JP2006116207A - Device for classifying electrocardiogram - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an electrocardiogram classifying device for easily extracting a heart beat waveform which is hardly extracted in a conventional method and has high probability for an erroneous classification. <P>SOLUTION: The heart beat waveform can be narrowed in consideration of at least one classification of at least not less than one heart beat waveform before/after the heart beat waveform. Consequently, the heart beat waveform is easily separated and extracted, which cannot be separated only by an RR ratio (RR ratio=RR<SB>(n-1)</SB>/RR<SB>n</SB>×100(%), RR<SB>n</SB>is interval between one foregoing heart beat and RR<SB>n-1</SB>is interval between the one foregoing heart beat and two foregoing heart beat) e.g. in a case where a normal heart beat following interpolated ventricular extrasystole is erroneously classified as supraventricular premature beat. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to an electrocardiogram classification apparatus, and more particularly to a classification apparatus for correctly classifying waveforms of heartbeats according to characteristics.

  Conventionally, long-term electrocardiogram data recorded by a Holter electrocardiograph or the like includes a very large number (for example, 100,000 times or more) of heartbeat waveforms, so that even if an abnormal heartbeat waveform is found, for example, it is not realistic to perform it manually. . Therefore, automatic classification is generally performed by the analysis device in accordance with the characteristics of individual heartbeat waveforms, intervals between adjacent heartbeats, and the like. By adding information such as serial numbers, classifications, and R-R intervals (R-wave time intervals) with the previous heartbeat for each heartbeat waveform by the analysis device and storing the information, for example, only heartbeat waveforms having similar characteristics are collected. Efficient use of electrocardiogram data for a long time such as display can be realized.

  More specifically, the analysis apparatus analyzes each waveform for each heartbeat included in the electrocardiogram data according to a predetermined classification condition such as a waveform (mainly QRS wave shape) and an RR interval from the previous heartbeat. By classifying, a heartbeat waveform group (morphology group) determined to have similar characteristics is generated.

  For example, heartbeat waveforms classified into a classification (morphology classification) of LV premature contraction (V) satisfying a predetermined condition are further divided into V1, V2, V3. . Are classified into heartbeat waveform groups having a morphology number such as The heartbeat waveforms included in one morphology number are collectively referred to as a morphology group.

  Morphology classification includes automatic classification other than the above-described ventricular extrasystole (V), normal heartbeat (N), supraventricular extrasystole (S), pace heartbeat (P), noise, etc. There are classifications given by the user later.

JP-A-7-132118

  The automatic waveform classification by the analyzer is very useful in the use of ECG data for a long time, but the ECG data is a biological signal that differs for each subject, and especially during normal life like a Holter ECG Since the recorded electrocardiogram data includes noises and level fluctuations due to various external causes, it is difficult to mechanically correctly determine and classify all the heartbeats.

  For example, the premature ventricular contraction has a waveform similar to that of a normal heartbeat, and is generally distinguished from the normal heartbeat by using the fact that the RR interval is shortened. However, the RR interval is shortened even when the heart rate is increased due to factors such as exercise, and the RR interval is apparently shortened even when noise is erroneously recognized as a heartbeat waveform. Easy to wake up. For this reason, a method for suppressing erroneous determination has been proposed (see, for example, Patent Document 1).

  Although such a misjudgment suppression technique reduces the probability that a normal heartbeat will be erroneously determined and classified as supraventricular premature contraction due to the effects of noise or intervening premature ventricular contraction, misclassification is reduced. It cannot be completely removed.

  Therefore, the analysis device has functions for reclassifying heartbeat waveforms that have been automatically classified into the wrong morphology group into the correct morphology group, or creating morphology classification and morphology groups based on user-specific criteria (morphology editing function) ) Is provided.

As a typical example of such a morphology editing function, an RR ratio division function is known. The RR ratio division is a function of reclassifying (dividing) a plurality of electrocardiogram data classified into a certain morphology group into two morphology groups with a predetermined RR ratio value as a boundary. RR ratio is heart B _n and the RR interval RR _n of the previous heartbeat B _(n-1), the previous heartbeat B _(n-1) further preceding heartbeat B _(n- The ratio of ₂₎ to the RR interval RR _(n-1) expressed as a percentage, ie,
RR ratio = RR _(n-1) / RR _n * 100 (%)
It is.

  RR ratio division is automatically classified erroneously by, for example, classifying only ECG data having an RR ratio that is significantly different from most of the other heartbeat waveforms classified into a certain morphology group into other morphology groups. It is possible to extract electrocardiogram data having a high possibility and to generate a more flexible morphology group according to the user's intention.

  However, there are also heartbeat waveforms that cannot be separated using the RR ratio division function despite the high possibility of being misclassified. In such a case, it is necessary to check whether there are any heartbeats that are misclassified while checking the heartbeat waveforms included in the morphology group one by one.

  The present invention has been made in view of such problems of the prior art, and is an electrocardiogram that can be easily extracted, for example, a heartbeat waveform that is likely to be erroneously determined, which is difficult to extract by the conventional method. An object is to provide a classification apparatus.

  That is, the gist of the present invention is an electrocardiogram classification device that reclassifies a plurality of heartbeat waveforms that have been previously classified into one classification, and at least one of the plurality of heartbeat waveforms before or after at least one heartbeat. An electrocardiogram classification apparatus comprising: extraction means for extracting a heartbeat waveform whose heartbeat waveform classification is a predetermined classification; and reclassification means for reclassifying the heartbeat waveform extracted by the extraction means into a new classification. Exist.

  With such a configuration, according to the present invention, since reclassification is performed in consideration of the classification of heartbeat waveforms before or after at least one heartbeat, heartbeat waveforms that could not be separated up to now can be easily collected at once. Can be extracted and reclassified. As a result, for example, normal sinus rhythm after interventricular extrasystole, which is erroneously determined as supraventricular extrasystole, can be easily extracted, and the labor for correcting the classification can be greatly reduced. It becomes possible.

Hereinafter, the present invention will be described in detail based on preferred embodiments with reference to the drawings.
<First Embodiment>
(Configuration of electrocardiogram analyzer)
FIG. 1 is a block diagram showing an example of a functional configuration of an electrocardiogram analysis apparatus as an electrocardiogram classification apparatus according to the first embodiment of the present invention.

  The data input unit 110 is, for example, a memory card reader or a network interface, and is an interface that reads and inputs electrocardiogram data recorded in advance from a recording medium or another device. The filter processing unit 120 performs a filtering process typified by waveform shaping processing such as noise removal and baseline fluctuation removal on the electrocardiogram data input from the data input unit 110, and writes the processed electrocardiogram data to the storage unit 130. .

  The storage unit 130 is composed of a large-capacity storage device such as a hard disk drive, and stores a long-time electrocardiogram recorded by a Holter electrocardiograph for the entire time. The waveform memory 140 is a memory for storing a plurality of types of standard waveforms for classifying heartbeats from waveforms, and a part of the storage unit 130 can also be used. The waveform memory 140 may store the waveform itself, but may store data such as feature points corresponding to the waveform instead.

  The classification processing unit 150 performs processing such as QRS waveform detection and RR interval calculation with respect to the previous heartbeat for all heartbeats stored in the storage unit 130, waveform data stored in the waveform memory 140, and predetermined processing. Based on the specified condition, the classification is made into the morphology classification and the morphology group within the morphology classification, and the result is written back to the storage unit 130.

  The waveform search unit 160 searches the total heart rate data recorded in the storage unit 130 for a specified condition, for example, a heart rate included in a specific morphology classification or morphology group, and supplies the result to the control unit 170.

  The control unit 170 is, for example, a CPU, and controls the operation of the entire electrocardiogram analyzer by executing a control program recorded in the storage unit 130, for example. The input unit 180 is at least one input device represented by a keyboard and a mouse, and is used when the user performs various settings and instructions. The display unit 190 is a display device such as an LCD or a CRT, and displays various information including an electrocardiogram under the control of the control unit 170.

  The electrocardiogram analyzer of the present embodiment having such a configuration can be realized by using a general-purpose computer device that is commercially available as a personal computer, for example. The filter processing unit 120, the classification processing unit 150, and the waveform search unit 160 may be realized by individual hardware, or may be realized by software by a CPU executing a program that realizes the function of each unit. good.

(Heart rate classification process)
Next, the flow of the heart rate classification process in the electrocardiogram analyzer of the present embodiment will be described using the flowchart shown in FIG. For convenience, it is assumed here that the electrocardiogram data already processed by the filter processing unit 120 is stored in the storage unit 130 at the time of starting the heart rate classification processing, but the data input processing and the heart rate classification processing are performed in parallel. You can go. In addition, since the electrocardiogram data of a plurality of channels is generally measured and recorded, the electrocardiogram data of the plurality of channels can be processed even in the analysis apparatus of the present embodiment. explain.

  First, in step S210, the control unit 170 instructs the classification processing unit 150 to execute classification processing. The classification processing unit reads electrocardiogram data for a predetermined time from the storage unit 130. Then, a QRS waveform is detected from the read electrocardiogram data by a well-known method, and electrocardiogram data of a predetermined time before and after the R wave (here, 400 ms before the R wave position and 1 second after 600 ms) for one heartbeat. Minute waveform data (step S220). Further, the position of the R wave (for example, a relative time or an absolute time when the recording start time of the entire electrocardiogram data is set to 0:00:00) is temporarily stored.

  Next, in step S230, the R wave position stored as the additional information of the previous heartbeat, the R-R interval obtained from the R wave position of the heartbeat, and data related to the reference waveform stored in the waveform memory 140 (reference waveform information) The morphology classification for classifying the heartbeat is determined based on both of the waveform comparison results based on ().

  Although it is possible to appropriately determine how the RR interval and the reference waveform information are used to determine the morphology classification, it is first determined whether the morphology classification can be clearly determined from the waveform, and cannot be determined from the waveform. It may generally be efficient to classify in consideration of the RR interval.

  Next, additional information is added to the classified ECG data for one beat (step S250). FIG. 3 shows an example of an electrocardiogram data format for one beat in the present embodiment. The electrocardiogram data is composed of a header portion and a waveform data portion, and additional information is stored in the header portion. The additional information includes a serial number from the heartbeat waveform recorded first, a symbol representing the classified morphology group, an R wave position of the heartbeat, a start time, and an end time. Actually, more additional information may be recorded, but the description is omitted because it is not directly related to the present embodiment. The electrocardiogram data to which the additional information is added is written back to the storage unit 130. At this point in time, only the morphology classification has been determined, so the morphology group information in the additional information is a symbol representing the morphology classification (for example, as described above, N for normal heartbeats, and extraventricular contraction). S, V, etc. if it is an intervening ventricular extrasystole.

In step S260, it is determined whether or not the processing has been completed for the electrocardiogram data for all heartbeats recorded in the recording unit 130. If there is unprocessed data, the process returns to step S210.
On the other hand, if it is determined that the processing for all the heartbeats has been completed, the process proceeds to step S270, and further, classification processing into a morphology group is performed.

  In step S <b> 270, the control unit 170 instructs the waveform search unit 160 to search the electrocardiogram data to which the same morphology classification symbol is assigned from the storage unit 130 and supply the result to the classification processing unit 150. The waveform search unit 160 searches for electrocardiogram data for each morphology classification in accordance with a predetermined order in accordance with this instruction, and supplies it to the classification processing unit 150.

The classification processing unit 150 generates, for example, a morphology group having the first supplied waveform as the top waveform (reference waveform) of the morphology group, and the morphology classification symbol in the additional information of the electrocardiogram data classified into the morphology group, It is rewritten to a symbol (morphology group symbol) having a configuration of morphological classification symbol + serial group number.
For example, since the first electrocardiogram data of the morphology classification V is the first waveform of the first morphology group in the morphology classification V, the morphology classification symbol of the additional information is rewritten from V to V1.

  Then, when the next electrocardiogram data is supplied, the similarity (correlation) with the top waveform is calculated by a well-known method, and when the degree of correlation is larger than a predetermined value, to belong to the same morphology group, The same morphology group symbol V1 as the top waveform is given. On the other hand, if the degree of correlation is less than or equal to the predetermined value, the top waveform of another morphology group is used, and the same morphology classification symbol + serial group number, and thus the morphology group symbol V2, is assigned.

  As described above, as long as the electrocardiogram data having a correlation degree larger than the predetermined value continues, the ECG data is classified into the same morphology group. By repeating this process, a plurality of morphology groups (Xn: integer of n ≧ 1) are generated in the same morphology classification (X). The electrocardiogram data that has been classified into the morphology group is written back to the storage unit 130 again.

When a morphological group is generated in this way and the electrocardiogram data is classified into the morphological group, if one electrocardiogram data having a different waveform is present while the electrocardiogram data having a high degree of correlation are continuous, the remaining electrocardiogram data is the whole Even if the degree of correlation is high, it is divided into two morphology groups. A plurality of morphology groups having a high degree of correlation can be combined into one morphology group using the merge function of the morphology editing function.
When such a classification process into the morphology group is performed for all the morphology classifications, the classification process is terminated.

(Morphology editing process)
Next, the morphology editing process of the analysis apparatus according to the present embodiment will be described.
Morphology editing corrects errors in automatic classification of electrocardiogram data for each heart rate that has been automatically classified, or divides ECG data included in the morphology group into two morphology groups (RR ratio division) according to the RR ratio. Provide a function of integrating (merging) a plurality of similar morphology groups.
The user can efficiently classify the measured and recorded electrocardiogram data by using the automatic classification function and the morphology editing function of the analysis apparatus together.

The analysis apparatus according to the present embodiment is characterized in that, in the morphology editing function, the RR ratio division function enables division in consideration of the previous heartbeat morphology classification.
As described above, the RR ratio division function is a function of reclassifying (dividing) a plurality of electrocardiogram data classified into a certain morphology group into two morphology groups with a predetermined RR ratio value as a boundary.

Hereinafter, the RR ratio division process in the analysis apparatus of the present embodiment will be described with reference to the flowchart of FIG.
First, in step S310, an initial screen is displayed. Specifically, the top heartbeat waveform of the morphology group included in the designated morphology classification is searched using the waveform search unit 160, and the result is displayed on the display unit 190 according to a predetermined layout.

  An example of the initial screen is shown in FIG. In the example of FIG. 5, the first heartbeat waveforms of 14 morphology groups (V15 to V28) included in the morphology classification of ventricular extrasystole (V) are displayed. The control unit 170 displays the selected category by controlling the waveform search unit 160 according to the category selected from the pull-down menu of the morphology category selection list box 51 via the input unit 180.

  The leading heartbeat waveform of each morphology group included in the selected morphology classification is displayed in the waveform display area 52. Here, a state in which 2ch heartbeat waveforms are simultaneously displayed is shown. The period displayed here is one second of 400 ms before and 600 ms after the R wave position. In the upper part of each waveform display area 52, a morphology group symbol 53 and the total heart rate 54 included in the morphology group are displayed. Morphology groups that cannot be displayed on the screen of the display unit 190 can be displayed on the screen by operating the scroll bar 56 with the input unit 190.

  In a state where such an initial screen is displayed, it is monitored whether RR ratio division is selected (step S320). The selection of the RR ratio division may be performed by an arbitrary method. For example, one of the displayed morphology groups is selected, and the RR ratio division is selected from the context menu or the like as an editing process for the selected morphology group. Thus, the user can instruct activation of the RR ratio division process for a desired morphology group. When the controller 170 detects such a predetermined instruction procedure, the controller 170 displays a division condition setting screen in step S330.

  FIG. 6 is a diagram illustrating an example of a division condition setting screen in the present embodiment. This example shows a case where RR ratio division is instructed for the morphology group N 1, and the selected morphology group symbol is displayed in the symbol display area 61. The division condition setting screen is a screen for setting an RR ratio as a reference for dividing a heart rate included in a selected morphology group into two morphology groups. Specifically, a histogram 62 of heart rate RR ratios included in the selected morphology group is displayed, and a cursor bar 63 for designating an RR ratio as a division criterion on the histogram 62 is displayed.

  The RR ratio is calculated by retrieving electrocardiogram data corresponding to the previous two heartbeats from the storage unit 130 using the serial number of the header information for each heartbeat in the morphology group and acquiring the R wave position of the data. be able to. The calculated RR ratio may be stored in the storage unit 130 in association with each heart beat in the morphology group, or may be added as header information of the electrocardiogram data. The RR ratio may be calculated when the histogram 62 is displayed or may be calculated in advance and recorded as one piece of header information.

  The cursor bar 63 moves within the display area of the histogram 62 to the position pointed to by the mouse cursor, for example, and the RR ratio corresponding to the movement position is displayed in the message “divide before XX%” on the histogram 62. Is done. Thus, in the present embodiment, a heart rate group having an RR ratio smaller than the RR ratio specified by the cursor bar 63 is divided as a new morphology group, and the remaining heart rate groups remain in the original morphology group. . Further, to the right of the message 68, the heart rate to be divided / the total heart rate in the morphology group are also displayed.

  The post-division list box 64 is for designating which morphology classification a morphology group newly generated by RR ratio division is to be used. When the “divide” button 65 is clicked with the mouse of the input unit 190, the morphology group is divided under the currently specified conditions. When the “Close” button 66 is clicked, the RR ratio division is stopped and the screen returns to the initial screen.

  In the present embodiment, as described above, not only the RR ratio but also the morphology classification of the previous heartbeat can be considered as the condition for dividing the morphology group. Specifically, a pre-beat classification list box 67 is provided in the division condition setting screen, and among all the heart beats included in the morphology group, for heart beats having a pre-beat matching the morphology classification specified here, RR ratio division is possible.

This point will be further described.
For example, since the supraventricular extrasystole has a waveform similar to that of a normal heartbeat, classification is difficult only from the waveform information. On the other hand, since it is known that the RR interval is shortened during the premature ventricular contraction, if the RR interval with the previous heartbeat is significantly shorter than the average value, for example, the extraventricular phase It can be determined that it is contraction. However, when noise or intervening ventricular extrasystole occurs during a normal heartbeat, the noise or peak of intervening ventricular extrasystole is detected as an R wave, and as a result, the RR of the next normal heartbeat is detected. The interval appears to be short. Therefore, the normal heartbeat next to such noise and intervening ventricular extrasystole is erroneously determined as an extraventricular extrasystole in the morphological classification determination based on the RR interval.

The normal heartbeat misclassified in this way and the case where the extra-ventricular extrasystole actually occurs cannot be separated by dividing the morphology group based only on the RR ratio.
FIG. 7A shows the case where the supraventricular premature contraction (S) actually occurs, and FIG. 7B shows the case where the intervening premature ventricular premature contraction (VPC) occurs during the normal heartbeat. An example is shown. In such a case, in FIG. 7B, the heart rate (arrow) following the intervening ventricular extrasystole is classified as an upper ventricular extrasystole (S) because the RR interval is short.

In both FIG. 7A and FIG. 7B, since the RR ratio with respect to the heart rate indicated by the arrow is the same value, FIG. 7B incorrectly classified into the morphological group of supraventricular extrasystole (S). ) Cannot be extracted using a division function based only on the RR ratio.
However, by considering the classification of the previous heart rate, when the heart rate group in which the previous heart rate is determined to be VPC among the heart rate groups included in the morphological group of premature ventricular contraction is divided into RR ratios as a target, FIG. It is possible to distinguish between the heart rate.

  Therefore, it is determined whether or not the previous heart rate classification is specified in the previous heart rate classification list box 67 (step S340), and the beats in the morphology group that match the previous heart rate classification are extracted as candidate heartbeat waveforms. Then, the histogram 62 for only the candidate heartbeat waveform is displayed (step S350), and the RR ratio division for the candidate heartbeat group narrowed down by the classification of the previous heartbeat is enabled. When the histogram 62 is updated, the total heart rate displayed on the histogram 62 is also updated to the reduced total heart rate.

  For example, as shown in FIG. 8, the classification of the previous heart rate is intervening premature ventricular premature contraction (V) or other heart rate (?: High possibility that noise is classified), around 100% There is a high possibility that the heart rate having the RR ratio is a normal heart rate (N) misrecognized as supraventricular extrasystole (S) in the pattern of FIG. Therefore, by specifying “normal heartbeat” in the post-division list box 64 and performing RR ratio division, it is possible to divide heartbeat groups that are likely to be misclassified into different morphology groups at once.

  In step S340, it is determined that there is a designation when the classification of the previous heartbeat is changed (including the cancellation of designation of classification). Accordingly, when the designation of the previous heartbeat is cancelled, in step S350, the histogram 62 is updated (returned) to histograms for all heartbeats in the morphology group. Therefore, the user can easily find an appropriate condition by trial and error of various conditions.

  In step S360, it is determined whether there is a division instruction, that is, whether the “divide” button 65 is clicked with the mouse of the input unit 190. If there is a division instruction, the morphology group division according to the designated RR ratio is performed for the heart rate currently displayed in the histogram 62 (step S370). If there is no division instruction in step S360, the process returns to step S340.

  As described above, according to the present embodiment, since the RR ratio division considering the classification of the previous heart rate is possible, the heart rate group that cannot be separated by the division based only on the RR ratio and has a high possibility of misclassification can be easily performed. Can be extracted and separated. Therefore, it is possible to greatly reduce the labor required for correcting the classification of the measured and recorded electrocardiogram data.

<Second Embodiment>
In the first embodiment described above, the analysis apparatus having the RR ratio division function in consideration of the classification of the previous heart rate has been described. However, regardless of the RR ratio division function, the classification of the heart rate before the previous heart rate or the classification of the rear heart rate is performed. It is possible to perform waveform extraction and classification processing in consideration.

  Hereinafter, an analysis apparatus as an example of an electrocardiogram classification apparatus according to the present embodiment will be described. In addition, since the structure of the analyzer of this embodiment is as having shown in FIG. 1, description is abbreviate | omitted. In addition, it is assumed that the automatic classification process already described with reference to FIG.

For example, when an intervening ventricular extrasystole (V) occurs during a continuous normal heartbeat (N) as described in FIG. 7B, it is erroneously recognized as an upper ventricular extrasystole (S). Let us consider a case where a normal heartbeat (N) after extraction is extracted. In this case, among the heartbeat waveforms included in the morphological group of the premature ventricular contraction, the classification of the previous heartbeat is an intervening ventricular premature contraction (V), and the classification of the previous heartbeat (previous heartbeat) is further It can be seen that there is a high possibility of erroneous recognition when the heart rate is normal (N).
Therefore, among the heartbeat waveforms included in the S morphology group, it is possible that the heartbeat was misrecognized by performing the morphology division process on the condition that the previous heartbeat classification is V and the previous heartbeat classification is N. It becomes possible to extract high heartbeat waveforms all at once.

  In addition, as shown in FIG. 9A, the single intermittent interventricular extrasystole (V) should have a longer RR interval with the posterior heartbeat. However, as shown in FIG. 9B, the classification of the rear heart rate is the normal heart rate (N), and the total of the RR interval with the previous heart rate and the RR interval with the rear heart rate is almost 100% ( If the heart rate waveform is classified as an intervening ventricular extrasystole (V), which is approximately equal to the RR interval of consecutive normal heartbeats, the mixed noise may be mistaken for intervening ventricular extrasystole. It is considered that there is a high possibility that it is classified as contraction (V). Of the heartbeat waveforms classified as intervening ventricular extrasystoles (V), the total of the RR interval with the previous heartbeat and the RR interval with the rear heartbeat is almost 100%. If the heart rate classification is also an intervening ventricular premature contraction (V), it is a continuous interventricular premature ventricular contraction and is considered to be a correct classification.

In FIG. 9B, in order to extract a heartbeat waveform that is mistakenly classified as an intervening ventricular extrasystole (V), both the previous heartbeat and the rearward heartbeat are normal heartbeats (N), and the front and rear heartbeats. A heartbeat waveform whose total RR interval is approximately 100% (almost RR interval between normal heartbeats) may be divided.
In this way, regardless of the RR ratio division function, by performing the morphology division process considering at least one of the classification of at least one pre-beat and the classification of at least one post-beat, the heart beat waveform of the current beat and the R− Heartbeat waveforms that are difficult to extract under conditions based on the R interval and the RR ratio can be easily extracted together.

  FIG. 10 is a diagram illustrating an example of a morphology division condition designation screen in the analysis apparatus of the present embodiment. This screen is the same as the division condition setting screen shown in FIG. 6. For example, one of the displayed morphology groups is selected on the morphology editing initial screen shown in FIG. 5, and context menu is selected as editing processing for the selected morphology group. Displayed when the morphology partitioning process is selected from.

  FIG. 10 shows an example of a screen that can specify the waveform classification of up to 2 heartbeats before and after, the RR interval and the RR ratio, but it is also possible to specify more classifications of the before and after heartbeats. In addition, it is possible to appropriately determine whether or not the RR interval and the RR ratio can be specified, and the conditions that can be specified.

  In the condition setting screen shown in FIG. 10, by selecting a desired classification (including no designation) from the pull-down menu corresponding to the two front and rear heartbeats, it is possible to designate the classification independently for the two front and rear heartbeats. As for the current heart rate classification, by default, the classification corresponding to the morphology group selected when the morphology division process is designated is automatically displayed, but can be changed on the setting screen.

  Also, the RR interval and the RR ratio can be individually specified. For the RR interval, the RR interval between the previous heartbeat and the previous heartbeat is A, the RR interval between the previous heartbeat and the current heartbeat is B,. . . As for conditions for any one or two of A to D, in this embodiment, the relationship (total, ratio, difference (large and small)) and its magnitude (100% (almost in the RR interval between normal heartbeats) Equal), specific values, etc.) can be specified. Similarly, with regard to the RR ratio, one or two conditions (values and their magnitude relationships in the present embodiment) can be designated for A / B, B / C, and C / D.

  Also, a plurality of conditions for the RR interval and the RR ratio can be set using an add button, and when a plurality of conditions are set, they are handled as AND conditions (conditions that should satisfy all at the same time).

  When a “divide” button at the bottom of the division condition setting screen is pressed with a mouse or the like, the analysis apparatus searches for a heartbeat waveform that satisfies the set condition and divides it into morphology classifications having names designated by the user.

  As described above, according to the present embodiment, as in the first embodiment, it is possible to easily extract and separate heartbeat groups that are highly likely to be misclassified. Therefore, it is possible to greatly reduce the labor required for correcting the classification of the measured and recorded electrocardiogram data.

(Other embodiments)
In the above-described embodiment, the description has been given focusing on the collective extraction of heartbeat waveforms with a high possibility of misclassification so that the effects of the present invention can be easily understood. However, the essence of the present invention resides in the morphology classification considering the classification of the front and rear heartbeats, and the batch extraction of heartbeat waveforms with high possibility of misclassification is only a part of the effects realized by the present invention. Morphology classification that takes into account the classification of front and back heart beats, such as the extraction of heartbeat waveforms of consecutive interventricular premature ventricular contractions, enabling more detailed classification, for example, Needless to say, this is useful not only for the waveform extraction.

  Furthermore, in the above-described embodiment, only the classification device having the automatic classification function has been described. However, if it is possible to provide the above-described RR ratio division function and morphology division function, as described with reference to FIG. Such automatic classification processing may be performed by another device.

It is a block diagram which shows the function structural example of the analyzer which concerns on embodiment of this invention. It is a flowchart explaining the waveform classification | category process operation which the analyzer which concerns on embodiment performs. It is a figure which shows the data structural example of the electrocardiogram data for 1 heartbeat. It is a flowchart explaining the RR ratio division | segmentation process operation | movement which the analyzer which concerns on embodiment performs. It is a figure which shows the example of a morphology edit initial screen. It is a figure which shows the example of a division condition setting screen. It is a figure which shows the example of the waveform which cannot be distinguished by the division | segmentation only by RR ratio. It is a figure which shows the state which narrowed down by classification | category of the previous heartbeat in the division | segmentation condition setting screen. It is a figure explaining the example of the misclassification resulting from noise. It is a figure which shows the example of the morphology division | segmentation condition designation | designated screen in 2nd Embodiment.

Claims (7)

An electrocardiogram classification device for reclassifying a plurality of heartbeat waveforms previously classified into one classification,
An extraction means for extracting a heartbeat waveform in which the classification of at least one heartbeat waveform before or after at least one heartbeat is a predetermined classification among the plurality of heartbeat waveforms;
An electrocardiogram classification apparatus comprising: reclassification means for reclassifying the heartbeat waveform extracted by the extraction means into a new classification. further,
RR ratio = RR _(n-1) / RR _n * 100 (%)
(However, RR _n is, RR interval before and heart rate, RR _n-1 is the RR interval before and heartbeat and before last heartbeat)
RR ratio calculating means for calculating
2. The electrocardiogram classification apparatus according to claim 1, wherein the reclassification unit reclassifies a heartbeat waveform extracted by the extraction unit to a new classification when the RR ratio is equal to or less than a set value.   The electrocardiogram classification apparatus according to claim 2, further comprising display means for displaying a histogram of the RR ratio of the extracted heartbeat waveform.   4. The electrocardiogram classification apparatus according to claim 2, further comprising setting means for setting a set value of the RR ratio according to a position designated by a user on the histogram. User interface means for allowing the user to select the predetermined classification from a plurality of classifications;
4. The heartbeat waveform according to claim 1, wherein when the classification selected through the user interface means is changed, the extraction means extracts a heartbeat waveform using the newly selected classification. The electrocardiogram classification device according to any one of the above.   The extraction means further includes, from the extracted heartbeat waveform, an RR interval with the previous heartbeat, an RR interval between successive predetermined heartbeats before that, an RR interval with the rear heartbeat, and thereafter 2. The electrocardiogram classification device according to claim 1, wherein a heartbeat waveform satisfying a condition for at least one of RR intervals between consecutive predetermined heartbeats is extracted.   The extraction means further determines, from the extracted heartbeat waveform, an RR ratio obtained from an RR interval with a previous heartbeat and an RR interval between successive predetermined heartbeats before that, and an RR interval with a rear heartbeat. 7. The electrocardiogram classification according to claim 1 or 6, wherein a heartbeat waveform satisfying a condition for at least one of the RR ratios determined from an RR interval between successive predetermined heartbeats thereafter is extracted. apparatus.