CN110974298A - Method for capturing diaphragm movement by utilizing ultrasonic AI technology to assist judgment of ventilator off-line - Google Patents
Method for capturing diaphragm movement by utilizing ultrasonic AI technology to assist judgment of ventilator off-line Download PDFInfo
- Publication number
- CN110974298A CN110974298A CN201911412157.4A CN201911412157A CN110974298A CN 110974298 A CN110974298 A CN 110974298A CN 201911412157 A CN201911412157 A CN 201911412157A CN 110974298 A CN110974298 A CN 110974298A
- Authority
- CN
- China
- Prior art keywords
- diaphragm
- inspiration
- detection device
- thickness
- ultrasonic
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
- A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/08—Clinical applications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M16/00—Devices for influencing the respiratory system of patients by gas treatment, e.g. ventilators; Tracheal tubes
- A61M16/0003—Accessories therefor, e.g. sensors, vibrators, negative pressure
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Surgery (AREA)
- Molecular Biology (AREA)
- Physics & Mathematics (AREA)
- Medical Informatics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Radiology & Medical Imaging (AREA)
- Pulmonology (AREA)
- Anesthesiology (AREA)
- Emergency Medicine (AREA)
- Hematology (AREA)
- Physiology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
Abstract
The invention discloses a method for capturing diaphragm movement by utilizing an ultrasonic AI technology to assist in judging whether a breathing machine is off-line, which comprises the following steps: step S1, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion state of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm thickness image during expiration and inspiration on a display interface of an ultrasonic detection device; step S2, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion states of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm movement degree change image during expiration and inspiration on a display interface of an ultrasonic detection device; step S3, the AI diagnostic apparatus scans the images generated in step S1 and step S2, respectively, analyzes the content of the processed images after the scanning is completed, and obtains the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user through measurement and calculation; step S4, the doctor compares the calculated specific numerical values of the diaphragm thickness change rate and the diaphragm mobility of the user with the diaphragm thickness change rate cutoff value and the diaphragm mobility cutoff value, respectively.
Description
Technical Field
The invention relates to the technical field of medical treatment. More particularly, the invention relates to a method for capturing diaphragm movement by using an ultrasonic AI technology to assist in judging whether a breathing machine is off-line.
Background
The diaphragm muscle is a muscle-fiber structure located between the thoracic cavity and abdominal cavity, and has an abdominal muscle around it and a aponeurosis in the center, which is also translated into the diaphragm, which is an important respiratory muscle of the body and accounts for 60% -80% of all respiratory muscle functions.
Adopt CT inspection or magnetic resonance imaging to catch diaphragm image among the prior art, but the CT inspection has the radiation, and is big to the human body injury, and magnetic resonance imaging accessibility is poor, and the check-up time is long, and the expense is high, simultaneously, needs artifical the measurement when measuring diaphragm image, and is inefficient, and the error is big. In view of the above, there is a need to develop a method for capturing diaphragm movement by using an ultrasound AI technology to assist in determining whether a ventilator is offline.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for capturing diaphragm movement by using an ultrasonic AI technology to assist in judging whether a respirator is off-line, wherein an ultrasonic detection device is used for capturing a diaphragm image, and an AI diagnosis device is used for analyzing and processing the diaphragm image, so that the investment of required medical expert resources is greatly reduced, the diagnosis time is shortened, the medical cost of a patient is saved, the image labeling precision and efficiency are improved, and the method has a wide market application value.
To achieve these objects and other advantages in accordance with the purpose of the invention, there is provided a method for determining ventilator off-line using an ultrasound AI technique to capture diaphragm motion to assist in determining ventilator off-line, comprising:
step S1, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion state of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm thickness image during expiration and inspiration on a display interface of an ultrasonic detection device;
step S2, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion states of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm movement degree change image during expiration and inspiration on a display interface of an ultrasonic detection device;
step S3, the AI diagnostic apparatus scans the images generated in step S1 and step S2, respectively, analyzes the content of the processed images after the scanning is completed, and obtains the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user through measurement and calculation;
step S4, the doctor compares the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user obtained by measurement and calculation of the AI diagnostic device with the diaphragm thickness change rate cutoff value and the diaphragm mobility cutoff value, respectively, to determine whether the diaphragm movement is normal, and further determine whether the ventilator of the patient can be taken off-line.
Preferably, the specific method for generating the diaphragm thickness image during exhalation and inhalation in step S1 is as follows:
taking a patient in a supine position, breathing autonomously, and placing a high-frequency ultrasonic probe on the right anterior axillary line, wherein the high-frequency ultrasonic probe is vertically placed between the 8 th rib and the 9 th rib of the chest wall;
the high-frequency ultrasonic probe captures the motion state of the diaphragm of the patient during expiration, and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate a diaphragm thickness image during expiration and displays the image on a display interface;
the high-frequency ultrasonic probe captures the motion state of the diaphragm of a patient during inspiration and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate an image of the thickness of the diaphragm during inspiration and displays the image on a display interface;
the ultrasonic detection device respectively generates at least 2 groups of diaphragm thickness images during expiration and at least 2 groups of diaphragm thickness images during inspiration.
Preferably, the specific method for generating the diaphragm movement degree change image from expiration to inspiration in step S2 is as follows:
the patient takes a supine position, breathes autonomously, a low-frequency ultrasonic probe is arranged on the midline of the clavicle on the right side, the low-frequency ultrasonic probe is arranged between the 7 th rib and the 8 th rib of the chest wall in parallel, the low-frequency ultrasonic probe takes a coronal position and moves in the axial direction perpendicular to the head and the tail of the diaphragm, and the diaphragm is positioned after the display interface of the ultrasonic detection device displays the gallbladder interface;
after the diaphragm moves stably, the low-frequency ultrasonic probe captures the movement state of the diaphragm when a patient inhales to exhales, and transmits the captured movement state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device analyzes and processes the data to generate an image of the movement degree change of the diaphragm when the patient inhales to exhales and displays the image on a display interface;
the ultrasonic detection device respectively generates at least 2 groups of images of the change of the diaphragm movement degree from inspiration to expiration.
Preferably, the specific step of obtaining the diaphragm thickness change rate of the user in step S3 is:
the AI diagnosis device respectively scans a plurality of groups of images of the diaphragm thickness during expiration on a display interface of the ultrasonic detection device, analyzes and processes the images after the scanning is finished, respectively generates corresponding expiratory diaphragm models, further respectively measures the thickness of the end-expiratory diaphragm in each expiratory diaphragm model, and takes the average value of the thicknesses of the end-expiratory diaphragms;
the AI diagnosis device respectively scans a plurality of groups of images of the diaphragm thickness during inspiration of a display interface of the ultrasonic detection device, analyzes and processes the images after the scanning is finished, respectively generates corresponding inspiration diaphragm models, further respectively measures the thickness of the last inspiration diaphragm in each inspiration diaphragm model, and takes the average value of the thicknesses of the last inspiration diaphragm;
the AI diagnostic device calculates the diaphragm thickness change rate of the patient by using the average value of the end-expiratory diaphragm thicknesses, the average value of the end-inspiratory diaphragm thicknesses and a diaphragm thickness change rate formula.
Preferably, the diaphragm thickness change rate is formulated as
Wherein η is diaphragm thickness change rate L1Mean value of diaphragm thickness at end of inspiration, L2The mean value of the end-tidal diaphragm thickness.
Preferably, the specific step of obtaining the diaphragm movement degree of the user in step S3 is: the AI diagnosis device respectively scans a plurality of groups of images of the movement degree of the diaphragm during inspiration to expiration on a display interface of the ultrasonic detection device, analyzes and processes the images after scanning is finished, respectively generates corresponding diaphragm models, further respectively measures the movement degree of the diaphragm in each diaphragm model, and takes the average value of the movement degree of the diaphragm;
preferably, the specific range of the diaphragm thickness change rate cutoff value in step S4 is 30% to 96%;
the specific range of the diaphragm mobility cutoff value is 14-60 mm.
The invention at least comprises the following beneficial effects: the invention provides a method for capturing diaphragm movement by utilizing an ultrasonic AI technology to assist in judging whether a breathing machine is off-line, which captures a diaphragm image by utilizing an ultrasonic detection device and analyzes and processes the diaphragm image by utilizing an AI diagnosis device, thereby greatly reducing the investment of required medical expert resources, reducing the diagnosis time, saving the medical cost of a patient, simultaneously improving the image labeling precision and efficiency and having wide market application value.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Detailed Description
The foregoing and other objects, features, aspects and advantages of the present invention will become more apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the annexed drawings, discloses a preferred embodiment of the present invention.
As an embodiment of the present invention, the present invention provides a method for assisting in determining whether a ventilator is offline by capturing diaphragm movement using an ultrasound AI technique, which includes: step S1, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion state of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm thickness image during expiration and inspiration on a display interface of an ultrasonic detection device;
step S2, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion states of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm movement degree change image during expiration and inspiration on a display interface of an ultrasonic detection device;
step S3, the AI diagnostic apparatus scans the images generated in step S1 and step S2, respectively, analyzes the content of the processed images after the scanning is completed, and obtains the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user through measurement and calculation;
step S4, the doctor compares the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user obtained by measurement and calculation of the AI diagnostic device with the diaphragm thickness change rate cutoff value and the diaphragm mobility cutoff value, respectively, to determine whether the diaphragm movement is normal, and further determine whether the ventilator of the patient can be taken off-line.
Further, the specific method for generating the diaphragm thickness image during exhalation and inhalation in step S1 is as follows:
taking a patient in a supine position, breathing autonomously, and placing a high-frequency ultrasonic probe on the right anterior axillary line, wherein the high-frequency ultrasonic probe is vertically placed between the 8 th rib and the 9 th rib of the chest wall;
the high-frequency ultrasonic probe captures the motion state of the diaphragm of the patient during expiration, and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate a first expiratory diaphragm thickness image which is displayed on a display interface;
the high-frequency ultrasonic probe captures the motion state of the diaphragm of a patient during inspiration and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate a first inspiration diaphragm thickness image which is displayed on a display interface;
the patient changes the expiration volume and the inspiration volume, and repeats the operations to obtain a second expiration diaphragm thickness image and a second inspiration diaphragm thickness image;
and the patient changes the expiration volume and the inspiration volume again, and repeats the operations to obtain a third expiration diaphragm thickness image and a third inspiration diaphragm thickness image.
Further, the specific method for generating the diaphragm movement degree change image from expiration to inspiration in step S2 is as follows:
the patient takes a supine position, breathes autonomously, a low-frequency ultrasonic probe is arranged on the midline of the clavicle on the right side, the low-frequency ultrasonic probe is arranged between the 7 th rib and the 8 th rib of the chest wall in parallel, the low-frequency ultrasonic probe takes a coronal position and moves in the axial direction perpendicular to the head and the tail of the diaphragm, and the diaphragm is positioned after the display interface of the ultrasonic detection device displays the gallbladder interface;
after the diaphragm moves stably, the low-frequency ultrasonic probe captures the motion state of the diaphragm when a patient inhales to exhales, and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate a diaphragm movement degree change image during the first inhaling to exhaling and displays the image on a display interface;
the patient changes the expiration and inspiration capacity, and repeats the operation to obtain a diaphragm movement degree change image from the third inspiration to the expiration;
and the patient changes the expiration volume and the inspiration volume again, and repeats the operation to obtain a diaphragm movement degree change image from the third inspiration to the expiration.
Further, the specific step of obtaining the diaphragm thickness change rate of the user in step S3 is:
the AI diagnosis device scans the image of the diaphragm thickness of the display interface of the ultrasonic detection device during the first expiration, performs analysis processing after the scanning is completed, generates a corresponding first expiratory diaphragm model, and then measures the thickness of the end-expiratory diaphragm in the first expiratory diaphragm model to obtain the thickness D of the first end-expiratory diaphragm1；
The AI diagnosis device scans the display interface of the ultrasonic detection device to obtain the image of the diaphragm thickness of the second expiratory diaphragm during the second expiratory breath, performs analysis processing after the scanning is completed, generates a corresponding second expiratory diaphragm model, and then measures the thickness of the end-expiratory diaphragm in the second expiratory diaphragm model to obtain the thickness D of the second end-expiratory diaphragm2；
The AI diagnosis device scans the image of the diaphragm thickness of the display interface of the ultrasonic detection device during the third expiration, performs analysis processing after the scanning is completed, generates a corresponding third expiratory diaphragm model, and then measures the thickness of the end-expiratory diaphragm in the third expiratory diaphragm model to obtain the thickness D of the third end-expiratory diaphragm3；
The AI diagnostic device calculates the thickness D of the first end-expiratory diaphragm1Second end-tidal diaphragm thickness D2And thickness D of the diaphragm at the end of the third expiration3Average value L of2；
The AI diagnostic device scans the first inspiratory diaphragm thickness image of the display interface of the ultrasonic detection device, performs analysis processing after scanning is completed, generates a corresponding first inspiratory diaphragm model, and then measures the inspiratory diaphragm thickness in the first inspiratory diaphragm model to obtain the first inspiratory diaphragm thickness d1；
The AI diagnostic device scans the second inspiratory diaphragm thickness image of the display interface of the ultrasonic detection device, and performs analysis processing after scanning to generate a corresponding second inspiratory diaphragm modelType, and then measure the last diaphragm thickness of breathing in the diaphragm model of second breathing in, obtain the last diaphragm thickness d of second breathing in2；
The AI diagnostic device scans the display interface of the ultrasonic detection device to obtain the image of the diaphragm thickness when the third inspiration is performed, performs analysis processing after the scanning is completed, generates a corresponding third inspiration diaphragm model, and then measures the thickness of the last diaphragm of inspiration in the third inspiration diaphragm model to obtain the thickness d of the last diaphragm of inspiration3；
The AI diagnostic device calculates the thickness d of the first last diaphragm of inspiration1Second last diaphragm thickness d2And thickness d of diaphragm at the end of the third inspiration3Average value L of1；
The AI diagnostic device utilizes the average value L of the end-expiratory diaphragm thickness2Average value L of thickness of diaphragm muscle at end of inspiration1And calculating the diaphragm thickness change rate of the patient by a diaphragm thickness change rate formula.
Further, the formula of the change rate of the diaphragm thickness is
Wherein η is diaphragm thickness change rate L1Mean value of diaphragm thickness at end of inspiration, L2The mean value of the end-tidal diaphragm thickness.
Further, the specific step of obtaining the diaphragm movement degree of the user in step S3 is:
the AI diagnostic device scans images of the movement degree of the diaphragm from first inspiration to expiration on a display interface of the ultrasonic detection device, performs analysis processing after scanning is completed, generates a corresponding first diaphragm model, and then measures the movement degree of the diaphragm in the first diaphragm model to obtain the movement degree a of the first diaphragm1；
The AI diagnostic device scans images of diaphragm movement degree change when the display interface of the ultrasonic detection device is second inhaled to exhale, and the images are analyzed and processed after scanning is completed to generate a corresponding second diaphragm model, so that the diaphragm movement degree in the first diaphragm model is measured to obtain a second diaphragm movement degree a2；
The AI diagnostic device scans images of diaphragm movement degree change when the display interface of the ultrasonic detection device is third inhaled to exhale, the images are analyzed and processed after scanning is completed, a corresponding third diaphragm model is generated, diaphragm movement degree in the first diaphragm model is further measured, and third diaphragm movement degree a is obtained3；
The AI diagnostic device calculates the first diaphragm mobility a1Second degree of diaphragm movement a2Third diaphragm mobility a3Average value A of (A);
further, in the step S4, the specific range of the diaphragm thickness change rate cutoff value is 30% to 96%;
the specific range of the diaphragm mobility cutoff value is 14-60 mm.
Further, the doctor compares the diaphragm thickness change rate η and the diaphragm mobility A of the user obtained through measurement and calculation of the AI diagnostic device with a diaphragm thickness change rate cutoff value and a diaphragm mobility cutoff value respectively, if the diaphragm thickness change rate η is greater than 30% and smaller than 96%, and the diaphragm mobility A is greater than 14mm and smaller than 60mm, the diaphragm motion of the patient is in a normal state, the ventilator of the patient can be operated offline, and if the diaphragm thickness change rate η is not 30% -96%, and the diaphragm mobility A is not 14-60 mm, the diaphragm motion of the patient is in an abnormal state, the ventilator of the patient can not be operated offline, and the patient needs the ventilator to assist breathing.
In summary, the invention provides a method for assisting in judging whether a breathing machine is off-line by capturing diaphragm movement by using an ultrasonic AI technology, which captures a diaphragm image by using an ultrasonic detection device and analyzes and processes the diaphragm image by using an AI diagnosis device, thereby greatly reducing the investment of required medical expert resources, reducing the diagnosis time, saving the medical cost of a patient, improving the image labeling precision and efficiency, and having wide market application value.
The number of apparatuses and the scale of the process described herein are intended to simplify the description of the present invention. Applications, modifications and variations of the present invention will be apparent to those skilled in the art.
While embodiments of the invention have been disclosed above, it is not intended to be limited to the uses set forth in the specification and examples. It can be applied to all kinds of fields suitable for the present invention. Additional modifications will readily occur to those skilled in the art. The invention is therefore not to be limited to the specific details described herein, without departing from the general concept as defined by the appended claims and their equivalents.
Claims (7)
1. A method for capturing diaphragm movement by utilizing an ultrasonic AI technology to assist in judging whether a breathing machine is off-line is characterized by comprising the following steps of:
step S1, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion state of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm thickness image during expiration and inspiration on a display interface of an ultrasonic detection device;
step S2, a doctor detects the position of the diaphragm of a patient by using an ultrasonic probe, captures the motion states of the diaphragm of the patient during expiration and inspiration, and generates a diaphragm movement degree change image during expiration and inspiration on a display interface of an ultrasonic detection device;
step S3, the AI diagnostic apparatus scans the images generated in step S1 and step S2, respectively, analyzes the content of the processed images after the scanning is completed, and obtains the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user through measurement and calculation;
step S4, the doctor compares the specific values of the diaphragm thickness change rate and the diaphragm mobility of the user obtained by measurement and calculation of the AI diagnostic device with the diaphragm thickness change rate cutoff value and the diaphragm mobility cutoff value, respectively, to determine whether the diaphragm movement is normal, and further determine whether the ventilator of the patient can be taken off-line.
2. The method for assisting in judging whether the ventilator is off-line by capturing diaphragm movement through an ultrasonic AI technology as claimed in claim 1, wherein the specific method for generating the diaphragm thickness image during expiration and inspiration in step S1 is as follows:
taking a patient in a supine position, breathing autonomously, and placing a high-frequency ultrasonic probe on the right anterior axillary line, wherein the high-frequency ultrasonic probe is vertically placed between the 8 th rib and the 9 th rib of the chest wall;
the high-frequency ultrasonic probe captures the motion state of the diaphragm of the patient during expiration, and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate a diaphragm thickness image during expiration and displays the image on a display interface;
the high-frequency ultrasonic probe captures the motion state of the diaphragm of a patient during inspiration and transmits the captured motion state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device performs analysis processing to generate an image of the thickness of the diaphragm during inspiration and displays the image on a display interface;
the ultrasonic detection device respectively generates at least 2 groups of diaphragm thickness images during expiration and at least 2 groups of diaphragm thickness images during inspiration.
3. The method for assisting in judging whether the ventilator is off-line by capturing diaphragm motion through an ultrasonic AI technology as claimed in claim 1, wherein the specific method for generating the image of the change of the diaphragm mobility from expiration to inspiration in step S2 is as follows:
the patient takes a supine position, breathes autonomously, a low-frequency ultrasonic probe is arranged on the midline of the clavicle on the right side, the low-frequency ultrasonic probe is arranged between the 7 th rib and the 8 th rib of the chest wall in parallel, the low-frequency ultrasonic probe takes a coronal position and moves in the axial direction perpendicular to the head and the tail of the diaphragm, and the diaphragm is positioned after the display interface of the ultrasonic detection device displays the gallbladder interface;
after the diaphragm moves stably, the low-frequency ultrasonic probe captures the movement state of the diaphragm when a patient inhales to exhales, and transmits the captured movement state data of the diaphragm to the ultrasonic detection device, and the ultrasonic detection device analyzes and processes the data to generate an image of the movement degree change of the diaphragm when the patient inhales to exhales and displays the image on a display interface;
the ultrasonic detection device respectively generates at least 2 groups of images of the change of the diaphragm movement degree from inspiration to expiration.
4. The method for assisting in judging whether the ventilator is off-line by capturing diaphragm movement through an ultrasonic AI technique according to claim 1, wherein the specific step of obtaining the diaphragm thickness change rate of the user in step S3 is:
the AI diagnosis device respectively scans a plurality of groups of images of the diaphragm thickness during expiration on a display interface of the ultrasonic detection device, analyzes and processes the images after the scanning is finished, respectively generates corresponding expiratory diaphragm models, further respectively measures the thickness of the end-expiratory diaphragm in each expiratory diaphragm model, and takes the average value of the thicknesses of the end-expiratory diaphragms;
the AI diagnosis device respectively scans a plurality of groups of images of the diaphragm thickness during inspiration of a display interface of the ultrasonic detection device, analyzes and processes the images after the scanning is finished, respectively generates corresponding inspiration diaphragm models, further respectively measures the thickness of the last inspiration diaphragm in each inspiration diaphragm model, and takes the average value of the thicknesses of the last inspiration diaphragm;
the AI diagnostic device calculates the diaphragm thickness change rate of the patient by using the average value of the end-expiratory diaphragm thicknesses, the average value of the end-inspiratory diaphragm thicknesses and a diaphragm thickness change rate formula.
5. The method for assisting in judging whether the ventilator is off-line by capturing diaphragm movement through an ultrasonic AI technology as claimed in claim 4, wherein the formula of the diaphragm thickness change rate is
Wherein η is diaphragm thickness change rate L1Mean value of diaphragm thickness at end of inspiration, L2The mean value of the end-tidal diaphragm thickness.
6. The method for assisting in judging whether the ventilator is offline by capturing diaphragm movement through an ultrasonic AI technique according to claim 1, wherein the specific steps of obtaining the diaphragm movement degree of the user in step S3 are as follows:
the AI diagnosis device scans a plurality of groups of images of the movement degree of the diaphragm from inspiration to expiration on a display interface of the ultrasonic detection device respectively, analyzes and processes the images after the scanning is finished, generates corresponding diaphragm models respectively, measures the movement degree of the diaphragm in each diaphragm model respectively, and takes the average value of the movement degree of the diaphragm.
7. The method for assisting in judging the ventilator off-line by capturing diaphragm movement through an ultrasonic AI technique as claimed in claim 1, wherein the specific range of the diaphragm thickness change rate cutoff value in step S4 is 30% -96%;
the specific range of the diaphragm mobility cutoff value is 14-60 mm.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911412157.4A CN110974298A (en) | 2019-12-31 | 2019-12-31 | Method for capturing diaphragm movement by utilizing ultrasonic AI technology to assist judgment of ventilator off-line |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911412157.4A CN110974298A (en) | 2019-12-31 | 2019-12-31 | Method for capturing diaphragm movement by utilizing ultrasonic AI technology to assist judgment of ventilator off-line |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110974298A true CN110974298A (en) | 2020-04-10 |
Family
ID=70079738
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911412157.4A Pending CN110974298A (en) | 2019-12-31 | 2019-12-31 | Method for capturing diaphragm movement by utilizing ultrasonic AI technology to assist judgment of ventilator off-line |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110974298A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2746569C1 (en) * | 2020-05-18 | 2021-04-15 | Федеральное государственное бюджетное учреждение "Новосибирский научно-исследовательский институт травматологии и ортопедии им. Я.Л. Цивьяна" Министерства здравоохранения Российской Федерации (ФГБУ "ННИИТО им. Я.Л. Цивьяна" Минздрава России) | Method for weaning from artificial ventilation of lung patients with spinal cord injury at the level of the neck spine with severity of spinal cord injury asia a and asia b |
| WO2022073306A1 (en) * | 2020-10-10 | 2022-04-14 | 深圳迈瑞生物医疗电子股份有限公司 | Ultrasonic measurement method and system for diaphragm |
| CN114983469A (en) * | 2022-06-21 | 2022-09-02 | 四川大学华西医院 | Method and device for respiratory drive assessment by using ultrasound |
| CN115778430A (en) * | 2022-12-05 | 2023-03-14 | 北京智影技术有限公司 | Method and device for automatically measuring diaphragm mobility and storage medium |
| CN115797296A (en) * | 2022-12-05 | 2023-03-14 | 北京智影技术有限公司 | Method and device for automatically measuring diaphragm thickness and storage medium |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5448995A (en) * | 1994-02-14 | 1995-09-12 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | Method and apparatus for non-invasive evaluation of diaphragmatic function |
| CN103142400A (en) * | 2013-03-20 | 2013-06-12 | 张栋 | Method for generating diaphragm rehabilitation stimulation signal and diaphragm functional rehabilitative apparatus |
| CN104545987A (en) * | 2013-10-10 | 2015-04-29 | 深圳迈瑞生物医疗电子股份有限公司 | Monitor for monitoring diaphragm motion conditions |
| CN106422060A (en) * | 2016-10-21 | 2017-02-22 | 上海海神医疗电子仪器有限公司 | Dual-mode dual-control diaphragm stimulation mechanical ventilation assist device |
| CN206560596U (en) * | 2016-10-21 | 2017-10-17 | 上海海神医疗电子仪器有限公司 | A kind of man-machine synchronized with breath ventilation assist device |
| CN109394511A (en) * | 2018-12-20 | 2019-03-01 | 张健鹏 | Abdomen squash type air-breather and its control method, two-way Breathing Suppotion ventilator |
| CN208591054U (en) * | 2017-10-09 | 2019-03-12 | 广州医科大学附属第一医院 | A device for accurate assessment of weaning |
| CN109758183A (en) * | 2018-12-13 | 2019-05-17 | 孔维炜 | It is a kind of intelligence bedside ultrasound to patients with mechanical ventilation diaphragm function assessment system |
-
2019
- 2019-12-31 CN CN201911412157.4A patent/CN110974298A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5448995A (en) * | 1994-02-14 | 1995-09-12 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | Method and apparatus for non-invasive evaluation of diaphragmatic function |
| CN103142400A (en) * | 2013-03-20 | 2013-06-12 | 张栋 | Method for generating diaphragm rehabilitation stimulation signal and diaphragm functional rehabilitative apparatus |
| CN104545987A (en) * | 2013-10-10 | 2015-04-29 | 深圳迈瑞生物医疗电子股份有限公司 | Monitor for monitoring diaphragm motion conditions |
| CN106422060A (en) * | 2016-10-21 | 2017-02-22 | 上海海神医疗电子仪器有限公司 | Dual-mode dual-control diaphragm stimulation mechanical ventilation assist device |
| CN206560596U (en) * | 2016-10-21 | 2017-10-17 | 上海海神医疗电子仪器有限公司 | A kind of man-machine synchronized with breath ventilation assist device |
| CN208591054U (en) * | 2017-10-09 | 2019-03-12 | 广州医科大学附属第一医院 | A device for accurate assessment of weaning |
| CN109758183A (en) * | 2018-12-13 | 2019-05-17 | 孔维炜 | It is a kind of intelligence bedside ultrasound to patients with mechanical ventilation diaphragm function assessment system |
| CN109394511A (en) * | 2018-12-20 | 2019-03-01 | 张健鹏 | Abdomen squash type air-breather and its control method, two-way Breathing Suppotion ventilator |
Non-Patent Citations (4)
| Title |
|---|
| 徐晓婷,刘玲: "床边超声对机械通气患者膈肌功能评估的研究进展", 《中华重症医学电子杂志(网络版)》 * |
| 林宁,黄秋霞,张慧珍,陈梦奇,唐力,卢锋峰: "膈肌超声在机械通气患者撤机中的应用", 《中国呼吸与危重监护杂志》 * |
| 管向东，于凯江，陈德昌，康焰: "《重症医学 2019》", 31 January 2019, 中华医学电子音像出版社 * |
| 邓超，李宝平，李兴旺，王小旗: "《数字图像处理与模式识别研究》", 30 June 2018 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| RU2746569C1 (en) * | 2020-05-18 | 2021-04-15 | Федеральное государственное бюджетное учреждение "Новосибирский научно-исследовательский институт травматологии и ортопедии им. Я.Л. Цивьяна" Министерства здравоохранения Российской Федерации (ФГБУ "ННИИТО им. Я.Л. Цивьяна" Минздрава России) | Method for weaning from artificial ventilation of lung patients with spinal cord injury at the level of the neck spine with severity of spinal cord injury asia a and asia b |
| WO2022073306A1 (en) * | 2020-10-10 | 2022-04-14 | 深圳迈瑞生物医疗电子股份有限公司 | Ultrasonic measurement method and system for diaphragm |
| CN114983469A (en) * | 2022-06-21 | 2022-09-02 | 四川大学华西医院 | Method and device for respiratory drive assessment by using ultrasound |
| CN115778430A (en) * | 2022-12-05 | 2023-03-14 | 北京智影技术有限公司 | Method and device for automatically measuring diaphragm mobility and storage medium |
| CN115797296A (en) * | 2022-12-05 | 2023-03-14 | 北京智影技术有限公司 | Method and device for automatically measuring diaphragm thickness and storage medium |
| CN115797296B (en) * | 2022-12-05 | 2023-09-05 | 北京智影技术有限公司 | Automatic diaphragm thickness measuring method, device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110974298A (en) | Method for capturing diaphragm movement by utilizing ultrasonic AI technology to assist judgment of ventilator off-line | |
| CN109996488B (en) | Breath early warning scoring system and method | |
| KR101805078B1 (en) | Devices and methods for respiratory variation monitoring by measurement of respiratory volumes, motion and variability | |
| JP6247217B2 (en) | Detection of mouth breathing in early expiration | |
| CN110996781A (en) | Respiratory volume monitors and ventilators | |
| RU2700981C2 (en) | Non-invasive assessment of intrapleural pressure and/or calculation of respiratory work based on non-invasive assessment of intrapleural pressure | |
| US10271767B2 (en) | Automated spirogram analysis and interpretation | |
| US20170055878A1 (en) | Method and system for respiratory monitoring | |
| CN112156301A (en) | Automatic optimization setting method for PEEP of breathing machine based on electrical impedance imaging | |
| EP3057509B1 (en) | Blood flow control system and methods for in-vivo imaging and other applications | |
| CN113017600B (en) | A training evaluation system and method for medical imaging examination | |
| CN114983469A (en) | Method and device for respiratory drive assessment by using ultrasound | |
| KR102105887B1 (en) | Non-invasive mechanical ventilation system to measure change of air voloume in lungs and obstruction degree of airway and operating method thereof | |
| US20170100059A1 (en) | Lung function monitoring | |
| CN112754465A (en) | Method for estimating quasi-static compliance of lung under pressure-controlled mechanical ventilation | |
| CN110623668A (en) | A rapid magnetic resonance imaging method for quantitative assessment of lung compliance | |
| JP6014846B2 (en) | Respiration measurement method and apparatus | |
| JP6273940B2 (en) | Image analysis apparatus, image photographing system, and image analysis program | |
| US11723549B2 (en) | System for capturing respiratory effort of a patient | |
| CN112089933A (en) | Method for dynamically measuring and calculating respiratory mechanics parameters based on breathing machine | |
| CN109316189B (en) | A kind of non-contact respiratory dynamic detection method and device | |
| US20230414889A1 (en) | Automatic detection of a diaphragm in time-motion data using ventilator waveforms | |
| US20240165353A1 (en) | Systems and methods for ultrasound-based assessment of regional respiratory parameters to guide lung protective ventilation | |
| Schott et al. | Real-time computation of a patient's respiratory effort during ventilation | |
| CN221786267U (en) | Respiration detection device for CT |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |