JP7762039B2 - Electrocardiogram analyzer and control method thereof - Google Patents

Description

Article 30, paragraph 2 of the Patent Act applies (1) Distribution date: February 5, 2021 Distribution location: Fukuda Denshi Co., Ltd.'s internal document management system (the system is only accessible to related parties, but after the distribution date, it has become possible to distribute to third parties through related parties who have access to the system) Distributor: Fukuda Denshi Co., Ltd. Contents of the distributed item: PDF data file of the catalog for the product (SCM-9000) equipped with a heart rate classification function based on P wave features invented by Fujiwara Hiroki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko (2) Sale date: March 26, 2021 Sale location: Fukuda Denshi Hiroshima Sales Co., Ltd. Distributor: Fukuda Denshi Co., Ltd. Contents of the sold item: Fukuda Denshi Co., Ltd. sold a product (SCM-9000) equipped with a heart rate classification function based on the P wave features invented by Fujiwara Hiroki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko to Fukuda Denshi Hiroshima Sales Co., Ltd. (3) Date of sale: March 29, 2021 Location of sale: Matsuyoshi Medical Instruments Co., Ltd. Publisher: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold a product (SCM-9000) equipped with a heart rate classification function based on the P wave features invented by Fujiwara Hiroki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko to Matsuyoshi Medical Instruments Co., Ltd. (4) Date of sale: March 30, 2021 Place of sale: Fukuda Denshi Minami Tohoku Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Minami Tohoku Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the P wave features invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (5) Date of sale: March 31, 2021 Place of sale: Fukuda Denshi Minami Tohoku Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Minami Tohoku Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the P wave features invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko.

Article 30, paragraph 2 of the Patent Act applies (6) Date of sale: March 31, 2021 Place of sale: Fukuda Denshi Minami Kanto Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Minami Kanto Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the features of the P wave invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (7) Date of sale: May 21, 2021 Place of sale: Fukuda Denshi Minami Kanto Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Minami Kanto Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the features of the P wave invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (8) Date of sale: June 24, 2021 Place of sale: Fukuda Denshi Seibu Minami Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Seibu Minami Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the features of the P wave invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (9) Date of sale: July 20, 2021 Place of sale: Fukuda Denshi Nishi Kanto Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Nishi Kanto Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the features of the P wave invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (10) Date of sale: July 28, 2021 Place of sale: Fukuda Denshi Hyogo Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold a product (SCM-9000) equipped with a heart rate classification function based on the P wave features invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko to Fukuda Denshi Hyogo Sales Co., Ltd. (11) Date of sale: August 23, 2021 Place of sale: Fukuda Denshi Hokuriku Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold a product (SCM-9000) equipped with a heart rate classification function based on the P wave features invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko to Fukuda Denshi Hokuriku Sales Co., Ltd.

Article 30, paragraph 2 of the Patent Act applies (12) Date of loan: August 25, 2021 Location of loan: Fukuda Denshi Keiji Sales Co., Ltd. Discloser: Fukuda Denshi Co., Ltd. Details of loaned item: Fukuda Denshi Co., Ltd. loaned to Fukuda Denshi Keiji Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on P wave features invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (13) Date of loan: September 6, 2021 Location of loan: Fukuda Denshi Keiji Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item loaned: Fukuda Denshi Co., Ltd. loaned a product (SCM-9000) equipped with a heart rate classification function based on the features of P waves invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko to Fukuda Denshi Keiji Sales Co., Ltd. (14) Date of sale: September 28, 2021 Location of sale: Fukuda Denshi Keiji Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold a product (SCM-9000) equipped with a heart rate classification function based on the features of P waves invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko to Fukuda Denshi Keiji Sales Co., Ltd. (15) Date of sale: September 29, 2021 Place of sale: Fukuda Denshi Minami Tohoku Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Minami Tohoku Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the P wave feature amount invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko. (16) Date of sale: September 30, 2021 Place of sale: Fukuda Denshi Keiji Sales Co., Ltd. Disclosed by: Fukuda Denshi Co., Ltd. Details of the item sold: Fukuda Denshi Co., Ltd. sold to Fukuda Denshi Keiji Sales Co., Ltd. a product (SCM-9000) equipped with a heart rate classification function based on the P wave feature amount invented by Fujiwara Yuki, Goto Takafumi, Yoshioka Eriko, Tsugawa Hidenori, and Noda Kazuko.

The present invention relates to an electrocardiogram analyzer and a control method thereof.

Long-term electrocardiogram measurements are performed using a Holter monitor to detect conditions such as arrhythmias that are difficult to detect with short-term electrocardiogram measurements. The quality of electrocardiograms measured with a Holter monitor is not consistent and contains waveforms representing tens of thousands of beats. For this reason, it is common for technicians and doctors to conduct various analyses based on the results of automatic analysis by an electrocardiogram analyzer (Patent Documents 1 and 2).

One of the functions provided by the automatic analysis device is an automatic classification function that classifies the measured electrocardiogram beat by beat according to predetermined conditions. The user (technologist) of the automatic analysis device can evaluate the automatic classification results and change the classification by classification unit or heartbeat unit, or create a new classification.

JP 2009-95552 A Japanese Patent Application Laid-Open No. 2020-130335

Previously, automatic classification functions performed classification using the characteristics of the QRS interval of the electrocardiogram waveform. Because the QRS interval indicates the electrical activity of the ventricles, it is not suitable for use in classifying the electrical activity of the atria. As a result, previously, technicians had to manually assign atrial (supraventricular) arrhythmia classifications beat by beat, a time-consuming process.

The present invention was made in consideration of these problems with the prior art, and in one aspect provides an electrocardiogram analysis device and a control method thereof that can provide a function to assist in classifying heartbeats related to supraventricular arrhythmias.

The above-mentioned object is achieved by an electrocardiogram analysis device comprising: an acquisition means for acquiring electrocardiogram data; a calculation means for determining P-wave features for each heartbeat in the electrocardiogram data; an output means for outputting a classification screen for classifying and displaying the heartbeats in the electrocardiogram data based on the P-wave features; and an editing means for providing a function for collectively assigning a user-specified classification to at least one of the heartbeats selected and the heartbeats not selected on the classification screen, wherein the classification screen has an area for displaying, in an overlapping manner, waveforms for multiple selected heartbeats among the classified and displayed heartbeats, and an area for displaying, in an overlapping manner, waveforms for multiple non-selected heartbeats.

With this configuration, the present invention can provide an electrocardiogram analysis device and a control method thereof that can provide information specific to electrocardiograms measured over multiple days.

1 is a block diagram illustrating an example of the functional configuration of a general-purpose computer as an example of an electrocardiogram analysis apparatus according to an embodiment of the present invention. FIG. 10 is a diagram showing an example of a waveform list screen presented by the electrocardiogram analysis apparatus according to the embodiment. FIG. 10 is a diagram showing an example of a P wave classification screen presented by the electrocardiogram analysis apparatus according to the embodiment. FIG. 10 is a diagram showing another example of a P wave classification screen presented by the electrocardiogram analysis apparatus according to the embodiment. 4 is a flowchart illustrating the operation of the electrocardiogram analysis apparatus according to the embodiment.

The present invention will now be described in detail based on illustrative embodiments with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the claimed invention. Furthermore, although the embodiments describe multiple features, not all of them are necessarily essential to the invention, and multiple features may be combined in any desired manner. Furthermore, in the accompanying drawings, the same reference numbers are used to designate identical or similar components, and redundant explanations will be omitted.

In the following embodiments, the present invention will be described as being implemented on a general-purpose computer such as a personal computer or tablet terminal. However, the present invention can also be implemented on any electronic device, such as a media player, smartphone, or game console.

Figure 1 is a block diagram showing an example of the functional configuration of a general-purpose computer 100 capable of functioning as an electrocardiogram analysis device according to this embodiment. The CPU 1, which functions as a control unit, realizes functions according to the program, for example, by reading a program stored in the storage device 10 into the RAM 3 and executing it. For example, by executing a specific application program (electrocardiogram analysis application) while the operating system (OS) is running on the general-purpose computer 100, the general-purpose computer 100 functions as the electrocardiogram analysis device according to this embodiment.

The storage device 10 is, for example, a hard disk drive (HDD) or solid state drive (SSD), and stores operating system (OS), device drivers, applications, user data, etc. The storage device 10 also stores GUI (graphical user interface) data for displaying menu screens, user setting data, and application initial setting data.

ROM2 stores programs and firmware necessary for starting up the computer, such as a bootstrap loader, as well as various setting information. ROM2 may be at least partially rewritable.

RAM 3 is used as an area for expanding programs executed by CPU 1, and as a temporary storage area for variables, data, etc. Part of RAM 3 may also be used as video memory.

Memory card 4 is a recording medium that can be inserted into card slot 5 and removed, and general-purpose computer 100 can read data from memory card 4 inserted into card slot 5 and write data to memory card 4. In this embodiment, general-purpose computer 100 acquires data such as long-term electrocardiograms recorded by a Holter electrocardiograph via memory card 4. Note that general-purpose computer 100 may also acquire electrocardiogram data to be automatically analyzed by other methods. For example, it may acquire electrocardiogram data to be automatically analyzed from the Holter electrocardiograph that performed the measurement, or from another external device 200 that stores the measured electrocardiogram data, by communication via communication interface 20, which will be described later.

The display unit 6 includes a display device such as a liquid crystal display (LCD) or an organic EL display, a display control circuit, and the like. Note that while FIG. 1 shows a configuration in which the display unit 6 is built into the general-purpose computer 100, the display unit 6 may also be external. Furthermore, the computer may include both a built-in display unit 6 and an external display unit 6.

The operation unit 8 is a device with which the user inputs instructions to the general-purpose computer 100, and is typically one or more input devices such as a keyboard, a pointing device (such as a mouse), or a contact-sensing device (such as a touch panel). The keyboard may be a hardware keyboard or a software keyboard. The touch panel may be provided on the display unit 6, or may be in the form of a touchpad, such as those commonly found on notebook computers.

The communication interface (I/F) 20 is hardware that enables the general-purpose computer 100 to communicate with the external device 200 in accordance with a specified standard. The communication I/F 20 has a configuration according to the communication standard it supports, such as a connector that complies with a wired communication standard, or a wireless transceiver that complies with a wireless communication standard. The communication I/F 20 may support multiple communication standards. There are no particular restrictions on the communication standards that the communication I/F 20 supports, but typical examples of wired communication standards include Ethernet (registered trademark) and USB, and typical examples of wireless communication standards include Bluetooth (registered trademark) and wireless LAN (IEEE802.11x).

A user (e.g., a technician) who uses the automatic analysis of electrocardiograms measured with a Holter monitor launches the automatic analysis application stored in storage device 10 using an operating method appropriate for the OS running on general-purpose computer 100. CPU 1 reads the automatic analysis application from storage device 10 into RAM 3 and executes it, causing general-purpose computer 100 to function as an electrocardiogram analyzer. Hereinafter, the general-purpose computer 100 functioning as an electrocardiogram analyzer will be referred to as electrocardiogram analyzer 100.

Next, we will explain the operation of the electrocardiogram analysis device 100, which is realized by the CPU 1 executing an automatic analysis application. The CPU 1 acquires a data file storing the electrocardiogram data to be automatically analyzed in response to an operation from the operation unit 8. The CPU 1 may, for example, present a file browser screen provided by the OS on the display unit 6 and allow the user to specify the data file to acquire. Alternatively, the CPU 1 may search a predetermined location, such as the memory card 4, and automatically acquire a data file that meets predetermined conditions (for example, a data file with a specified file name).

The CPU 1 stores the acquired data file in the storage device 10. Note that instead of acquiring the entire data file all at once, the electrocardiogram data stored in the data file may be acquired in fixed amounts at a time. Note that in this embodiment, the electrocardiogram data is digital data that has been A/D converted under predetermined conditions. There are no particular restrictions on the type or number of leads included in the electrocardiogram data, and they may be one or more of the leads measured by a typical Holter monitor, such as NASA leads, CC5 leads, and CM5 leads, or the standard 12 leads. Furthermore, the measurement period for electrocardiogram data using a Holter monitor is generally 24 hours or more, but a measurement period of 24 hours or more is not required.

CPU1 first applies quality check processing to the electrocardiogram data to detect poor signal sections that are unsuitable for analysis. For example, CPU1 evaluates the baseline level and superimposed noise, and identifies sections where the superimposed level exceeds a threshold or noise sections as poor signal sections and excludes them from analysis processing. If measurements are being taken on multiple channels (leads) using a Holter electrocardiograph, CPU1 applies quality check processing to the data on each channel.

CPU 1 applies quality check processing to all data from the start to the end of measurement, and stores information that can identify the detected bad signal sections (e.g., the start date and time and end date and time of the section) in association with the data file's identification information (e.g., the file name) in storage device 10. CPU 1 applies subsequent processing to sections of the electrocardiogram data excluding the bad signal sections (referred to as analysis sections or valid signal sections).

Next, CPU 1 detects QRS interval candidates from the electrocardiogram data. If measurements are being taken from multiple channels (leads) using a Holter electrocardiograph, CPU 1 detects QRS interval candidates from the data of each channel. CPU 1 then detects the candidate that is determined to be highly reliable as the final QRS interval. Reliability can be determined based on one or more of, for example, signal quality, the degree of noise contamination, the validity of the RR interval, and whether or not it has been detected in other leads.

The CPU 1 then calculates feature quantities (parameters) based on the QRS interval. The parameters calculated here include, but are not limited to, the RR interval (RRI) between adjacent QRS intervals, the width of the QRS interval, the height of the QRS interval, the direction of the QRS interval, and the area of the QRS interval. Furthermore, the CPU 1 can calculate other parameters, such as heart rate variability (HRV), from the parameters based on the QRS interval.

The CPU 1 also executes an automatic classification function that divides the electrocardiogram data into beat-by-beat segments and assigns a classification to each beat based on multiple predetermined conditions related to parameters based on the QRS interval and the shape of the QRS interval. Classifications assigned here include, but are not limited to, normal heartbeat (N), premature ventricular contractions (S), bundle branch block (B), and paced heartbeat (P). Each classification may also have subclassifications. For example, normal heartbeat (N) may be further subdivided into multiple subclassifications (N1 to Nx, where x is an integer greater than or equal to 2). The CPU 1 also classifies heartbeats that fall within a poor signal interval as noise (A).

In this embodiment, the CPU 1 further detects P waves for each beat and determines feature quantities (parameters) related to the P waves. Feature quantities related to the P waves may be, for example, but are not limited to, the PR interval, PQ interval, P wave height (level), P wave width, and P wave polarity (convex upward or convex downward). Note that if P waves cannot be detected or if the P waves are abnormal and feature quantities cannot be determined, these are used as feature quantities.

The CPU 1 stores all parameters calculated for each heartbeat in the storage device 10 in association with the heartbeat identification information (e.g., a consecutive number starting from 1 assigned to each heartbeat from the start to the end of the measurement interval) and the electrocardiogram data or the electrocardiogram data identification information (e.g., a file name).

Figure 2 shows an example of a waveform list screen 200 that the electrocardiogram analysis device 100 presents on the display unit 6. The waveform list screen 200 is a screen that displays a list of representative waveforms for each heart rate group that have been assigned the same classification by the automatic classification function.

A classification tab 210 is provided for each classification assigned by the automatic classification function. The CPU 1 displays the representative waveform of the classification corresponding to the selected tab from the classification tabs 210 in the waveform display area 230. Figure 2 shows the state in which the tab corresponding to normal heartbeat (N) is selected. Therefore, the waveform display area 230 displays the representative waveform of the heartbeat classified as normal heartbeat (N). In this case, since the normal heartbeat (N) classification has nine sub-classifications N1 to N9, the representative waveform for each sub-classification is displayed.

A representative waveform is a waveform that represents the waveforms of heartbeats assigned to the same classification. The representative waveform may be a waveform selected according to any criteria, such as the waveform that most closely matches the classification criteria. The representative waveform is displayed along with the classification (subclassification) and heartbeat number. The heartbeat number is a sequential number assigned with the first heartbeat numbered 1, and serves as identification information for the heartbeat. In this case, two of the multiple leads included in the electrocardiogram data are set as targets for automatic analysis, so a representative waveform is displayed for each lead.

The user checks the representative waveform and, if necessary, other waveforms to determine the validity of the automatic classification. By operating the waveform list screen 200, the user can perform editing tasks such as combining multiple sub-classifications or changing classifications by sub-classification unit.

As described above, the automatic classification function classifies heartbeats according to the characteristics of the QRS interval of the heartbeat waveform, and does not classify supraventricular arrhythmias. In this embodiment, to assist in the classification of supraventricular arrhythmias, a function is provided that allows the user to collectively assign a classification to multiple heartbeats based on P-wave characteristics. Specifically, when the CPU 1 detects operation of the P-wave classification button 220 on the waveform list screen 200, it causes the display unit 6 to display a P-wave classification screen that allows the user to collectively assign a classification to multiple heartbeats based on P-wave characteristics.

Figure 3 shows an example of a P-wave classification screen 300. The P-wave classification screen 300 provides a function that allows a user to select multiple heartbeats based on P-wave features and assign a classification to them all at once. In the example of Figure 3, the P-wave classification screen 300 includes a histogram 310 of heartbeats related to P-wave features, allowing a user to select multiple heartbeats all at once based on the histogram 310.

The P-wave feature used in the histogram 310 can be changed using the pull-down menu 311. Figure 3 shows a case where the PQ interval is specified as the P-wave feature. The CPU 1 generates a heartbeat histogram 310 using predetermined conditions (number of bins, width, value range) for the feature selected by operating the pull-down menu 311, and displays it on the P-wave classification screen 300.

For example, if the height of the P wave is specified as the feature of the P wave, the histogram 310 can be generated with the horizontal axis having a bin containing 0.0 mV in the center, with negative values on the left and positive values on the right. Note that heartbeats for which no P wave was detected or heartbeats for which the P wave feature used to generate the histogram 310 has a clearly abnormal value are excluded from the histogram 310 as unclassified heartbeats.

When there are multiple leads to be automatically analyzed, the CPU 1 generates a histogram 310 for one predetermined lead. The user can change the lead for which the histogram 310 is generated by selecting a radio button 312. In this way, the user can display a histogram 310 relating to the desired P-wave feature value for the desired lead on the P-wave classification screen 300.

The histogram 310 allows the selection of one or multiple consecutive bins of P-wave features by operating the operation unit 8. When a selection operation on the histogram 310 is detected, the CPU 1 recognizes this as an operation to select heartbeats classified into the selected range or bin of P-wave features. Figure 3 shows a state in which a large value range 313 is selected in the histogram 310 for PQ intervals.

When the CPU 1 detects a selection operation on the histogram 310,
(1) Heartbeats included in the selection range (selected),
(2) heartbeats that are not included in the selected range (not selected), and (3) unclassified heartbeats (heartbeats that are not displayed in the histogram 310 and heartbeats for which P-wave features could not be obtained).
For each of these, waveforms are displayed in overlapping order.

In Figure 3, the P-wave classification screen 300 displays overlaid heartbeat waveforms in the waveform display area 320 located to the right of the histogram 310. "Inside selected range," "Outside selected range," and "Unclassified" correspond to the heartbeats (1) to (3) above, respectively. Overlaid waveform display can be achieved by overlapping the waveforms of the corresponding multiple heartbeats, aligning their horizontal positions with the R waves. For convenience, Figure 3 shows the same overlaid display for (1) to (3).

By overlaying the waveforms of the heart rate groups selected according to the selection criteria set by the user, the appropriateness of assigning the same classification to the selected heart rate groups can be intuitively understood. Overlaying the waveforms only needs to be performed for at least the selected heart rate groups.

However, by presenting an overlaid display of waveforms for heart rate groups that were not selected, it becomes possible to select the heart rate you want to exclude and assign a classification to the remaining heart rate collectively, thereby improving usability. Furthermore, by presenting an overlaid display of waveforms for heart rate groups that were not displayed in histogram 310, it becomes possible to check the waveforms of heart rate groups that are not displayed in histogram 310 or to collectively classify them as noise, again improving usability.

The display color of the coordinates that make up the superimposed display may be changed depending on the frequency with which the waveforms overlap those coordinates. This makes it possible to distinguish between highly common and less common parts of the superimposed heartbeat waveform group, which is useful for the user in adjusting the heartbeat selection conditions.

Furthermore, some of the heartbeats whose waveforms are superimposed on the display may be selectable in response to an operation on the superimposed display via the operation unit 8, and the selected heartbeat may be excluded from being subject to a collective classification. For example, the CPU 1 detects a position or area specification operation on the superimposed display as an operation to select a heartbeat corresponding to a waveform passing through the specified position or area. The CPU 1 then erases the waveform of the selected heartbeat from the superimposed display and also excludes it from being subject to classification assignment for the heartbeat group whose waveforms are superimposed on the display.

A judgment code change button 321 is located adjacent to the superimposed waveform display. When the CPU 1 detects an operation on the judgment code change button 321 via the operation unit 8, it displays a judgment code change menu 322. The judgment code change menu 322 displays assignable classifications that can be selected. When the CPU 1 detects a selection operation on the judgment code change menu 322 via the operation unit 8, it assigns the selected classifications collectively to the heart rate groups whose waveforms are superimposed and closes the P-wave classification screen 300. Note that the P-wave classification screen 300 may remain displayed until an explicit instruction is given by the user.

Figure 4 shows another example of a P-wave classification screen. Components that are the same as those in the P-wave classification screen 300 shown in Figure 3 are given the same reference numerals, and their description will be omitted. Instead of the histogram 310, the P-wave classification screen 400 has an area (XY plot) 410 in which individual heartbeats are plotted within a two-dimensional area in which a first characteristic value of the P wave is assigned to the first axis and a second characteristic value of the P wave is assigned to the second axis.

Here, an XY plot 410 is shown in which the PQ interval is assigned as the first feature and the P-wave height is assigned as the second feature. The first and second feature values may be changeable by the user through a pull-down menu, similar to the P-wave classification screen 300, for example.

When an operation to select a two-dimensional area within the XY plot 410 is detected, the CPU 1 recognizes this as an operation to select the heartbeat corresponding to the plot included in the selected two-dimensional area. Figure 4 shows, for example, a state in which a rectangular area 411 has been selected via the operation unit 8, and the CPU 1 displays the heartbeat waveform corresponding to the plot included in the rectangular area 411 superimposed on the area within the "selected range" of the waveform display area 320.

Furthermore, the CPU 1 superimposes and displays the waveforms of heartbeats corresponding to plots not included in the rectangular area 411 in the "outside selected range" area of the waveform display area 320, and the waveforms of heartbeats not plotted in the XY plot 410 in the "P wave not detected" area of the waveform display area 320.

Assigning classifications using the judgment code change button 321 and judgment code change menu 322, and excluding heartbeats in response to operations on the superimposed display, are as described using Figure 3.

By using the XY plot 410, it is possible to select a heartbeat by taking into account the relationship between the two P-wave features. Furthermore, by operating the operation unit 8, the user can switch between displaying the histogram 310 and the XY plot 410, allowing the user to select a heartbeat group based on various selection conditions related to the P-wave features.

Next, the waveform editing operation of the electrocardiogram analyzer 100, which is realized by the CPU 1 executing the automatic analysis application, will be described with reference to the flowchart shown in FIG.
In S501, the CPU 1 acquires a data file storing electrocardiogram data to be automatically analyzed in response to an operation from the operation unit 8. The CPU 1 may, for example, display a file browser screen provided by the OS on the display unit 6, and allow the user to specify the data file to be acquired. Alternatively, the CPU 1 may search a predetermined location such as the memory card 4, and automatically acquire a data file that meets predetermined conditions (for example, a data file with a predetermined file name).

The CPU 1 stores the acquired data file in the storage device 10. Note that instead of acquiring the entire data file all at once, the electrocardiogram data stored in the data file may be acquired in fixed amounts at a time. Note that in this embodiment, the electrocardiogram data is assumed to be digital data that has been A/D converted under predetermined conditions. The electrocardiogram data also includes the type and number of leads from which X, Y, and Z leads can be derived. For example, the electrocardiogram data may include three leads, eV1, eV5, and eVF, or the standard 12 leads, but is not limited to these.

In S503, CPU 1 applies preprocessing to the electrocardiogram data. Preprocessing may be a quality check process that detects poor signal sections unsuitable for analysis from the electrocardiogram data. In the quality check process, CPU 1 evaluates, for example, the baseline level and superimposed noise, and determines sections where the superimposed level exceeds a threshold or noise sections as poor signal sections and excludes them from the analysis process. If measurements are being taken on multiple channels (leads) using a Holter electrocardiograph, CPU 1 applies preprocessing to the data for each channel.

CPU 1 applies preprocessing to all data from the start to the end of measurement, and stores information that can identify the detected bad signal interval (e.g., the start date and time and end date and time of the interval) in association with the data file's identification information (e.g., the file name) in storage device 10. CPU 1 applies subsequent processing to the interval of the electrocardiogram data excluding the bad signal interval (referred to as the analysis interval or valid signal interval).

At S505, CPU 1 calculates predetermined features (parameters) for the electrocardiogram data related to the lead to be automatically analyzed from among one or more leads included in the electrocardiogram data. CPU 1 divides the electrocardiogram data for the lead for which features are to be calculated into individual heartbeats and detects the QRS interval. For example, CPU 1 detects QRS interval candidates based on the signal level, and detects the candidate determined to be highly reliable as the final QRS interval. Reliability can be determined based on one or more of, for example, signal quality, the degree of noise contamination, the validity of the RR interval, and whether or not it has been detected in other leads.

The CPU 1 can then calculate feature quantities such as the R wave level and QRS interval width based on the detected QRS interval. Furthermore, the CPU 1 can calculate HR and its variability (HRV) from the RR interval (RRI) of adjacent QRS intervals. The CPU 1 also detects P waves from one beat's worth of electrocardiogram data and calculates feature quantities related to the P waves. The CPU 1 stores the calculated feature quantity data in the storage device 10, for example, for each lead.

At S507, CPU 1 executes an automatic classification process that assigns a classification to each heartbeat. In the automatic classification process, CPU 1 can assign a classification to each heartbeat based on features calculated for the QRS interval, the shape of the QRT interval, predetermined criteria, etc.

In S509, the CPU 1 outputs a P-wave classification screen to the display unit 6. As described above, the P-wave classification screen may be called from the waveform display screen that displays a list of representative waveforms of heartbeats classified by the automatic classification process. When the P-wave classification screen is displayed, it is assumed that settings such as whether to display a histogram or an XY plot, and which P-wave feature value to use are set in advance.

In S511, CPU 1 determines whether an operation on the P-wave classification screen has been detected, and if it is determined that an operation has been detected, executes S513; if not, executes S511 again.

In S513, CPU 1 determines whether the detected operation is a range specification operation for histogram 310 or XY plot 410. The range specification operation may be, for example, a mouse drag or an equivalent touch operation, or any range specification operation using a keyboard. If CPU 1 determines that a range specification operation has been detected, it executes S515; if not, it executes S517.

In S515, CPU 1 displays superimposed waveforms for heartbeats that correspond to the specified range (selected heartbeats). As described above, CPU 1 can also display superimposed waveforms for heartbeats that do not correspond to the specified range (non-selected heartbeats) or that are not included in the histogram 310 or XY plot 410. After displaying the superimposed waveforms, CPU 1 executes S511.

In S517, CPU 1 determines whether the detected operation is a classification designation operation. A classification designation operation may be, for example, a selection operation on the judgment code change menu 322 described above. If CPU 1 determines that a classification designation operation has been detected, it executes S519. If other operations are detected, such as an operation to change the P-wave feature amount, an operation to switch between the histogram 310 and the XY plot 410, or an operation for displaying overlapping waveforms, CPU 1 performs an operation corresponding to the operation and then executes S511 again.

In S519, CPU 1 collectively assigns the classification specified by the classification specification operation to the heart rate group that is the target of the classification specification operation. The heart rate group that is the target of the classification specification operation is the heart rate group whose waveform is displayed in the superimposed display of the waveform that is the target of the classification specification operation. CPU 1 then executes S511 again. Alternatively, CPU 1 ends the display of the P-wave classification screen and executes an editing operation, for example, via the waveform list screen.

As described above, the electrocardiogram analysis device of this embodiment presents a classification screen that classifies heartbeats according to P-wave features, and has the function of assigning a classification to heartbeat groups selected by the user from the classification screen all at once. This effectively supports the task of assigning supraventricular arrhythmia classifications to heartbeats, which could not be assigned using the automatic classification function based on QRS intervals.

(Other embodiments)
The present invention can also be implemented as a program that causes a computer to function as the electrocardiogram analyzer described in the above embodiment. Furthermore, the present invention is not limited to the content of the above embodiment, and various changes and modifications can be made without departing from the spirit and scope of the invention. Therefore, the following claims are appended to clarify the scope of the invention.

100... General-purpose computer (electrocardiogram analyzer), 1... CPU, 4... Memory card, 10... Storage device, 200... External device

Claims (13)

an acquisition means for acquiring electrocardiogram data;
a calculation means for calculating a feature value of a P wave for each heartbeat of the electrocardiogram data;
an output means for outputting a classification screen that classifies and displays the heartbeats of the electrocardiogram data based on the feature amount of the P wave;
an editing means for providing a function of collectively assigning a classification designated by a user to at least one of the heartbeats selected and the heartbeats not selected on the classification screen;
An electrocardiogram analysis device characterized in that the classification screen has an area for displaying overlapping waveforms for multiple selected heartbeats among the classified and displayed heartbeats, and an area for displaying overlapping waveforms for multiple heartbeats not selected. The electrocardiogram analysis device of claim 1, characterized in that the classification screen includes a histogram relating to the P wave features. The electrocardiogram analysis device of claim 1, characterized in that the classification screen includes an area in which individual heartbeats are plotted within a two-dimensional area in which a first feature of the P wave is assigned to a first axis and a second feature of the P wave is assigned to a second axis. The classification screen includes:
a histogram relating to the feature amount of the P wave;
a region in which individual heartbeats are plotted within a two-dimensional region in which a first feature value of the P wave is assigned to a first axis and a second feature value of the P wave is assigned to a second axis;
2. The electrocardiogram analyzer according to claim 1, wherein the display is switchable. An electrocardiogram analysis device according to any one of claims 1 to 4, characterized in that the editing means provides a function for collectively assigning a classification designated by the user to heartbeats not displayed on the classification screen. An electrocardiogram analysis device according to any one of claims 1 to 5, characterized in that at least one of the waveforms of the selected plurality of heartbeats and the waveforms of the non-selected plurality of heartbeats is displayed superimposed with its horizontal position aligned. the classification screen has an area for displaying waveforms for heartbeats that are not displayed on the classification screen,
7. The electrocardiogram analyzer according to claim 6, wherein waveforms for a plurality of heartbeats that are not displayed on the classification screen are displayed in an overlapping manner with their positions aligned in the horizontal direction. An electrocardiogram analysis device as described in claim 6 or 7, characterized in that the display color of the coordinates constituting the waveform overlay display varies depending on the frequency of the waveforms overlaying those coordinates. An electrocardiogram analysis device according to any one of claims 6 to 8, characterized in that a heartbeat corresponding to a waveform selected in an area where the waveforms of multiple heartbeats are displayed in an overlapping manner is excluded from targets for which a classification is assigned collectively. An electrocardiogram analysis device according to any one of claims 1 to 9, characterized in that a classification relating to supraventricular arrhythmia can be specified as the classification. An electrocardiogram analysis device according to any one of claims 1 to 10, characterized in that the P wave feature quantity includes one or more of the PR interval, PQ interval, P wave width, P wave height, and P wave polarity. an acquisition step of acquiring electrocardiogram data;
a calculation step of calculating a feature value of a P wave for each heartbeat of the electrocardiogram data;
an output step of outputting a classification screen that classifies and displays the heartbeats of the electrocardiogram data based on the feature amount of the P wave;
an editing step of providing a function of collectively assigning a classification designated by a user to at least one of the heartbeats selected and the heartbeats not selected on the classification screen;
and
A method for controlling an electrocardiogram analysis device, characterized in that the classification screen has an area for displaying overlapping waveforms for multiple selected heartbeats from the classified and displayed heartbeats, and an area for displaying overlapping waveforms for multiple heartbeats not selected. A program for causing a computer to function as each of the means possessed by the electrocardiogram analysis device described in any one of claims 1 to 11.