CN116919357A - Pulse wave processing method and device, electronic equipment and medium - Google Patents
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- A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
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- 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
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Abstract
The embodiment of the application provides a pulse wave processing method, a device, electronic equipment and a medium, wherein in the method, acquired pulse wave information is analyzed and processed to determine the waveform characteristics of pulse waves; inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network; according to the pulse condition, the pulse type of the pulse wave is determined. The pulse wave information is analyzed to obtain waveform characteristics, pulse conditions corresponding to the waveform characteristics are determined based on a pulse condition identification network, pulse types of the pulse waves are determined according to the pulse conditions, pulse condition data corresponding to the waveform characteristics are obtained by using an artificial intelligence technology and a big data analysis technology, comparison is carried out not only by relying on manpower or a single index, and the detection result can be improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a pulse wave processing method, apparatus, electronic device, and medium.
Background
The pulse detection is used for checking whether the pulse is normal or not, and the traditional pulse detection mode is mainly that the traditional Chinese medicine senses the pulse fluctuation through fingers and performs pulse analysis, or pulse wave data are acquired through a sensor or a singlechip and then are compared with set indexes to obtain a result of whether the pulse is normal or not.
However, the above-described detection method relies on too simple indicators, which results in inaccurate detection results.
Disclosure of Invention
The embodiment of the application provides a pulse wave processing method, a device, electronic equipment and a medium, which are used for solving the problem that the detection result is inaccurate due to too simple index depending on a pulse detection mode in the prior art.
In a first aspect, an embodiment of the present application provides a pulse wave processing method, including:
transmitting the position information of the robot to a server;
receiving a map updating instruction sent by the server, wherein the map updating instruction comprises a map and a working area corresponding to the position information;
and controlling the robot to update the locally stored map according to the map, and moving to the working area.
Further, the sending the position information of the robot to the server includes:
when the robot has the condition of changing the working place, the robot is controlled to send the position information to the server through the positioning module.
Further, the moving to the working area includes:
and controlling the robot to move to the base station position of the robot in the working area according to the repositioning function.
Further, the method further comprises:
controlling the robot to execute a cleaning task in the working area according to the map, analyzing and processing the acquired pulse wave information, and determining the waveform characteristics of the pulse wave;
inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network;
and determining the pulse type of the pulse wave according to the pulse condition.
Further, the method further comprises:
and acquiring a pulse waveform curve acquired by the finger pulse detector.
Further, the analyzing the obtained pulse wave information, and determining the waveform characteristics of the pulse wave includes:
converting the acquired pulse waveform curve into a pulse waveform image;
determining pulse characteristics in the pulse waveform image;
and determining the waveform characteristics of the pulse wave according to the pulse characteristics.
Further, the pulse characteristics include one or more of the following: coordinates of key points of the pulse period, amplitude, or the area occupied by a closed curve formed by pulse signals and a transverse axis;
the coordinates of the keypoints include one or more of the following: coordinates of a start point, a main peak, or a replay wave.
Further, the determining, according to the pulse condition, the pulse type to which the pulse wave belongs includes:
and determining the pulse type corresponding to the pulse condition according to the data in the waveform characteristic library, wherein the waveform characteristic library is formed by big data analysis according to the historical data.
Further, the method further comprises:
comparing the pulse type with data in a set knowledge base, and determining a report corresponding to the pulse wave information.
Further, comparing the pulse type with data in a set knowledge base, and determining a report corresponding to the pulse wave information includes:
comparing the pulse type with data in a set knowledge base, and determining a formative report corresponding to the pulse type;
and determining a report corresponding to the pulse wave information according to the formative report and the physiological index data corresponding to the waveform characteristics.
In a second aspect, an embodiment of the present application provides a pulse wave processing apparatus, which is characterized in that the apparatus includes:
the characteristic determining module is used for analyzing and processing the acquired pulse wave information and determining the waveform characteristics of the pulse wave;
the pulse condition determining module is used for inputting the waveform characteristics into a pulse condition identification network and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network;
and the type determining module is used for determining the pulse type of the pulse wave according to the pulse condition.
In a third aspect, an embodiment of the present application provides an electronic device, where the electronic device includes at least a processor and a memory, and the processor is configured to execute the steps of any one of the pulse wave processing methods described above when executing a computer program stored in the memory.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, performs the steps of the pulse wave processing method described in any one of the above.
In the embodiment of the application, the acquired pulse wave information is analyzed and processed to determine the waveform characteristics of the pulse wave; inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network; according to the pulse condition, the pulse type of the pulse wave is determined. In the method, firstly, the pulse wave information is analyzed and processed to obtain waveform characteristics, then, based on a pulse condition identification network, the pulse condition corresponding to the waveform characteristics is determined, and then, the pulse type of the pulse wave is determined according to the pulse condition, and the pulse condition data corresponding to the waveform characteristics is obtained by using an artificial intelligence technology and a big data analysis technology, so that the detection result can be improved by comparing the pulse condition data not only depending on manual work or a single index.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram illustrating a pulse wave processing process according to some embodiments of the present application;
FIG. 2 is a schematic diagram of pulse waves according to some embodiments of the present application;
FIG. 3 is a schematic diagram of a pulse wave processing flow according to some embodiments of the present application;
FIG. 4 is a schematic diagram of a pulse wave processing flow according to some embodiments of the present application;
fig. 5 is a schematic structural diagram of a pulse wave processing device according to some embodiments of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to some embodiments of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In order to improve the detection effect, the embodiment of the application provides a pulse wave processing method, a device, electronic equipment and a medium. In the embodiment of the application, the acquired pulse wave information is analyzed and processed to determine the waveform characteristics of the pulse wave; inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network; according to the pulse condition, the pulse type of the pulse wave is determined. The pulse wave information is analyzed and processed to obtain waveform characteristics, then the pulse condition corresponding to the waveform characteristics is determined based on a pulse condition identification network, then the pulse type of the pulse wave is determined according to the pulse condition, the pulse condition data corresponding to the waveform characteristics is obtained by using an artificial intelligence technology and a big data analysis technology, and the pulse condition data is compared not only by relying on manpower or a single index, so that the detection result can be improved.
The pulse wave processing procedure provided by the embodiment of the application is described below. Referring to fig. 1, a pulse wave processing process according to some embodiments of the present application is shown, the process includes:
s101: and analyzing and processing the acquired pulse wave information to determine the waveform characteristics of the pulse wave.
The pulse wave processing method provided by the embodiment of the application is applied to electronic equipment, and the electronic equipment can be user equipment, household equipment, a server or the like. Wherein the user device includes, but is not limited to, a cell phone, a computer, or a wearable device, and the home device includes, but is not limited to, a home health detection instrument, such as a finger vein detector.
In a scene, if the electronic device is not an instrument such as a finger pulse detector, the electronic device can acquire pulse wave information from the instruments and then perform pulse wave processing, and if the electronic device is an instrument such as a finger pulse detector, the electronic device, namely the instrument such as the finger pulse detector, can acquire the pulse wave information itself and then perform pulse wave processing.
An analysis processing algorithm for analyzing and processing the pulse wave may be stored in the electronic device in advance, so that after the pulse wave information is acquired, the waveform characteristics of the pulse wave may be determined according to the analysis processing algorithm. The waveform characteristics of pulse waves, which are formed by the peripheral propagation of the pulsation of the heart along arterial blood vessels and blood flows, are closely related to cardiovascular diseases, and are expressed in terms of morphology (wave shape), intensity (wave amplitude), velocity (wave velocity), rhythm (wave period), and the like.
S102: the waveform characteristics are input into a pulse condition identification network, and pulse conditions corresponding to the waveform characteristics are determined based on the pulse condition identification network.
The electronic device stores a pulse condition identification network, the pulse condition identification network is a neural network/neuron network, and by summarizing the identification results of each neuron on the waveform characteristics, the pulse condition corresponding to the waveform characteristics can be determined, for example, the probability maximum pulse condition result is adopted as the identification result output by the pulse condition identification network.
S103: according to the pulse condition, the pulse type of the pulse wave is determined.
The electronic device stores a pulse type determining algorithm, so that after determining the pulse condition, the pulse type corresponding to the pulse condition can be determined, and then the pulse type to which the pulse wave belongs is determined.
In the embodiment of the application, the pulse wave information is firstly analyzed and processed to obtain the waveform characteristics, then the pulse condition corresponding to the waveform characteristics is determined based on the pulse condition identification network, then the pulse type of the pulse wave is determined according to the pulse condition, the pulse condition data corresponding to the waveform characteristics is obtained by using the artificial intelligence technology and the big data analysis technology, and the pulse condition data is compared not only by relying on manual or single index, so that the detection result can be improved.
Based on the foregoing embodiment, in an embodiment of the present application, the foregoing method further includes:
and acquiring a pulse waveform curve acquired by the finger pulse detector.
The blood flow change of the finger tip of the person is not obvious at ordinary times, but with the help of the professional finger pulse detector, the change can be detected to be tiny, and the change can be processed by a series of processing technologies and then visually presented. Through a large number of scientific experiments, the finger blood flow change has strong relevance with the conditions of vascular aging, physical condition and the like of the human body.
Pulse wave data is acquired through a pulse finger instrument, and then through effective extraction of waveforms, technical analysis is carried out by means of an artificial intelligence analysis engine, so that relevant diagnosis data is obtained.
The product model, manufacturer, etc. of the finger vein detector are not limited herein.
In the embodiment of the application, the finger pulse detector can acquire fine changes, the pulse wave information is detected, the acquisition is more convenient, and the acquired data is more accurate.
Based on the above embodiments, in the embodiment of the present application, analyzing and processing the acquired pulse wave information, determining waveform characteristics of the pulse wave includes:
converting the acquired pulse waveform curve into a pulse waveform image;
determining pulse characteristics in the pulse waveform image;
from the pulse characteristics, waveform characteristics of the pulse wave are determined.
In general, the pulse waveform curve is usually one-dimensional data, and the electronic device may convert the one-dimensional data into a pulse waveform image, which may be two-dimensional waveform data.
In one implementation, the electronic device may perform wavelet transform on the pulse waveform image to mark the feature values, where the wavelet transform may decompose the original signal into signals at different frequency bins, thereby determining the pulse features in the pulse waveform image. Thus, the signal can be conveniently analyzed and processed in different frequency bands.
By way of example, pulse characteristics may include, but are not limited to, one or more of the following: coordinates of key points of the pulse period, the amplitude, or the area occupied by a closed curve formed by the pulse signal and the horizontal axis. The coordinates of the keypoints include, but are not limited to, one or more of the following: coordinates of a start point, a main peak, or a replay wave. Several possible pulse features are shown in fig. 2, where fig. 2 is a pulse waveform image in a single cycle, where point b represents the starting point, point c represents the main peak, point g represents the replay wave, and T represents the arterial cycle.
After determining the pulse characteristics, the electronic device may extract trusted information in the waveform, such as extracting relevant information in the characteristic values, from the pulse characteristics for use in signal classification, identification, analysis, etc., to determine waveform characteristics of the pulse wave.
The embodiment of the application is beneficial to analyzing and processing signals in different frequency bands, and further improves the detection accuracy.
Based on the above embodiments, in the embodiment of the present application, determining, according to the pulse condition, the pulse type to which the pulse wave belongs includes:
and determining the pulse type corresponding to the pulse condition according to the data in the waveform characteristic library, wherein the waveform characteristic library is formed by analyzing big data according to the historical data.
In this embodiment, the electronic device may form the intelligent model and the waveform feature library by analyzing big data according to the data accumulated previously, so as to compare the newly extracted data (such as pulse wave information) with the data in the intelligent model and the waveform feature library, and obtain the type of the waveform. Specifically, the electronic device analyzes the historical data to form a waveform database, and then compares the pulse condition output by the pulse condition identification network with the data in the waveform database, and determines the pulse type corresponding to the matched data as the pulse type corresponding to the pulse condition.
In this embodiment, the artificial intelligence model is used to perform a series of complex calculations, analyses, and processing operations based on waveform characteristics. Based on huge data accumulated for a long time, the artificial intelligence technology and the big data analysis technology are fully used, visual and reliable data can be obtained, and the reliability of results is improved.
Based on the foregoing embodiments, in the embodiments of the present application, the method further includes:
comparing the pulse type with the data in the set knowledge base, and determining a report corresponding to the pulse wave information.
The data in the setting knowledge base may include information such as description content of different types of pulses, susceptibility to diseases, etc., for example, the data in the setting knowledge base includes, but is not limited to, information corresponding to one or more of the following pulse types:
pulse floating: the ascending and forceful pulse condition is the exterior excess, while the descending and forceful pulse condition is the exterior deficiency. Superficial pulse is often found in gastrointestinal colds, acute gastroenteritis and other diseases.
Pulse sinking: the pulse can be felt only by taking force without feeling the pulse lightly, and the pulse is forcefully indicated to be excessive and the pulse is weak to be deficient. The blockage of qi and blood, unsmooth yang and deep and forceful pulse are all the more so; weak body, sinking yang qi, deep and weak pulse. The deep pulse is usually found in viscera weakness or qi and blood deficiency.
Delayed pulse: after taking pulse, the pulse is felt to be under 60 times per minute, the pulse condition is forceful and is excessive cold, the pulse condition is weak and is deficient cold, the pulse is slow and forceful and is excessive cold, and the pulse is slow and is weak and is deficient cold. The delayed pulse is mostly caused by sinus bradycardia, atrioventricular block and other diseases. Generally indicated as having a heat syndrome. The pathogenic heat is active, the viscera heat is excessive, the blood circulation is accelerated, the pulse is rapid and forceful, the yin deficiency and the fire are excessive, the body fluid and blood are deficient, and the pulse is rapid and weak, namely the deficiency heat. The rapid pulse is often associated with sinus tachycardia, anemia, hyperthyroidism and the like.
After the electronic equipment acquires the information corresponding to the pulse type from the data in the set knowledge base, a report corresponding to the pulse wave information can be formed according to a certain rule. The certain rules are not limited herein, e.g., the certain rules constrain the templates of the report, i.e., which information is included in the report.
In the embodiment of the application, the electronic equipment can finally form a comprehensive and detailed report by comparing the analysis result with the knowledge base data of the long-term accumulation and scientific authentication, thereby being beneficial to improving the detection accuracy.
Based on the above embodiments, in the embodiment of the present application, comparing the pulse type with the data in the set knowledge base, and determining the report corresponding to the pulse wave information includes:
comparing the pulse type with data in a set knowledge base to determine a formative report corresponding to the pulse type;
and determining a report corresponding to the pulse wave information according to the formative report and the physiological index data corresponding to the waveform characteristics.
In this embodiment, the electronic device determines the formative report corresponding to the pulse type according to the pulse type, for example, after the data in the set knowledge base obtains the information corresponding to the pulse type, the formative report may be obtained according to a certain rule. The electronic device then forms the final report from the formed report and the physiological index data and other instruments.
In one implementation, the electronic device uses artificial intelligence model classification computation to compute physiological index data based on the waveform features, e.g., the electronic device inputs the waveform features to a pulse condition recognition network, based on which the physiological index data is output.
In the embodiment of the application, the electronic equipment can output the pulse wave type and related physiological index data, and the data is analyzed and processed by utilizing a computer technology to obtain a final report.
On the basis of the above embodiments, the embodiment of the present application further provides a software system design structure, as shown in fig. 3, which includes a pulse wave signal acquisition and display unit, an information analysis processing unit, a trusted data unit extraction and calculation, analysis and processing unit using artificial intelligence, a knowledge base comparison and report display unit, an information storage unit, and an information data unit, wherein the information data unit stores information data therein. The following describes the design structure of the software system in detail with reference to the flow shown in fig. 4, firstly, pulse wave information is acquired through the pulse wave signal acquisition and display unit, then waveform characteristic values are extracted through the information analysis processing unit and the trusted data extraction unit, whether the extraction is successful is judged, if not, the extraction characteristic threshold is reset, and the waveform characteristic values are re-extracted. If so, loading an artificial intelligent model (such as the pulse condition identification network), loading a waveform feature library, performing calculation, analysis and processing by using artificial intelligence, classifying and calculating by using the artificial intelligent model according to waveform features, and outputting pulse waveform classification, calculation results and formation reports by using a knowledge base comparison and report display unit, wherein the classification, calculation results and formation reports can be stored into an information data unit through an information storage unit. In short, the sensor is used for collecting finger waveform data, then big data is analyzed through artificial intelligence according to the data accumulated before, analysis results are compared with knowledge base data accumulated for a long time and subjected to scientific authentication, and finally a comprehensive and detailed report is formed.
On the basis of the above embodiments, the present application provides a pulse wave processing apparatus, and fig. 5 is a schematic structural diagram of a pulse wave processing apparatus according to some embodiments of the present application, as shown in fig. 5, where the apparatus includes:
the feature determining module 501 is configured to analyze and process the obtained pulse wave information, and determine waveform features of the pulse wave;
the pulse condition determining module 502 is configured to input the waveform characteristic into a pulse condition identification network, and determine a pulse condition corresponding to the waveform characteristic based on the pulse condition identification network;
the type determining module 503 is configured to determine a pulse type to which the pulse wave belongs according to the pulse condition.
In a possible implementation manner, the feature determining module 501 is further configured to acquire a pulse waveform curve acquired by the finger pulse detector.
In one possible implementation, the feature determining module 501 is specifically configured to convert the acquired pulse waveform curve into a pulse waveform image; determining pulse characteristics in the pulse waveform image; from the pulse characteristics, waveform characteristics of the pulse wave are determined.
In one possible embodiment, the pulse characteristics include one or more of the following: coordinates of key points of the pulse period, amplitude, or the area occupied by a closed curve formed by pulse signals and a transverse axis;
the coordinates of the keypoints include one or more of the following: coordinates of a start point, a main peak, or a replay wave.
In one possible implementation manner, the type determining module 503 is specifically configured to determine a pulse type corresponding to a pulse condition according to data in a waveform feature library, where the waveform feature library is formed by big data analysis according to historical data.
In one possible embodiment, the apparatus further comprises:
and the report determining module is used for comparing the pulse type with the data in the set knowledge base and determining a report corresponding to the pulse wave information.
In one possible implementation manner, the report determining module is specifically configured to compare the pulse type with data in a set knowledge base, and determine a forming report corresponding to the pulse type; and determining a report corresponding to the pulse wave information according to the formative report and the physiological index data corresponding to the waveform characteristics.
On the basis of the above embodiment, the present application further provides an electronic device, and fig. 6 is a schematic structural diagram of an electronic device provided by the embodiment of the present application, as shown in fig. 6, including: processor 601, communication interface 602, memory 603 and communication bus 604, wherein processor 601, communication interface 602, memory 603 complete the communication each other through communication bus 604;
the memory 603 has stored therein a computer program which, when executed by the processor 601, causes the processor 601 to perform the steps of:
analyzing and processing the obtained pulse wave information to determine the waveform characteristics of the pulse wave;
inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network;
according to the pulse condition, the pulse type of the pulse wave is determined.
In a possible implementation, the processor 601 is further configured to:
and acquiring a pulse waveform curve acquired by the finger pulse detector.
In one possible implementation, the processor 601 is specifically configured to:
converting the acquired pulse waveform curve into a pulse waveform image;
determining pulse characteristics in the pulse waveform image;
from the pulse characteristics, waveform characteristics of the pulse wave are determined.
In one possible embodiment, the pulse characteristics include one or more of the following: coordinates of key points of the pulse period, amplitude, or the area occupied by a closed curve formed by pulse signals and a transverse axis;
the coordinates of the keypoints include one or more of the following: coordinates of a start point, a main peak, or a replay wave.
In one possible implementation, the processor 601 is specifically configured to:
and determining the pulse type corresponding to the pulse condition according to the data in the waveform characteristic library, wherein the waveform characteristic library is formed by analyzing big data according to the historical data.
In a possible implementation, the processor 601 is further configured to:
comparing the pulse type with the data in the set knowledge base, and determining a report corresponding to the pulse wave information.
In one possible implementation, the processor 601 is specifically configured to:
comparing the pulse type with data in a set knowledge base to determine a formative report corresponding to the pulse type;
and determining a report corresponding to the pulse wave information according to the formative report and the physiological index data corresponding to the waveform characteristics.
The communication bus mentioned for the above-mentioned electronic devices may be a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus or an EISA (Extended Industry Standard Architecture ) bus, or the like. 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 602 is used for communication between the electronic device and other devices described above.
The Memory may include RAM (Random Access Memory ) or NVM (Non-Volatile Memory), 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, an NP (Network Processor ), etc.; but may also be a DSP (Digital Signal Processing, digital instruction processor), application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like.
On the basis of the above embodiments, the embodiments of the present application provide a computer-readable storage medium, in which a computer program executable by an electronic device is stored, which when executed on the electronic device causes the electronic device to perform the steps of:
analyzing and processing the obtained pulse wave information to determine the waveform characteristics of the pulse wave;
inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network;
according to the pulse condition, the pulse type of the pulse wave is determined.
In one possible embodiment, the method further comprises:
and acquiring a pulse waveform curve acquired by the finger pulse detector.
In one possible implementation manner, analyzing the acquired pulse wave information, and determining the waveform characteristics of the pulse wave includes:
converting the acquired pulse waveform curve into a pulse waveform image;
determining pulse characteristics in the pulse waveform image;
from the pulse characteristics, waveform characteristics of the pulse wave are determined.
In one possible embodiment, the pulse characteristics include one or more of the following: coordinates of key points of the pulse period, amplitude, or the area occupied by a closed curve formed by pulse signals and a transverse axis;
the coordinates of the keypoints include one or more of the following: coordinates of a start point, a main peak, or a replay wave.
In one possible implementation, determining the pulse type to which the pulse wave belongs according to the pulse condition includes:
and determining the pulse type corresponding to the pulse condition according to the data in the waveform characteristic library, wherein the waveform characteristic library is formed by analyzing big data according to the historical data.
In one possible embodiment, the method further comprises:
comparing the pulse type with the data in the set knowledge base, and determining a report corresponding to the pulse wave information.
In one possible implementation, comparing the pulse type with data in a set knowledge base, and determining a report corresponding to the pulse wave information includes:
comparing the pulse type with data in a set knowledge base to determine a formative report corresponding to the pulse type;
and determining a report corresponding to the pulse wave information according to the formative report and the physiological index data corresponding to the waveform characteristics.
Since the principle of the above-mentioned computer readable storage medium for solving the problem is similar to that of the pulse wave processing method, the implementation of the above-mentioned computer readable storage medium can refer to the embodiment of the method, and the repetition is omitted.
The computer readable storage medium may be any available medium or data storage device that can be accessed by a processor in an electronic device, including but not limited to magnetic memories such as floppy disks, hard disks, tapes, MO (magneto optical disks), etc., optical memories such as CD, DVD, BD, HVD, etc., and semiconductor memories such as ROM, EPROM, EEPROM, NAND FLASH (non-volatile memories), SSD (solid state disk), etc.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A pulse wave processing method, the method comprising:
analyzing and processing the acquired pulse wave information, and determining the waveform characteristics of the pulse wave;
inputting the waveform characteristics into a pulse condition identification network, and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network;
and determining the pulse type of the pulse wave according to the pulse condition.
2. The method of claim 1, wherein the method further comprises:
and acquiring a pulse waveform curve acquired by the finger pulse detector.
3. The method of claim 2, wherein analyzing the acquired pulse wave information to determine waveform characteristics of the pulse wave comprises:
converting the acquired pulse waveform curve into a pulse waveform image;
determining pulse characteristics in the pulse waveform image;
and determining the waveform characteristics of the pulse wave according to the pulse characteristics.
4. A method as claimed in claim 3, wherein the pulse characteristics include one or more of: coordinates of key points of the pulse period, amplitude, or the area occupied by a closed curve formed by pulse signals and a transverse axis;
the coordinates of the keypoints include one or more of the following: coordinates of a start point, a main peak, or a replay wave.
5. The method of any one of claims 1-4, wherein said determining the pulse type to which the pulse wave belongs based on the pulse condition comprises:
and determining the pulse type corresponding to the pulse condition according to the data in the waveform characteristic library, wherein the waveform characteristic library is formed by big data analysis according to the historical data.
6. The method of any one of claims 1-4, wherein the method further comprises:
comparing the pulse type with data in a set knowledge base, and determining a report corresponding to the pulse wave information.
7. The method of claim 6, wherein comparing the pulse type with data in a set knowledge base, determining a report corresponding to the pulse wave information comprises:
comparing the pulse type with data in a set knowledge base, and determining a formative report corresponding to the pulse type;
and determining a report corresponding to the pulse wave information according to the formative report and the physiological index data corresponding to the waveform characteristics.
8. A pulse wave processing apparatus, the apparatus comprising:
the characteristic determining module is used for analyzing and processing the acquired pulse wave information and determining the waveform characteristics of the pulse wave;
the pulse condition determining module is used for inputting the waveform characteristics into a pulse condition identification network and determining pulse conditions corresponding to the waveform characteristics based on the pulse condition identification network;
and the type determining module is used for determining the pulse type of the pulse wave according to the pulse condition.
9. An electronic device comprising at least a processor and a memory, the processor being adapted to implement the steps of the pulse wave processing method according to any of claims 1-7 when executing a computer program stored in the memory.
10. A computer storage medium, characterized in that it stores a computer program executable by an electronic device, which when run on the electronic device causes the electronic device to perform the steps of the pulse wave processing method of any one of claims 1-7.
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| CN120531363A (en) * | 2025-07-25 | 2025-08-26 | 杭州秋果计划科技有限公司 | A pulse detection method and related equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN120531363A (en) * | 2025-07-25 | 2025-08-26 | 杭州秋果计划科技有限公司 | A pulse detection method and related equipment |
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