CN102512161A - Intraoperative motor area function localization system based on cortex electroencephalogram mu rhythm wavelet analysis - Google Patents
Intraoperative motor area function localization system based on cortex electroencephalogram mu rhythm wavelet analysis Download PDFInfo
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Abstract
The invention discloses an intraoperative motor area function localization system based on cortex electroencephalogram mu rhythm wavelet analysis, which collects cortex electroencephalogram signals by embedding an electrode array. The cortex electroencephalogram signals are treated by an amplification filter and output into a signal processing module through an analog to digital (A/D) converter. An electroencephalogram signal pretreatment unit of the signal processing module can previously treat and filter data collected by all electrodes through resolving and reconfiguration algorithm of the wavelet analysis. A mu rhythm feature extraction unit and a pattern classification unit perform feature extraction and classification based on mu rhythm feature extraction and classification algorithm to recognize special properties of all electrodes to finally process and output motor area localization images. The localization system can accurately and quickly detect motor area electroencephalogram signals and output brain motor area function localization images without wound. Through specificity analysis on brain motor area cortex electroencephalogram signals, clinical application of function localization in brain cortex motor area operation of human neurosurgery is achieved.
Description
Technical field
The present invention relates to the medical electronics instrument field, be specifically related to a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis.
Background technology
Brain function district pathological changes
,Mainly refer to be positioned at the tumor in motion, sensation and language district; Vascular malformation and epileptogenic focus, its sickness rate reports that at the investigation of wide scope of China's tissue only the prevalence of epilepsy just has 8 ‰ by World Health Organization (WHO), China has epileptic patient more than 1,000 ten thousand people now; Wherein medically intractable epilepsy accounts for about 30% of epileptic patient; China has 3,000,000 intractable epileptic patient to need operative treatment at present, and this does not also comprise the low level glioma that is positioned at functional areas, metastatic tumor; Former benign tumor, cavernous hemangioma and arteriovenous malformotion etc.Brain function district pathological changes is serious threat people's life not only, and have a strong impact on patient's existence and quality of life, and the individual who causes simultaneously, society and financial burden all are permanent and huge, have become serious society, economy and humanistic care problem.
The neurosurgery treatment is one of first-selected Therapeutic Method of brain function district pathological changes; Confirm cerebral nerve brain domain border through the location, functional areas; The help doctor excises focus to greatest extent and controls growth of tumor and recurrence, protects perilesional normal cerebral tissue as much as possible simultaneously, avoids function of nervous system's infringement; Keep normal function of nervous system, be related to the life quality of patient's postoperative.How in the art accurately in real time " brain domain " location be exactly the key of this type of operation.
At present, the method for neural cortex (motor region) functional localization mainly comprises technological, the methods such as neuroimaging is technological, neural electrophysiological technique of microneurosurgery.
The classical functional localization of dissecting is significant for clinical medicine, but certain error is arranged, because the occupy-place effect of individual variation and tumor, causes that functional areas pass and reinvent, and the classical functional localization error of dissecting can reach 20mm.
Rely on the high-resolution spiral CT and the functional type magnetic resonance (f-MRI) of image technology; And the many cortex dissect physiologies of can accomplishing of single photon emission computerized tomography,SPECT (SPECT), positron emission tomography scanning (PET), magneticencephalogram (MEG) and operation guiding system are located; But there is certain false positive in the iconography method, still can not monitor the state of operation process and definite brain function in real time.Functional type magnetic resonance (f-MRI) is that blood oxygen level carries out functional localization in the dependence cerebral blood flow, and the maximum error that can reach 20mm appears in the blood supply meeting that pathological changes influences cortex.Positron emission tomography scanning (PET) system also can position the active zone of brain metabolism, but only there is 65% coincidence rate the functional areas that it and electrophysiological stimulation are shown.
Can confirm the cortex and the location, subcortical function district of brain functioies such as motion, sensation, language even memory in real time based on stimulus of direct current art under cortex or the cortex in the art of electrophysiological technique; Be the most accurate, believable at present brain domain localization method commonly used, can reach about 5 mm based on the degree of accuracy of stimulus of direct current art under cortex or the cortex in the art of electrophysiological technique; But exist electricity irritation possibly damage cerebral cortex, trigger problems such as epilepsy and second operation, and the operating time reach 0.5 to several hours.
The defective of above-mentioned functions district localization method has shown in the neurosurgery treatment practice; The relation of functional structure and pathological changes can not differentiated and grasp to the functional localization technology of traditional operation fully; Very easily when the excision focus, cause the brain function structural damage, the permanent function of nervous system infringement complication of traditional operation is 13-27% according to statistics.In addition, because severe complication appears in functional areas disease surgery easily, also make the operative doctor excision not positive, usually appeasing property excision is merely 43% like the excision fully and time full resection rate of low level glioma.So not only make the pathological changes aftertreatment become difficult, and cause the recurrence of disease or symptom to be difficult to control easily, have a strong impact on the treatment prognosis.
This shows that present neural cortex (motor region) functional localization method is in speed, accurately and aspect the safety can not satisfy the brain domain operation needs fully.How can be in art accurately, fast, noinvasive, even non-wake-up states down the location brain domain be to perplex clinical and rationale problem neuromedicine research always, need to be resolved hurrily.
Do not see as yet at present both at home and abroad have a kind of based on motor region functional localization systematic account in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; Simultaneously, does not still have both at home and abroad yet use clinically based on motor region functional localization system in the art of the electric mu rhythm and pace of moving things of cortex brain wavelet analysis.Therefore research and development have independent intellectual property right based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; Realize accurate, quick, noninvasive brain motor region functional localization; To help the doctor to excise focus to greatest extent; Protect simultaneously the normal brain activity function as much as possible, improve patient's postoperative life quality, to future big cerebral surgery operation have great application value.Simultaneously, the biomechanism scientific research of locating senior cognitive function cortex for next step cortex brain electricity provides new technical method means, and big senior cognition functions of brain scientific research in future is significant.Have huge social and economic benefits prospect.
Summary of the invention
The objective of the invention is to the defective to prior art, is principle with the motor region specificity brain electricity mu rhythm and pace of moving things, and combined with wavelet transformed discloses a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis.This system can be accurately, fast, noinvasive ground detects motor function district EEG signals and imports; And the output of completion brain motor region functional localization figure; Through the specificity analyses of the brain motor region cortex EEG signals mu rhythm and pace of moving things, realize that accurate, quick, the non-invasive clinical of nerve system of human body motor area of cerebral cortex functional localization used.
The mu rhythm and pace of moving things is the specificity brain wave rhythm of the sensorimotor area cortex of brain; The real motion of limbs or imagery motion can cause the relevant desynchronization of incident (ERD) and the incident related synchronizationization (ERS) of the mu and the beta rhythm and pace of moving things in the sensorimotor cortex zone, and the spatial distribution of the ERD/ERS of different limb motions on the cortical motor areas also meets the characteristic that the body specific region distributes.Therefore, through detecting the specificity brain electricity mu rhythm and pace of moving things that exists in the cortex motor function district, and the spatial distribution of the ERD/ERS that when limb motion, produces on cortex, can be static locate the spatial distribution in cortex motor function district with detection of dynamic.Wavelet transformation has many resolution characteristics, utilizes the decomposition and reconstruction fast algorithm of Mallat from motor region brain electricity, to extract the mu rhythm and pace of moving things, for the motor region specificity EEG signals mu rhythm and pace of moving things detects the strong instrument that provides.
Based on above-mentioned principle, the technical scheme that the present invention adopted is described below:
A kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; Comprise the eeg signal acquisition module; Signal processing module; Functional localization map output module, said signal processing module comprise EEG signals pretreatment unit, mu prosodic feature extraction unit and pattern classification unit; The EEG signals that the eeg signal acquisition module is gathered; Carry out pretreatment filtering via the EEG signals pretreatment unit; Be sent to mu prosodic feature extraction unit and extract specificity mu prosodic feature; Classify through the pattern classification unit again, at last through location, functional areas map output module feedback positioning result.
Said eeg signal acquisition module comprises implanted electrode, amplifilter and A/D transducer; Implanted electrode is gathered EEG signals; Carry out amplification filtering via amplifilter and handle, convert EEG signals into digital signal through A/D converter then, be input to signal processing module at last.
Said implanted electrode is the dura mater platinum electrode, comprises platinum 6*8 or 8*8 electrod-array, and electrode diameter is 4mm, and the adjacent electrode spacing is 10mm.Implanted electrode is placed on people's the cerebral cortex.Amplifilter and A/D transducer adopt the Synamps2 amplifier, are used for the amplification and the digitized of electrode detection signal.
The pretreatment filtering of said EEG signals pretreatment unit comprises multiple dimensioned decomposition.The discrete db3 wavelet transformation of said multiple dimensioned decomposition utilization carries out 7 layers of wavelet decomposition, and the decomposition and the restructing algorithm of the small echo Mallat algorithm of employing are seen formula (3).Said mu prosodic feature extraction unit extracts d6 monolayer detail coefficients, the reconstruct of counting entirely then, and the signal Sd6 after its reconstruct exports as the mu rhythm and pace of moving things.Said pattern classification unit is that characteristic threshold value is/not classification the identification specificity electrode to the mu rhythm and pace of moving things with 40%.
Wherein,
H,
GBe the wavelet decomposition wave filter in the time domain,
h,
gBe the wavelet reconstruction wave filter in the time domain; T is a discrete-time series,
t=1,2 ...,
N jBe the decomposition number of plies,
j=1,2 ...,
J,
JBe the decomposition degree of depth,
f(
t) be primary signal.
a j For
f(
t)
jThe wavelet coefficient of the approximate part of layer;
d j For
f(
t)
jThe wavelet coefficient of layer detail section.
During each list band signal of reconstruct, only extract the approximate or detail coefficients of monolayer, all the other coefficients put 0, then to the reconstruct of counting entirely of this monolayer coefficient.Formula (4) is seen in the calculating of reconstruction signal characteristic quantity (motion event front and back ERD time self-energy takes place than ERD).
Wherein, ER is the quadratic sum of each sampling point value of each the sub-band reconstruction signal in the ERD time window before the motion event, and EA is the quadratic sum of each sampling point value of each the sub-band reconstruction signal in the ERD time window behind the calculating motion event.
The motion specific function district network for location of location, said functional areas map output module output; Be that the specificity electrode coordinate of discerning with the pattern classification unit is a boundary point match boundary curve; That is: motion specific function district network for location, the zone that closed curve surrounds are motion specific function district.
The relative prior art of the present invention has following advantage and effect:
(1) specificity detects the accuracy height: the incident ERD specificity that the present invention is based on the motor function district mu rhythm and pace of moving things; Rational feature band, eigenvalue have been selected; And feature extraction and sorting algorithm have the reliable detection principle; Guaranteed that fundamentally specificity detects accuracy, its specificity detects accuracy and reaches 78%-100%.
(2) the electrode detection precision is high: the electrode that system adopts has distance between the implanted electrode of 4mm diameter and 10mm, has higher space and frequency resolution, and neuronic electrical activity information near the 5mm radius of electrode centers point can be provided.The essence of characteristic threshold value is near detected smallest effective characteristic quantity in 5mm radius electrode centers point.Therefore space, the location microcosmic degree of accuracy of calculating native system can reach 5 mm.Compare with stimulus of direct current art under cortex in the art or the cortex, native system has further improved the detection degree of accuracy.
(3) detection speed is fast: native system is that the specificity brain electricity in motor function district is a detected object with the spontaneous brain electricity mu rhythm and pace of moving things, and the sampling experimental period of the ERD of the spontaneous brain electricity mu rhythm and pace of moving things and time window are 4 seconds, and therefore, sample rate is 4 seconds in theory.Consider that reliability adopts the common method of judging of sampling experimental result 10 times, add the time of Computer Processing, a functional localization of native system detection time is 60 seconds.Reaching 0.5 to several hours with the stimulus of direct current art operating time under cortex in the art or the cortex compares; Native system has greatly improved detection speed; Greatly reduced doctor's operating time and patient's misery, saved huge man power and material, had good economy and humanistic care and be worth.
(4) detection is non-invasive: native system extracts the passive detection mode that the spontaneous brain electricity mu rhythm and pace of moving things adopts EEG signals, does not have the wound that initiatively stimulation causes.Avoid in the art under cortex or the cortex stimulus of direct current art possibly damage cerebral cortex, triggered problem such as epilepsy.Greatly reduced doctor's operating time and patient's misery, saved huge man power and material, had good economy and humanistic care and be worth.
Description of drawings
Fig. 1 is a motor region brain function navigation system structure chart.
Fig. 2 is an eeg signal acquisition system module structure chart.
Fig. 3 is the wavelet decomposition and the reconstruct of primary signal.
Fig. 4 is the wavelet transform filtering of primary signal.
Fig. 5 is a motion specific function district network for location.
The specific embodiment
Below in conjunction with accompanying drawing and embodiment the present invention is described further, but enforcement of the present invention is not limited thereto.
A kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; As shown in Figure 1; Comprise the eeg signal acquisition module; Signal processing module, location, functional areas map output module, signal processing module comprises EEG signals pretreatment unit, mu prosodic feature extraction unit and pattern classification unit.The composition of eeg signal acquisition module is as shown in Figure 2, comprises implanted electrode, amplifilter and A/D transducer.Cortex EEG signals ECoG gathers through the dura mater bottom electrode array of implanted electrode in this system, carries out amplification filtering via amplifilter and handles, and converts EEG signals into digital signal through A/D converter then, is input to signal processing module again; The EEG signals pretreatment unit of signal processing module is through the decomposition and reconstruction algorithm of wavelet analysis; Data to each electrode collection are carried out pretreatment filtering; Be sent to mu prosodic feature extraction unit and extract specificity mu prosodic feature; Classify through the pattern classification unit again, accomplish the functional areas network for location through location, functional areas map output module at last and handle output.
On every patient's cerebral cortex, lay dura mater bottom electrode array and extract the ECoG data; For patient implant dura mater platinum 6*8 or 8*8 electrod-array (subdural electrode arrays (and Ad-Tech, Racine, WI); Each electrode diameter is 4mm, and the distance between adjacent electrode is 10mm; (Neuroscan, ElPaso TX) are used for the amplification and the digitized of electrode detection signal to the Synamps2 amplifier, and the ECoG data sampling rate is 1000Hz, through the filtering of 0.05-200Hz passband.
Signal processing module is provided by COMPREHENSIVE CALCULATING machine processing system, the motion indication is provided and stores instruction time to patient, receives and store the EEG signals data of Synamps2 amplifier.
During each the experiment, according to " motion-rest " indication of computer display, patient elder generation motion finger 2 seconds was had a rest 2 seconds then; Repeat repeatedly above-mentioned identical experiment again.Collection is positioned at the specific cortex zone ECoG data in cerebral nerve cortex motor function district, carries out image data altogether 10 times, is used for the work of treatment of computer system.
Confirm to decompose level according to the mu rhythm and pace of moving things and the interferential frequency band of power frequency: the EEG signals that the present invention studied comprise the mu rhythm and pace of moving things (8-12 Hz), some transient signals and power frequency and disturb (50 Hz), confirm that through table 1 frequency band computing formula decomposing level is 7.
Table 1: the ERD index eigenvalue of each list frequency band reconstruction signal
| List frequency band reconstruction signal | The frequency band computing formula | Frequency range | The ERD eigenvalue |
| Sa7(delta) | 0,fs/256 | 0--3.9 | -1.6122 |
| Sd7(theta) | fs/256, fs/128 | 3.9--7.8125 | 0.4956 |
| Sd6(mu) | fs/128, fs/64 | 7.8125--15.625 | 0.9148 |
| Sd5(beta) | fs/64, fs/32 | 15.625--31.25 | 0.8539 |
| Sd4 | fs/32, fs/16 | 31.2--62.5 | 0.5193 |
| Sd3 | fs/16, fs/8 | 62.5--125 | -0.2009 |
| Sd2 | fs/8, fs/4 | 125--250 | -0.2831 |
| Sd1 | fs/4, fs/2 | 250--500 | -0.1619 |
EEG signals and processing unit utilize the multiresolution characteristic of wavelet transformation, and the EEG signals that will contain noise carry out multiple dimensioned decomposition, obtain the subband signal of different frequency bands.Specific as follows: the original cortex eeg data that single test is had background noise is imported the matlab software application, utilizes discrete db3 wavelet transformation to carry out seven layers of wavelet decomposition, and the result sees Fig. 3.Abscissa express time among the figure, unit are sampling number (sample frequency are 1000Hz), and the longitudinal axis is represented amplitude, and unit is μ V.The moment of zero corresponding constantly experiment beginning of abscissa.D1-d7 is the detail signal that yardstick 1-6 goes up wavelet decomposition, and a6 is the approximation signal of the wavelet decomposition on the yardstick 6.
Mu prosodic feature extraction unit is handled the frequency band that contains noise, and the EEG signals behind the noise such as power frequency interference are removed in reconstruct then, and extract mu rhythmic movement district specificity EEG signals.Specific as follows: as to extract the mu rhythm and pace of moving things (frequency range 8-12 Hz); Only extract d6 (frequency range 7.812-15.625 Hz) monolayer detail coefficients, all the other coefficients put 0, then to the reconstruct of counting entirely of this monolayer coefficient; Its reconstruction signal Sd6 sees Fig. 4 as the output of the mu rhythm and pace of moving things.Simultaneously, noise and some other transition interfering signals such as power frequency interference have been eliminated.Abscissa express time among the figure, unit are sampling number (sample frequency are 1000Hz), and the longitudinal axis is represented amplitude, and unit is μ V.The moment of zero corresponding constantly experiment beginning of abscissa.
The pattern classification unit is according to the specificity mu prosodic feature of motor region brain electricity; ERD/ERS index with d6 (7.812 ~ 15.625 Hz) feature band reconstruction signal is an eigenvalue; With 40% is that characteristic threshold value is carried out " being/deny " classification, discerns the specificity attribute of each electrode.
Motion specific function district network for location output module forms coordinate system with the structure of dura mater bottom electrode array; Coordinate with whole 48 specificity electrodes is a boundary point match boundary curve; Form closed curve figure and export ground motion specific function district network for location exactly; The zone that surrounds in the closed curve is motion specific function district, and is as shown in Figure 5.Be applied to clinical medicine surgical functions district when location, cooperate the secondary function district to locate, confirm to form last accurate motor function district network for location in the border in motion specific function district with other method (like the electric cortical stimulation method etc.).Extract and sorting result according to the mu prosodic feature, realize the network for location output of brain motor function district.
Claims (10)
1. one kind based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; Comprise the eeg signal acquisition module; Signal processing module; Location, functional areas map output module is characterized in that said signal processing module comprises EEG signals pretreatment unit, mu prosodic feature extraction unit and pattern classification unit; The EEG signals that the eeg signal acquisition module is gathered; Carry out pretreatment filtering via the EEG signals pretreatment unit; Be sent to mu prosodic feature extraction unit and extract specificity mu prosodic feature; Classify through the pattern classification unit again, at last through location, functional areas map output module feedback positioning result.
2. according to claim 1 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; It is characterized in that said eeg signal acquisition module comprises implanted electrode, amplifilter and A/D transducer; Implanted electrode is gathered EEG signals; Carry out amplification filtering via amplifilter and handle, convert EEG signals into digital signal through A/D converter then, be input to signal processing module at last.
3. according to claim 2 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; It is characterized in that said implanted electrode is the dura mater platinum electrode; Comprise platinum 6*8 or 8*8 electrod-array, electrode diameter is 4mm, and the adjacent electrode spacing is 10mm.
4. according to claim 3 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis, it is characterized in that said implanted electrode is placed on people's the cerebral cortex.
5. according to claim 2 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; It is characterized in that amplifilter and A/D transducer adopt the Synamps2 amplifier, are used for the amplification and the digitized of electrode detection signal.
6. according to claim 1 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis, it is characterized in that the pretreatment filtering of said EEG signals pretreatment unit comprises multiple dimensioned decomposition.
7. according to claim 6 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis, it is characterized in that the discrete db3 wavelet transformation of said multiple dimensioned decomposition utilization carries out 7 layers of wavelet decomposition, concrete according to like formula (1):
（1）；
Wherein,
H,
GBe the wavelet decomposition wave filter in the time domain,
h,
gBe the wavelet reconstruction wave filter in the time domain; T is a discrete-time series,
t=1,2 ...,
N jBe the decomposition number of plies,
j=1,2,
J,
JBe the decomposition degree of depth,
f(
t) be primary signal;
a j For
f(
t)
jThe wavelet coefficient of the approximate part of layer;
d j For
f(
t)
jThe wavelet coefficient of layer detail section.
8. according to claim 7 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; It is characterized in that said mu prosodic feature extraction unit only extracts d6 monolayer detail coefficients; Other coefficient zero setting, the reconstruct of counting entirely then, the signal Sd6 after its reconstruct exports as the mu rhythm and pace of moving things; Formula (2) is seen in the calculating of reconstruction signal characteristic quantity (motion event the 2 seconds self-energys in front and back takes place than ERD)
Wherein, ER is the quadratic sum of each sampling point value of each the sub-band reconstruction signal in preceding 2 seconds of the motion event, and EA is for calculating the quadratic sum of each sampling point value of each the sub-band reconstruction signal in 2 seconds behind the motion event.
9. according to claim 8 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis, it is characterized in that said pattern classification unit is that characteristic threshold value is/not classification the identification specificity electrode to the mu rhythm and pace of moving things with 40%.
10. according to claim 9 a kind of based on motor region functional localization system in the art of cortex brain electricity mu rhythm and pace of moving things wavelet analysis; It is characterized in that the motion specific function district network for location of location, said functional areas map output module output, is that the specificity electrode coordinate of discerning with the pattern classification unit is a boundary point match boundary curve.
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Application publication date: 20120627 |