KR20170119162A - Arrhythmia diagnosis apparatus usnig electrocardiogram signal and method using the same - Google Patents

Abstract

The present invention relates to an arrhythmia diagnosis apparatus using electrocardiogram signals and an arrhythmia diagnosis method using the same.
The method of diagnosing an arrhythmia using an arrhythmia diagnosis apparatus according to the present invention comprises the steps of receiving an electrocardiogram signal of a subject, time information of a starting point, an ending point and an R peak point of each QRS complex of the electrocardiogram signal Calculating the RR interval time and the duration of the QRS group using the time information of the starting point, the ending point and the R peak point of each QRS group, and calculating the calculated RR interval time and the QRS group duration And diagnosing an arrhythmia of the subject by using the measurement data.
As described above, according to the present invention, since the RR interval time of the electrocardiogram signal and the QRS group duration are simultaneously used, the accuracy of the arrhythmia diagnosis of the subject can be improved. In addition, since data for each waveform is calculated for the arrhythmia determination without using the average value of the RR interval time and the QRS group duration time, it is possible to detect minute changes according to the heartbeat change of the subject, which is effective for diagnosis of arrhythmia prevention diagnosis .

Description

TECHNICAL FIELD [0001] The present invention relates to an arrhythmia diagnosis apparatus using an electrocardiogram signal and an arrhythmia diagnosis method using the same. BACKGROUND ART [0002] ARRHYTHMIA DIAGNOSIS APPARATUS USNIG ELECTROCARDIOGRAM SIGNAL AND METHOD USING THE SAME [0003]

The present invention relates to an arrhythmia diagnosis apparatus using an electrocardiogram signal and an arrhythmia diagnosis method using the same, and more particularly, to an arrhythmia diagnosis apparatus using an electrocardiogram signal for improving the accuracy of an arrhythmia diagnosis and an arrhythmia diagnosis method using the same.

The heart is composed of two left and right atria and ventricles and contracts and relaxes by electrical stimulation of the heart muscle. At this time, there may be a case where the electrical stimulation is not generated in the heart and the heart is not delivered, or abnormally rapid electrical stimulation is generated, so that it may not be regularly shrunk and relaxed. This is called arrhythmia.

If electrical stimulation is not produced in the heart, the ability of the heart to discharge blood is reduced, resulting in a reduction in the amount of blood that is exhaled, and symptoms such as dyspnea, dizziness, and syncope may occur. In addition, if a malignant arrhythmia such as ventricular contraction, ventricular tachycardia, or ventricular fibrillation occurs, the cardiac function is instantaneously paralyzed instantaneously and can die immediately from a heart attack.

Conversely, if an abnormally rapid electrical stimulation is produced, there is no time for the heart to physically contract and relax. This may result in symptoms such as chest throbbing, dyspnea and dizziness, as well as complications such as heart failure or cerebral infarction, which is fatal to health.

Therefore, if an arrhythmia occurs, you should immediately receive emergency treatment. However, since arrhythmias occur frequently in patients, it is not easy to diagnose and treat them early if the ECG is not routinely examined.

Therefore, it is urgent to develop a diagnostic device capable of promptly estimating an arrhythmia and diagnosing its arrhythmia by carrying it on a daily basis.

The technology of the background of the present invention is disclosed in Korean Patent Laid-Open No. 10-2012-0133793 (published Dec. 12, 2012).

SUMMARY OF THE INVENTION The present invention provides an arrhythmia diagnosis device using an electrocardiogram signal for improving the accuracy of an arrhythmia diagnosis and an arrhythmia diagnosis method using the same.

According to an aspect of the present invention, there is provided an arrhythmia diagnosis method using an arrhythmia diagnosis apparatus, comprising: receiving an electrocardiogram signal of a subject; inputting a start point of each QRS complex of the electrocardiogram signal, Calculating the RR interval time and the QRS group duration using the time information of the start point, the end point, and the R peak point of each QRS group; And diagnosing an arrhythmia of the subject using the RR interval time and the QRS group duration.

And removing a noise signal included in the electrocardiogram signal and a linear trend signal included in the electrocardiogram signal from the electrocardiogram signal.

The step of calculating the RR interval time and each QRS group duration includes calculating a difference value between consecutive R peak point times and calculating a difference value between a start point time and an end point time of each QRS group .

The step of diagnosing an arrhythmia of the subject includes generating a distribution pattern by matching the calculated RR interval time and the QRS group duration with a two-dimensional coordinate system in which the RR interval time is uniaxial and the QRS group duration is another axis And diagnosing an arrhythmia of the subject by comparing the generated distribution pattern with a previously stored arrhythmia pattern.

Generating the distribution pattern comprises generating coordinate values for the two-dimensional coordinate system by coupling the RRS interval time and the QRS group duration including an R peak point at which the RR interval starts, Dimensional coordinate system in accordance with a plurality of reference values, calculating a distribution map of the matched coordinate values for each of the predetermined zones, Selecting a region corresponding to a distribution map larger than the set threshold value, and generating the distribution pattern according to the selected region.

The step of diagnosing the arrhythmia of the subject includes the step of determining the degree of similarity between the generated distribution pattern and the pre-stored arrhythmia pattern, and the step of determining the arrhythmia pattern having the highest degree of similarity as the diagnosis result of the subject .

An arrhythmia diagnosis apparatus according to another embodiment of the present invention includes an input unit for receiving an electrocardiogram signal of a subject, an acquiring unit for acquiring time information of a start point, an end point, and an R peak point of each QRS complex of the electrocardiogram signal Calculating a RR interval time and a QRS group duration using time information of a starting point, an ending point, and an R peak point of each QRS complex, and calculating the RR interval time and the QRS group duration And diagnosing the arrhythmia of the subject using time.

As described above, according to the present invention, since the RR interval time of the electrocardiogram signal and the QRS group duration are simultaneously used, the accuracy of the arrhythmia diagnosis of the subject can be improved. In addition, since data for each waveform is calculated for the arrhythmia determination without using the average value of the RR interval time and the QRS group duration time, it is possible to detect minute changes according to the heartbeat change of the subject, which is effective for diagnosis of arrhythmia prevention diagnosis .

In addition, since the degree of similarity of the distribution pattern is determined without complicated arithmetic operation and the arrhythmia of the subject is diagnosed, the computation speed is fast, and it is possible to implement it with relatively simple equipment.

1 is a block diagram of an arrhythmia diagnosis apparatus according to an embodiment of the present invention.
2 is a flowchart of an arrhythmia diagnosis method according to an embodiment of the present invention.
FIG. 3 is a view for explaining the step S220 of FIG.
4 is a view for explaining the step S230 of FIG.
5 is a view for explaining the step S240 of FIG.
FIG. 6 is a detailed flowchart of step S250 of FIG.
FIG. 7 is a detailed flowchart of step S260 of FIG.
8 is a view for explaining the step S260 of FIG.
FIG. 9 is a detailed flowchart of step S270 of FIG.
10 is a view for explaining an arrhythmia pattern according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when an element is referred to as "comprising ", it means that it can include other elements as well, without excluding other elements unless specifically stated otherwise.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention.

First, a configuration of an arrhythmia diagnosis apparatus 100 according to an embodiment of the present invention will be described with reference to FIG. 1 is a block diagram of an arrhythmia diagnosis apparatus according to an embodiment of the present invention.

1, an arrhythmia diagnosis apparatus 100 according to an embodiment of the present invention includes an input unit 110, an acquisition unit 130, an operation unit 140, and a diagnosis unit 150, and the filtering unit 120 ).

First, the input unit 110 receives the electrocardiogram signal of the subject. At this time, the electrocardiogram signal can be measured through an electrocardiogram measuring sensor attached to the body of the subject. Meanwhile, the electrocardiogram measuring sensor may be connected to the input unit 110 by wire or wireless communication, and may transmit the measured electrocardiogram signal to the input unit 110.

Next, the filtering unit 120 removes a noise signal included in the electrocardiogram signal and a linear trend signal included in the electrocardiogram signal from the electrocardiogram signal.

Next, the acquisition unit 130 acquires time information of the start point, the end point, and the R peak point of each QRS complex (QRS complex) of the electrocardiogram signal.

Next, the operation unit 140 calculates the RR interval time and the QRS group duration using the time information of the start point, the end point, and the R peak point of each QRS group.

Specifically, the operation unit 140 calculates a difference value of consecutive R peak point times, and the difference value is an RR interval time. In addition, the operation unit 140 calculates the difference value between the start point and the end point time of each QRS group, and the difference value is the QRS group duration.

Next, the diagnosis unit 150 diagnoses the arrhythmia of the subject using the calculated RR interval time and the QRS group duration.

First, the diagnosis unit 150 generates a distribution pattern by matching the RR interval time and the QRS group duration calculated in the two-dimensional coordinate system having the RRS interval time as one axis and the QRS group duration as the other axis.

Specifically, the diagnosis unit 150 generates the coordinate values for the two-dimensional coordinate system by coupling the RRS interval time and the QRS group duration including the R peak point at which the RR interval starts. Then, the diagnosis unit 150 matches the generated coordinate values to the two-dimensional coordinate system. Then, the diagnosis unit 150 sets a zone in the two-dimensional coordinate system according to a plurality of reference values. Thereafter, the diagnosis unit 150 calculates a distribution map of the coordinate values matched for each set zone. Then, the diagnosis unit 150 selects a region corresponding to a distribution map that is larger than a predetermined threshold value among the calculated distribution maps, and generates a distribution pattern according to the selected region.

Next, the diagnosis unit 150 diagnoses the arrhythmia of the subject by comparing the generated distribution pattern with the pre-stored arrhythmia pattern.

Specifically, the diagnosis unit 150 determines the degree of similarity between the generated distribution pattern and the pre-stored arrhythmia pattern. Then, the diagnosis unit 150 determines the arrhythmia pattern having the highest degree of similarity as the diagnosis result of the subject.

2 to 10, an arrhythmia diagnosis method using the arrhythmia diagnosis apparatus 100 according to an embodiment of the present invention will be described. 2 is a flowchart of an arrhythmia diagnosis method according to an embodiment of the present invention.

2, an input unit 110 of an arrhythmia diagnosis apparatus 100 according to an embodiment of the present invention receives an electrocardiogram signal of a subject (S210).

Then, the filtering unit 120 removes a noise signal included in the electrocardiogram signal from the electrocardiogram signal (S220). FIG. 3 is a view for explaining the step S220 of FIG. As shown in FIG. 3, the ECG signal (raw ECG) input by the input unit 110 includes a continuous fine amplitude change. Herein, the fine amplitude change refers to a noise signal that is input when the electrocardiogram of the subject is measured or when the input unit 110 receives the electrocardiogram signal.

If the electrocardiogram signal including such a noise signal is used as it is, an error may occur in the diagnosis of an arrhythmia. Therefore, the filtering unit 120 removes the noise signal from the electrocardiogram signal through step S220. Then, the denoise ECG signal with the noise signal removed as shown in FIG. 3 can be obtained.

Then, the filtering unit 120 removes the linear trend signal included in the electrocardiogram signal (S230). 4 is a view for explaining the step S230 of FIG. Referring to FIG. 4, it can be seen that the signal amplitude linearly increases with time as the ECG signal (denoise ECG) from which the noise signal is removed. Here, the linear signal magnitude increase means a trend ECG that is measured when the subject's electrocardiogram is measured or when the input unit 110 receives the electrocardiogram signal.

An error in the diagnosis of arrhythmia may occur if the electrocardiogram signal including the linear trending signal (trend ECG) is used as it is. Therefore, the filtering unit 120 removes the linear trending signal (trend ECG) from the electrocardiogram signal through step S230. Then, the ECG signal (trend ECG) from which the linear trending signal (trend ECG) as shown in FIG. 4 is removed can be obtained.

Next, the acquiring unit 130 acquires time information of the start point, the end point, and the R peak point of each QRS complex QRS complex of the electrocardiogram signal (S240). 5 is a view for explaining the step S240 of FIG. Referring to FIG. 5, the electrocardiogram signal includes a plurality of QRSs QRS ₁ , QRS ₂ ,. Each QRS group includes start points Q ₁ , Q ₂ , ..., end points S ₁ , S ₂ , ..., and R peak points R ₁ , R ₂ ,. Accordingly, the acquisition unit 130 acquires the time (Q ₁ , Q ₂ , ...), the end point (S ₁ , S ₂ , ...) and the R peak point (R ₁ , R ₂ , And time information of each point is obtained.

In step S240, the acquiring unit 130 may use the electrocardiogram signal that has undergone the signal processing of steps S220 and S230, and the number of the QRS complexes may vary according to the length of the received electrocardiogram signal.

Then, the operation unit 140 calculates the RR interval time and the QRS group duration using the time information of the start point, the end point, and the R peak point of each obtained QRS group (S250). FIG. 6 is a detailed flowchart of step S250 of FIG.

Referring to FIG. 6, the operation unit 140 calculates a difference value between consecutive R peak point times (S251). 5, the calculation unit 140 calculates a difference value (| R ₁ point time-R ₂ point time |) between R ₁ point and R ₂ point time which are consecutive R peak points. At this time, the difference value (| R ₁ point time - R ₂ point time |) becomes the RR interval time.

Then, the operation unit 140 calculates the difference value between the start point time and the end point time of the same QRS complex (S252). For example, the operation unit 140 calculates the difference value (| Q ₁ point time-S ₁ point time |) between the Q ₁ point and the S ₁ point time, which is the starting point of the QRS ₁ group in FIG. At this time, the difference value (| Q ₁ point time-S ₁ point time |) becomes the QRS group duration time.

Although only two QRSs are shown in FIG. 5, since a plurality of QRSs exist according to the length of the inputted ECG signal, the calculating unit 140 calculates a plurality of RR interval time and QRS duration time through step S250 .

In operation S260, the diagnosis unit 150 generates a distribution pattern of operation results by matching the operation result of step S250 with the two-dimensional coordinate system in which the RR interval time is uniaxial and the QRS group duration is the other axis. FIG. 7 is a detailed flowchart of step S260 of FIG. 2, and FIG. 8 is a view for explaining step S260 of FIG.

Referring to FIG. 7, the diagnostic unit 150 generates coordinate values for the two-dimensional coordinate system by coupling the RRS interval time and the QRS group duration including the R peak point at which the RR interval starts (S261).

5, since the R peak point at which the RR ₁ interval starts is R ₁ , the diagnosis unit 150 determines that the RR ₁ interval duration and the QRS ₁ Couples the group duration to generate the coordinate values. Assuming that the X axis is the QRS group duration and the Y axis is the RR interval time, the coordinate values are (RR ₁ interval time, QRS ₁ group duration).

Then, the diagnosis unit 150 matches the generated coordinate values to the two-dimensional coordinate system (S262). Since a plurality of coordinate values are formed according to the length of the electrocardiogram signal, a plurality of coordinate values are matched to the two-dimensional coordinate system.

Then, the diagnosis unit 150 sets a zone in the two-dimensional coordinate system according to a plurality of reference values (S263). Referring to FIG. 8, the diagnosing unit 150 may include six zones (first zone, second zone, and third zone) in a two-dimensional coordinate system according to three reference values (a first reference value in the QRS group duration time axis and second and third reference values in the RR interval time axis) To the sixth zone) can be set. At this time, the first reference value may be set to 0.1 [sec], the second reference value may be set to 0.6 [sec], and the third reference value may be set to 1 [sec].

Meanwhile, according to the embodiment of the present invention, the number of reference values and reference values can be changed by an ordinary technician and stored in the diagnosis unit 150 or input from outside.

Then, the diagnosis unit 150 calculates a distribution map of the coordinate values matched to the set zone (S264).

At this time, the diagnosis unit 150 can calculate the number of coordinate values matched to each zone. For example, in FIG. 8, each point represents a matched coordinate value. In FIG. 8, the total number of coordinate values is 50. Since the number of coordinate values matched in the first zone is 35, the distribution of the first zone is 0.70. In the case of the third zone, since the seven coordinate values are matched, the distribution degree becomes 0.14.

Next, the diagnostic unit 150 selects a region corresponding to a distribution map that is larger than a predetermined threshold value among the calculated distribution maps (S265). For example, assume that the threshold value is 0.3 in FIG. In this case, since only the distribution chart of the first zone is larger than the threshold value and the distribution charts of the second to sixth zones are smaller than the threshold value, the diagnosis unit 150 selects only the first zone.

Then, the diagnosis unit 150 generates a distribution pattern according to the selected area (S266). If only the first zone is selected as in the example of step S264, only the first zone generates the selected distribution pattern. If the threshold value is set to 0.1 and the first and third zones are selected, the diagnosis unit 150 generates the distribution pattern in which the first and third zones are sorted.

Next, the diagnosis unit 150 diagnoses the arrhythmia of the subject by comparing the generated distribution pattern with the pre-stored arrhythmia pattern (S270). FIG. 9 is a detailed flowchart of step S270 of FIG. 2, and FIG. 10 is a view for explaining an arrhythmia pattern according to an embodiment of the present invention.

Referring to FIG. 9, the diagnostic unit 150 determines the similarity between the generated distribution pattern and the pre-stored arrhythmia pattern (S271). Here, the pre-stored arrhythmia pattern may be stored as shown in FIG. FIG. 9 is a graph showing the results of normal sinus rhythm (NSR), synchronous bradycardia (SB), synchronous tachycardia (ST), atrial tachycardia contraction plus sinus tachycardia (PAC + SVT), atrial sinus rhythm (PAC + NSR) + Corresponding to normal sinus rhythm (PVC + NSR), atrial tachycardia (AT), ventricular tachycardia (VT), synchronous pause (PAUSE), ventricular fibrillation (AF), dysfunctional (SICKSINUS) 12 arrhythmia patterns are shown. According to the embodiment of the present invention, the pre-stored arrhythmia pattern may further include arrhythmia patterns other than the twelve patterns shown in FIG.

Then, the diagnosis unit 150 determines the arrhythmia pattern having the highest degree of similarity as the diagnosis result of the subject (S272).

For example, it is assumed that a distribution pattern in which the first zone is selected as in the case of step S265 is generated. At this time, the distribution pattern in which the first region is selected has the highest similarity with the arrhythmia pattern shown in (k) of FIG. Therefore, the diagnosis unit 150 judges the functional failure (SICKSINUS) as the diagnosis result of the subject.

Meanwhile, in the arrhythmia diagnosis apparatus 100 according to the embodiment of the present invention and the arrhythmia diagnosis method using the same, the arrhythmia of the subject is diagnosed using the RR interval time, but the arrhythmia can be diagnosed by converting the RR interval time to the heart rate have. The process of converting the RR interval time to the heart rate is obvious to those skilled in the art, and a detailed description thereof will be omitted.

According to the embodiment of the present invention, since the RR interval time of the electrocardiogram signal and the QRS group duration are simultaneously used, the accuracy of the arrhythmia diagnosis of the subject can be improved. In addition, since data for each waveform is calculated for the arrhythmia determination without using the average value of the RR interval time and the QRS group duration time, it is possible to detect minute changes according to the heartbeat change of the subject, which is effective for diagnosis of arrhythmia prevention diagnosis .

In addition, since the degree of similarity of the distribution pattern is determined without complicated arithmetic operation and the arrhythmia of the subject is diagnosed, the computation speed is fast, and it is possible to implement it with relatively simple equipment.

While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

100: arrhythmia diagnosis apparatus 110: input unit
120: filtering unit 130:
140: Operation unit 150:

Claims (12)

A method for diagnosing an arrhythmia using an arrhythmia diagnosis apparatus,
Receiving an electrocardiogram signal of a subject,
Obtaining time information of a start point, an end point, and an R peak point of each QRS complex of the electrocardiogram signal,
Calculating the RR interval time and the QRS group duration using the time information of the starting point, the ending point and the R peak point of each QRS group, and
And diagnosing an arrhythmia of the subject using the calculated RR interval time and the QRS group duration. The method according to claim 1,
And removing a noise signal included in the electrocardiogram signal and a linear trend signal included in the electrocardiogram signal from the electrocardiogram signal. The method according to claim 1,
The step of calculating the RR interval time and each QRS group duration comprises:
Computing a difference value of successive R peak point times, and
And calculating a difference value between a start point time and an end point time of each QRS complex group. The method according to claim 1,
The step of diagnosing an arrhythmia of the subject comprises:
Generating a distribution pattern by matching the calculated RR interval time and the QRS group duration with a two-dimensional coordinate system in which the RR interval time is uniaxial and the QRS group duration is another axis, and
And diagnosing an arrhythmia of the subject by comparing the generated distribution pattern with a pre-stored arrhythmia pattern. 5. The method of claim 4,
Wherein the generating the distribution pattern comprises:
Generating coordinate values for the two-dimensional coordinate system by coupling the RRS interval time and a QRS group duration including an R peak point at which the RR interval starts,
Matching the generated coordinate values to the two-dimensional coordinate system,
Setting a zone in the two-dimensional coordinate system according to a plurality of reference values,
Calculating a distribution map of the matched coordinate values for each zone,
Selecting a region corresponding to a distribution map that is larger than a predetermined threshold value among the calculated distribution maps, and
And generating the distribution pattern according to the selected zone. The method according to claim 1,
The step of diagnosing an arrhythmia of the subject comprises:
Determining a degree of similarity between the generated distribution pattern and a pre-stored arrhythmia pattern, and
And determining the arrhythmia pattern having the highest degree of similarity as a diagnosis result of the subject. An input unit for receiving an electrocardiogram signal of a subject,
An acquisition unit for acquiring time information of a start point, an end point, and an R peak point of each QRS complex of the electrocardiogram signal,
An operation unit for calculating the RR interval time and the QRS group duration using the time information of the starting point, the ending point and the R peak point of each QRS complex,
And diagnosing the arrhythmia of the subject using the calculated RR interval time and the QRS group duration. 8. The method of claim 7,
And a filtering unit for removing a noise signal included in the electrocardiogram signal and a linear trend signal included in the electrocardiogram signal from the electrocardiogram signal. 8. The method of claim 7,
The operation unit,
Calculating a difference value between successive R peak point times and calculating a difference value between a start point time and an end point time of each QRS complex group. 8. The method of claim 7,
Wherein the diagnosis unit comprises:
A distribution pattern is generated by matching the calculated RR interval time and the QRS group duration with a two-dimensional coordinate system in which the RR interval time is uniaxial and the QRS group duration is another axis, and the generated distribution pattern and pre-stored arrhythmia pattern To thereby diagnose an arrhythmia of the subject. 11. The method of claim 10,
Wherein the diagnosis unit comprises:
The RR interval time and the R-peak point at which the RR interval starts, to generate coordinate values for the two-dimensional coordinate system, and the generated coordinate values are matched to the two-dimensional coordinate system A zone is set in the two-dimensional coordinate system according to a plurality of reference values, a distribution map of the matched coordinate values is calculated for each zone, and a zone corresponding to a distribution map larger than a predetermined threshold value is selected And generating the distribution pattern according to the selected area. 8. The method of claim 7,
Wherein the diagnosis unit comprises:
And determines a diagnosis result corresponding to the arrhythmia pattern having the highest degree of similarity as the diagnosis result of the subject.

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