CN107463908A - It is a kind of that the higher-order of oscillation automatic checkout system for calculating baseline is distributed based on maximum wave crest point - Google Patents
It is a kind of that the higher-order of oscillation automatic checkout system for calculating baseline is distributed based on maximum wave crest point Download PDFInfo
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Abstract
The present invention relates to a kind of higher-order of oscillation automatic checkout system that calculating baseline is distributed based on maximum wave crest point, it is by following module composition：Higher-order of oscillation automatic detection module (1), individuation brain mould prepares module (2), with result it is comprehensive and and report output module (3), wherein, higher-order of oscillation automatic detection module (1) obtains data from the original electroencephalogram of patient, using the algorithm for being maximally distributed wave crest point calculating Dynamic Baseline, after baseline is calculated, data result is obtained；Individuation brain mould prepares module (2) and obtains data from nuclear magnetic resonance and CT scan result, the data result that the data and higher-order of oscillation automatic detection module (1) obtain combines, draw out individuation brain mould jointly, by result it is comprehensive and and report output module (3) output clinical examination report.
Description
Technical field：
It is more particularly to a kind of to be calculated based on the distribution of maximum wave crest point the present invention relates to a kind of medical EEG signals detecting system
The higher-order of oscillation automatic checkout system of baseline.
Background technology：
For epilepsy as a kind of common central nervous system disease, the incidence of disease in China is 0.7%.Though drug therapy is
The first choice of epilepsy therapy, but antiepileptic can only control the epileptic attack of about 60-70% epileptic patient and develop into
For medically intractable epilepsy.At present for medically intractable epilepsy patient, operative treatment is preferred treatment method.And perform the operation into
Can the key that lost be accurately to position Zhi Xian areas.At present usually due to can not accurately position Zhi Xian areas, so that can not be clear and definite
Surgery excision region and can not perform the operation, or surgical effect is bad.
In the more than ten years in past, a large amount of animals and clinical trial certificate：Phase, breaking-out early stage and stage of attack between epileptic attack
The higher-order of oscillation (High frequency oscillations, HFOs) can be recorded in epilepsy sintering (Huo Zhixian areas) to go out
The increase of existing frequency.A series of retrospective clinical is verified:Surgery excision produces the brain of the pathologic higher-order of oscillation
Tissue is closely related with postoperative good final result, sent out again without epilepsy more than the most of patient for higher-order of oscillation brain tissue occur of excision or
Epileptic attack significantly reduces.Have been recognized that can be as the sintering Huo Zhixian areas of localising epileptic for the higher-order of oscillation at present；Evaluation is each
The effect of kind of epilepsy therapy method and judge epilepsy neurological susceptibility a kind of potential biomarker.
In more than ten years in past, the manual analysis higher-order of oscillation is the goldstandard of higher-order of oscillation analysis.But manual analysis method
It is quite time-consuming, and there is inevitable subjectivity, then cause the analysis result between different analysts larger difference occur
It is different.In order that the higher-order of oscillation from now on can clinically extensive use, it is exploitation strength, quick, precisely, objectively automatically analyze detection
System has highly important clinical meaning.A variety of autotests are had been reported that at present, such as：RMS detection methods,
Line-length detection methods, Hilbert detection methods, MNI detection methods, RBF neural detection method, automatic time-frequency
Analyzing detecting method, ARR detection methods etc..The shortcomings that existing higher-order of oscillation Automatic Measurement Technique and brain mould technology of preparing：
1st, the autotest researched and developed at present can not when the higher-order of oscillation or high frequency noise take place frequently accurately establishment of base line.
So as to which automatic higher-order of oscillation precision of analysis can have been had a strong impact on.
Although the 2, there are some brain mould vegetation programs at present, do not have higher-order of oscillation testing result and individual also
Brain mould combines and shows the form of the higher-order of oscillation, so as to be difficult to allow clinician intuitively analysis of high frequency vibration and epilepsy sintering
The relation in Huo Zhixian areas.
There is a unsolved bottleneck problem in prior art, i.e., how smart in the EEG signals that high spectrum activity takes place frequently
Accurately determine baseline.Due to the inaccuracy of baseline determination, the accuracy of higher-order of oscillation detection and analysis has been had a strong impact on.It is conventional in addition
The form of numerical value has provided as a consequence it is difficult to allow clinician to get information about the higher-order of oscillation and epilepsy higher-order of oscillation detection program
Sintering Huo Zhixian areas correlation, which also limits the application of higher-order of oscillation result clinically.
The bottleneck problem for being badly in need of solving for higher-order of oscillation automatic testing method set forth above, this research team propose
A kind of baseline computational methods of brand new ideas -- utilize the algorithm for being maximally distributed wave crest point calculating Dynamic Baseline.The algorithm carries significantly
The high accuracy of establishment of base line in the EEG signals that high frequency seizure frequency differs, so as to significantly improve autotest
Accuracy.We number have developed simultaneously a kind of automatically generates individual according to the scanning of patient's cerebral magnetic resonance and CT scan result
Change brain mold process sequence, and the result of higher-order of oscillation autotest is directly represented on individual's brain mould of generation, group
Into a set of higher-order of oscillation automatic checkout system.There is provided a kind of accurate disease for clinician, the higher-order of oscillation is examined automatically easily to operate
Examining system.
The content of the invention：
Therefore, the present invention provides a kind of higher-order of oscillation automatic checkout system for being distributed based on maximum wave crest point and calculating baseline,
The system, including with lower module：
Higher-order of oscillation automatic detection module (1), individuation brain mould prepare module (2), and result it is comprehensive and and report output mould
Block (3), wherein, higher-order of oscillation automatic detection module (1) obtains data from the original electroencephalogram of patient, using being maximally distributed wave crest point
The algorithm of Dynamic Baseline is calculated, after baseline is calculated, obtains data result；Individuation brain mould prepares module (2) and is total to from nuclear-magnetism
Shake and CT scan result obtains data, the data result that the data and higher-order of oscillation automatic detection module (1) obtain combines, jointly
Draw out individuation brain mould, by result it is comprehensive and and report output module (3) output clinical examination report.
Wherein, higher-order of oscillation automatic detection module (1) from electroencephalogram after baseline is calculated, by the width according to baseline
Value, optimize higher-order of oscillation detection threshold value, start higher-order of oscillation autotest, the quantity of the automatic detection higher-order of oscillation, continue
Time and energy.
Wherein, the result that higher-order of oscillation automatic detection module (1) obtains prepares module (2) by individuation brain mould and tied with it
Fruit is combined, then by result it is comprehensive and and report output module (3) higher-order of oscillation testing result of automatic detection is shown automatically
It is shown in the corresponding brain area of individuation brain mould.Wherein, higher-order of oscillation automatic detection module (1) is using maximum distribution wave crest point meter
The algorithm of Dynamic Baseline is calculated, the algorithm is through following five steps：
(1) filter,
If the EEG signals for needing to analyze are fo (t), wherein t is moment point (t>0), primary signal fo (t) is entered first
Row bandpass filtering, filtered signal f (x) is obtained, the setting scope of wave filter is the required higher-order of oscillation frequency for calculating baseline
Scope；
(2) calculate extreme point,
F^'(t is obtained to filtered signal f (t) derivation), next solve equation：F^'(t)=0
If equation root is r, signal f^'(t can be obtained) extreme point, Extremum (r)；
(3) sort,
The absolute value of obtained extreme point is ranked up, obtains the order description of signal amplitude distribution：Order (r)=
Sort (| Extremum (r) |), wherein sort is sequence from small to large, | * | it is absolute value；
(4) linear fit,
For EEG signals, if the high-energy component (high frequency event and high-energy high-frequency noise) in signal is not more than always
Linearly interval occurs in the 40% of body signal, extreme point sequencing signal Order (r) 30% to 60% scope, next right
30% to 60% scope of Order (r) signals carries out linear fit, obtains straight line：Y=a × r+b, due to high-energy component simultaneously
The calculating of straight line parameter is not involved in, so the baseline with high-frequency signal is had strong correlation by the parameter a and b of straight line；
(5) baseline estimations,
By straight line parameter a and b, obtain and (be set to r_0) when r institutes value is 100% point, y value and signal base line
Value has fixed coefficient relation, if the coefficient is G, the final baseline for estimating the higher-order of oscillation is Base=G × (a × r_0+b), G
Eeg data test can be passed through to obtain；Below by way of Fig. 4, module map of the invention, the group of each module of the detailed description present invention
Part, the connected mode of each component, operation principle and working method, and use and operating method：
Higher-order of oscillation automatic detection module (1) includes following procedure：
1. application maximum distribution wave crest point calculates the program of Dynamic Baseline.
2. find the traversal program of optimal threshold.
3. the program of the higher-order of oscillation is detected according to optimal threshold.
Individuation brain mould, which prepares module (2), includes following procedure：
1. brain function mapping software (Brain function mapping, BMP), extract the cerebral cortex in image data
With grey matter information, three-dimensional brain mould is fused into.
2. by carrying out registration for nuclear magnetic scanning and CT scan, intracranial electrode is accurately marked on individual brain mould
Program.
As a result it is comprehensive and and report output module (3) include following procedure：
1. brain function mapping software, the automatic result of the higher-order of oscillation can be projected and mark pair in individuation brain mould by this program
Answer in electrode points and brain area.
2. form the image report (high frequency oscillation prompting De Zhixian areas can be delimited if necessary) of higher-order of oscillation distribution situation.
The task that module 1 is mainly engaged in:
1) band logical (80-200Hz and 200-500Hz) filtering is carried out automatically.
2) algorithm being distributed according to maximum wave crest point, calculates Dynamic Baseline.
3) optimal parameter that basis has been set up, quantity, duration and the energy of the higher-order of oscillation are detected.
Module 2 is mainly from task of being：
1) by the nuclear magnetic resonance of patient and CT scan result, brain mould figure is fused into after positioning is calibrated.
2) higher-order of oscillation quantity that detects module 1, duration and energy mark are in corresponding electrode area and right
The brain area position answered.
The main task of module 3：
1) result that module 2 marks is printed to clinical examination report in the form of three-dimensional brain mould figure.
2) higher-order of oscillation quantity, duration and energy are gone out into report in the form of sorting.
3) networked with hospital data management system, automatic uploading detection report.
The present invention is the baseline computational methods by a kind of brand new ideas -- calculate dynamic base using wave crest point is maximally distributed
The method of line is come in the EEG signals of different high spectrum activity frequencies, accurately determines Limit Distribution, so as to improve the higher-order of oscillation
The accuracy of autotest.
High frequency automatic checkout system is combined by the present invention with patient's brain mould preparation procedure, the brain mould in patient of individuation
The upper distributed areas that the higher-order of oscillation is presented.
The baseline of EEG signals is accurately determined by brand-new baseline confirmation method, so as to improve Zi to detecting system
Accuracy.A kind of brand-new higher-order of oscillation automatic checkout system is formed with reference to brain mould preparation procedure.The system can be with report
Form will automatically analyze that result is simple, is legibly presented to clinician.
The theory of the computational methods of the present invention is summarized as follows：Because high spectrum activity is often more of short duration event, so
Although the lead to be taken place frequently in EEG signals in high frequency, baseline is also the main component in EEG signals.By maximum in brain electricity
The distribution situation of wave crest point is distributed, we can make a distinction baseline composition with radio-frequency component.
Traditional higher-order of oscillation autotest, being frequently run onto in the EEG signals that high spectrum activity takes place frequently can not be accurate
Establishment of base line bottleneck problem.The higher-order of oscillation autotest that we develop significantly improves to be produced in different high spectrum activities
The accuracy of baseline determination in the EEG signals of raw frequency, the accurate of higher-order of oscillation autotest is substantially increased so as to bright
Property.Individual's brain mould technology of preparing is combined together by we with higher-order of oscillation autotest in addition, forms height
Frequency vibration swings automatic checkout system.The system can be quick, objective, accurate, concise the report higher-order of oscillation caused by quantity, energy
Amount, frequency and position, the strong evidence for determining Zhi Xian areas can be provided for clinician.And Zhi Xian areas are accurately positioned, again may be used
Significantly to improve Epilepsy Surgery success rate of operation.
The key problem in technology point of the present invention is：(1) utilize and be maximally distributed wave crest point calculating dynamic Dynamic Baseline.(2) basis
The brain mould software for drawing that the NMRS result of patient is combined with CT scan result.(3) by the high frequency vibrating of automatic detection
Swing the corresponding brain area technology that testing result is shown in individuation brain mould automatically.
Beneficial effects of the present invention are further illustrated below by way of experimental data：
We have chosen 37 patients for needing to make epileptogenic focus resection operation, and all patients implant cranium when assessing in the preoperative
Interior electrode simultaneously have recorded 3-7 days EEG signals.We are extracted the EEG signals of phase between the epileptic attack of slow wave sleep phase at random.
After bandpass filtering (80-200Hz and 200-500Hz), the EEG signals of 5 seconds have been randomly selected, will be each in signal
The absolute value of wave crest point makes a brain wave peak dot distribution curve (peak point according to being arranged in order from small to large
Distribution curve, PPDC).We have found that the value part by a narrow margin (＞ 60%) of curve is in almost a straight line, and high-amplitude
Value part curve has rising.PPDC prepared by the pink noise according to simulation EEG signals almost in line, in the absence of height
The obvious rise phenomenon of amplitude.It is considered that the EEG signals of no high spectrum activity should linear state, and rise part be
Caused by high spectrum activity or noise.So we have selected the point that straight line amplitude 5% is begun to ramp up and deviateed in curve
For separation (flex point).It is high spectrum activity or noise after flex point it is considered that being baseline before flex point.So as to which we can
To regard the average amplitude of all baselines as baseline (see Fig. 1).
After being determined that brain wave peak dot distribution curve determines baseline profile, we are in 7 epileptic's encephalic brain electricity hairs
The deep sleep phase of phase (away from front and rear epileptic attack at least two more than hour) intercepts 5 minutes brain electricity of 10 leads at random between work
Signal.Artificial detection higher-order of oscillation result, for detecting 3687 ripples and 1059 quick ripples.Then we set up one
The traveling time window of individual 5 seconds, Dynamic Baseline is formulated according to wave crest point distribution curve in this dynamic time window.And then I
According to limit amplitude make judge high frequency caused by Low threshold (3-7 standard deviation of baseline amplitude) and high threshold (9-11
Individual standard deviation), at least eight wave crest point reaches Low threshold, and 3-8 wave crest point reaches high threshold and be determined as the higher-order of oscillation.We
The method for applying traversal, with a fixed step size (0.5 standard deviation, 1) 0.5 standard deviation and confirmation optimal parameter.We provide
Two high frequency interval of events merge into a higher-order of oscillation less than 25 seconds (ripples) and 10 seconds (quick ripple).By 7 trouble
The traversal detection for amounting to 70 leads of person, the Optimal Parameters that we draw are ripple：8 wave crest points are more than baseline amplitude
3.5 standard deviations, while 6 wave crest points are more than 9 standard deviations of baseline amplitude.Quick ripple：8 wave crest points shake more than baseline
3 standard deviations of width, while 4 wave crest points are more than 10.5 standard deviations of baseline amplitude.By our automatic detection algorithm with
Manual analysis Comparative result shows that our automatic detection result is respectively for ripple, sensitivity and specificity：71% He
75%；For quick ripple, sensitivity and specificity are respectively：66% and 84%.By with opening eeg data and open code
Four kinds of traditional automatic testing method (short-time energy methods；Line length is analyzed in short-term；Hilbert envelope method；MNI methods) it is compared
Afterwards, our method integration capability is better than the above method.
After the automatic detection for completing the higher-order of oscillation, in order to more easily, intuitively give one result of clinician, I
Team have developed using patient cerebral nucleus magnetic oscillation scanning result and CT scanning results fusion brain mould software for drawing, should
Software can with individuation making every patient brain mould figure, and on brain mould figure accurately display intracranial electrode position (see
Fig. 2).(each multi-channel high frequency vibrates total the result that then our autotest can analyze the automatic higher-order of oscillation
Quantity, total duration and gross energy are shown in position where brain mould and electrode in the form of a color).To prompt clinician can
The cause epilepsy region of energy (see Fig. 2).Make skill so as to form a kind of mould novel high-frequency automatic detection algorithm and individuation brain
The automatic higher-order of oscillation analysis system that art is combined as a whole.
Brief description of the drawings：
Fig. 1, maximum distribution wave crest point calculate base-line method A) our baseline determination program.First row：By bandpass filtering
The EEG signals and wave crest point of latter second are shown (blue point is wave crest point).Second row：The crest made according to wave crest point
Distribution curve (PPDC, blue solid lines).The first half of curve is linear, and blue dotted line is the extended line of anterior straight line.It is and blue
The circle of color is differentiation baseline and the turning point of high spectrum activity.3rd row：After finding turning point on PPDC, turnover
It is baseline before point, is high spectrum activity part after turning point.After different color marks, red crest is baseline, blueness
Crest is high spectrum activity.Then, we are using the average amplitude of baseline as baseline.4th row：It is us according to baseline width
Value has calculated the height of the measure higher-order of oscillation, low and individual threshold value (red line is high threshold, and green line is Low threshold).(B) in patient's cranium
PPDC is verified on interior EEG signals.Upper figure is by 80-200Hz bandpass filterings, and figure below is by 200-500Hz bandpass filterings
The PPDC made afterwards.As a result show all flex points after the 60% of PPDC distributions.(C) PPDC ideographs.Three curves
Represent the difference containing high spectrum activity composition in EEG signals.Red highs activity is minimum, and at most, green is placed in the middle for blueness.
Prepared by Fig. 2, brain mould, electrode positioning and higher-order of oscillation result display schematic diagram：(A) prepared by nuclear magnetic resonance result
Individual patients brain mould.(B) be by merging patient's nuclear magnetic scanning and CT scan after, position intracranial electrode on brain mould.(C)
This autotest will automatically analyze after higher-order of oscillation testing result be expressed in automatically individual's brain mould encephalic electricity
On pole and corresponding brain area.
Fig. 3, the higher-order of oscillation result of automatic detection are presented in individual's brain mould and Operative Range automatically.(A、
B, C) total quantity of the higher-order of oscillation, total duration, gross energy are represented respectively.Red line region is that we are thought by high-frequency detection
Need the cause epilepsy tissue regions cut off.Functional areas in green line.LSF, left superior frontal gyrus；LIF, Broca's convolution；LC, left centre LP, it is left
Top；LO, left pillow.
Fig. 4, module map of the invention
Embodiment：
The present invention is further illustrated by the following examples.
Embodiment 1
Our depths in 7 epileptic's encephalic brain electricity interictals (away from front and rear epileptic attack at least two more than hour)
Spend 5 minutes EEG signals that sleep period intercepts 10 leads at random.Artificial detection higher-order of oscillation result, detects 3687 altogether
Ripple and 1059 quick ripples.The module (1) of these EEG signals typings present invention, the module set up the shifting of 5 seconds
Dynamic time window, the program for calculating Dynamic Baseline using maximum branch's wave crest point in this dynamic time window find dynamic base
Line.And then we according to limit amplitude make judge high frequency caused by Low threshold (3-7 standard deviation of baseline amplitude) and height
The scope of threshold value (9-11 standard deviation), at least eight wave crest point reach Low threshold, and 3-8 wave crest point reaches high threshold and judged
For the higher-order of oscillation.The program that we apply, with a fixed step size (0.5 standard deviation, 1) 0.5 standard deviation and searching optimal threshold.
We provide that two high frequency interval of events merge into a higher-order of oscillation less than 25 seconds (ripples) and 10 seconds (quick ripple).
Detected by the traversal for amounting to 70 leads of 7 patients, the optimal threshold that we draw is ripple：8 wave crest points are more than
3.5 standard deviations of baseline amplitude, while 6 wave crest points are more than 9 standard deviations of baseline amplitude.Quick ripple：8 wave crest points
More than 3 standard deviations of baseline amplitude, while 4 wave crest points are more than 10.5 standard deviations of baseline amplitude.Then in optimal threshold
On the basis of value result is obtained using the program of the detection higher-order of oscillation.
Using the brain function mapping software in individuation brain mould module (2), extract in the imaging of patient's brain magnetic resonance imaging and CT
Cerebral cortex and grey matter information, be fused into three-dimensional brain mould.Using the program of encephalic electroencephalographic electrode registration, according to electrode in CT
With the three-dimensional coordinate of the three-dimensional brain mould of fusion, electrode and three-dimensional brain mould are subjected to autoregistration.
It is total quantity that each multi-channel high frequency for obtaining automatic detection module (1) using brain function mapping software vibrates, total
On Different electrodes that duration, gross energy are shown in individuation brain mould module (2) with different colors and Different brain region,
Represented respectively from high level to low value from red to blueness.Then output module (3) automatically forms the figure of higher-order of oscillation distribution situation
As report.Fig. 3 shows the higher-order of oscillation result that an epileptic detects using our higher-order of oscillation automatic checkout system,
And it is shown on his brain mould.The higher-order of oscillation that high quantity, duration and energy can be seen is distributed in left volume top and pillow
Leaf, although occipital lobe, there is also the higher-order of oscillation of more high-energy, because occipital lobe is primary vision area, discriminating is physiological herein
The higher-order of oscillation or the pathologic higher-order of oscillation are very difficult.According to traditional preoperative evaluation method, the region of left volume top is recognized
To be epilepsy Zhi Xian areas.So we have carried out selective left volume top selectivity cortex resection to patient, functional areas are still given
Give reservation.Most of higher-order of oscillation region with high-energy is removed in art.In Follow-up After 1 year, patient's epilepsy hair
Disappear.
Comparative example 1,
Table 1,2 lists our automatic monitoring method and other four kinds more conventional traditional automatic monitoring methods gained
To result compare.These four methods are respectively：Short-time energy method；Line length is analyzed in short-term；Hilbert envelope method；MNI methods.
Our detection method is substantially better than other four kinds of methods on the synthesis result of sensitivity and specificity.
The result of the present invention and the result of prior art carry out data comparison, illustrate that the present invention is better than prior art.
The results contrast of the automatic testing method of the present invention of table 1 and other methods detection ripple
Note：CI：95% credibility interval (95%confidence intervals).
The automatic testing method of the present invention of table 2 detects the results contrast of quick ripple with other methods
Note：* HIL detection methods are not detected by quick ripple；CI：95% credibility interval (95%confidence
intervals)。
Claims (9)
1. a kind of be distributed the higher-order of oscillation automatic checkout system for calculating baseline based on maximum wave crest point, it is characterised in that by following
Module composition：Higher-order of oscillation automatic detection module (1), individuation brain mould prepare module (2), and result it is comprehensive and and report output mould
Block (3), wherein, higher-order of oscillation automatic detection module (1) obtains data from the original electroencephalogram of patient, using being maximally distributed wave crest point
The algorithm of Dynamic Baseline is calculated, after baseline is calculated, obtains data result；Individuation brain mould prepares module (2) and is total to from nuclear-magnetism
Shake and CT scan result obtains data, the data result that the data and higher-order of oscillation automatic detection module (1) obtain combines, jointly
Draw out individuation brain mould, by result it is comprehensive and and report output module (3) output clinical examination report, wherein the higher-order of oscillation from
Dynamic detection module (1) calculates the algorithm of Dynamic Baseline, the algorithm, through following five steps using maximum distribution wave crest point
Suddenly：
(1) filter,
If the EEG signals for needing to analyze are fo (t), wherein t is moment point (t>0) band, is carried out to primary signal fo (t) first
Pass filter, filtered signal f (x) is obtained, the setting scope of wave filter is the required high frequency oscillation frequency range for calculating baseline；
(2) calculate extreme point,
F^'(t is obtained to filtered signal f (t) derivation), next solve equation：F^'(t)=0
If equation root is r, signal f^'(t can be obtained) extreme point, Extremum (r)；
(3) sort,
The absolute value of obtained extreme point is ranked up, obtains the order description of signal amplitude distribution：
Order (r)=sort (| Extremum (r) |), wherein sort is sequence from small to large, | * | it is absolute value；
(4) linear fit,
For EEG signals, if the high-energy component (high frequency event and high-energy high-frequency noise) in signal is not more than overall signal
40%, linearly interval occurs in extreme point sequencing signal Order (r) 30% to 60% scope, next to Order (r)
30% to 60% scope of signal carries out linear fit, obtains straight line：Y=a × r+b, because high-energy component does not participate in
The calculating of straight line parameter, so the baseline with high-frequency signal is had strong correlation by the parameter a and b of straight line；
(5) baseline estimations,
By straight line parameter a and b, obtain and (be set to r_0) when r institutes value is 100% point, y value and signal base line value have
There is fixed coefficient relation, if the coefficient is G, the final baseline for estimating high frequency oscillation is Base=G × (a × r_0+b), and G can be with
Test and obtain by eeg data.
2. automatic checkout system according to claim 1, it is characterised in that wherein, higher-order of oscillation automatic detection module (1)
From electroencephalogram after baseline is calculated, by the amplitude according to baseline, optimize higher-order of oscillation detection threshold value, start the higher-order of oscillation
Autotest, quantity, duration and the energy of the automatic detection higher-order of oscillation.
3. automatic checkout system according to claim 1, it is characterised in that wherein, higher-order of oscillation automatic detection module (1)
Obtained result prepares module (2) by individuation brain mould and is combined with its result, then by result it is comprehensive with and report output
The higher-order of oscillation testing result of automatic detection is shown in the corresponding brain area of individuation brain mould by module (3) automatically.
4. automatic checkout system according to claim 1, it is characterised in that wherein, higher-order of oscillation automatic detection module (1)
Including following procedure：
1. application maximum distribution wave crest point calculates the program of Dynamic Baseline；
2. find the traversal program of optimal threshold；
3. the program of the higher-order of oscillation is detected according to optimal threshold.
5. automatic checkout system according to claim 1, it is characterised in that wherein, individuation brain mould prepares module (2) bag
Include following procedure：
1. brain function mapping software, cerebral cortex and grey matter information in image data are extracted, is fused into three-dimensional brain mould；
2. by carrying out registration, journey intracranial electrode being accurately marked on individual brain mould for nuclear magnetic scanning and CT scan
Sequence.
6. automatic checkout system according to claim 1, it is characterised in that wherein, as a result comprehensive and and report output module
(3) following procedure is included：
1. brain function mapping software, the automatic result of the higher-order of oscillation can be projected and mark the corresponding electricity in individuation brain mould by this program
In limit and brain area；
2. form the image report (high frequency oscillation prompting De Zhixian areas can be delimited if necessary) of higher-order of oscillation distribution situation.
7. automatic checkout system according to claim 1, it is characterised in that wherein, higher-order of oscillation automatic detection module (1)
Method of work it is as follows:
1) band logical (80-200Hz and 200-500Hz) filtering is carried out automatically；
2) algorithm being distributed according to maximum wave crest point, calculates Dynamic Baseline；
3) optimal parameter that basis has been set up, quantity, duration and the energy of the higher-order of oscillation are detected.
8. automatic checkout system according to claim 1, it is characterised in that wherein, individuation brain mould prepares module (2)
Method of work is as follows：
1) by the nuclear magnetic resonance of patient and CT scan result, brain mould figure is fused into after positioning is calibrated；
2) higher-order of oscillation quantity that detects module 1, duration and energy mark are in corresponding electrode area and corresponding
Brain area position.
9. automatic checkout system according to claim 1, it is characterised in that wherein, as a result comprehensive and and report output module
(3) method of work is as follows：
1) result that module 2 marks is printed to clinical examination report in the form of three-dimensional brain mould figure；
2) higher-order of oscillation quantity, duration and energy are gone out into report in the form of sorting；
3) networked with hospital data management system, automatic uploading detection report.
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