KR101787828B1 - Heartrate measuring system using skin color filter - Google Patents

Heartrate measuring system using skin color filter Download PDF

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KR101787828B1
KR101787828B1 KR1020150124988A KR20150124988A KR101787828B1 KR 101787828 B1 KR101787828 B1 KR 101787828B1 KR 1020150124988 A KR1020150124988 A KR 1020150124988A KR 20150124988 A KR20150124988 A KR 20150124988A KR 101787828 B1 KR101787828 B1 KR 101787828B1
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value
peak value
unit
heart rate
skin color
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KR20170028113A (en
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황만원
민병수
김용석
김동욱
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주식회사 제론헬스케어
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0062—Arrangements for scanning
    • A61B5/0064—Body surface scanning
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0077—Devices for viewing the surface of the body, e.g. camera, magnifying lens
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2503/00—Evaluating a particular growth phase or type of persons or animals
    • A61B2503/04—Babies, e.g. for SIDS detection
    • A61B2503/045—Newborns, e.g. premature baby monitoring

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  • Life Sciences & Earth Sciences (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Molecular Biology (AREA)
  • Physics & Mathematics (AREA)
  • Biophysics (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Cardiology (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Physiology (AREA)
  • Measuring Pulse, Heart Rate, Blood Pressure Or Blood Flow (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

According to the present invention, an image obtaining unit 110 for obtaining image data of a newborn baby photographed; The entire image of the image data filtered on the basis of the general skin color band is divided into blocks of a predetermined size and subjected to frequency conversion to select a plurality of blocks having a relatively high frequency component, A skin color band generating unit 120 for generating a skin color band having a lower limit value as a band range; An image filtering unit 130 for filtering the image data obtained on the basis of the generated skin color band and extracting a face skin region for heart rate extraction; A BVP data extracting unit 140 for extracting BVP data (Blood Volume Pulse Data) that changes per unit time using pixel values of the extracted face skin region; And a heart rate calculator 150 for calculating a heart rate using the extracted BVP data.

Description

{HEARTRATE MEASURING SYSTEM USING SKIN COLOR FILTER}

The present invention relates to a heart rate measuring system using a skin color filter, and more particularly, to a heart rate measuring system for measuring a heart rate by detecting a change in a pixel value of a face region through image analysis of image data of a newborn baby .

Conventionally, in order to measure the heart rate, it was possible to calculate the heart rate through the pulse sensed after placing the sensor at the pulse area. However, the method of measuring the heart rate using the sensor was limited to the newborn having a small body.

There was an attempt to measure the heart rate indirectly by sensing the minute movement of the head or the body part of the newborn during heartbeat by image analysis of the image data of the newborn baby. However, since there is an error in the measurement data, .

In recent years, in order to solve such a problem, a method of measuring the heart rate by indirectly measuring the change of the pixel value of the face region by analyzing the image data of the newborn baby using the feature that the face color of the newborn baby changes minutely during heartbeat Is used.

The heart rate measurement through this image analysis is measured through the average change of the skin pixels of the face, but the fluctuation is very small, so that it is greatly affected by the fine noise.

Generally, video images obtained from a camera or a CCTV are transmitted in a compressed state, so that video loss due to compression is inevitable. However, such a video loss is more likely to occur in a region where the change is severe.

The areas where the change in the face area of the newborn baby is severe include eyes, nose, mouth, ear, and jaw. When the area is included in the detection target area for detecting a change in the pixel value, information loss due to compression There is a problem that the measured value greatly fluctuates even in a small motion such as a change in the facial expression and acts as noise in the measurement of the heart rate.

Japanese Patent Application Laid-Open No. 10-2015-0093036 (2015.08.17), a biometric information measuring apparatus and a measuring method

SUMMARY OF THE INVENTION The present invention has been made in order to solve the above-mentioned problems, and an object of the present invention is to provide a method and apparatus for eliminating areas where facial expressions and movement changes frequently, such as eyes, nose, mouth, The present invention is to provide a heart rate measuring system that can measure a heart rate more precisely by minimizing a measurement error of a heart rate by applying a skin color filter.

According to an aspect of the present invention, there is provided a heart rate measuring system comprising: an image acquiring unit (110) for acquiring image data of a newborn baby; The entire image of the image data filtered on the basis of the general skin color band is divided into blocks of a predetermined size and subjected to frequency conversion to select a plurality of blocks having a relatively high frequency component, A skin color band generating unit 120 for generating a skin color band having a lower limit value as a band range; An image filtering unit 130 for filtering the image data obtained on the basis of the generated skin color band and extracting a face skin region for heart rate extraction; A BVP data extracting unit 140 for extracting BVP data (Blood Volume Pulse Data) that changes per unit time using pixel values of the extracted face skin region; And a heart rate calculator 150 for calculating a heart rate using the extracted BVP data.

The skin color band generating unit 120 includes an image dividing unit 121 dividing an entire image of the filtered image data into blocks having the same size as a compression block of the video compression format, A frequency transform unit 123 for frequency-transforming the image of the extracted block, and a frequency comparator 123 for comparing the frequencies of the extracted blocks and extracting the upper limit value and the lower limit value And a band setting unit 124 that sets the extracted upper limit value and the lower limit value to the band range of the skin color band based on the extracted upper limit value and the lower limit value.

In addition, the block extracting unit 122 detects the face position in the entire block based on the feature points on the face of the newborn baby, sets the face background area based on the detected face position, It is possible to select the block corresponding to the face area.

The heart rate calculator 150 includes a peak value candidate extractor 151 for extracting a peak value candidate using the slope value on the extracted BVP data and a subwindow having a predetermined width on the time axis, A peak value selection unit 152 for selecting a peak value candidate having a maximum size within each subwindow in a value candidate position and a peak value selection unit 152 for measuring a time interval value of each peak value, A weighted average value calculator 153 for calculating a weighted average value of the time interval values by reflecting the weighted values in the middle values of the respective time interval values, and a weighted average value calculator 153 for calculating the calculated weighted average value by a heart rate cycle, And a heart rate conversion unit 154 for calculating the heart rate.

In addition, the peak value candidate extractor 151 may extract a position having a slope value of '0' on the variation curve of the BVP data as a peak value candidate.

In addition, the peak value candidate extracting unit 151 may exclude a slope value whose slope value is '0' on the change curve of the BVP data, and whose slope does not change from + to -, from the peak value candidate.

The peak value selection unit 152 may set a predetermined width of the sub window in consideration of the average heartbeat period of a typical newborn baby.

The peak value selection unit 152 arranges the center of the subwindow having the minimum size at the position of each peak value so that a single peak value candidate exists in the subwindow or a larger value And the peak value selection process is repeated a predetermined number of times while gradually increasing the width on the time axis of the sub window to determine the optimum width on the time axis of the sub window And a subwindow with the smallest deviation of the time interval value can be designated as an application target and reflected in the peak value selection.

The peak value selection unit 152 sets the width on the time axis of the sub window having the minimum size to reflect the minimum value of the average heart rate cycle category, The peak value can be selected while gradually increasing the width of one sub-window.

In addition, the weighted average value calculator 153 lowers the reflection ratio of the time interval value having a relatively large or low value using the Gaussian normal distribution curve in a state in which the peak values are sorted in order of magnitude, The weighted average value can be calculated by raising the reflection ratio of the data value.

According to the heart rate measuring system of the present invention,

First, the measurement error is caused by applying a skin color filter to exclude areas with frequent facial expressions and motion changes such as eyes, nose, mouth, ear, and jaw in the face region of acquired neonatal image data from the pixel value change detection region More precise heart rate measurement can be performed by sensing the change of the pixel value only in the region where the possibility is relatively low.

Second, in dividing an entire image into blocks to generate skin color bands, macroblocks, which are video compression units, are normally normalized for each block, so that a deviation occurs between blocks, and a change in pixel value However, it is possible to minimize the error in judging whether there is a block (eye, nose, mouth, ear, jaw or the like) in which the change is severe by uniformly including the block boundary by dividing the block into blocks of the same size as the video compression format have.

Third, the heart rate is calculated using the pixel values of the facial skin measured through the image analysis of the image data of the newborn baby. The candidates of the peak value for determining the heart rate are selected by applying the sub window, and the time interval The error of the measured heart rate can be minimized by reflecting the weight to the value.

1 is a block diagram illustrating a functional configuration of a heart rate measuring system according to a preferred embodiment of the present invention.
FIG. 2 is a schematic view showing a configuration in which an image acquiring unit according to a preferred embodiment of the present invention is installed in a neonate bed;
FIGS. 3 to 5 are diagrams for explaining the principle of operation of the heart rate measuring system according to the preferred embodiment of the present invention. FIG.
FIG. 6 is a photograph showing a state of a newborn in the image acquiring unit according to a preferred embodiment of the present invention,
FIGS. 7 and 8 are graphs for explaining the operation principle of the heart rate calculation unit according to the preferred embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, terms and words used in the present specification and claims should not be construed as limited to ordinary or dictionary terms, and the inventor should appropriately interpret the concepts of the terms appropriately The present invention should be construed in accordance with the meaning and concept consistent with the technical idea of the present invention.

Therefore, the embodiments described in this specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention and do not represent all the technical ideas of the present invention. Therefore, It is to be understood that equivalents and modifications are possible.

The heart rate measuring system 100 according to the preferred embodiment of the present invention includes a skin color filter for excluding a region where face and motion changes frequently such as eyes, nose, mouth, ear and jaw parts in the face region of neonatal baby image data are excluded 1, a skin color band generating unit 120, a skin color band generating unit 130, a skin color band generating unit 130, A BVP data extracting unit 140, and a heart rate calculating unit 150. [

First, the image acquiring unit 110 may be a conventional imaging apparatus such as an analog camera, a CCTV, and an IP camera as imaging means for acquiring image data of a newborn baby, Is used as the basic data for detecting.

Here, as shown in FIG. 1, it is mounted on one side of a newborn bed 10 accommodating a newborn baby. The newborn baby bed 10 is installed on the side of the newborn bed 10 through a cradle for stably photographing the newborn baby, Or may be mounted on the side wall of the newborn bed 10 through the bracket or integrally mounted on the newborn bed 10. [

In addition, when the system is operated in a neonatal room where a large number of newborn babies are densely arranged, such as an anus part and a postpartum care unit, each image acquisition unit 110 is installed so as to match 1: 1 for each newborn bed 10, So that an independent image can be secured.

The skin color band generation unit 120 generates skin color bands having a specific band range so that only a stable skin region can be selected in the face region of a newborn baby. As shown in FIG. 2, 130 divides the entire image of the image data filtered based on the general skin color band into blocks each having a predetermined size and performs frequency conversion to select a plurality of blocks having a relatively high frequency component, And generates a skin color band having an upper limit value and a lower limit frequency as a band range.

Here, when a high frequency component of values obtained by frequency-transforming an image through a Fast Fourier Transform (FFT) or a Discrete Cosine Transform (DCT) in block units is large, it means that there are many changes with a short period in the spatial domain. This indicates that the change is complicated and large, and the change of the pixel value occurs in such a region even with small movement or trembling. Based heartbeat measurement in which the variation of the mean ± 0.2 pixel value in the period of the information of 0.9 Hz to 2 Hz in the time domain must be measured.

More specifically, the skin color band generating unit 120 includes an image dividing unit 121 dividing the entire image of the filtered image data into blocks having the same size as the compression block of the video compression format, A block extracting unit 122 for extracting a block corresponding to the face region of the newborn baby (indicated by a red line in FIG. 4), a frequency transforming unit 123 for frequency-transforming the image of the extracted block, And a band setting unit 124 that extracts the upper and lower limits of the frequencies, and sets the band color of the skin color band based on the extracted upper and lower limit values.

Here, in dividing the entire image into blocks in order to generate skin color bands, macroblocks, which are video compression units, are normally normalized for each block, so that a deviation occurs between blocks, and a change in pixel value However, it is possible to minimize the error in judging whether there is a block (eye, nose, mouth, ear, jaw or the like) in which the change is severe by uniformly including the block boundary by dividing the block into blocks of the same size as the video compression format have.

4 and 6, the block extracting unit 122 detects the face position in the entire block on the basis of the feature points on the face of the newborn baby, and based on the detected face position, The face region is tracked and only blocks corresponding to the tracked face region can be selected.

The image filter unit 130 primarily filters the image data acquired by the image acquisition unit 110 on the basis of a general skin color band so as to acquire a skin color band for selecting a block of a stable skin area , And extracts a face skin area for heart rate extraction by re-filtering the obtained image data based on the skin color band finally generated through the skin color band generating unit 120. [

FIG. 3 illustrates an image in which image data is primarily filtered by applying a general skin color band by the image filter unit 130. Referring to FIG. 3, when image data obtained by a general skin color band having a relatively wide color band is filtered, all areas similar to skin color are detected.

Here, a general color filter defines a range of values for each channel (R, G, B), and a commonly used skin color filter has a wide band for each channel so as to cover all the skin colors of various people and various parts.

FIG. 5 shows an image in which image data is finally filtered by applying the skin color band generated by the image filter unit 130. FIG. As shown in FIG. 5, a skin color filter is used to exclude an area in which face and motion changes frequently, such as eyes, nose, mouth, ear, and jaw, in the face region of the acquired neonatal image data, It is possible to measure the heart rate more precisely by detecting the change of the pixel value only in the region where the possibility of measurement error is relatively low. In other words, it is possible to automatically extract only the face pixel information of a stable region, which is highly varied and complex.

That is, if the color filter bands are defined by determining the maximum and minimum values for each channel based on the pixel values of the stable face region such as the balls and forehead except for the unstable regions such as eyes, nose, mouth, ear and jaw in the entire face region of the newborn, It is possible to generate a skin color filter specialized for the face ball and the forehead. By applying the skin color filter thus generated to only the face region of the newborn baby, only the pixels of the stable region such as the ball and the forehead can be obtained, and only the change of the skin pixel value due to the heartbeat over time can be clearly seen.

6 and 7, the BVP data extracting unit 140 extracts BVP data (an upper curve graph in FIG. 7) varying per unit time using the extracted pixel values of the facial skin region And the heart rate calculator 150 calculates the heart rate using the extracted BVP data.

Here, the BVP data extracting unit 140 preferably eliminates the high-frequency components included in the data value using a bandpass filter so that an error according to the noise data does not occur.

2, the heart rate calculation unit 150 includes a peak value candidate extraction unit 151, a peak value selection unit 152, a weighted average value calculation unit 153, and a heart rate conversion unit 154).

The peak value candidate extracting unit 151 extracts a peak value candidate using the slope value on the extracted BVP data, and the peak value selecting unit 152 selects a subwindow having a predetermined width on the time axis as a peak value And a peak value candidate having a maximum size within each subwindow is selected as a peak value.

Here, a position having a slope value of '0' on the variation curve of the BVP data is extracted as a peak value candidate. At this time, a slope value that is '0' on the variation curve of the BVP data and whose slope does not change from + to - is excluded from the peak value candidate.

In addition, the peak value selection unit 152 preferably sets a predetermined width of the sub-window in consideration of the average heartbeat period of a typical newborn baby.

In addition, the center of a subwindow having a minimum size is arranged at a position of each peak value, and a corresponding peak value candidate having a single peak value candidate in the subwindow or having a larger value than another peak value candidate is set as a peak value And then the peak value selection process is repeated a predetermined number of times while gradually increasing the width on the time axis of the sub window.

That is, the width of the sub-window is gradually widened and the deviation of the values of the time intervals is compared. Through this procedure, the peak value detection is repeated to determine the optimum sub-window width. Specify the window to be applied and reflect it to the peak value selection.

The peak value selection unit 152 sets the width on the time axis of the subwindow having the minimum size to reflect the minimum value of the average heart rate cycle category, The peak value is selected while gradually increasing the width of the sub-window.

For example, when the average heartbeat period category of the newborn infants is 100 / s to 150 / s, the width on the time axis of the minimum size of the sub window is set to 100 / s, The line width can be set to 150 / s.

The weighted average value calculator 153 measures a time interval value of each peak value, sorts the measured time interval value in order of magnitude, reflects a weight to an intermediate value of each time interval value, and calculates a weighted average value of the time interval value And the heart rate conversion unit 154 designates the calculated weighted average value as a heart rate cycle, and converts the calculated weighted average value into a time unit to calculate a heart rate.

Here, in a state in which each peak value is sorted in order of magnitude, a reflection ratio of a time interval value having a relatively large value or a relatively low value is decreased using the Gaussian normal distribution curve, and the reflection ratio of the intermediate data value or the average value is increased The weighted average value is calculated.

More specifically, a peak value candidate is extracted using the slope value on the extracted BVP data, and a subwindow having a predetermined width on the time axis (a? -Shaped display portion in FIG. 7) is arranged at each peak value candidate position A peak value candidate having a maximum size in each sub window is selected as a peak value.

8, a time interval value (tick) of each peak value is measured, a measured time interval value is sorted in order of magnitude, a weight value is reflected in an intermediate value or an average value of each time interval value, And calculates the heart rate by converting the calculated weighted average value into a heart rate cycle and converting it into a time unit.

Here, since the weighted average value is a heart rate cycle and the unit is time (second), the heart rate can be calculated by converting this per minute.

Further, in selecting the peak value, the peak value selection process is repeated a predetermined number of times while gradually increasing the width on the time axis of the sub window. That is, the width of the sub window is gradually widened and the deviation of each time interval value is compared. The peak value detection is repeated through this procedure to determine the optimum sub window width, A small subwindow is designated as the applicable target and reflected in the peak value selection.

As described above, the heart rate is calculated using the pixel values of the facial skin measured through the image analysis of the image data of the newborn baby. The candidates of the peak value for determining the heart rate are selected by applying the sub window, The error of the measured heart rate can be minimized by reflecting the weight to the interval value.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. It is to be understood that various modifications and changes may be made without departing from the scope of the appended claims.

100 ... heart rate measuring system 110 ... image acquiring unit
120 ... skin color band generating unit 130 ... image filter unit
140 ... BVP data extracting unit 150 ... The heart rate calculating unit

Claims (10)

An image acquisition unit 110 for acquiring image data of a newborn baby;
The entire image of the image data filtered on the basis of the skin color band is divided into blocks each having a predetermined size and subjected to frequency conversion to select a plurality of blocks having a relatively high frequency component and to select an upper limit value and a lower limit value A skin color band generating unit 120 for generating a skin color band having a band range;
An image filtering unit 130 for filtering the image data obtained on the basis of the generated skin color band and extracting a face skin region for heart rate extraction;
A BVP data extracting unit 140 for extracting BVP data (Blood Volume Pulse Data) that changes per unit time using pixel values of the extracted face skin region; And
And a heart rate calculator 150 for calculating a heart rate using the extracted BVP data,
The skin color band generation unit 120 generates a skin color band,
An image dividing unit 121 dividing the entire image of the filtered image data into blocks having the same size as the compression block of the video compression format,
A block extracting unit 122 for extracting a block corresponding to a face region of a newborn baby from all blocks,
A frequency conversion unit 123 for frequency-converting the image of the extracted block,
And a band setting unit (124) for comparing the frequencies of the extracted blocks and extracting the upper and lower limit values, and setting a band range of the skin color band based on the extracted upper and lower limit values.
delete The method according to claim 1,
The block extracting unit (122)
The face position in the entire block is detected based on the feature points on the face of the newborn baby, the face background region is set based on the detected face position, and the heart rate Measuring system.
The method according to claim 1,
The heart rate calculator 150 calculates a heart rate
A peak value candidate extracting unit 151 for extracting a peak value candidate using the slope value on the extracted BVP data,
A peak value selection unit 152 for arranging a subwindow having a predetermined width on the time axis line at each peak value candidate position and selecting a peak value candidate having a maximum size within each subwindow as a peak value,
A weighted average value calculator 153 for calculating a time interval value of each peak value, arranging the measured time interval values in order of magnitude, reflecting a weight on the intermediate value of each time interval value to calculate a weighted average value of the time interval value, ,
And a heart rate conversion unit (154) for calculating a calculated weighted average value by a heart rate cycle and converting the calculated weighted average value into a time unit to calculate a heart rate.
5. The method of claim 4,
The peak value candidate extracting unit 151 extracts,
And a position where a slope value is '0' on a change curve of the BVP data is extracted as a peak value candidate.
6. The method of claim 5,
The peak value candidate extracting unit 151 extracts,
Wherein the slope value of the BVP data is set to '0' and the slope value of the BVP data does not change from + to -, from the peak value candidate.
5. The method of claim 4,
The peak value selection unit 152 selects,
Wherein a predetermined width of the sub window is set in consideration of a mean heartbeat period of a typical newborn baby.
8. The method of claim 7,
The peak value selection unit 152 selects,
Selecting a peak value candidate having a single peak value candidate in the subwindow or having a larger value than another peak value candidate by arranging the center of the subwindow having the minimum size at the position of each peak value, The peak value selection process is repeated a predetermined number of times while gradually increasing the width on the time axis of the sub window to determine the optimal width of the sub window in the time axis direction, The heart rate measurement system that is specified as the applicable target and reflected in the peak value selection.
9. The method of claim 8,
The peak value selection unit 152 selects,
Setting a width on the time axis of the sub window having the minimum size to reflect the minimum value of the average heartbeat category,
Wherein a peak value is selected while gradually increasing a width of a subwindow set reflecting the maximum value of the average heartbeat cycle category.
5. The method of claim 4,
The weighted average value calculator 153 calculates a weighted average value
Using the Gaussian normal distribution curve with each peak value sorted in order of magnitude, the reflection ratio of the time interval value having a relatively large or low value is lowered, and the reflection ratio of the intermediate data value is increased, Heart rate measurement system to calculate.
KR1020150124988A 2015-09-03 2015-09-03 Heartrate measuring system using skin color filter KR101787828B1 (en)

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KR102132925B1 (en) * 2018-02-19 2020-07-10 와이케이씨테크(주) Method and apparatus for estimating blood volume based on a skin image
KR102487926B1 (en) 2018-03-07 2023-01-13 삼성전자주식회사 Electronic device and method for measuring heart rate
CN111166313A (en) * 2019-12-26 2020-05-19 中国电子科技集团公司电子科学研究院 Heart rate measuring method and device and readable storage medium
KR102570982B1 (en) * 2023-01-12 2023-08-25 (주) 에버정보기술 A Method For Measuring Biometric Information non-contact

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