CN117281494B - Method and device for identifying signal characteristic points of arterial blood pressure signals - Google Patents
Method and device for identifying signal characteristic points of arterial blood pressure signals Download PDFInfo
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- 230000004872 arterial blood pressure Effects 0.000 title claims abstract description 58
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000004458 analytical method Methods 0.000 claims abstract description 88
- 230000008859 change Effects 0.000 claims abstract description 73
- 230000036772 blood pressure Effects 0.000 claims abstract description 64
- 238000013507 mapping Methods 0.000 claims abstract description 33
- 210000001765 aortic valve Anatomy 0.000 claims abstract description 30
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
- A61B5/022—Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers
- A61B5/0225—Measuring pressure in heart or blood vessels by applying pressure to close blood vessels, e.g. against the skin; Ophthalmodynamometers the pressure being controlled by electric signals, e.g. derived from Korotkoff sounds
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
- A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
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Abstract
The embodiment of the application provides a method and a device for identifying signal characteristic points of arterial blood pressure signals, and relates to the technical field of medical equipment, wherein the method comprises the following steps: performing global valley analysis and local valley analysis on the analysis signals, determining an intersection between a global valley set and a local valley set obtained by analysis, and determining signal points in the determined intersection as signal points representing aortic valve opening as valve opening points; determining peak points in a first target signal segment between every two adjacent valve opening points in the analysis signal, and mapping the determined peak points to the blood pressure change signal to obtain mapping points of the blood pressure change signal; a signal point characterizing aortic valve closure is determined as a valve closure point based on the amplitude variation characteristics of each signal point within the second target signal segment between every two adjacent mapping points in the blood pressure variation signal. By applying the scheme provided by the embodiment, the accuracy of identifying the signal characteristic points of arterial blood pressure can be improved.
Description
Technical Field
The application relates to the technical field of medical equipment, in particular to a method and a device for identifying signal characteristic points of arterial blood pressure signals.
Background
The arterial blood pressure signal reflects the intra-aortic pressure. The signal characteristic points of the arterial blood pressure signal include an aortic valve opening point and an aortic valve closing point. The aortic valve opens, indicating that the heart is in systole, and the aortic pressure gradually rises; the aortic valve closes, indicating that the heart is in diastole. Based on the aortic valve opening and closing points of the arterial blood pressure signal, the heart state, such as cardiac output, ejection speed, vascular elasticity, etc., can be accurately estimated. Therefore, a signal feature point identification scheme of arterial blood pressure signals is needed.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for identifying signal feature points of an arterial blood pressure signal, so as to accurately identify aortic valve development and closing points of the arterial blood pressure signal. The specific technical scheme is as follows:
in a first aspect, an embodiment of the present application provides a method for identifying signal feature points of an arterial blood pressure signal, where the method includes:
acquiring an arterial blood pressure signal, and determining an analysis signal corresponding to the arterial blood pressure signal and a blood pressure change signal representing the signal change characteristic of the arterial blood pressure signal;
performing global valley analysis and local valley analysis on the analysis signals, determining an intersection between a global valley set and a local valley set obtained by analysis, and determining signal points in the determined intersection as signal points representing aortic valve opening as valve opening points;
determining peak points in a first target signal segment between every two adjacent valve opening points in the analysis signal, and mapping the determined peak points to the blood pressure change signal to obtain mapping points of the blood pressure change signal;
and determining a signal point representing aortic valve closure as a valve closure point based on the amplitude change characteristic of each signal point in the second target signal segment between every two adjacent mapping points in the blood pressure change signal.
In one embodiment of the present application, determining, as the valve closing point, a signal point that characterizes aortic valve closing based on the amplitude variation characteristic of each signal point in the second target signal segment between every two adjacent mapping points in the blood pressure variation signal includes:
determining a signal point which meets a preset condition in a second target signal section between every two adjacent mapping points in the blood pressure change signal as a first signal point, wherein the preset condition is that the slope of a signal wave section where the signal point is positioned is positive and the amplitude is zero;
determining a peak point in each second target signal segment as a second signal point;
and determining a signal point representing aortic valve closure as a valve closure point based on the first signal point and the second signal point corresponding to each second target signal segment.
In an embodiment of the present application, determining, as the valve closing point, a signal point representing aortic valve closing based on the first signal point and the second signal point corresponding to each second target signal segment includes:
for each second target signal segment, a first signal point with a time sequence positioned before a corresponding second signal point in the corresponding first signal points is determined to be used as a valve closing point.
In one embodiment of the present application, the performing global valley analysis and local valley analysis on the resolved signal includes:
performing global index on the analytic signals to obtain a global valley set of the analytic signals;
and determining fourth signal points meeting preset conditions in signal points contained in the analysis signal, and determining a set formed by valley signal points in a third target signal section between every two adjacent fourth signal points in the analysis signal as a local valley set, wherein the preset conditions are that the slope of a signal wave band where the signal points are located is positive and the amplitude is zero.
In a second aspect, an embodiment of the present application provides a signal feature point identifying device for an arterial blood pressure signal, where the device includes:
the signal acquisition module is used for acquiring an arterial blood pressure signal, determining an analysis signal corresponding to the arterial blood pressure signal and a blood pressure change signal representing the signal change characteristic of the arterial blood pressure signal;
the first signal point determining module is used for carrying out global valley analysis and local valley analysis on the analysis signals, determining an intersection between a global valley set and a local valley set obtained by analysis, and determining signal points in the determined intersection as signal points representing aortic valve opening as valve opening points;
the signal point mapping module is used for determining peak points in a first target signal segment between every two adjacent valve opening points in the analysis signal, mapping the determined peak points to the blood pressure change signal and obtaining mapping points of the blood pressure change signal;
and the second signal point determining module is used for determining a signal point representing aortic valve closure as a valve closing point based on the amplitude change characteristic of each signal point in a second target signal segment between every two adjacent mapping points in the blood pressure change signal.
In an embodiment of the present application, the second signal point determining module includes:
a first signal point determining submodule, configured to determine a signal point that satisfies a preset condition in a second target signal segment between every two adjacent mapping points in the blood pressure change signal, as a first signal point, where the preset condition is that a slope of a signal band where the signal point is located is positive and an amplitude is zero;
the second signal point determining submodule is used for determining a peak point in each second target signal segment to serve as a second signal point;
and the third signal point determining submodule is used for determining a signal point representing aortic valve closure as a valve closing point based on the first signal point and the second signal point corresponding to each second target signal segment.
In an embodiment of the present application, the third signal point determining submodule is specifically configured to determine, for each second target signal segment, a first signal point, of the corresponding first signal points, whose timing sequence is located before the corresponding second signal point, as the valve closing point.
In one embodiment of the present application, the first signal point determining module is specifically configured to perform global indexing on the resolved signal to obtain a global valley set of the resolved signal; and determining fourth signal points meeting preset conditions in signal points contained in the analysis signal, and determining a set formed by valley signal points in a third target signal section between every two adjacent fourth signal points in the analysis signal as a local valley set, wherein the preset conditions are that the slope of a signal wave band where the signal points are located is positive and the amplitude is zero.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and a processor, configured to implement the method steps described in the first aspect when executing the program stored in the memory.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, in which a computer program is stored, which when executed by a processor, implements the method steps of the first aspect.
From the above, by applying the scheme provided by the embodiment of the application, on one hand, because the signal points in the intersection of the two valley sets are determined to be valve opening points, and because the global valley set has a wide range and the accuracy of the local valley set is higher, the accuracy of integrating the signal points in the intersection determined by the two valley sets to be valve opening points is higher. On the other hand, since the amplitude change characteristic of the signal point in the blood pressure change signal is affected by valve closure, the valve closure point can be accurately determined based on the amplitude change characteristic of the signal point in the blood pressure change signal. In combination with the two aspects, the determined valve opening point can accurately represent the valve opening condition, and the valve closing point can accurately represent the valve closing condition, so that the recognition accuracy of the signal characteristic points of arterial blood pressure is improved.
Of course, not all of the above-described advantages need be achieved simultaneously in practicing any one of the products or methods of the present application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will briefly introduce the drawings that are required to be used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other embodiments may also be obtained according to these drawings to those skilled in the art.
Fig. 1 is a schematic flow chart of a method for identifying signal feature points of an arterial blood pressure signal according to an embodiment of the present application;
FIG. 2a is a schematic diagram of an arterial blood pressure signal according to an embodiment of the present application;
FIG. 2b is a schematic diagram of a blood pressure variation signal according to an embodiment of the present disclosure;
FIG. 2c is a schematic diagram of an analytic signal according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a signal feature point recognition device for arterial blood pressure signals according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. Based on the embodiments herein, a person of ordinary skill in the art would be able to obtain all other embodiments based on the disclosure herein, which are within the scope of the disclosure herein.
Referring to fig. 1, fig. 1 is a flowchart of a method for identifying signal feature points of an arterial blood pressure signal according to an embodiment of the present application, where the method includes the following steps S101 to S104.
Step S101: an arterial blood pressure signal is acquired, and an analysis signal corresponding to the arterial blood pressure signal and a blood pressure change signal representing the signal change characteristics of the arterial blood pressure signal are determined.
The analysis signal is used for representing the signal energy distribution situation of the arterial blood pressure signal, and the blood pressure change signal is used for representing the signal change characteristic of the arterial blood pressure signal.
Fig. 2a, 2b and 2c are schematic signal waveforms of an arterial blood pressure signal, a blood pressure change signal and an analysis signal, respectively.
The arterial blood pressure signal can be acquired in a non-invasive manner or in a medical database.
The analysis signal and the blood pressure change signal may be converted from the arterial blood pressure signal in advance, the analysis signal and the blood pressure change signal are stored in the memory, and the controller may read the analysis signal and the blood pressure change signal corresponding to the arterial blood pressure signal from the memory. The controller may also perform signal conversion on the arterial blood pressure signal in real time after the arterial blood pressure signal is acquired.
Both of the above methods involve the conversion of arterial blood pressure signals. When the signal conversion is carried out, the first-order differential operation can be carried out on the arterial blood pressure signal to obtain a blood pressure change signal; and performing secondary Hilbert transformation on the blood pressure change signal to obtain an analysis signal corresponding to the arterial blood pressure signal.
Step S102: and carrying out global valley analysis and local valley analysis on the analysis signals, determining an intersection between the global valley set and the local valley set obtained by analysis, and determining signal points in the determined intersection as signal points representing aortic valve opening as valve opening points.
The global valley analysis refers to a process of extracting a valley of an analysis signal from a signal overall angle analysis, and the local valley analysis refers to a process of extracting a valley of an analysis signal from a signal local angle analysis. The global valley analysis is from the global angle, the containing range is wider, the local valley analysis is from the local angle, the pertinence is higher, and the accuracy is higher.
The global valley sets contain the various valleys of the analytic signals obtained through the global valley analysis, and the local valley sets contain the various valleys of the analytic signals obtained through the local valley analysis.
The signal points in the intersection of the two valley sets are determined to be valve opening points, and the accuracy of the signal points in the intersection determined by integrating the two valley sets is high because the global valley sets are wide in range and the local valley sets are high in accuracy.
When the analysis signal is subjected to global valley analysis, the analysis signal can be subjected to global index to obtain the global valley of the analysis signal. The global index is to determine the amplitude of each signal point in the analysis signal, determine the valley value in the preset step length through the amplitude comparison in the preset step length, and determine the set formed by the determined valley values as a global valley value set.
When the analysis signal is subjected to local valley analysis, fourth signal points meeting preset conditions in signal points contained in the analysis signal can be determined, and a set formed by valley signal points in a third target signal segment between every two adjacent fourth signal points in the analysis signal is determined as a local valley set.
The preset condition is that the slope of the signal wave band where the signal point is located is positive and the amplitude is zero. When determining the fourth signal point, the analysis signal may be derived, a signal band with positive slope may be determined, and a signal point with zero amplitude in the signal band may be determined as the fourth signal point. The fourth signal point may also be referred to as a zero crossing.
And dividing the analysis signal by taking the fourth signal point as a division point. And determining signal points with the smallest amplitude in the third target signal section between every two adjacent fourth signal points, namely valley signal points, wherein a set formed by the valley signal points is a local valley set.
Because the analysis signals are subjected to global index, the obtained global valley value set can more fully cover the global valley value signal points of the analysis signals; meanwhile, the analysis signal is divided by utilizing the fourth signal points, and each third target signal segment is extracted by the targeted valley signal points, so that the obtained local valley set has higher pertinence and higher accuracy.
Step S103: and determining peak points in a first target signal segment between every two adjacent valve opening points in the analysis signals, and mapping the determined peak points to the blood pressure change signals to obtain mapping points of the blood pressure change signals.
Specifically, the amplitude of each signal point in the first target signal segment may be compared, and the peak point is determined based on the signal point with the largest amplitude. The amplitude values of the signal points in the preset range in the first target signal segment can be compared, the signal point with the largest amplitude value in each preset range is determined to be a peak point, in this case, a plurality of peak points are obtained, and the last peak point is mapped to the blood pressure change signal to obtain the mapping point of the blood pressure change signal.
Step S104: a signal point characterizing aortic valve closure is determined as a valve closure point based on the amplitude variation characteristics of each signal point within the second target signal segment between every two adjacent mapping points in the blood pressure variation signal.
The amplitude change characteristics include maximum amplitude, minimum amplitude, amplitude change rate, and the like.
When determining the valve closing point, in one implementation manner, signal points meeting preset conditions in second target signal segments between every two adjacent mapping points in the blood pressure change signal can be determined and used as first signal points, and peak points in each second target signal segment are determined and used as second signal points; and determining a signal point representing aortic valve closure as a valve closure point based on the first signal point and the second signal point corresponding to each second target signal segment.
The preset condition is that the slope of a signal wave band where the signal point is located is positive and the amplitude is zero.
Each mapping point divides the blood pressure change signal, the slope of each continuous wave band in the second target signal section between every two adjacent mapping points is determined, and the signal point with the amplitude of zero in the wave band with the positive slope is determined as the first signal point. Thus, a plurality of first signal points, which may also be referred to as zero crossings, exist in each second target signal segment.
And comparing the amplitude of the signal points in each second target signal segment, and determining the signal point with the largest amplitude as the second signal point.
In determining the valve closing point, in one embodiment, for each second target signal segment, a first signal point of the corresponding first signal points, whose timing is located before the corresponding second signal point, may be determined as the valve closing point. Since the first signal point with the time sequence before the second signal point is determined as the valve closing point, and through a lot of researches by the inventor, the valve closing point is located before the peak value of the blood pressure change signal and is related to the zero crossing point of the blood pressure change signal, the first signal point is determined as the valve closing point, so that the accurate positioning of the valve closing point is realized.
In another embodiment, the first signal point and the second signal point may be input into a pre-trained closing point prediction model, so as to obtain a signal point output by the closing point prediction model as a valve closing point. The closing point prediction model is a model for predicting a signal point of aortic valve closing using a neural network learning algorithm.
The valve closing point is determined through the first signal point and the second signal point, wherein the first signal point is a zero crossing point in the blood pressure change signal, the second signal point is a peak value in the blood pressure change signal, and the valve closing point is related to the zero crossing point and the peak value in the blood pressure change signal, so that the determined signal point is the valve closing point with higher accuracy.
From the above, by applying the scheme provided by the embodiment, on one hand, since the signal points in the intersection of the two valley sets are determined to be the valve opening points, and since the global valley set has a wide range and the accuracy of the local valley set is higher, the accuracy of integrating the signal points in the intersection determined by the two valley sets to be the valve opening points is higher. On the other hand, since the amplitude change characteristic of the signal point in the blood pressure change signal is affected by valve closure, the valve closure point can be accurately determined based on the amplitude change characteristic of the signal point in the blood pressure change signal. In combination with the two aspects, the determined valve opening point can accurately represent the valve opening condition, and the valve closing point can accurately represent the valve closing condition, so that the recognition accuracy of the signal characteristic points of arterial blood pressure is improved.
Corresponding to the above method for identifying signal feature points of arterial blood pressure signals, the embodiment of the application also provides a device for identifying signal feature points of arterial blood pressure signals.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a signal feature point identifying device for arterial blood pressure signals according to an embodiment of the present application, where the device includes 301-304.
The signal acquisition module 301 is configured to acquire an arterial blood pressure signal, and determine an analysis signal corresponding to the arterial blood pressure signal and a blood pressure variation signal that characterizes a signal variation characteristic of the arterial blood pressure signal;
a first signal point determining module 302, configured to perform global valley analysis and local valley analysis on the analysis signal, determine an intersection between the global valley set and the local valley set obtained by the analysis, and determine a signal point in the determined intersection as a signal point representing aortic valve opening as a valve opening point;
a signal point mapping module 303, configured to determine a peak point in a first target signal segment between every two adjacent valve open points in the analysis signal, map the determined peak point to the blood pressure change signal, and obtain a mapped point of the blood pressure change signal;
a second signal point determining module 304, configured to determine a signal point representing aortic valve closure as a valve closure point based on an amplitude variation characteristic of each signal point in a second target signal segment between every two adjacent mapping points in the blood pressure variation signal.
From the above, by applying the scheme provided by the embodiment, on one hand, since the signal points in the intersection of the two valley sets are determined to be the valve opening points, and since the global valley set has a wide range and the accuracy of the local valley set is higher, the accuracy of integrating the signal points in the intersection determined by the two valley sets to be the valve opening points is higher. On the other hand, since the amplitude change characteristic of the signal point in the blood pressure change signal is affected by valve closure, the valve closure point can be accurately determined based on the amplitude change characteristic of the signal point in the blood pressure change signal. In combination with the two aspects, the determined valve opening point can accurately represent the valve opening condition, and the valve closing point can accurately represent the valve closing condition, so that the recognition accuracy of the signal characteristic points of arterial blood pressure is improved.
In one embodiment of the present application, the second signal point determining module 304 includes:
a first signal point determining submodule, configured to determine a signal point that satisfies a preset condition in a second target signal segment between every two adjacent mapping points in the blood pressure change signal, as a first signal point, where the preset condition is that a slope of a signal band where the signal point is located is positive and an amplitude is zero;
the second signal point determining submodule is used for determining a peak point in each second target signal segment to serve as a second signal point;
and the third signal point determining submodule is used for determining a signal point representing aortic valve closure as a valve closing point based on the first signal point and the second signal point corresponding to each second target signal segment.
The valve closing point is determined through the first signal point and the second signal point, wherein the first signal point is a zero crossing point in the blood pressure change signal, the second signal point is a peak value in the blood pressure change signal, and the valve closing point is related to the zero crossing point and the peak value in the blood pressure change signal, so that the determined signal point is the valve closing point with higher accuracy.
In an embodiment of the present application, the third signal point determining submodule is specifically configured to determine, for each second target signal segment, a first signal point, of the corresponding first signal points, whose timing sequence is located before the corresponding second signal point, as the valve closing point.
Since the first signal point with the time sequence before the second signal point is determined as the valve closing point, and through a lot of researches by the inventor, the valve closing point is located before the peak value of the blood pressure change signal and is related to the zero crossing point of the blood pressure change signal, the first signal point is determined as the valve closing point, so that the accurate positioning of the valve closing point is realized.
In one embodiment of the present application, the first signal point determining module is specifically configured to perform global indexing on the resolved signal to obtain a global valley set of the resolved signal; and determining fourth signal points meeting preset conditions in signal points contained in the analysis signal, and determining a set formed by valley signal points in a third target signal section between every two adjacent fourth signal points in the analysis signal as a local valley set, wherein the preset conditions are that the slope of a signal wave band where the signal points are located is positive and the amplitude is zero.
Because the analysis signals are subjected to global index, the obtained global valley value set can more fully cover the global valley value signal points of the analysis signals; meanwhile, the analysis signal is divided by utilizing the fourth signal points, and each third target signal segment is extracted by the targeted valley signal points, so that the obtained local valley set has higher pertinence and higher accuracy.
Corresponding to the above method for identifying the signal feature points of the arterial blood pressure signal, the embodiment of the application also provides an electronic device.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present application, including a processor 401, a communication interface 402, a memory 403, and a communication bus 404, where the processor 401, the communication interface 402, and the memory 403 complete communication with each other through the communication bus 404,
a memory 403 for storing a computer program;
the processor 401 is configured to implement the method for identifying signal feature points of arterial blood pressure signals provided in the embodiment of the present application when executing the program stored in the memory 403.
The communication bus mentioned above for the electronic devices may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The communication interface is used for communication between the electronic device and other devices.
The Memory may include random access Memory (Random Access Memory, RAM) or may include Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
In still another embodiment provided in the present application, there is further provided a computer readable storage medium, in which a computer program is stored, the computer program implementing the signal feature point identification method for arterial blood pressure signals provided in the embodiments of the present application when executed by a processor.
In yet another embodiment provided herein, a computer program product containing instructions is also provided, which when run on a computer, causes the computer to implement the signal feature point identification method for arterial blood pressure signals provided by the embodiments of the present application.
From the above, by applying the scheme provided by the embodiment, the physiological performance parameters of the heart are determined based on the signal parameter information of the valve opening point and the signal parameter information of the valve closing point, and then the control parameters of the ventricular assist device are determined based on the physiological performance parameters.
On the one hand, the signal points in the intersection of the two valley sets are determined to be valve opening points, and on the other hand, the signal points in the intersection determined by integrating the two valley sets are determined to be valve opening points with high accuracy because the global valley sets are wide in range and the local valley sets are high in accuracy. On the other hand, since the amplitude change characteristic of the signal point in the blood pressure change signal is affected by valve closure, the valve closure point can be accurately determined based on the amplitude change characteristic of the signal point in the blood pressure change signal. In combination with the two aspects, the determined valve opening point can accurately represent the valve opening condition, and the valve closing point can accurately represent the valve closing condition.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains an integration of one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), etc.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
In this specification, each embodiment is described in a related manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for apparatus, electronic devices, computer readable storage medium embodiments, since they are substantially similar to method embodiments, the description is relatively simple, and relevant references are made to the partial description of method embodiments.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the present application. Any modifications, equivalent substitutions, improvements, etc. that are within the spirit and principles of the present application are intended to be included within the scope of the present application.
Claims (8)
1. A method for identifying signal feature points of an arterial blood pressure signal, the method comprising:
acquiring an arterial blood pressure signal, and determining an analysis signal corresponding to the arterial blood pressure signal and a blood pressure change signal representing the signal change characteristic of the arterial blood pressure signal;
performing global valley analysis and local valley analysis on the analysis signals, determining an intersection between a global valley set and a local valley set obtained by analysis, and determining signal points in the determined intersection as signal points representing aortic valve opening as valve opening points;
determining peak points in a first target signal segment between every two adjacent valve opening points in the analysis signal, and mapping the determined peak points to the blood pressure change signal to obtain mapping points of the blood pressure change signal;
determining a signal point representing aortic valve closure as a valve closure point based on the amplitude variation characteristic of each signal point in a second target signal segment between every two adjacent mapping points in the blood pressure variation signal;
the determining, based on the amplitude variation characteristics of each signal point in the second target signal segment between every two adjacent mapping points in the blood pressure variation signal, a signal point representing aortic valve closure as a valve closure point includes:
determining a signal point which meets a preset condition in a second target signal section between every two adjacent mapping points in the blood pressure change signal as a first signal point, wherein the preset condition is that the slope of a signal wave section where the signal point is positioned is positive and the amplitude is zero;
determining a peak point in each second target signal segment as a second signal point;
and determining a signal point representing aortic valve closure as a valve closure point based on the first signal point and the second signal point corresponding to each second target signal segment.
2. The method of claim 1, wherein determining a signal point indicative of aortic valve closure as a valve closure point based on the first signal point and the second signal point corresponding to each second target signal segment comprises:
for each second target signal segment, a first signal point with a time sequence positioned before a corresponding second signal point in the corresponding first signal points is determined to be used as a valve closing point.
3. The method according to claim 1 or 2, wherein said performing a global valley analysis and a local valley analysis on said resolved signal comprises:
performing global index on the analytic signals to obtain a global valley set of the analytic signals;
and determining fourth signal points meeting preset conditions in signal points contained in the analysis signal, and determining a set formed by valley signal points in a third target signal section between every two adjacent fourth signal points in the analysis signal as a local valley set, wherein the preset conditions are that the slope of a signal wave band where the signal points are located is positive and the amplitude is zero.
4. A signal feature point recognition device for arterial blood pressure signals, the device comprising:
the signal acquisition module is used for acquiring an arterial blood pressure signal, determining an analysis signal corresponding to the arterial blood pressure signal and a blood pressure change signal representing the signal change characteristic of the arterial blood pressure signal;
the first signal point determining module is used for carrying out global valley analysis and local valley analysis on the analysis signals, determining an intersection between a global valley set and a local valley set obtained by analysis, and determining signal points in the determined intersection as signal points representing aortic valve opening as valve opening points;
the signal point mapping module is used for determining peak points in a first target signal segment between every two adjacent valve opening points in the analysis signal, mapping the determined peak points to the blood pressure change signal and obtaining mapping points of the blood pressure change signal;
a second signal point determining module, configured to determine a signal point representing aortic valve closure as a valve closure point based on an amplitude variation characteristic of each signal point in a second target signal segment between every two adjacent mapping points in the blood pressure variation signal;
the second signal point determining module includes:
a first signal point determining submodule, configured to determine a signal point that satisfies a preset condition in a second target signal segment between every two adjacent mapping points in the blood pressure change signal, as a first signal point, where the preset condition is that a slope of a signal band where the signal point is located is positive and an amplitude is zero;
the second signal point determining submodule is used for determining a peak point in each second target signal segment to serve as a second signal point;
and the third signal point determining submodule is used for determining a signal point representing aortic valve closure as a valve closing point based on the first signal point and the second signal point corresponding to each second target signal segment.
5. The device of claim 4, wherein the third signal point determination submodule is configured to determine, for each second target signal segment, a first signal point of the corresponding first signal points whose timing is before the corresponding second signal point as a valve closing point.
6. The apparatus according to claim 4 or 5, wherein the first signal point determining module is specifically configured to perform global indexing on the resolved signal to obtain a global valley set of the resolved signal; and determining fourth signal points meeting preset conditions in signal points contained in the analysis signal, and determining a set formed by valley signal points in a third target signal section between every two adjacent fourth signal points in the analysis signal as a local valley set, wherein the preset conditions are that the slope of a signal wave band where the signal points are located is positive and the amplitude is zero.
7. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
a memory for storing a computer program;
a processor for carrying out the method steps of any one of claims 1-3 when executing a program stored on a memory.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program which, when executed by a processor, implements the method steps of any of claims 1-3.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008302127A (en) * | 2007-06-11 | 2008-12-18 | Denso Corp | Blood pressure measuring apparatus, program, and recording medium |
| CN101951831A (en) * | 2007-12-13 | 2011-01-19 | 心动力医疗公司 | Method and apparatus for acquiring and analyzing data relating to a physiological condition of a subject |
| KR20130095862A (en) * | 2012-02-03 | 2013-08-29 | 강원대학교산학협력단 | Estimation scheme of the cardiac output using arterial blood pressure |
| CN108471987A (en) * | 2015-08-28 | 2018-08-31 | 布鲁塞尔大学 | Cardiac monitoring or improvement related with cardiac monitoring |
| CN113966193A (en) * | 2019-06-05 | 2022-01-21 | 奥尔堡大学 | Multi-parameter estimation of cardiopulmonary fitness in a cardiography |
| CN116158748A (en) * | 2022-09-08 | 2023-05-26 | 广东乐心医疗电子股份有限公司 | Method, system and electronic device for determining blood pressure signal envelope curve |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6511438B2 (en) * | 2001-04-03 | 2003-01-28 | Osypka Medical Gmbh | Apparatus and method for determining an approximation of the stroke volume and the cardiac output of the heart |
| US7024244B2 (en) * | 2002-04-22 | 2006-04-04 | Medtronic, Inc. | Estimation of stroke volume cardiac output using an intracardiac pressure sensor |
| US7806830B2 (en) * | 2004-06-16 | 2010-10-05 | Cordeus, Inc. | Apparatus and method for determination of stroke volume using the brachial artery |
| WO2009027522A1 (en) * | 2007-08-30 | 2009-03-05 | Oslo Universitetssykehus Hf | Automated monitoring of myocardial function by ultrasonic transducers positioned on the heart |
| US8690787B2 (en) * | 2009-04-29 | 2014-04-08 | St. Jude Medical Ab | Implantable coronary perfusion monitoring device |
| US10722132B2 (en) * | 2010-12-28 | 2020-07-28 | Sotera Wireless, Inc. | Body-worn system for continuous, noninvasive measurement of cardiac output, stroke volume, cardiac power, and blood pressure |
| CA2871015C (en) * | 2012-04-23 | 2022-10-25 | Turun Yliopisto | Method and apparatus for determining information indicative of cardiac malfunctions and abnormalities |
| EP2712549B1 (en) * | 2012-10-01 | 2015-03-11 | Sorin CRM SAS | Device for assessing temporal ventricular dyssynchrony |
-
2023
- 2023-11-27 CN CN202311590166.9A patent/CN117281494B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008302127A (en) * | 2007-06-11 | 2008-12-18 | Denso Corp | Blood pressure measuring apparatus, program, and recording medium |
| CN101951831A (en) * | 2007-12-13 | 2011-01-19 | 心动力医疗公司 | Method and apparatus for acquiring and analyzing data relating to a physiological condition of a subject |
| KR20130095862A (en) * | 2012-02-03 | 2013-08-29 | 강원대학교산학협력단 | Estimation scheme of the cardiac output using arterial blood pressure |
| CN108471987A (en) * | 2015-08-28 | 2018-08-31 | 布鲁塞尔大学 | Cardiac monitoring or improvement related with cardiac monitoring |
| CN113966193A (en) * | 2019-06-05 | 2022-01-21 | 奥尔堡大学 | Multi-parameter estimation of cardiopulmonary fitness in a cardiography |
| CN116158748A (en) * | 2022-09-08 | 2023-05-26 | 广东乐心医疗电子股份有限公司 | Method, system and electronic device for determining blood pressure signal envelope curve |
Non-Patent Citations (2)
| Title |
|---|
| 基于小波变换过零点表征的脉搏信号分析;白金星;赵子婴;王艳苹;;航天医学与医学工程;20060615(03);全文 * |
| 基于波形特征和小波的脉搏波特征点识别研究;季忠;刘旭;;仪器仪表学报;20160215(02);全文 * |
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