on the standard imaging contour of the human arm to obtain a sub-image corresponding to the on-site patient's arm and output it as a reference sub-image; an information extraction device connected to the data analysis device, for extracting the horizontal coordinate values ​​and vertical coordinate values ​​of each pixel point of the reference sub-image and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image; A blood vessel detection device is used to obtain the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of a standard human blood vessel and output them as color association information corresponding to the standard human blood vessel; The blood drawing identification mechanism is connected to the successive generation device, the information extraction device, and the blood vessel detection device, respectively, and is used to intelligently identify the width of the thickest part of the blood vessel in the arm of the on-site patient using an intelligent identification model based on color association information corresponding to standard human blood vessels, each horizontal coordinate value and each vertical coordinate value of each pixel point of the reference sub-image, and each red and green component value, each black and white component value, and each yellow and blue component value of each pixel point of the reference sub-image; The signal mapping mechanism is connected to the blood drawing identification mechanism, and is used to send a blood drawing difficulty signal when the width of the thickest part of the blood vessel in the arm of the on-site patient is less than or equal to a preset width threshold, and is also used to send a blood drawing easy signal when the width of the thickest part of the blood vessel in the arm of the on-site patient is greater than the preset width threshold.

2. The medical health intelligence analysis system according to claim 1, wherein: An intelligent recognition model is used to intelligently identify the width of the thickest part of the blood vessels in the arm of a patient on site based on the color association information corresponding to the standard human blood vessels, the horizontal coordinate values ​​and the vertical coordinate values ​​of each pixel point of the reference sub-image, and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image. The method includes: synchronously inputting the color association information corresponding to the standard human blood vessels, the horizontal coordinate values ​​and the vertical coordinate values ​​of each pixel point of the reference sub-image, and the red and green component values, the black and white component values, and the yellow and blue component values ​​of each pixel point of the reference sub-image into the intelligent recognition model.

3. The medical health intelligence analysis system according to claim 2, characterized in that: The system also includes: The numerical analysis mechanism is connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, respectively, and is used to measure the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively; Among them, the numerical analysis mechanism is respectively connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to respectively measure the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device. The numerical analysis mechanism includes multiple height measurement units, which are used to be respectively connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device to complete the separate measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device.

4. The medical health intelligence analysis system according to claim 3, wherein: The numerical analysis mechanism includes multiple height measurement units, which are used to be connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively to complete the separate measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device. The multiple height measurement units are multiple height sensors, which are used to be connected to the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively to complete the separate measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device.

5. The medical health intelligence analysis system according to claim 4, wherein: The multiple height measurement units are multiple height sensors, which are used to connect with the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively to complete the separate measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the structures of the multiple height sensors are the same.

6. The medical health intelligence analysis system according to claim 5, wherein: The multiple height measurement units are multiple height sensors, which are used to connect with the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device respectively to complete the separate measurement of the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device. It also includes: the multiple height sensors have the same height measurement upper limit value and height measurement lower limit value.

7. The medical health intelligence analysis system according to claim 3, characterized in that: The system also includes: The real-time display mechanism is connected to multiple height sensors of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to synchronously play the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device.

8. The medical health intelligence analysis system according to claim 7, wherein: The real-time display mechanism is respectively connected to multiple height sensors of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to synchronously play the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the real-time display mechanism is a character display device.

9. The medical health intelligence analysis system according to claim 7, wherein: The real-time display mechanism is respectively connected to multiple height sensors of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, and is used to synchronously play the current real-time height values ​​of the blood drawing identification mechanism, the successive generation device, the information extraction device and the blood vessel detection device, including: the real-time display mechanism is a voice playback device.