JP5413869B2 - ECG automatic analyzer and electrocardiogram automatic analysis program - Google Patents

Description

The present invention, ECG is measured from a subject (ECG: Electrocardiogram) about automatically analyzed to electrocardiogram automatic analysis equipment Contact and electrocardiogram automatic analysis program.

  An electrocardiogram widely used for diagnosing a heart disease is generally composed of 12 types of induction waveforms called standard 12 induction waveforms. This standard 12-lead waveform includes six lead waveforms (I, II, III, aVR, aVL, aVF) obtained from four electrodes respectively attached to both wrists and ankles of the subject, It consists of six induction waveforms (V1, V2, V3, V4, V5, V6) obtained from six electrodes attached to the chest. The heart disease of the subject can be diagnosed by the characteristics of the standard 12-lead waveform measured from the subject.

  On the other hand, depending on the type of heart disease, there is a feature that it is difficult to appear in the standard 12-lead waveform and easily appears in other induced waveforms. For example, Brugada syndrome is known to show characteristic ST elevation (covered type, saddleback type) in the right chest lead waveform (V1 to V3). This characteristic of the Brugada syndrome is called Brugada sign, and is more likely to appear in the induction waveform measured by raising the attachment position of the chest electrode than the standard 12 induction waveform, and may not be captured only by the analysis of the standard 12 induction waveform. is there.

  Therefore, in order to diagnose the Brugada syndrome, after measuring the standard 12-lead waveform, raise the attachment position of the chest electrode and re-measure, and analyze both of these lead waveforms to determine the presence or absence of Brugada sign. desirable. However, changing the electrode attachment position and re-measurement of the 12-lead waveform effectively means that the measurement is performed twice for one subject, It is cumbersome to perform such measurement every time.

Therefore, as a technique for solving this problem, the present applicant uses, for example, a standard 12-lead waveform measured from the subject, for example, a virtual position between the first and second positions of the electrode positions of the V1-V3 induced waveform. A biological information processing apparatus that synthesizes a predicted induced waveform that would have been measured at an electrode position has been proposed (see, for example, Patent Document 1). According to this technique, it is considered that the diagnostic accuracy of the Brugada syndrome can be improved by analyzing the synthesized predicted induced waveform in addition to the actually measured standard 12 induced waveform.
JP 2006-141813 A

  However, in the technique described in Patent Document 1, although the accuracy of diagnosis of Brugada syndrome can be further improved as the number of predicted induced waveforms to be analyzed increases, the burden on the doctor who interprets these increases, Efficiency is lowered.

The present invention has been made in view of the foregoing, provides subjects while improving the diagnostic accuracy of a cardiac disease, an electrocardiogram automatic analysis equipment Contact and electrocardiogram automatic analysis program capable of enhancing the diagnostic efficiency The purpose is to do.

An electrocardiogram automatic analyzer according to the present invention includes an acquisition unit that acquires a synthetic electrocardiogram waveform that can be derived from an actually measured electrocardiogram waveform, a measurement unit that measures data of the acquired synthetic electrocardiogram waveform, and an acquired synthetic heart the presence or absence of features of Brugada syndrome in the electrocardiographic waveform, possess a determination unit by using the data measured, and the measurement unit, the synthetic electrocardiographic waveform incomplete RSR 'pattern or complete right bundle branch block pattern And STj, ST1, ST2, Ta, and Sa are measured as parameters of the amplitude of the synthetic electrocardiogram waveform .

The electrocardiogram automatic analysis program of the present invention includes an acquisition step of acquiring a synthetic electrocardiogram waveform that can be derived from an actually measured electrocardiogram waveform, a measurement step of measuring data of the acquired synthetic electrocardiogram waveform, and an acquired synthetic heart And determining whether or not there is a characteristic of Brugada syndrome in the radio wave shape by using measured data, and the measuring step includes an incomplete RSR ′ pattern or a complete right leg of the synthetic electrocardiogram waveform. STj, ST1, ST2, Ta, and Sa are measured as parameters of the presence or absence of the block pattern and the amplitude of the synthetic electrocardiogram waveform .

  ADVANTAGE OF THE INVENTION According to this invention, the diagnostic efficiency can be improved, improving the diagnostic accuracy of the subject's heart disease.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

  FIG. 1 is a block diagram showing an example of the configuration of an electrocardiogram automatic analyzer 100 according to an embodiment of the present invention.

  The electrocardiogram automatic analysis device 100 analyzes a measured lead electrocardiogram waveform transmitted from an external device such as an electrocardiogram measurement device or a form for analyzing a measured lead electrocardiogram waveform recorded on a recording medium such as a memory card or an optical disk. Various forms such as a form or a form incorporated in an electrocardiogram measurement apparatus can be adopted. In the present embodiment, a description will be given of an example in which an actually measured electrocardiographic waveform measured and transmitted by an electrocardiogram measuring apparatus is analyzed.

  In FIG. 1, an electrocardiogram automatic analyzer 100 includes an actually measured lead electrocardiogram waveform readout unit 110, a filter processing unit 120, a waveform synthesis unit 130, a synthetic electrocardiogram waveform acquisition unit 140, a waveform data measurement unit 150, a heart It has a disease feature database (hereinafter referred to as “heart disease feature DB”) 160, a heart disease determination unit 170, and an output unit 180.

  The measured lead electrocardiogram waveform reading unit 110 reads the actually measured lead electrocardiogram waveform. That is, the actually measured lead electrocardiogram waveform reading unit 110 receives the actually measured lead electrocardiogram waveform transmitted from the electrocardiogram measuring apparatus. The actually measured lead electrocardiogram waveform reading unit 110 outputs the read actually measured lead electrocardiogram waveform to the filter processing unit 120.

  Here, the “measured lead electrocardiogram waveform” is obtained by subjecting an electrocardiogram signal detected by an electrode (for example, 12 lead electrodes) attached to the body surface of the subject to processing such as amplification and analog-digital conversion. Is an electrocardiogram waveform (for example, a standard 12-lead waveform) obtained by the above. In the present embodiment, a standard 12-lead waveform will be described as an example of the “measured lead electrocardiogram waveform”.

  The filter processing unit 120 removes, for example, AC disturbance (ham), electromyogram disturbance (muskell), and baseline fluctuation (drift) from the measured induced electrocardiogram waveform input from the measured induced electrocardiogram waveform reading unit 110. Waveform shaping processing is performed. The filter processing unit 120 outputs the actually measured electrocardiographic waveform after the waveform shaping process to the waveform synthesis unit 130.

  The waveform synthesizer 130 derives a synthesized electrocardiogram waveform from the actually measured induced electrocardiogram waveform input from the filter processor 120. More specifically, first, the waveform synthesis unit 130 creates an XYZ lead waveform from the actually measured lead electrocardiogram waveform. Next, the waveform synthesizer 130 converts the created XYZ induced waveform into an XYZ component of the electromotive force vector H in which changes in the electromotive force are captured three-dimensionally (stereoscopically). Then, the waveform synthesizer 130 obtains the inner product of the XYZ component of the electromotive force vector H and the synthetic induction vector L indicating the position coordinates on the body surface of the subject, thereby obtaining the on-body surface of the subject. A plurality of synthetic electrocardiogram waveforms in a range that covers the diagnostic site are prepared. The plurality of synthetic electrocardiogram waveforms are electrocardiogram waveforms that are not actually measured but are predicted to be measured using electrodes attached to a part on the body surface of the subject. The waveform synthesizing unit 130 outputs the created plurality of synthesized electrocardiographic waveforms to the synthesized electrocardiographic waveform acquiring unit 140. The waveform synthesis processing by the waveform synthesis unit 130 will be described in detail later.

  A synthetic electrocardiogram waveform acquisition unit 140 as an acquisition unit acquires a plurality of synthetic electrocardiogram waveforms input from the waveform synthesis unit 130. The synthetic electrocardiogram waveform acquisition unit 140 outputs the plurality of acquired synthetic electrocardiogram waveforms to the waveform data measurement unit 150 and the output unit 180.

  The waveform data measuring unit 150 as a measuring unit measures data indicating the characteristics of the electrocardiographic waveform for each of the plurality of synthetic electrocardiographic waveforms input from the synthetic electrocardiographic waveform acquiring unit 140. The data indicating the characteristics of the electrocardiographic waveform includes, for example, the amplitude, time width, and shape of each portion of the synthetic electrocardiographic waveform. The waveform data measurement unit 150 outputs data indicating the characteristics of the measured synthetic electrocardiogram waveform to the heart disease determination unit 170. The measurement processing of data indicating the characteristics of the synthetic electrocardiographic waveform by the waveform data measuring unit 150 will be described in detail later.

  The heart disease feature DB 160 stores a heart disease name and a diagnosis algorithm for the heart disease in association with each other. This diagnostic algorithm indicates a diagnostic criterion or a diagnostic basis for a heart disease based on waveform data. In other words, the diagnostic algorithm is created so that the presence or absence of the feature of the heart disease can be determined using the data indicating the feature of the synthetic electrocardiogram waveform measured by the waveform data measuring unit 150. The diagnostic algorithm stored in the heart disease feature DB 160 will be described in detail while illustrating later.

  The heart disease determination unit 170 serving as a determination unit uses the data indicating the characteristics of the synthetic electrocardiogram waveform input from the waveform data measurement unit 150 to determine whether or not there is a specific heart disease characteristic in the synthetic electrocardiogram waveform. . More specifically, the heart disease determination unit 170 determines whether or not the data indicating the characteristics of the synthetic electrocardiogram waveform satisfies a condition (diagnosis standard) defined by the diagnosis algorithm held in the heart disease characteristic DB 160. To do. The heart disease determination unit 170 outputs the determination result of the presence or absence of features of the heart disease to the output unit 180. The determination process of the presence or absence of a heart disease by the heart disease determination unit 170 will be described in detail later.

  The output unit 180 is, for example, a display device such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube), or a printing device such as a printer. The output unit 180 outputs a synthetic electrocardiogram waveform determined from the synthetic electrocardiogram waveform input from the synthetic electrocardiogram waveform acquisition unit 140 as having some heart disease characteristic, a determination result, and a comment related thereto. That is, the output unit 180 has a function as a warning unit that warns of abnormalities in the composite electrocardiogram waveform. In addition, the warning of the abnormality of the synthetic electrocardiogram waveform can be performed according to code classification such as various MN codes.

  In the present embodiment, the measured lead electrocardiogram waveform reading unit 110, the filter processing unit 120, and the waveform synthesis unit 130 have been described as internal components of the electrocardiogram automatic analyzer 100, but the present invention is not limited to this. For example, some or all of these components may be provided outside the electrocardiogram automatic analyzer 100.

  The configuration of the electrocardiogram automatic analyzer 100 has been described above.

  Here, the waveform synthesis processing by the waveform synthesis unit 130 will be described.

In the waveform synthesis process by the waveform synthesis unit 130, once the XYZ components of the electromotive force vector H are obtained from the actually measured electrocardiogram-induced waveform, the XYZ components of the electromotive force vector H and the position coordinates on the body surface of the subject. By calculating the inner product with the synthetic induction vector L indicating, it is possible to derive a synthetic electrocardiogram waveform that is predicted to be actually measured using electrodes attached to every part on the body surface of the subject. Based on the principle. In this principle, the potential at an arbitrary point P on the body surface is Vp, the XYZ component of the electromotive force vector H is H (X, Y, Z), and the combined induction vector is L (a, b, c). ) Is proved by the fact that the following equation (1) holds.
Vp = H · L = aX + bY + cZ (1)

H (X, Y, Z) is obtained by the following equation (2) indicating a linear sum of standard 12-lead waveforms, for example, a linear sum using leads V1 to V6, lead I, and lead II. This technique is widely known as the “inverse Dower method”. For the inverse Dower method, see, for example, (PW Macfarlane et al., Translated by Kuniaki Otsuka, “12-lead vector electrocardiogram”, Medical Electro Times, Inc., issued on June 11, 1996, pp. 33-36) I want.
X = -0.172V1-0.074V2 + 0.122V3 + 0.231V4 + 0.239V5 + 0.194V6 + 0.156 (I) -0.010 (II)
Y = 0.057V1-0.019V2-0.106V3-0.022V4 + 0.041V5 + 0.048V6-0.227 (I) +0.887 (II)
Z = 0.229V1 + 0.310V2 + 0.246V3 + 0.063V4-0.055V5-0.108V6-0.022 (I) -0.102 (II) (2)

  L (a, b, c) is obtained by determining which point on the image surface (Image) of Frank corresponds to a point on the body surface of the subject. More specifically, after obtaining the coordinates on the image surface corresponding to the electrode position used for the standard 12 lead in the torso model by the torso model and the image surface, the combined lead vector for the standard 12 lead waveform from the coordinates of the electrode position. L (a, b, c) is determined. Here, the image surface is an XYZ space obtained by projecting a potential on the body surface in a state where H (X, Y, Z) is fixed in the above formula (1). For details of the torso model and image surface, see Frank's paper (Ernest Frank, "THE IMAGE SURFACE OF A HOMOGENEOUS TORSO", Amer. Heart. J, 47: pp. 757-768, 1954).

  As described above, by using the torso model and the image surface, it is possible to obtain a synthetic guide vector indicating any position coordinate on the body surface of the subject. As a result, it is possible to derive a large number of combined induction waveforms when it is assumed that electrodes are attached to each point where the diagnostic site is finely cut. For example, at the time of diagnosis of Brugada syndrome, a large number of synthetic induction waveforms that are predicted to be measured at a number of points finely chopped up to one or two electrode positions of the V1-V3 induction waveform in standard 12 leads Can be derived.

  Strictly speaking, the image surface may vary from subject to subject depending on various parameters such as body type, age, and gender, so there may be some deviation in the coordinate position on the image surface. In order to deal with this, as shown in Patent Document 1 described above, a plurality of candidate waveforms are generated for the actually measured induced waveform, and among these candidate waveforms, a candidate waveform that is most similar to the standard 12 induced waveform is synthesized. The used guidance vector may be selected and used for the waveform synthesis processing of the waveform synthesis unit 130.

  The waveform synthesis process by the waveform synthesis unit 130 has been described above.

  Next, the measurement processing of data indicating the characteristics of the synthetic electrocardiographic waveform by the waveform data measuring unit 150 will be described. The data measured by the waveform data measuring unit 150 is roughly divided into items measured from a continuous synthetic electrocardiogram waveform and items measured from one of the continuous synthetic electrocardiogram waveforms (one heartbeat). .

(Measurement of data from continuous synthetic ECG waveform)
A measurement process of data from continuous synthetic electrocardiogram waveforms will be described with reference to FIGS. 2A to 2C are diagrams illustrating an example of characteristics of data measured from a continuous synthetic electrocardiogram waveform.

  First, as shown in FIG. 2A, the waveform data measurement unit 150 obtains the start point and end point of the QRS wave and the end point of the T wave for each heartbeat.

  Next, as shown in FIG. 2B, the waveform data measurement unit 150 measures the P wave and the f wave in a section (search area) from the start point of the QRS wave to the end point of the T wave of the previous heartbeat. Thereby, each division point of the continuous synthetic electrocardiogram waveform is recognized.

Then, as shown in FIG. 2C, the waveform data measurement unit 150 measures the following items for each heartbeat.
RR time: time between previous R wave, PR time: time between QRS wave start point and P wave start point QRS time: time between QRS wave start point and end point -QT time: time between the start point of QRS wave and the end point of T wave-Number of P wave and f wave: Number of P wave and f wave in the interval to T wave end point of previous heartbeat-PP time : Time between P wave of previous heartbeat P1-P2 time: Time between first and second when there are two P waves ・ Amplitude of QRS wave: Amplitude of QRS wave ・ QRS wave Area: Integral value from QRS wave start point to end point QRS wave axis: Electrical axis obtained from QRS wave area QRS wave direction: Information indicating whether the QRS wave is upward or downward

  Finally, the waveform data measuring unit 150 obtains an average value of all heartbeats of the RR time, the PR time, the QRS time, and the QT time from the measured values of each heartbeat.

(Measurement of data from one of the continuous synthetic ECG waveforms)
A measurement process of data from one of the continuous synthetic electrocardiogram waveforms will be described with reference to FIGS. FIGS. 3A to 3E are diagrams illustrating an example of characteristics of data measured from one of continuous synthetic electrocardiogram waveforms.

  First, the waveform data measurement unit 150 extracts one heartbeat of the most prevalent waveform from among the continuous synthetic electrocardiogram waveforms in order to perform waveform analysis (extraction of dominant waveform). More specifically, the waveform data measurement unit 150 removes a heartbeat that is suspected of extrasystole from a continuous synthetic electrocardiogram waveform, and then checks a dominant waveform from check items for short RR, abnormal QRS, and baseline drift. Then, 400 ms before the R wave apex and 600 ms (1 second) after the R wave apex are extracted in phase.

  On the other hand, the waveform data measurement unit 150 calculates a waveform obtained by superimposing and averaging the waveforms of the heartbeats with the apex of the R wave of each heartbeat as a base point after removing the abnormal heartbeat (calculation of average waveform).

Then, the waveform data measurement unit 150 recognizes the division points using both the extracted dominant waveform and the calculated average waveform, and further subdivides the waveform, determines the amplitude and time width of the waveform, and the like. calculate. Thereby, as shown in FIGS. 3A to 3E, the following items are obtained.
P1a (mV): P1 amplitude (+,-)
P2a (mV): P2 amplitude (+,-)
Qa (mV): Q amplitude (+,-)
Ra (mV): R amplitude (+,-)
Sa (mV): S amplitude (+,-)
R′a (mV): R ′ amplitude (+, −)
S'a (mV): S 'amplitude (+,-)
ST1 (mV): ST1 amplitude (+,-)
ST2 (mV): ST2 amplitude (+,-)
T1a (mV): T1a amplitude (+,-)
T2a (mV): T2a amplitude (+,-)
P1d (ms): P1 time width P2d (ms): P2 time width Qd (ms): Q time width Rd (ms): R time width Sd (ms): S time width -R'd (ms): Time width of R '-S'd (ms): Time width of S'-PR (ms): Time width from Pb to Qb-QRS (ms): Qb-Se Time range to FVT (ms): Time from Qb to first waveform vertex

  Each data measured by the waveform data measuring unit 150 can be used as an important parameter for determining the presence / absence of various heart disease characteristics. The waveform data measurement unit 150 performs the series of data measurement processes described above for each of the plurality of synthetic electrocardiogram waveforms input from the synthetic electrocardiogram waveform acquisition unit 140.

  The synthetic electrocardiographic waveform data measured by the waveform data measuring unit 150 is not limited to the above-described data, and may be further added depending on the heart disease to be diagnosed.

  In the above, the measurement processing of the data which shows the characteristic of the synthetic electrocardiogram waveform by the waveform data measurement unit 150 has been described.

  Next, a diagnosis algorithm stored in the heart disease feature DB 160 will be described with reference to FIG. FIG. 4 is a diagram illustrating an example of a diagnostic algorithm stored in the heart disease feature DB 160.

  In FIG. 4, the diagnostic algorithms are classified by heart disease names. Each diagnosis algorithm is created so that the presence or absence of a feature of a heart disease can be determined using data indicating the feature of the combined electrocardiogram waveform measured by the waveform data measurement unit 150.

  For example, the diagnostic algorithm (No. 1) uses the RR interval, the QST width, the presence / absence of a P wave, the regularity of the PP interval, and the presence / absence of an f wave and an F wave in a synthetic electrocardiogram waveform. It is created so that it can be determined whether or not.

  The diagnostic algorithm (No. 2) determines the presence and extent of ventricular hypertrophy using the QRS complex high potential, axial deviation, ST-T abnormality, P wave abnormality, etc. in the composite electrocardiogram waveform. Created as possible.

  The diagnostic algorithm (No. 3) is created so that the myocardial infarction site and its severity can be determined using the presence or absence and range of abnormal Q wave, ST rise, and coronary T wave in the composite electrocardiogram waveform. ing.

  Here, the diagnosis algorithm (No. 4) for diagnosing the Brugada syndrome will be described more specifically with reference to FIGS.

  FIGS. 5A to 5C are diagrams for explaining features of Brugada syndrome, for example, Brugada sign, in an electrocardiogram waveform. FIG. 5A is a diagram showing a synthetic electrocardiogram waveform having no waveform abnormality, and FIG. 5B is a diagram showing a synthetic electrocardiogram waveform exhibiting a Brugada sign indicating a saddleback type ST rise. FIG. 5 (C) is a diagram showing a synthetic electrocardiogram waveform exhibiting a Brugada sign indicating a covered ST rise.

  As shown in FIGS. 5A to 5C, the electrocardiographic waveform having the characteristics of the Brugada syndrome exhibits a characteristic ST increase as compared with an electrocardiographic waveform having no waveform abnormality. Therefore, the diagnostic algorithm (No. 4) for diagnosing Brugada syndrome is an algorithm for detecting this characteristic ST elevation.

(Diagnostic algorithm of saddleback type Brugada syndrome)
The detection condition of Brugada sign in saddleback type Brugada syndrome is that there is an incomplete RSR 'pattern or a complete right leg block pattern in FIG. 5 (B), and the following formula (3) is established by V1 induction or V2 induction It is.
ST1 ≧ 0.2 mV, Ta <STj × 1.5, and | Sa | ≦ 3.0 mV (3)
Here, STj is the ST value of the junction (point J) between the QRS wave and the ST region, and ST1 is the ST value from the point J to the point QT / 10.

(Diagnostic algorithm for covered Brugada syndrome)
The detection condition of Brugada sign in the covered Brugada syndrome is that, in FIG. 5C, the following expression (4) is established by V1 induction or V2 induction.
STj ≧ ST1 ≧ ST2, and ST1 ≧ 0.2 mV, Ta <STj × 1.5, and | Sa | ≦ 3.0 mV (4)
Here, STj is the ST value of the junction (Q point) between the QRS wave and the ST region, ST1 is the ST value from the J point to QT / 10, and ST2 is further QT / Q from ST1. ST value of 10 points.

  The diagnosis algorithm stored in the heart disease feature DB 160 has been described above.

  Next, heart disease determination processing by the heart disease determination unit 170 will be described.

  The heart disease determination unit 170 determines whether or not the data indicating the characteristics of the synthetic electrocardiogram waveform satisfies the conditions (diagnosis criteria) defined by the diagnostic algorithm held in the heart disease feature DB 160 as exemplified above. .

  For example, when determining the presence or absence of the Brugada syndrome feature in the synthetic electrocardiogram waveform, the heart disease determination unit 170 first detects the presence or absence of an incomplete RSR ′ pattern or a complete right leg block pattern, and then the measurement unit 150 It is determined whether the measured STj, ST1, ST2, Ta, and Sa satisfy the above formula (3) or formula (4).

  When the incomplete RSR ′ pattern or the complete right leg block pattern is detected and the expression (3) is satisfied, the heart disease determination unit 170 determines that the synthetic electrocardiogram waveform has the characteristics of the saddleback type Brugada syndrome. To do. Further, when Expression (4) is satisfied, the heart disease determination unit 170 determines that the combined electrocardiogram waveform has a feature of a covered Brugada syndrome. On the other hand, if neither of the expressions (3) and (4) is satisfied, the heart disease determination unit 170 determines that the synthetic electrocardiogram waveform does not have the Brugada syndrome characteristic, that is, a normal waveform.

  The heart disease determination process by the heart disease determination unit 170 has been described above.

  Hereinafter, the operation of the electrocardiogram automatic analyzer 100 configured as described above will be described with reference to FIG.

  FIG. 6 is a flowchart showing an example of an electrocardiogram automatic analysis process by the electrocardiogram automatic analyzer 100 according to the present embodiment. Here, the case where the presence or absence of the characteristic of Brugada syndrome in the synthetic electrocardiogram waveform is determined will be described as an example. Note that the procedure of the automatic analysis process described here is an example, and the steps included in this procedure and the order thereof can be variously changed.

  First, the measured lead electrocardiogram waveform reading unit 110 reads the original waveform data, that is, the actually measured lead electrocardiogram waveform (S1). The actually measured electrocardiogram waveform read by the actually measured electrocardiogram waveform reading unit 110 is subjected to waveform shaping processing by the filter processing unit 120 and output to the waveform synthesis unit 130.

  Next, the waveform synthesizer 130 generates an XYZ lead waveform from the input actually measured lead electrocardiogram waveform (S2), and a synthetic lead vector indicating the generated XYZ lead waveform and position coordinates on the body surface of the subject, Are used to create a number of synthetic electrocardiographic waveforms in a range that covers the diagnosis site of the subject (S3). The large number of synthesized electrocardiogram waveforms created by the waveform synthesizer 130 are acquired by the synthesized electrocardiogram waveform acquisition unit 140.

  Here, the waveform synthesizer 130 is at least a diagnostic part for determining the presence or absence of features of the Brugada syndrome, for example, electrodes on the first and second ribs on the right chest lead V1 to V3 in the standard 12 lead A synthetic electrocardiogram waveform that is expected to be measured when the is attached is created. In this way, a synthetic electrocardiogram waveform is comprehensively created at a site where the characteristics of Brugada syndrome are likely to appear. The number of synthesized electrocardiogram waveforms created by the waveform synthesizer 130 is not particularly limited, and a plurality of synthesized electrocardiogram waveforms may be created from one glance.

  Next, the waveform data measurement unit 150 shows the characteristics (for example, amplitude, time width, shape, etc.) of the electrocardiographic waveform in the various items described above for the synthetic electrocardiographic waveform acquired by the synthetic electrocardiographic waveform acquisition unit 140. Data is measured (S4). Here, the waveform data measuring unit 150 measures at least data (STj, ST1, ST2, Ta, Sa) for detecting the presence or absence of the Brugada sign for the synthetic electrocardiogram waveform. These data measured by the waveform data measurement unit 150 are output to the heart disease determination unit 170.

  The heart disease determination unit 170 uses the data indicating the characteristics of the composite waveform input from the waveform data measurement unit 150 and the diagnosis algorithm stored in the heart disease feature DB 160 to determine whether there is a heart disease feature in the composite electrocardiogram waveform. To determine whether the composite electrocardiogram waveform is abnormal or normal (S5). Here, the heart disease determination unit 170 first detects the presence or absence of an incomplete RSR ′ pattern or a complete right leg block pattern from the synthetic electrocardiogram waveform, and the data measured by the waveform data measurement unit 150 is the above equation (3). ) Or Expression (4) is determined to determine whether the composite electrocardiogram waveform is abnormal or normal (in this case, whether the composite waveform exhibits a Brugada sign).

  The waveform data measuring unit 150 and the heart disease determining unit 170 are created by the waveform synthesizing unit 130, and for all of the many synthetic electrocardiographic waveforms acquired by the synthetic waveform acquiring unit 140, the above-described data measurement process and waveform calculation are performed. Abnormal or normal diagnosis processing is performed (S6: NO, S7).

  Then, when the processing of step S4 and step S5 is completed for all synthetic electrocardiogram waveforms (S6: YES), heart disease determination unit 170 outputs the determination result to output unit 180 for each synthetic electrocardiogram waveform. .

  When the output unit 180 receives from the heart disease determination unit 170 a determination result indicating that any of the synthetic electrocardiogram waveforms is abnormal, that is, presents a Brugada sign (S8: YES), the output of the synthetic electrocardiogram The form and the determination result are output, and a comment about the form is output (S9), and the automatic analysis process is terminated. This comment includes, for example, a description of the waveform, diagnostic criteria and basis, clinical disease to be considered, severity and response, or suggestion of necessary secondary tests.

  On the other hand, when the diagnosis result indicating that there is no abnormality in any of the synthetic electrocardiogram waveforms is input from the heart disease determination unit 170 (S8: NO), the output unit 180 determines that there is no abnormality in the electrocardiogram and performs automatic analysis processing. Exit. In this case, the output unit 180 may output a comment indicating that an electrocardiogram abnormality has not been diagnosed and terminate the automatic analysis process.

  Here, the heart disease that is the object of diagnosis has been described specifically for Brugada syndrome, but the present invention is not limited to this. In other words, the electrocardiogram automatic analyzer 100 can automatically diagnose the presence or absence of characteristics of a plurality of heart diseases (for example, arrhythmia, ventricular hypertrophy, myocardial infarction, WPW, etc.) in the synthetic electrocardiogram waveform.

  The electrocardiogram automatic analysis processing by the electrocardiogram automatic analyzer 100 has been described above.

  In the present embodiment, it is predicted that the measurement is performed at an electrode position above the electrode position of the right chest leads V1 to V3 in the standard 12 leads in order to determine the presence or absence of features of Brugada syndrome. Although a synthetic electrocardiogram waveform is created, the present invention is not limited to this. For example, when diagnosing a right ventricular abnormality in a child, it is preferable to create a synthetic electrocardiogram waveform around the electrode positions of V3R to V4R, and when diagnosing posterior wall infarction, the electrode positions of V7 to V9 It is preferable to create a synthetic electrocardiogram waveform in the vicinity of. As described above, by generating and analyzing a synthetic electrocardiogram waveform around a site where a characteristic of a heart disease that is a diagnosis target is likely to appear, the possibility that a waveform abnormality is discovered can be improved.

  In the present embodiment, the standard 12-lead waveform is described as an example of the actually measured lead electrocardiogram, but the present invention is not limited to this. For example, the measured lead electrocardiogram waveform may be a waveform derived by NASA lead or CM5 lead used in the Holter electrocardiogram. That is, as long as the actually-guided electrocardiogram waveform can generate the XYZ lead waveform necessary for generating the composite electrocardiogram waveform, the guide method and the number of waveforms are not limited.

  Further, although cases have been described with the above embodiment as examples where the present invention is configured by hardware, the present invention can also be realized by software. For example, the above-described electrocardiogram automatic analysis method may be executed by a computer as software. That is, a program for executing the electrocardiogram automatic analysis method described in the above embodiment is recorded in advance on a recording medium such as a ROM (Read Only Memory), and the program is operated by a CPU (Central Processing Unit). The electrocardiogram automatic analysis method of the present invention can be executed.

  As described above, according to the present embodiment, the synthesized electrocardiogram waveform acquisition unit 140 acquires the synthesized electrocardiogram waveform derived from the actually measured induced electrocardiogram waveform, and the waveform data measurement unit 150 acquires the synthesized heart. The radio wave shape data is measured, and the heart disease determination unit 170 determines whether or not there is a feature of a specific heart disease in the obtained synthetic electrocardiogram waveform using the measurement data of the waveform data measurement unit 150. As a result, it is possible to automatically perform a diagnosis of a heart disease without leakage in a range that covers the site where the electrodes are attached by simply measuring an actually measured electrocardiogram waveform, for example, a standard 12-lead waveform. That is, even if the characteristic of the heart disease does not appear in the actually measured electrocardiogram waveform, it may appear in the synthesized electrocardiogram waveform, so that the diagnosis accuracy can be improved. Even if the number of synthetic electrocardiogram waveforms to be determined increases, the determination process is automatically performed by the waveform data measurement unit 150 and the heart disease determination unit 170, so that highly efficient diagnosis can still be realized.

  Moreover, since the automatic diagnosis technique of the present invention is performed by a quantitative method based on waveform data and a diagnosis algorithm, diagnosis constancy and reproducibility are high. As a result, the automatic diagnosis technique of the present invention can be used in the sense of an objective double check after interpretation by a doctor, while waveform data to be interpreted by a doctor from a large number of waveform data, that is, determined as abnormal. It can also be used to extract the waveform data to be processed.

  Therefore, the automatic diagnosis technology of the present invention can detect whether or not there is a characteristic of a dangerous disease that is present in a low rate of 1 or 2 in 1000 people, such as Brugada syndrome, and may cause sudden death. It is particularly useful for determining.

The block diagram which shows an example of a structure of the electrocardiogram automatic analyzer which concerns on one embodiment of this invention (A) The figure which shows an example of the characteristic of the data measured from the continuous synthetic electrocardiogram waveform, (B) The figure which shows the other example of the characteristic of the data measured from the continuous synthetic electrocardiogram waveform, (C) Continuous Of yet another example of data characteristics measured from the synthesized ECG waveform (A) The figure which shows an example of the characteristic of the data measured from one of the continuous synthetic electrocardiogram waveforms, (B) The other of the characteristic of the data measured from one of the continuous synthetic electrocardiogram waveforms (C) The figure which shows the further another example of the characteristic of the data measured from one of the continuous synthetic electrocardiogram waveforms, (D) One of the continuous synthetic electrocardiogram waveforms The figure which shows the further another example of the characteristic of the data measured from (E) The figure which shows the further another example of the characteristic of the data measured from one of the continuous synthetic electrocardiogram waveforms The figure which shows an example of the diagnostic algorithm held in the heart disease feature database (A) a diagram showing an electrocardiogram waveform without waveform abnormality, (B) a diagram showing an electrocardiogram waveform exhibiting a saddleback type ST elevation, and (C) a heart presenting a covulated type ST elevation. Diagram showing radio wave form Flowchart showing an example of an electrocardiogram automatic analysis process by the electrocardiogram automatic analyzer according to the present embodiment

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Electrocardiogram automatic analyzer 110 Actual measurement induced electrocardiogram waveform reading unit 120 Filter processing unit 130 Waveform synthesis unit 140 Synthetic electrocardiogram waveform acquisition unit 150 Waveform data measurement unit 160 Heart disease characteristic database 170 Heart disease determination unit 180 Output unit

Claims (6)

An acquisition unit for acquiring a synthetic electrocardiogram waveform that can be derived from the actually measured electrocardiogram waveform;
A measurement unit for measuring the data of the obtained synthetic electrocardiogram waveform;
A determination unit that determines the presence or absence of a characteristic of Brugada syndrome in the obtained synthetic electrocardiogram using data measured,
Have
The measurement unit measures the presence or absence of an incomplete RSR ′ pattern or a complete right leg block pattern of the synthetic electrocardiogram waveform, and STj, ST1, ST2, Ta, and Sa as amplitude parameters of the synthetic electrocardiogram waveform. To
An electrocardiogram automatic analyzer characterized by that. The measurement unit measures the parameter using a dominant waveform extracted from the synthetic electrocardiogram waveform and an average waveform calculated from the synthetic electrocardiogram waveform.
The electrocardiogram automatic analyzer according to claim 1. The synthetic electrocardiographic waveform is derived by an inner product of an electromotive force vector obtained from a linear sum of the actually measured electrocardiographic waveform and a synthetic induction vector indicating coordinates on the body surface of the subject.
The electrocardiogram automatic analyzer according to claim 1. As a result of the determination, when it is determined that the acquired synthetic electrocardiogram waveform has characteristics of a specific heart disease, it further includes a warning unit that issues a warning.
The electrocardiogram automatic analyzer according to claim 1. The synthetic electrocardiogram waveform includes a lead electrocardiogram waveform predicted to be measured when an electrode is attached at a position above the electrode position corresponding to the right chest lead in the standard 12 lead.
The electrocardiogram automatic analyzer according to claim 1. An acquisition step of acquiring a synthetic electrocardiogram waveform derivable from the actually measured electrocardiogram waveform;
A measurement step for measuring the data of the obtained synthetic electrocardiogram waveform;
A determination step for determining the presence or absence of the Brugada syndrome characteristic in the obtained synthetic electrocardiogram using the measured data;
To the computer,
In the measurement step, STj, ST1, ST2, Ta, and Sa are measured as presence / absence of an incomplete RSR ′ pattern or a complete right leg block pattern of the synthetic electrocardiogram waveform and an amplitude parameter of the synthetic electrocardiogram waveform. To
An electrocardiogram automatic analysis program characterized by that.

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