CN114073534A - Heart function analysis algorithm - Google Patents
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/346—Analysis of electrocardiograms
- A61B5/349—Detecting specific parameters of the electrocardiograph cycle
- A61B5/366—Detecting abnormal QRS complex, e.g. widening
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- A61B5/316—Modalities, i.e. specific diagnostic methods
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- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/346—Analysis of electrocardiograms
- A61B5/349—Detecting specific parameters of the electrocardiograph cycle
- A61B5/352—Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
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- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
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- A61B5/346—Analysis of electrocardiograms
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- A61B5/355—Detecting T-waves
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- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B5/346—Analysis of electrocardiograms
- A61B5/349—Detecting specific parameters of the electrocardiograph cycle
- A61B5/358—Detecting ST segments
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Abstract
The invention discloses a cardiac function analysis algorithm, belongs to the technical field of cardiac function analysis, and aims to solve the problems of inconsistent identification precision and low identification speed caused by obtaining a numerical value corresponding to an electrocardiographic waveform by manually observing the electrocardiographic waveform in the prior art. The waveform can be effectively and rapidly identified through an algorithm based on waveform characteristics, and data under a unified rule are obtained. The time interval information of the QRS wave complex can be accurately identified, a large amount of QRS wave complex data of the waveform can be rapidly obtained, and the problem of different precision caused by visual identification is avoided by using a unified standard. The invention is suitable for the cardiac function analysis algorithm.
Description
Technical Field
The invention belongs to the technical field of cardiac function analysis, and particularly relates to a cardiac function analysis algorithm.
Background
The cardiac function analysis searches for each time interval of the electrocardio QRS complex, compares the found result with a normal numerical value, and is used for cardiac function examination, electrocardio monitoring and heart rate variation analysis. At present, the electrocardiographic waveform is observed manually to obtain corresponding numerical values, so that data obtained by observing different people are different, and the recognition speed is influenced.
Disclosure of Invention
The invention aims to provide a cardiac function analysis algorithm, which solves the problems of inconsistent identification precision and low identification speed caused by obtaining a numerical value corresponding to an electrocardiographic waveform by artificially observing the electrocardiographic waveform in the prior art.
The technical scheme adopted by the invention is as follows:
a cardiac function analysis algorithm comprising the following algorithm steps:
(1) eliminating the influence of small-amplitude waveforms on the electrocardio analysis through smooth filtering, wherein the size of a window selected by the smooth filtering is determined according to the width of the obtained small-amplitude clutter of the waveforms and the sampling rate, the sampling rate is the sampling number of discrete signals which are extracted from continuous signals and formed in unit time, each data point and a plurality of data points adjacent to the left and the right are averaged during the smooth filtering, and then the data points are replaced by the average values;
(2) the number of the electrocardio QRS wave groups is obtained by averaging the bidirectional slopes, the condition of baseline drift is avoided,
slope step-size 0.06 x (1/sampling rate);
analyzing the slope, wherein all turning point parts are positions of R points of the electrocardio, and the number of the QRS wave groups of the electrocardio can be obtained through the number of the turning points;
(3) the average heart rate HR is calculated by the distance between two adjacent R waves, namely the RR interval
(4) According to the position of the R point, taking a numerical value in a range of 0.3s to the left and taking a numerical value in a range of 0.44s to the right, and judging that a complete QRS complex is necessarily present in the range;
PR interval: 0.12-0.20 second;
QRS complex: 0.06-0.10 seconds;
QT interval: 0.30-0.44 seconds;
maximum left-handed R wave: 0.20+0.10 ═ 0.3 seconds;
the maximum value of the R wave is taken to the right: 0.44 second;
(5) inquiring the maximum value in the range, re-correcting the position of the R wave, and storing;
(6) according to the waveform characteristics, Q waves are the first wave trough met by the R waves towards the left, S waves are the first wave trough met by the R waves towards the right, and the Q waves, the R waves and the S waves are finally found out, wherein the wave troughs are searched for to avoid clutter influence, and the point is guaranteed to be the lowest point in the range (0.06S-0.10S);
(7) according to the PR interval: 0.12-0.20, searching the maximum value in the region from the R point to the left, wherein the point is the P wave;
(8) the first wave trough of the P wave which is found to the left is the starting point of the P wave, so that the influence of small clutter on normal wave troughs is avoided, and even if smooth filtering is used, the point needs to be smaller than all points from the right side to the P point;
(9) when T waves are searched, the maximum value of the R point towards the right is the T waves, and meanwhile, a first wave trough is searched according to the fact that the T waves towards the left and the right, namely the starting point and the ending point of the T waves;
(10) searching from the Q wave to the left through the P wave and the Q wave, wherein the first wave crest is the starting point of the Q wave;
(11) searching from the S wave to the right through the S wave and the T wave, wherein the first encountered wave crest is an S wave end point;
(12) after the positions of all the points are obtained, the corresponding intervals are calculated according to the following formula:
PR interval (Q wave start-P wave start)/sampling rate;
QT interval (T wave end point-Q wave start point)/sampling rate;
QRS time limit (S wave end-Q wave start)/sampling rate;
ST period (T wave start point-S wave end point)/sampling rate;
p wave amplitude is equal to P wave number value-P wave starting point value;
r wave amplitude is R wave number value-Q wave starting point value;
the amplitude of the T wave is equal to the value of the T wave number-the value of the starting point of the T wave;
s wave amplitude is equal to S wave number value-S wave end point value;
q wave amplitude is Q wave number value-Q wave initial point value;
and the ST wave amplitude is equal to the T wave starting point value-S wave ending point value.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. in the invention, based on waveform characteristics, the waveform can be effectively and rapidly identified through an algorithm, and data under a unified rule is obtained. The time interval information of the QRS wave complex can be accurately identified, a large amount of QRS wave complex data of the waveform can be rapidly obtained, and the problem of different precision caused by visual identification is avoided by using a unified standard.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and that for those skilled in the art, other relevant drawings can be obtained according to the drawings without inventive effort, wherein:
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 is a single waveform analysis diagram of the present invention;
FIG. 3 is a graph of a plurality of waveform analyses in accordance with the present invention;
FIG. 4 is a sample schematic of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: reference numerals and letters designate similar items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings or the orientations or positional relationships that the products of the present invention usually place when in use, and are simply used for simplifying the description of the present invention, but do not indicate or imply that the devices or elements indicated must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Furthermore, the terms "horizontal", "vertical" and the like do not imply that the components are required to be absolutely horizontal or pendant, but rather may be slightly inclined. For example, "horizontal" merely means that the direction is more horizontal than "vertical" and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; mechanical connection or electrical connection can be realized; the two original pieces can be directly connected or indirectly connected through an intermediate medium, or the two original pieces can be communicated with each other. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
A cardiac function analysis algorithm comprising the following algorithm steps:
(1) eliminating the influence of small-amplitude waveforms on the electrocardio analysis through smooth filtering, wherein the size of a window selected by the smooth filtering is determined according to the width of the obtained small-amplitude clutter of the waveforms and the sampling rate, the sampling rate is the sampling number of discrete signals which are extracted from continuous signals and formed in unit time, each data point and a plurality of data points adjacent to the left and the right are averaged during the smooth filtering, and then the data points are replaced by the average values;
(2) the number of the electrocardio QRS wave groups is obtained by averaging the bidirectional slopes, the condition of baseline drift is avoided,
slope step-size 0.06 x (1/sampling rate);
analyzing the slope, wherein all turning point parts are positions of R points of the electrocardio, and the number of the QRS wave groups of the electrocardio can be obtained through the number of the turning points;
(3) the average heart rate HR is calculated by the distance between two adjacent R waves, namely the RR interval
(4) According to the position of the R point, taking a numerical value in a range of 0.3s to the left and taking a numerical value in a range of 0.44s to the right, and judging that a complete QRS complex is necessarily present in the range;
PR interval: 0.12-0.20 second;
QRS complex: 0.06-0.10 seconds;
QT interval: 0.30-0.44 seconds;
maximum left-handed R wave: 0.20+0.10 ═ 0.3 seconds;
the maximum value of the R wave is taken to the right: 0.44 second;
(5) inquiring the maximum value in the range, re-correcting the position of the R wave, and storing;
(6) according to the waveform characteristics, Q waves are the first wave trough met by the R waves towards the left, S waves are the first wave trough met by the R waves towards the right, and the Q waves, the R waves and the S waves are finally found out, wherein the wave troughs are searched for to avoid clutter influence, and the point is guaranteed to be the lowest point in the range (0.06S-0.10S);
(7) according to the PR interval: 0.12-0.20, searching the maximum value in the region from the R point to the left, wherein the point is the P wave;
(8) the first wave trough of the P wave which is found to the left is the starting point of the P wave, so that the influence of small clutter on normal wave troughs is avoided, and even if smooth filtering is used, the point needs to be smaller than all points from the right side to the P point;
(9) when T waves are searched, the maximum value of the R point towards the right is the T waves, and meanwhile, a first wave trough is searched according to the fact that the T waves towards the left and the right, namely the starting point and the ending point of the T waves;
(10) searching from the Q wave to the left through the P wave and the Q wave, wherein the first wave crest is the starting point of the Q wave;
(11) searching from the S wave to the right through the S wave and the T wave, wherein the first encountered wave crest is an S wave end point;
(12) after the positions of all the points are obtained, the corresponding intervals are calculated according to the following formula:
PR interval (Q wave start-P wave start)/sampling rate;
QT interval (T wave end point-Q wave start point)/sampling rate;
QRS time limit (S wave end-Q wave start)/sampling rate;
ST period (T wave start point-S wave end point)/sampling rate;
p wave amplitude is equal to P wave number value-P wave starting point value;
r wave amplitude is R wave number value-Q wave starting point value;
the amplitude of the T wave is equal to the value of the T wave number-the value of the starting point of the T wave;
s wave amplitude is equal to S wave number value-S wave end point value;
q wave amplitude is Q wave number value-Q wave initial point value;
and the ST wave amplitude is equal to the T wave starting point value-S wave ending point value.
In the implementation process, the waveform can be effectively and rapidly identified through an algorithm based on the waveform characteristics, and data under a unified rule are obtained. The time interval information of the QRS wave complex can be accurately identified, a large amount of QRS wave complex data of the waveform can be rapidly obtained, and the problem of different precision caused by visual identification is avoided by using a unified standard.
Example 1
A cardiac function analysis algorithm eliminates the influence of small-amplitude waveforms on electrocardio analysis through smooth filtering, the size of a window selected by the smooth filtering is determined according to the width of the obtained small-amplitude clutter of the waveforms and the sampling rate, the sampling rate is the sampling number of discrete signals which are extracted from continuous signals and formed in unit time, each data point and a plurality of data points adjacent to the left and the right are averaged during the smooth filtering, and then the average value is used for replacing the data point;
(2) the number of the electrocardio QRS wave groups is obtained by averaging the bidirectional slopes, the condition of baseline drift is avoided,
slope step-size 0.06 x (1/sampling rate);
analyzing the slope, wherein all turning point parts are positions of R points of the electrocardio, and the number of the QRS wave groups of the electrocardio can be obtained through the number of the turning points;
(3) the average heart rate HR is calculated by the distance between two adjacent R waves, namely the RR interval
(4) According to the position of the R point, taking a numerical value in a range of 0.3s to the left and taking a numerical value in a range of 0.44s to the right, and judging that a complete QRS complex is necessarily present in the range;
PR interval: 0.12-0.20 second;
QRS complex: 0.06-0.10 seconds;
QT interval: 0.30-0.44 seconds;
maximum left-handed R wave: 0.20+0.10 ═ 0.3 seconds;
the maximum value of the R wave is taken to the right: 0.44 second;
(5) inquiring the maximum value in the range, re-correcting the position of the R wave, and storing;
(6) according to the waveform characteristics, Q waves are the first wave trough met by the R waves towards the left, S waves are the first wave trough met by the R waves towards the right, and the Q waves, the R waves and the S waves are finally found out, wherein the wave troughs are searched for to avoid clutter influence, and the point is guaranteed to be the lowest point in the range (0.06S-0.10S);
(7) according to the PR interval: 0.12-0.20, searching the maximum value in the region from the R point to the left, wherein the point is the P wave;
(8) the first wave trough of the P wave which is found to the left is the starting point of the P wave, so that the influence of small clutter on normal wave troughs is avoided, and even if smooth filtering is used, the point needs to be smaller than all points from the right side to the P point;
(9) when T waves are searched, the maximum value of the R point towards the right is the T waves, and meanwhile, a first wave trough is searched according to the fact that the T waves towards the left and the right, namely the starting point and the ending point of the T waves;
(10) searching from the Q wave to the left through the P wave and the Q wave, wherein the first wave crest is the starting point of the Q wave;
(11) searching from the S wave to the right through the S wave and the T wave, wherein the first encountered wave crest is an S wave end point;
(12) after the positions of all the points are obtained, the corresponding intervals are calculated according to the following formula:
PR interval (Q wave start-P wave start)/sampling rate;
QT interval (T wave end point-Q wave start point)/sampling rate;
QRS time limit (S wave end-Q wave start)/sampling rate;
ST period (T wave start point-S wave end point)/sampling rate;
p wave amplitude is equal to P wave number value-P wave starting point value;
r wave amplitude is R wave number value-Q wave starting point value;
the amplitude of the T wave is equal to the value of the T wave number-the value of the starting point of the T wave;
s wave amplitude is equal to S wave number value-S wave end point value;
q wave amplitude is Q wave number value-Q wave initial point value;
and the ST wave amplitude is equal to the T wave starting point value-S wave ending point value.
The above description is an embodiment of the present invention. The foregoing is a preferred embodiment of the present invention, and the preferred embodiments in the preferred embodiments can be combined and used in any combination if not obviously contradictory or prerequisite to a certain preferred embodiment, and the specific parameters in the embodiments and examples are only for the purpose of clearly illustrating the verification process of the invention and are not intended to limit the patent protection scope of the present invention, which is subject to the claims and all the equivalent structural changes made by the content of the description and the drawings of the present invention are also included in the protection scope of the present invention.
Claims (1)
1. A cardiac function analysis algorithm, comprising the following algorithm steps:
(1) eliminating the influence of small-amplitude waveforms on the electrocardio analysis through smooth filtering, wherein the size of a window selected by the smooth filtering is determined according to the width of the obtained small-amplitude clutter of the waveforms and the sampling rate, the sampling rate is the sampling number of discrete signals which are extracted from continuous signals and formed in unit time, each data point and a plurality of data points adjacent to the left and the right are averaged during the smooth filtering, and then the data points are replaced by the average values;
(2) the number of the electrocardio QRS wave groups is obtained by averaging the bidirectional slopes, the condition of baseline drift is avoided,
slope step-size 0.06 x (1/sampling rate);
analyzing the slope, wherein all turning point parts are positions of R points of the electrocardio, and the number of the QRS wave groups of the electrocardio can be obtained through the number of the turning points;
(3) the average heart rate HR is calculated by the distance between two adjacent R waves, namely the RR interval
(4) According to the position of the R point, taking a numerical value in a range of 0.3s to the left and taking a numerical value in a range of 0.44s to the right, and judging that a complete QRS complex is necessarily present in the range;
PR interval: 0.12-0.20 second;
QRS complex: 0.06-0.10 seconds;
QT interval: 0.30-0.44 seconds;
maximum left-handed R wave: 0.20+0.10 ═ 0.3 seconds;
the maximum value of the R wave is taken to the right: 0.44 second;
(5) inquiring the maximum value in the range, re-correcting the position of the R wave, and storing;
(6) according to the waveform characteristics, Q waves are the first wave trough met by the R waves towards the left, S waves are the first wave trough met by the R waves towards the right, and the Q waves, the R waves and the S waves are finally found out, wherein the wave troughs are searched for to avoid clutter influence, and the point is guaranteed to be the lowest point in the range (0.06S-0.10S);
(7) according to the PR interval: 0.12-0.20, searching the maximum value in the region from the R point to the left, wherein the point is the P wave;
(8) the first wave trough of the P wave which is found to the left is the starting point of the P wave, so that the influence of small clutter on normal wave troughs is avoided, and even if smooth filtering is used, the point needs to be smaller than all points from the right side to the P point;
(9) when T waves are searched, the maximum value of the R point towards the right is the T waves, and meanwhile, a first wave trough is searched according to the fact that the T waves towards the left and the right, namely the starting point and the ending point of the T waves;
(10) searching from the Q wave to the left through the P wave and the Q wave, wherein the first wave crest is the starting point of the Q wave;
(11) searching from the S wave to the right through the S wave and the T wave, wherein the first encountered wave crest is an S wave end point;
(12) after the positions of all the points are obtained, the corresponding intervals are calculated according to the following formula:
PR interval (Q wave start-P wave start)/sampling rate;
QT interval (T wave end point-Q wave start point)/sampling rate;
QRS time limit (S wave end-Q wave start)/sampling rate;
ST period (T wave start point-S wave end point)/sampling rate;
p wave amplitude is equal to P wave number value-P wave starting point value;
r wave amplitude is R wave number value-Q wave starting point value;
the amplitude of the T wave is equal to the value of the T wave number-the value of the starting point of the T wave;
s wave amplitude is equal to S wave number value-S wave end point value;
q wave amplitude is Q wave number value-Q wave initial point value;
and the ST wave amplitude is equal to the T wave starting point value-S wave ending point value.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101766484A (en) * | 2010-01-18 | 2010-07-07 | 董军 | Method and equipment for identification and classification of electrocardiogram |
| CN108814591A (en) * | 2018-03-23 | 2018-11-16 | 南京大学 | A kind of detection method and its ecg analysis method of Electrocardiograph QRS Wave group width |
| CN108814590A (en) * | 2018-03-23 | 2018-11-16 | 江苏华康信息技术有限公司 | A kind of detection method and its ecg analysis method of Electrocardiograph QRS Wave group |
| CN109875550A (en) * | 2019-04-02 | 2019-06-14 | 东北大学 | A kind of sequences of ventricular depolarization critical point detection method |
| WO2020114068A1 (en) * | 2018-12-07 | 2020-06-11 | 上海数创医疗科技有限公司 | Electrocardiosignal st section automatic determination method and apparatus based on artificial intelligence technology |
| CN112257518A (en) * | 2020-09-30 | 2021-01-22 | 西安交通大学第二附属医院 | ECG identity recognition method based on WT and WOA-PNN algorithm |
| WO2021143401A1 (en) * | 2020-01-17 | 2021-07-22 | 上海优加利健康管理有限公司 | Method and device for detecting p wave and t wave in electrocardiogram signal |
| WO2021169296A1 (en) * | 2020-02-27 | 2021-09-02 | 平安科技（深圳）有限公司 | Method and apparatus for processing electrocardiogram data, computer device, and storage medium |
-
2021
- 2021-11-25 CN CN202111413547.0A patent/CN114073534B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101766484A (en) * | 2010-01-18 | 2010-07-07 | 董军 | Method and equipment for identification and classification of electrocardiogram |
| CN108814591A (en) * | 2018-03-23 | 2018-11-16 | 南京大学 | A kind of detection method and its ecg analysis method of Electrocardiograph QRS Wave group width |
| CN108814590A (en) * | 2018-03-23 | 2018-11-16 | 江苏华康信息技术有限公司 | A kind of detection method and its ecg analysis method of Electrocardiograph QRS Wave group |
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| WO2021169296A1 (en) * | 2020-02-27 | 2021-09-02 | 平安科技（深圳）有限公司 | Method and apparatus for processing electrocardiogram data, computer device, and storage medium |
| CN112257518A (en) * | 2020-09-30 | 2021-01-22 | 西安交通大学第二附属医院 | ECG identity recognition method based on WT and WOA-PNN algorithm |
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| CN116570295B (en) * | 2023-07-14 | 2024-04-30 | 浙江好络维医疗技术有限公司 | Electrocardiogram low-voltage T-wave end point positioning method |
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