KR102291083B1 - Signal Processing Method for Determining The Presence of Vital Signal and System Thereof - Google Patents

Abstract

The present invention relates to a signal processing method and a signal processing system for determining the presence or absence of a biosignal. According to the present invention, an electromagnetic wave for detecting a biosignal of a human body is transmitted, a reflected wave is received, and a waveform of the received reflected wave is provided. The DC component is removed from the data, the amplitude of the waveform is made positive for the waveform data from which the DC component is removed, the signal-to-noise ratio is increased by amplifying the positive waveform data, and the signal-to-noise ratio is increased in the waveform data. Disclosed is a technology capable of accurately determining the presence or absence of a person in an arbitrary place by filtering noise and judging the presence or absence of a bio-signal, thereby improving the accuracy and reliability of judging the presence of a bio-signal.

Description

Signal Processing Method for Determining The Presence of Vital Signal and System Thereof

The present invention relates to a signal processing method and a signal processing system for determining the presence or absence of a biosignal from electromagnetic waves measured in a non-contact manner in order to determine whether a person exists in an arbitrary place or location.

A safety accident may occur because the guardian does not know the state of the infant left in the vehicle. In addition, when fragments of a building occur due to a natural disaster or a building accident, it is important to accurately determine whether there are any buried victims and where they were buried.

As such, various technologies are being researched and developed to accurately determine whether a person exists in a specific place or location. Among these technologies, there is a technology for determining whether a person is present in a specific place or location by determining the presence or absence of a human biosignal from a signal sensed in a non-contact manner.

Signals sensed by the non-contact method include not only human biosignals, but also various noises such as reflected waves from other objects.

Accordingly, there has been a demand for a technology capable of accurately determining the presence or absence of a biosignal.

Republic of Korea Patent Registration No. 10-1804681

An object of the present invention is to solve the conventional problems as described above, and to provide a signal processing method and system for determining the presence or absence of a biosignal from a signal measured in order to determine the presence or absence of a person in an arbitrary space. have.

In accordance with an embodiment of the present invention for achieving the above object, there is provided a signal processing method for determining the presence or absence of a biosignal, comprising: a signal processing system transmitting electromagnetic waves for detecting a biosignal of a human body; a receiving step of receiving, by the signal processing system, a reflected wave from which the electromagnetic wave transmitted in the transmitting step is reflected and returned; a DC offset step in which the signal processing system removes a DC component from the waveform data of the reflected wave received in the receiving step; a positive-signaling step in which the signal processing system makes the amplitude of a waveform positive with respect to the waveform data from which the DC component is removed in the DC offset step; an amplification step in which the signal processing system amplifies the waveform data acquired in the positive acquisition step to increase a signal-to-noise ratio; a filtering step of filtering, by the signal processing system, the noise from the waveform data so that noise is reduced or removed from the waveform data whose signal-to-noise ratio is increased in the amplification step; and a determination step of determining, by the signal processing system, the presence or absence of the biosignal in the waveform data obtained by filtering the noise from the waveform data in the filtering step. It may be characterized as one of including.

Here, in the DC offset step, another feature may be that the signal processing system removes the DC component from the waveform data by applying a curve-fitting to the waveform data.

Here, in the positiveization step, another feature may be that the waveform data becomes positive by applying a root-sum of square to the amplitude of the waveform.

Here, in the amplification step, it may be further characterized in that the waveform data is amplified by integrating the waveform data with respect to time.

Here, in the filtering step, another feature may be to filter the noise from the waveform data by applying a Savitzky-Golay filter to the waveform data.

A signal processing system for determining the presence or absence of a biosignal according to an embodiment of the present invention for achieving the above object includes: a transmitter for transmitting electromagnetic waves for detecting a biosignal of a human body; a receiving unit receiving a reflected wave that is reflected back by the electromagnetic wave transmitted by the transmitting unit; Controls the transmitter to transmit the electromagnetic wave, receives the waveform data of the reflected wave from the receiver, removes a DC component from the waveform data of the reflected wave received from the receiver, and positively increases the amplitude of the waveform of the waveform data and amplifying the waveform data to increase the signal-to-noise ratio, filtering noise from the waveform data with the increased signal-to-noise ratio to reduce or remove noise from the waveform data, and to reduce or remove noise from the filtered waveform data. a processor unit for determining the presence or absence of a signal; and a storage unit for storing a command executed by the processor or the waveform data to determine the presence or absence of the biosignal. It may be characterized as one of including.

Here, as another feature in that the processor unit removes the DC component from the waveform data, the processor unit removes the DC component from the waveform data by applying a curve-fitting to the waveform data. You may.

Here, when the processor unit quantifies the waveform data, another feature may be that the quantization is performed by the processor unit applying a root-sum of square to the amplitude of the waveform of the waveform data. .

Here, the amplification of the waveform data by the processor unit may be further characterized in that the amplification of the waveform data is performed by the processor unit integrating the waveform data with respect to time.

Herein, the filtering by the processor may be further characterized in that the processor filters the noise from the waveform data by applying a Savitzky-Golay filter to the waveform data.

The signal processing method and signal processing system for determining the presence or absence of a bio-signal according to the present invention can determine the presence or absence of a bio-signal from small-sized waveform data measured at a spaced distance, and numerically accumulated waveform data signals. After significantly increasing the signal-to-noise ratio through analysis, the presence or absence of a biosignal is identified, thereby increasing the accuracy and reliability of judgment.

1 is a block diagram schematically showing a signal processing system capable of performing a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
2 is a flowchart schematically illustrating a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
3 is a diagram schematically illustrating waveform data of a reflected wave in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
4 is a diagram schematically showing waveform data of a reflected wave and a graph according to a linearly modeled regression equation in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
5 is a diagram schematically illustrating waveform data after DC offset processing is performed on original waveform data in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
6 is a diagram schematically illustrating positive waveform data by rooting sum of squares on DC offset-processed waveform data in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
7 is a diagram schematically illustrating the integration of waveform data with respect to time in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
8 is a diagram schematically illustrating waveform data including noise before being filtered in the signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.
9 is a diagram schematically illustrating waveform data filtered in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

Hereinafter, a preferred embodiment will be described with reference to the accompanying drawings so that the present invention can be understood in more detail.

Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to specific embodiments, and it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention.

Terms such as first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being “connected” or “connected” to another component, it is understood that the other component may be directly connected or connected to the other component, but other components may exist in between. it should be On the other hand, when it is said that a certain element is "directly connected" or "directly connected" to another element, it should be understood that no other element is present in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It should be understood that this does not preclude the existence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the accompanying drawings. In describing the present invention, in order to facilitate the overall understanding, the same reference numerals are used for the same components in the drawings, and duplicate descriptions of the same components are omitted.

First, a signal processing system capable of performing a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention will be described with reference to FIG. 1 , and then to determine the presence or absence of a biosignal according to an embodiment of the present invention A signal processing method for this will be described.

1 is a block diagram schematically showing a signal processing system capable of performing a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

Referring to FIG. 1 , a signal processing system (hereinafter simply referred to as a 'signal processing system') 100 for determining the presence or absence of a biosignal according to an embodiment of the present invention includes a transmitter 140, a receiver 150, It may include a processor unit 110 and a storage unit 120 .

Also, the signal processing system 100 may further include a network interface device 130 connected to a network to perform communication.

In addition, each component included in the signal processing system 100 may be connected by a bus 170 to communicate with each other.

The transmitter 140 transmits an electromagnetic wave for detecting a biosignal of the human body. The transmitter 140 follows the control of the processor 110 .

The receiver 150 receives the reflected wave that is reflected back by the electromagnetic wave transmitted by the transmitter. Waveform data of the reflected wave received by the receiver 150 is transferred to the processor 110 . The receiving unit 150 follows the control of the processor 110 .

The processor unit 110 controls the transmitter 140 and the receiver 150 .

Then, the processor unit 110 performs signal processing for determining the presence or absence of a human body signal from the waveform data received from the receiving unit 150 .

To this end, the processor 110 removes the DC component from the waveform data of the reflected wave received from the receiver 150 .

In order for the processor unit 110 to remove the DC component from the waveform data, the processor unit 110 may remove the DC component from the waveform data by applying a curve-fitting to the waveform data.

Then, the processor unit 110 posits the amplitude of the waveform of the waveform data from which the DC component has been removed. Since there are parts where the amplitude of the waveform appears as a negative value, it is desirable to make it positive.

In order for the processor unit 110 to quantify the waveform data, the processor unit 110 applies a root-sum of square to the amplitude of the waveform of the waveform data to make the waveform data positive.

In addition, the processor unit 110 amplifies the positive waveform data to increase the signal-to-noise ratio. The larger the signal-to-noise ratio, the easier it is to distinguish the signal from the noise, so it is desirable to increase the signal-to-noise ratio.

In order to amplify the positive waveform data, the processor unit 110 integrates the waveform data with respect to time to amplify the waveform data.

In addition, the processor unit 110 filters noise from the waveform data having an increased signal-to-noise ratio to reduce or remove noise from the waveform data.

In order for the processor unit 110 to reduce or remove noise from the waveform data, the processor unit 110 may apply a Savitzky-Golay filter to the waveform data to reduce or remove noise from the waveform data.

With respect to the filtered waveform data as described above, the processor unit 110 determines the presence or absence of a biosignal. Determining whether there is a bio-signal in the filtered waveform data is determined by the processor unit 110 comparing the waveform of the bio-signal with the filtered waveform data and determining whether the waveform of the bio-signal is included in the filtered waveform data. can

Standard waveform data of the biosignal may be stored in the storage unit 120 so that the processor unit 110 can determine whether the filtered wave data includes the biosignal.

As described above, the storage unit 120 may store a command or waveform data that the processor unit 110 performs to determine the presence or absence of a biosignal. The storage unit 120 may transmit a command to be executed by the processor unit 110 to determine the presence or absence of a biosignal, and may store waveform data according to control in the processor unit 110 .

Using the signal processing system 100 for determining the presence or absence of such a bio-signal, the following signal processing method for determining the presence or absence of a bio-signal may be performed.

Next, a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention will be described with further reference to FIG. 2 .

2 is a flowchart schematically illustrating a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

Referring to FIG. 2 , the signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention includes a transmitting step (S110), a receiving step (S120), a DC offset step (S130), a positive handing step (S140), It may include an amplification step (S150), a filtering step (S160) and a determination step (S170).

<< S110 >>

The transmitting step ( S110 ) is a step in which the transmitting unit 140 of the signal processing system 100 transmits an electromagnetic wave for detecting a biosignal of the human body. In order to determine whether a person exists in an arbitrary location or space, the transmitter 140 transmits an electromagnetic wave toward an arbitrary location or space.

<< S120 >> ,

The receiving step (S120) is a step in which the receiving unit 150 of the signal processing system 100 receives a reflected wave that is reflected back by the electromagnetic wave transmitted from the transmitting unit 140 of the signal processing system 100 in the transmitting step (S110). am.

When the electromagnetic wave transmitted from the transmitter 140 is reflected by the human body in the sending step S110, the received reflected wave includes a biological signal of the human body.

The reflected wave received by the receiving unit 150 in the receiving step S120 is signal-processed by the processor 150 through various steps after the receiving step S130 as waveform data.

<< S130 >>

The DC offset step (S130) is a step in which the processor unit 110 removes the DC component from the waveform data of the reflected wave received by the receiving unit 150 in the receiving step (S120).

Since the processor unit 110 applies a linear regression (curve-fitting) to the waveform data, the DC component may be removed from the waveform data.

Linear regression (curve-fitting) is an analysis method that models the linear correlation between the dependent variable y and one or more independent variables or explanatory variables X. Modeling based on one independent variable can be called simple linear regression. Linear regression models a regression equation using a linear predictive function, and an unknown variable is estimated from input data.

Here, linear regression analysis may be applied to maintain a constant value within the section or to remove a linearly deformed DC value.

에 대하여 종속 변수

와 독립변수

사이의 선형 관계를 다음과 같은 형태로 모델링 한다.Linear regression is a set of given waveform data.

about the dependent variable

and independent variable

The linear relationship between them is modeled in the following form.

Expressing this expression in vector form, it can be expressed as:

는 오차 항이며, 종속 변수와 독립 변수 사이의 오차를 나타낸다.where a is the coefficient of the independent variable, and p is the number of parameters estimated by linear regression.

is the error term and represents the error between the dependent variable and the independent variable.

In linear regression, we find the optimal linear regression equation that expresses the relationship between the variables y and x. The best way to express the relationship between the variables y and x is to find the straight line closest to the points represented by the coordinates of (x, y). . That is, it is an expression of a straight line in which the sum of the distances in the coordinates is the minimum. If a that satisfies the equation of this straight line is found using the least squares method, the value can be expressed as follows.

The processor unit 110 applies such a linear regression method to the waveform data. Here, it will be described with further reference to FIGS. 3 to 5 . First, FIG. 3 is a graph schematically illustrating waveform data of a reflected wave in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

The processor 110 receives the waveform data as shown in FIG. 3 from the receiver 150 and applies the linear regression method.

4 is a diagram schematically showing waveform data of a reflected wave and a graph according to a linearly modeled regression equation in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

4 , the processor unit 110 finds coefficients of a straight line for optimal linear regression in the given raw waveform data.

5 is a diagram schematically illustrating waveform data after the processor 110 performs DC offset processing on the original waveform data in the signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

In order for the processor unit 110 to remove the DC offset, which is a linear value that changes with time, from the waveform data, linear regression is applied to the waveform data as shown in FIG. 4 to obtain a straight line that is a fitting line. If subtracted from the waveform data, a waveform data graph as shown in FIG. 5 is obtained.

In this way, the processor unit 110 applies linear regression to the original waveform data obtained by receiving the reflected wave in the receiving step (S120) to remove the DC component.

<< S140 >>

The positive step (S140) is a step performed after the DC offset step (S130), and the processor unit 110 makes the amplitude of the waveform of the waveform data from which the DC component is removed in the DC offset step (S130) positive. .

6 is a diagram schematically illustrating positive waveform data by performing root-processing of the sum of squares on the DC offset-processed waveform data in the signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

In order to quantify the amplitude of the waveform of the waveform data from which the DC component has been removed in the DC offset step (S130), the processor unit 110 may quantify it using the root-sum of square, FIG. As referenced in 6, the amplitude of the waveform is positive.

In this way, the positive waveform data is amplified by the processor unit 110 in the amplification step (S150).

<< S150 >>

The amplification step (S150) is a step that can be performed after the positiveization step (S140). The processor unit 110 amplifies the waveform data from which the DC component has been removed through linear regression to amplify the signal-to-noise ratio. .

7 is a diagram schematically illustrating the integration of waveform data with respect to time in a signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention.

The larger the signal-to-noise ratio of the waveform data, the easier it is to distinguish the signal from the noise, so it is desirable to increase the signal-to-noise ratio. Accordingly, the processor unit 110 integrates the waveform data with respect to time in order to amplify the positive waveform data in step S140, so that the waveform data is amplified as shown in FIG.

<< S160 >>

The filtering step (S160) is a step that may be performed after the amplifying step (S150), and the filtering step (S160) is the processor unit 110 such that noise is reduced or removed from the waveform data whose signal-to-noise ratio is increased in the amplifying step (S150). ) is the filtering step.

8 is a diagram schematically illustrating waveform data including noise before being filtered in the signal processing method for determining the presence or absence of a biosignal according to an embodiment of the present invention, and FIG. 9 is a biometric data according to an embodiment of the present invention. It is a diagram schematically showing the filtered waveform data in the signal processing method for determining the presence or absence of a signal.

First, as shown in FIG. 8 , since noise exists in the waveform data, it is difficult to analyze the waveform of the signal. Accordingly, in the amplification step ( S150 ), the processor unit 110 filters the waveform data with the increased signal-to-noise ratio using a Savitzky-Golay filter in order to remove or reduce noise.

The Sabatsky-Golay filter is a signal smoothing method using linear regression. The Sabatsuki-Golay filter is a filter that determines a value at each data point by finding a random nth-order polynomial that best matches the surrounding point at each data point when there is data given at regular intervals.

The Sabatsuki-Golay filter determines the current value by using a polynomial created by regressing the data and adjacent data into a polynomial. The regression process by analyzing the data can be expressed in the following way.

는 포인트에서의 데이터값을 나타낸다. 그리고. n은 평활화에 사용되는 데이터 포인트의 수이며 측정된 데이터에 따라 임의로 설정될 수 있다.

는 설정해주는 다항식의 차수를 나타낸다. h는 표준화 계수이며, n의 수치에 따라 결정되는 값이다. here

represents the data value at the point. And. n is the number of data points used for smoothing and may be arbitrarily set according to the measured data.

represents the degree of the polynomial to be set. h is a standardization coefficient, and is a value determined according to the value of n.

When such a Sabatsuki-Golay filter is applied to waveform data, noise included in the waveform data can be reduced or removed. Accordingly, if noise is removed or reduced through filtering using the Sabatsuki-Golay filter, noise is reduced or eliminated as shown in FIG. 9 .

<< S170 >>

The determination step S170 is a step in which the processor unit 110 of the signal processing system 100 filters noise from the waveform data in the filtering step S160 to determine the presence or absence of a biosignal in the waveform data.

That is, the processor unit 110 determines whether or not the biosignal is included in the waveform data that has undergone the quantization step (S140), the amplification step (S150), and the filtering step (S160) after the DC offset step (S130).

Determining whether there is a bio-signal in the filtered waveform data is determined by the processor unit 110 comparing the bio-signal waveform with the filtered waveform data and determining whether the bio-signal waveform is included in the filtered waveform data. can

The standard waveform data of the biosignal may be stored in the storage unit 120 so that the processor unit 110 can determine whether the filtered wave data includes the biosignal.

If the bio-signal is not included in the waveform data, the processor unit 110 determines that the person is absent because there is no bio-signal. If the biosignal is included in the waveform data, it is determined that a person is present.

As described above, the presence or absence of a biosignal can be accurately determined through the method of processing a signal, which is waveform data, so that it is possible to accurately determine whether a person exists in an arbitrary space.

As described above, it is possible to accurately determine whether a person is present in an arbitrary place through the signal processing method and signal processing system for determining the presence or absence of a biosignal according to an embodiment of the present invention.

Therefore, by using the signal processing method and the signal processing system for determining the presence or absence of a biosignal according to the present invention, it is possible to prevent an accident due to an infant being left in the vehicle in advance. In addition, it can be used to determine whether an elderly person living alone is alive or dead in real time, and it can be used to determine the location of a victim in a collapsed building or a fire site.

As described above, the detailed description of the present invention has been made by the embodiments with reference to the accompanying drawings, but since the above-described embodiments have only been described with reference to the preferred embodiments of the present invention, the present invention It should not be construed as being limited only to the embodiments, and the scope of the present invention should be understood as the following claims and their equivalents.

100: signal processing system 110: processor unit
120: storage unit 130: network interface device
140: transmitter 150: receiver
170: bus

Claims (10)

a signal processing system transmitting an electromagnetic wave for detecting a human body signal;
a receiving step of receiving, by the signal processing system, a reflected wave from which the electromagnetic wave transmitted in the transmitting step is reflected and returned;
a DC offset step in which the signal processing system removes a DC component from the waveform data of the reflected wave received in the receiving step;
a positive-signaling step in which the signal processing system makes the amplitude of a waveform positive with respect to the waveform data from which the DC component is removed in the DC offset step;
an amplification step in which the signal processing system amplifies the waveform data acquired in the positive acquisition step to increase a signal-to-noise ratio;
a filtering step of filtering, by the signal processing system, the noise from the waveform data so that noise is reduced or removed from the waveform data whose signal-to-noise ratio is increased in the amplification step; and
a determination step of determining, by the signal processing system, the presence or absence of the biosignal in the waveform data obtained by filtering the noise from the waveform data in the filtering step; including,
In the DC offset step,
characterized in that the signal processing system removes the DC component from the waveform data by applying a linear regression (curve-fitting) to the waveform data,
In the amniotic fluid step,
Characterized in that it becomes positive by applying a root-sum of square to the amplitude of the waveform of the waveform data,
A signal processing method for determining the presence or absence of a biosignal.
delete delete The method of claim 1,
In the amplification step,
characterized in that the waveform data is amplified by integrating the waveform data with respect to time,
A signal processing method for determining the presence or absence of a biosignal.
5. The method of claim 4,
In the filtering step,
characterized in that the noise is filtered from the waveform data by applying a Savitzky-Golay filter to the waveform data,
A signal processing method for determining the presence or absence of a biosignal.
a transmitter that transmits an electromagnetic wave for detecting a biosignal of a human body;
a receiving unit receiving a reflected wave that is reflected back by the electromagnetic wave transmitted by the transmitting unit;
Controls the transmitter to transmit the electromagnetic wave, receives the waveform data of the reflected wave from the receiver, removes a DC component from the waveform data of the reflected wave received from the receiver, and positiveizes the amplitude of the waveform of the waveform data and amplifying the waveform data to increase the signal-to-noise ratio, filtering noise from the waveform data with the increased signal-to-noise ratio to reduce or remove noise from the waveform data, and to reduce or remove noise from the filtered waveform data. a processor unit for determining the presence or absence of a signal; and
a storage unit for storing a command executed by the processor or the waveform data to determine the presence or absence of the biosignal; including,
The processor removes the DC component from the waveform data,
The processor unit is characterized in that the DC component is removed from the waveform data by applying a linear regression (curve-fitting) to the waveform data,
When the processor unit quantifies the waveform data,
It characterized in that the positive number is made by the processor unit applying a root-sum of square to the amplitude of the waveform of the waveform data,
A signal processing system for determining the presence or absence of a biosignal.
delete delete 7. The method of claim 6,
The processor amplifies the waveform data,
It characterized in that the amplification of the waveform data is made by the processor unit integrating the waveform data with respect to time,
A signal processing system for determining the presence or absence of a biosignal.
10. The method of claim 9,
That the processor unit performs the filtering,
characterized in that the processor unit filters the noise from the waveform data by applying a Savitzky-Golay filter to the waveform data,
A signal processing system for determining the presence or absence of a biosignal.

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