KR102555586B1 - Portable respiratory disease smart integrated diagnosis system and method - Google Patents

Abstract

The present invention relates to a portable respiratory disease smart integrated diagnosis system, wherein an integrated measurement investigation unit collects patient data by performing low-dose X-ray imaging, body temperature measurement, and oxygen saturation measurement, and transmits the patient data received from the integrated measurement investigation unit to a medical staff. communication unit, a data reading unit that automatically converts the patient data collected by the integrated measurement and investigation unit into a preset format and reads whether or not the suspected area is included, and the data reading unit reads that the suspected area is included as a result of reading, It is characterized in that it includes an AI model unit for diagnosing the patient's lung disease disease name by matching the patient data with previously stored lung disease patient data.

Description

Portable respiratory disease smart integrated diagnosis system and its method {PORTABLE RESPIRATORY DISEASE SMART INTEGRATED DIAGNOSIS SYSTEM AND METHOD}

The present invention relates to a respiratory disease diagnosis system and method, and more particularly, to a portable respiratory disease smart integrated diagnosis system that selects patients through one-stop testing of infectious and febrile respiratory diseases of patients.

Recently, many people have been infected with the COVID-19 virus, a respiratory infectious disease, and if symptoms worsen from isolation with mild symptoms, they may barely maintain breathing through a respirator throughout 24 hours, and if symptoms worsen, they may die. do up to

The COVID-19 virus is pandemic not only in specific regions but also around the world, causing not only social problems such as medical collapse and crowding restrictions, but also economic problems due to large-scale factory closures and strict immigration control due to group infections.

As such, the reason why the Corona 19 virus is the most lethal to the human body is that pneumonia, which is inflamed in the lungs, is the biggest reason.

In particular, problems caused by pneumonia can be more fatal for the elderly over 65 years of age or those with chronic diseases.

In order to prevent the spread of such infectious diseases, government medical institutions or public health centers can diagnose infection through screening tests. Chest X-ray examination is not performed for reasons of radiation exposure and examination cost.

However, among elderly asymptomatic patients, there are many patients who are diagnosed with severe pneumonia on a chest X-ray, but miss the timing of treatment because they cannot be tested early.

Therefore, using an artificial intelligence-based integrated diagnosis system that simultaneously measures low-dose chest X-ray imaging, body temperature, and oxygen saturation for diagnosis of lung disease including respiratory infectious disease infection such as the COVID-19 virus and diagnosis of lung disease disease. An integrated diagnostic method for respiratory diseases is required.

Korean Patent Registration No. 10-1536671

An object of the present invention is to simplify the diagnosis process by one-stop the process of measuring body temperature, taking and reading a chest X-ray, and measuring oxygen saturation.

In addition, the purpose is to block the expansion path of infectious diseases by screening for infectious and febrile diseases using artificial intelligence-based integrated diagnostic software and identifying patients subject to quarantine at an early stage.

In addition, the purpose is to secure the safety of medical staff from secondary infection of patients by providing non-face-to-face treatment through an integrated diagnosis system.

In addition, by using a low-dose portable X-Ray generator, an object is to minimize the patient's radiation exposure and ease the restrictions of the examination place by facilitating movement.

In addition, by using an AI model based on DNN (Deep Neural Network), which is mainly used in deep learning, the purpose is to diagnose the patient with an accurate lung disease name based on the patient's symptoms and test results.

The portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention includes an integrated measurement investigation unit that collects patient data by performing low-dose X-ray imaging, body temperature measurement, and oxygen saturation measurement, and the patient data received from the integrated measurement investigation unit. A communication unit that transmits data to the medical staff, a data reading unit that automatically converts the patient data collected by the integrated measurement and investigation unit into a preset format and reads whether or not the suspected area is included, and the reading result of the data reading unit reads that the suspected area is included. In this case, an AI model unit for diagnosing the patient's lung disease disease by matching the patient data with previously stored lung disease patient data may be included.

In addition, the integrated measurement and investigation unit includes a thermal imaging body temperature measurement camera that measures the patient's body temperature through a thermal image, an X-ray imaging unit that transmits X-rays through the patient and extracts a chest X-ray image, and measures the oxygen content in the patient's blood. A sensor for measuring oxygen saturation, a rendering unit for generating a 3D rendering image using the patient data, an output unit for outputting the rendered image, and the 3D rendering image output to the output unit to be output to the medical staff's examination monitor Transmitting It may include a transmission unit.

In addition, the integrated measurement investigation unit displays a fever alarm on the examination monitor of the medical staff when the body temperature measured from the patient is 37.5 degrees or more, and after completing the measurement of the patient with the fever alarm displayed, ventilation and ventilation for a predetermined time A disinfection alarm can be maintained to induce ventilation and disinfection of the examination site.

In addition, the data reading unit matches the patient's X-ray image data, body temperature data and oxygen saturation data collected by the integrated measurement and investigation unit with pre-stored preliminary reading data to output whether or not a lung disease is suspected to the examination monitor of the medical staff , In case of determining whether or not the patient is suspected of lung disease, the location corresponding to the normal X-ray imaging data is matched based on the position of the bronchi of the patient's X-ray imaging image data, and then matching is performed, and the body temperature data is a preset body temperature range It is determined whether or not it is included within, and it is determined whether or not the oxygen saturation data is included within a predetermined oxygen saturation range, and it is possible to determine whether the lung disease of the patient is suspected.

In addition, the AI model unit, when the data reading unit determines that the patient is suspected of having a lung disease, sequentially matches all previously stored lung disease patient data to diagnose the disease name, progression, and onset site of the lung disease, Based on DNN (Deep Neural Network), it is possible to additionally learn X-ray data of lung disease patients, body temperature measurement data, and oxygen saturation measurement data of lung disease patients.

In addition, the data reading unit calculates color code ratios of pixels for each unit area of the X-ray image taken from the patient, and calculates color code ratios of pixels for each unit area. If it is out of the standard range, a suspected lung disease alarm may be sent.

In addition, when a lung disease suspected alarm based on the color code ratio of pixels for each unit area calculated from the patient's X-ray image is transmitted, a coordinate system having the bronchi as the origin is created in the patient's X-ray image, and the lung disease is detected. Coordinate values of the suspected unit area may be calculated, and chest X-rays may be re-photographed centering on the calculated coordinate values.

According to the present invention, it is possible to simplify the diagnosis process by one-stop the process of measuring body temperature, taking and reading chest X-ray, and measuring oxygen saturation.

In addition, by using artificial intelligence-based integrated diagnostic software to select infectious and febrile diseases and identify patients subject to quarantine at an early stage, it is possible to block the spread of infectious diseases.

In addition, by providing non-face-to-face treatment through an integrated diagnosis system, it is possible to secure the safety of medical staff from secondary infection of patients.

In addition, by using a low-dose portable X-Ray generator, it is possible to minimize the patient's radiation exposure and ease the restrictions of the examination place because it is easy to move.

In addition, by using an AI model based on DNN (Deep Neural Network), which is mainly used in deep learning, it is possible to diagnose patients with accurate lung disease names based on the patient's symptoms and test results.

1 is a flow chart of a portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention.
2 is a diagram illustrating a fusion-type low-dose portable X-ray generator according to an embodiment of the present invention.
FIG. 3 is a diagram showing diagnosis through wireless AP communication of the portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention.
4 is a diagram illustrating AI modeling of a portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention.

The specific details, including the problems to be solved, the means for solving the problems, and the effects of the invention for the present invention as described above are included in the embodiments and drawings to be described below. Advantages and features of the present invention, and methods for achieving them, will become clear with reference to the detailed description of the following embodiments in conjunction with the accompanying drawings.

The scope of the present invention is not limited to the examples described below, and can be variously modified and implemented by those skilled in the art without departing from the technical gist of the present invention.

Hereinafter, the portable respiratory disease smart integrated diagnosis system of the present invention will be described in detail with reference to FIGS. 1 to 4 attached.

First, FIG. 1 is a flow chart of a portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention, FIG. 2 is a diagram showing a convergence type low-dose portable X-ray generator according to an embodiment of the present invention, and FIG. 3 is a diagram showing diagnosis through wireless AP communication of a portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention, and FIG. 4 is an AI of a portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention It is a drawing showing modeling.

Referring to FIG. 1, the portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention may include an integrated measurement research unit 110, a communication unit 120, a data reading unit 130, and an AI model unit 140. can

The integrated measurement survey unit 110 may collect patient data by performing low-dose X-ray imaging, body temperature measurement, and oxygen saturation measurement.

At this time, the integrated measurement survey unit 110 will be described in more detail with reference to FIG. 2 .

Referring to FIG. 2 , the integrated measurement survey unit 110 includes a thermal imaging body temperature measurement camera 210, an X-ray photographing unit 220, an oxygen saturation measurement sensor 230, a rendering unit 240, and an output unit 250. And it may include a transmission unit 260.

The thermal image body temperature measurement camera 210 may measure the patient's body temperature through a thermal image.

The X-ray imaging unit 220 may transmit X-rays through the patient's chest to extract a chest X-ray image.

Here, the X-ray imaging unit 220 can more clearly identify structures and lesions during imaging compared to conventional X-ray imaging equipment, and can radiate low-dose X-rays that minimize radiation exposure of the subject by reducing the amount of X-rays used.

The oxygen saturation measurement sensor 230 is attached using an oxygen saturation measurement sensor attachment connector located outside the integrated measurement research unit 110 and may serve to measure the patient's oxygen saturation.

At this time, the oxygen saturation measuring sensor 230 may measure and digitize the oxygen saturation of the patient through measurement for about 5 seconds in a form of being bitten or inserted into the patient's finger.

When determining whether or not there is a lung disease according to the measured oxygen saturation, a different reference value may be applied according to the condition of the subject. For example, when the patient has chronic obstructive pulmonary disease, even if the measured oxygen saturation is 90 to 94%, it may be determined to be normal in consideration of the lung disease. On the other hand, for a subject without any underlying disease, even if the measured oxygen saturation corresponds to 90 to 94%, it is judged as suspected lung disease.

The rendering unit 240 may convert the measured patient data into a 3D rendered image.

Here, the rendering unit 240 converts the external appearance of the patient into a 3D image, and converts the imaged image into an image displaying the measured body temperature for each part of the patient.

The patient's body shape or silhouette can be rendered through low-dose X-rays, and the body temperature and oxygen saturation can be expressed in the rendered 3D image with colors and contour lines.

The output unit 250 may output the 3D rendered image converted by the rendering unit 240 to a screen.

The transmission unit 260 may transmit the 3D rendered image output to the output unit 250 to the examination monitor of the medical staff.

Meanwhile, the integrated measurement and investigation unit 110 may display a fever alarm on the medical staff's inspection monitor when the measured body temperature of the patient is 37.5 degrees or higher.

At this time, after the measurement of the patient with the fever alarm displayed, ventilation and disinfection alarms may be maintained for a predetermined time to induce ventilation and disinfection of the examination place.

Here, the disinfection alarm may be maintained for at least 10 minutes after the patient finishes the measurement, and may be locked so that the measurement operation of the integrated measurement investigation unit 110 is not performed while the disinfection alarm is maintained.

The communication unit 120 may transmit the patient data received from the integrated measurement survey unit 110 to a medical staff.

Here, the communication unit 120 may be described in more detail with reference to FIG. 3 .

Referring to FIG. 3 , the communication unit 120 not only transmits the patient data, but also transmits examination guides or instructions to the patient under examination by the medical staff, so that the examination of the patient can be performed accurately.

In addition, by transmitting the patient data and diagnosis data to the medical staff's PC or smart device, the medical staff's convenience can be further increased.

The data reading unit 130 may automatically convert the patient data collected by the integrated measurement investigation unit 110 into a preset format and read whether or not a suspicious area is included.

Here, the data reading unit 130 matches the patient's X-ray image data, body temperature data, and oxygen saturation data collected by the integrated measurement and investigation unit 110 with pre-stored preliminary reading data to determine whether lung disease is suspected. It can be output to the medical staff's inspection monitor.

At this time, when it is determined whether the lung disease of the patient is suspected, the location corresponding to the normal X-ray imaging data may be matched based on the location of the bronchi of the X-ray imaging image data taken from the patient, and then matched.

It is determined whether the body temperature data is included within a predetermined body temperature range, wherein the predetermined body temperature range is 36.4 to 38 ° C for 0 to 2 years old, 36.1 to 37.8 ° C for 3 to 10 years old, and 11 to 11 years old according to the age of the patient. 35.9 to 37.6 ° C. for those aged 65 and 35.8 to 37.5 ° C. for those aged 65 or older may be set as normal ranges to determine whether the measured body temperature of the patient is normal.

It is determined whether the oxygen saturation data is within a predetermined oxygen saturation range, and it is possible to determine whether or not the lung disease of the patient is suspected.

At this time, when the predetermined oxygen saturation range is 95 to 99%, it can be determined as 'normal', and when it is 90 to 94%, it can be determined as 'hypoxia state', and the measured oxygen saturation is 90%. If it is less than %, it can be judged as 'hypoxia dyspnea warning' state.

Meanwhile, the data reading unit 130 may calculate a color code ratio of pixels for each unit area of the X-ray image captured from the patient.

Here, the data reading unit 130 can be described in more detail with reference to FIG. 4 .

Referring to FIG. 4, the color code is a method of expressing colors using R (red), G (green), and B (blue), which are three primary colors of light. It can be expressed in RGB, and the value of the RGB can be assigned from 0 to a maximum of 255.

In addition, the given numerical value of 0 to 255 can be converted into a hexadecimal number and converted into a color code by attaching a '#' sign.

For example, in the case of the blackest color code, the RGB values are calculated as 0,0,0, respectively, and can be expressed as #000000 as a color code, and the whitest RGB values are calculated as 255,255,255, respectively, and expressed as #FFFFFF. can

In this case, since the X-ray image is expressed only in black and white, the color code can be measured with the values of 0 to 255 of the RGB values all maintained the same.

That is, all colors expressed in the X-ray image, such as dark gray and gray located between black and white, have RGB values of 133, 133, 133, or 79, 79, and 79, respectively. It can be expressed with the same color code.

Also, the unit area may refer to a horizontal and vertical pixel value area of the patient's X-ray image.

For example, when the X-ray image of the patient has a width of 627px (pixels) and a length of 460px, the color code of 1px in the unit region may be calculated by setting the unit area to 10x10px.

Through this, when the calculated color code ratio of pixels for each unit area is out of a standard range of the pre-stored color code ratio of pixels for each unit area, a suspected lung disease alarm can be transmitted to the medical staff.

Here, the pre-stored color code ratio of pixels for each unit area is calculated by calculating the average value of the color code for each unit area of the patient's X-ray images that are determined to be normal collected by the integrated measurement investigation unit 110 or determined normal collected from the outside. A color code ratio obtained by calculating the color code for each unit area of the received patient's X-ray image may be stored as a normal reference range.

Meanwhile, when a lung disease suspected alarm based on the color code ratio of pixels for each unit area calculated from the patient's X-ray image is transmitted, a coordinate system having the bronchus as the origin may be created in the patient's X-ray image.

More specifically, the origin may be set to a central point where the bronchi are merged into the trachea in the X-ray image of the patient.

In this case, it is possible to determine in more detail whether or not the patient has a lung disease by calculating the coordinate values of the unit region suspected of having the lung disease and re-taking a chest X-ray based on the calculated coordinate values.

The AI model unit 140 can diagnose the patient's lung disease by matching the patient data with pre-stored lung disease patient data, when the reading result of the data reading unit indicates that the suspect region is included.

That is, when the data reading unit 130 determines that the patient is suspected of having a lung disease, it is possible to diagnose the disease name, progression, and onset site of the lung disease by sequentially matching with all previously stored lung disease patient data.

Here, the pre-stored lung disease patient data may be matched with the patient data by storing at least 10,000 pieces of data including body temperature, oxygen saturation, and X-ray image data of the lung disease patient from the outside.

In addition, based on Deep Neural Network (DNN), a deep learning neural network technology, additionally updated X-ray data of lung disease patients, body temperature measurement data of lung disease patients, and oxygen saturation measurement data of lung disease patients can be periodically additionally learned.

Through this, it is possible to extract characteristic elements according to the type of lung disease, analyze the patient data in a short time by converting it into big data, and deliver the suspected lung disease and the name of the lung disease to the medical staff to assist in quick diagnosis. there is.

Through the above process, the portable respiratory disease smart integrated diagnosis system provides a one-stop service for determining whether a patient has a lung disease through a low-dose X-ray generator, a thermal imaging body temperature measurement camera, and an oxygen saturation measurement sensor, and transmits the test results through wireless communication. The most similar result data is matched with a plurality of patient data using the data reading unit 130 and the AI model unit 140 to prevent further infection of the infectious disease by transmitting the data to the medical staff using the data reading unit 130 and the AI model unit 140. A portable respiratory disease smart integrated diagnosis system can be provided that extracts and delivers the patient's lung disease and the name of the lung disease to the medical staff to quickly diagnose and prevent diagnosis errors.

According to the effects of the present invention as described above, it is possible to simplify the diagnosis process by one-stop the processes of body temperature measurement, chest X-ray imaging and reading, and oxygen saturation measurement.

In addition, by using artificial intelligence-based integrated diagnostic software to select infectious and febrile diseases and identify patients subject to quarantine at an early stage, it is possible to block the spread of infectious diseases.

In addition, by providing non-face-to-face treatment through an integrated diagnosis system, it is possible to secure the safety of medical staff from secondary infection of patients.

In addition, by using a low-dose portable X-Ray generator, it is possible to minimize the patient's radiation exposure and ease the restrictions of the examination place because it is easy to move.

In addition, by using an AI model based on DNN (Deep Neural Network), which is mainly used in deep learning, it is possible to diagnose patients with accurate lung disease names based on the patient's symptoms and test results.

In addition, the control method of the portable respiratory disease smart integrated diagnosis system according to an embodiment of the present invention may be recorded in a computer readable medium containing program instructions for performing various computer-implemented operations. The computer readable medium may include program instructions, data files, data structures, etc. alone or in combination. The medium may include program instructions specially designed and configured for the present invention, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. - includes hardware devices specially configured to store and execute program instructions, such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include high-level language codes that can be executed by a computer using an interpreter, as well as machine language codes such as those produced by a compiler.

As described above, although one embodiment of the present invention has been described by means of limited embodiments and drawings, one embodiment of the present invention is not limited to the above-described embodiments, which is based on common knowledge in the field to which the present invention belongs. Those who have it can make various modifications and variations from these materials. Therefore, one embodiment of the present invention should be grasped only by the claims described below, and all equivalent or equivalent modifications thereof will be said to belong to the scope of the present invention.

100: Portable respiratory disease smart integrated diagnosis system
110: Integrated measurement investigation department
120: wireless communication unit
130: data reading unit
140: AI model unit
210: thermal imaging body temperature measurement camera
220: X-ray imaging unit
230: oxygen saturation measurement sensor
240: rendering unit
250: output unit
260: transmission unit

Claims (7)

An integrated measurement investigation unit that collects patient data by performing low-dose X-ray imaging, measuring body temperature, and measuring oxygen saturation;
a communication unit which transmits the patient data received from the integrated measurement survey unit to a medical staff;
a data reading unit that automatically converts the patient data collected by the integrated measurement investigation unit into a preset format and reads whether or not the suspected area is included; and
an AI model unit for diagnosing the name of the patient's lung disease by matching the patient data with previously stored lung disease patient data when the reading result of the data reading unit indicates that the suspected region is included;
including,
The integrated measurement investigation unit,
a thermal imaging body temperature measurement camera that measures a patient's body temperature through a thermal image;
an X-ray imaging unit that transmits X-rays through the patient and extracts a chest X-ray image;
An oxygen saturation measurement sensor for measuring the oxygen content in the patient's blood;
a rendering unit generating a 3D rendering image using the patient data;
an output unit outputting the rendered image; and
A portable respiratory disease smart integrated diagnosis system comprising a; transmission unit for transmitting the 3D rendering image output to the output unit to be output to an examination monitor of a medical staff.
delete According to claim 1,
The integrated measurement investigation unit,
When the body temperature measured from the patient is 37.5 degrees or more, a fever alarm is displayed on the examination monitor of the medical staff,
After completing the measurement of the patient with the fever alarm displayed, the portable respiratory disease smart integrated diagnosis system, characterized in that by displaying a quarantine alarm to induce ventilation and disinfection of the examination site by maintaining the ventilation and disinfection alarm for a predetermined time.
According to claim 1,
The data reading unit,
The patient's X-ray image data, body temperature data, and oxygen saturation data collected by the integrated measurement and investigation unit are matched with pre-stored preliminary reading data to output suspected lung disease on the examination monitor of the medical staff,
When determining whether or not the patient has a suspected lung disease, the location corresponding to the normal X-ray imaging data is matched based on the location of the bronchi of the patient's X-ray imaging image data, and the body temperature data is included within a preset body temperature range. Portable respiratory disease smart integrated diagnosis system, characterized in that for determining whether or not, determining whether the oxygen saturation data is included within a predetermined oxygen saturation range, and determining whether the patient's lung disease is suspected.
According to claim 4,
The AI model unit,
If the data reading unit determines that the patient is suspected of having a lung disease, it is sequentially matched with all previously stored lung disease patient data to diagnose the disease name, progression, and onset site of the lung disease,
A portable respiratory disease smart integrated diagnosis system characterized in that it additionally learns X-ray image data of lung disease patients, body temperature measurement data of lung disease patients, and oxygen saturation measurement data of lung disease patients added based on DNN (Deep Neural Network).
According to claim 1,
The data reading unit,
Calculate a color code ratio of pixels for each unit area of the X-ray image taken from the patient;
When the calculated color code ratio of pixels for each unit area is out of the standard range of the pre-stored color code ratio of pixels for each unit area, a lung disease suspected alarm is transmitted. A portable respiratory disease smart integrated diagnosis system.
According to claim 6,
When a lung disease suspected alarm based on the color code ratio of pixels for each unit area calculated from the patient's X-ray image is transmitted, a coordinate system having a preset point in the patient's X-ray image as the origin is created,
A portable respiratory disease smart integrated diagnosis system, characterized in that for calculating the coordinate values of the unit area suspected of having the lung disease and re-photographing the chest X-ray based on the calculated coordinate values.