CN108742599A - A kind of foetus health early warning system and method - Google Patents
A kind of foetus health early warning system and method Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- 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]
- A61B5/344—Foetal cardiography
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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Abstract
The application belongs to mother and baby's monitoring technology field, more particularly to a kind of foetus health early warning system and method.The foetus health early warning system includes that mathematical analysis model establishes module and data analysis module；The mathematical analysis model establishes data of the module for collecting fetal rhythm measuring instrument, establishes mathematical analysis model；The data analysis module is used for the mathematical analysis model according to foundation, utilize data mining technology, it is closer with desired value to reach output valve, and foetus health warning information is provided according to fetal heart rate data, wherein, the fetal heart rate data is Fetal Heart Rate deceleration data, including Fetal Heart Rate deceleration variable deceleration fall and variable deceleration duration.The embodiment of the present application can more accurately predict foetus health, and provide warning information to foetus health in time, ensure fetal well-being.
Description
Technical field
The application belongs to mother and baby's monitoring technology field, more particularly to a kind of foetus health early warning system and method.
Background technology
Fetal heart frequency monitoring be judge fetus in parent whether a healthy important technology index.It is how general by ultrasound
After the methods of Le obtains fetal heart rate signal, judge whether fetus is healthy, obtains tire by relevant foetus health warning algorithm
Youngster's healthy early warning information.Existing foetus health warning algorithm generally existing accuracy is relatively low, Algorithm Analysis real result not
High technical problem.
Invention content
This application provides a kind of foetus health early warning system and methods, it is intended to solve existing skill at least to a certain extent
One of above-mentioned technical problem in art.
To solve the above-mentioned problems, this application provides following technical solutions：
A kind of foetus health early warning system, including mathematical analysis model establish module and data analysis module；The mathematics
Analysis model establishes data of the module for collecting fetal rhythm measuring instrument, establishes mathematical analysis model；The data analysis module is used
In the mathematical analysis model according to foundation, using data mining technology, it is closer with desired value to reach output valve, and according to fetal rhythm
Rate data provide foetus health warning information, wherein the fetal heart rate data is Fetal Heart Rate deceleration data, including Fetal Heart Rate deceleration
Variable deceleration fall and variable deceleration duration.
The technical solution that the embodiment of the present application is taken further includes：The mathematical analysis model of the foundation includes that Fetal Heart Rate accelerates
Mathematical model, Fetal Heart Rate slow down mathematical model, the mathematical model of FHR variability, the mathematical model of uterine contraction curve, fetal rhythm
Counting smooth curve mathematic model and uterine contraction smoothed curve mathematical model.
The technical solution that the embodiment of the present application is taken further includes：The data mining technology of the data analysis module includes：
Decision Tree algorithms, neural network algorithm, cluster algorithm and timing alorithm, specially：From the data of input, using poly-
Alanysis algorithm and timing alorithm, classify to data, the data sample that decision tree needs are generated, according to decision Tree algorithms pair
Data sample is tested, is corrected, and generates the back end of neural network, weighted value is added in the connection of each node, according to god
Through network algorithm, weight is constantly adjusted, it is closer with desired value to reach output valve.
The technical solution that the embodiment of the present application is taken further includes：It is described according to Fetal Heart Rate deceleration variable deceleration fall and
The variable deceleration duration provides foetus health warning information：If Fetal Heart Rate deceleration variable deceleration fall <
30bpm, and variable deceleration duration < 30s, then Fetal Heart Rate deceleration is slight；If the range of decrease under Fetal Heart Rate deceleration variable deceleration
Degree is in 30-60bpm, and the variable deceleration duration in 30-60s, then it is moderate that Fetal Heart Rate, which slows down,；Become if Fetal Heart Rate slows down
Different to slow down amplitude > 60bpm, and variable deceleration duration > 60s, then it is severe that Fetal Heart Rate, which slows down,.
The technical solution that the embodiment of the present application is taken further includes data management module, and the data management module includes relationship
Type and non-relational data management module, data fusion and integration module, data extraction module and data filtering module.
Another technical solution that the embodiment of the present application is taken is：A kind of foetus health method for early warning, including：
Step a：The fetal rhythm and movement of the foetus data of fetus are monitored using fetus-voice meter；
Step b：According to monitoring data, variable deceleration fall and variable deceleration duration are calculated, is subtracted according to variation
Fast fall and variable deceleration duration classify Fetal Heart Rate deceleration；
Step c：According to Fetal Heart Rate deceleration classification and residing period, foetus health warning information is provided, wherein described
Fetal heart rate data is Fetal Heart Rate deceleration data, including Fetal Heart Rate deceleration variable deceleration fall and variable deceleration duration.
The technical solution that the embodiment of the present application is taken further includes：Further include after the step a：According to acquisition Fetal Heart Rate base
Line judges whether that baseline makes a variation, and b is then entered step if there is baseline variation, and step is then returned if there is no baseline variation
Rapid a continues to monitor.
The technical solution that the embodiment of the present application is taken further includes：In the step b, according to variable deceleration fall and
The variable deceleration duration is classified Fetal Heart Rate deceleration specially：If Fetal Heart Rate deceleration variable deceleration fall <
30bpm, and variable deceleration duration < 30s, then Fetal Heart Rate deceleration is slight；If the range of decrease under Fetal Heart Rate deceleration variable deceleration
Degree is in 30-60bpm, and the variable deceleration duration in 30-60s, then it is moderate that Fetal Heart Rate, which slows down,；Become if Fetal Heart Rate slows down
Different to slow down amplitude > 60bpm, and variable deceleration duration > 60s, then it is severe that Fetal Heart Rate, which slows down,.
The technical solution that the embodiment of the present application is taken further includes：The Fetal Heart Rate deceleration residing period includes early deceleration
And late deceleration.
Compared with the existing technology, the advantageous effect that the embodiment of the present application generates is：The foetus health of the embodiment of the present application
Early warning system and method can more accurately predict foetus health, and provide warning information to foetus health in time, ensure tire
Youngster's safety.
Description of the drawings
Fig. 1 is the structural schematic diagram of the foetus health early warning system of the embodiment of the present application；
Fig. 2 is neural network weight adjustment process schematic；
Fig. 3 is the flow chart of the foetus health method for early warning of the embodiment of the present application.
Specific implementation mode
It is with reference to the accompanying drawings and embodiments, right in order to make the object, technical solution and advantage of the application be more clearly understood
The application is further elaborated.It should be appreciated that specific embodiment described herein is only to explain the application, not
For limiting the application.
Referring to Fig. 1, being the structural schematic diagram of the foetus health early warning system of the embodiment of the present application.The embodiment of the present application
Foetus health early warning system includes that mathematical analysis model establishes module, data analysis module and data management module.Mathematical analysis
Model building module is used to collect the data of fetal rhythm measuring instrument, establishes mathematical analysis model.The foetus health of the embodiment of the present application
Early warning system in order to provide more accurate foetus health prediction and warning, only according to platform intelligent mobile terminal collect metric data also not
Enough, platform is collected using the shared information API of medical department and web crawlers technology, keeps data various and abundant, carry by all kinds of means
The accuracy of high intelligent analysis process.In order to which the data measured to fetus-voice meter carry out in-depth investigation and research, inherent rule is analyzed,
Intellectualized analysis platform establishes following mathematical analysis model：A. the mathematical model that Fetal Heart Rate accelerates；B. the number that Fetal Heart Rate slows down
Learn model；C. the mathematical model of FHR variability；D. the mathematical model of uterine contraction curve；E. Fetal Heart Rate smoothed curve mathematical model；
F. uterine contraction smoothed curve mathematical model.Data analysis module is used for the mathematical analysis model according to foundation, utilizes data mining skill
Art, it is closer with desired value to reach output valve, and provides foetus health warning information according to fetal heart rate data.Also referring to figure
2, it is neural network weight adjustment process schematic.The data mining technology of data analysis module includes mainly：Decision Tree algorithms,
Neural network algorithm, cluster algorithm and timing alorithm.First from a lot of mixed and disorderly unordered data, cluster point is utilized
Algorithm and timing alorithm are analysed, is classified to data, the data sample that decision tree needs is generated, according to decision Tree algorithms to data
Sample is tested, is corrected, and generates the back end of neural network, weighted value is added in the connection of each node, according to nerve net
Network algorithm, constantly adjusts weight, and it is closer with desired value to reach output valve.Excessive, the doctor for data results error
Intervention is corrected, in order to avoid analysis result is caused to mislead pregnant woman.Fetal Heart Rate deceleration refers to slowing down with the temporary fetal rhythm that uterine contraction occurs, such as
Fruit Fetal Heart Rate deceleration variable deceleration fall (bpm) < 30, and variable deceleration duration (s), then Fetal Heart Rate deceleration is light
Degree；If Fetal Heart Rate deceleration variable deceleration fall (bpm) in 30-60, and the variable deceleration duration (s) in 30-60,
It is moderate that then Fetal Heart Rate, which slows down,；Fetal Heart Rate if deceleration variable deceleration fall (bpm) > 60, and variable deceleration duration
(s) 60 >, then it is severe degree that Fetal Heart Rate, which slows down,.The Fetal Heart Rate deceleration residing period includes early deceleration and late deceleration, early stage
It is mostly physiological phenomenon to slow down, and most fetus postpartum are good；Late deceleration indicates that fetus reserve capabillity is poor, intrauterine fetal anoxia, such as
Do not terminate to give a birth as early as possible, asphyxia neonatorum may be led to, or even jeopardize fetal life.
Data management module includes relationship type and non-relational data management module, data fusion and integration module, data
Abstraction module and data filtering module.Using non-relational data management module, problems with is predominantly solved：High concurrent is read
Demand is write, the user concurrent of website is very high, often reaches secondary read-write requests up to ten thousand per second, for traditional Relational DataBase
For, hard disk I/O is a prodigious bottleneck；The high efficiency of mass data is read and write, and the data volume that website generates daily is huge
, for relevant database, inquired in the table comprising mass data at one, efficiency is low-down；High scalability
And availability, database be most difficult to carry out it is extending transversely, when the user volume and visit capacity of application system are growing day by day
When, database is but had no idea as webserver and appserver simply by the more hardware of addition and service
Node comes scalability and load capacity.Meanwhile one is required to provide for the platform of 24 hours persistent services, when need
When Database Systems being upgraded and be extended, maintenance shut-downs and Data Migration are generally required, big inconvenience is caused.
Referring to Fig. 3, being the flow chart of the foetus health method for early warning of the embodiment of the present application.The fetus of the embodiment of the present application
Healthy early warning method includes：
Step 100：The fetal rhythm and movement of the foetus data of fetus are monitored using fetus-voice meter；
In step 100, the fetal rhythm data of monitoring include the baseline fetal heart rate of fetus, and baseline fetal heart rate refers to no movement of the foetus
When with uterine contraction, 10 minutes or more average Fetal Heart Rates, 110~160bpm is normal, is tachycardia more than 160bpm, is less than
110bpm is bradycardia.Baseline fetal heart rate is in sinusoidal waveform.
Step 200：It judges whether that baseline makes a variation according to baseline fetal heart rate is obtained, then enters if there is baseline variation
Step 300, if there is no baseline variation then return to step 100, continue to monitor；
In step 200, baseline variation refers to the amplitude and frequency that baseline fetal heart rate is swung.
Step 300：When baseline variation is that Fetal Heart Rate slows down, when judging that variable deceleration fall and variable deceleration continue
Between, Fetal Heart Rate deceleration is classified according to variable deceleration fall and variable deceleration duration；
In step 300, Fetal Heart Rate deceleration refers to slowing down with the temporary fetal rhythm that uterine contraction occurs, and is become if Fetal Heart Rate slows down
Different to slow down amplitude (bpm) < 30, and variable deceleration duration (s), then Fetal Heart Rate deceleration is slight；If Fetal Heart Rate subtracts
Fast variable deceleration fall (bpm) is in 30-60, and the variable deceleration duration (s) in 30-60, then Fetal Heart Rate deceleration is
Moderate；If Fetal Heart Rate deceleration variable deceleration fall (bpm) > 60, and variable deceleration duration (s) > 60, then fetal rhythm
It is severe degree that rate, which is slowed down,.
Step 400：According to Fetal Heart Rate deceleration classification and residing period, foetus health warning information is provided.
In step 400, the Fetal Heart Rate deceleration residing period includes early deceleration and late deceleration, and early deceleration is mostly to give birth to
Phenomenon is managed, most fetus postpartum are good；Late deceleration indicates that fetus reserve capabillity is poor, intrauterine fetal anoxia, if do not terminated as early as possible
Childbirth, may lead to asphyxia neonatorum, or even jeopardize fetal life.
Specifically in clinical practice, Heart rate decelerations and the relationship of Apgar scorings are：
| 8-10 (divides) | 4-7 (divides) | 0-3 (divides) | Total (dividing) | |
| Early deceleration | 21 | 1 | 0 | 22 |
| Late deceleration | 7 | 2 | 4 | 13 |
Early deceleration：The Apgar scoring 8-10 persons of dividing 21, childbirth result is cord around neck or distortion；7 points of scoring or less
Person 1, childbirth result are Meconium-stained Amniotic Fluid, hapamnion.
Late deceleration：The 8-10 persons of dividing 7, wherein childbirth result is placental calcification person 6, long cord is around 3 weeks persons 1 of neck
Example；Scoring is the 4-7 persons of dividing 2, wherein childbirth result is omphaloproptosis person 1, prolonged pregnancy hapamnion and placental calcification
Person 1；Score the 0-3 persons of dividing 4, wherein childbirth result is omphaloproptosis person 1, Severe Pregnancy Induced, placenta are big
Area calcification person 2, relative cephalopelvic disproportion 1.
In fetal heart monitoring, Fetal Heart Rate deceleration has an important clinical meaning, the type that Fetal Heart Rate slows down and Apgar score with
And clinical childbirth result has close relationship.
The foregoing description of the disclosed embodiments enables professional and technical personnel in the field to realize or use the application.
Various modifications to these embodiments will be apparent to those skilled in the art, as defined herein
General Principle can in other embodiments be realized in the case where not departing from spirit herein or range.Therefore, the application
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest range caused.
Claims (9)
1. a kind of foetus health early warning system, which is characterized in that establish module and data analysis module including mathematical analysis model；
The mathematical analysis model establishes data of the module for collecting fetal rhythm measuring instrument, establishes mathematical analysis model；The data point
Module is analysed to be used for according to the mathematical analysis model of foundation, using data mining technology, it is closer with desired value to reach output valve, and
Foetus health warning information is provided according to fetal heart rate data, wherein the fetal heart rate data is Fetal Heart Rate deceleration data, including tire
Heart rate decelerations variable deceleration fall and variable deceleration duration.
2. foetus health early warning system according to claim 1, which is characterized in that the mathematical analysis model packet of the foundation
Include the number of the mathematical model of Fetal Heart Rate acceleration, the mathematical model that Fetal Heart Rate slows down, the mathematical model of FHR variability, uterine contraction curve
Learn model, Fetal Heart Rate smoothed curve mathematical model and uterine contraction smoothed curve mathematical model.
3. foetus health early warning system according to claim 2, which is characterized in that the data of the data analysis module are dug
Pick technology includes：Decision Tree algorithms, neural network algorithm, cluster algorithm and timing alorithm, specially：From the number of input
In, using cluster algorithm and timing alorithm, classify to data, generates the data sample that decision tree needs, according to
Decision Tree algorithms are tested to data sample, are corrected, and the back end of neural network is generated, and power is added in the connection of each node
Weight values constantly adjust weight according to neural network algorithm, and it is closer with desired value to reach output valve.
4. foetus health early warning system according to claim 2 or 3, which is characterized in that described slowed down according to Fetal Heart Rate becomes
It is different to slow down amplitude and the variable deceleration duration provides foetus health warning information and includes：If Fetal Heart Rate slows down, variation subtracts
Fast fall < 30bpm, and variable deceleration duration < 30s, then Fetal Heart Rate deceleration is slight；Become if Fetal Heart Rate slows down
The different amplitude that slows down is in 30-60bpm, and the variable deceleration duration in 30-60s, then it is moderate that Fetal Heart Rate, which slows down,；If
Fetal Heart Rate deceleration variable deceleration fall > 60bpm, and variable deceleration duration > 60s, then it is severe that Fetal Heart Rate, which slows down,.
5. foetus health early warning system according to claim 1, which is characterized in that further include data management module, it is described
Data management module includes relationship type and non-relational data management module, data fusion and integration module, data extraction module
With data filtering module.
6. a kind of foetus health method for early warning, including：
Step a：The fetal rhythm and movement of the foetus data of fetus are monitored using fetus-voice meter；
Step b：According to monitoring data, variable deceleration fall and variable deceleration duration are calculated, according under variable deceleration
Range of decrease degree and variable deceleration duration classify Fetal Heart Rate deceleration；
Step c：According to Fetal Heart Rate deceleration classification and residing period, foetus health warning information is provided, wherein the fetal rhythm
Rate data are Fetal Heart Rate deceleration data, including Fetal Heart Rate deceleration variable deceleration fall and variable deceleration duration.
7. foetus health method for early warning according to claim 6, which is characterized in that further include after the step a：According to
It obtains baseline fetal heart rate and judges whether that baseline makes a variation, b is then entered step if there is baseline variation, if there is no baseline
Make a variation then return to step a, continues to monitor.
8. foetus health method for early warning according to claim 7, which is characterized in that in the step b, subtracted according to variation
Fast fall and variable deceleration duration are classified Fetal Heart Rate deceleration specially：If Fetal Heart Rate deceleration variable deceleration
Fall < 30bpm, and variable deceleration duration < 30s, then Fetal Heart Rate deceleration is slight；The variation if Fetal Heart Rate slows down
Amplitude is slowed down in 30-60bpm, and the variable deceleration duration in 30-60s, then it is moderate that Fetal Heart Rate, which slows down,；If tire
Heart rate decelerations variable deceleration fall > 60bpm, and variable deceleration duration > 60s, then it is severe that Fetal Heart Rate, which slows down,.
9. foetus health method for early warning according to claim 6, which is characterized in that in the step c, the Fetal Heart Rate
Period residing for slowing down includes early deceleration and late deceleration.
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| CN112971799A (en) * | 2021-02-04 | 2021-06-18 | 北京理工大学 | Non-stimulation fetal heart monitoring classification method based on machine learning |
| CN112971752A (en) * | 2019-12-13 | 2021-06-18 | 深圳市理邦精密仪器股份有限公司 | Fetal heart rate deceleration type correction method and device and fetal monitoring equipment |
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