CN117224146A

CN117224146A - Method and system for detecting characteristic waves in electrocardiosignal

Info

Publication number: CN117224146A
Application number: CN202311271729.8A
Authority: CN
Inventors: 王雪; 周浩; 付迅; 吴彦北
Original assignee: Wuhan Zhongke Medical Technology Industrial Technology Research Institute Co Ltd
Current assignee: Wuhan Zhongke Medical Technology Industrial Technology Research Institute Co Ltd
Priority date: 2023-09-27
Filing date: 2023-09-27
Publication date: 2023-12-15

Abstract

The embodiment of the specification discloses a method and a system for detecting characteristic waves in an electrocardiosignal. The method comprises the following steps: acquiring a target electrocardiosignal, wherein the target electrocardiosignal comprises a plurality of data points which are sequentially acquired; forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point. By forward detection and superposition amplitude judgment based on slope judgment, the characteristic wave in the electrocardiosignal can be accurately detected in real time.

Description

Method and system for detecting characteristic waves in electrocardiosignal

Technical Field

The present disclosure relates to the field of electrocardiographic signal analysis, and in particular, to a method and system for detecting a characteristic wave in an electrocardiographic signal.

Background

Heart disease is a common and serious threat to human health at present, and diagnosis and prevention of heart disease are one of the main problems to be solved in medical research. To date, heart disease has generally been diagnosed primarily clinically by means of Electrocardiogram (ECG) measurements and assisted by other therapeutic means. Electrocardiogram reflects the contraction and relaxation of ventricles and atria by recording the body surface potential difference generated by the change of the heart electrical activity in each cardiac cycle, and usually, the detection of waveforms and heart rate in electrocardiosignals can accurately diagnose heart diseases.

With the development of medical technology, real-time waveform detection of dynamic electrocardiosignals has gradually become an important link in clinical diagnosis and treatment of heart diseases. The real-time detection technology of the waveform can further improve the accuracy of judging the current heart state of the patient, the accuracy of treatment, assist other diagnosis means to a greater extent, and the like. Thus, it is often clinically desirable to achieve accurate detection of electrocardiographic waveforms in real time.

Disclosure of Invention

The application aims to provide a method capable of accurately detecting characteristic waves in electrocardiosignals in real time.

A first aspect of embodiments of the present specification provides a method of detecting a characteristic wave in an electrocardiographic signal, comprising: acquiring a target electrocardiosignal, wherein the target electrocardiosignal comprises a plurality of data points; forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point.

In some embodiments, the first threshold condition is further defined based on a time interval threshold from the starting point to a reference data point.

In some embodiments, in determining whether a data point meets the first threshold condition, it is first determined whether an amplitude of the data point meets the first threshold condition, and when the amplitude of the data point meets the first threshold condition, it is then determined whether a slope of the data point meets the first threshold condition.

In some embodiments, the target feature wave comprises an R wave. The first threshold condition of the R-wave includes: the amplitudes of the data point and the last data point reach the amplitude threshold of the R wave starting point, and the slopes of the data point and the last data point reach the slope threshold of the R wave starting point. The second threshold condition of the R wave includes: the peak point is behind the R wave starting point, and a first time interval of the peak point is larger than or equal to a first time length threshold value and smaller than or equal to a first preset multiple of an average R wave interval, wherein the first time interval is a time interval from the peak point to a determined latest R wave crest, and the average R wave interval is an average time interval between all determined adjacent R waves. In some embodiments, the first time length threshold is 0.2 seconds and the first preset multiple is 1.66.

In some embodiments, before determining the first R-wave starting point, the method further comprises: and initializing an amplitude threshold of an R wave starting point, a slope threshold of the R wave starting point, an amplitude of a noise peak and an amplitude of an R wave peak based on the initial part of the target electrocardiosignal. Before determining the next R-wave starting point, the method further comprises: if there is a peak point where the first time interval is less than or equal to the first time length threshold, determining it as a noise peak; updating an amplitude threshold of an R wave starting point based on the determined amplitude of the latest R wave peak and the determined amplitude of the latest noise peak; updating the slope threshold of the R-wave onset based on the determined magnitude of the most recent R-wave peak and the determined magnitude of the most recent R-wave onset. In some embodiments, the updated R-wave onset point amplitude threshold is equal to a weighted sum of the determined latest R-wave peak amplitude and the determined latest noise peak amplitude, wherein the determined latest R-wave peak amplitude corresponds to a weight of 0.25 and the determined latest noise peak amplitude corresponds to a weight of 0.75.

In some embodiments, the target feature wave further comprises a T wave. The first threshold condition of the T wave includes: the time interval from the data point and the last data point to the determined latest R wave crest is larger than or equal to the second time length threshold and smaller than or equal to the third time length threshold, the amplitude of the data point and the last data point reaches the amplitude threshold of the T wave starting point, and the slopes of the data point and the last data point reach the slope threshold of the T wave starting point. The second threshold condition of the T wave includes: and the second time interval of the peak point is smaller than or equal to the third time length threshold value after the T wave starting point, wherein the second time interval is the time interval from the peak point to the determined latest R wave crest. In some embodiments, the second duration threshold is 0.04 seconds and the third duration threshold is 0.5 seconds.

In some embodiments, before determining the first T-wave initiation point, the method further comprises: and initializing an amplitude threshold of a T wave starting point based on the initial part of the target electrocardiosignal. Before determining the next T-wave starting point, the method further comprises: if there is a peak point where the second time interval is greater than or equal to the third duration threshold, determining it as a noise peak; the amplitude threshold of the T-wave onset is updated based on the determined amplitude threshold of the latest T-wave onset and the determined amplitude of the latest T-wave peak. Before determining the starting point of each T-wave, the method further comprises: and calculating a second preset multiple of the slope threshold value of the determined latest R wave starting point to obtain the slope threshold value of the T wave starting point.

In some embodiments, the initial value of the amplitude threshold of the R-wave onset is equal to a first preset proportion of the maximum amplitude of the onset portion, the initial value of the slope threshold of the R-wave onset is equal to a second preset proportion of the maximum slope of the onset portion, the initial value of the amplitude of the noise peak is equal to a third preset proportion of the average amplitude of the onset portion, and the initial value of the amplitude of the R-wave peak is equal to the initial value of the amplitude threshold of the R-wave onset portion. The initial value of the amplitude threshold of the T wave starting point is equal to the sum of a fourth preset proportion of a target difference value and the minimum amplitude of the starting part, the target difference value is the difference value between the initial value of the amplitude threshold of the R wave starting point and the minimum amplitude, the updated amplitude threshold of the T wave starting point is equal to the fifth preset proportion of a target sum value, and the target sum value is the sum of the determined amplitude threshold of the latest T wave starting point and the determined amplitude of the latest T wave crest. In some embodiments, the first preset ratio is 1/3, the second preset ratio is 1/2, the third preset ratio is 1/2, the fourth preset ratio is 3/5, and the fifth preset ratio is 1/4; the second preset multiple is equal to 0.1.

A second aspect of embodiments of the present specification provides an apparatus for detecting a characteristic wave in an electrocardiographic signal, comprising a processor and a storage device. The storage device is used for storing instructions, and when the processor executes the instructions, the method for detecting the characteristic wave in the electrocardiosignal according to any embodiment of the specification is realized.

A third aspect of the embodiments of the present specification provides a system for detecting a characteristic wave in an electrocardiographic signal, including a signal acquisition module and a waveform detection module. The signal acquisition module is used for acquiring a target electrocardiosignal, and the target electrocardiosignal comprises a plurality of data points. The waveform detection module is used for: forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point.

A fourth aspect of the embodiments of the present specification provides an imaging control method, including: acquiring a target electrocardiosignal, wherein the target electrocardiosignal comprises a plurality of data points; forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; in the process of judging whether a data point meets the first threshold condition, judging whether the amplitude of the data point meets the first threshold condition, and judging whether the slope of the data point meets the first threshold condition when the amplitude of the data point meets the first threshold condition; continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point. In some embodiments, the method further comprises: when the peak of the R wave or the end point of the T wave is determined, the imaging device is controlled to acquire a frame of image of the heart, wherein the target characteristic wave comprises the R wave or the T wave, and the end point of the T wave is determined based on the peak of the same T wave. In other embodiments, the method further comprises: and controlling the imaging equipment to acquire a frame of image of the heart at the arrival time of the T wave end point, wherein the target characteristic wave comprises an R wave, and the arrival time of the T wave end point is predetermined based on the arrival time of the R wave crest in the same cardiac cycle.

A fifth aspect of embodiments of the present specification provides an imaging control apparatus, including a processor and a storage device for storing instructions, which when executed by the processor, implement an imaging control method according to any of the embodiments of the present specification.

A sixth aspect of the embodiments of the present specification provides an imaging control system including a signal acquisition module, a waveform detection module, and an imaging control module. The signal acquisition module is used for acquiring a target electrocardiosignal, and the target electrocardiosignal comprises a plurality of data points. The waveform detection module is used for: forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point. In the process of judging whether the data point meets the first threshold condition, judging whether the amplitude of the data point meets the first threshold condition, and judging whether the slope of the data point meets the first threshold condition when the amplitude of the data point meets the first threshold condition. The waveform detection module is further configured to: continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point. In some embodiments, the imaging control module is to: when the peak of the R wave or the end point of the T wave is determined, the imaging device is controlled to acquire a frame of image of the heart, wherein the target characteristic wave comprises the R wave or the T wave, and the end point of the T wave is determined based on the peak of the same T wave. In other embodiments, the imaging control module is configured to: and controlling the imaging equipment to acquire a frame of image of the heart at the arrival time of the T wave end point, wherein the target characteristic wave comprises an R wave, and the arrival time of the T wave end point is predetermined based on the arrival time of the R wave crest in the same cardiac cycle.

A seventh aspect of the embodiments of the present specification provides an image processing method, including: acquiring a target electrocardiosignal, wherein the target electrocardiosignal comprises a plurality of data points which are sequentially acquired; forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; in the process of judging whether a data point meets the first threshold condition, judging whether the amplitude of the data point meets the first threshold condition, and judging whether the slope of the data point meets the first threshold condition when the amplitude of the data point meets the first threshold condition; continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point; the target characteristic wave comprises an R wave and a T wave, and the wave crest of the target characteristic wave comprises an R wave crest and a T wave crest; acquiring an image sequence of a heart, the image sequence comprising a plurality of frames of images; and marking images corresponding to the arrival time of the R wave crest and/or the T wave end point in the image sequence, wherein the T wave end point is determined based on the crest of the same T wave.

In some embodiments, the time interval from the T-wave end point to the corresponding R-wave peak is equal to a sixth preset proportion of the average R-wave interval, the sixth preset proportion ranging from 30% to 35%.

An eighth aspect of the embodiments of the present specification provides an image processing apparatus, including a processor and a storage device, where the storage device is configured to store instructions, and when the processor executes the instructions, implement an image processing method according to any of the embodiments of the present specification.

A ninth aspect of the embodiments of the present specification provides an image processing system, including a signal acquisition module, a waveform detection module, an image acquisition module, and a marking module. The signal acquisition module is used for acquiring a target electrocardiosignal which comprises a plurality of data points acquired in sequence. The waveform detection module is used for: forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point. In the process of judging whether the data point meets the first threshold condition, judging whether the amplitude of the data point meets the first threshold condition, and judging whether the slope of the data point meets the first threshold condition when the amplitude of the data point meets the first threshold condition. The waveform detection module is further configured to: continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point. The target characteristic wave comprises an R wave and a T wave, and the wave crest of the target characteristic wave comprises an R wave crest and a T wave crest. The image acquisition module is used for acquiring an image sequence of the heart, wherein the image sequence comprises a plurality of frames of images. The marking module is used for marking images corresponding to the arrival time of the R wave crest and/or the T wave end point in the image sequence, wherein the T wave end point is determined based on the crest of the same T wave.

A tenth aspect of the embodiments of the present specification provides a computer-readable storage medium storing computer instructions which, when executed by a computer, implement a method as described in any of the embodiments of the present specification, for example, a method of detecting a characteristic wave in an electrocardiographic signal, an imaging control method, an image processing method.

Embodiments of the present specification provide a method and system for detecting a characteristic wave in an electrocardiographic signal. The method comprises the following steps: forward detection is maintained in the target electrocardiosignal to sequentially detect a starting point and a peak of the target characteristic wave, wherein threshold conditions met by the starting point and the peak are defined based on an amplitude threshold and a slope threshold. By forward detection and superposition amplitude judgment based on slope judgment, the characteristic wave in the electrocardiosignal can be accurately detected in real time.

Drawings

The present specification will be further elucidated by way of example embodiments, which will be described in detail by means of the accompanying drawings. The embodiments are not limiting, in which like numerals represent like structures, wherein:

FIG. 1 shows the band composition of an electrocardiogram;

FIGS. 2A and 2B are exemplary block diagrams of medical information handling systems according to some embodiments of the present disclosure;

FIG. 3 is an exemplary flow chart for detecting a characteristic wave in an electrocardiographic signal according to some embodiments of the present description;

FIG. 4 is an exemplary flow chart of an R-wave detection method according to some embodiments of the present description;

FIG. 5 shows the real-time detection of R-waves using the R-wave detection method described above under normal heart rate conditions;

FIG. 6 shows the calculation of R-R intervals for a normal heart rate situation;

FIG. 7 shows the R-wave real-time detection results obtained by the R-wave detection method described above in the case of arrhythmia;

FIG. 8 is an exemplary flow chart of a T-wave detection method according to some embodiments of the present description;

fig. 9 shows the T-wave real-time detection result obtained by the T-wave detection method under the normal heart rate condition.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present specification, the drawings that are required to be used in the description of the embodiments will be briefly described below. It is apparent that the drawings in the following description are only some examples or embodiments of the present specification, and it is possible for those of ordinary skill in the art to apply the present specification to other similar situations according to the drawings without inventive effort. Unless otherwise apparent from the context of the language or otherwise specified, like reference numerals in the figures refer to like structures or operations.

It will be appreciated that "system," "apparatus," "unit" and/or "module" as used herein is one method for distinguishing between different components, elements, parts, portions or assemblies of different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

As used in this specification, the terms "a," "an," "the," and/or "the" are not intended to be limiting, but rather are to be construed as covering the singular and the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that the steps and elements are explicitly identified, and they do not constitute an exclusive list, as other steps or elements may be included in a method or apparatus.

A flowchart is used in this specification to describe the operations performed by the system according to embodiments of the present specification. It should be appreciated that the preceding or following operations are not necessarily performed in order precisely. Rather, the steps may be processed in reverse order or simultaneously. Also, other operations may be added to or removed from these processes.

Fig. 1 shows the band composition of an electrocardiogram. As shown in fig. 1, the electrocardiographic signal of each cardiac cycle is composed of several bands containing several characteristic waves, for example, P-wave, Q-wave, R-wave, S-wave, T-wave, U-wave. There are also some bands between the characteristic waves, e.g., P-R band, S-T band. The electrocardiographic signal also has some important intervals (intervals), such as P-R intervals, Q-T intervals, S-T intervals, P-P intervals, R-R intervals. The cardiac cycle (cardiac cycle) refers to the start of one heartbeat to the start of the next heartbeat.

Fig. 2A and 2B are exemplary block diagrams of medical information processing systems according to some embodiments of the present description. Medical information processing system 200 (system 200 for short) may be implemented on a processing device. As shown in fig. 2A or 2B, the system 200 includes a signal acquisition module 210 and a waveform detection module 220. At this time, the system 200 is a system for detecting a characteristic wave in an electrocardiographic signal.

The signal acquisition module 210 is configured to acquire a target electrocardiographic signal, where the target electrocardiographic signal includes a plurality of data points. The target electrocardiographic signal may include amplitudes of the plurality of data points acquired sequentially at a plurality of time points, the plurality of time points being in one-to-one correspondence with the plurality of data points. Referring to fig. 1, the point in time corresponding to a data point (also referred to as the arrival time of the data point) is the abscissa of the data point, and the magnitude of the data point is the ordinate of the data point.

The waveform detection module 220 is configured to detect, in a forward direction along the plurality of data points, a data point that satisfies a first threshold condition of the target characteristic wave as a start point of the target characteristic wave, for example, detect an R-wave start point and/or a T-wave start point. The first threshold condition may be defined based on one or more thresholds (e.g., slope threshold, amplitude threshold, time interval threshold to a particular data point, etc.) of the starting point.

In some embodiments, the waveform detection module 220 is further configured to detect, in a forward direction along the plurality of data points, a data point that satisfies a second threshold condition of the target feature wave as a peak of the target feature wave, e.g., detect an R-wave peak and/or a T-wave peak. The peak of the target characteristic wave (e.g., R wave) is the peak point (e.g., R point in fig. 1) of the target characteristic wave. When the target characteristic wave is doped with a noise peak, the target characteristic wave peak is usually the peak point with the largest amplitude in the target characteristic wave. The second threshold condition may be defined based on a time interval threshold of the peak to reference data point.

In some embodiments, as shown in fig. 2A, the system 200 further includes an imaging control module 230. At this point, system 200 is an imaging control system. In some embodiments, the imaging control module 230 is to: based on the determined specific data points (such as R wave peak and T wave end point), the imaging device is controlled to acquire a frame of image of the heart at the end diastole (corresponding to the R wave peak) and/or at the end systole (corresponding to the T wave end point). In some embodiments, as shown in fig. 2B, the system 200 further includes an image acquisition module 240 and a marking module 250. At this point, system 200 is an image processing system. The image acquisition module 240 is used to acquire a sequence of images of the heart. The labeling module 250 is configured to label a frame of image of end diastole of a ventricle and/or a frame of image of end systole of a ventricle (corresponding to the T-wave end point) in the image sequence based on the determined specific data points (e.g., R-wave peak, T-wave end point). In some embodiments, system 200 may be implemented by a computing device. The computing device may be part of an Electrocardiogram (ECG) machine and/or an ultrasound imaging device. Alternatively, the computing device may be a stand-alone computing device.

For more details on system 200 and its modules, reference may be made to FIG. 3 and its associated description.

It should be appreciated that the systems shown in fig. 2A, 2B and modules thereof may be implemented in a variety of ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Wherein the hardware portion may be implemented using dedicated logic; the software portions may then be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system of the present specification and its modules may be implemented not only with hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also with software executed by various types of processors, for example, and with a combination of the above hardware circuits and software (e.g., firmware).

It should be noted that the above description of the system and its modules is for convenience of description only and is not intended to limit the present description to the scope of the illustrated embodiments. It will be appreciated by those skilled in the art that, given the principles of the system, various modules may be combined arbitrarily or a subsystem may be constructed in connection with other modules without departing from such principles. For example, the signal acquisition module 210 and the waveform detection module 220 may be two modules, or may be combined into one module. Such variations are within the scope of the present description.

Fig. 3 is an exemplary flow chart for detecting a characteristic wave in an electrocardiographic signal according to some embodiments of the present description. The process 300 may be performed by a processing device. In some embodiments, the process 300 is performed by the system 200. As shown in fig. 3, the process 300 includes the following steps.

In step 310, a target electrocardiographic signal is acquired, the target electrocardiographic signal including a plurality of data points. In some embodiments, step 310 is performed by signal acquisition module 210.

In some embodiments, the signal acquisition module 210 acquires an initial electrocardiographic signal and performs filtering processing on the initial electrocardiographic signal to obtain a target electrocardiographic signal.

In some embodiments, the signal acquisition module 210 may directly acquire the target electrocardiographic signal, for example, the external device may perform filtering processing on the initial electrocardiographic signal, and send the obtained target electrocardiographic signal to the signal acquisition module 210.

The initial and/or target electrocardiograph signals may be acquired by any electrocardiograph signal acquisition instrument.

Step 320, detecting, forward along a time dimension, among the plurality of data points, to detect a data point satisfying a first threshold condition of the target feature wave as a starting point of the target feature wave. In some embodiments, step 320 is performed by waveform detection module 220.

The target characteristic wave may include one or more of R wave, T wave, P wave, Q wave, S wave.

Forward detection (also referred to as forward detection/forward search) refers to detecting a plurality of data points along a direction of time lapse to find data points that satisfy a condition (e.g., a first threshold condition). For example, for three data points A, B, C acquired sequentially (arrival times satisfy t _A <t _B <t _C ) The waveform detection module 220 may detect one by one in the order a→b→c to find data points that satisfy the condition.

Opposite to forward detection is backward detection (also referred to as reverse detection/reverse search), which refers to detecting a previous data point against the direction of the passage of time after detecting a specific data point (e.g., a start point) to find a data point satisfying the condition. For example, for two data points A, B acquired in sequence (arrival time satisfies t _A <t _B ) After detecting that the data point B is the R wave start point, the waveform detection module 220 returns to detect whether the data point a is the R wave peak.

The forward detection may improve the real-time performance of the waveform detection compared to the backward detection.

For convenience of distinction, the text refers to a threshold condition for detecting a start point (onset point) of the target feature wave as a first threshold condition of the target feature wave, and a threshold condition for detecting a peak of the target feature wave as a second threshold condition of the target feature wave.

In some embodiments, the first threshold condition may be defined based on a slope threshold of the starting point. For example, the first threshold condition of the R-wave may be defined based on a slope threshold of the R-wave starting point. When the slope of a data point reaches the slope threshold of the R-wave onset point, the waveform detection module 220 may determine the data point as the R-wave onset point.

In the detection mode which depends on the slope threshold only, the accuracy of the detection result is easily interfered by signal noise. In some embodiments, the first threshold condition may be defined based on an amplitude threshold and a slope threshold of the starting point. Thus, the accuracy of the detection result can be improved. For example, the first threshold condition of the R-wave may be defined based on an amplitude threshold and a slope threshold of the R-wave starting point. When the amplitude of a data point reaches the amplitude threshold of the R-wave onset and the slope reaches the slope threshold of the R-wave onset, the waveform detection module 220 may determine the data point as the R-wave onset.

The accuracy of the detection result can be improved and the detection efficiency can be improved by superposing amplitude judgment on the basis of slope judgment. In particular, if data points are detected one by one depending only on the slope threshold, the calculation amount of the slope will be very large. By setting the judgment priority of the amplitude to be higher than the judgment priority of the slope, the number of data points required to calculate the slope can be effectively reduced, i.e., the calculation amount of the slope is reduced, so that the detection efficiency can be improved. Specifically, in determining whether the data point satisfies the first threshold condition, the waveform detection module 220 may determine whether the amplitude of the data point satisfies the first threshold condition, and determine whether the slope of the data point satisfies the first threshold condition when the amplitude of the data point satisfies the first threshold condition.

In some embodiments, the first threshold condition may also be defined based on a time interval threshold from the starting point to the reference data point. That is, the first threshold condition may additionally limit the time range of the starting point. Reference data points referred to herein generally take the form of characteristic data points (e.g., characteristic peaks) that have been determined. For example, the first threshold condition may additionally limit the range of time intervals from the T-wave start point to the determined latest R-wave peak.

Similarly, in determining whether a data point meets a first threshold condition, the waveform detection module 220 may first determine whether the amplitude of the data point and/or the time interval (to a reference data point) meets the first threshold condition, and then determine whether the slope of the data point meets the first threshold condition when the amplitude and/or the time interval of the data point meets the first threshold condition. Thus, the amount of calculation of the slope can be reduced, thereby improving the detection efficiency.

In some embodiments, the process 300 may further include a detection step 330 of a characteristic peak (peak of the target characteristic wave).

And 330, continuing to detect forward along the acquisition time dimension after the starting point of the target characteristic wave, so as to detect the peak point meeting the second threshold condition of the target characteristic wave as the peak of the target characteristic wave. In some embodiments, step 330 is performed by waveform detection module 220.

In some embodiments, the second threshold condition is defined based on a time interval threshold of the characteristic peak to the reference data point. That is, the second threshold condition may limit the time range of the characteristic peak. For example, the second threshold condition may limit the time interval between adjacent two R-wave peaks, i.e., the R-R interval (R-wave interval).

In some embodiments, when the target feature wave comprises an R wave, the first threshold condition of the R wave may comprise: the amplitude of the data point and the last data point reach the amplitude threshold of the R wave starting point, and the slope of the data point and the last data point reach the slope threshold of the R wave starting point. It will be appreciated that the arrival time of data point a is earlier than the arrival time of data point B (i.e., t _A <t _B ) In this case, data point A may be referred to as the last data point of data point B (also referred to as data point A preceding data point B), and data point B may be referred to as the next data point of data point A (also referred to as data point B following data point A)). That is, when both the amplitude and slope of two consecutive data points reach a threshold, the waveform detection module 220 may determine the latter of the two data points as the R-wave onset point.

Based on the determined R-wave start point, the waveform detection module 220 may further determine an R-wave peak from a peak point subsequent to the R-wave start point. Specifically, the second threshold condition of the R wave may include: the peak point is behind the R wave starting point, and the first time interval of the peak point is larger than or equal to a first time length threshold value and smaller than or equal to a first preset multiple of the average R wave interval. Wherein the first time interval is the time interval from the peak point to the determined latest R wave peak, and the average R wave interval is the average time interval (i.e. average R-R interval) between all the determined adjacent R waves. When the first time interval of the peak point is too small, the peak point is typically a noise peak rather than an R-wave peak, and thus, the waveform detection module 220 may determine the peak point where the first time interval is less than or equal to the first time length threshold as a noise peak. When the first time interval of the peak point is too large, there may be R-wave missed detection, so if the first time interval of the peak point is greater than the first preset multiple of the average R-wave interval, the peak point will not be the R-wave peak. In some embodiments, the first time length threshold is in a range of 0.18 to 0.22 seconds and the first predetermined multiple is in a range of 1.6 to 1.7. In some embodiments, the first time length threshold is 0.2 seconds and the first preset multiple is 1.66.

The determination of the critical value is not particularly limited in this specification. For example only, in some embodiments, the waveform detection module 220 determines the peak point as a noise peak when the first time interval of the peak point is equal to the first time length threshold. In other embodiments, the waveform detection module 220 determines the peak point as the R-wave peak when the first time interval of the peak point is equal to the first time threshold.

In some embodiments, the waveform detection module 220 initializes a correlation threshold for R-wave detection based on a starting portion of the target electrocardiograph signal to determine a first R-wave starting point. Further, at each cardiac cycle, the waveform detection module 220 updates the correlation threshold for R-wave detection to determine the next R-wave onset.

Specifically, before determining the first R-wave onset, the waveform detection module 220 initializes an amplitude threshold of the R-wave onset, a slope threshold of the R-wave onset, an amplitude of the noise peak, and an amplitude of the R-wave peak based on the onset portion of the target electrocardiograph signal. Further, before determining the next R-wave starting point: if there is a peak point where the first time interval is less than or equal to the first time length threshold, the waveform detection module 220 determines it as a noise peak; based on the determined amplitude of the most recent R-wave peak and the determined amplitude of the most recent noise peak, the waveform detection module 220 updates the amplitude threshold of the R-wave onset point; based on the determined amplitude of the most recent R-wave peak and the determined amplitude of the most recent R-wave onset, the waveform detection module 220 updates the slope threshold of the R-wave onset.

In some embodiments, the updated R-wave onset point amplitude threshold is equal to a weighted sum of the determined latest R-wave peak amplitude and the determined latest noise peak amplitude. The weight corresponding to the determined latest R-wave peak amplitude and the weight corresponding to the determined latest noise peak amplitude may take any suitable values. For example, the determined amplitude of the most recent R-wave peak corresponds to a weight of 0.25, and the determined amplitude of the most recent noise peak corresponds to a weight of 0.75. The update of the amplitude threshold for the R-wave start point can be expressed as follows:

R_amplitude_threshold＝noise_amplitude+0.25*(R_peak_amplitude-noise_amplitude) (1)。

where r_amplitude_threshold represents the amplitude threshold of the R wave start point, noise_amplitude represents the amplitude of the determined latest noise peak, and r_peak_amplitude represents the amplitude of the determined latest R wave peak.

For a specific detection procedure of the R wave, reference may be made to fig. 4 and the description thereof.

In some embodiments, when the target feature wave further comprises a T wave, the first threshold condition of the T wave comprises: the time interval from the data point and the last data point to the determined latest R wave crest is larger than the second time length threshold and smaller than or equal to the third time length threshold, the amplitude of the data point and the last data point reaches the amplitude threshold of the T wave starting point, and the slope of the data point and the last data point reaches the slope threshold of the T wave starting point. That is, the waveform detection module 220 may determine the latter of two consecutive data points as the T-wave start point when the amplitude, time interval to the determined latest R-wave peak, and slope of both data points satisfy the threshold condition.

By limiting the amplitude of the T wave starting point and the time interval from the T wave starting point to the R wave crest, the false detection rate and the omission rate of the T wave can be reduced, and the calculated amount of the slope can be reduced. This limitation is particularly important when setting a lower R-wave slope threshold, as a lower R-wave slope threshold increases the false detection rate of the T-wave and the amount of slope calculation.

In an electrocardiogram, the QRS complex has a duration of about 0.04 to 0.12 seconds (also shown as 0.06 to 0.08 seconds), the S-T segment has a duration of about 0.05 to 0.15 seconds, and the Q-T interval has a duration of about 0.4 seconds or less. In summary, it is considered that the time interval from the T wave to the R wave peak is in the range of 0.04 to 0.5 seconds. Thus, it is possible to set: the second duration threshold is equal to 0.04 second and the third duration threshold is equal to 0.5 second, so that the condition of T wave missing detection is effectively avoided. It should be appreciated that the second duration threshold may also be set to any other suitable value, for example, 0.05 seconds, 0.06 seconds, etc.; the third duration threshold may also be set to any other suitable value, for example, 0.4 seconds, 0.45 seconds, etc.

Based on the determined T-wave start point, the waveform detection module 220 may further determine a T-wave peak from a peak point subsequent to the T-wave start point. Specifically, the second threshold condition of the T wave includes: the peak point is behind the T wave starting point, and the second time interval of the peak point is smaller than or equal to the third time length threshold value, wherein the second time interval is the time interval from the peak point to the determined latest R wave crest. When the second time interval of the peak point is too large, the peak point is typically a noise peak rather than a T-wave peak, and thus, the waveform detection module 220 may determine the peak point where the second time interval is greater than or equal to the third duration threshold as a noise peak. In some embodiments, more strictly, the second threshold condition of the T wave includes: the second time interval of the peak point is smaller than or equal to the third time threshold after the T wave starting point, and the amplitude of the peak point is smaller than the amplitude of the R wave crest in the same cardiac cycle. That is, when the amplitude of the peak point is not less than the amplitude of the R wave peak in the same cardiac cycle, the peak point is determined as a noise peak instead of the T wave peak.

In some embodiments, the waveform detection module 220 initializes a correlation threshold for T-wave detection based on a starting portion of the target electrocardiograph signal to determine a first T-wave starting point. Further, at each cardiac cycle, the waveform detection module 220 updates the correlation threshold for T-wave detection to determine the next T-wave starting point.

Specifically, before determining the first T-wave onset, the waveform detection module 220 initializes an amplitude threshold for the T-wave onset based on the onset portion of the target electrocardiograph signal. Before determining the next T-wave start point: if there is a peak point where the second time interval is greater than or equal to the third duration threshold, the waveform detection module 220 determines it as a noise peak; the amplitude threshold of the T-wave onset is updated based on the determined amplitude threshold of the latest T-wave onset and the determined amplitude of the latest T-wave peak. Before determining each T-wave start point, the waveform detection module 220 calculates a second preset multiple of the slope threshold of the determined latest R-wave start point, to obtain the slope threshold of the T-wave start point.

After the peak of the R wave is detected in each cardiac cycle, a detection link of the T wave is entered. The amplitude of the T wave is relatively small and the waveform is significantly wider than the R wave, which has a large amplitude and a narrow waveform, so that the slope of the whole is small. Based on this, the slope threshold value of the T-wave start point may be set to 0.1 to 0.3 times the slope threshold value of the R-wave start point. According to the foregoing, if a lower slope threshold of the T-wave start point is set (for example, the slope threshold of the T-wave start point is set to 0.1 times the slope threshold of the R-wave start point), then: by limiting the amplitude of the T wave start point and the time interval from the T wave start point to the R wave peak (for example, in the range of 0.04 to 0.5 seconds), the false detection rate and the omission rate of the T wave can be reduced, and the calculation amount of the slope can be reduced.

In some embodiments, the starting portion for threshold initialization may be a signal portion of a preset duration, e.g., the first 2s data point in the target electrocardiograph signal.

In some embodiments, for R-wave detection: the initial value of the amplitude threshold of the R wave starting point is equal to a first preset proportion of the maximum amplitude of the starting part; the initial value of the slope threshold of the R wave starting point is equal to a second preset proportion of the maximum slope of the starting part; the initial value of the amplitude of the noise peak is equal to a third preset proportion of the average amplitude of the initial part; the initial value of the amplitude of the R-wave peak is equal to the initial value of the amplitude threshold of the R-wave starting point. Meanwhile, for T-wave detection: the initial value of the amplitude threshold of the T wave starting point is equal to the sum of a fourth preset proportion of a target difference value and the minimum amplitude of the starting part, wherein the target difference value is the difference value between the initial value of the amplitude threshold of the R wave starting point and the minimum amplitude; the updated amplitude threshold of the T-wave start point is equal to a fifth preset ratio of a target sum value, which is the sum of the determined amplitude threshold of the latest T-wave start point and the determined amplitude of the latest T-wave peak.

In some embodiments, the first preset ratio is 1/3, the second preset ratio is 1/2, the third preset ratio is 1/2, the fourth preset ratio is 3/5, the fifth preset ratio is 1/4, and the second preset multiple is equal to 0.1.

For example only, the initialization of the amplitude threshold for the R-wave starting point may be represented as follows:

R_amplitude_threshold＝max_value/3 (2)

where r_amplitude_threshold represents the amplitude threshold of the R wave starting point and max_value represents the maximum amplitude of the data point of the first 2 s. It should be appreciated that the duration of the initial portion for threshold initialization may also be other values, e.g., 2.5s, 3s, 3.5s, 4s, etc.

The initialization of the slope threshold for the R-wave onset can be expressed as follows:

R_slope_threshold＝max_slope/2 (3)

where r_slope_threshold represents the slope threshold of the R wave starting point and max_slope represents the maximum slope of the data point of the previous 2 s.

The initialization of the noise peak can be expressed as follows:

noise_amplitude＝0.5*sum_value/N (4)

where noise_amplitude represents the amplitude of the noise peak, sum_value represents the sum of the amplitudes of the data points of the previous 2s, and N represents the number of data points of the previous 2 s.

The initialization of the R-wave peak can be expressed as follows:

R_peak_amplitude＝R_amplitude_threshold (5)

where r_peak_amplitude represents the amplitude of the R wave peak.

The initialization of the amplitude threshold for the T-wave initiation point can be expressed as follows:

T_amplitude_threshold＝(R_amplitude_threshold-min_value)*0.6+min_value (6)

where t_amplitude_threshold represents the amplitude threshold of the T wave starting point, and min_value represents the minimum amplitude of the data point of the first 2 s.

The update of the amplitude threshold of the T-wave start point can be expressed as follows:

T_amplitude_threshold＝0.25*(T_tmp+T_amplitude_threshold) (7)

where t_tmp represents the amplitude of the T wave peak.

The update of the slope threshold for the T-wave onset can be expressed as follows:

T_slope_threshold＝0.1*R_slope_threshold (8)

where t_slope_threshold represents the slope threshold of the T wave starting point.

In this specification, for example, a five-point differential method may be used as a method for calculating a slope in the process of initializing a threshold and judging conditions, and the method for calculating a slope may be expressed as follows:

slope(n)＝-2*ecg(n-2)-ecg(n-1)+ecg(n+1)+2*ecg(n+2) (9)

where, ecg (n) represents the amplitude (e.g., voltage value) of the nth data point in the target electrocardiograph signal, and slope (n) represents the slope at the nth data point.

For a specific detection procedure of the T wave, reference may be made to fig. 8 and the description thereof.

Fig. 4 is an exemplary flow chart of an R-wave detection method according to some embodiments of the present description.

As shown in fig. 4, after acquiring the initial electrocardiographic signal, the signal acquisition module 210 filters the initial electrocardiographic signal. Further, the waveform detection module 220 sequentially determines whether the filtered data points reach an amplitude threshold for the R-wave onset. If the amplitudes of two consecutive data points reach the amplitude threshold of the R-wave onset, the waveform detection module 220 derives the slope at these two data points by differential derivation. If any of the pair of data points does not reach the amplitude threshold for the R-wave onset, the waveform detection module 220 continues to determine if the next pair of data points all reach the amplitude threshold for the R-wave onset. If the slope at both data points reaches the slope threshold for the R-wave onset, the waveform detection module 220 determines the latter of the two data points as the R-wave onset. If the slope at any one of the pair of data points does not reach the slope threshold for the R-wave onset, the waveform detection module 220 continues to determine if the next pair of data points all reach the amplitude threshold for the R-wave onset. The signal acquisition module 210 may continue to determine the R-wave peak for the same cardiac cycle every time an R-wave start point is determined. For each R-wave peak determined, the signal acquisition module 210 may update the amplitude threshold and the slope threshold of the R-wave onset to determine the R-wave onset in the next cardiac cycle. In this manner, the signal acquisition module 210 may detect R-waves over multiple cardiac cycles.

More details about R-wave detection (e.g., threshold initialization, determination of R-wave peaks, etc.) can be found elsewhere in this specification.

EDG data (i.e., electrocardiosignals) of the MIT/BIH database are verified by adopting the R wave detection method. FIG. 5 shows the real-time detection result of R-wave obtained by the method under the condition of normal heart rate, wherein the data points corresponding to the symbols are R-wave peaks and the symbols areCorresponding toThe data points are R-wave starting points. Figure 6 shows the calculation of the R-R interval (interval) for a normal heart rate situation. As can be seen from fig. 6, the method has high accuracy for real-time detection of the R wave under the normal heart rate condition, and the time interval between the starting point of the R wave and the peak of the R wave is shorter, so that the calculation amount of differential derivation is reduced. Fig. 7 shows the R-wave real-time detection results obtained using this method in the case of arrhythmia. From fig. 7, it can be seen that the method can effectively avoid false detection and missing detection of the R wave by limiting the amplitude of the R wave starting point and the time interval between adjacent R wave peaks, and has higher accuracy and efficiency.

Fig. 8 is an exemplary flow chart of a method of T-wave detection according to some embodiments of the present description.

As shown in fig. 8, after acquiring the initial electrocardiographic signal, the signal acquisition module 210 filters the initial electrocardiographic signal. Then, the waveform detection module 220 starts to detect R-waves. If an R-wave is detected (i.e., an R-wave onset and an R-wave peak are determined), the waveform detection module 220 updates the amplitude threshold and the slope threshold of the R-wave onset. If no R wave is detected, the R wave is continuously detected. After updating the slope threshold of the R-wave start point, the waveform detection module 220 correspondingly updates the slope threshold of the T-wave start point. Further, the waveform detection module 220 sequentially determines whether the data point is within the T-wave effective range and the amplitude reaches the threshold, wherein the two end points of the T-wave effective range are the second duration threshold and the third duration threshold (e.g., the T-wave effective range is 0.04 to 05 seconds), and whether the data point is within the T-wave effective range, i.e., the time interval from the data point to the determined latest R-wave peak is within the range. If two consecutive data points are within the effective range of the T-wave and the amplitude reaches the amplitude threshold, the waveform detection module 220 will derive the slope at these two data points by derivative. If any of the pair of data points is no longer within the T-wave effective range or the amplitude does not reach the amplitude threshold, the waveform detection module 220 continues to determine if the next pair of data points are all within the T-wave effective range and the amplitude reaches the amplitude threshold. If the slope at both data points reaches the slope threshold for the T-wave onset, the waveform detection module 220 determines the latter of the two data points as the T-wave onset. If the slope at any one of the pair of data points does not reach the slope threshold for the T-wave onset point, the waveform detection module 220 continues to determine if the next pair of data points are all within the T-wave effective range and the amplitudes all reach the amplitude threshold. The signal acquisition module 210 may continue to determine the T-wave peak for the same cardiac cycle every time a T-wave start point is determined. For each T-wave peak determined, the signal acquisition module 210 may update the amplitude threshold of the T-wave onset to determine the T-wave onset in the next cardiac cycle. In this manner, the signal acquisition module 210 may detect T waves over multiple cardiac cycles.

More details about T-wave detection (e.g., threshold initialization, determination of T-wave peaks, etc.) can be found elsewhere in this specification.

And verifying the electrocardio data of the MIT/BIH database by adopting the T wave detection method. Fig. 9 shows the T-wave real-time detection result obtained by the method under the normal heart rate condition. Wherein, the data point corresponding to the sign is R wave crest, the data point corresponding to the sign is X wave crest, the sign is T wave crestThe corresponding data point is the T-wave starting point. From fig. 9, it can be seen that the accuracy of the algorithm for detecting the T wave in real time based on the determined R wave peak position is high, the time interval from the start point of the T wave to the peak of the T wave is short, and the calculation amount of differential derivation is reduced. The method can effectively avoid false detection and missed detection of the T wave by limiting the time interval from the T wave to the R wave crest and the amplitude of the T wave starting point. By combining the R wave detection method, a real-time wave detection method with higher accuracy and efficiency is provided.

The methods of detecting characteristic waves in electrocardiographic signals provided herein may be used to improve or boost various types of medical devices, including but not limited to Electrocardiogram (ECG) machines, imaging devices (e.g., cardiac MR devices, coronary CT devices, ultrasound imaging devices), wearable medical devices. The processing device performing the method (flow 300) may be integrated with or connected to the medical device.

It should be noted that, although the present description mainly uses the detection of R-waves and T-waves as an example, the principles of the related embodiments are also applicable to the detection of other characteristic waves (such as P-waves, Q-waves, S-waves) having the same characteristics (e.g., both of rising edges and falling edges).

In the technologies of magnetic resonance, CT, ultrasound and the like, an electrocardio synchronization technology can be adopted when the heart is imaged, and the heart is realized by placing an electrocardio gating device. Since motion of the heart can cause artifacts, reducing the quality and accuracy of the imaging, it is desirable to provide a sufficiently high temporal resolution and "freeze" the motion of the heart. The heart is in a relatively static state in each cardiac cycle and appears in the end diastole and the end systole of the ventricle, and the imaging effect of the heart in the two states is good, so that the heart structure in the two states can be clearly presented. Thus, the imaging control module 230 may control the imaging device to acquire an image of the heart at end diastole and/or an image of the heart at end systole. In each cardiac cycle, end diastole corresponds to the R-wave peak and end systole corresponds to the T-wave end point, these two data points can be used as trigger (trigger) points for electrocardiographic gating.

In some embodiments, the imaging control module 230 controls the imaging device to acquire a frame of image of the heart when determining the R-wave peak or the T-wave end point, wherein the T-wave end point is determined based on the peak of the same T-wave. At this time, as long as the determination timing of the R-wave peak or the T-wave end point is sufficiently close to the arrival timing of the R-wave peak or the T-wave end point, it can be approximately considered that the imaging apparatus can acquire one frame of image of the heart at the arrival timing of the R-wave peak or the T-wave end point. That is, real-time detection of the R-wave peak or T-wave end point facilitates immediate acquisition of cardiac images at a set trigger point.

For example only, after determining the peak of the T-wave, the imaging control module 230 may determine the endpoint of the same T-wave by sequentially determining the trend of the amplitude change for a subsequent plurality of pairs of data points. When the magnitude of the latter in a certain pair of data points is greater than the magnitude of the former, the imaging control module 230 may determine the former as a T-wave end point.

In some embodiments, the imaging control module 230 controls the imaging device to acquire a frame of image of the heart at the arrival time of the T-wave end point. Wherein the arrival time of the T wave end point is predetermined based on the arrival time of the R wave peak in the same cardiac cycle. This electrocardiographic gating approach belongs to prospective gating. For example only, the imaging control module 230 may take 30% to 35% of the average R-wave interval (i.e., the average R-R interval) as the time interval between the R-wave peak and the T-wave end point in the same cardiac cycle, considering that the waveform of the T-wave is relatively smooth and that the T-wave may appear inverted or unclear in the electrocardiogram. That is, the imaging control module 230 may delay the arrival time of the R wave peak determined in real time by 30% -35% of the average R-R interval to obtain the arrival time of the T wave end point in the same cardiac cycle.

In some embodiments, the image acquisition module 240 acquires a sequence of images of the heart, the sequence of images comprising a plurality of frames of images. Further, the marking module 250 marks images corresponding to the arrival times of the R-wave peaks and/or T-wave end points in the image sequence, wherein the T-wave end points are determined based on the peaks of the same T-wave. This electrocardiographic gating approach belongs to retrospective gating. The marked heart image can be found by review. For more details on determining the T-wave end point based on the T-wave peak, reference may be made to the foregoing embodiments.

It should be noted that the above description of the flow is only for the purpose of illustration and description, and does not limit the application scope of the present specification. Various modifications and changes to the flow may be made by those skilled in the art under the guidance of this specification. However, such modifications and variations are still within the scope of the present description.

Possible benefits of embodiments of the present description include, but are not limited to: (1) By setting proper threshold conditions (defined by an amplitude threshold, a slope threshold and a time interval threshold), real-time detection of target characteristic waves (such as a starting point and a characteristic peak) can be realized, and false detection and missing detection of the target characteristic waves are effectively avoided; (2) The detection method mainly relates to threshold judgment, is simple to realize, has high processing speed, and is suitable for accurate analysis of a real-time electrocardiogram; (3) Based on the determined specific data points (such as R wave crest and T wave end point), the imaging device is controlled to acquire two relatively static cardiac images or mark the images in the two states in an image sequence of the heart, so that the heart structure in the two states can be clearly presented. It should be noted that, the advantages that may be generated by different embodiments may be different, and in different embodiments, the advantages that may be generated may be any one or a combination of several of the above, or any other possible advantages that may be obtained.

While the basic concepts have been described above, it will be apparent to those skilled in the art that the foregoing detailed disclosure is by way of example only and is not intended to be limiting of the embodiments of the present disclosure. Although not explicitly described herein, various modifications, improvements, and adaptations to the embodiments of the present disclosure may occur to one skilled in the art. Such modifications, improvements, and modifications are suggested in the present description examples, and therefore, are intended to fall within the spirit and scope of the example embodiments of this description.

Meanwhile, the specification uses specific words to describe the embodiments of the specification. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means that a particular feature, structure, or characteristic is associated with at least one embodiment of the present description. Thus, it should be emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various positions in this specification are not necessarily referring to the same embodiment. Furthermore, certain features, structures, or characteristics of one or more embodiments of the present description may be combined as suitable.

Furthermore, those skilled in the art will appreciate that aspects of the embodiments of the specification can be illustrated and described in terms of several patentable categories or conditions, including any novel and useful processes, machines, products, or compositions of matter, or any novel and useful improvements thereof. Accordingly, aspects of the embodiments of this specification may be performed entirely by hardware, entirely by software (including firmware, resident software, micro-code, etc.) or by a combination of hardware and software. The above hardware or software may be referred to as a "data block," module, "" engine, "" unit, "" component, "or" system. Furthermore, aspects of embodiments of the present description may take the form of a computer product, including computer-readable program code, embodied in one or more computer-readable media.

The computer storage medium may contain a propagated data signal with the computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take on a variety of forms, including electro-magnetic, optical, etc., or any suitable combination thereof. A computer storage medium may be any computer readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code located on a computer storage medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or the like, or a combination of any of the foregoing.

Computer program code necessary for operation of portions of embodiments of the present description may be written in any one or more programming languages, including an object oriented programming language such as Java, scala, smalltalk, eiffel, JADE, emerald, C ++, c#, vb net, python and the like, a conventional programming language such as C language, visualBasic, fortran2003, perl, COBOL2002, PHP, ABAP, dynamic programming languages such as Python, ruby and Groovy, or other programming languages and the like. The program code may execute entirely on the user's computer or as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or processing device. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or the use of services such as software as a service (SaaS) in a cloud computing environment.

Furthermore, the order in which the elements and sequences are presented in the examples, the use of numerical letters, or other designations are used, unless specifically indicated in the claims, is not intended to limit the order in which the steps of the examples and methods are presented. While certain presently useful inventive embodiments have been discussed in the foregoing disclosure, by way of various examples, it is to be understood that such details are merely illustrative and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements included within the spirit and scope of the embodiments of the present disclosure. For example, while the system components described above may be implemented by hardware devices, they may also be implemented solely by software solutions, such as installing the described system on an existing processing device or mobile device.

Similarly, it should be noted that in order to simplify the description of embodiments disclosed herein and thereby facilitate an understanding of one or more inventive embodiments, various features are sometimes grouped together in a single embodiment, figure, or description thereof. This method of disclosure, however, is not intended to imply that more features than are required by the embodiments of the present disclosure. Indeed, less than all of the features of a single embodiment disclosed above.

Each patent, patent application publication, and other material, such as articles, books, specifications, publications, documents, etc., referred to in this specification is incorporated herein by reference in its entirety. Except for application history files that are inconsistent or conflicting with the disclosure of this specification, files that are limiting to the broadest scope of the claims of the present application (currently or later in the application) are also excluded. It is noted that, if the description, definition and/or use of a term in an attached material in this specification does not conform to or conflict with what is described in this specification, the description, definition and/or use of the term in this specification controls.

Finally, it should be understood that the embodiments described in this specification are merely illustrative of the principles of the embodiments of this specification. Other variations are also possible within the scope of the embodiments of the present description. Thus, by way of example, and not limitation, alternative configurations of embodiments of the present specification may be considered as consistent with the teachings of the present specification. Accordingly, the embodiments of the present specification are not limited to only the embodiments explicitly described and depicted in the present specification.

Claims

1. A method of detecting a characteristic wave in an electrocardiographic signal, comprising:

Acquiring a target electrocardiosignal, wherein the target electrocardiosignal comprises a plurality of data points;

forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point;

continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point.

2. The method of claim 1, wherein in determining whether a data point satisfies the first threshold condition, determining whether a magnitude of the data point satisfies the first threshold condition is performed first, and determining whether a slope of the data point satisfies the first threshold condition when the magnitude of the data point satisfies the first threshold condition.

3. The method of claim 2, wherein the target feature wave comprises an R wave;

The first threshold condition of the R-wave includes: the amplitude of the data point and the last data point reach the amplitude threshold value of the R wave starting point, and the slope of the data point and the last data point reach the slope threshold value of the R wave starting point;

the second threshold condition of the R wave includes: the peak point is behind the R wave starting point, and a first time interval of the peak point is larger than or equal to a first time length threshold value and smaller than or equal to a first preset multiple of an average R wave interval, wherein the first time interval is a time interval from the peak point to a determined latest R wave crest, and the average R wave interval is an average time interval between all determined adjacent R waves.

4. The method of claim 3, wherein prior to determining the first R-wave initiation point, the method further comprises:

initializing an amplitude threshold of an R wave starting point, a slope threshold of the R wave starting point, an amplitude of a noise peak and an amplitude of an R wave peak based on the starting part of the target electrocardiosignal;

before determining the next R-wave starting point, the method further comprises:

if there is a peak point where the first time interval is less than or equal to the first time length threshold, determining it as a noise peak;

Updating an amplitude threshold of an R wave starting point based on the determined amplitude of the latest R wave peak and the determined amplitude of the latest noise peak;

updating the slope threshold of the R-wave onset based on the determined magnitude of the most recent R-wave peak and the determined magnitude of the most recent R-wave onset.

5. The method of claim 3, wherein the target feature wave further comprises a T wave;

the first threshold condition of the T wave includes: the time interval from the data point and the last data point to the determined latest R wave crest is larger than or equal to the second time length threshold and smaller than or equal to the third time length threshold, the amplitude of the data point and the last data point reaches the amplitude threshold of the T wave starting point, and the slopes of the data point and the last data point reach the slope threshold of the T wave starting point;

the second threshold condition of the T wave includes: and the second time interval of the peak point is smaller than or equal to the third time length threshold value after the T wave starting point, wherein the second time interval is the time interval from the peak point to the determined latest R wave crest.

6. The method of claim 5, wherein prior to determining the first T-wave initiation point, the method further comprises:

Initializing an amplitude threshold of a T wave starting point based on the starting part of the target electrocardiosignal;

before determining the next T-wave starting point, the method further comprises:

if there is a peak point where the second time interval is greater than or equal to the third duration threshold, determining it as a noise peak; updating the amplitude threshold of the T wave starting point based on the determined amplitude threshold of the latest T wave starting point and the determined amplitude of the latest T wave crest;

before determining the starting point of each T-wave, the method further comprises:

and calculating a second preset multiple of the slope threshold value of the determined latest R wave starting point to obtain the slope threshold value of the T wave starting point.

7. The method of claim 6, wherein an initial value of an amplitude threshold for an R-wave starting point is equal to a first preset proportion of a maximum amplitude of the starting portion; the initial value of the slope threshold of the R wave starting point is equal to a second preset proportion of the maximum slope of the starting part; the initial value of the amplitude of the noise peak is equal to a third preset proportion of the average amplitude of the initial part; the initial value of the amplitude of the R wave crest is equal to the initial value of the amplitude threshold of the R wave starting point;

the initial value of the amplitude threshold of the T wave starting point is equal to the sum of a fourth preset proportion of a target difference value and the minimum amplitude of the starting part, wherein the target difference value is the difference value between the initial value of the amplitude threshold of the R wave starting point and the minimum amplitude; the updated amplitude threshold of the T-wave start point is equal to a fifth preset ratio of a target sum value, which is the sum of the determined amplitude threshold of the latest T-wave start point and the determined amplitude of the latest T-wave peak.

8. An apparatus for detecting a characteristic wave in an electrocardiographic signal, comprising a processor and a storage device for storing instructions which, when executed by the processor, implement a method of detecting a characteristic wave in an electrocardiographic signal as claimed in any one of claims 1 to 7.

9. An imaging control method, characterized by comprising:

forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; in the process of judging whether a data point meets the first threshold condition, judging whether the amplitude of the data point meets the first threshold condition, and judging whether the slope of the data point meets the first threshold condition when the amplitude of the data point meets the first threshold condition;

continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point;

When the peak of the R wave or the end point of the T wave is determined, the imaging device is controlled to acquire a frame of image of the heart, wherein the target characteristic wave comprises the R wave or the T wave, and the end point of the T wave is determined based on the peak of the same T wave.

10. An imaging control method, characterized by comprising:

And controlling the imaging equipment to acquire a frame of image of the heart at the arrival time of the T wave end point, wherein the target characteristic wave comprises an R wave, and the arrival time of the T wave end point is predetermined based on the arrival time of the R wave crest in the same cardiac cycle.

11. An imaging control apparatus comprising a processor and a storage device for storing instructions which, when executed by the processor, implement the imaging control method of claim 9 or 10.

12. An image processing method, comprising:

Continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point; the target characteristic wave comprises an R wave and a T wave, and the wave crest of the target characteristic wave comprises an R wave crest and a T wave crest;

acquiring an image sequence of a heart, the image sequence comprising a plurality of frames of images;

and marking images corresponding to the arrival time of the R wave crest and/or the T wave end point in the image sequence, wherein the T wave end point is determined based on the crest of the same T wave.

13. An image processing apparatus comprising a processor and a storage device for storing instructions which, when executed by the processor, implement the image processing method of claim 12.

14. A system for detecting characteristic waves in an electrocardiosignal, which is characterized by comprising a signal acquisition module and a waveform detection module;

the signal acquisition module is used for acquiring a target electrocardiosignal, and the target electrocardiosignal comprises a plurality of data points;

The waveform detection module is used for: forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point.

15. An imaging control system is characterized by comprising a signal acquisition module, a waveform detection module and an imaging control module;

the waveform detection module is used for: forward detecting along an acquisition time dimension among the plurality of data points to detect a data point satisfying a first threshold condition of a target characteristic wave as a starting point of the target characteristic wave, the first threshold condition being defined based on an amplitude threshold and a slope threshold of the starting point; in the process of judging whether a data point meets the first threshold condition, judging whether the amplitude of the data point meets the first threshold condition, and judging whether the slope of the data point meets the first threshold condition when the amplitude of the data point meets the first threshold condition;

The waveform detection module is further configured to: continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point;

the imaging control module is used for: when the peak of the R wave or the end point of the T wave is determined, the imaging device is controlled to acquire a frame of image of the heart, wherein the target characteristic wave comprises the R wave or the T wave, and the end point of the T wave is determined based on the peak of the same T wave.

16. An imaging control system is characterized by comprising a signal acquisition module, a waveform detection module and an imaging control module;

the imaging control module is used for: and controlling the imaging equipment to acquire a frame of image of the heart at the arrival time of the T wave end point, wherein the target characteristic wave comprises an R wave, and the arrival time of the T wave end point is predetermined based on the arrival time of the R wave crest in the same cardiac cycle.

17. An image processing system is characterized by comprising a signal acquisition module, a waveform detection module, an image acquisition module and a marking module;

the signal acquisition module is used for acquiring a target electrocardiosignal which comprises a plurality of data points acquired in sequence;

The waveform detection module is further configured to: continuing to detect forward along an acquisition time dimension after a start point of the target feature wave to detect a peak point satisfying a second threshold condition of the target feature wave as a peak of the target feature wave, the second threshold condition being defined based on a time interval threshold of the peak to a reference data point; the target characteristic wave comprises an R wave and a T wave, and the wave crest of the target characteristic wave comprises an R wave crest and a T wave crest;

the image acquisition module is used for acquiring an image sequence of the heart, wherein the image sequence comprises a plurality of frames of images;

the marking module is used for marking images corresponding to the arrival time of the R wave crest and/or the T wave end point in the image sequence, wherein the T wave end point is determined based on the crest of the same T wave.