JPH02102640A - Electrocardiogram murmur detection method in arrhythmia analyzer - Google Patents

Abstract

PURPOSE:To attain the irregular pulse analysis processing of satisfactory accuracy by comparing electrocardiogram block data, which are surround by two QRS groups, block data in the past with the same time phase and judging that a noise is included when the block data at a present time are changed from the block data in the past. CONSTITUTION:The thorn-like wave group (QRS group) of a Q-wave, an R-wave and an S-wave is detected among an electrocardiogram waveform. Next, the position of the R-wave and a wave height value are computed from this QRS group. The wave height value of this R-wave is stored to an arrangement R on a memory. Continuously, by subtracting the position of the R-wave before one pulse from the position of the R-wave, an interval (R-R interval) between the present R-wave and the R-wave is computed. The segmentation of the block data is executed from the interval between these R-waves and stored to an arrangement CD on the memory. After the block data are segmented, the computation of an area value (TH) is executed and noise detection is executed by utilizing this area value (TH). Namely, present block data (CD) are compared with past block data (PD) with matching the time phase. Then, the present data exceeds the area value (TH) to the past block data (PD), it is decided that the noise is included in the present block data.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a method for detecting electrocardiogram noise applied in an arrhythmia analyzer.

[Existing necessity of invention]

The present invention is a method for detecting electrocardiogram noise in an arrhythmia analyzer, in which electrocardiogram section data surrounded by two QRS complexes is compared with past section data in the same phase, and the current section data is compared with the past section data. If there is a change exceeding a predetermined range, it is determined that noise is included in the current section, thereby ensuring accurate noise detection regardless of the waveform shape of the electrocardiogram signal.

[Background Art and Problems] When an arrhythmia analyzer automatically detects an arrhythmia from electrocardiogram information, the detection accuracy depends on the magnitude of noise contained in the underlying electrocardiogram.

By accurately detecting electrocardiogram murmurs, the accuracy of arrhythmia detection, the amplitude measurement of each QRS whale wave, and the ST point measurement are improved, and as a result, false alarms of the arrhythmia analyzer are reduced. Accurate detection of electrocardiogram murmurs is essential in arrhythmia analyzers.

Conventionally, the method for detecting electrocardiogram noise in this type of arrhythmia analyzer is to observe the signal levels before and after the QRS complex of the electrocardiogram waveform. or when the T wave is large),
There was a problem that the correct signal was recognized as noise.

The present invention has been made in view of the above, and an object of the present invention is to provide a method that allows accurate noise detection regardless of the waveform shape of an electrocardiogram.

[Means to solve the problem]

In order to achieve the above object, the method of the present invention, as shown in FIG. When comparing the current section data (CD) with the past section data (PD) in the same phase, and when there is a change exceeding the predetermined threshold value (TH) with respect to the past section data (PD), the current section contains noise. The system is designed to determine if the

[For production]

According to the above method, accurate noise detection is performed regardless of the shape of the electrocardiogram waveform.
This is effective in improving the accuracy of arrhythmia analyzers.

〔Example〕 Hereinafter, the present invention will be described in detail with reference to the drawings.

First, FIG. 1 shows the configuration of an arrhythmia analysis device.

That is, an electrocardiogram signal detected from an electrode attached to a subject (living body) is amplified to a predetermined level by an electrocardiogram amplifier (1), converted to a digital signal by an A/D converter (2), and then sent to the CPU ( 3) is done manually.

The CPU (3) stores this digital signal in the memory (
4) is stored in a circular buffer composed of steps 4) and 4). Note that this memory has a sufficient size to store data equal to or more than -heartbeats. Then, the CPU (3) detects noise from the electrocardiogram waveform for each heartbeat according to the processing program stored in the program memory (5), performs a predetermined arrhythmia analysis process, and displays the result on the display unit (6).

A method for detecting electrocardiogram murmurs in this arrhythmia analyzer will be described below.

First, FIG. 2 shows an example of a normal electrocardiogram waveform, which usually consists of R waves, Q waves, R waves, S waves, and T waves. In general, an electrocardiogram consists of repetitions of approximately the same waveform, and in the case of an electrocardiogram with a normal rhythm, R
The level A of the signal located at a point where the same amount of time β has elapsed from the wave as the base point is always approximately the same level.

The present invention takes advantage of this property and compares the ECG section surrounded by the two QRS complexes with the past one in the same phase, and if the current ECG section has changed from the past one, there is noise in the current section. is determined to be included.

A specific method of detecting this noise will be explained in detail in FIGS. 3 and 4. FIG. 4 is a flowchart showing the processing procedure for -heartbeats of the arrhythmia analyzer, and will be explained along the blocks of this flowchart with reference to the electrocardiogram waveform of FIG. 3.

(10) First, a complex of Q waves, R waves, and S waves (hereinafter referred to as the QRS complex) is detected from the electrocardiogram waveform as shown in FIG.

(11) Next, the position and wave height of the R wave are calculated from this QRS complex. This R wave height value is stored in array R on the memory, and is used in threshold value calculation γ (14), which will be described later.

(12) Next, by subtracting the position of the R wave one beat before from the position of the R wave found in (11), the R wave of the bone is calculated this time.
The interval between the waves and the R waves (R-R interval) is calculated.

(13) Then, cut out section data from between these R waves and record it in the array CD on the memory.
Take two sips.

This electrocardiogram interval data is extracted from the data between R and R, excluding the preceding and succeeding dl and d2. Here, d is set to ~0.382 X R-R average (S) time 52 (ms) d2 = 100 (ms), and the interval data length is 56 (ms) ~500
(ms).

FIG. 5 shows a processing program used to cut out this section data.

(14) After cutting out the section data as described above, the threshold value (TH) is calculated. This threshold (T
H) is used to compare past section data and current section data, as described later, and its value is the R of the past 4 heartbeats.
The threshold value (T
I) and stored in memory.

This area is shown in Figure 6! The processing program used to calculate i1 (TH) is shown.

(15) Then, noise detection is performed using this threshold value (TH). That is, in this noise detection, current section data (CD) and past section data (PD) are compared with the same time phase using the following equation.

a= FD(N)-CD(N)-THHere, N indicates the number of data obtained by sampling, and in the above equation, change N from 0 to the shorter number of data between CD and FD, and a 〉If there is even one N that is ○, it is determined that the current section data contains noise.

In other words, as shown in the lower part of Figure 3, the current section data (C
D) is the threshold value (TH) for the past section data (P D)
If there is even a small portion (shaded area in the figure) that exceeds 100 kHz, it is determined that the current section data contains noise, and the noise flag is set to I"IJ. If it is determined that the noise is not included, the noise flag is set to "0". This noise flag is used in later arrhythmia analysis processing.

FIG. 7 shows a processing program used for this noise detection.

(16) After noise detection is performed in this manner, past section data (PD) are averaged using the following equation for the next processing, and stored in the array PD on the memory.

PD(N) - (3XPD(N) - CDI)/4 Here, N changes from 0 to (number of current section data times number of past section data)/2.

FIG. 8 shows a processing program used for this interval data averaging.

(17) After the noise detection processing is performed as described above, arrhythmia analysis processing is performed using a predetermined method. In this arrhythmia analysis processing, if the noise flag described above is "0", normal processing is performed. is performed, and if the noise flag is Vl, the current electrocardiogram waveform is not directly used for arrhythmia analysis, and processing is performed to prevent false alarms from occurring.

By repeating the above processes (10) to (17) for each heartbeat, noise detection in arrhythmia analysis is performed continuously, and highly accurate arrhythmia analysis is realized.

FIG. 4 is a flowchart showing a processing procedure of the arrhythmia analysis device, and FIGS. 5 to 8 are flowcharts showing the main part of the processing program.

: Effect of the invention] As described above, the method of the present invention compares electrocardiogram interval data surrounded by two QRS complexes with past interval data in the same phase,
By determining that noise is included when there is a change in the current section data compared to the past section data, accurate noise detection is possible regardless of the waveform shape of the ECG signal, resulting in accuracy. This has the effect of performing a good arrhythmia analysis process.

[Brief explanation of the drawing]

Figure 1 is a block diagram showing the configuration of the arrhythmia analyzer;
The figure shows an example of a normal electrocardiogram waveform. Figure 3 is a representative electrocardiogram waveform used to explain the method of the present invention. Figure 8

Claims (1)

[Claims] The QRS complex is detected from the electrocardiogram waveform signal, and the electrocardiogram section data surrounded by the two QRS complexes is compared with the past section data in the same phase, and if the current section data is different from the past section data, noise is detected. An electrocardiogram murmur detection method in an arrhythmia analyzer that determines that an electrocardiogram murmur is included.