Medical health intelligent analysis system based on artificial intelligence

Abstract

The invention relates to a medical health intelligent analysis system based on artificial intelligence. The system 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 based on artificial intelligence is compact in structure and intelligent to control.

Description

Technical Field

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

[0002] Healthcare has become the focus of people's attention. With the improvement of living standards and the enhancement of health awareness, people's demand for medical services has become increasingly diversified. In this era full of challenges and opportunities, Ping An Healthcare has become a leader in the field of healthcare with its outstanding strength and innovative ideas. It is committed to providing people with comprehensive and high-quality medical services, focusing on health management and disease prevention, protecting people's health and creating a better future. The expected healthcare system has a wide network of medical resources and has established close cooperative relations with many well-known medical institutions at home and abroad. By integrating high-quality medical resources, it provides patients with comprehensive medical services, including expert consultation, telemedicine, referral services, etc. No matter where patients are, they can enjoy first-class medical services.

[0003] CN119157508A discloses a real-time monitoring device for medical health supervision and a monitoring method thereof, including a support mechanism, the support mechanism including a support seat, the top of the support seat is provided with three groups of No. 1 monitoring mechanisms in a circular array for sliding, the moving path of the three groups of No. 1 monitoring mechanisms is to move from the circumference of the support seat to its center, and the center of the top of the support seat is fixedly connected with a No. 2 monitoring mechanism. This technology has the advantages of flexible adjustment and accurate monitoring, and solves the problem that the above-mentioned device requires the user to manually adjust the position of the monitoring components, such as the seat, pedal and blood pressure monitoring sleeve, which may lead to inaccurate adjustment and affect the measurement results, and there is no intelligent adjustment function, and the position of the monitoring components cannot be automatically adjusted according to the height and body shape of the user; there is also a lack of effective buffering and limit design, which leads to vibration and lateral displacement during use, affecting the stability and accuracy of the measurement.

[0004] CN119092155A discloses a remote medical health consultation and management platform, including: a user detection terminal, a user terminal, a health management platform background server and an intelligent question-and-answer terminal. First, the user detection terminal collects body index data, and the user terminal receives a text description of the consultation question. This information is stored and managed by the health management platform background server, and then the intelligent question-and-answer terminal uses the collected data to provide users with customized answers based on their personal health status and specific questions, thereby realizing 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 based on artificial intelligence, 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 the patient on site based on multiple visual data selected in a targeted manner, and when the width of the thickest part of the blood vessel in the arm of the patient on site that is intelligently identified 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 based on artificial intelligence is provided, the system comprising: A sequential 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, and the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional shooting 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, for analyzing a sub-image corresponding to the arm of the on-site patient from the received on-site shot image based on the standard imaging contour of the human arm to output as a reference sub-image; an information extraction device, connected to the data analysis device, for extracting 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 blood vessel detection device, used to obtain each red and green component value, each black and white component value and each yellow and blue component value of each pixel point of a standard human blood vessel to output 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 blood vessel width at the thickest part of the blood vessel in the arm of the on-site patient by using an intelligent identification model based on the color association information corresponding to the standard human blood vessel, 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, used to send a blood drawing difficulty signal when the blood vessel width at the thickest part of the blood vessel at the arm of the on-site patient is less than or equal to a preset width threshold, and also used to send a blood drawing ease signal when the blood vessel width at the thickest part of the blood vessel at the arm of the on-site patient is greater than the preset width threshold; Among them, the batch generation component 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 for each time to obtain the Hoffet neural network after each training operation and output as the 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 imaging device, wherein 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 monotonically positively correlated with the vertical resolution of the directional imaging device, thereby completing the targeted design of the intelligent recognition model for performing subsequent intelligent recognition of blood vessel width; Second, a directional shooting device is used to perform a shooting operation facing the arm of the on-site patient who is about to have blood drawn, so as to obtain and output a corresponding on-site shot image, and a sub-image corresponding to the arm of the on-site patient is parsed from the on-site shot image based on the standard imaging contour of the human arm as a reference sub-image, and 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 are obtained, thereby completing the targeted selection of visual data for subsequent intelligent recognition of blood vessel width; Third: A signal mapping mechanism is introduced to intelligently identify that 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 eyes of medical staff to complete the preliminary identification of whether the current patient is easy to draw blood.

[0008] The medical health intelligence analysis system based on artificial intelligence of the present invention has a compact structure and intelligent operation. It can use a customized artificial intelligence model to intelligently identify the width of the thickest part of the blood vessels in the arm of the patient on site based on multiple visual data selected in a targeted manner, and send a blood drawing difficulty signal when the width of the blood vessels at the thickest part is less than or equal to the preset width threshold, thereby replacing the naked eyes of medical staff to complete the preliminary identification of whether the current patient is easy to draw blood. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0010] Figure 1 The structure block diagram of the medical health intelligence analysis system based on artificial intelligence is shown according to the first embodiment of the present invention.

[0011] Figure 2 It is a structural block diagram of a medical health intelligence analysis system based on artificial intelligence according to the second embodiment of the present invention.

[0012] Figure 3 1 is a structural block diagram of a medical health intelligence analysis system based on artificial intelligence according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0013] 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 is different. It is obviously too rough to rely solely on manual experience to judge. 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 before the human body is drawn. Obviously, there is currently a lack of corresponding mature technical solutions.

[0014] The following is a detailed description of an embodiment of the medical health intelligence analysis system based on artificial intelligence of the present invention with reference to the accompanying drawings.

[0015] Figure 1 The structure block diagram of the medical health intelligence analysis system based on artificial intelligence according to the first embodiment of the present invention is shown, and the system includes: A sequential 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, and the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional shooting device; For example, the device is generated one by one, and is used for performing 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, and 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: using a numerical conversion formula to express the numerical conversion relationship of the number of each training operation performed by the Hoffet neural network and the resolution of the directional shooting device being monotonically positively correlated; 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, for analyzing a sub-image corresponding to the arm of the on-site patient from the received on-site shot image based on the standard imaging contour of the human arm to output as a reference sub-image; an information extraction device, connected to the data analysis device, for extracting 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 blood vessel detection device, used to obtain each red and green component value, each black and white component value and each yellow and blue component value of each pixel point of a standard human blood vessel to output 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 blood vessel width at the thickest part of the blood vessel in the arm of the on-site patient by using an intelligent identification model based on the color association information corresponding to the standard human blood vessel, 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, used to send a blood drawing difficulty signal when the blood vessel width at the thickest part of the blood vessel at the arm of the on-site patient is less than or equal to a preset width threshold, and also used to send a blood drawing ease signal when the blood vessel width at the thickest part of the blood vessel at the arm of the on-site patient is greater than the preset width threshold; The multiple generation component 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. 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; And wherein, the intelligent recognition model is used to intelligently identify the blood vessel width at the thickest part of the blood vessel 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, including: 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.

[0016] Figure 2 It is a structural block diagram of a medical health intelligence analysis system based on artificial intelligence according to the second embodiment of the present invention.

[0017] Compared to Figure 1 , Figure 2 The AI-based medical and health intelligence analysis system can also include: A 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; 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, 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; Wherein, the numerical analysis mechanism includes a plurality of 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, 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 respectively, including: 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 respectively; 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 respectively, 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 respectively, and also include: the multiple height sensors have the same height measurement upper limit value and height measurement lower limit value.

[0018] Figure 3 1 is a structural block diagram of a medical health intelligence analysis system based on artificial intelligence according to Embodiment 3 of the present invention.

[0019] Compared to Figure 1 , Figure 3 The AI-based medical and health intelligence analysis system can also include: A real-time display mechanism, connected to the multiple 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.

[0020] In addition, in the artificial intelligence-based medical health intelligent analysis system, the intelligent recognition model is used to intelligently identify the blood vessel width at the thickest part 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 part of the blood vessel in the arm of the on-site patient as its output.

[0021] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A medical health intelligence analysis system based on artificial intelligence, characterized in that: The system comprises: A sequential 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, and the number of each training operation performed by the Hoffet neural network is monotonically positively correlated with the resolution of the directional shooting 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 shot image; A data analysis device, connected to the directional shooting device, for analyzing a sub-image corresponding to the arm of the on-site patient from the received on-site shot image based on the standard imaging contour of the human arm to output as a reference sub-image; an information extraction device, connected to the data analysis device, for extracting 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 blood vessel detection device, used to obtain each red and green component value, each black and white component value and each yellow and blue component value of each pixel point of a standard human blood vessel to output 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 blood vessel width at the thickest part of the blood vessel in the arm of the on-site patient by using an intelligent identification model based on the color association information corresponding to the standard human blood vessel, 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, used to send a blood drawing difficulty signal when the blood vessel width at the thickest part of the blood vessel at the arm of the on-site patient is less than or equal to a preset width threshold, and also used to send a blood drawing ease signal when the blood vessel width at the thickest part of the blood vessel at the arm of the on-site patient is greater than the preset width threshold; Among them, the batch generation component 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.

2. The medical health intelligence analysis system based on artificial intelligence as claimed in claim 1, characterized in that: The intelligent recognition model is used to intelligently identify the width of the thickest part of the blood vessel 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 the pixels 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 the pixels of the reference sub-image, including: synchronously inputting the color association information corresponding to the standard human blood vessels, the horizontal coordinate values ​​and the vertical coordinate values ​​of the pixels 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 the pixels of the reference sub-image into the intelligent recognition model.

3. The medical health intelligence analysis system based on artificial intelligence as claimed in claim 2, characterized in that: The system further comprises: A 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 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 measurements 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 based on artificial intelligence as claimed in claim 3, characterized in that: 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, 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 respectively. 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 respectively.

5. The medical health intelligence analysis system based on artificial intelligence as claimed in claim 4, characterized in that: 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 respective measurements 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 based on artificial intelligence as claimed in claim 5, characterized in that: 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 respectively, and also include: 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 based on artificial intelligence as claimed in claim 3, characterized in that: The system further comprises: 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.

8. The medical health intelligence analysis system based on artificial intelligence as claimed in claim 7, characterized in that: 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. The real-time display mechanism is a character display device.

9. The medical health intelligence analysis system based on artificial intelligence as claimed in claim 7, characterized in that: 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.

Images