JP3806371B2 - Detection and evaluation system for paroxysmal atrial fibrillation based on electrocardiogram - Google Patents

Detection and evaluation system for paroxysmal atrial fibrillation based on electrocardiogram Download PDF

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JP3806371B2
JP3806371B2 JP2002171136A JP2002171136A JP3806371B2 JP 3806371 B2 JP3806371 B2 JP 3806371B2 JP 2002171136 A JP2002171136 A JP 2002171136A JP 2002171136 A JP2002171136 A JP 2002171136A JP 3806371 B2 JP3806371 B2 JP 3806371B2
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atrial fibrillation
data
paroxysmal atrial
electrocardiogram
distribution
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JP2004016248A (en
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順一郎 早野
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順一郎 早野
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Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a detection / evaluation system for paroxysmal atrial fibrillation capable of appropriately and automatically identifying paroxysmal atrial fibrillation based on electrocardiogram data such as a Holter electrocardiogram and the like, and its evaluation. Is.
[0002]
[Prior art]
Conventionally, the prognosis of atrial fibrillation is more serious than is generally recognized. That is, even in a survey of all patients with chronic atrial fibrillation regardless of age or underlying disease, the mortality rate of patients in three years has increased to 20%. In particular, atrial fibrillation is associated with a high rate of embolism such as cerebral infarction in elderly people over 70 years of age, and worsens life prognosis and QOL (Quality of Life). .
Atrial fibrillation is itself a risk factor for heart failure, and if the underlying disease is equivalent to atrial fibrillation, the presence of atrial fibrillation increases mortality by 1.5 to 1.9 times.
[0003]
However, paroxysmal atrial fibrillation (PAF) is atrial fibrillation that appears transiently and has a duration ranging from a few seconds to a few days. Paroxysmal atrial fibrillation (PAF) is also associated with unpleasant symptoms in a significant number of patients and not only impairs QOL, but also carries the risk of embolism as does chronic atrial fibrillation. In addition, paroxysmal atrial fibrillation (PAF) is often a precursor to the transition to chronic atrial fibrillation.
[0004]
Therefore, grasping the presence, frequency, and duration of paroxysmal atrial fibrillation (PAF) is important in determining the therapeutic effect for preventing the onset of chronic atrial fibrillation. There are two types of paroxysmal atrial fibrillation (PAF), night type and intermediate type, depending on the temporal distribution of occurrence and cessation. Because the former type involves parasympathetic tone, and the latter type involves sympathetic tone, identifying which type an individual case belongs to is important in selecting a treatment for a patient. is important. In order to select such a treatment method, it is necessary to know the daily distribution of the occurrence time and stop time of paroxysmal atrial fibrillation (PAF).
[0005]
From this point of view, long-term ECG monitors such as Holter ECG have been used for diagnosis and clinical evaluation of paroxysmal atrial fibrillation (PAF). The device does not have a function to automatically detect paroxysmal atrial fibrillation (PAF).
[0006]
However, paroxysmal atrial fibrillation (PAF) appears seizureally and its duration varies from seconds to days. Diagnosis of paroxysmal atrial fibrillation (PAF) is confirmed by an electrocardiogram during the stroke, and there is no test method for diagnosing paroxysmal atrial fibrillation (PAF) including the electrocardiogram during non-stroke. For this reason, if the presence of paroxysmal atrial fibrillation (PAF) is assumed or if you want to know the frequency and temporal distribution of paroxysmal atrial fibrillation (PAF), Holter ECG is performed. At present, detection of atrial fibrillation (PAF) relies on visual observation of the electrocardiogram of the judge.
[0007]
[Problems to be solved by the invention]
However, it is apparent that there is a limit to visually determining paroxysmal atrial fibrillation (PAF) with respect to long-term electrocardiogram data obtained by the above-mentioned long-term electrocardiogram monitor. For example, in cases where the frequency of paroxysmal atrial fibrillation (PAF) is low, there is a high probability of missing paroxysmal atrial fibrillation (PAF). Also, in cases where the probability of the presence of paroxysmal atrial fibrillation (PAF) is low, taking a long time to determine the presence or absence of paroxysmal atrial fibrillation (PAF) is inefficient. Furthermore, with the resolution of Holter electrocardiogram analyzers that are currently in general use compared to Holter ECG original waveform data, paroxysmal atrial fibrillation (PAF) and other supraventricular tachycardia are visually observed. (Atrial flutter, frequent occurrence of supraventricular premature contraction, paroxysmal supraventricular tachycardia) are difficult to distinguish.
[0008]
Therefore, as a result of intensive studies and examinations, the present inventor, based on long-term electrocardiogram data obtained from a long-term electrocardiogram monitor using a Holter electrocardiogram, converts RR interval time-series data into, for example, Poincare (Poincare). ) By developing a two-dimensional scatter diagram (that is, a graph in which the RR interval is plotted on the vertical axis and the RR interval immediately before is plotted on the horizontal axis) by plotting or the like, the distribution form is inherent in the distribution form. From these characteristics, it was found that the presence or absence of paroxysmal atrial fibrillation (PAF) can be discriminated.
[0009]
That is, in the two-dimensional scatter diagram based on the time series data of the RR interval of the electrocardiogram, the paroxysmal atrial fibrillation is obtained when the distribution form of the plot is almost evenly distributed in a large square or a rhombus close thereto. (PAF) can be determined.
[0010]
Based on the detection of the paroxysmal atrial fibrillation (PAF), (1) automatically measuring the occurrence time and stop time of each paroxysmal atrial fibrillation (PAF), the duration and their time distribution, (2) Automatic measurement of mean heart rate, RR interval variability and minimum RR interval for each paroxysmal atrial fibrillation (PAF), and (3) the frequency of occurrence of paroxysmal atrial fibrillation (PAF) in one day and By automatically measuring the time and the like, it was found that an appropriate diagnosis for selecting a treatment method for paroxysmal atrial fibrillation (PAF) of a patient can be easily performed.
[0011]
Accordingly, an object of the present invention is to make it possible to easily and appropriately identify and identify paroxysmal atrial fibrillation (PAF) based on long-term electrocardiogram data obtained from a long-term electrocardiogram monitor such as a Holter electrocardiogram. Of time, duration, average heart rate, RR interval variability, frequency of occurrence, etc., regarding the occurrence and cessation of paroxysmal atrial fibrillation (PAF) to make an appropriate diagnosis in selecting a treatment for the patient It is an object of the present invention to provide a detection / evaluation system for paroxysmal atrial fibrillation based on an electrocardiogram capable of automatically measuring the amount and displaying the graph.
[0012]
[Means for Solving the Problems]
In order to achieve the above object, a system for detecting and evaluating paroxysmal atrial fibrillation based on an electrocardiogram according to the present invention includes an electrocardiogram monitor for obtaining electrocardiogram data,
An R wave is detected based on the electrocardiogram data, and with respect to the relationship between two adjacent RR interval data in a predetermined section, the first RR interval data is set as the horizontal coordinate, and the next RR is obtained. By repeating the operation of plotting the interval data as a point with the coordinate of the vertical axis for all continuous RR interval data while shifting the position of the window by one beat, the time series data of the RR interval is 2 ECG data processing means for converting to dimensional data to obtain a two-dimensional scatter diagram;
Regarding the distribution state of the two- dimensional data for obtaining the two-dimensional scatter diagram , the shape of the distribution of the two-dimensional data, the size of the distribution of the two-dimensional data, the irregularity of the distribution of the two-dimensional data, and the irregularity of the distribution of the two-dimensional data Hazuki group uniform on various indices of the reference, the identification determining paroxysmal atrial fibrillation discrimination and decision means paroxysmal atrial fibrillation by comparing the numerical value set in advance,
About the identification determination result of the paroxysmal atrial fibrillation, a display means for automatically measuring and displaying as a statistic of each of the various indicators of the distribution state of the two-dimensional data in the two-dimensional scatter diagram is provided. Features.
[0016]
DETAILED DESCRIPTION OF THE INVENTION
Next, an embodiment of a paroxysmal atrial fibrillation detection / evaluation system based on an electrocardiogram according to the present invention will be described in detail with reference to the accompanying drawings.
[0017]
FIG. 1 and FIG. 2 are control block system diagrams showing an embodiment of a paroxysmal atrial fibrillation detection / evaluation system based on an electrocardiogram according to the present invention. That is, in FIG. 1, reference numeral 10 indicates a long-term electrocardiogram monitor such as a Holter monitor for obtaining long-term electrocardiogram data, and reference numeral 20 inputs long-term electrocardiogram data from the long-term electrocardiogram monitor 10. An electrocardiogram data processing means comprising a microcomputer or the like for detecting and evaluating paroxysmal atrial fibrillation is shown.
[0018]
And for the arithmetic processing means 20 for the electrocardiogram data, an operating means 14 for performing arithmetic processing operation, a storage means 16 for storing and holding the processing data arithmetically processed by the arithmetic processing means 20, Furthermore, display means 18 for displaying each of the processing data calculated by the arithmetic processing means 20, that is, various statistical graphs relating to paroxysmal atrial fibrillation, are connected.
[0019]
FIG. 2 shows a control system configuration for implementing the paroxysmal atrial fibrillation detection / evaluation system according to the present embodiment, which detects and evaluates paroxysmal atrial fibrillation by inputting electrocardiogram data for a long time. An electrocardiogram data processing means 20 comprising a microcomputer or the like is provided with a CPU 21. For example, an electrocardiogram data input unit 12 for inputting Holter electrocardiogram data as long-term electrocardiogram data obtained from a Holter electrocardiogram monitor as the long-time electrocardiogram monitor 10 is input to the CPU 21 by the electrocardiogram data input unit 12. For storing the processed electrocardiogram data, storing the processing data calculated by the CPU 21, the display unit 18 for displaying the processed data as an image, and instructing the CPU 21 to calculate the electrocardiogram data. Are connected to each other.
[0020]
For the CPU 21, an R wave detection processing means stage 22 for performing R wave detection processing on the electrocardiogram data input from the electrocardiogram data input unit 12 and stored in the storage unit 16, and the electrocardiogram data. RR interval time-series data calculation processing means 23 for calculating RR interval time-series data, two-dimensional scatter diagram calculation processing means 24 for calculating two-dimensional scatter diagrams, and the two-dimensional scatter Paroxysmal atrial fibrillation identification determination processing means 25 for performing identification determination processing of paroxysmal atrial fibrillation based on the figure, and the seizure atrial fibrillation that displays the identification determination result and the two-dimensional scatter diagram on the display unit 18 The motion determination result display processing unit 26 calculates and processes data such as time, duration, average heart rate, RR interval variability, and occurrence frequency related to the occurrence and stop of the identified and determined paroxysmal atrial fibrillation. Calculation And data calculation and display process unit 27 about paroxysmal atrial fibrillation which image display of the physical data on the display unit 18, connected respectively configured.
[0021]
Next, with respect to the control operation example of the paroxysmal atrial fibrillation detection / evaluation system of the present embodiment configured as described above, referring to FIGS. 3, 4 and 5 together with the control system configuration shown in FIG. explain.
[0022]
First, Holter electrocardiogram data as long-term electrocardiogram data obtained by a long-time electrocardiogram monitor 10 such as a Holter monitor is input to the CPU 21 as the electrocardiogram data processing means 20 via the electrocardiogram data input unit 12 ( STEP-1). The input electrocardiogram data is stored and held in advance in the storage unit 16 in time series. Next, all the R waves are detected by the operation of the R wave detection processing means stage 22 for the electrocardiogram data stored and held in the storage unit 16 (STEP-2), and RR interval time series data calculation processing is performed. By the operation of the means 23, time series data about the RR interval is calculated and stored in the storage unit 16 as appropriate (STEP-3).
[0023]
Next, a window for determining and evaluating paroxysmal atrial fibrillation (PAF) (from what time to what time of the continuously measured time to RR interval time-series data to be evaluated) is set. (STEP-4).
[0024]
Each time the RR interval time-series data in the window range is moved, the data relating to all RR intervals in the window are converted into two-dimensional data (X, X, X) by the operation of the two-dimensional scatter diagram calculation / display processing means 24. Y) = (R-Rn, R-Rn + 1) is converted (STEP-5). In this way, when converting the data regarding all RR intervals into two-dimensional data, the first RR interval data is used as the horizontal axis coordinates with respect to the relationship between two adjacent RR interval data. By repeating the operation of plotting the next RR interval data as a point with the coordinate of the vertical axis for all continuous RR interval data while shifting the window position by one beat, spectrum analysis and standard deviation are performed. A Poincare plotting method can be applied in which a relationship existing between consecutive RR intervals that does not appear in is depicted (see FIG. 4).
[0025]
Therefore, the two-dimensional scatter diagram obtained by the two-dimensional scatter diagram calculation processing means 24 is calculated and stored in the storage unit 16 by the Poincare plot method. Based on the two-dimensional scatter diagram obtained in this way, the identification of the paroxysmal atrial fibrillation (PAF) is performed by the operation of the paroxysmal atrial fibrillation identification determination processing means 25 (STEP-6).
[0026]
Therefore, in the identification determination of paroxysmal atrial fibrillation (PAF) in the paroxysmal atrial fibrillation identification determination processing means 25, for example, identification determination is performed based on the following four indices, for example.
(1) Index of the shape of the distribution of two-dimensional data (X, Y) (degree of dissociation from the square) This is the ratio of the distribution width of the plotted points in the Y = X axis and the Y = −X axis direction. This is based on the logarithmic value Ratio. That is, in FIG. 4, it can obtain | require by Ratio = log (L1 / L2).
(2) Index of the distribution size of the two-dimensional data (X, Y) This is the area Parea obtained from the Y = X axis of the plotted point and the confidence interval of the distribution width in the Y = −X axis direction. It is a standard. That is, in FIG. 4, it can be obtained by Parea = L1 × L2.
(3) Index of irregularity of distribution of two-dimensional data (X, Y) This is based on an approximate value Ap En (Approximate Entropy) of the RR interval. In this case, the order of the approximate value Ap En is 2, and the tolerance (Tolerance) is expected between two plotted points when the two-dimensional data (Xi, Xi + 1) are evenly distributed in the area Parea. Distance Ed, that is,
Can be standardized. Where N is the total number of points plotted within the required range.
(4) Index of non-uniformity of distribution of two-dimensional data (X, Y) This is the ratio CR of plotted points that are gathered together within a distance normalized by the expected distance Ed. This is based on (Clustering Ratio). That is, CR indicates the ratio of the plotted points such that there are more than the required ratio with respect to the total number N of all the plotted points.
[0027]
As described above, when the identification determination of paroxysmal atrial fibrillation (PAF) is performed by the paroxysmal atrial fibrillation identification determination processing means 25, the identification determination is then performed by the paroxysmal atrial fibrillation determination result display processing means 26. The result and the two-dimensional scatter diagram are displayed on the display unit 18 (STEP-7). The determination result of paroxysmal atrial fibrillation and the two-dimensional scatter diagram obtained in this way are displayed as moving images that change every beat and are stored and held in the storage unit 16 (STEP-8). The operations from STEP-4 to STEP-7 are repeated while shifting the window position. FIG. 4 shows a display example of a two-dimensional scatter diagram displayed as an image on the display unit 18 when it is discriminated as paroxysmal atrial fibrillation.
[0028]
Furthermore, when it is determined as paroxysmal atrial fibrillation (PAF) in the discrimination determination of paroxysmal atrial fibrillation (PAF) by the above-described paroxysmal atrial fibrillation identification determination processing means 25, (1) each seizure property Automatic measurement of atrial fibrillation (PAF) onset and stop times, duration and their time distribution, (2) average heart rate, RR interval variability and minimum of each paroxysmal atrial fibrillation (PAF) The RR interval is automatically measured, and (3) the frequency and time of occurrence of paroxysmal atrial fibrillation (PAF) in one day are automatically measured, and these statistics are stored in the storage unit over the entire recording time. 16 is set so that each statistic can be displayed in a graph on the display unit 18 (STEP-9).
[0029]
[Clinical cases A to L]
Based on the above-described identification determination index of paroxysmal atrial fibrillation (PAF), a plurality of patients (panels) A to L were determined, and the results shown in Table 1 and the two-dimensional data shown in FIG. A scatter plot was obtained.
[0030]
[Table 1]
[0031]
In FIG. 5, according to the display examples of the two-dimensional scatter diagrams shown in panels A to L, from the RR interval time-series data of the electrocardiogram, each RR interval is represented by the X axis, and the RR interval immediately before it is represented. In the distribution state of the two-dimensional data (X, Y) obtained by developing on the two-dimensional XY plane as the Y axis, the RR interval at the time of atrial fibrillation satisfies all the following conditions And its characteristics were confirmed to be unique to atrial fibrillation. In paroxysmal atrial fibrillation (PAF), this feature appears only during a stroke, and in persistent atrial fibrillation, this feature persists.
[0032]
That is, features unique to atrial fibrillation are as follows.
(1) The distribution form of the two-dimensional data (X, Y) is close to a square with X = Y as one diagonal, and the two sides on the origin side show clear boundaries (see panels A, B, and C). .
(2) The area of the square in the distribution form is equal to or greater than a predetermined value defined by the average RR interval at that time, and increases in correlation with the average RR interval.
(3) The distribution density of the two-dimensional data (X, Y) in the square in the distribution form is substantially uniform within the square, or decreases smoothly as the distance from the origin increases. With the exception of one of the corners, it does not concentrate on a specific point or show an island-like or grid-like distribution.
[0033]
In contrast, in supraventricular tachycardia attacks other than sinus rhythm and atrial fibrillation, the distribution form of the two-dimensional data (X, Y) shows the following characteristics.
(1) In the case of sinus rhythm, the distribution form of the two-dimensional data (X, Y) forms one set of dots, rods or thin sectors on the axis corresponding to X = Y (panel D, E, F).
(2) In the case of supraventricular tachycardia other than atrial fibrillation, the distribution pattern of the two-dimensional data (X, Y) forms a plurality of sets, and sometimes a sinus rhythm-like set coexists (panel G, H, I, J, K, L).
[0034]
Accordingly, when detecting the detection of paroxysmal atrial fibrillation, a window having an appropriate size is set along the time series of the RR interval of the electrocardiogram, and this window is continuously moved, and the R- If a continuous two-dimensional scatter diagram with R intervals is created, whether or not the window is in atrial fibrillation can be easily identified and determined from the characteristics of the distribution state of the two-dimensional data (X, Y). This makes it possible to detect paroxysmal atrial fibrillation (PAF) and to identify its onset or stop time.
[0035]
According to the atrial fibrillation detection criteria described above, the two-dimensional scatter plots in panels A, B, and C clearly show the occurrence of paroxysmal atrial fibrillation (PAF). That is, in the paroxysmal atrial fibrillation (PAF) in this case, the distribution form of the two-dimensional data is distributed almost evenly in a large square or a rhombus close thereto, which is a characteristic characteristic of the atrial fibrillation described above. It is confirmed that
In the occurrence of paroxysmal atrial fibrillation (PAF), as shown in Table 1, an area that is an index of the distribution size of two-dimensional data as compared with sinus rhythm (panels D, E, and F) It is clear that Parea is small and the area Parea is relatively large with respect to the average RR interval.
[0036]
On the other hand, frequent PACs of supraventricular extrasystoles (panels G and H), atrioventricular block AVblock (panel I), supraventricular tachycardia PSVT showing multiple conduction ratios (panels J and K), atrial flutter In AFL (panel L), the logarithmic value ratio and area Parea of the distribution width ratio, which is an index of the distribution shape (degree of dissociation from the square) of the two-dimensional data, are the same as those of paroxysmal atrial fibrillation (PAF) In comparison with these conditions, in paroxysmal atrial fibrillation (PAF), the approximate value Ap En of the RR interval, which is an index of irregularity of the distribution of two-dimensional data, is large. It is also understood that the ratio CR of plotted points within the expected distance Ed, which is an index of the non-uniformity of the distribution of the two-dimensional data (X, Y), is small.
[0037]
From the above clinical examples A to L, a numerical standard for each index for determining and determining paroxysmal atrial fibrillation (PAF) based on the distribution (two-dimensional scatter diagram) of two-dimensional data (X, Y) is obtained. And can be expressed as:
[0038]
(1) For the index of the distribution shape (degree of dissociation from the square) of the two-dimensional data (X, Y), the logarithmic value Pratio of the distribution width ratio is:
[Expression 2]
It becomes.
[0039]
(2) For the index of the distribution size of the two-dimensional data (X, Y), the area Parea obtained from the confidence interval of the distribution width is classified according to the magnitude relation of the average RR interval of 380 ms,
Parea> C
In this case, assuming that the average RR interval is 380 ms,
[Equation 3]
It becomes.
[0040]
(3) For the index of irregularity of the distribution of the two-dimensional data (X, Y), the approximate value Ap En of the RR interval is
Ap En> 1.0
It becomes.
[0041]
(4) For the non-uniform index of the distribution of the two-dimensional data (X, Y), the ratio CR of the plotted points within the expected distance Ed is
CR <40%
It becomes.
[0042]
Therefore, in the case of paroxysmal atrial fibrillation (PAF), it was confirmed that the conditions for all the above-mentioned indices were satisfied.
[0043]
Although the preferred embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments, and many design changes can be made without departing from the spirit of the present invention.
[0044]
【The invention's effect】
The preferred embodiment of the detection / evaluation system for paroxysmal atrial fibrillation based on the electrocardiogram according to the present invention has been described above. However, in the automatic detection / evaluation system for paroxysmal atrial fibrillation based on the electrocardiogram according to claim 1, According to this, it is possible to easily and appropriately identify and identify paroxysmal atrial fibrillation (PAF) based on long-term electrocardiogram data obtained from a long-term electrocardiogram monitor such as a Holter electrocardiogram.
[0045]
【The invention's effect】
Moreover, according to the detection / evaluation system of paroxysmal atrial fibrillation based on the electrocardiogram according to claim 1 of the present invention , based on the index of the distribution state of the two-dimensional data based on the two-dimensional scatter diagram, it is simple and appropriate. Detection and evaluation of paroxysmal atrial fibrillation can be performed.
[0046]
Furthermore, according to the detection / evaluation system for paroxysmal atrial fibrillation based on the electrocardiogram according to claim 1 of the present invention, an arithmetic process for obtaining a two-dimensional scatter diagram for detecting / evaluating paroxysmal atrial fibrillation is performed. Can be done easily and properly.
[0047]
According to the system for detecting and evaluating paroxysmal atrial fibrillation based on the electrocardiogram according to claim 1 of the present invention, the paroxysmal atrial fibrillation for making an appropriate diagnosis for selecting a treatment method for a patient (PAF) onset and stop time, duration, average heart rate, RR interval variability, frequency of occurrence and other statistics are automatically measured, these automatically measured statistics are displayed in graphs, seizures It is possible to more appropriately and efficiently discriminate / determine the characteristic atrial fibrillation (PAF).
[Brief description of the drawings]
FIG. 1 is a control block diagram showing an example of a paroxysmal atrial fibrillation detection / evaluation system based on an electrocardiogram according to an embodiment of the present invention.
FIG. 2 is a configuration diagram of a control system for implementing the paroxysmal atrial fibrillation detection / evaluation system based on the electrocardiogram according to the embodiment of the present invention shown in FIG. 1;
FIG. 3 is a flowchart showing an example of a control program of a paroxysmal atrial fibrillation detection / evaluation system based on an electrocardiogram according to an embodiment of the present invention.
FIG. 4 is an explanatory diagram showing a display example of a two-dimensional scatter diagram in the paroxysmal atrial fibrillation detection / evaluation system based on an electrocardiogram according to an embodiment of the present invention.
FIG. 5 is an explanatory diagram comparing and displaying display examples A to L of various two-dimensional scatter diagrams in the paroxysmal atrial fibrillation detection / evaluation system based on an electrocardiogram according to an embodiment of the present invention.
[Explanation of symbols]
10 ECG monitor for a long time 12 Holter ECG data input unit 14 Operating means (operating unit)
16 Storage means (storage unit)
18 Display means (display unit)
18a 2D scatter plot display 18b Statistical graph display 20 ECG data calculation processing means 21 CPU
22 R-wave detection processing means 23 RR interval time series data calculation processing means 24 2D scatter diagram calculation processing means 25 paroxysmal atrial fibrillation identification determination processing means 26 paroxysmal atrial fibrillation determination result display processing means 27 paroxysmal Data calculation / display processing means for atrial fibrillation

Claims (1)

  1. An electrocardiogram monitor for obtaining electrocardiogram data;
    An R wave is detected based on the electrocardiogram data, and with respect to the relationship between two adjacent RR interval data in a predetermined section, the first RR interval data is used as the horizontal coordinate, and the next RR is obtained. By repeating the operation of plotting the interval data as a point with the coordinate of the vertical axis for all the continuous RR interval data while shifting the position of the window by one beat, the time series data of the RR interval is 2 ECG data processing means for obtaining a two-dimensional scatter diagram by converting into dimensional data;
    Regarding the distribution state of the two- dimensional data for obtaining the two-dimensional scatter diagram , the shape of the distribution of the two-dimensional data, the size of the distribution of the two-dimensional data, the irregularity of the distribution of the two-dimensional data, and the irregularity of the distribution of the two-dimensional data Hazuki group uniform on various indices of the reference, the identification determining paroxysmal atrial fibrillation discrimination and decision means paroxysmal atrial fibrillation by comparing the numerical value set in advance,
    About the identification determination result of the paroxysmal atrial fibrillation, a display means for automatically measuring and displaying a graph as the statistics of the various indicators of the distribution state of the two-dimensional data in the two-dimensional scatter diagram is provided. A system for detecting and evaluating paroxysmal atrial fibrillation based on the characteristic ECG.
JP2002171136A 2002-06-12 2002-06-12 Detection and evaluation system for paroxysmal atrial fibrillation based on electrocardiogram Active JP3806371B2 (en)

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DK1790285T3 (en) 2004-05-20 2013-05-21 Kiyoshi Takizawa Diagnostic method and apparatus for this and diagnostic program
JP2007105131A (en) * 2005-10-12 2007-04-26 Nippon Telegr & Teleph Corp <Ntt> Pulse wave diagnostic apparatus and pulse wave diagnostic apparatus control method
JP5148850B2 (en) * 2006-08-07 2013-02-20 テルモ株式会社 Heart rate fluctuation detection device
JP4885660B2 (en) * 2006-09-13 2012-02-29 テルモ株式会社 Heart rate fluctuation detection device and information processing method thereof
JP4965205B2 (en) * 2006-09-13 2012-07-04 テルモ株式会社 Heart rate fluctuation detection device
JP4885659B2 (en) * 2006-09-13 2012-02-29 テルモ株式会社 Heart rate fluctuation detection device and information processing method thereof
JP5192179B2 (en) * 2007-05-11 2013-05-08 テルモ株式会社 Pulsation fluctuation measuring apparatus and information processing method thereof
JP5207172B2 (en) * 2008-03-21 2013-06-12 国立大学法人 大分大学 Waveform analysis apparatus and waveform analysis program
JP5327458B2 (en) * 2009-03-31 2013-10-30 地方独立行政法人山口県産業技術センター Mental stress evaluation, device using it and its program
JP5160586B2 (en) * 2010-04-15 2013-03-13 日本電信電話株式会社 Pulse wave diagnostic device and pulse wave diagnostic device control method
US10244949B2 (en) 2012-10-07 2019-04-02 Rhythm Diagnostic Systems, Inc. Health monitoring systems and methods
US10413251B2 (en) 2012-10-07 2019-09-17 Rhythm Diagnostic Systems, Inc. Wearable cardiac monitor
US10610159B2 (en) 2012-10-07 2020-04-07 Rhythm Diagnostic Systems, Inc. Health monitoring systems and methods
WO2016160674A1 (en) * 2015-04-02 2016-10-06 Cardiac Pacemakers, Inc. Atrial fibrillation detection
US20190239793A1 (en) * 2016-09-20 2019-08-08 Sharp Kabushiki Kaisha State acquisition computer, state acquisition method, and information processing system
CN108403105A (en) * 2017-02-09 2018-08-17 深圳市理邦精密仪器股份有限公司 A kind of methods of exhibiting and displaying device of electrocardio scatterplot

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