CN107095684B - A kind of autism of children risk evaluating system based on brain electricity - Google Patents
A kind of autism of children risk evaluating system based on brain electricity Download PDFInfo
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- CN107095684B CN107095684B CN201710178070.XA CN201710178070A CN107095684B CN 107095684 B CN107095684 B CN 107095684B CN 201710178070 A CN201710178070 A CN 201710178070A CN 107095684 B CN107095684 B CN 107095684B
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- A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
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- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
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- A61B5/369—Electroencephalography [EEG]
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Abstract
The invention discloses a kind of autism of children risk evaluating systems based on brain electricity, belong to autism of children risk assessment field.A kind of autism of children risk evaluating system based on brain electricity goes interference processing system, EEG signals clearing system, assessment self-closing disease risk system and display system including archipelago eeg signal acquisition system, EEG signals.It can be realized through archipelago eeg signal acquisition system acquisition EEG signals, interference signal is by digital filter and goes algorithm of interference computer preliminary treatment interference signal, using arma modeling and the adaptive predictor based on arma modeling effectively evades error caused by interference signal, eliminate disturbing factor, the healthy children data-signal of label and autism children signal are acquired respectively using the system simultaneously, a large amount of characteristic information will be acquired and be stored in first database, the child dataset signal for acquiring tested in the recent period is compared with it, so as to provide the self-closing disease Risk Results of rationalization.
Description
Technical field
The present invention relates to autism of children risk assessment field, more specifically to a kind of children based on brain electricity from
Close disease risk evaluating system.
Background technology
Self-closing disease is classified as one kind due to developmental disorder caused by nervous system disorder, it is impossible to carry out normal language table
It reaches and social activity, often does some mechanical and repeated actions and behavior, electroencephalogram is clinically mainly used for checking brain work(
Can, nervous system disorders disease be diagnosed, electroencephalogram is free from side effects, it is possible to find structural damage not only provides and work(occurs
Position that can be abnormal and degree, additionally it is possible to obtain the key message of brain function exception, electroencephalogram energy when assessing autism of children
Enough play a role.
When carrying out eeg monitoring to children, electroencephalogram technology is applied mostly in stringenter environment, such as hospital
Clinical treatment or the laboratory of scientific research institutions, even under limitation stringent in this way, the measurement of EEG signals also can be by one
The influence of a little factors, in addition when assessing children, information content is fewer, and feature very clearly, can not obtain corresponding
The characteristic information for tested children provide the self-closing disease Risk Results of rationalization.
Invention content
1. technical problems to be solved
For disturbing factor Interference Detection in the prior art, it is impossible to which the self-closing disease Risk Results for providing rationalization are asked
Topic, the purpose of the present invention is to provide a kind of autism of children risk evaluating systems based on brain electricity, it can realize that elimination is dry
Factor is disturbed, the self-closing disease Risk Results of rationalization can be provided.
2. technical solution
To solve the above problems, the present invention adopts the following technical scheme that.
A kind of autism of children risk evaluating system based on brain electricity, including archipelago eeg signal acquisition system, brain telecommunications
Number go interference processing system, EEG signals clearing system, assessment self-closing disease risk system and display system, the archipelago brain telecommunications
Number acquisition system, EEG signals go to interference processing system, EEG signals clearing system, assessment self-closing disease risk system and display system
System is sequentially connected, and the archipelago eeg signal acquisition system includes analog signal module and digital signaling module, the brain telecommunications
Interference processing system number is gone to include arma modeling, digital signal filter, remove algorithm of interference computer and based on arma modeling
Adaptive predictor, the EEG signals clearing system include feature extraction and disaggregated model, the assessment self-closing disease risk system
System includes first database, the second database and data comparator, the first database and the second database with data ratio
It is connected compared with device, the first database storage acquires the healthy children number of label by archipelago eeg signal acquisition system respectively
It is believed that number and the autism children data-signal of label, the second database storage multiple measurement data in the recent period, by more
Island eeg signal acquisition system acquisition EEG signals handle interference signal using arma modeling, and interference signal passes through digital filtering
Device and algorithm of interference computer preliminary treatment interference signal is gone, using arma modeling and the adaptive predictor based on arma modeling
Effectively evade error caused by interference signal, eliminate disturbing factor, while acquire the healthy youngster of label respectively using the system
Virgin data-signal and autism children data-signal will acquire a large amount of characteristic information and be stored in first database, will adopt in the recent period
The child dataset signal for collecting tested is compared with it, so as to provide the self-closing disease Risk Results of rationalization.
Preferably, the analog signal module includes pre-amplification circuit and filter circuit, passes through EEG preamplifier
Faint EEG signals are amplified, EEG signals are filtered by filter circuit.
Preferably, the filter circuit includes low pass circuit and trap circuit, and trap circuit effectively copes with EEG signals
Hz noise during acquisition.
Preferably, the disaggregated model includes linear classification, neural network, non-linear Bayesian classifier and arest neighbors classification
Device handles various features brain telecommunications respectively by linear classification, neural network, non-linear Bayesian classifier and nearest neighbor classifier
Number, it is convenient for analyzing.
Preferably, the archipelago eeg signal acquisition system acquires non-linear brain telecommunications using nonlinear dynamics theory
Number, EEG signals have the characteristics that Kind of Nonlinear Dynamical System, by nonlinear dynamics theory convenient for acquisition.
It is preferably, described that algorithm of interference computerized algorithm is gone to use regression algorithm, wavelet transformation or independent principal component analysis,
By regression algorithm, wavelet transformation or independent principal component analysis, effective preliminary elimination interference signal.
3. advantageous effect
Compared with the prior art, the advantage of the invention is that：
（1）This programme handles interference letter by archipelago eeg signal acquisition system acquisition EEG signals using arma modeling
Number, interference signal is by digital filter and goes algorithm of interference computer preliminary treatment interference signal, utilizes arma modeling and base
The error caused by the adaptive predictor of arma modeling effectively evades interference signal eliminates disturbing factor, while is using this
System acquires the healthy children data-signal of label and autism children data-signal respectively, will acquire a large amount of characteristic information and deposits
It stores up in first database, the child dataset signal for acquiring tested in the recent period is compared with it, so as to provide the self-closing of rationalization
Disease Risk Results.
（2）Faint EEG signals are amplified by EEG preamplifier, by filter circuit to EEG signals
It is filtered.
（3）Trap circuit effectively copes with Hz noise during eeg signal acquisition
（4）A variety of spies are handled by linear classification, neural network, non-linear Bayesian classifier and nearest neighbor classifier respectively
EEG signals are levied, are convenient for analyzing
（5）EEG signals have the characteristics that Kind of Nonlinear Dynamical System, by nonlinear dynamics theory convenient for acquisition.
（6）By regression algorithm, wavelet transformation or independent principal component analysis, effective preliminary elimination interference signal.
Description of the drawings
Fig. 1 is the system principle diagram of the present invention；
Fig. 2 is the archipelago eeg signal acquisition system block diagram of the present invention；
Fig. 3 is that the EEG signals of the present invention remove interference processing system schematic diagram；
Fig. 4 is the EEG signals clearing system block diagram of the present invention；
Fig. 5 is the functional-block diagram of the comparative evaluation self-closing disease risk of the present invention.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention；Technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes；Obviously；Described embodiment is only part of the embodiment of the present invention；Instead of all the embodiments.It is based on
Embodiment in the present invention；Those of ordinary skill in the art are obtained every other without making creative work
Embodiment；It shall fall within the protection scope of the present invention.
Embodiment 1：
- 5 are please referred to Fig.1, a kind of autism of children risk evaluating system based on brain electricity, including archipelago eeg signal acquisition
System, EEG signals go interference processing system, EEG signals clearing system, assessment self-closing disease risk system and display system, more
Island eeg signal acquisition system, EEG signals remove interference processing system, EEG signals clearing system, assessment self-closing disease risk system
It is sequentially connected with display system, archipelago eeg signal acquisition system includes analog signal module and digital signaling module, brain telecommunications
Interference processing system number is gone to include arma modeling, digital signal filter, remove algorithm of interference computer and based on arma modeling
Adaptive predictor, EEG signals clearing system include feature extraction and disaggregated model, and assessment self-closing disease risk system includes the
One database, the second database and data comparator, first database and the second database are connected with data comparator, and first
Database purchase acquires the healthy children data-signal and label of label by archipelago eeg signal acquisition system respectively
Autism children data-signal, the recent multiple measurement data of the second database storage, is adopted by archipelago eeg signal acquisition system
Collect EEG signals, handle interference signal using arma modeling, interference signal is by digital filter and removes algorithm of interference computer
Preliminary treatment interference signal is effectively evaded interference signal and caused using arma modeling with the adaptive predictor based on arma modeling
Error, eliminate disturbing factor, while acquire the healthy children data-signal of label and self-closing disease youngster respectively using the system
Virgin signal will acquire a large amount of characteristic information and be stored in first database, will acquire tested child dataset signal and its in the recent period
It is compared, so as to provide the self-closing disease Risk Results of rationalization.
Analog signal module includes pre-amplification circuit and filter circuit, by EEG preamplifier to faint brain electricity
Signal is amplified, and EEG signals are filtered by filter circuit, and filter circuit includes low pass circuit and trap electricity
Road, trap circuit effectively cope with Hz noise during eeg signal acquisition, disaggregated model include linear classification, neural network,
Non-linear Bayesian classifier and nearest neighbor classifier pass through linear classification, neural network, non-linear Bayesian classifier and arest neighbors
Grader handles various features EEG signals respectively, is convenient for analyzing, and archipelago eeg signal acquisition system uses Nonlinear Dynamic
Theory of mechanics acquires non-linear EEG signals, and EEG signals have the characteristics that Kind of Nonlinear Dynamical System, pass through nonlinear kinetics
Theory removes algorithm of interference computerized algorithm using regression algorithm, wavelet transformation or independent principal component analysis, by returning convenient for acquisition
Reduction method, wavelet transformation or independent principal component analysis, effective preliminary elimination interference signal.
Operation principle：First with archipelago eeg signal acquisition system respectively to the largely healthy children of label and
The autism children of label carries out eeg signal acquisition, and extracts relevant characteristic signal and carry out classification model construction, is stored in the
One database, when detecting tested children, using archipelago eeg signal acquisition system acquisition EEG signals, at arma modeling
Interference signal is managed, interference signal is by digital filter and goes algorithm of interference computer preliminary treatment interference signal, utilizes ARMA
Model and adaptive predictor based on arma modeling effectively evade error caused by interference signal, will treated EEG signals
It carries out feature extraction and carrying out classification model construction by EEG signals clearing system, be stored in the second database, it will be multiple near
Phase measurement data is compared using data comparator with a large amount of targetedly data models acquired in first database, so as to
Provide the self-closing disease Risk Results of rationalization.
It is described above；It is merely preferred embodiments of the present invention；But protection scope of the present invention is not limited thereto；
Any one skilled in the art is in the technical scope disclosed by the present invention；According to the technique and scheme of the present invention and its
It improves design and is subject to equivalent substitution or change；Should all it cover within the scope of the present invention.
Claims (1)
1. a kind of autism of children risk evaluating system based on brain electricity, it is characterised in that：Including leading eeg signal acquisition system more
System, EEG signals go interference processing system, EEG signals clearing system, assessment self-closing disease risk system and display system, lead more
Eeg signal acquisition system, EEG signals go interference processing system, EEG signals clearing system, assessment self-closing disease risk system and
Display system is sequentially connected, and is led eeg signal acquisition system more and is included analog signal module and digital signaling module, EEG signals
Go interference processing system include arma modeling, digital signal filter, go algorithm of interference computer and based on arma modeling from
Adaptive prediction device, EEG signals clearing system include feature extraction and disaggregated model, and assessment self-closing disease risk system includes first
Database, the second database and data comparator, first database and the second database are connected with data comparator, the first number
According to library storage by lead more eeg signal acquisition system acquire respectively label healthy children data-signal and label from
Close disease child dataset signal, the recent multiple measurement data of the second database storage, by more leading eeg signal acquisition system acquisition
EEG signals handle interference signal using arma modeling, and interference signal is by digital filter and at the beginning of removing algorithm of interference computer
Step processing interference signal, caused by effectively evading interference signal using arma modeling and the adaptive predictor based on arma modeling
Error eliminates disturbing factor, while acquires the healthy children data-signal and autism children of label respectively using the system
Signal will acquire a large amount of characteristic information and be stored in first database, will acquire in the recent period tested child dataset signal with its into
Row compares, so as to provide the self-closing disease Risk Results of rationalization；
The analog signal module includes pre-amplification circuit and filter circuit, by EEG preamplifier to faint brain electricity
Signal is amplified, and EEG signals are filtered by filter circuit, and filter circuit includes low pass circuit and trap electricity
Road, trap circuit effectively cope with Hz noise during eeg signal acquisition, disaggregated model include linear classification, neural network,
Nonlinear Bayesian grader and nearest neighbor classifier, by linear classification, neural network, Nonlinear Bayesian grader and
Nearest neighbor classifier handles various features EEG signals respectively, is convenient for analyzing, and leads eeg signal acquisition system using non-more
Linear power theory acquires non-linear EEG signals, and EEG signals have the characteristics that Kind of Nonlinear Dynamical System, by non-linear
Kinetic theory is convenient for acquisition, and algorithm of interference computerized algorithm is gone to use regression algorithm, wavelet transformation or independent principal component analysis,
By regression algorithm, wavelet transformation or independent principal component analysis, effective preliminary elimination interference signal.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107887027A (en) * | 2017-11-06 | 2018-04-06 | 广州优涵信息技术有限公司 | A kind of self-closing disease diagnosis and therapy system |
| CN108143411A (en) * | 2017-12-13 | 2018-06-12 | 东南大学 | A kind of tranquillization state brain electricity analytical system towards Autism Diagnostic |
| CN109411053B (en) * | 2018-12-12 | 2021-01-15 | 深圳大学 | Old people action rehabilitation training management data model construction method |
| CN110584662A (en) * | 2019-09-17 | 2019-12-20 | 五邑大学 | Self-imposed disease risk quantification method and device based on electroencephalogram information and storage medium |
| CN111671419B (en) * | 2020-06-12 | 2022-02-11 | 山东大学 | Electroencephalogram signal-based epilepsy early detection and identification method and system |
| CN112690775B (en) * | 2020-12-24 | 2022-04-29 | 华中师范大学 | Bayes-based imaging system for focal zone with abnormal brain activity of children |
| CN113679387B (en) * | 2021-08-14 | 2024-03-19 | 合肥巴灵瑞教育科技有限公司 | Early warning system for children growth and development abnormality |
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| US20190209097A1 (en) * | 2015-05-15 | 2019-07-11 | The General Hospital Corporation | System and methods for early diagnosis of autism spectrum disorders |
| US20190008436A1 (en) * | 2015-07-31 | 2019-01-10 | Atentiv Llc | Method and system for monitoring and improving attention |
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| 基于现代谱估计的抑郁症脑电研究;孙名厚;《中国优秀硕士学位论文全文数据库医药卫生科技辑（月刊 ）》;20161215(第12期);全文 * |
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