CN114983371A - Heart rate irregularity testing system and method for cardiology department based on artificial intelligence - Google Patents
Heart rate irregularity testing system and method for cardiology department based on artificial intelligence Download PDFInfo
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- CN114983371A CN114983371A CN202210578669.3A CN202210578669A CN114983371A CN 114983371 A CN114983371 A CN 114983371A CN 202210578669 A CN202210578669 A CN 202210578669A CN 114983371 A CN114983371 A CN 114983371A
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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
- A61B5/02—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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/02405—Determining heart rate variability
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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
Abstract
The invention relates to the technical field of medical instruments, in particular to a heart rate irregularity testing system and method for cardiology department based on artificial intelligence, which comprises the following steps: acquire intracardiac branch of academic or vocational study test heart rate data, convert intracardiac branch of academic or vocational study test heart rate data into sampling data, calculate the correlation rule data probability number of intracardiac branch of academic or vocational study test heart rate data, judge according to correlation rule data probability number whether intracardiac branch of academic or vocational study test heart rate data is normal. Judging whether the heart rate data tested by the cardiology department is normal or not according to the probability number of the correlation rule data; specifically, whether the calculated probability number of the correlation rule data exceeds a threshold value or not is judged, if the probability number of the correlation rule data does not exceed the threshold value, the corresponding test heart rate data is normal, otherwise, the corresponding test heart rate data is abnormal, and therefore whether the heart rate data is normal or not can be accurately judged.
Description
Technical Field
The invention relates to a heart rate irregularity testing system and method for cardiology department based on artificial intelligence.
Background
The arrhythmia test belongs to a more complex problem, and in the prior art, for example, CN201611263403.0 discloses a method for applying a definite learning theory in the field of dynamic pattern recognition to the local accurate modeling and holographic feature extraction of the intrinsic system dynamics of the ST-T segment of ECG, and the dynamic knowledge of the system obtained by the learning and training is stored and utilized to construct a pattern library, the method is used for identifying electrocardiosignals, for example, CN201910117098.1 electrocardiosignal processing method based on CNN, similar technologies all focus on the processing of the characteristic identification of signals or heart rate data, no technology exists in the prior art for judging whether the heart rate data is normal, but the arrhythmia test belongs to a more complex problem and has strong personalized characteristics, therefore, on the basis of no technology for judging whether the heart rate data is normal or not, the problem of unpredictability exists in the simple processing of the signal or the characteristic identification of the heart rate data.
Disclosure of Invention
The invention aims to provide a heart rate irregularity testing system and method for cardiology department based on artificial intelligence, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the heart arrhythmia testing method for the cardiology department based on artificial intelligence comprises the following steps: acquire intracardiac branch of academic or vocational study test heart rate data, convert intracardiac branch of academic or vocational study test heart rate data into sampling data, calculate the correlation rule data probability number of intracardiac branch of academic or vocational study test heart rate data, judge according to correlation rule data probability number whether intracardiac branch of academic or vocational study test heart rate data is normal.
Further, the raw data of the heart rate data of the cardiology department test is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Will (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Conversion to k (i) Wherein i is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) For different data dimensions x, calculate:
therein
Are respectively { k (i) The three dimensions of the computation volume.
Calculating the data probability number of correlation rule of heart rate data tested in the department of cardiology, specifically for { k } (i) And (5) setting the sampling step length as w/i, configuring w/i-u +1 arrays,
t is more than or equal to 1 and less than or equal to w/i-u +1, u is the dimension of an array, d is defined as the reference value of regular probability, and the difference of the arrays is
Definition of p t To satisfy
definition o t To satisfy
the probability number of the correlation rule data is as follows:
further, whether the heart rate data tested by the cardiology department are normal or not is judged according to the probability number of the correlation rule data, whether the calculated probability number of the correlation rule data exceeds a threshold value or not is specifically judged, if the probability number of the correlation rule data does not exceed the threshold value, the corresponding heart rate data tested by the cardiology department is normal, and otherwise, the corresponding heart rate data tested by the cardiology department is abnormal.
The heart rate irregularity testing system for the cardiology department based on artificial intelligence comprises a cloud computing unit built on a cloud server, wherein the cloud computing unit comprises a sampling data processing module, a probability number computing unit and a data abnormality judging unit which are connected with each other,
the sampling data processing module is used for acquiring testing heart rate data of the cardiology department and converting the testing heart rate data of the cardiology department into sampling data;
the rate number calculating unit is used for calculating the probability number of the correlation rule data of the heart rate data in the cardiology department test;
the data abnormity judging unit is used for judging whether the heart rate data of the cardiology department test is normal according to the data probability number of the correlation rule.
Further, the heart rate irregularity testing system for the cardiology department based on artificial intelligence comprises a storage medium configured on a cloud server, wherein the storage medium is used for executing commands of the sampling data processing module, the probability number calculating unit and the data abnormality judging unit.
Compared with the prior art, the invention has the beneficial effects that: judging whether the heart rate data tested by the cardiology department is normal or not according to the probability number of the correlation rule data; specifically, whether the calculated probability number of the correlation rule data exceeds a threshold value or not is judged, if the probability number of the correlation rule data does not exceed the threshold value, the corresponding test heart rate data is normal, otherwise, the corresponding test heart rate data is abnormal, and therefore the heart rate data can be accurately judged whether the heart rate data is normal or not.
Drawings
FIG. 1 is a flow chart of a cardiac arrhythmia testing method for cardiology department based on artificial intelligence.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The application discloses heart arrhythmia test method for department of cardiology based on artificial intelligence, as shown in figure 1, includes the steps of:
acquire intracardiac branch of academic or vocational study test heart rate data, convert intracardiac branch of academic or vocational study test heart rate data into sampling data, calculate the correlation rule data probability number of intracardiac branch of academic or vocational study test heart rate data, judge according to correlation rule data probability number whether intracardiac branch of academic or vocational study test heart rate data is normal.
Preferably, the raw data of the heart rate data in the cardiology department test is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Will (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Conversion to k (i) Wherein i is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) For different data dimensions x, calculate:
therein
Are respectively { k (i) The three dimensions of the computation volume.
Preferably, a correlation law data probability number for the cardiology test heart rate data is calculated, specifically for { k } (i) Setting the sampling step length as w/i, configuring w/i-u +1 arrays,
t is more than or equal to 1 and less than or equal to w/i-u +1, u is array dimension, d is defined as reference value of regular probability, and the difference of the arrays is
Definition of p t To satisfy
definition o t To satisfy
the probability number of the correlation rule data is as follows:
preferably, whether the heart rate data tested by the cardiology department is normal or not is judged according to the probability number of the correlation rule data, whether the calculated probability number of the correlation rule data exceeds a threshold value or not is specifically judged, if the probability number of the correlation rule data does not exceed the threshold value, the corresponding heart rate data tested is normal, and if not, the corresponding heart rate data tested is abnormal.
The application also discloses an artificial intelligence-based cardiac rate irregularity testing system for the department of cardiology, which comprises a cloud computing unit built in a cloud server, wherein the cloud computing unit comprises a sampling data processing module, a probability number computing unit and a data abnormality judging unit which are connected, the sampling data processing module is used for acquiring testing cardiac rate data of the department of cardiology and converting the testing cardiac rate data of the department of cardiology into sampling data; the rate number calculation unit is used for calculating the probability number of the correlation rule data of the heart rate data tested by the cardiology department;
the data abnormity judging unit is used for judging whether the heart rate data tested by the cardiology department is normal according to the data probability number of the correlation rule; the heart rate irregularity testing system for the cardiology department based on artificial intelligence comprises a storage medium configured on a cloud server, wherein the storage medium is used for executing commands of a sampling data processing module, a probability number calculating unit and a data abnormality judging unit.
As a specific embodiment, the sampling data processing module acquires cardiology department testing heart rate data and converts the cardiology department testing heart rate data into sampling data; the original data of the heart rate data for the cardiology department test is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Will (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Conversion to k (i) Wherein i is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) For different data dimensions x, calculate:
therein
Are respectively { k (i) The three dimensions of the computation volume.
The probability number calculating unit calculates the probability number of the correlation rule data of the heart rate data tested by the cardiology department; calculating correlation rule number of heart rate data in cardiology department testData probability number, in particular for k (i) And (5) setting the sampling step length as w/i, configuring w/i-u +1 arrays,
t is more than or equal to 1 and less than or equal to w/i-u +1, u is the dimension of an array, d is defined as the reference value of regular probability, and the difference of the arrays is
Definition of p t To satisfy
definition o t To satisfy
the probability number of the correlation rule data is as follows:
the data abnormality judging unit judges whether the heart rate data tested by the cardiology department is normal according to the data probability number of the correlation rule; specifically, whether the calculated probability number of the correlation rule data exceeds a threshold value or not is judged, if the probability number of the correlation rule data does not exceed the threshold value, the corresponding test heart rate data is normal, otherwise, the corresponding test heart rate data is abnormal, and therefore whether the heart rate data is normal or not can be accurately judged.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described above, or equivalents may be substituted for elements thereof. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (5)
1. Heart arrhythmia testing method for internal medicine based on artificial intelligence, which is characterized by comprising the following steps:
the method comprises the steps of obtaining testing heart rate data of the cardiology department, converting the testing heart rate data of the cardiology department into sampling data, calculating the probability number of correlation rule data of the testing heart rate data of the cardiology department, and judging whether the testing heart rate data of the cardiology department is normal or not according to the probability number of the correlation rule data.
2. The artificial intelligence based arrhythmia testing method for cardiology as claimed in claim 1,
the original data of the heart rate data for the cardiology department test is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Will (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) Conversion to k (i) Wherein i is (j) 1 ,j 2 ,j 3 ,......j w-1 ,j w ) For different data dimensions x, calculate:
therein are
Are respectively { k (i) Three-dimensional computation quantity of };
calculating the data probability number of correlation rule of heart rate data in cardiology test
For k (i) Setting the sampling step length as w/i, configuring w/i-u +1 arrays,
t is more than or equal to 1 and less than or equal to w/i-u +1, u is the dimension of an array, d is defined as the reference value of regular probability, and the difference of the arrays is
Definition of p t To satisfy
definition o t To satisfy
the probability number of the correlation rule data is as follows:
3. the artificial intelligence based arrhythmia testing method for the cardiology department as claimed in claim 1, wherein the method determines whether the cardiology department testing heart rate data is normal based on the correlation rule data probability number, specifically determines whether the calculated correlation rule data probability number exceeds a threshold, indicates that the corresponding testing heart rate data is normal if the correlation rule data probability number does not exceed the threshold, and otherwise indicates that the corresponding testing heart rate data is abnormal.
4. The heart rate irregularity testing system for the cardiology department based on artificial intelligence is characterized by comprising a cloud computing unit built in a cloud server, wherein the cloud computing unit comprises a sampling data processing module, a probability number computing unit and a data abnormality judging unit which are connected with each other,
the sampling data processing module is used for acquiring testing heart rate data of the cardiology department and converting the testing heart rate data of the cardiology department into sampling data;
the rate number calculation unit is used for calculating the probability number of the correlation rule data of the heart rate data tested by the cardiology department;
and the data abnormality judging unit is used for judging whether the heart rate data tested by the cardiology department is normal according to the data probability number of the correlation rule.
5. The system according to claim 4, comprising a storage medium disposed in the cloud server, the storage medium being configured to execute the commands from the sampling data processing module, the probability number calculating unit, and the data abnormality determining unit.
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| WO2019160504A1 (en) * | 2018-02-13 | 2019-08-22 | Agency For Science, Technology And Research | System and method for assessing clinical event risk based on heart rate complexity |
| US20200372348A1 (en) * | 2019-05-21 | 2020-11-26 | Firstbeat Analytics Oy | Method and apparatus for detecting a sleep state |
| KR20210015306A (en) * | 2019-08-01 | 2021-02-10 | 성균관대학교산학협력단 | Apparatuses and methods for classifying heart condition based on class probability output network |
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- 2022-05-25 CN CN202210578669.3A patent/CN114983371A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6245021B1 (en) * | 1997-04-11 | 2001-06-12 | Heartlink Na Patent Corporation | Method for diagnosing psychiatric disorders |
| CN107951496A (en) * | 2017-11-27 | 2018-04-24 | 新绎健康科技有限公司 | Method and system based on multi-scale entropy analysis psychosoma relevance |
| WO2019160504A1 (en) * | 2018-02-13 | 2019-08-22 | Agency For Science, Technology And Research | System and method for assessing clinical event risk based on heart rate complexity |
| US20200372348A1 (en) * | 2019-05-21 | 2020-11-26 | Firstbeat Analytics Oy | Method and apparatus for detecting a sleep state |
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