阅读说明：本技术 心房颤动解析装置、心房颤动解析方法以及程序 (Atrial fibrillation analysis device, atrial fibrillation analysis method, and program ) 是由 笹野哲郎 佐佐木奏绘 于 2019-12-23 设计创作，主要内容包括：心房颤动解析装置的控制部仅从基于在包括被检者的体轴方向以及左右方向的平面上的一个方向的导联的心电图、或者仅从基于在所述平面上正交的两个方向的导联的心电图中取得P波数据,并从所取得的P波数据中提取P波片段。然后,基于P波片段的数量和/或P波片段的持续时间,解析心房颤动的发病的可能性。(The control unit of the atrial fibrillation analysis device acquires P-wave data from only an electrocardiogram based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject or from only an electrocardiogram based on leads in two directions orthogonal to the plane, and extracts a P-wave segment from the acquired P-wave data. The likelihood of onset of atrial fibrillation is then analyzed based on the number of P-wave segments and/or the duration of the P-wave segments.)

1. An atrial fibrillation resolving device comprising:

a P-wave data acquisition unit that acquires P-wave data from only an electrocardiogram based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject, or from only an electrocardiogram based on leads in two directions orthogonal to the plane;

a segment extraction unit that extracts a P-wave segment from the P-wave data acquired by the P-wave data acquisition unit; and

and an analysis unit which analyzes the possibility of the onset of atrial fibrillation on the basis of the number of P-wave segments and/or the duration of the P-wave segments.

2. The atrial fibrillation resolving device of claim 1, wherein,

the atrial fibrillation analyzer further includes an electrocardiogram measuring unit for measuring the electrocardiogram.

3. The atrial fibrillation resolving device of claim 1 or 2, wherein,

the P-wave data acquisition unit acquires a plurality of P-wave data from the electrocardiogram,

the segment extraction unit calculates average P-wave data by averaging the plurality of pieces of P-wave data, extracts extreme values from the average P-wave data, and extracts a line connecting the extreme values as a P-wave segment when a potential difference between adjacent extreme values exceeds a predetermined value.

4. The atrial fibrillation resolving device of claim 3, wherein,

when the P-wave data is acquired by the P-wave data acquisition unit from an electrocardiogram based on leads in two directions orthogonal to each other on the plane, the segment extraction unit calculates the average P-wave data by averaging the plurality of P-wave data for each of the leads to calculate a root-mean-square.

5. The atrial resolver of claim 3 or 4,

the segment extraction unit further performs filtering processing for removing frequencies in a predetermined range from the average P-wave data, and extracts P-wave segments from the average P-wave data after the filtering processing.

6. An atrial fibrillation interpretation method comprising:

a P-wave data acquisition step of acquiring P-wave data from only an electrocardiogram based on leads in one direction on a plane including a body axis direction and a left-right direction of a subject, or from only an electrocardiogram based on leads in two directions orthogonal to the plane;

a segment extraction step of extracting a P-wave segment from the P-wave data acquired in the P-wave data acquisition step; and

and analyzing the possibility of the occurrence of the atrial fibrillation based on the number of the P wave segments and/or the duration of the P wave segments.

7. A program for causing a computer to function as:

a P-wave data acquisition unit that acquires P-wave data from only an electrocardiogram based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject, or from only an electrocardiogram based on leads in two directions orthogonal to the plane;

a segment extraction unit that extracts a P-wave segment from the P-wave data acquired by the P-wave data acquisition unit; and

and an analysis unit which analyzes the possibility of the onset of atrial fibrillation on the basis of the number of P-wave segments and/or the duration of the P-wave segments.

Technical Field

The present invention relates to an atrial fibrillation analysis device, an atrial fibrillation analysis method, and a program.

Background

Atrial Fibrillation (AF) is a persistent arrhythmia disease with the highest frequency and causes cerebral infarction or heart failure, and therefore, early diagnosis thereof is important. Further, atrial fibrillation is an arrhythmia disease that develops as an episode and becomes chronic. Conventionally, atrial fibrillation can be diagnosed by observing an electrocardiogram at the time of onset, but cannot be diagnosed by observing an electrocardiogram at the time of non-onset. Therefore, it is desired to analyze the possibility of the onset of atrial fibrillation using an electrocardiogram, which is a noninvasive test, even in the non-onset time.

Among them, non-patent document 1 proposes a method of counting P-wave fragments (fragments) after a band-pass filter process in an electrocardiogram as a new analysis method for evaluating conduction in the atrium.

Documents of the prior art

Non-patent document

Non-patent document 1, Murthy S, Rizzi P, Mewton N, Strauss DG, Liu CY, Volpe GJ, Marchlinski FE, Spooner P, Berger RD, Kellman P, Lima JAC, Tereshchenko LG. "Number of P-Wave fragments on P-SAECG gratings with Infilmed attached approach Fat", Ann Noninivasive electrocardial 2014; 19:114-121.

Disclosure of Invention

Problems to be solved by the invention

However, non-patent document 1 only observes the correlation between the P-wave segment and the fat in the interatrial septum, and does not evaluate the correlation with the prediction of the onset of atrial fibrillation. In non-patent document 1, the XYZ-lead electrocardiogram using the special lead (Frank lead) method does not use the 12-lead electrocardiogram generally used for medical treatment. Therefore, an expensive device and a highly skilled examiner are required for diagnosis, and there is a great problem in order to spread the diagnosis widely. Further, since the number of electrocardiogram data measured in the past is small in the analysis of the electrocardiogram using the special lead method, there is a problem that it is difficult to improve the accuracy of the analysis of the possibility of the occurrence of atrial fibrillation.

The present invention addresses the problem of being able to determine the possibility of onset of atrial fibrillation with high accuracy even in the non-onset state by a non-invasive, inexpensive, easy, and short-time examination.

Means for solving the problems

In order to solve the above problem, an atrial fibrillation analysis device according to claim 1 includes:

a P-wave data acquisition unit that acquires P-wave data from only an electrocardiogram based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject, or from only an electrocardiogram based on leads in two directions orthogonal to the plane;

a segment extraction unit that extracts a P-wave segment from the P-wave data acquired by the P-wave data acquisition unit; and

and an analysis unit which analyzes the possibility of the onset of atrial fibrillation on the basis of the number of P-wave segments and/or the duration of the P-wave segments.

The invention described in claim 2 is the invention described in claim 1,

also comprises an electrocardiogram measuring part for measuring the electrocardiogram.

The invention described in claim 3 is the invention described in claim 1 or 2,

the P-wave data acquisition unit acquires a plurality of P-wave data from the electrocardiogram,

the segment extraction unit calculates average P-wave data by averaging the plurality of pieces of P-wave data, extracts extreme values from the average P-wave data, and extracts a line connecting the extreme values as a P-wave segment when a potential difference between adjacent extreme values exceeds a predetermined value.

The invention described in claim 4 is the invention described in claim 3,

when the P-wave data is acquired by the P-wave data acquisition unit from an electrocardiogram based on leads in two directions orthogonal to each other on the plane, the segment extraction unit calculates the average P-wave data by averaging the plurality of P-wave data for each of the leads to calculate a root-mean-square.

The invention described in claim 5 is the invention described in claim 3 or 4,

the segment extraction unit further performs filtering processing for removing frequencies in a predetermined range from the average P-wave data, and extracts P-wave segments from the average P-wave data after the filtering processing.

The atrial fibrillation analysis method according to the invention described in claim 6 includes:

a P-wave data acquisition step of acquiring P-wave data from only an electrocardiogram based on leads in one direction on a plane including a body axis direction and a left-right direction of a subject, or from only an electrocardiogram based on leads in two directions orthogonal to the plane;

a segment extraction step of extracting a P-wave segment from the P-wave data acquired in the P-wave data acquisition step; and

and analyzing the possibility of the occurrence of the atrial fibrillation based on the number of the P wave segments and/or the duration of the P wave segments.

The program of the invention described in claim 7 causes a computer to function as:

a P-wave data acquisition unit that acquires P-wave data from only an electrocardiogram based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject, or from only an electrocardiogram based on leads in two directions orthogonal to the plane;

a segment extraction unit that extracts a P-wave segment from the P-wave data acquired by the P-wave data acquisition unit; and

and an analysis unit which analyzes the possibility of the onset of atrial fibrillation on the basis of the number of P-wave segments and/or the duration of the P-wave segments.

ADVANTAGEOUS EFFECTS OF INVENTION

According to the present invention, it is possible to accurately determine the possibility of onset of atrial fibrillation even in a non-onset state by a non-invasive, inexpensive, easy, and short-time examination. As a result, early diagnosis of atrial fibrillation can be performed.

Drawings

Fig. 1 is a block diagram showing a functional configuration of an atrial fibrillation analysis device according to an embodiment of the present invention.

Fig. 2 is a flowchart showing a flow of atrial fibrillation analysis processing a executed by the control unit of fig. 1 in embodiment 1.

Fig. 3 is a diagram for explaining a waveform of an electrocardiogram.

Fig. 4A is a diagram showing the X and Y leads of an electrocardiograph of XYZ leads.

Figure 4B is a diagram showing limb leads of a 12-lead electrocardiograph.

FIG. 5 is a diagram schematically representing the process of calculating the number and duration of P-wave segments from the averaged P-wave data.

Fig. 6A is a diagram showing an example of the number and duration of P-wave plates in a healthy subject.

Fig. 6B is a graph showing an example of the number and duration of P-wave segments in a patient with atrial fibrillation.

Fig. 7A is a graph showing a comparison result between the number of P-wave segments based on XY leads and the number of P-wave segments based on XYZ leads.

FIG. 7B is a graph showing the results of comparing the duration of the P-wave plate segment based on the XY leads and the duration of the P-wave plate segment based on the XYZ leads.

Fig. 8A is a graph showing the number of P-wave segments based on XY leads versus the number of P-wave segments based on the I-and aVF leads of a 12-lead electrocardiograph.

FIG. 8B is a graph showing XY lead based P-wave segment duration versus P-wave segment duration for the I and aVF leads of a 12 lead electrocardiograph.

Fig. 9A is a graph showing the number of P-wave segments based on the I and aVF leads of a 12-lead electrocardiograph versus the number of P-wave segments based on the II and aVL leads.

FIG. 9B is a graph showing the relationship of P-wave segment duration for the I lead and aVF lead based on a 12 lead electrocardiograph to the P-wave segment duration for the II lead and aVL lead.

Fig. 10A is a graph showing the number of P-wave segments based on the I-lead and aVF-lead of a 12-lead electrocardiograph versus the number of P-wave segments based on the III-lead and aVR-lead.

FIG. 10B is a graph showing the relationship of P-wave segment duration for the I lead and aVF lead based on a 12 lead electrocardiograph to the P-wave segment duration for the III lead and aVR lead.

Fig. 11 is a flowchart showing the flow of atrial fibrillation analysis processing B executed by the control unit of fig. 1 in embodiment 2.

Detailed Description

Hereinafter, embodiments of the present invention will be described with reference to the drawings. However, the scope of the invention is not limited to the illustrated examples.

< embodiment 1 >

In embodiment 1, an example will be described in which the possibility of the occurrence of atrial fibrillation is analyzed using only electrocardiograms based on leads in two directions orthogonal to a plane (forehead plane) including the body axis direction (cranio-caudal direction) and the left-right direction of the subject, without using electrocardiograms based on leads in the front-back direction (dorsoventral direction) of the body.

(construction of atrial fibrillation analysis device 1)

First, the configuration of atrial fibrillation analysis device 1 according to embodiment 1 of the present invention will be described.

Fig. 1 is a block diagram showing a functional configuration of an atrial fibrillation analysis apparatus 1. As shown in fig. 1, the atrial fibrillation analysis device 1 includes a control unit 11, a storage unit 12, an operation unit 13, a display unit 14, an electrocardiogram measurement unit 15, a communication unit 16, and the like, and the respective units are connected by a bus 17. In the present embodiment, the atrial fibrillation analysis device having the electrocardiogram measurement unit is shown, but the atrial fibrillation analysis device may not have the electrocardiogram measurement unit. In the case of an atrial fibrillation analysis device that does not have an electrocardiogram measurement unit, it is preferable that electrocardiogram data be stored in a storage unit via a communication unit or the like, and atrial fibrillation analysis processing be performed based on the electrocardiogram data stored in the storage unit.

The control Unit 11 is constituted by a CPU (Central Processing Unit), a RAM (Random Access Memory), and the like. The CPU of the control unit 11 reads out a system program or various processing programs stored in the storage unit 12 based on the operation of the operation unit 13, develops the system program or the various processing programs in the RAM, and performs centralized control of the operations of the respective units of the atrial fibrillation analyzer 1 according to the developed programs. For example, the control unit 11 executes atrial fibrillation analysis processing, which will be described later, in accordance with the operation of the operation unit 13, and functions as a P-wave data acquisition unit, a segment extraction unit, and an analysis unit.

The storage unit 12 is constituted by a nonvolatile semiconductor memory, a hard disk, or the like. The storage unit 12 stores data such as a system program, various programs executed by the control unit 11, and parameters necessary for executing processing by the programs. For example, the storage unit 12 stores a program or the like for executing atrial fibrillation analysis processing described later. The storage unit 12 may store electrocardiographic data. Various programs are stored in the form of readable program codes, and the control unit 11 sequentially executes operations according to the program codes.

The operation unit 13 is configured to have various function keys, a pointing device such as a mouse, and output a pointing signal input by a key operation or a mouse operation performed by a user to the control unit 11. The operation unit 13 may be provided with a touch panel on the display screen of the display unit 14, and in this case, outputs an instruction signal input via the touch panel to the control unit 11.

The Display unit 14 is constituted by a monitor such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube), and displays input instructions, data, and the like from the operation unit 13 in accordance with instructions of Display signals input from the control unit 11.

The electrocardiogram measuring unit 15 measures electrical changes in the myocardium via electrodes disposed on the body surface of the subject, and records the electrical changes as an electrocardiogram. As the electrocardiogram measuring unit 15, for example, a 12-lead electrocardiograph which is widely used in general can be used, but an XYZ-lead electrocardiograph may be used.

The communication section 16 includes a LAN Adapter, a modem, a TA (Terminal Adapter), or the like, and controls data transmission and reception with an external device connected to a communication network.

[ action of the atrial fibrillation analysis device 1 ]

Next, the operation of the atrial fibrillation analysis device 1 according to the present embodiment will be described.

Fig. 2 is a flowchart showing the flow of atrial fibrillation analysis processing (referred to as atrial fibrillation analysis processing a) executed by the control unit 11 of the atrial fibrillation analysis device 1. The atrial fibrillation analysis process a is executed by the CPU of the control unit 11 in cooperation with the program stored in the storage unit 12 in accordance with the operation of the operation unit 13.

First, the control unit 11 causes the electrocardiogram measuring unit 15 to measure the electrocardiogram of the subject and records the digital data (electrocardiogram data) of the electrocardiogram of sinus rhythm (at the time of non-episode) (step S1).

In order to maintain the accuracy of analysis, the measurement time of the electrocardiogram is preferably 10 seconds to 1 hour. More preferably 10 seconds to 30 minutes, and most preferably 10 seconds to 3 minutes. The analysis method of atrial fibrillation analysis apparatus 1 is preferable because long-time measurement, such as 24-hour measurement using a holter electrocardiogram, is not necessary, and the possibility and risk of onset of atrial fibrillation can be analyzed by short-time measurement. In the present embodiment, it is assumed that about 100 beats are measured within 2 minutes.

In the analysis of the present embodiment, since the leads in the front-back direction of the body are not used, the measurement based on the leads in the front-back direction of the body can be omitted.

Fig. 3 is a diagram showing an example of electrocardiographic data for one beat. As shown in fig. 3, the electrocardiographic data is composed of P-wave, Q-wave, R-wave, S-wave, (QRS-wave), T-wave, and U-wave. The horizontal axis represents the time axis (mS) and the vertical axis represents the potential difference (mV).

Next, the control unit 11 acquires electrocardiographic data based on leads in two directions orthogonal to a plane including the body axis direction and the left-right direction of the subject from the electrocardiographic data acquired by the electrocardiographic measurement unit 15 (step S2).

Fig. 4A is a diagram showing X and Y leads of an XYZ lead electrocardiograph, and fig. 4B is a diagram showing limb leads of a 12 lead electrocardiograph. As shown in fig. 4A and 4B, as leads in two directions orthogonal to a plane including the body axis direction (cranio-caudal direction, vertical direction) and the left-right direction of the subject, groups of the X lead and the Y lead (hereinafter referred to as XY lead) of the electrocardiograph of the XYZ lead, the I lead and the aVF lead, the II lead and the aVL lead, and the III lead and the aVR lead in the limb leads of the 12 lead electrocardiograph are respectively matched. Therefore, when the electrocardiograph measuring unit 15 is a 12-lead electrocardiograph, the control unit 11 acquires electrocardiographic data in at least two directions that are the above-described pair (in the present embodiment, electrocardiographic data of all the limb leads) among electrocardiographic data of the limb leads. When the electrocardiograph measuring unit 15 is an XYZ-lead electrocardiograph, electrocardiographic data of X-lead and Y-lead are acquired.

Next, the control unit 11 selects electrocardiographic data of a waveform indicating a single peak where the P-wave is most clear from among the acquired electrocardiographic data of each lead, and detects an R-wave peak from the selected electrocardiographic data (step S3).

In step S3, for example, the acquired electrocardiographic data of the respective leads may be displayed side by side on the display portion 14, and electrocardiographic data including a waveform representing a single peak in which the P-wave is most clear may be selected by a user operation. Alternatively, the control unit 11 may automatically select the waveform according to the shape and height of the waveform included in the electrocardiographic data of each lead.

For example, when 100 beats of electrocardiographic data are recorded, an R peak of 100 is detected from the selected electrocardiographic data. The R-wave peaks detected here may be at least a part of a plurality of beats obtained by one electrocardiographic measurement, but preferably R-wave peaks of all beats. In addition, the P-wave peak or the R-wave peak included in the electrocardiographic data may be automatically detected by the control portion 11 based on the shape of the waveform.

Next, the control unit 11 detects P peaks from the electrocardiographic data of the leads selected in step S3 for a predetermined range based on the R peaks detected from the selected electrocardiographic data (step S4).

The predetermined range to be a target of detecting the P peak is a range empirically determined experimentally as a range in which the P peak exists, and is, for example, a range of-50 to-200 mS based on each R peak.

For example, when 100 beats of electrocardiographic data are recorded, 100P peaks are detected from the electrocardiographic data of each lead.

Next, the control unit 11 cuts out a predetermined range from the time point of the P wave peak detected in step S4 in the electrocardiographic data of each lead, acquires the range as P-wave data, and performs addition averaging (step S5).

The P-wave data extracted here is P-wave data of at least a part of, and preferably all, the multiple beats obtained by one electrocardiographic measurement. The number of P-wave data is preferably 100 or more, more preferably 500 or more, and most preferably 1000 or more.

The predetermined range cut out as the P wave data is a range empirically determined experimentally as a range including the P wave and the baseline before and after the P wave, and is preferably a range between-500 mS and +300mS based on the P peak and including 0mS, and an absolute value on the negative side is larger than an absolute value on the positive side, for example, a range between-300 mS and +150mS based on each P peak. Baseline refers to the portion of the electrocardiogram data where the heart is not excited.

Next, the control unit 11 selects a portion to be a base line from the P-wave data obtained by adding and averaging the leads (step S6).

For example, the control unit 11 selects a predetermined range (for example, a range of-200 to-100 mS) as a baseline with respect to each P peak. The range selected as the baseline is a range empirically determined experimentally as the range existing as the baseline. In addition, the portion to be the baseline may also be selected by the user.

Next, the control unit 11 performs baseline correction of the P-wave data after the addition-averaging based on the selected baseline portion (step S7).

For example, the average value of the selected baseline portion is calculated, and the average value is subtracted from each value of the P-wave data, thereby performing baseline correction. This enables the value of the baseline portion to be substantially 0.

Next, the control unit 11 calculates mean P-wave data by calculating the Root Mean Square (RMS) of the P-wave data based on the leads in the two orthogonal directions (step S8).

For example, when the electrocardiograph unit 15 is a 12-lead electrocardiograph, 3 sets of mean P-wave data are calculated by calculating the root mean square of 3 sets of the P-wave data of the I-th lead and the aVF lead, the P-wave data of the II-th lead and the aVL lead, and the P-wave data of the III-th lead and the aVR lead. Alternatively, the root mean square of the P-wave data of the I-th lead and the aVF lead may be calculated, and only 1 group of average P-wave data may be calculated and used.

In addition, in the case where the electrocardiograph unit 15 is an XYZ-lead electrocardiograph, the root mean square of the P-wave data of the X-lead and the Y-lead is calculated, and 1 group of average P-wave data is calculated.

Next, the calculated average P-wave data is subjected to band-pass filter processing (step S9). The frequency range to be passed is a value empirically obtained through experiments, and is preferably 30 to 300Hz, and most preferably 40 to 150 Hz.

Next, the control unit 11 sets a detection range of the P-wave segment in the average P-wave data after the band-pass filter processing (step S10).

For example, the range from immediately after the baseline portion selected in step S6 to immediately before the QRS wave in the average P-wave data after the band-pass filter processing is set as the detection range of the P-wave segment.

Next, the control unit 11 detects an extremum in the detection range of the P-wave segment (step S11).

Next, the control unit 11 calculates a standard deviation (baseline standard deviation) of the value of the baseline portion of the average P-wave data after the band-pass filter processing (step S12).

The baseline standard deviation represents the noise level at which the electrocardiogram was measured.

Here, when the electrocardiograph unit 15 is a 12-lead electrocardiograph, the standard deviation is calculated from the 3 pieces of mean P-wave data, and the mean P-wave data having the lowest standard deviation, that is, the lowest noise, is determined as the waveform used to calculate the P-wave segment. Alternatively, instead of using 3 mean P-wave data, the standard deviation may be calculated from only the mean P-wave data of the I-th lead and aVF lead.

Next, when the potential difference between the adjacent extreme values detected in step S11 exceeds n times the baseline standard deviation (n is a positive number), the controller 11 defines a line connecting the two points as a P-wave segment (step S13).

n is a value calculated based on an experiment, and is preferably 2 or more and 10 or less, more preferably 2 or more and 5 or less, and is 3, for example.

Next, the control unit 11 calculates the number of P-wave segments (step S14).

Next, the control unit 11 calculates the time (duration of the P-wave plate segment) from the start point (the first start point in one piece of average P-wave data) to the end point (the last end point in one piece of average P-wave data) of the P-wave segment (step S15).

FIG. 5 shows a process flow for calculating the number and duration of P-wave segments based on the average P-wave data.

Then, the control unit 11 analyzes the possibility of the occurrence of atrial fibrillation based on the number and/or duration of the P-wave segments, displays the analysis result on the display unit 14 (step S16), and ends the atrial fibrillation analysis process a.

Fig. 6A is a diagram showing an example of the number and duration of P-wave plates in a healthy subject, and fig. 6B is a diagram showing an example of the number and duration of P-wave plates in a patient with atrial fibrillation. In the present embodiment, n is 3. That is, in the present embodiment, when the potential difference between the adjacent extreme values exceeds 3 times the standard deviation of the baseline, the line connecting the two points is determined as the P-wave segment. As shown in fig. 6A and 6B, the number and duration of P-wave segments in patients with paroxysmal atrial fibrillation are greater than those of healthy individuals. In the present embodiment, the number of P-wave segments for healthy subjects is 17, and the number of P-wave segments for patients with atrial fibrillation is 25. The P-wave plate duration (duration) of healthy subjects was 137ms, and that of patients with atrial fibrillation was 172 ms.

Therefore, in step S16, for example, a value of the number or duration of the P-wave plate segments is displayed as an index value indicating the possibility of the onset of atrial fibrillation. Alternatively, a threshold value may be set for the number or duration of P-wave plates, and when the calculated number or duration of P-wave plates is higher than the threshold value, it may be determined that atrial fibrillation is likely to occur, and this may be indicated. Alternatively, in the case where the number or duration of the P-wave plates is less than or equal to the threshold 1, it is determined that there is a possibility of atrial fibrillation: if the threshold value 1 to less than the threshold value 2 are low, it is determined that atrial fibrillation is likely: in the case of the threshold value of 2 or more, it is determined that atrial fibrillation is likely: high, indicating this (threshold 1< threshold 2). Alternatively, for example, a table in which combinations of the number and duration of P-wave plates are associated with index values of the likelihood of onset of atrial fibrillation may be stored in the storage unit 12 in advance, and the index values corresponding to the calculated combinations of the number and duration of P-wave plates may be read and displayed.

(verification)

However, as a result of intensive studies, the inventors of the present application have found that since the posterior left atrial wall is a region important for the occurrence of atrial fibrillation and is along a plane including the body axis direction and the left-right direction of the body, leads in the body longitudinal direction are not necessary for analysis of the possibility of the occurrence of atrial fibrillation. It was also verified whether the number and duration of P-wave plate segments calculated using only leads in two directions orthogonal to each other on a plane including the body axis direction and the left-right direction, which were measured at the time of non-onset, can be used to determine the possibility of onset of paroxysmal atrial fibrillation without using leads in the front-back direction of the body.

Fig. 7A is a graph showing the comparison results of the number (average value) of P-wave fragments calculated by the above method, which were recorded for 2 minutes using XY leads and XYZ leads for PAF (patient population with onset atrial fibrillation), AC (age-appropriate control population), and YC (young control population). Fig. 7B is a graph showing the comparison results of the P-plate segment duration (average) calculated by the above-described method, recorded for 2 minutes for PAF, AC, and YC through the XY lead and the XYZ lead, respectively. In addition, the threshold for determining the P-wave segment is set to 3 times the noise level of the baseline portion.

As shown in fig. 7A and 7B, in all PAF, AC, and YC, the number of P-wave plates and the duration of P-wave plates based on XY leads are substantially the same as those based on XYZ leads, and in patients with paroxysmal atrial fibrillation, the number of P-wave plates and the duration of P-wave plates are larger than those of healthy subjects.

That is, it was confirmed that the number and duration of P-wave segments calculated using only XY leads orthogonal in a plane including the body axis direction and the left-right direction can be used to determine the onset of paroxysmal atrial fibrillation.

The inventors of the present application performed calculations of the number of P-wave plate segments and the P-wave plate segment duration time of the I-lead and aVF-lead of XY-lead and 12-lead electrocardiographs for a plurality of healthy subjects and patients with paroxysmal atrial fibrillation, and investigated whether or not there is a correlation. Fig. 8A to 10B show the results of the examination.

Fig. 8A is a scatter plot showing the relationship between the number of P-wave segments based on XY leads and the number of P-wave segments based on the I-th lead and aVF lead of a 12-lead electrocardiograph. FIG. 8B is a scatter plot showing XY lead based P-wave plate segment time versus P-wave plate segment duration for the I and aVF leads of a 12 lead electrocardiograph. As shown in fig. 8A, correlation coefficient R between the number of P-wave segments based on XY leads and the number of P-wave segments based on I-th lead and aVF lead of 12-lead electrocardiograph was 0.64, and correlation was confirmed. In addition, as shown in fig. 8B, the correlation coefficient R between the P-wave plate segment duration based on the XY lead and the P-wave plate segment duration based on the I lead and the aVF lead of the 12 lead electrocardiograph was 0.77, and correlation was confirmed.

In order to confirm whether or not there is a correlation between the number of P-waveplate segments and the P-waveplate segment duration based on XY leads and the number of P-waveplate segments and the P-waveplate segment duration based on II leads and aVL leads and III leads and aVR leads, the inventors of the present application studied whether or not there is a correlation between the number of P-waveplate segments and the P-waveplate segment duration based on I leads and aVF leads and the number of P-waveplate segments and the P-waveplate segment duration based on II leads and aVL leads and III leads and aVR leads.

Fig. 9A is a scatter diagram showing the relationship between the number of P-wave segments from the I-lead and aVF-lead of the 12-lead electrocardiograph and the number of P-wave segments from the II-lead and aVL-lead. FIG. 9B is a scatter plot showing the relationship between the duration of the P-wave segment for lead I and aVF based on 12-lead electrocardiograph and the duration of the P-wave segment for lead II and aVL based on 12-lead electrocardiograph. As shown in fig. 9A, correlation coefficient R between the number of P-wave segments based on the I-th lead and aVF lead and the number of P-wave segments based on the II-th lead and aVL lead is 0.90, and correlation is confirmed. In addition, as shown in fig. 9B, the correlation coefficient R between the duration of the P-wave plate segment based on the I-lead and aVF-lead and the duration of the P-wave plate segment based on the II-lead and aVL-lead is 0.83, and thus correlation is confirmed. That is, the number of P-waveplates and the P-waveplate duration based on XY leads, and the number of P-waveplates and the P-waveplate duration based on II leads and aVL leads were also found to be related.

Fig. 10A is a scatter diagram showing the relationship between the number of P-wave segments based on the I-th lead and aVF lead of the 12-lead electrocardiograph and the number of P-wave segments based on the III-th lead and aVR lead. FIG. 10B is a scatter plot showing the relationship between the duration of the P-wave segment for lead I and aVF based on 12-lead electrocardiography and the duration of the P-wave segment for lead III and aVR. As shown in fig. 10A, correlation coefficient R between the number of P-wave segments based on I-th lead and aVF lead and the number of P-wave segments based on III-th lead and aVR lead is 0.81, and correlation is confirmed. As shown in fig. 10B, the correlation coefficient R between the duration of the P-wave plate segment based on the I-th lead and aVF lead and the duration of the P-wave plate segment based on the III-th lead and aVR lead was 0.83, and correlation was confirmed. That is, the number of P-wave segments and the P-wave segment duration based on XY leads, and the number of P-wave segments and the P-wave segment duration based on III-th leads and aVR leads were also found to be related.

From the above, the following was confirmed: the number and duration of P-wave segments calculated for the I and aVF leads using only the 12 lead electrocardiograph, the II and aVL leads using only the III and aVR leads can also be used to discriminate the onset of paroxysmal atrial fibrillation.

Electrocardiographic examination is examination that can macroscopically capture the state of the entire heart in a noninvasive manner. In particular, examination by a 12-lead electrocardiogram is inexpensive and widely spread in medical practice, and can be easily performed by many examiners, and it is not necessary to perform long-time measurement such as measurement for 24 hours as in the case of a holter electrocardiogram. In the atrial fibrillation analysis process a, because the possibility of the occurrence of atrial fibrillation is analyzed using only electrocardiographic data based on leads in two directions orthogonal to each other in a plane including the body axis direction and the left-right direction during non-onset, without using electrocardiographic data based on leads in the front-back direction of the body, it is possible to perform analysis using only electrocardiographic data based on 12-lead electrocardiographs, particularly electrocardiographic data based on measurement of simple limb leads, and it is possible to predict the possibility of the occurrence of atrial fibrillation even during non-onset by noninvasive, inexpensive, easy, and short-time examination. As a result, early diagnosis of atrial fibrillation can be performed.

In addition, since 12-lead electrocardiograms are more widely used than ever, as described above, a large amount of data exists in the past. Therefore, by using the electrocardiogram data of the past atrial fibrillation patient and the electrocardiogram data of the healthy person who is not the atrial fibrillation patient, the threshold used for positioning the P-wave or determining the P-wave segment, the threshold used for analyzing the possibility of the onset of atrial fibrillation, and the like can be obtained with higher accuracy, and the possibility of the onset of atrial fibrillation can be predicted with higher accuracy. That is, the possibility of occurrence of atrial fibrillation can be predicted from the past 12-lead electrocardiographic measurement data itself without newly measuring the electrocardiogram. Further, by effectively using huge past 12-lead electrocardiographic measurement data and inputting the data to software or AI (machine learning) for analysis, it is possible to predict the possibility of the onset of atrial fibrillation with higher accuracy without performing a large number of examinations and collecting data from now on.

For example, when the measurement is performed for several minutes (for example, 2 minutes) in step S1 and the analysis is performed using 2 minutes of electrocardiographic data, it is also conceivable that the measurement time is insufficient if the measurement is performed using short (for example, 10 seconds) electrocardiographic data in the past. In this case, by inputting a plurality of pieces of electrocardiogram data acquired by measuring 2 minutes into the AI, creating a machine learning model for estimating 2 minutes of electrocardiogram data from 10 seconds of electrocardiogram data, and inputting the past 10 seconds of electrocardiogram data into the machine learning model to predict 2 minutes of electrocardiogram data, it is possible to effectively utilize past short measurement time of electrocardiogram data to improve the accuracy of the possibility of the occurrence of atrial fibrillation. The AI may be realized by cooperation of the control unit 11 and the program, or may be realized by dedicated hardware.

In addition, even in the case of an electrocardiograph using XYZ leads, measurement based on the Z lead is not necessary, and therefore, the electrocardiograph does not need to include electrodes for the Z lead (dedicated electrodes different from the X lead and the Y lead), and can have an inexpensive device configuration. Furthermore, since it is not necessary to use the electrocardiographic data of the Z-lead, it is possible to reduce the time taken for measurement, the load on the patient, the processing time for analysis, or the processing load.

< embodiment 2 >

Next, embodiment 2 of the present invention will be explained.

While the example of analyzing the possibility of the occurrence of atrial fibrillation using only electrocardiographic data based on leads in two directions orthogonal to each other on a plane including the body axis direction and the left-right direction of the subject has been described in embodiment 1, the example of evaluating the possibility of the occurrence of atrial fibrillation based on only electrocardiographic data based on leads in one direction (for example, the left-right direction) on a plane including the body axis direction and the left-right direction of the subject will be described in embodiment 2.

The components in embodiment 2 are substantially the same as those described with reference to fig. 1, but in the present embodiment, the electrocardiogram measuring unit 15 may be configured to measure only electrocardiogram data based on leads in a predetermined one direction on a plane including the body axis direction and the left-right direction of the subject. Therefore, in the present embodiment, the description will be given assuming that the electrocardiogram measuring unit 15 measures only electrocardiogram data based on leads in a predetermined one direction (for example, the left-right direction) of a plane including the body axis direction and the left-right direction of the subject. In this case, a wrist band type device or a wristwatch type device in which the electrocardiogram measuring unit 15 is attached to the wrist can be used, and the load on the subject is small, which is preferable.

Since the configuration in the other embodiment 2 is the same as that described in embodiment 1, the description is given below with reference to the description, and the operation of embodiment 2 will be described below.

Next, the operation of the atrial fibrillation analysis device 1 according to embodiment 2 will be described.

Fig. 11 is a flowchart showing the flow of atrial fibrillation analysis processing (referred to as atrial fibrillation analysis processing B) executed by the control unit 11 of the atrial fibrillation analysis device 1. The atrial fibrillation analysis process B is executed by the CPU of the control unit 11 in cooperation with the program stored in the storage unit 12 in accordance with the operation of the operation unit 13.

First, the control unit 11 causes the electrocardiogram measuring unit 15 to measure an electrocardiogram of the subject and records electrocardiogram data of a sinus rhythm (at the time of non-attack) (step S21).

The number of measurement beats and the measurement time required for electrocardiographic measurement are preferably the same as those described in step S1 of fig. 2, for example.

Next, the control unit 11 detects an R peak from electrocardiographic data obtained by electrocardiographic measurement (step S22).

Next, the control unit 11 detects a P peak for a predetermined range based on each detected R peak (step S23).

The predetermined range to be a target of detecting the P peak is a range determined empirically as a range in which the P peak exists, and is, for example, a range of-50 to-200 mS based on each R peak.

Next, the control unit 11 cuts out a predetermined range as P-wave data based on the time point of the detected P-wave peak, and calculates average P-wave data by performing addition averaging (step S24).

The predetermined range cut out as the P-wave data is a range empirically determined experimentally as a range including the P-wave and the baseline before and after the P-wave, and is, for example, a range of-300 mS to +150mS based on each P-wave peak.

Next, the control unit 11 selects a portion to be a baseline from the average P-wave data (step S25).

For example, the control unit 11 selects a predetermined range (for example, a range of-200 to-100 mS) as a baseline with respect to each P peak. The range selected as the baseline is a range empirically determined experimentally as the range existing as the baseline. In addition, the portion to be the baseline may also be selected by the user.

Next, the control unit 11 performs baseline correction of the average P-wave data based on the selected baseline portion (step S26).

For example, baseline correction is performed by calculating an average of the selected baseline portion and subtracting the average from the waveform. This enables the value of the baseline portion to be substantially 0.

Next, the control unit 11 performs a band pass filter process on the addition average waveform after the baseline correction (step S27). The frequency range of the passing is preferably 30-300 Hz, and most preferably 40-150 Hz.

Next, the control unit 11 sets a detection range of the P-wave segment in the average P-wave data after the band-pass filter processing (step S28).

For example, the range from the immediate rear of the baseline portion selected in step S25 to the immediate front of the QRS wave of the average P-wave data after the band-pass filter processing is set as the detection range of the P-wave segment.

Next, the control unit 11 detects an extremum in the detection range of the P-wave segment (step S29).

Next, the control unit 11 calculates a standard deviation (baseline standard deviation) of the value of the baseline portion of the average P-wave data after the band-pass filter processing (step S30).

Next, when the potential difference between the adjacent extreme values detected in step S30 exceeds n times the baseline standard deviation (n is a positive number), the controller 11 defines a line connecting the two points as a P-wave segment (step S31).

n is a value calculated based on experiments, and is, for example, 3.

Next, the control unit 11 calculates the number of P-wave segments (step S32).

Next, the control unit 11 calculates the time from the start point to the end point of the P-wave segment (the duration of the P-wave segment) (step S33).

Then, the control unit 11 analyzes the possibility of the occurrence of atrial fibrillation based on the number and/or duration of P-wave segments, displays the analysis result on the display unit 14 (step S34), and ends the atrial fibrillation analysis process B.

The processing of step S34 is, for example, the same processing as that described in step S16 of fig. 2.

In embodiment 2 described above, since the possibility of the occurrence of atrial fibrillation is analyzed using electrocardiographic data of leads in only one direction (for example, the left-right direction) of a plane including the body axis direction and the left-right direction of the subject, measurement results in a simple electrocardiographic examination using a wrist band-type or wristwatch-type device can be used, and the load on the subject can be reduced, which is preferable. On the other hand, there is a possibility that the analysis accuracy is inferior to that in the case of the electrocardiogram using leads in two directions as in embodiment 1.

Therefore, for example, it is also possible to provide: electrocardiographic measurements including leads (leads to be analyzed) used for analysis in the atrial fibrillation analysis process B and leads in directions orthogonal to the leads in a plane including the body axis direction and the left-right direction of the subject are performed a plurality of times, and the number and/or duration of P-wave segments calculated using only electrocardiographic data of leads to be analyzed among the obtained electrocardiographic data and the number and/or duration of P-wave segments calculated using electrocardiographic data of leads in two directions, the direction to be analyzed and the direction orthogonal thereto, are input to an AI built in the atrial fibrillation analysis device 1 and learned, and a machine learning model is created. Then, it is also possible to: the control unit 11 inputs the number and/or duration of P-wave segments calculated in the processing up to steps S32 to S33 in fig. 11 to the machine learning model, estimates the number and/or duration of P-wave segments calculated using electrocardiographic data of leads in two directions, and analyzes the possibility of the onset of atrial fibrillation based on the estimated number and/or duration of P-wave segments. This makes it possible to obtain the same effect as in embodiment 1 by a simpler inspection.

As described above, according to the atrial fibrillation analysis device 1, the control unit 11 acquires P-wave data from only an electrocardiogram based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject or an electrocardiogram based on leads in two directions orthogonal to the plane, and extracts a P-wave segment from the acquired P-wave data. The likelihood of onset of atrial fibrillation is then analyzed based on the number of P-wave segments and/or the duration of the P-wave segments.

Therefore, the possibility of the occurrence of atrial fibrillation is analyzed using only electrocardiographic data based on leads in one direction or leads in two orthogonal directions on a plane including the body axis direction and the left-right direction of the subject during non-onset, without using electrocardiographic data based on leads in the front-back direction of the body, so that the possibility of the occurrence of atrial fibrillation can be predicted even during non-onset by noninvasive, inexpensive, easy, and short-time examination, by analyzing only electrocardiographic data based on leads in one direction or two orthogonal directions, which is a plane including the body axis direction and the left-right direction of the subject, and particularly by measuring simple limb leads of the 12-lead electrocardiogram. As a result, early diagnosis of atrial fibrillation can be performed.

The description of the above embodiments is a preferred example of the present invention, and is not limited to this.

For example, in the above-described embodiments 1 and 2, the atrial fibrillation analysis device 1 is a device that analyzes the possibility of the occurrence of atrial fibrillation only from electrocardiographic data based on leads in one direction on a plane including the body axis direction and the left-right direction of the subject or only from electrocardiographic data in two directions orthogonal to each other on a plane including the body axis direction and the left-right direction of the subject, although the device and the atrial fibrillation analysis method in the device have been described, the device and the analysis method (P-wave plate segment analysis device and P-wave plate segment analysis method) may be configured to calculate the number and/or duration of P-wave segments from only electrocardiographic data of leads in one direction in a plane including the body axis direction and the left-right direction of the subject or only electrocardiographic data in two directions orthogonal to each other in a plane including the body axis direction and the left-right direction of the subject.

In addition, in the above-described embodiment 2, the case where the electrocardiogram measuring unit 15 measures only electrocardiogram data based on leads in a predetermined one direction (for example, the left-right direction) on a plane including the body axis direction and the left-right direction of the subject has been described, but the present invention is not limited to this, and an electrocardiograph capable of acquiring electrocardiograms based on leads in a plurality of directions, such as a 12-lead electrocardiograph or an XYZ-lead electrocardiograph, may be used. The control unit 11 may acquire electrocardiographic data in a predetermined direction from the measured electrocardiographic data, and perform the P-wave plate segment analysis and the analysis of the possibility of the occurrence of atrial fibrillation.

In the above description, for example, an example of a computer-readable medium using a hard disk, a semiconductor nonvolatile memory, or the like as the program of the present invention is disclosed, but the present invention is not limited to this example. As another computer-readable medium, a portable recording medium such as a CD-ROM can be applied. In addition, a Carrier wave (Carrier wave) is also applicable as a medium for supplying data of the program of the present invention via a communication line.

The detailed structure and detailed operation of each device constituting the atrial fibrillation analysis device may be appropriately modified without departing from the scope of the present invention.

Industrial applicability of the invention

The invention can be used in the medical field.

Description of the reference symbols

1 atrial fibrillation analysis device

11 control part

12 storage part

13 operating part

14 display part

15 electrocardiogram measuring part

16 communication unit

17 bus line.