CN108836310A - A kind of method and system for judging automatically user's electrocardio state based on artificial intelligence - Google Patents
A kind of method and system for judging automatically user's electrocardio state based on artificial intelligence Download PDFInfo
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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
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
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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
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
- A61B5/0006—ECG or EEG signals
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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
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
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- 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
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
Abstract
The method and system for judging automatically user's electrocardio state based on artificial intelligence that the invention discloses a kind of, method include the following steps：Obtain the ECG data that electrocardiogram monitoring equipment is sent；Record the waveform parameter of heartbeat and comparison every time in first time period and second time period；Obtain the comparison result of waveform parameter differential information；Comparison result is subjected to scoring and forms evaluation of estimate；Set electrocardiographic wave parameter evaluation level threshold value；Evaluation of estimate is compared with evaluation criterion threshold value；According to the difference between evaluation of estimate and level threshold value, judge whether exception；If the determination result is YES, then abnormity prompt is sent to user terminal or doctor terminal.The present invention can monitor automatically user's electrocardiogram state sum it for the previous period in difference, then will likely the problem of be sent directly to doctor terminal and analyze or prompt user for doctor, it allows user to take appropriate measures, diagnoses in time, provide health care for user.
Description
Technical field
The present invention relates to medical artificial intelligence aided diagnosis technique fields, and in particular to a kind of based on the automatic of artificial intelligence
Judge the method and system of user's electrocardio state.
Background technique
Electrocardiogram (ECG or EKG) is to record electricity caused by heart each cardiac cycle from body surface using electrocardiograph
The technology of activity change figure.Ecg wave form is recorded from body surface for the first time in Holland physiologist W.Einthoven within 1885, at that time
It is to use capillary electrometer, is modified to string galvanometer within 1910.Thus the history of surface electrocardiogram record has been started.It is expert at routine
When ECG examination, 4 limb leads electrodes and V1~V66 Precardial lead electrode are usually placed, records the conventional 12 lead hearts
Electrograph.Leads different one by one is formed between electrode or between electrode and central potential end two-by-two, passes through conducting wire and electrocardio
The positive and negative anodes for scheming electromechanical flowmeter are connected, and record the electrical activity of heart.Electrocardiogram is the important tool of clinical diagnosis and condition assessment,
A large amount of clinical data shows that electrocardiographic abnormality is the predictive factor because of coronary heart disease, cardiovascular disease and the death of the full cause of disease.Therefore,
The timely judgement of abnormal progress for electrocardiogram is further important.
In the prior art without it is long when electrocardio equipment to user reject the condition discrimination based on electrocardiogram.
Equipment is removed currently, being substantially with wearing electrocardiogram when the head of a household, the data for then wearing this upload
It can just draw a conclusion to diagnosis software, cause diagnosis not in time, cannot find the electrocardiographic abnormality information of user as early as possible.
Summary of the invention
The method for judging automatically user's electrocardio state based on artificial intelligence that the purpose of the present invention is to provide a kind of and it is
System, to solve the problems, such as that electrocardiographic abnormality cannot find that diagnosis is caused to be delayed in time in the prior art.
To achieve the above object, the technical scheme is that
In a first aspect, a kind of method for judging automatically user's electrocardio state based on artificial intelligence, includes the following steps：
Obtain the ECG data that electrocardiogram monitoring equipment is sent；
Record the waveform parameter of each heartbeat in first time period；
Record second time period in every time heartbeat waveform parameter, wherein second time period linking in first time period it
Afterwards；
The waveform parameter of heartbeat each in the waveform parameter and first time period of heartbeat each in second time period is compared；
Obtain the comparison result of waveform parameter differential information；
Comparison result is subjected to scoring and forms evaluation of estimate；
Set electrocardiographic wave parameter evaluation level threshold value；
Evaluation of estimate is compared with evaluation criterion threshold value；
According to the difference between evaluation of estimate and level threshold value, judge whether exception；
Judging result is obtained, if the determination result is YES, then sends abnormity prompt to user terminal or doctor terminal.
As a preferred solution of the present invention, it executes according to the difference between evaluation of estimate and level threshold value, judges whether
When abnormal step, if judging result be it is no, record in first time period and second time period new in next time cycle
The waveform parameter of each heartbeat simultaneously compares.
As a preferred solution of the present invention, when executing the waveform parameter of heartbeat each in second time period with first
Between when the waveform parameter of heartbeat compares step every time in section, compared using the method for clustering.
As a preferred solution of the present invention, the clustering includes the following steps
Electrocardiogram in a period of time is subjected to equal equal segments；
According to distribution situation, the heartbeat waveform parameter of every section of electrocardiogram is obtained；
Preset similarity threshold；
The waveform that similarity is higher than threshold value is classified as the first kind；
Waveform by similarity less than or equal to threshold value is classified as the second class；
The second class waveform parameter in the second class waveform parameter and second time period in first time period is obtained respectively；
Compare the second class waveform parameter in the second class waveform parameter and second time period in first time period；
Obtain the second class waveform parameter difference letter in the second class waveform parameter and second time period in first time period
The comparison result of breath.
As a preferred solution of the present invention, when executing the waveform parameter of heartbeat each in second time period with first
Between when the waveform parameter of heartbeat compares step every time in section, waveform parameter includes at least likelihood, slope, amplitude, mean value.
As a preferred solution of the present invention, execute it is described by comparison result carry out scoring form evaluation of estimate step when,
Evaluation of estimate is obtained by the parameter including including at least similarity, slope, amplitude, mean value.
Second aspect, a kind of system for judging automatically user's electrocardio state based on artificial intelligence, including electrocardiogram obtain
Module, electrocardiographic recorder module, comparison of wave shape module, comparison result evaluation module, level threshold value comparison module, exception judge mould
Block, exception information sending module；
Electrocardiogram obtains module, the ECG data that electrocardiogram monitoring equipment is sent is received, from the ECG data of acquisition
In, it is each in the second time period after first time period to record the waveform parameter and linking of each heartbeat in first time period
The waveform parameter recorded twice is sent to comparison of wave shape module by the waveform parameter of heartbeat；
Comparison of wave shape module receives electrocardiogram and obtains the waveform parameter twice that module is sent, and waveform parameter will carry out twice
Comparison, generation compare parameter, will compare parameter and be sent to comparison result evaluation module；
Comparison result evaluation module receives the comparison parameter that waveform contrast module is sent, and forms evaluation according to parameter is compared
Value, and it is sent to level threshold value comparison module；
Level threshold value comparison module, preset standard threshold value, the evaluation of estimate and standard that will be obtained from comparison result evaluation module
Threshold value is compared, and obtains comparison result；
Abnormal judgment module judges whether electrocardiogram abnormal according to comparison result, judging result be it is yes, then by exception information
It is sent to exception information sending module；
Exception information sending module receives the electrocardiographic abnormality information that abnormal judgment module is sent, and is sent to user's end
End or doctor terminal.
As a preferred solution of the present invention, the comparison of wave shape module further includes clustering submodule, cluster point
It analyses submodule and the conscientious equal equal segments of the electrocardiogram in a period of time is obtained into the heart of every section of electrocardiogram according to distribution situation first
Fight waveform parameter, preset similarity threshold, the waveform that similarity is higher than threshold value is classified as the first kind, similarity is lower than or
Waveform equal to threshold value is classified as the second class, is obtained in the second class waveform parameter and second time period in first time period respectively
Second class waveform parameter simultaneously compares, and obtains the comparison result of waveform parameter differential information, and comparison result is sent to and compares knot
Fruit evaluation module.
As a preferred solution of the present invention, the level threshold value be by include at least similarity, slope, amplitude,
The standard parameter that multiple parameters standard value including value is formed.
The invention has the advantages that：
The present invention can monitor automatically user's electrocardiogram state sum it for the previous period in difference, then will likely ask
Topic is sent directly to doctor terminal and analyzes or prompt user for doctor, allows user to take appropriate measures, reaches and examine in time
Disconnected, the purpose of delay treatment, does not provide health care for user.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Fig. 2 is the flow chart of clustering.
Specific embodiment
The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention..
Embodiment 1
See Fig. 1, a kind of method for judging automatically user's electrocardio state based on artificial intelligence disclosed in the present embodiment, including
Following steps：
Step S1 obtains the ECG data that electrocardiogram monitoring equipment is sent.Electrocardiogram monitoring equipment includes what user wore
Electrocardiogram monitoring equipment or other terminal monitoring equipment when long；
Step S2 records the waveform parameter of each heartbeat in first time period.According to ECG data according to monitoring time into
Capable record such as extracts the waveform in 10 minutes, and records to waveform parameter.
Step S3 records the waveform parameter of each heartbeat in second time period.Wherein, first time period and second time period
Duration may it is identical may also second time period be shorter than first time period, and second time period linking in first time period it
Afterwards.Specifically, then second time period is 10-20 minutes this segment if first time period is 0-10 minutes this segment,
Waveform is extracted, and waveform parameter is recorded.
When step S4 is by the waveform parameter of (i.e. the 10th minute to the 20th minute) in second time period each heartbeat and first
Between in section (i.e. the 0th minute to the 10th minute) heartbeat every time waveform parameter comparison.Wherein, the information of comparison includes at least similar
Rate, slope, amplitude, mean value.
The comparison result of step S5 acquisition waveform parameter differential information.Comparison result includes at least the value of likelihood, slope
Value, range value and mean value.
Comparison result is carried out scoring and forms evaluation of estimate by step S6.To parameters such as likelihood, slope, amplitude and mean values, press
It is set according to different weights, forms a evaluation of estimate summarized；
Step S7 sets electrocardiographic wave parameter evaluation level threshold value.Evaluation criterion threshold value is according to the ginseng used when comparing
Number is determining, and then last threshold value is different for different parameter selections, ultimately forms a evaluation criterion threshold value summarized.
Step S8 evaluation of estimate is compared with evaluation criterion threshold value.Comparison to the effect that the evaluation of estimate of waveform parameter
Whether limited in value range with the data differences size of level threshold value.
Step S9 judges whether exception according to the difference between evaluation of estimate and level threshold value.
Step S10 obtains judging result, if the determination result is YES, i.e., excessive with standard value difference, then to user terminal or
Doctor terminal sends abnormity prompt；If judging result be it is no, record first time period and new in next time cycle
It the waveform parameter of each heartbeat and is compared in two periods, contrastive detection is repeated.
See Fig. 2, further, executing will be each in the waveform parameter and first time period of heartbeat each in second time period
When the waveform parameter of heartbeat compares step, compared using the method for clustering.
The clustering includes the following steps：Electrocardiogram in a period of time is subjected to equal equal segments, such as 10 sections；According to
Distribution situation obtains the heartbeat waveform parameter of every section of electrocardiogram；Preset similarity threshold, i.e. every section of electrocardiogram it is similar
Degree；The waveform that similarity is higher than threshold value is classified as the first kind, since first kind electrocardiographic wave is recurrent waveform, definition
For normal waveform；Waveform by similarity less than or equal to threshold value is classified as the second class, since the second class electrocardiographic wave is non-anti-
It appears again existing waveform, is defined as improper waveform；The second class waveform parameter and the second time in first time period are obtained respectively
The second class waveform parameter in section；Compare the second class wave in the second class waveform parameter and second time period in first time period
Shape parameter；Obtain the second class waveform parameter differential information in the second class waveform parameter and second time period in first time period
Comparison result.
Specifically, execute it is described by comparison result carry out scoring form evaluation of estimate step when, evaluation of estimate by include at least phase
It is obtained like the parameter including degree, slope, amplitude, mean value.
Embodiment 2
The present embodiment discloses a kind of system for judging automatically user's electrocardio state based on artificial intelligence, including electrocardiogram obtains
Modulus block, electrocardiographic recorder module, comparison of wave shape module, comparison result evaluation module, level threshold value comparison module, abnormal judgement
Module, exception information sending module.
Electrocardiogram obtains module.For receiving the ECG data of electrocardiogram monitoring equipment transmission, from the electrocardiogram of acquisition
In data, the waveform parameter and linking of each heartbeat in first time period are recorded in the second time period after first time period
The waveform parameter of each heartbeat, is sent to comparison of wave shape module for the waveform parameter recorded twice.
Comparison of wave shape module receives electrocardiogram and obtains the waveform parameter twice that module is sent, and waveform parameter will carry out twice
Comparison, generation compare parameter, will compare parameter and be sent to comparison result evaluation module.
Comparison result evaluation module receives the comparison parameter that waveform contrast module is sent, and forms evaluation according to parameter is compared
Value, and it is sent to level threshold value comparison module.
Level threshold value comparison module, preset standard threshold value, wherein level threshold value is by including at least similarity, slope, width
The standard parameter that multiple parameters standard value including degree, mean value is formed.By the evaluation of estimate obtained from comparison result evaluation module with
Level threshold value is compared, and obtains comparison result.
Abnormal judgment module judges whether electrocardiogram abnormal according to comparison result, judging result be it is yes, then by exception information
It is sent to exception information sending module.
Exception information sending module receives the electrocardiographic abnormality information that abnormal judgment module is sent, and is sent to user's end
End or doctor terminal.
Further, the comparison of wave shape module further includes clustering submodule, and clustering submodule is first by one
The conscientious equal equal segments of electrocardiogram in the section time obtain the heartbeat waveform parameter of every section of electrocardiogram, set in advance according to distribution situation
Determine similarity threshold, the waveform that similarity is higher than threshold value is classified as the first kind, the waveform by similarity less than or equal to threshold value is returned
For the second class, the second class waveform parameter in the second class waveform parameter and second time period in first time period is obtained respectively simultaneously
Comparison, obtains the comparison result of waveform parameter differential information, and comparison result is sent to comparison result evaluation module.
The present invention use neural network model, automatically record a period of time (such as 10 minutes) in every time heartbeat waveform and
Heartbeat gap in different time dimension, then carries out clustering, after analyzing by under the waveform of heartbeat and gap several times
Analogy is carried out, if the excessive then trigger notice of difference, notifies user to take measures, or doctor terminal is sent by this section of heartbeat and carries out
Analysis.
The technical solution that the present invention is protected, it is not limited to above-described embodiment, it is noted that any one embodiment
The combination of technical solution in technical solution and other one or more embodiments, within the scope of the present invention.
Although above having used general explanation and specific embodiment, the present invention is described in detail, at this
On the basis of invention, it can be made some modifications or improvements, this will be apparent to those skilled in the art.Therefore,
These modifications or improvements without departing from theon the basis of the spirit of the present invention are fallen within the scope of the claimed invention.
Claims (9)
1. a kind of method for judging automatically user's electrocardio state based on artificial intelligence, which is characterized in that include the following steps：
Obtain the ECG data that electrocardiogram monitoring equipment is sent；
Record the waveform parameter of each heartbeat in first time period；
Record the waveform parameter of each heartbeat in second time period, wherein second time period is connected after first time period；
The waveform parameter of heartbeat each in the waveform parameter and first time period of heartbeat each in second time period is compared；
Obtain the comparison result of waveform parameter differential information；
Comparison result is subjected to scoring and forms evaluation of estimate；
Set electrocardiographic wave parameter evaluation level threshold value；
Evaluation of estimate is compared with evaluation criterion threshold value；
According to the difference between evaluation of estimate and level threshold value, judge whether exception；
Judging result is obtained, if the determination result is YES, then sends abnormity prompt to user terminal or doctor terminal.
2. a kind of method for judging automatically user's electrocardio state based on artificial intelligence according to claim 1, feature
Be, execute according to the difference between evaluation of estimate and level threshold value, when judging whether abnormal step, if judging result be it is no,
It records the waveform parameter of each heartbeat in first time period and second time period new in next time cycle and compares.
3. a kind of method for judging automatically user's electrocardio state based on artificial intelligence according to claim 1, feature
It is, executes and compare the waveform parameter of heartbeat each in the waveform parameter and first time period of heartbeat each in second time period
When step, compared using the method for clustering.
4. a kind of method for judging automatically user's electrocardio state based on artificial intelligence according to claim 3, feature
It is, the clustering includes the following steps
Electrocardiogram in a period of time is subjected to equal equal segments；
According to distribution situation, the heartbeat waveform parameter of every section of electrocardiogram is obtained；
Preset similarity threshold；
The waveform that similarity is higher than threshold value is classified as the first kind；
Waveform by similarity less than or equal to threshold value is classified as the second class；
The second class waveform parameter in the second class waveform parameter and second time period in first time period is obtained respectively；
Compare the second class waveform parameter in the second class waveform parameter and second time period in first time period；
Obtain the second class waveform parameter differential information in the second class waveform parameter and second time period in first time period
Comparison result.
5. a kind of method for judging automatically user's electrocardio state based on artificial intelligence according to claim 1, feature
It is, executes and compare the waveform parameter of heartbeat each in the waveform parameter and first time period of heartbeat each in second time period
When step, waveform parameter includes at least likelihood, slope, amplitude, mean value.
6. a kind of method for judging automatically user's electrocardio state based on artificial intelligence according to claim 1, feature
Be, execute it is described by comparison result carry out scoring form evaluation of estimate step when, evaluation of estimate by include at least similarity, slope,
Parameter including amplitude, mean value obtains.
7. a kind of system for judging automatically user's electrocardio state based on artificial intelligence, which is characterized in that obtained including electrocardiogram
Module, electrocardiographic recorder module, comparison of wave shape module, comparison result evaluation module, level threshold value comparison module, exception judge mould
Block, exception information sending module；
Electrocardiogram obtains module, receives the ECG data that electrocardiogram monitoring equipment is sent, from the ECG data of acquisition, note
Record the waveform parameter of each heartbeat and each heartbeat in the second time period being connected after first time period in first time period
Waveform parameter, the waveform parameter recorded twice is sent to comparison of wave shape module；
Comparison of wave shape module receives electrocardiogram and obtains the waveform parameter twice that module is sent, waveform parameter will compare twice,
Parameter is compared in generation, will compare parameter and is sent to comparison result evaluation module；
Comparison result evaluation module receives the comparison parameter that waveform contrast module is sent, and forms evaluation of estimate according to parameter is compared, and
It is sent to level threshold value comparison module；
Level threshold value comparison module, preset standard threshold value, the evaluation of estimate and level threshold value that will be obtained from comparison result evaluation module
It is compared, obtains comparison result；
Abnormal judgment module judges whether electrocardiogram abnormal according to comparison result, judging result be it is yes, then exception information is sent
To exception information sending module；
Exception information sending module receives the electrocardiographic abnormality information that abnormal judgment module is sent, and be sent to the user terminal or
Doctor terminal.
8. a kind of system for judging automatically user's electrocardio state based on artificial intelligence according to claim 7, feature
It is, the comparison of wave shape module further includes clustering submodule, and clustering submodule is first by the heart in a period of time
The conscientious equal equal segments of electrograph obtain the heartbeat waveform parameter of every section of electrocardiogram, preset similarity threshold according to distribution situation
The waveform that similarity is higher than threshold value is classified as the first kind by value, and the waveform by similarity less than or equal to threshold value is classified as the second class, point
It the second class waveform parameter in the second class waveform parameter and second time period in first time period and Huo Qu not compare, obtain wave
The comparison result of shape parameter differential information, and comparison result is sent to comparison result evaluation module.
9. a kind of system for judging automatically user's electrocardio state based on artificial intelligence according to claim 7, feature
It is, the level threshold value is by being formed including at least the multiple parameters standard value including similarity, slope, amplitude, mean value
Standard parameter.
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| CN109875549A (en) * | 2019-03-28 | 2019-06-14 | 吕金兰 | A kind of healthy early warning method based on electrocardiogram |
| CN110353657A (en) * | 2019-07-16 | 2019-10-22 | 上海数创医疗科技有限公司 | It is a kind of based on double multiple waveforms type screening techniques and device for selecting mechanism |
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| CN113392874A (en) * | 2021-05-13 | 2021-09-14 | 中车唐山机车车辆有限公司 | Rail vehicle abnormal state diagnosis method and device and terminal equipment |
| CN113768516A (en) * | 2021-09-27 | 2021-12-10 | 牛海成 | Artificial intelligence-based electrocardiogram abnormal degree detection method and system |
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