KR102117748B1 - Apparatus and method for evaluating quality of signal for measurement of vital sign - Google Patents

Abstract

The present invention is an apparatus for evaluating the quality of a signal for measuring biometric information, which evaluates the quality of a radar signal based on an autocorrelation signal of a radar signal including biometric information, to determine whether the radar signal is suitable for measuring biometric information, and I suggest a method. An apparatus according to the present invention includes an autocorrelation signal detection unit for detecting an autocorrelation signal based on a radar signal including biometric information; A first period calculator configured to calculate first periods between peaks included in the autocorrelation signal; And a score calculation unit that compares the first periods with the second periods obtained from the reference signal to calculate a score for determining whether the radar signal is suitable for measuring biometric information.

Description

Apparatus and method for evaluating quality of signal for measurement of vital sign}

The present invention relates to an apparatus and method for evaluating the quality of a signal. More specifically, it relates to an apparatus and method for evaluating the quality of a signal for measuring biometric information.

Conventionally, many studies have been conducted on the measurement of biological signals based on IR-UWB (Impulse Radio Ultra Wide-Band) radar, but most of them are limited to frequency spectrum based measurement methods corresponding to breathing and heart rate.

This frequency domain approach has the advantage of being able to measure bio signals, such as breathing and heart rate, regardless of the aspect of the signal, but has a problem that the state of the time domain signal is not considered. Since IR-UWB radar is vulnerable to minute movements, signal distortions may occur to the extent that bio signals cannot be measured due to movement.

In addition, if there is no measurement target in the detection distance of the IR-UWB radar, the biosignal itself may not exist.

Korean Patent Publication No. 2014-0106795 (Publication Date: 2014.09.04.)

The present invention has been devised to solve the above problems, and evaluates the quality of the radar signal based on the autocorrelation signal of the radar signal including the biometric information to determine whether the radar signal is suitable for measuring biometric information. An object of the present invention is to propose an apparatus and method for evaluating the quality of a signal for measuring biometric information.

However, the object of the present invention is not limited to the above-mentioned matters, and other objects not mentioned will be clearly understood by those skilled in the art from the following description.

The present invention is devised to achieve the above object, an autocorrelation signal detection unit for detecting an autocorrelation signal based on a radar signal including biometric information; A first period calculator configured to calculate first periods between peaks included in the autocorrelation signal; And a score calculating unit comparing the first periods with the second periods obtained from the reference signal to calculate a score for determining whether the radar signal is suitable for measuring the biometric information. We propose a quality evaluation device for measurement signals.

In addition, the present invention comprises the steps of detecting an autocorrelation signal based on a radar signal containing biometric information; Calculating first periods between peaks included in the autocorrelation signal; And comparing the first periods with the second periods obtained from the reference signal to calculate a score for determining whether the radar signal is suitable for measuring the biometric information. We propose a method for evaluating the quality of the signal.

The present invention also proposes a computer program stored in a computer-readable medium for executing a method for evaluating the quality of a signal for measuring biometric information in a computer.

The present invention can achieve the following effects through the configuration for achieving the above object.

First, when measuring a biosignal using an IR-UWB (Impulse Radio Ultra Wide-Band) radar, it may be determined whether the current signal is suitable for measuring the biosignal before measuring the biosignal.

Second, the accuracy of the biosignal measurement can be improved by evaluating the reliability of the biosignal measurement.

1 is a graph showing an autocorrelation of a slow time window signal and a signal used to measure a biosignal in the present invention.
2 is a graph showing a slow time window signal when a motion occurs and autocorrelation of the signal.
3 is a block diagram schematically illustrating an apparatus for evaluating a signal quality for measuring biometric information according to a preferred embodiment of the present invention.
4 is a flowchart schematically illustrating a method for evaluating the quality of a signal for measuring biometric information according to a preferred embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. First, when adding reference numerals to the components of each drawing, it should be noted that the same components have the same reference numerals as possible even though they are displayed on different drawings. In addition, in describing the present invention, when it is determined that detailed descriptions of related well-known structures or functions may obscure the subject matter of the present invention, detailed descriptions thereof will be omitted. In addition, although preferred embodiments of the present invention will be described below, the technical spirit of the present invention is not limited to or limited thereto, and can be variously implemented by a person skilled in the art.

As a method of measuring a person's respiration and heart rate at a long distance, a method using an impulse radio ultra wide-band (IR-UWB) radar has been widely used. This method uses the IR-UWB radar to detect the subject's position and then measures the body's microscopic movements due to breathing and heartbeat.

However, this method has a problem in that the accuracy of the biosignal measurement is significantly deteriorated when the position of the subject is incorrectly detected, or when the movement of the subject's breath or heart movement is excessively large.

Before measuring the biosignal, if it is possible to quantify how well the currently measured radar signal is suitable for measuring the biosignal, information on the reliability of the biosignal to be measured can be obtained.

In view of this, the present invention proposes a method for evaluating the reliability (or quality) of a signal used for biosignal measurement, that is, a technique for evaluating the reliability of biosignal measurement using an IR-UWB radar.

Most of the existing methods aiming to measure the heart rate are implemented by converting the time axis signal into the frequency domain and finding the heart rate within the frequency range of a typical heart rate, rather than observing the periodic waveform of the heart on the time axis.

The present invention targets a time domain signal obtained using an IR-UWB radar. In the present invention, this time domain signal is defined as a slow-time windowed signal.

The slow time windowed signal is shown as the signal shown in Fig. 1 (a) (vital signal (B)). When the auto-correlation signal of this signal is obtained, it appears as the signal (auto-correlation (c)) shown in FIG. 1 (b). Here, since the autocorrelation signal is symmetrical to the left and right, the-(minus) component is ignored. Since the autocorrelation signal C exhibits its periodicity better than the original signal, it can be used for periodicity discrimination.

In the present invention, the periodicity of the autocorrelation signal C is used. The interval between the maximum values appearing in the autocorrelation signal C can be obtained. The condition for obtaining the maximum value and its index is to obtain C (k) and k satisfying the following equation.

C (k-N) <C (k-N + 1) <… <C (k-1) <C (k)

C (k)> C (k + 1)>… > C (k + N-1)> C (k + N)

By adjusting N in the above formula, the sensitivity of the maximum value detection can be adjusted. The maximum value detection result is shown in FIG. 1 (b) as a local maxima.

When the original signal B is frequency-domain transformed, a dominant frequency component due to a regular biosignal can be obtained. The expected biosignal period is obtained based on this frequency component. In the present invention, the cycle thus obtained is defined as T_B.

Subsequently, the period T_B obtained using a Fourier Transform (FT) is compared with the maximum value interval of the autocorrelation signal. Assuming that the maximum x intervals of the autocorrelation signal are obtained, if the y intervals are identical within the respiratory period and the error range, the evaluation score at that time can be obtained by the following equation.

Evaluation score = y / x

For example, if all intervals are similar to the breathing cycle, the evaluation score is 1 out of 10. Therefore, the higher the reliability of the slow time window signal, the higher the evaluation score at that time.

1 (a) and 1 (b) are examples when the signal quality is good. On the other hand, (a) and (b) of Figure 2 is an example in the case of poor signal quality.

When the method proposed in the present invention is used to measure a biosignal based on the IR-UWB radar, it is possible to detect a case where the biosignal is distorted even when the subject's movement occurs, and breathing is unstable or excessively noisy. It is also possible to filter out cases.

The main contents of the present invention have been briefly described above. Hereinafter, the present invention will be summarized once again with reference to equations and the like.

In the case of measuring vital signs using an IR-UWB radar, it is difficult to accurately measure the vital signs when breathing and movement other than heart rate occur in the human body. If the slow-time windowed signal has components related to movements, the spectral aspect of the slow-time windowed signal changes significantly. This can lead to errors in measurements of respiratory rate and heart rate.

As a method for solving this problem, a method of simply scaling a motion size may be used. According to this method, the movement can be expressed as a difference value between the current signal and the previous signal.

However, this method has a problem in that it is difficult to filter the motion when the motion is similar to or smaller than the size of the breathing signal. In addition, in order to evaluate the quality of a biosignal, a factor that determines the period of the signal is required.

If the slow time windowed signal is periodic, it is easier to filter the signal, and it is also advantageous to decompose the signal in various ways. On the other hand, if the slow time windowed signal has a respiratory component of various frequencies, the reliability of the biosignal extracted from the slow time windowed signal is reduced.

The present invention proposes a method for simultaneously determining and scoring the motion and periodicity of a slow time window signal to a person in order to implement this function.

The received signal of the IR-UWB radar can be represented by the sum of each channel response, and one of these channel responses may be due to a human respiratory signal and a heart signal.

In the above, r (t, τ) denotes a received signal, and t and τ denote a slow-time factor and a fast-time factor, respectively. The fast time factor refers to the axis related to the range observed according to the received signal, and the slow time factor refers to the real time factor of the measured value.

p (τ) means a normalized received pulse, and τ _i means a delay of the received i-th impulse signal. A means the amplitude of the signal reflected from the human, A _i means the multiplied value.

τ _d (t) means delay, which changes to slow time due to distance changes due to breathing and heartbeat. τ _d (t) can be obtained as follows.

τ _d (t) = 2d (t) / c

In the above, d denotes a distance between a person and a radar, and c denotes a speed of light.

τ _selected may be _selected as a fast time component for extracting breathing signals and heart signals. The slow time windowed signal B (t) may be extracted from the fast time component based on Equation 1, which is expressed as follows.

In the above, T _s denotes a windowing period, and T ₀ denotes a time to start windowing.

B (t) includes both breathing information and heart rate information. The autocorrelation of B (t) can be expressed as C (k) as shown in Equation 3 below.

In the above, conj () means complex conjugate.

Since autocorrelation has a symmetric relationship, it is only necessary to consider when k is greater than 0 (k> 0). C (k) shows stronger periodicity in the main respiratory frequency components than B (t).

When there is no movement due to normal breathing, B (t) and C (k) show patterns as shown in FIGS. 1 (a) and (b). The components due to heart rate and noise have relatively smaller values than breathing. Therefore, C (k) shows only the respiratory component as shown in Fig. 1 (b).

In the present invention, the quality of a signal is evaluated based on periodicity using B (t) and C (k). If the signal quality is good, the periodicity of the slow time windowed signal is constant over the entire signal. In this case, the time between the local maxima of C (k) appears equal to the breathing cycle. The respiration period can be obtained using the dominant frequency component of the slow time windowed signal B (t). The peak value of C (k) can be obtained by finding k that satisfies the condition of Equation (4).

The sensitivity of peak detection can be adjusted by controlling N. For example, if N is set to 2, C (k) can be obtained as shown in FIG. 1 (b).

When intervals are obtained based on local maximums at C (k), these intervals are compared to the breathing cycle. Assuming that there is an x section in C (k), if y of this section coincides with the breathing period within the error range, then the score at that time becomes (x / y) points. That is, if all the sections of C (k) coincide with the breathing cycle, the score at that time is 1 point. In the present invention, the higher the quality of the signal, the higher the score.

If there are many local noise frequency components due to movements, the period of C (k) does not match the period obtained from the slow time windowed signal B (t). In this case, B (t) and C (k) appear as shown in Figs. 2 (a) and 2 (b). Referring to (b) of FIG. 2, some peaks having no regularity are captured due to the distortion of the signal, and thus the sections of C (k) are different from each other. Therefore, the score is very low regardless of the breathing cycle of B (t).

The method proposed in the present invention can be applied to cardiac signals for more accurate quality evaluation. The heart signal may be obtained by passing through a BPF (Band Pass Filter), or may be obtained using various decomposition methods. The heart signal can be weighted through Equations 3 and 4. Previous scores and scores from cardiac signals can be fused appropriately.

The present invention described above can be used for non-contact vital sign monitoring, heart rate measurement, respiratory rate measurement, and the like. Also, the present invention can be applied to a sleep monitoring device.

The embodiments of the present invention have been described above with reference to FIGS. 1 and 2. Hereinafter, a preferred form of the present invention that can be deduced from such an embodiment will be described.

3 is a block diagram schematically illustrating an apparatus for evaluating a signal quality for measuring biometric information according to a preferred embodiment of the present invention.

The quality evaluation device 100 is a device for evaluating the quality of a signal for measuring biometric information obtained using an IR-UWB (Impulse Radio Ultra Wide Band) radar, and measures the respiration rate and heart rate of a user located at a long distance with biometric information. Can be used when.

According to FIG. 3, the quality evaluation apparatus 100 includes an autocorrelation signal detection unit 110, a first period calculation unit 120, a score calculation unit 130, a power supply unit 140, and a main control unit 150.

The power supply unit 140 performs a function of supplying power to each component constituting the quality evaluation device 100.

The main control unit 150 performs a function of controlling the overall operation of each component constituting the quality evaluation device 100.

The autocorrelation signal detection unit 110 performs a function of detecting an autocorrelation signal based on a radar signal including biometric information.

The autocorrelation signal detector 110 may detect an autocorrelation signal based on a radar signal obtained using an IR-UWB radar.

The autocorrelation signal detector 110 acquires a slow time windowed signal associated with a time domain signal using an IR-UWB radar, and can detect an autocorrelation signal based on the slow time window signal. .

The first period calculator 120 performs a function of calculating first periods between peaks included in the autocorrelation signal detected by the autocorrelation signal detector 110.

The score calculation unit 130 compares the first periods calculated by the first period calculation unit 120 with the second periods obtained from the reference signal to determine whether the radar signal is suitable for measuring biometric information. It performs the function of calculating the score.

The score calculator 130 may calculate a value (y / x) obtained by dividing the number (y) of the first periods determined by the second periods by the total number (x) of the first periods as the score. .

The quality evaluation device 100 may further include a second period calculation unit 160.

The second period calculator 160 performs a function of calculating second periods based on dominant frequency components included in the reference signal by using a signal obtained by Fourier transforming a radar signal as a reference signal. do.

The quality evaluation device 100 may further include a signal suitability determination unit 170.

The signal suitability determining unit 170 performs a function of determining a radar signal as a signal suitable for measuring bio-information when the score is determined to be higher than the reference value by comparing the score with the reference value. For example, if the score calculated by the score calculating unit 130 is 0.7 and the reference value is 0.5, the signal suitability determining unit 170 may determine the current signal as a signal suitable for measuring biometric information according to the above determination criteria. .

Meanwhile, when it is determined that the score is less than the reference value, the signal suitability determining unit 170 determines the radar signal as a signal not suitable for measuring biometric information.

Next, an operation method of the quality evaluation device 300 will be described.

4 is a flowchart schematically illustrating a method for evaluating the quality of a signal for measuring biometric information according to a preferred embodiment of the present invention.

First, the autocorrelation signal detection unit 110 detects an autocorrelation signal based on a radar signal including biometric information (S210).

Thereafter, the first period calculator 120 calculates first periods between peaks included in the autocorrelation signal detected by the autocorrelation signal detector 110 (S220).

Thereafter, the score calculation unit 130 compares the first periods calculated by the first period calculation unit 120 with the second periods obtained from the reference signal to determine whether the radar signal is suitable for measuring biometric information. The score for the calculation is calculated (S230).

Meanwhile, between steps S220 and S230, the second period calculating unit 160 uses a signal obtained by Fourier transforming the radar signal as a reference signal, based on dominant frequency components included in the reference signal. The second periods can be calculated.

On the other hand, after the step S230, the signal suitability determining unit 170 compares the score with the reference value and determines that the radar signal is a signal suitable for measuring biometric information when it is determined that the score is equal to or greater than the reference value. On the other hand, when it is determined that the score is less than the reference value, the signal suitability determining unit 170 determines the radar signal as an unsuitable signal for measuring biometric information.

The fact that all components constituting the embodiments of the present invention described above are described as being combined or operated as one, the present invention is not necessarily limited to these embodiments. That is, within the object scope of the present invention, all of the components may be selectively combined and operated. In addition, although all of the components may be implemented by one independent hardware, a part or all of the components are selectively combined to perform a part or all of functions combined in one or a plurality of hardware. It may be implemented as a computer program having a. In addition, such a computer program is stored in a computer readable recording medium (Computer Readable Media), such as a USB memory, CD disk, flash memory, etc., and read and executed by a computer, thereby implementing an embodiment of the present invention. The recording medium of the computer program may include a magnetic recording medium, an optical recording medium, and the like.

In addition, all terms, including technical or scientific terms, have the same meaning as generally understood by a person skilled in the art to which the present invention pertains, unless otherwise defined in the detailed description. Commonly used terms, such as predefined terms, should be interpreted as being consistent with the contextual meaning of the related art, and are not to be interpreted as ideal or excessively formal meanings unless explicitly defined in the present invention.

The above description is merely illustrative of the technical idea of the present invention, and those of ordinary skill in the art to which the present invention pertains may make various modifications, changes, and substitutions without departing from the essential characteristics of the present invention. will be. Therefore, the embodiments and the accompanying drawings disclosed in the present invention are not intended to limit the technical spirit of the present invention, but to explain the scope of the technical spirit of the present invention. . The scope of protection of the present invention should be interpreted by the claims below, and all technical spirits within the scope equivalent thereto should be interpreted as being included in the scope of the present invention.

Claims (13)

An autocorrelation signal detection unit for detecting an autocorrelation signal based on a radar signal including biometric information;
A first period calculator configured to calculate first periods between peaks included in the autocorrelation signal; And
A score calculating unit that compares the first periods with the second periods obtained from the reference signal to calculate the score of the radar signal
Device for evaluating the quality of a signal for measuring biometric information, comprising a. According to claim 1,
The auto-correlation signal detection unit detects the auto-correlation signal based on the radar signal obtained by using an IR-UWB (Impulse Radio Ultra Wide Band) radar. According to claim 2,
The autocorrelation signal detector acquires a slow time windowed signal associated with a time domain signal using the IR-UWB radar, and detects the autocorrelation signal based on the slow time window signal. A device for evaluating the quality of a signal for measuring biometric information. According to claim 1,
A second period calculator that calculates the second periods based on dominant frequency components included in the reference signal by using a signal obtained by Fourier transforming the radar signal as the reference signal.
Device for evaluating the quality of a signal for measuring biometric information, further comprising a. According to claim 1,
The score calculation unit evaluates the quality of the signal for biometric information measurement, characterized in that the value obtained by dividing the number of the first periods determined to match the second periods by the total number of the first periods is calculated as the score. Device. According to claim 1,
A signal suitability determining unit comparing the score with a reference value to determine whether the score is greater than or equal to the reference value
Device for evaluating the quality of a signal for measuring biometric information, further comprising a. According to claim 1,
The quality evaluation device is a device for evaluating the quality of a signal for measuring bio-information, characterized in that it is used to measure the respiration rate and heart rate of a user located at a long distance with the bio-information. As a method performed in the apparatus for evaluating the quality of a signal for measuring biometric information,
Detecting an autocorrelation signal based on a radar signal including biometric information;
Calculating first periods between peaks included in the autocorrelation signal; And
Calculating a score of the radar signal by comparing the first periods with the second periods obtained from the reference signal
Method for evaluating the quality of a signal for measuring biometric information, comprising a. The method of claim 8,
In the detecting, the autocorrelation signal is detected based on the radar signal obtained by using an IR-UWB (Impulse Radio Ultra Wide Band) radar. The method of claim 9,
In the detecting, a slow time windowed signal related to a time domain signal is obtained using the IR-UWB radar, and the autocorrelation signal is detected based on the slow time window signal. A method for evaluating the quality of a signal for measuring biometric information. The method of claim 8,
Calculating the second periods based on dominant frequency components included in the reference signal using a signal obtained by Fourier transforming the radar signal as the reference signal
Method for evaluating the quality of a signal for measuring biometric information, further comprising a. The method of claim 8,
Comparing the score with a reference value to determine whether the score is greater than or equal to the reference value
Method for evaluating the quality of a signal for measuring biometric information, further comprising a. A computer program stored in a computer readable medium for executing a method for evaluating the quality of a signal for measuring biometric information according to any one of claims 8 to 12 in a computer.

Images