KR101978900B1 - Apparatus, and method for examining pulmonary function using face image, and computer readable recording medium for recoring the same - Google Patents

Abstract

An apparatus and method for measuring pulmonary function using facial images and a computer-readable recording medium recording the same are disclosed. The apparatus for measuring pulmonary function using a facial image according to the present invention executes a camera, a memory, and a specific application, receives personal information of at least one of age, sex, key, or weight of a user, And a control unit for photographing the respiration process of the user through the camera, extracting at least one face region from the captured image, and detecting the lung function using the color data of the at least one face region. According to the present invention, obstructive / restrictive ventilatory disturbance can be determined in a non-contact manner, and lung function measurement can be performed in consideration of individual differences, thereby improving accuracy.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an apparatus and method for measuring lung function using facial images, and a computer readable recording medium storing the same. [0002]

The present invention relates to an apparatus and method for measuring pulmonary function using a facial image acquired through a camera, and a computer-readable recording medium on which the method is recorded.

The pulmonary function test is a test to evaluate the gas exchange process of the lungs, that is, the ventilation, perfusion, and diffusing function. In particular, evaluation of the ventilatory function is called pulmonary function test. Pulmonary function tests are performed for the purpose of assessing obstructive and restrictive ventilatory disturbances and their severity. They are used mainly for the diagnosis of chronic obstructive pulmonary disease, the prognosis of surgical treatment such as asthma and lung cancer.

Conventionally, the lung function measurement was performed by inverting a water tank filled with water, breathing through the rubber pipe to the inside of the water tank, blocking the input of the water tank, and measuring the forced vital capacity by the amount of water remaining. However, there is a problem in that it can not provide an objective numerical value.

In addition, if the breathing volume of the diagnosed spirometry device is maximized, the breathing is detected in the rotating air flow measuring sensor mounted on the turbine of the measuring instrument, and the rotational air flow rate data is obtained and analyzed to measure the lung function Is used. However, this method is problematic in hygienic or durability because the user directly spits on the skin of the user because the user spits the breath which is maximally swallowed to the flow head of the diagnostic lung volume measuring device and measures the forced lung capacity.

In addition, although a non-contact method for measuring the forced vital capacity by breathing after maximum intake of a microphone of a smart device has been developed, there is a problem that surrounding noise is mixed or the objectivity is not secured due to the performance of the microphone.

In order to solve the above-mentioned problems and other problems, the present invention provides a lung function measuring apparatus using a face image, which enables non-contact lung function measurement by calculating maximal expiratory flow rate and forced lung capacity using color data of a facial image, And a computer-readable recording medium on which the method is recorded.

According to an aspect of the present invention, there is provided a method of inputting information (sex, age, weight, key, etc.) of a user and acquiring a face image do. The facial image includes the skin area of the user. The arithmetic unit detects the skin region from the face image captured by the camera. The algorithm by which the computing device detects the region of interest of the skin can use various techniques known in the art.

The computing device obtains the average of the color data for the skin area of interest. The computing device may obtain the average value of the color data for the entire extracted skin area. Also, the computing device may obtain an average of color data for a specific skin region in the acquired image. The arithmetic unit continuously obtains color data in successive images (consecutive frames).

Various values can be used for the color data. For example, (1) the color data may use at least one of an R value, a G value, and a B value based on the RGB color scheme. The color data may use an average value for at least one of R value, G value, and B value. (2) The computing device can convert the RGB color scheme to another color scheme. For example, the computing device may convert the RGB color scheme to various color schemes such as YUV, HSV, YCbCr, YCgCo, and the like. In this case, the color data may use one of color difference components that receive less image in the surrounding environment (illumination, etc.). For example, in the case of YCbCr, at least one of Cb and Cr can be used. In the case of YCgCo, at least one of Cg and Co may be used. Further, one of the two chrominance components, which is more robust to the variation of the illuminance, can be used. For example, in the case of YCgCo, only Cg can be used. In this case, the computing device can extract the average value of the Cg color data of the skin region as color data. (3) Further, the color data may be a value obtained by combining weights applied to at least one color component in various color systems such as RGB, YUV, HSV, YCbCr, YCgCo, and the like. In the case of combining color components, the color data may be a value obtained by adding different weighted values depending on the color system and the type of color component. Hereinafter, it is assumed that the calculation device obtains the average value of Cg color data in YCgCo and uses it. The computing device can change the face image having the RGB color scheme to the YCgCo color system using [Equation 1] below.

, Forced Expiratory Volume)을 측정한다. 또한, 측정된 1초, 2초, 3초 강제 호기량을 이용하여 강제 폐활량(FVC, Forced Vital Capacity)을 측정하여 폐기능을 검출하는 것을 특징으로 하는 얼굴 영상을 이용한 폐기능 측정 장치를 제공한다.After breathing as much as possible, it converts the RGB color scheme of the face image to the YCgCo color scheme. The Cg color data average height value from the smallest peak value to the next positive peak value is detected by applying filtering to the average value of Cg color data continuously calculated in the designated skin area, (PEF, Peak Expiratory Flow) and 1 second, 2 second, and 3 second forced expiratory volume (PEF)

, And forced expiratory volume). The present invention also provides a device for measuring pulmonary function using facial images, characterized in that the pulmonary function is detected by measuring the forced vital capacity (FVC) using the measured forced expiratory volume of 1 second, 2 seconds, and 3 seconds.

The lung function measuring apparatus using face images further includes a display unit, wherein the calculating unit displays the result of the lung function detection on the display unit, wherein the maximum breathing flow rate, the forced breathing rate of 1 second, 2 seconds, The forced vital capacity can be displayed numerically.

The arithmetic unit applies a MAF (Moving Average Filter) or a BPF (Band Pass Filter) to the average value of the Cg color data continuously calculated in a face image in a state where the image is maximally inspired after the maximum inspiration using a camera, It is possible to detect the average value of the color data from the peak value to the next positive peak value and to calculate the expiratory flow rate corresponding to the change in the average value of the color data to measure the maximum expiratory flow rate.

The computing device can measure the first, second, and third forced expiratory volumes corresponding to the height of the average value of the Cg color data measured at 1 second, 2 seconds, and 3 seconds based on the smallest negative peak value.

The calculating device can measure the forced lung capacity by applying the first, second, and third forced expiratory volumes calculated by the above method to the following equation (2).

The memory used the "maximum expiratory flux first regression equation" and the "maximum expiratory flow first regression equation", which show the correlation between the height of the Cg color data average value and the maximum expiratory flow rate obtained through the contact type spirometry Quot; maximum expiratory flow rate second regression analysis equation ", which indicates a correlation between the estimated maximum expiratory flow rate and the maximum expiratory flow rate obtained through the contact type spirometry device, can be stored.

The computing device searches the memory for the "maximum expiratory flow rate first regression analysis equation" and the "maximum expiratory flow rate second regression analysis equation" corresponding to the individual information (sex, etc.) The maximum estimated expiratory flow rate is measured by applying the estimated maximum expiratory flow rate to the "maximum expiratory flow rate first regression analysis equation", and the improved maximum expiratory flow rate can be measured by applying the measured estimated maximum expiratory flow rate to the "maximum expiratory flow rate second regression analysis equation" have.

According to an aspect of the present invention, there is provided a method of operating a camera, comprising: inputting personal information of a user (sex, age, height, weight, etc.) Detecting an area of interest of the user's skin in the photographed image; converting the RGB color scheme of the skin region of interest to a YCgCo color scheme; calculating a Cg color data average value (1), (2), (3), (4), (5), and (5) Calculating the 3-second forced expiratory volume and the forced vital capacity, calculating the maximum expiratory flow rate and the forced vital capacity for 1 second, 2 seconds, To provide a method of measuring lung function using a face image, comprising the step of detecting a pulmonary function.

The lung function measurement method using the facial image may further include a step of detecting the lung function and then displaying the maximum expiratory flow rate and the forced lung capacity using numerical values.

The filtering may be performed by applying a MAF (Moving Average Filter) or a BPF (Band Pass Filter) to the Cg color data average value continuously calculated in the skin region of interest to determine a color from the smallest peak value to the next positive peak value The data average value height can be detected and the exhalation flow rate corresponding to the change in the color data average value height can be calculated and measured as the maximum exhalation flow rate.

Wherein the step of calculating the forced aerobic volume and the forced vital capacity of each of the first, second, and third accelerating / 2 and the third forced expiratory volume, and the forced forced vital capacity can be calculated using the first, second, and third forced expiratory volumes.

In the step of calculating the forced vital capacity, the forced vital capacity can be calculated by applying the first, second, and third forced expiratory volumes to the equation (2).

Determining a "forced expiratory volume first regression analysis expression" indicating a correlation between the height of the Cg color data average value and the forced expiratory volume of 1 second, 2 seconds, and 3 seconds acquired through the contact type spirometry instrument; 1, 2, and 3 sec forced expiratory volume obtained by the contact type spirometry analyzer with the estimated 1, 2, And a step of storing the "forced expiratory volume first regression analysis equation" and the "forced expiratory volume second regression analysis equation" in correspondence with the user's personal information (sex, etc.) .

The step of calculating the maximum expiratory flow rate and the forced expiratory volume for 1 second, 2 seconds, and 3 seconds and the forced expiratory volume may include a "maximum expiratory flow first regression analysis equation" corresponding to the input personal information (sex, etc.) Flow rate second regression analysis equation " is determined, and the height of the Cg color data average value to which the filtering is applied is applied to the " maximum expiratory flow first regression analysis equation " The estimated maximum expiratory flow rate can be applied to the " maximum expiratory flow rate second regression analysis equation " to measure the improved maximum expiratory flow rate.

It is also possible to search for "forced forced expiratory volume first regression analysis expression" and "forced forced expiratory volume second regression analysis expression" corresponding to the inputted personal information (sex, etc.), and to set the height of the Cg color data average value, The forced forced expiratory volume can be applied to the " forced expiratory volume first regression analysis equation ", and the forced forced expiratory volume can be calculated by applying the measured forced forced expiratory volume to the " forced expiratory volume second regression analysis equation ".

According to an aspect of the present invention, there is also provided a computer-readable recording medium having recorded thereon a program for performing each step of a method for measuring pulmonary function using a facial image on a computer.

An apparatus and method for measuring lung function using a facial image according to the present invention and an effect of a computer readable recording medium on which the apparatus and method are recorded will be described below.

According to at least one of the embodiments of the present invention, the lung function can be measured in a noncontact manner and the lung function measurement is performed in consideration of the user's personal information (sex, age, height, weight, etc.) .

Also, according to at least one of the embodiments of the present invention, there is an advantage that the error of lung function measurement can be reduced through two-step regression analysis.

Further scope of applicability of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and specific examples, such as the preferred embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art.

1 is a schematic block diagram of a lung function measuring apparatus using a face image according to an embodiment of the present invention.
2 is a flowchart of a method for measuring pulmonary function using a facial image according to an embodiment of the present invention.
3 is a view for explaining a method of extracting a face image in a lung function measuring method using a face image according to an embodiment of the present invention.
FIGS. 4 to 6 are diagrams for explaining a maximum expiratory flow regression analysis DB and a method for calculating a maximum expiratory flow rate in a lung function measurement method using a facial image according to an embodiment of the present invention.
FIGS. 7 to 9 are views for explaining a forced aerobic regression analysis DB and a method for calculating forced aerobic capacity in a lung function measuring method using facial images according to an embodiment of the present invention.
FIG. 10 is a view for explaining a method of calculating a forced vital capacity using the forced aerobic volume calculated in FIG. 7 in the lung function measuring method using the facial image according to the embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals are used to designate identical or similar elements, and redundant description thereof will be omitted. The suffix " module " and " part " for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role. In the following description of the embodiments of the present invention, a detailed description of related arts will be omitted when it is determined that the gist of the embodiments disclosed herein may be blurred. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. , ≪ / RTI > equivalents, and alternatives.

Terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between. The singular expressions include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", and the like are used to specify that a feature, a number, a step, an operation, an element, a component, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

The apparatus for measuring pulmonary function using the facial image described herein may be a general PC, a tablet PC, an ultrabook, a laptop, a computer, a mobile phone, a smart phone ), A digital broadcasting terminal, a personal digital assistant (PDA), and a portable multimedia player (PMP).

1 is a schematic block diagram of a lung function measuring apparatus using a face image according to an embodiment of the present invention.

Referring to FIG. 1, an apparatus 100 for measuring lung function using a facial image according to an embodiment of the present invention may include a camera 110, a memory 120, and a computing device 130. In addition, the lung function measuring apparatus 100 using a face image may further include a display unit 140. [

The camera 110 processes image frames such as still images or moving images obtained by the image sensor and the processed image frames can be displayed on the display unit 140 or stored in the memory 120. [

The memory 120 may temporarily store data input / output from the computing device 130. [ The memory 120 may be a flash memory type, a hard disk type, a solid state disk type, an SDD type (Silicon Disk Drive type), a multimedia card micro type ), Card type memory (e.g., SD or XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read memory, a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and / or an optical disk.

Specifically, the memory 120 stores a "maximum expiratory flow rate first regression analysis expression" that indicates a correlation between a color data average value in a skin area of interest of a face image and a maximum breathing flow rate obtained through a contact type spirometry meter, Quot; maximum regression equation ", which expresses the correlation between the estimated maximum expiratory flow rate estimated by applying the first regression analysis equation and the maximum expiratory flow rate obtained through the contact type spirometry device, can be stored.

The arithmetic unit 130 detects the skin region of interest from the face image of the breathing process photographed by the camera 110. The algorithms for the computing device 130 to detect skin-of-interest regions may utilize a variety of techniques known in the art. The computing device 130 obtains a color data average value for the skin region of interest.

The arithmetic operation unit 130 may obtain the average value of the color data for the entire extracted skin area. In addition, the arithmetic unit 130 may obtain a color data average value for a specific skin area in the acquired image, and the arithmetic unit 130 obtains the color data continuously in a continuous image (continuous frame).

The arithmetic operation unit 130 detects a positive peak value and a negative peak value by applying MAF (Moving Average Filter) or BPF (Band Pass Filter) to the color data average value, and detects the next positive peak Quot; maximum flow rate regression analysis equation " retrieved from the calculation device 130 and calculate the maximum flow rate. Also, the average value of the Cg color data measured at intervals of 1 second on the basis of the smallest peak value is applied to the " forced aerobic volume regression equation " retrieved from the computing device 130 to calculate the first, second, Can be calculated. At this time, the computing device 130 searches the memory 120 for a regression analysis expression corresponding to personal information (sex, etc.) to the user. As described above, the forced vital capacity can be calculated by applying the first, second, and third forced expiratory volumes to the above equation (2). Here, FVC represents the forced vital capacity, and FEV ₁ , FEV ₂ , and FEV ₃ represent the first, second, and third forced breath volumes.

The calculating device 130 may calculate the maximum expiratory flow rate and the forced vital capacity by comparing the regression analysis equation and the filtered height value of the Cg color data average value, and may detect the pulmonary function using the maximum expiratory flow rate and the forced vital capacity.

Specifically, the computing device 130 searches the memory 120 for a first regression analysis equation and a second regression analysis equation corresponding to the user's personal information (sex, etc.). The arithmetic unit 130 then applies the height value of the filtered average value of the Cg color data to the " maximum expiratory flow first regression analysis equation " retrieved from the arithmetic unit 130 to estimate the maximum expiratory flow rate, Can be applied to the " maximum expiratory flow rate second regression analysis equation " to measure the improved maximum expiratory flow rate.

When the lung function detection is completed, the calculation device 130 can display the lung function detection result on the display unit 140. [ Specifically, the computing device 130 can display the maximum expiratory flow rate and the forced vital capacity by numerical values.

The display unit 140 displays information processed by the lung function measurement apparatus 100 using the face image. For example, it is possible to display execution screen information of an application program driven by the apparatus 100 for measuring lung function using a face image, or UI (User Interface) and GUI (Graphic User Interface) information according to the execution screen information .

2 is a flowchart of a method for measuring pulmonary function using a facial image according to an embodiment of the present invention.

Referring to FIG. 2, a method of measuring a lung function using a facial image according to an embodiment of the present invention inputs user's personal information (sex, age, height, weight, etc.) (S210) In S220, the source image is extracted as much as possible. The source image includes a skin area of the user. The computer device detects a skin region in the source image captured by the camera (S230).

The computer device calculates a color data average value for the skin area of interest (S240). The computer device may obtain the average value of the color data for the entire extracted skin area. In addition, the computer device may obtain an average of color data for a specific skin region in the acquired image.

The computer device detects a positive peak value and a negative peak value by applying MAF (Moving Average Filter) or BPF (Band Pass Filter) to the average value of color data (S250), and detects the next positive peak The difference between the values can be used to calculate the maximum expiratory flow rate. Also, the first, second, and third forced expiratory volumes can be calculated using the average value of Cg color data measured at intervals of 1 second based on the smallest peak value. In addition, the forced vital capacity can be measured using the calculated first, second, and third forced expiratory volumes (S260).

The computer device may display the calculated forced expiratory volume, forced expiratory volume, and maximum expiratory flow rate at 1 second, 2 seconds, and 3 seconds (S270). Also, the computer device can calculate the spirometric capacity which is a standard of the normal person by applying the personal information (age, height, weight, etc.) of the inputted user to [Equation 3]. The difference between the compulsory spontaneous volume calculated from the face image and the normal standard forced spontaneous volume calculated from the user's personal information can be provided to provide the difference information (S280).

Specifically, the method of measuring the lung function using the face image may input the user's personal information (age, sex, height, weight, etc.) (S210). Next, the breathing process image of the user can be photographed through the camera (S220). When the user's breathing process image capturing is completed, the skin region of interest is detected in the captured image (S230), the RGB color scheme of the skin region of interest is converted into the YCgCo color scheme, and the average of the Cg color data is continuously calculated (S240 ). At this time, positive peak value and negative peak value are detected by applying MAF (Moving Average Filter) or BPF (Band Pass Filter) to the average value of Cg color data (S250), and the next positive peak It is possible to calculate the exhalation flow rate corresponding to the difference value of the value as the maximum exhalation flow rate. Also, the first, second, and third forced expiratory volumes corresponding to the average Cg color data measured at intervals of 1 second based on the smallest peak value can be calculated. As described above, the forced vital capacity can be calculated by applying the first, second, and third forced expiratory volumes to the equation (2) (S260). In addition, the maximum expiratory flow rate and the forced expiratory volume for 1 second, 2 seconds, and 3 seconds and the forced vital capacity can be displayed on the display unit (S270).

(Age, height, weight, etc.) of the inputted user can be applied to [Equation 3] to calculate the spirometric capacity which is a standard of a normal person. The difference between the estimated forced vital capacity estimated from the facial image and the normal standard forced vital capacity estimated from the user's personal information may be compared to provide the difference information (S280).

The method of calculating the maximum expiratory flow rate and the forced vital capacity includes searching the first regression analysis equation and the second regression analysis equation corresponding to the inputted personal information (sex, etc.), and then changing the height variation of the filtered average value of the Cg color data The estimated maximum expiratory flow rate or forced expiratory volume for 1 second, 2 seconds, 3 seconds, or forced expiratory volume was estimated by applying the regression equation to the maximum expiratory flow rate, 1 second, 2 seconds, 3 seconds forced expiration volume, The regression equation can be used to calculate the improved maximum expiratory flow rate or forced expiratory volume for 1 second, 2 seconds, 3 seconds, or forced expiratory volume. A method of ultimately measuring the maximum expiratory flow rate, the forced expiratory volume for one second, two seconds, and three seconds, and the forced vital capacity by calculating the first regression analysis equation and the second regression analysis equation will be described in detail with reference to FIGS. 4 through 10 .

3 is a diagram for explaining a method of extracting a face image in a lung function measuring method using a face image according to an embodiment of the present invention.

Referring to FIG. 3, the breathing process of a user can be photographed using a lung function measuring device using a face image on which a camera is mounted. Particularly, a lung function measuring apparatus using a face image (hereinafter, referred to as a lung function measuring apparatus) can take a face image of a maximum inspiration and a maximum breath during a user's breathing process.

The lung function measuring device can extract the entire skin area F from the user's face image IM and extract the skin area of interest Fa from the entire skin area F. [ The lung function measuring apparatus may obtain an average value of color data for the extracted skin region, and the lung function measuring apparatus may obtain an average value of color data for a specific skin region in the acquired image.

The RGB color scheme of the skin region of interest Fa may be converted to the YCgCo color scheme and the average value of the Cg color data continuously calculated in the skin region of interest Fa may be used for pulmonary function detection.

FIGS. 4 to 6 are diagrams for explaining a method of calculating a maximum expiratory flow rate in a lung function measuring method using a facial image according to an embodiment of the present invention. FIGS. 7 to 10 are views FIG. 5 is a diagram illustrating a method for calculating forced expiratory volume and forced vital capacity for 1 second, 2 seconds, and 3 seconds in a lung function measurement method using an image.

Referring to FIG. 4, the pulmonary function measuring device measures MAF (Moving Average Filter) or BPF (Band Pass) on the average value of the Cg color data of the skin region of interest Fa detected in a face image, Filter) can be applied to calculate the smallest peak value and the next largest detected peak value (A, B).

Specifically, the lung function measuring device may display data filtered by applying MAF or BPF to the average value of Cg color data continuously calculated in the skin area of interest Fa by the graph (CH) during the user's breathing process . The lung function measuring device calculates the difference value H between the smallest peak value A and the next detected positive peak value B and outputs the calculated difference value H to the & Regression equation "to estimate the maximum expiratory flow rate. Next, the lung function measuring device can finally measure the improved maximum expiratory flow rate by applying the estimated maximum expiratory flow rate to the " maximum expiratory flow rate second regression analysis equation ".

Referring to FIG. 5, the lung function measuring device measures the maximum expiratory flow rate (C) of the data (R) that measures the flow rate of the breathing process using the contact type diagnostic lung function measuring device and the difference The regression analysis is applied to the value (H) to derive the "maximum expiratory flux first regression equation" and store it in the "maximum expiratory flow first regression analysis DB".

The difference value (H) between the smallest peak value (A) and the next detected positive peak value (B) corresponds to the maximum expiratory flow rate when the contact type diagnostic lung function measuring device is used. A regression line (or curve) equation can be calculated. The regression equation expresses the relationship between two variables by representing a point set on the correlation chart as a straight line or a curve.

The pulmonary function measuring device can display the data graph (CH) filtered by applying MAF or BPF to the average value of the Cg color data of the skin region of interest Fa detected in the face image which is maximally consecutive after breathing as much as possible . The lung function measuring device calculates the difference value H between the smallest peak value A and the next detected peak value B and calculates the difference value H between the calculated difference value H and the contact type diagnostic lung function measurement The maximum expiratory flow rate can be estimated by comparing the maximum expiratory flow rate (C) of the data (R) which measures the flow rate of the breathing process using the apparatus.

Referring to FIG. 6, the lung function measuring device may display a data graph (CH) filtered by applying MAF or BPF to the average value of Cg color data of the skin area of interest Fa. The lung function measuring device calculates the difference value H between the smallest peak value A and the next detected positive peak value B and outputs the calculated difference value H to the & Regression equation "to estimate the maximum expiratory flow rate. The regression analysis was applied to the maximum expiratory flow rate estimated from the facial image and the maximum expiratory flow rate (C) of the data (R) obtained by measuring the flow rate of the breathing process using the contact type diagnostic lung function measuring device, Regression analysis equation ". Here, the " maximum expiratory flow rate second regression analysis equation " is an improvement of the error by comparing the estimated maximum expiratory flow rate with the actual maximum expiratory flow rate database.

The lung function measuring device can finally estimate the improved maximum expiratory flow rate by applying the estimated maximum expiratory flow rate to the " maximum expiratory flow rate second regression equation ".

Referring to FIG. 7, the computer device applies MAF or BPF to the average value of Cg color data of the skin region of interest Fa detected in a face image which is maximally consecutive after breathing to the maximum extent, and then filters the positive and negative peaks Value. The difference values (h1, h2) of the first, second and third color data corresponding to the average value of the Cg color data measured at intervals of (t1, t2, t3) at intervals of 1 second on the basis of the smallest peak value , h3) can be detected (CH ').

Specifically, the pulmonary function measuring apparatus measures color data h1 at a time point t1 when one second elapses from the smallest peak value (A), h2 color data at a time point t2 after two seconds have elapsed, h3 And calculate the first, second, and third forced expiratory volumes by applying the calculated h1, h2, and h3 to the "forced expiratory volume first regression analysis equation". Next, the lung function measuring device can apply the estimated first, second and third forced expiratory volumes to the " forced expiratory volume second regression equation " to finally measure the improved first, second, and third forced expiratory volume have.

의 높이값(h1, h2, h3)과 얼굴 영상의 피부 관심 영역에서 계산된 h1, h2, h3 각 각에 회귀 분석을 적용하여 “강제 호기량 제1 회귀 분석식”을 도출한다. Referring to FIG. 8, the lung function measuring device is a device for measuring the first, second, and third forced expiratory volume of the breathing process using the contact type diagnostic lung function measuring device (R ')

(H1, h2, h3) of the facial image and the h1, h2, h3 calculated in the skin area of interest of the face image by using regression analysis.

When using the contact type diagnostic lung function measurement device with h1, h2, h3 at 1 second, 2 seconds, and 3 seconds (t1, t2, t3) from the point where the smallest negative peak value is obtained in the filtered Cg color data (H1, h2, h3) of the forced expiratory volume (FEV ₁ , FEV ₂ , FEV ₃ ) of 1 second, 2 seconds and 3 seconds can be calculated.

 The regression equation expresses the relationship between two variables by representing a point set on the correlation chart as a straight line or a curve.

The lung function measuring device filters MAF or BPF by applying the average value of the Cg color data of the skin region of interest Fa detected in the face image which maximally expires after drinking the breath to the maximum and then detects positive and negative peak values do. The first, second and third color data h1, h2 and h3 corresponding to the average value of the Cg color data measured at intervals of 1 second (t1, t2 and t3) on the basis of the smallest peak value (A) (CH ').

The lung function measuring device can estimate the first, second, and third forced expiratory volumes (FEV ₁ , FEV ₂ , FEV ₃ ) by applying the detected h1, h2, h3 to the "forced expiratory volume first regression analysis equation" .

Referring to FIG. 9, the pulmonary function measuring device measures the skin area of interest Fa

의 높이값에 회귀 분석을 적용하여 “강제 호기량 제2 회귀 분석식”을 도출할 수 있다. 여기서, “강제 호기량 제2 회귀 분석식”은 추정 강제 호기량과 실제 강제 호기량 데이터베이스를 비교하여 오차를 개선한 것이다. Cg The data graph (CH ') filtered by applying MAF or BPF to the average value of color data can be displayed. The lung function measuring apparatus calculates the difference value H between the smallest peak value A and the next detected positive peak value B and outputs the calculated difference value H as " Analytical equations "to estimate the forced expiratory volume for 1 second, 2 seconds, and 3 seconds. The data of the first, second, and third forced expiratory volume (R ') of the respiratory process were measured using the forced air volume for 1 second,

The second regression equation for forced expiratory volume can be derived by applying a regression analysis to the height value of the forced expiratory volume. Here, the "forced expiratory volume second regression analysis formula" is an improvement of the error by comparing the estimated forced expiratory volume with the actual forced expiratory volume database.

The lung function measuring device can finally estimate the forced forced expiratory volume by applying the estimated forced expiratory volume to the " forced expiratory volume second regression analysis equation ".

의 높이값에 회귀 분석을 적용하여 “강제 호기량 제2 회귀 분석식”을 도출할 수 있다. 여기서, “강제 호기량 제2 회귀 분석식”은 추정 강제 호기량과 실제 강제 호기량 데이터베이스를 비교하여 오차를 개선한 것이다.Referring to FIG. 10, the lung function measuring apparatus may display a data graph (CH ') filtered by applying MAF or BPF to the average value of Cg color data of the skin region of interest Fa. The lung function measuring apparatus calculates the difference value H between the smallest peak value A and the next detected positive peak value B and outputs the calculated difference value H as " Analytical equations "to estimate the forced expiratory volume for 1 second, 2 seconds, and 3 seconds. The data of the first, second, and third forced expiratory volume (R ') of the respiratory process were measured using the forced air volume for 1 second,

The second regression equation for forced expiratory volume can be derived by applying a regression analysis to the height value of the forced expiratory volume. Here, the "forced expiratory volume second regression analysis formula" is an improvement of the error by comparing the estimated forced expiratory volume with the actual forced expiratory volume database.

The lung function measuring device can finally estimate the forced forced expiratory volume by applying the estimated forced expiratory volume to the " forced expiratory volume second regression analysis equation ".

Also, the lung function measuring device applies FVC (FEV ₁ , FEV ₂ , and FEV ₃ ), which are the first, second, and third forced breath volumes measured from the facial image, Can be measured.

The first and second regression analysis equations can be represented by a linear equation as shown in [Table 1] and [Table 2], or as a quadratic equation as shown in [Table 2] and [Table 3]. (There may be some differences depending on DB used in 1st and 2nd equation below.)

division gender Regression straight  expression

male

female

male

female

male

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male

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division gender Regression straight  expression

male

female

male

female

male

female

male

female

division gender Regression curve equation

male

female

male

female

male

female

male

female

division gender Regression curve equation

male

female

male

female

male

female

male

female

According to the present invention, lung function can be measured in a non-contact manner, and lung function measurement can be performed in consideration of individual differences, thereby improving accuracy.

In addition, the lung function measuring device can calculate the forced vital capacity to be a standard of a normal person by applying the inputted user's personal information (age, height, weight, etc.) to [Equation 3]. The forced vital capacity estimated from the color data average value of the facial image can be compared with the standard forced vital capacity of the normal person calculated from the user's personal information and the difference information can be provided to the user.

According to another aspect of the present invention, there is provided a computer readable recording medium having recorded thereon a computer program for performing each step of a lung function measurement method using a facial image.

The present invention described above can be embodied as computer-readable codes on a medium on which a program is recorded. The computer readable medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of the computer readable medium include a hard disk drive (HDD), a solid state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, . The computer may also include a computing device 130 of the terminal. Accordingly, the above description should not be construed in a limiting sense in all respects and should be considered illustrative. The scope of the present invention should be determined by rational interpretation of the appended claims, and all changes within the scope of equivalents of the present invention are included in the scope of the present invention.

100: Pulmonary function measuring device using face image
110: camera 120: memory
130: computing device 140:

Claims (14)

camera;
Memory; And
The method includes the steps of: receiving personal information including a user's gender; photographing a breathing process of the user through the camera; extracting a skin region of interest from the photographed face image; And an arithmetic unit for detecting the arithmetic operation unit,
Wherein the computing device searches the memory for a regression equation corresponding to the gender, converts the RGB color scheme of the skin region of interest into a specified color scheme, and filters the continuously calculated color data average value to obtain a positive peak value And the difference value of the next positive peak value at the smallest negative peak value is compared with the above-mentioned regression equation to determine the maximum expiratory flow rate, 1 second, 2 seconds, 3 second forced expiratory volume, forced vital capacity And a lung function measurement device using facial images characterized by the maximum expiratory flow rate, the forced expiratory volume for 1 second, 2 seconds, and 3 seconds, and the forced lung volume detection.
The method according to claim 1,
And a display unit,
Wherein the calculation device displays the result of the lung function detection on the display unit and displays the maximum breathing flow rate and the forced breathing volume for 1 second, 2 seconds, 3 seconds, and numerical values of the forced breathing volume. Used lung function measuring device.
The method according to claim 1,
The arithmetic unit detects a positive peak value and a negative peak value by applying MAF (Moving Average Filter) or BPF (Band Pass Filter) to the average value of the color data, and detects the next positive peak Calculating a breathing rate corresponding to a difference value of the breathing rate, and measuring the breathing rate using the face image.
The method of claim 3,
The calculation device calculates first, second, and third forced expiratory volumes corresponding to the color data measured at intervals of one second based on the smallest negative peak value, and calculates the first, second, and third And the forced lung capacity is calculated using the forced expiratory volume.
5. The method of claim 4,
Wherein the calculating device calculates the forced lung capacity by applying the first, second, and third forced expiratory volumes to the following equation.

(Where FVC represents the forced vital capacity, and FEV ₁ , FEV ₂ , and FEV ₃ represent the first, second, and third forced aerobic volumes)
The method according to claim 1,
Wherein the calculating device includes a first maximum regression equation expressing a correlation between a change in the height of the filtered color data average value and a maximum expiratory flow rate obtained through the contact type spirometry analyzer, and a maximum regression equation Calculating a maximum expiratory flow rate second regression equation expressing a correlation between an estimated maximum expiratory flow rate and a maximum expiratory flow rate acquired through the contact type spirometry analyzer, and storing the calculated regression analysis equation in the memory A device for measuring pulmonary function using facial images.
The method according to claim 6,
Wherein the computing device searches the memory for a first regression analysis equation and a second regression analysis equation corresponding to the input gender and applies a height value of the filtered color data average value to the first regression analysis equation Measuring the maximum expiratory flow rate, and applying the measured estimated maximum expiratory flow rate to the second regression analysis equation to measure the maximum expiratory flow rate.
Inputting personal information including a sex of a user;
Capturing a user's breathing process image through a camera;
Extracting a skin region of interest from the photographed face image;
Converting the RGB color scheme of the skin region of interest into a specified color scheme and filtering the calculated color data;
A regression analysis equation corresponding to the input gender is retrieved from the memory and the difference value of the filtered color data average value is applied to a regression analysis equation to calculate the maximum expiratory flow rate and the forced expiratory volume for 1 second, Calculating; And
Detecting pulmonary function using the maximum expiratory flow rate, the forced expiratory volume for 1 second, 2 seconds, and 3 seconds, and the forced vital capacity;
A method for measuring pulmonary function using a facial image.
9. The method of claim 8,
After the step of detecting the lung function,
And displaying the maximum expiratory flow rate and the forced expiratory volume for 1 second, 2 seconds, and 3 seconds and the forced vital capacity by numerical values.
9. The method of claim 8,
The filtering may include detecting a positive peak value and a negative peak value by applying a MAF (Moving Average Filter) or a BPF (Band Pass Filter) to an average of color data continuously calculated in the skin region of interest, Calculating a breathing flow rate corresponding to a difference value of a next positive peak value at a negative peak value and measuring the breathing flow rate at the maximum breathing flow rate.
11. The method of claim 10,
Wherein the step of calculating the forced vital capacity includes calculating first, second, and third forced expiratory volumes corresponding to the average of the color data measured at intervals of one second based on the smallest negative peak value, Wherein the forced lung capacity is calculated by applying the second and third forced expiratory volumes to the following equations.

(Where FVC represents the forced vital capacity, and FEV ₁ , FEV ₂ , and FEV ₃ represent the first, second, and third forced aerobic volumes)
9. The method of claim 8,
Filtering the color data; and calculating the maximum expiratory flow rate and the one second, two second, three second forced aerobic volume and mandatory vital capacity,
Determining a first regression equation expressing a correlation between a change in the height of the color data average value and a maximum expiratory flow rate obtained through the contact type spirometer;
Calculating a second regression equation expressing a correlation between the estimated maximum expiratory flow rate estimated by applying the first regression analysis equation and the maximum expiratory flow rate acquired through the contact type spirometry analyzer; And
Storing the first regression analysis equation and the second regression analysis equation in correspondence with personal information including a sex of a user;
Wherein the lung function measurement is performed using the face image.
13. The method of claim 12,
Wherein the calculating the maximum expiratory flow rate comprises:
A first regression analysis equation and a second regression analysis equation corresponding to the input gender are searched for and a moving average filter (MAF) or a band pass filter (BPF) is applied to the filtered color data average value to calculate a positive peak value And a difference value of the next positive peak value at the smallest negative peak value is applied to the first regression analysis equation to measure the estimated maximum expiratory flow rate, Wherein the method is applied to a second regression analysis equation to measure a maximum expiratory flow rate.
A computer-readable recording medium having recorded thereon a computer program for performing each step of a lung function measurement method using a face image according to any one of claims 8 to 13 on a computer.

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