KR20180137690A - A bio-information determination apparatus and method using time series data analysis of radar signal - Google Patents

Abstract

Disclosed are an apparatus and a method for determining biometric information using time series data analysis of an impulse radar signal. A method for determining biometric information of a target using an impulse radar signal comprises the following steps: generating a first frame set by accumulating single frames formed by overlapping radar pulses reflected from a target to measure a heartbeat, according to a predetermined reception time; generating a second frame set consisting of cross-correlation coefficients by analyzing cross-correlation between the first frame set converted into binary data and templates representing the heartbeat, based on a predetermined reference; selecting an optimal sampler including time series data having the highest similarity among the time series data included in the second frame set by comparing the time series data with the heartbeat of the target; correcting the time series data included in the selected optimal sampler; and extracting heartbeat information of the target based on the corrected time series data included in the optimal sampler.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and method for determining biological information using time-series data of a radar signal,

More particularly, the present invention relates to a biometric information determination apparatus and method using time-series data analysis of a radar signal, and more particularly, to a biometric information determination apparatus and method using a radar signal, And more particularly, to an apparatus and method for detecting a change in heart rate frequency and heart rate in a time domain.

Radar technology has been used to detect distant targets in aeronautical and military applications, or to measure distances to targets. In recent years, attempts have been made to acquire non-invasive and non-contact biological information such as pulse, heartbeat, and respiration from a close-range person using radar technology.

An impulse radar and a CW Doppler radar may be used as a radar technique for acquiring biometric information of a person. These two types of radar technology have different application areas because of differences in power consumption, target detection distance, and spatial resolution.

Among them, UWB (Ultra Wide Band) impulse radar has advantages of low risk of overexposure of electromagnetic wave and low power consumption when used in human body. In addition, the UWB impulse radar has excellent characteristics in terms of coexistence with peripheral devices, and is superior in spatial resolution compared to other methods, and can be considered as a method suitable for acquiring human biometric information.

In order to extract non-invasive and non-invasive human biometric information in this way, a study focusing on radar signals in the frequency domain is mainly focused on analysis of conventional studies using impulse radar. However, if the radar signal is processed in the frequency domain, it is impossible to observe a change in the short-term characteristics in the time domain. In addition, in the case of a heartbeat distributed in a narrow and low frequency band, The problem of increasing the signal acquisition time occurs.

In the present invention, a new radar signal processing method capable of accurately extracting the heartbeat frequency of human biometric information using a UWB impulse radar with high accuracy as well as accurately detecting the change in heart rate in the time domain is proposed .

The present invention relates to an apparatus and a method for detecting a change in a heart rate and a heart rate in a time domain more accurately by converting a frame set generated through a radar signal into binary data and analyzing a cross correlation using a template for a heart beat .

A method of determining a biometric information of a target according to an embodiment of the present invention includes accumulating a single frame formed by superimposing radar pulses reflected from a target for measuring a heartbeat according to a predetermined reception time to generate a first frame set ; Analyzing a cross correlation between a first frame set converted into binary data and a template representing a heartbeat based on a predetermined reference to generate a second frame set composed of cross correlation coefficients; Selecting an optimum sampler including time-series data having the highest degree of similarity compared with a heartbeat of the target among the time-series data included in the second frame set; And extracting the heartbeat information of the target based on the time series data included in the selected optimum sampler.

Wherein the selecting comprises: selecting a plurality of candidate samplers using a histogram created through cross correlation coefficients that constitute the second frame set; And determining an optimal sampler including time series data having the highest degree of similarity to the heartbeat of the target based on the distribution type of the time series data and the number information of the candidate samplers located in the neighborhood for each of the selected plurality of candidate samplers can do.

Wherein the step of selecting the optimum sampler comprises the steps of: selecting a candidate sampler to which the highest weight of the candidate samplers is assigned as an optimum sampler, wherein the weight is set so that the distribution form of the time series data identified for each of the plurality of candidate samplers is uniform Or the higher the number of candidate samplers located in the identified neighbors for each of the plurality of candidate samplers, the higher the number of candidate samplers.

Further comprising the step of correcting time series data by removing a blank of a block corresponding to time series data included in the selected optimum sampler, wherein the extracting step extracts the heartbeat information of the target based on the corrected time series data can do.

Wherein the correcting step comprises: removing a first blank located inside a block corresponding to time series data included in the best sampler; And a second space located between a block corresponding to the time series data included in the optimum sampler and a block corresponding to time series data included in the neighboring candidate sampler based on the number of candidate samplers located in the neighborhood of the optimum sampler, As shown in FIG.

The removing of the first blank may remove the first blank located within the block using the average length of the block corresponding to the time series data for each of the best sampler and the candidate sampler located next to the best sampler have.

Wherein removing the second blank is performed by comparing a length of a block located before and after the second blank if there is one candidate sampler located next to the best sampler in which the first blank located inside the block is removed The second blank can be removed by filling the block having the short length with 1.

Wherein the step of removing the second blank comprises the steps of: if there are two candidate samplers located next to the best sampler in which the first blank located inside the block is removed, There is no time series data included in the optimum sampler, and the second blank is eliminated by filling the second blank at the position of the best sampler with 1.

The extracting may determine a frequency of a heartbeat for the target using a time interval between center points of a block corresponding to time series data included in the optimum sampler.

A computer-readable recording medium containing a program for performing the image processing method according to any one of claims 1 to 10.

A target biometric information determination apparatus according to an exemplary embodiment of the present invention includes a processor for signal processing a single frame formed by overlapping radar pulses reflected from a target for measuring a heart beat, The first frame set is converted into binary data based on a predetermined reference, and the first frame set and the heartbeat are converted into binary data based on a predetermined reference. And generating a second frame set composed of cross correlation coefficients by analyzing a cross correlation between the target frame and the template representing the target frame, comparing the target frame with the heartbeat of the target among the time series data included in the second frame set, The sampler is selected, and the time series included in the selected optimum sampler Based on the emitter it is possible to extract the heart rate information of said target.

Wherein the processor selects a plurality of candidate samplers using a histogram created through cross correlation coefficients constituting the second frame set, calculates a distribution type of time series data for each of the selected plurality of candidate samplers, The optimum sampler including the time series data having the highest degree of similarity to the heartbeat of the target can be determined based on the number information of the target.

Wherein the processor selects a candidate sampler having the highest weight among the candidate samplers as an optimum sampler and the weight is set to be higher as the distribution form of the time series data identified for each of the plurality of candidate samplers is uniform, The larger the number of candidate samplers located in the identified neighbor for each of the plurality of candidate samplers, the higher the number of candidate samplers can be set.

The processor can correct the time series data by removing the space of the block corresponding to the time series data included in the selected optimum sampler and extract the heartbeat information of the target based on the corrected time series data.

Wherein the processor removes a first blank located in a block corresponding to the time series data included in the optimum sampler and outputs the time series data corresponding to the time series data included in the optimum sampler based on the number of candidate samplers located in the neighborhood of the optimum sampler And a second blank located between blocks corresponding to time series data included in the neighboring candidate sampler and time series data included in the neighboring candidate sampler are removed to correct time series data.

The processor may remove a first blank located within the block using the average length of blocks corresponding to time series data for each of the best sampler and the candidate sampler located next to the best sampler.

When the candidate sampler located adjacent to the best sampler in which the first space is located is located in the block, the processor compares the length of the block located before and after the second space with the length of the block having a short length 1, the second blank can be removed.

When the candidate sampler located adjacent to the best sampler in which the first space is located is located in the block, the time series data included in the candidate sampler located in the neighborhood at the position corresponding to the second space is And filling the second blank at the position of the best sampler with 1 to remove the second blank.

The processor can extract the heartbeat information of the target by determining the frequency of the heartbeat for the target using the time interval between the center points of the block corresponding to the time series data included in the optimum sampler.

According to an embodiment of the present invention, a frame set generated through a radar signal is converted into binary data, and a cross-correlation is analyzed using a template for a heartbeat, thereby more accurately changing a heart rate and a heart rate in a time domain Can be detected.

1 is a view showing a biological information determination system using a radar signal according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating a method of generating a first frame set according to an embodiment of the present invention. Referring to FIG.
3 is a flowchart illustrating a method of determining biometric information using time series data analysis of a radar signal according to an exemplary embodiment of the present invention.
4 is a diagram showing the shape of a radar signal after the preprocessing of the first frame set according to an embodiment of the present invention.
FIG. 5 is a diagram illustrating a shape of a preprocessed first frame set at a bird's-eye view according to an embodiment of the present invention.
6 is a diagram illustrating an example of converting a preprocessed first frame set according to an embodiment of the present invention into binary data.
FIG. 7 is a diagram illustrating the physical meaning of a pattern observed in a preprocessed first frame set according to an embodiment of the present invention.
FIG. 8 is a diagram illustrating a result of applying a cross-correlation using a first frame set converted to binary data and a template for a heartbeat according to an embodiment of the present invention.
FIG. 9 is a view showing an example of a pattern of a shape of a template and a heartbeat according to an embodiment of the present invention.
10 is a diagram illustrating an example of a blank interval existing in time series data according to an embodiment of the present invention.
11 is a diagram illustrating an example of a method of correcting time-series data of an optimum sampler according to an embodiment of the present invention.
12 is a diagram illustrating an example of extracting the heartbeat information using the time-series data of the corrected optimum sampler according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a view showing a biological information determination system using a radar signal according to an embodiment of the present invention.

In order to determine the biometric information of the target 110, the biometric information determination apparatus 100 may project a radar signal toward a direction in which the target 110 is positioned using a transmission antenna. At this time, the transmission radar signal projected through the transmission antenna may be a pulse-shaped radar signal. For example, the transmitted radar signal may be a radar signal in the form of a low-risk, low-power UWB impulse to the human body. At this time, a frequency characteristic such as a center frequency and a bandwidth of a UWB impulse type radar signal projected through the biological information determination apparatus 100 is defined as a standard.

The biometric information determination apparatus 100 can determine the biometric information of the target 110 using the received radar signal that is reflected from the target 110 and collected through the reception antenna. At this time, the biometric information determination apparatus 100 can measure the change in the short-term characteristics of the biometric information according to the time, by analyzing the received radar signal in the time domain, unlike the conventional technique of analyzing the received radar signal in the frequency domain. Various bio-information of the target 110 can be measured using a radar signal, but the present invention provides a method of measuring the heartbeat information among them.

FIG. 2 is a diagram illustrating a method of generating a first frame set according to an embodiment of the present invention. Referring to FIG.

The transmission radar signal projected from the biological information determination apparatus 100 may be in the form of a pulse whose width is extremely narrow on the time axis as shown in FIG. The biological information determination apparatus 100 can project a transmission radar signal of this type to the target 110 at regular time intervals using a transmission antenna.

The biometric information determination apparatus 100 can collect the radar signal reflected from the target 110 using the receiving antenna. At this time, the biological information determination apparatus 100 may collect the reception radar signal through the reception antenna according to a predetermined time. The received radar signal collected via the receive antenna may be a signal in the form of a superposition of multiple radar pulses.

The biological information determination apparatus 100 may convert the reception radar signal collected through the reception antenna into digital data. At this time, the receiving radar signal collected through the receiving antenna can be converted into digital data by being sampled using a plurality of samplers. In the present invention, a receiving radar signal converted into digital data is referred to as a frame.

FIG. 2 (b) shows the shape of a single frame in the present invention. In this case, the sampler index axis corresponding to the horizontal axis represents the number of each sampler index, and the signal amplitude axis corresponding to the vertical axis represents the voltage of the radar signal collected through the receiving antenna. At this time, each sampler index number may be proportional to the distance from the radar antenna to the target 110. For example, the larger the sampler index number, the greater the distance from the radar antenna to the target 110.

The biometric information determination apparatus 100 may generate and use a frame set in which a plurality of single frames are accumulated in accordance with the flow of time in order to efficiently extract the heart rate frequency of the target 110 from the received radar signal. At this time, a plurality of single frames to be accumulated can be used in units of n power of 2, such as 512, 1024, and so on.

Specifically, FIG. 2C shows a form of a frame set in the present invention. The frame set has a form in which the size of the received radar signal is expressed on a plane formed by the sampled index axis and the time axis. That is, the frame set can be represented by a data structure of a two-dimensional matrix.

For example, suppose that the biometric information determination apparatus 100 supports 256 samplers. The sampler index axis of the frameset can then be composed of 256. And that the bioinformation determination apparatus 100 acquires 512 reception radar signals at 20 ms intervals. Then, since a single frame collected every 20ms interval accumulates in the time axis direction to constitute a frame set, the time axis is composed of 512 unit time (0.02 second), and one frame set is generated by receiving radar signal collected for 10.24 seconds . Such a frame set is not limited to the above example, but may be changed into various values according to needs and uses.

The frame set generated through the biometric information determination apparatus 100 includes biometric information of the target 110. Particularly, the data showing the largest fluctuation among the data in the time axis direction included in the frame set represents information about respiration of the target 110. That is, as shown in FIG. 2 (c), a large variation in the data in the time axis direction of the 138th sampler indicates that the phase of the received radar signal varies due to the respiration of the target 110 .

On the other hand, a ripple appearing in a small size on the data in the time axis direction of almost all samplers represents information about the heartbeat of the target 110. [ The biometric information determination apparatus 100 of the present invention selects an optimum sampler related to a heartbeat of a target 110 among a plurality of samplers and analyzes data in time axis direction of the selected optimum sampler, that is, time series data, The heartbeat information of the target 110 can be measured.

3 is a flowchart illustrating a method of determining biometric information using time series data analysis of a radar signal according to an exemplary embodiment of the present invention.

In step 310, the biometric information determination apparatus 100 generates a first frame set by accumulating a single frame formed by superimposing radar pulses reflected from a target for measuring heartbeat according to a predetermined reception time can do. At this time, the generated frame set has a form in which the size of the received radar signal is expressed on the plane formed by the sampled index axis and the time axis. That is, the frame set can be represented by a data structure of a two-dimensional matrix.

In step 320, the biometric information determination apparatus 100 analyzes a cross-correlation between a first frame set converted into binary data and a template representing a heartbeat based on a predetermined criterion, and generates a second frame set Can be generated. To this end, the biological information determination apparatus 100 may perform a preprocessing process on the time series data, which is a data set in the time axis direction of each sampler in the first frame set.

More specifically, the time-series data includes a phase change component due to respiration in addition to the heartbeat information of the target 110. At this time, the large amplitude wave component seen in the time series data is due to breathing, and the small amplitude wave component placed thereon is due to the heartbeat. In general, the movement of the heartbeat by the thorax has a displacement of about 0.2-0.5 mm, and the movement of the thorax by the respiration has a displacement of 4-12 mm. Therefore, the heartbeat component of the target 110 can be effectively extracted by removing the respiratory component from the time-series data reflecting the movement of the ribcage.

For this purpose, the bio-information determination apparatus 100 may use a band-pass filter to extract the heartbeat information of the target 110 by removing the DC component, respiration component, and noise from the time series data of each sampler. Since the heartbeat frequency of a person is distributed in a band of 1 to 3 Hz, the biological information determination apparatus 100 filters the time series data of each sampler by using a bandpass filter that selectively passes a signal component composed of frequencies in the range of 1 to 3 Hz Only one signal component affected by heartbeat can be left in one frame set. That is, the low-frequency component or the high-frequency noise component contained in the signal reflected from the stationary background object can be effectively removed through the band-pass filter.

At this time, the biometric information determination apparatus 100 may adopt an IIR (Infinite Impulse Response) type filter as shown in Equation 1 below to implement the band pass filter, and the 4th order The characteristics of the Butterworth band-pass filter of FIG. By substituting the time series data of each sampler into the input variable x [n] in Equation 1, the result y [n] can be obtained.

[Formula 1]

In Equation 1, a [k] and b [k] are coefficients for implementing the band-pass filter characteristic, and are shown in Table 1 below. The variables N and M represent the number of coefficients a [k] and b [k], respectively, and have a value of 5 respectively.

[Table 1] Values of coefficients for band pass filter

FIG. 4A shows a result of filtering the time-series data of each sampler constituting the first frame set using a band-pass filter, and it can be seen that the DC component and the respiration component are removed. The result of accumulating the time series data of all samplers that have passed through the band-pass filter is shown in FIG. 4 (b). At this time, a plurality of peaks observed in a section from about the 150th sampler to the 200th sampler means that the phase change pattern of the radar signal due to the heartbeat is highlighted by the band pass filter.

5A and 5B are diagrams showing the first frame set before and after the band pass filter processing at the bird's-eye view point in order to more easily observe the phase change pattern of the radar signal due to the heartbeat. In FIG. 5 (a), it is possible to observe the appearance of peaks continuously appearing along the time axis in the section from about the 150th sampler to the 200th sampler, and no movement in the direction of the sampler axis from the peak of the peak is observed. However, in FIG. 5 (b), it can be seen that a certain pattern repeatedly appears in the section from the about 150th sampler to the 200th sampler, which is attributed to the characteristics of the UWB impulse radar operating method.

Specifically, when a radar pulse of a high frequency is repeatedly projected from the transmission antenna of the radar system toward the target 110, when a plurality of pulses are reflected from the body surface, Return to the antenna. In the receiving antenna, pulses are collected at a frequency relatively lower than the radar transmission frequency, so that a frame in which a number of pulses having undergone a phase change are overlapped is generated. If only the frequency band component of the heartbeat is extracted by using the band pass filter in the first frame set, the heartbeat pattern appears in the time axis direction and the size of the frame changed in the sampler axis direction by the band pass filter A peak will appear.

Then, the biometric information determination apparatus 100 sets all the data of the first frame set subjected to the preprocessing process to a value higher than a specific threshold value to "1" and a lower value to "0" 6 < / RTI > At this time, the specific threshold may be determined experimentally as a factor that affects the accuracy of the overall signal processing result. The black dots and lines shown in FIG. 6 represent values of "1" and blank spaces represent "0". Looking at the time series data of each sampler, it can be seen that a row of "1" Can be observed. Using the phase relationship between the type of the time series data converted into the binary data and the time series data of each sampler, the bio-information determination apparatus 100 can highlight the part where the influence of the heartbeat appears in the binary data.

The biometric information determination apparatus 100 can generate a second frame set having cross correlation coefficients by analyzing cross correlation between templates showing heartbeats using binary data in which the influence of heartbeats is emphasized. Specifically, when there is a specific form to be searched in an arbitrary image, by analyzing the two-dimensional cross correlation with the entire image using the template as a template, a specific shape can be found in the corresponding arbitrary image.

A schematic view of the pattern observed in the image of the binary data to analyze the physical meaning of the heartbeat pattern is shown in FIG. The pattern shown in the binary image is a pattern in which a periodic row of " 1 "having a phase opposite to that of a column of" 1 "repeated at regular intervals in the time axis direction and an adjacent position in the sampler axis direction appears. The spacing of the samplers with opposite phases is in the range of 3 or less. The larger the threshold value used in the process of generating the binary image, the wider the interval, and the smaller the threshold, the smaller the interval becomes.

In the column of "1" repeatedly appearing in the time axis direction, the time series data passing through the band pass filter is represented by a binary value based on a specific threshold, and is synchronized with the displacement of the body surface due to the actual heartbeat. The pattern repeatedly appearing in the sampler axis direction is represented by a binary value of each peak of a single frame affected by the band pass filter. The interval of each pattern is wide when the threshold value used in the binary image conversion is large and when the threshold value is small It appears to be narrow.

It is possible to derive a representative pattern representing the occurrence of heartbeat by analyzing various patterns in the frequency band of 1 to 3 Hz corresponding to the frequency band of the heartbeat, and the biometric information determination apparatus 100 of the present invention can utilize it as a template . The template is a 45-by-5 two-dimensional array, consisting of columns of "1" and "0" with length 15, which is shown in Figure 8 (a). In order to examine whether the shape of the template can represent various patterns due to actual heartbeats, in the case where the frequency of the heartbeat is the lowest limit of 1 Hz (FIG. 9 (b)) and the maximum limit of 3 Hz (c)) and the already derived template (Fig. 9 (a)) are shown together in Fig. Then, the length of the template and the direction of the time axis in each pattern is expressed in time units. As shown in FIG. 9, a heartbeat pattern occurring in a band of 1 to 3 Hz can be regarded as a scaled version of the template in the time axis direction. Therefore, when the template is used to analyze the two-dimensional cross-correlation with the binary image, a relatively large correlation coefficient can be obtained at the position of the actual heartbeat pattern than at the peripheral portion without the heartbeat. In conclusion, it can be seen that the template can be used to find the location of the heartbeat in the binary image.

The binary image shown in Fig. 6 is represented by f (x, y), which is a 512 ㅧ 250 image having a time axis variable x and a sampler axis variable y, and a template of 45 ㅧ 5 size is expressed by w (x, y) (X, y), which is a two-dimensional cross-correlation coefficient, is expressed by the following equation (2).

[Formula 2]

The shape of a new second frame set composed of cross correlation coefficients is shown in FIG. 8 (b). A large number of peaks are observed, which means that the correlation coefficient value is larger than that at the periphery in the section from the about 150th sampler to the 200th sampler in FIG. 8 (b). The location of these peaks is where the probability of a heartbeat pattern is high and is used to find a sampler with time-series data that best reveals heartbeats in the following process.

In step 330, the biometric information determination apparatus 100 can select an optimal sampler including time series data having the highest similarity in comparison with the heartbeat of the target 110 among the time series data included in the second frame set. For this, the biometric information determination apparatus 100 finds a sampler represented by a maximum correlation coefficient at a unit time point on a time axis for a second frame set, creates a histogram for the sampler, and selects a plurality of candidate samplers having the highest occurrence frequency can do.

In the selection process of the candidate sampler, a sampler in which the heartbeat is most visible at each time axis can be found. That is, it contributes to finely expressing the change in the heart rate according to the time. Since the number of each sampler corresponds to the physical distance from the antenna to the target, it implies that the heartbeat is clearly observed at a position corresponding to the sampler selected as the candidate.

Then, the biometric information determination apparatus 100 includes time series data having the highest degree of similarity to the heartbeat of the target 110 based on the distribution form of the time series data and the number information of the candidate samplers located in the vicinity, for each of the plurality of selected candidate samplers The optimum sampler can be selected.

First, the biometric information determination apparatus 100 may assign different weights according to the distribution pattern of the time series data for each of the plurality of candidate samplers. Since the "1" and "0" columns formed along the time axis in the binary image shown in FIG. 6 are synchronized with the heartbeat, it is important to select the sampler having the time series data with the most uniform distribution of each column as the candidate sampler . This is because the heartbeat component is most apparent in samplers with the most evenly distributed time series data. As a result, the process of selecting the sampler with the most evenly distributed time series data leads to a more accurate detection of the heartbeat location and selects the sampler with the highest signal-to-noise ratio as the candidate sampler .

To this end, the biological information determination apparatus 100 may perform run length encoding on the time series data of each candidate sampler. Continuous length coding is a technique that is mainly used for lossless compression of data, and is a method of representing a sequence of continuous data by a repeated value and its number. In the present invention, this is utilized in calculating the lengths of the columns of "1" and "0 " in the time series data of each of the plurality of candidate samplers.

After the continuous length coding is completed, the biological information determination apparatus 100 can calculate the standard deviation of the encoded data for each candidate sampler. At this time, it can be estimated that the arrangement of "1" and "0" is most evenly distributed in the time series data of the candidate sampler with the smallest standard deviation. Therefore, the biometric information determination apparatus 100 gives a higher weight to each candidate sampler as the standard deviation becomes smaller (the more uniform the distribution form of the time series data), and the larger the standard deviation becomes (the distribution form of the time series data becomes uneven It is possible to give a low weight.

Next, the biometric information determination apparatus 100 may assign different weights to the respective candidate samplers according to the number of candidate samplers located in the neighborhood. If there is a candidate sampler at a position within +3 or -3 for each candidate sampler, this may be called a neighbor sampler. The biometric information determination apparatus 100 may assign weights differentially depending on the presence or absence of neighboring samplers. If the number of neighboring samplers located on both sides of each candidate sampler is greater, a higher weight is given, and a lower weight Can be granted. This is because it is likely that the location of the heartbeat is following a normal distribution centering on a specific sampler. The process of assigning different weights according to the neighborhood sampler is a sampler having the highest probability of showing heartbeats, that is, It can help you to select the closest sampler.

The biometric information determination apparatus 100 multiplies the weights given in accordance with the distribution type of the time series data for each of the plurality of candidate samplers with the weight given according to the presence or absence of neighboring samplers, And the candidate sampler with the highest score among them can be selected as the optimum sampler.

In step 340, the biological information determination apparatus 100 can correct the time series data included in the selected optimum sampler. First, as shown in FIG. 10, an array of consecutive "1" s in the time series data included in the optimum sampler can be referred to as a block. If the time series data is examined, there may be a blank interval in the block, and an example thereof is shown in FIG. In FIG. 10, the intervals indicated by (a) and (b) correspond to spaces. Space may be caused by a quantization error or an external noise generated in the process of sampling the radar signal and may occur when the threshold value is set too high in the process of converting the first frame set to binary data. In the following process, since the position of the heartbeat must be calculated using the length of the block, the blank serves as a factor to lower the signal-to-noise ratio. Therefore, it is necessary to remove the whitespace by reflecting the appropriate value at the position corresponding to the whitespace. (A) type of blank corresponds to a blank existing in a specific block of time series data included in the optimum sampler, and (b) type of blank is included in a neighboring sampler And a blank space that can be found through comparison with the time series data. If we look at the relationship between time series data of the optimum sampler and neighbor sampler, the phase of the block appears to be the opposite, so that it can be easily removed.

과 공백의 뒤에 위치한 블록의 길이

, 그리고 공백의 폭

를 측정할 수 있다. 이때, 시계열 데이터 내의 "1"과 "0"의 열에 대한 길이는 앞서 행한 연속길이 부호화 과정에서 측정된 바가 있으므로, 이를 활용하여 블록과 공백의 길이를 측정할 수 있다. 이후 생체 정보 결정 장치(100)는 두 블록의 길이와 공백의 폭을 더한 값이 블록의 평균 길이인

의 120%와 같거나 짧은 경우 즉,

인 경우 생체 정보 결정 장치(100)는 공백을 "1"로 채워 넣어 시계열 데이터를 보정할 수 있다. 이러한 블록의 내부에 위치한 공백을 제거하는 보정 작업은 최적 샘플러와 모든 이웃 샘플러에 대해 수행될 수 있다.The biometric information determination apparatus 100 may remove a blank located inside the block as shown in FIG. 11 (a). First, the biometric information determination apparatus 100 determines the length of a block located in front of a space

And the length of the block after the space

, And the width of the blank

Can be measured. In this case, since the lengths of the "1" and "0" columns in the time series data have been measured in the continuous length coding process, the length of the block and the blank space can be measured. Then, the biometric information determination apparatus 100 determines whether the value obtained by adding the lengths of the two blocks and the width of the blank is an average length of the blocks

Is equal to or shorter than 120% of < RTI ID = 0.0 >

The biometric information determination apparatus 100 can correct the time series data by filling in the blank with "1 ". Correction operations to remove blanks located inside these blocks may be performed for the best sampler and all neighbor samplers.

The biometric information determination apparatus 100 can perform correction for a vacant space that is found after removing all the abnormal vacancies located inside the block, if the vacant space is not clear to which sampler. In this case, the time series data can be corrected by comparing the distributions of the time series data included in the optimum sampler and the neighboring sampler to find a blank and then removing the blank. At this time, the biometric information determination apparatus 100 changes the correction method according to the number of neighboring samplers possessed by the optimum sampler, and if all of the neighboring samplers are present at the positions of the forward and backward positions, Kl 3, If calibration is possible and there is only one neighbor sampler, the correction is made in a simpler way.

이 공백의 뒤에 위치한 최적 샘플러의 블록 길이

보다 긴 것을 알 수 있다. 이러한 경우 생체 정보 결정 장치(100)는 길이가 -은 블록이 위치한 최적 샘플러의 공백 위치에 "1"을 채워 넣는 방식으로 시계열 데이터를 보정할 수 있다.When the neighboring sampler of the optimum sampler in which a space in a single block is removed is one, the length of a single block located before and after the blank included in the optimum sampler is compared to obtain a single block having a short length 1 < / RTI > For example, as shown in FIG. 11 (b), the block length of a neighboring sampler located in front of a blank

The block length of the best sampler after this space

A longer one can be seen. In this case, the biometric information determination apparatus 100 can correct the time series data in such a manner that "1" is filled in the blank position of the optimum sampler in which the block of length - is located.

에서는 172, 178번 이웃 샘플러에 데이터가 존재하지 않으므로 생체 정보 결정 장치(100)는

시점에서 최적 샘플러가 데이터를 가질 확률이 높다고 판단하여 최적 샘플러의 공백을 "1"로 채울 수 있다. On the other hand, if there are two candidate samplers located in the neighborhood of the optimum sampler in which a space within a single block is removed, a method of filling the space of the optimum sampler with "1" only when there is no data of neighboring samplers at the current blank position To correct the time series data. For example, as shown in (c) of FIG. 11, it can be seen that neighbor samplers exist at positions 172 and 178 before and after the 175 sampler, which is the optimum sampler. At this point,

Since no data exists in neighboring samplers 172 and 178, the biometric information determining apparatus 100

It is determined that the optimum sampler has a high probability of having data, and the space of the optimum sampler can be filled with "1 ".

에서는 178번 이웃 샘플러의 경우 데이터가 존재하지만 172번 이웃 샘플러는 비어있으므로 생체 정보 결정 장치(100)는

시점에서 172번 이웃 샘플러가 데이터를 가질 확률이 높다고 판단하여 172번 이웃 샘플러의 공백을 "1"로 채우고 최적 샘플러의 공백은 비워두게 된다.However,

In the case of the neighboring sampler 178, data exists but the neighboring sampler 172 is empty, so that the biometric information determining apparatus 100

It is assumed that the neighboring sampler 172 is likely to have the data at the time point, so that the space of the neighboring sampler 172 is filled with "1 ", and the space of the optimum sampler becomes empty.

At step 350, the biological information determination apparatus 100 can extract the heartbeat information of the target 110 based on the time series data included in the corrected optimum sampler. Since each block included in the time series data of the optimum sampler is synchronized with the heartbeat, the bioinformation determining apparatus 100 can estimate the center point of each block as the time point of the heartbeat. Therefore, the interval between the center points of each block can be regarded as a time interval between heartbeats, and the bioinformation determining apparatus 100 can calculate the heartbeat frequency of the target 110 by obtaining the inverse of the time interval between heartbeats.

FIG. 12 shows an example in which the time series data of the finally selected optimum sampler is composed of N blocks, and the bio-information determination apparatus 100 can calculate the heart rate frequency of the target 110 through Equation 1 below.

[Formula 3]

The present invention provides a method for efficiently extracting heartbeat information of a target 110 using a UWB impulse radar. The biometric information determination apparatus 100 of the present invention processes a radar signal in a time domain to extract heartbeat information carried on a radar signal reflected from a human body, and based on the obtained temporal position of the heartbeat, Can be detected.

Such a biological information determination apparatus 100 can be applied to various fields such as security, safety, surveillance, and health care. Particularly, if the radar system is composed of one transmitting end and two or more receiving ends or an array antenna composed of a plurality of antennas is used in the radar system, the position of the target 110 in the space can be determined, Accurate biometric information and location information can be measured at the same time, which can be utilized in various applications.

Meanwhile, the method according to the present invention may be embodied as a program that can be executed by a computer, and may be embodied as various recording media such as a magnetic storage medium, an optical reading medium, and a digital storage medium.

Implementations of the various techniques described herein may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or combinations thereof. Implementations may be implemented in a computer program product, such as an information carrier, e.g., a machine readable storage device, such as a computer readable storage medium, for example, for processing by a data processing apparatus, Apparatus (computer readable medium) or as a computer program tangibly embodied in a propagation signal. A computer program, such as the computer program (s) described above, may be written in any form of programming language, including compiled or interpreted languages, and may be stored as a stand-alone program or in a module, component, subroutine, As other units suitable for use in the present invention. A computer program may be deployed to be processed on one computer or multiple computers at one site or distributed across multiple sites and interconnected by a communications network.

Processors suitable for processing a computer program include, by way of example, both general purpose and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. The elements of a computer may include at least one processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer may include one or more mass storage devices for storing data, such as magnetic, magneto-optical disks, or optical disks, or may receive data from them, transmit data to them, . ≪ / RTI > Information carriers suitable for embodying computer program instructions and data include, for example, semiconductor memory devices, for example, magnetic media such as hard disks, floppy disks and magnetic tape, compact disk read only memory A magneto-optical medium such as a floppy disk, an optical disk such as a DVD (Digital Video Disk), a ROM (Read Only Memory), a RAM , Random Access Memory), a flash memory, an EPROM (Erasable Programmable ROM), an EEPROM (Electrically Erasable Programmable ROM), and the like. The processor and memory may be supplemented or included by special purpose logic circuitry.

In addition, the computer-readable medium can be any available media that can be accessed by a computer, and can include both computer storage media and transmission media.

While the specification contains a number of specific implementation details, it should be understood that they are not to be construed as limitations on the scope of any invention or claim, but rather on the description of features that may be specific to a particular embodiment of a particular invention Should be understood. Certain features described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination. Further, although the features may operate in a particular combination and may be initially described as so claimed, one or more features from the claimed combination may in some cases be excluded from the combination, Or a variant of a subcombination.

Likewise, although the operations are depicted in the drawings in a particular order, it should be understood that such operations must be performed in that particular order or sequential order shown to achieve the desired result, or that all illustrated operations should be performed. In certain cases, multitasking and parallel processing may be advantageous. Also, the separation of the various device components of the above-described embodiments should not be understood as requiring such separation in all embodiments, and the described program components and devices will generally be integrated together into a single software product or packaged into multiple software products It should be understood.

It should be noted that the embodiments of the present invention disclosed in the present specification and drawings are only illustrative of specific examples for the purpose of understanding and are not intended to limit the scope of the present invention. It will be apparent to those skilled in the art that other modifications based on the technical idea of the present invention are possible in addition to the embodiments disclosed herein.

100: Biometric information determination device
110: Target

Claims (20)

Generating a first frame set by accumulating a single frame formed by overlapping radar pulses reflected from a target for measuring heartbeat according to a predetermined reception time;
Analyzing a cross correlation between a first frame set converted into binary data and a template representing a heartbeat based on a predetermined reference to generate a second frame set composed of cross correlation coefficients;
Selecting an optimum sampler including time-series data having the highest degree of similarity compared with a heartbeat of the target among the time-series data included in the second frame set;
Extracting the heartbeat information of the target based on the time series data included in the selected optimum sampler
And determining the biometric information of the target. The method according to claim 1,
Wherein the selecting comprises:
Selecting a plurality of candidate samplers using a histogram created through cross correlation coefficients constituting the second frame set; And
Determining an optimal sampler including time series data having the highest degree of similarity to the heartbeat of the target based on the distribution type of the time series data and the number information of the candidate samplers located in the neighborhood for each of the selected plurality of candidate samplers
And determining the biometric information of the target. 3. The method of claim 2,
Wherein the step of selecting the optimum sampler comprises:
Selecting a candidate sampler having the highest weight among the candidate samplers as an optimum sampler,
The weighting value,
The distribution form of the time series data identified for each of the plurality of candidate samplers is set to be higher as the distribution type is uniform
Wherein the number of candidate samplers located in the vicinity of each of the plurality of candidate samplers is set to be higher. The method according to claim 1,
Correcting the time series data by removing a blank of a block corresponding to the time series data included in the selected optimum sampler;
Further comprising the steps of: 5. The method of claim 4,
Wherein the extracting comprises:
And extracting the heartbeat information of the target based on the corrected time series data. 5. The method of claim 4,
Wherein the correcting comprises:
Removing a first blank space located inside a block corresponding to time series data included in the optimum sampler; And
A second space located between a block corresponding to the time series data included in the optimum sampler and a block corresponding to time series data included in the neighboring candidate sampler based on the number of candidate samplers located in the neighborhood of the optimum sampler, Steps to remove
And determining the biometric information of the target. The method according to claim 6,
Wherein removing the first blanking comprises:
And eliminating a first blank located inside the block using an average length of a block corresponding to time series data for each of the optimal sampler and a candidate sampler positioned next to the optimal sampler. The method according to claim 6,
The step of removing the second blank may comprise:
If there is one candidate sampler positioned next to the best sampler in which the first space is located within the block, a block having a short length is filled with 1 in comparison with the length of blocks before and after the second space Thereby removing the second blank. The method according to claim 6,
The step of removing the second blank may comprise:
When there are two candidate samplers located next to the best sampler in which the first space located inside the block is removed, there is no time series data included in the neighboring candidate sampler at a position corresponding to the second space, And removing the second blank by filling a second blank existing at a position of the sampler with 1. The method according to claim 1,
Wherein the extracting comprises:
Determining a frequency of a heartbeat for the target using a time interval between center points of a block corresponding to time series data included in an optimum sampler. A computer-readable recording medium storing a program for performing the image processing method according to any one of claims 1 to 10. A processor for processing a single frame formed by superimposing radar pulses reflected from a target for measuring a heartbeat
Lt; / RTI >
The processor generates a first frame set by accumulating a single frame formed by overlapping radar pulses reflected from a target to be measured with respect to a heartbeat according to a predetermined reception time and outputs the first frame set as binary data And generating a second frame set composed of cross correlation coefficients by analyzing a cross correlation between the converted first frame set and a template representing a heartbeat, comparing the similarity with the heartbeat of the target among the time series data included in the second frame set, Selects the optimum sampler including the highest time series data and extracts the heartbeat information of the target based on the time series data included in the selected optimum sampler. 13. The method of claim 12,
The processor comprising:
A plurality of candidate samplers are selected by using a histogram created through cross correlation coefficients constituting the second frame set, and a distribution type of time series data and a number of candidate samplers located in the neighborhood of the selected plurality of candidate samplers Determining an optimum sampler including time-series data having the highest degree of similarity to the heartbeat of the target. 13. The method of claim 12,
The processor
Wherein the candidate sampler having the highest weight among the candidate samplers is selected as an optimum sampler and the weight is set to be higher as the distribution form of the time series data identified for each of the plurality of candidate samplers is uniform, And the higher the number of candidate samplers located in the identified neighbor for each of the samplers, the higher the number of candidate samplers is. 13. The method of claim 12,
The processor
Correcting the time series data by removing a blank of a block corresponding to the time series data included in the selected optimum sampler and extracting the heartbeat information of the target based on the corrected time series data. 16. The method of claim 15,
The processor comprising:
A block corresponding to the time series data included in the optimum sampler based on the number of candidate samplers located in the neighborhood of the optimum sampler and a block corresponding to the time series data included in the optimal sampler, And corrects the time series data by removing a second blank located between blocks corresponding to the time series data included in the candidate sampler located in the neighborhood. 17. The method of claim 16,
The processor comprising:
Wherein the first space located inside the block is removed by using an average length of blocks corresponding to time series data for each of the optimum sampler and the candidate sampler located next to the optimum sampler. 17. The method of claim 16,
The processor comprising:
If there is one candidate sampler positioned next to the best sampler in which the first space is located within the block, a block having a short length is filled with 1 in comparison with the length of blocks before and after the second space Thereby removing the second blank. 17. The method of claim 16,
The processor comprising:
When there are two candidate samplers located next to the best sampler in which the first space located inside the block is removed, there is no time series data included in the neighboring candidate sampler at a position corresponding to the second space, And removing the second blank by filling a second blank existing at a position of the sampler with 1. 13. The method of claim 12,
The processor comprising:
Wherein the heartbeat information of the target is extracted by determining a frequency of a heartbeat for the target using a time interval between center points of a block corresponding to time series data included in an optimum sampler.

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