CN102613971A - Electroencephalograph (EEG)-based epilepsy detection and intervention device - Google Patents
Electroencephalograph (EEG)-based epilepsy detection and intervention device Download PDFInfo
- Publication number
- CN102613971A CN102613971A CN2012100977169A CN201210097716A CN102613971A CN 102613971 A CN102613971 A CN 102613971A CN 2012100977169 A CN2012100977169 A CN 2012100977169A CN 201210097716 A CN201210097716 A CN 201210097716A CN 102613971 A CN102613971 A CN 102613971A
- Authority
- CN
- China
- Prior art keywords
- brain
- module
- epilepsy
- eeg
- wave acquisition
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Landscapes
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The invention provides an electroencephalograph (EEG)-based epilepsy detection and intervention device, which has the functions of recording EEG (scalp EEG, electrocorticogram (ECoG) and deep local field potential (LFP) EEG), analyzing the recorded EEG, detecting epilepsy electrograph onset (EO), forecasting epilepsy behavior onset and giving an alarm about the forecast epilepsy onset or implementing intervention means such as electrical stimulation. The device can also be used for research of corresponding animal experiments.
Description
Technical field
The present invention relates to based on brain electricity (the scalp brain electricity EEG of laboratory animals such as the mankind or rat, rabbit, monkey; Cortex brain electricity ECoG and brain deep local field potentials LFP) epilepsy detect and therapeutic intervention device and epilepsy detection algorithm thereof; Can be used for having closed-loop feed-back type nerve stimulator that automatic detection stimulates as required or external epilepsy detection alarm device; These apparatus and method also can be used for belonging to the implantation medical instrument field in the corresponding animal experiment study of epilepsy detection and intervention.
Background technology
Embedded nerve stimulator is a type in the implantation medical equipment; Through being provided electricity irritation, nervous system treats some disease; At present the whole world has dropped into clinical use or has been used to treat DBS device (DBS is commonly called as brain pacemaker), SCS device (SCS), cortex stimulator (CNS), the vagus nerve stimulator (VNS) of dyskinetic diseases such as parkinson, epilepsy, muscular tension are not normal in mainly comprising of development registration phase.Wherein vagus nerve stimulator has been widely used in intractable treatment of epilepsy abroad, and DBS device, cortex stimulator are used for epilepsy therapy and have also got into clinical experimental stage.
Epilepsy is commonly called as " epilepsy ", is a kind of common nervous system disease, influences the population in the whole world about 1%, in state-owned 9,000,000 patients.It is to cause a kind of chronic disease that the suddenly unusual over-discharge of cranial nerve cell causes the brain function imbalance by brain lesions.The patient understands loss of consciousness during epilepsy, produces whole body and twitches, phenomenon such as spit out white foams, and the slight outbreak of part then only shows quiet phenomenon such as upright, inattentive.Though epilepsy itself can be not fatal, can influence the human's nervous system operate as normal, the outbreak in specific environment possibly cause life danger in addition, like occurrence of traffic accident, drowned, high falling etc.If it is can give the alarm in advance,, all significant to patient's life and health no matter forecast or combined treatment equipment is intervened epilepsy on the horizon.
At epilepsy clinical episodes (clinical onset; CO) several seconds before to a few minutes so that the longer time; Unusual performance can appear in brain electricity in advance; Show as characteristic brain wave outbreak, as typical epileptic electroencephalogram (eeg) outbreak such as spike, sharp wave, slow wave and spike and slow wave complex, sharp and slow wave complex (electrograph onset, EO).The present invention forms the prediction to the epilepsy clinical episodes through detecting the epileptic electroencephalogram (eeg) outbreak.This system can detect based on the brain electricity on a plurality of yardsticks; Comprise scalp brain electricity (electroencephalograph, EEG), brain dura mater hypodermal layer brain electricity (electrocorticograph; ECoG); (there is multiple embodiments in the difference according to emphasis in clinical practices such as epilepsy diagnosis, prevention, treatment to brain deep local field potentials for local field potential, LFP) brain electricity.As carrying out the epilepsy forecast in the ward or outside the institute, arrange safeguard procedures etc. in advance to remind doctor, nurse or family members; Or cooperate record, transmission equipment, and the brain electric information before and after the epilepsy is stored and spread out of, supply research worker to conduct a research.The typical application of the present invention is to have the nerve stimulator that the epilepsy measuring ability can stimulate as required.Current nerve stimulator all adopts parameter preset to stimulate according to fixed pattern, does not make a response according to patient's situation and carries out the function of " stimulating as required ".The electricity irritation unnecessary to brain belongs to overstimulation, possibly have potential risk, can reduce this risk if stimulate then as required.In addition; For the limited battery electric quantity of the embedded nerve stimulator of full implant into body, under reasonable software and hardware configuration, the pattern of detection-stimulation can obtain with respect to the lower power consumption of pattern that continues stimulation; Prolong and once implant service life, reduce patient's operation misery and financial burden.Before possible clinical practice is carried out, need carry out the zoopery checking, under the prerequisite that does not change essence of the present invention, can process laboratory animals such as being suitable for rat, rabbit, monkey and carry out zooperal prototype and carry out zoopery.
Summary of the invention
To the problems referred to above; The purpose of this invention is to provide and a kind ofly can carry out epilepsy based on brain wave and detect and to report to the police then or implement device like intervention means such as electricity irritation; Has brain electricity (the scalp brain electricity EEG of laboratory animals such as the mankind or rat, rabbit, monkey to recording; Cortex brain electricity ECoG and brain deep local field potentials LFP) analyze; Detect the function of epileptic electroencephalogram (eeg) outbreak and forecast epilepsy behavior outbreak, have forecasting that epilepsy on the horizon reports to the police or implement the function like intervention means such as electricity irritation.The present invention can be used for corresponding zooperal research simultaneously.
The present invention is achieved through following technical scheme.
A kind of epilepsy based on the brain electricity detects and tampering devic, comprising: brain wave acquisition module, brain electricity analytical module, memory module and intervention module;
Said brain wave acquisition module can be carried out brain wave acquisition, and said brain electricity analytical module can be carried out epilepsy according to the EEG signals that collect and detected, and according to the result of said detection the mode of operation of said intervention module is set; And,
Said brain electricity analytical module is configured to carry out following steps:
(1) eeg data of reception measurand;
(2) from said eeg data, extract the brain electro-detection factor;
(3) whether epileptic electroencephalogram (eeg) shows effect with the corresponding said object of threshold decision according to the said brain electro-detection factor.
Preferably, the said brain electro-detection factor does
X wherein
1, x
2...,
Be the N1 in the said eeg data continuous or interval sampling data point.
Preferably, the said brain electro-detection factor does
Wherein
Promptly every at a distance from N
3The point sampling prospect is got full N
4Point is done and is forgotten the method calculating background of processing according to the prospect of calculating.
Preferably, the extraction of the said brain electro-detection factor may further comprise the steps:
N to continuous or interval sampling
4The point brain:
(1) finds Local Extremum
(2) duration and the amplitude between continuous two Local Extremum of calculating, and do suitable rolling average
(3) calculate detection factor r3=amplitude/duration
2
Preferably, said brain wave acquisition module comprises dual purpose electrodes, is used to switch the analog switch of said dual purpose electrodes record and stimulatory function, and the brain wave acquisition circuit.
Preferably, said brain wave acquisition circuit comprises:
Amplifying unit carries out elementary amplification with primary signal, and its input links to each other with said dual purpose electrodes through analog switch;
Filter unit, its input links to each other with the outfan of amplifying unit;
A/D converter, its input links to each other with the outfan of said filter unit, converts EEG signals into digital form from analog form.
Preferably, said brain wave acquisition module comprises recording electrode and brain wave acquisition circuit; Said intervention module comprises stimulating electrode, pulse generating circuit control unit, and pulse generating circuit;
Said device also comprises wireless communication module, and said brain electricity analytical module is controlled said intervention module through said wireless communication module.
Preferably, said recording electrode is an electrode in vitro, and said stimulating electrode is an implanted electrode.
Preferably, it is characterized in that said brain wave acquisition module comprises recording electrode and brain wave acquisition circuit; Said intervention module comprises alarm module and memory module.
Preferably, said measurand is human epileptic or laboratory animal.
Through adopting above technical scheme; The present invention has following beneficial effect: record analysis brain of the present invention electric-examination is measured the epileptic electroencephalogram (eeg) outbreak and is predicted that the epilepsy clinical episodes that possibly arrive stimulates again; Compare with traditional embedded nerve stimulator; Have the closed loop feedback function, reducing stimulates, and reduces the risk that electricity irritation has side effects to nervous system; It is less and do not have in the system of strict power consumption constraints that the present invention can be integrated into a volumes; Supply the epileptic to wear; No longer need long-term bed; Judge the patient and possibly provide warning in advance by epilepsy, give relatives, nurse, the time of doctor of nurse, improved patients ' life quality to react and to intervene.
Description of drawings
Fig. 1 is first kind of embodiment high-level schematic functional block diagram of the present invention;
Fig. 2 is second kind of embodiment high-level schematic functional block diagram of the present invention;
Fig. 3 is the third embodiment high-level schematic functional block diagram of the present invention;
Fig. 4 is the flow chart that epilepsy of the present invention detects or intervenes;
Fig. 5 is the program flow diagram of epilepsy detection method of the present invention when considering in single-chip microcomputer that low-power consumption is used;
Wherein:
11, dual purpose electrodes (record/stimulation); 12, analog switch (switching 11 records/stimulatory function); 13, recording electrode; 14, stimulating electrode; 2, brain wave acquisition circuit; 21, amplifying unit; 22, filter unit; 23, A/D converter; 3, brain electricity analytical module; 31, wireless communication module; 4, pulse generating circuit; 41, pulse generating circuit control unit; 5, alarm module; 6, memory module.
The specific embodiment
In conjunction with accompanying drawing embodiment of the present invention are elaborated:
Implement ten thousand formulas one:
With reference to accompanying drawing 1; A kind of epilepsy based on brain electricity detects with tampering devic and comprises: dual purpose electrodes 11, and linking to each other with said dual purpose electrodes 11 is used to switch the analog switch 12 of electrode record/stimulatory function, brain wave acquisition circuit 2; Brain electricity analytical module 3, memory module 6 and pulse generating circuit 4.Owing to be conceived in embedded nerve stimulator, use, each several part need be selected volume components and parts little, low in energy consumption as far as possible, and adopts low power dissipation design.
Said device acquiescence is operated in the eeg recording analysis state; Pulse generating circuit 4 cuts out under this state; Analog switch 12 makes dual purpose electrodes 11 be connected to brain wave acquisition circuit 2 to carry out brain wave acquisition, brain electricity operation epilepsy detection algorithm program and necessary control program that 3 pairs of brain electricity analytical modules collect.If the epilepsy detection algorithm of brain electricity analytical module 3 does not detect the epileptic electroencephalogram (eeg) outbreak, then whole device remains running in the eeg recording analysis state.If detect the epileptic electroencephalogram (eeg) outbreak; The control sequence control analog switch 12 disconnection dual purpose electrodes 11 of brain electricity analytical module 3 and being connected of brain wave acquisition circuit 2; Then dual purpose electrodes 11 is connected with pulse generating circuit 4; And control impuls generation circuit 4 sends electric pulse, is transmitted to neuronal target through dual purpose electrodes 11, stimulates.
Said dual purpose electrodes 11; Can be that strip shaped electric poles, the gate-shaped electrode that is arranged in the skull maybe can be implanted the depth electrode below the cortical surface; Be used for writing down or stimulate the relevant neurological region of epilepsy; Like brain deep nuclei, cerebral cortex, vagus nerve etc., linked to each other with brain wave acquisition circuit 2 or pulse generating circuit 4 by analog switch 12 controls, said dual purpose electrodes 11 configurable one-tenth record or stimulus modelities.Can dispose and be no less than two electrodes; As 4 or 8, according to treatment needs and zoopery demand, each electrode is configured to recording electrode, stimulating electrode, record/stimulating electrode separately; And be placed on the neural correct position record of brain or other or/and stimulate, treat.
Said brain wave acquisition circuit 2 comprises: amplifying unit 21 is used for original EEG signals are carried out elementary amplification; Filter unit 22 carries out bandpass filtering to the brain electricity; A/D converter 23 converts EEG signals into digital form from analog form, and its outfan is through the microprocessor of chip chamber interface bus and signal processing module 3.The chip chamber interface bus is selected difference and the difference of chip for use according to A/D converter 23, and commonly used is I2C bus and spi bus.Said brain wave acquisition circuit 2 each several parts will be selected chip low in energy consumption or the high complete bio electricity analog front-end chip of chip as 21,22,23 3 unit are integrated of integrated level for use, to adapt to the small volume low watt consumption designing requirement of battery powered implantation medical equipment.
The main body of said signal processing module 3 is the low-power consumption microprocessor chip, or with epilepsy detection algorithm and the solidified custom chip of control sequence, to adapt to the small volume low watt consumption designing requirement of battery powered implantation medical equipment.Said epilepsy detection algorithm adopts three kinds of different algorithms independently to extract three types of different brain electrical features, forms three and detects the factor, and set corresponding threshold value, has judged whether the epileptic electroencephalogram (eeg) outbreak in view of the above.
Said pulse generating circuit 4 is consistent with traditional nerve stimulator, and non-the present invention is concerned about emphasis, does not do detailed description.
Said memory module 6 is a nonvolatile storage, is used for storing EEG signals, in needs, reads out to supply off-line analysis research to use.Be generally storage card or commercial memory chip, through USB interface or chip chamber interface bus such as connections such as I2C bus, spi bus.
With reference to Fig. 4, the present invention carries out according to the closed loop feedback method that the epilepsy testing result is implemented the epilepsy intervention as follows:
A, arrange dual purpose electrodes 11 or recording electrode 13, gather the brains electricity, digitized brain is electrically communicate to brain electricity analytical module 3 through A/D converter 23 through brain wave acquisition circuit 2 at patient's intracranial or scalp.With three kinds independently the algorithm of computational efficient respectively the brain electricity is analyzed.
B1, algorithm one: to the N1 point brain of continuous or interval sampling:
1, does difference and take absolute value and add and for every continuous 2 as molecule;
2, the difference of N1 maximum of ordering and minima is as denominator;
3, the detection factor r1=molecule/denominator of algorithm one
This algorithm is that a kind of simplification of typing dimension is calculated, and is shown below:
B2, algorithm two:
N2 point brain to continuous or interval sampling:
1, gets the data point that N2 point brain level side ordering is positioned at p% and do prospect
Like p=50, then for getting intermediate value, step 1 is called medium filtering
2, every at a distance from N3 point sampling prospect, get full N4 point and do and forget the method calculating background of processing according to the prospect of calculating;
3, the detection factor r2=foreground/background of algorithm two
The main body of this algorithm is called order statistics filtering, is shown below:
Prospect:
Background:
K=nN
3, n is a positive integer
B3, algorithm three:
N to continuous or interval sampling
2The point brain:
1, finds Local Extremum
2, duration and the amplitude between continuous two Local Extremum of calculating, and do suitable rolling average
3, the detection factor r3=amplitude/duration of algorithm three
2
C, be that the detection factor of three kinds of algorithms is set space threshold value T1 separately, T2, T3, unified time threshold value D, D2 provides corresponding alarm state according to the relation that detects the factor and space, time threshold:
When r1 surpasses T1 or r2 and surpasses T2 or r3 when surpassing T3, get into primary alarm
When r1 surpasses T1 or r2 and surpasses T2 or r3 and surpass T3 and persistent period D, get into second-level alarm
If r1 surpasses T1 and do not reach time D, or r2 surpasses T2 and do not reach time D, or r3 surpasses T3 and do not reach time D, keeps primary alarm, after continuing to be lower than the space threshold time and reaching D2, sounds all clear
As long as D has a kind of detection algorithm result to think the entering alarm state, whole system gets into alarm state, and alarm module or pulse generating circuit are made a response according to corresponding alarm:
No alarm: do not intervene
Primary alarm: possibly be about to occur the epileptic electroencephalogram (eeg) outbreak, can suitably intervene
Second-level alarm: detect the epileptic electroencephalogram (eeg) outbreak, intervene at once
Accompanying drawing 5 is that the present invention is integrated into the software flow pattern of considering low-power consumption in the battery powered closed-loop feed-back type embedded nerve stimulator.The epilepsy detection algorithm need reduce computation complexity as much as possible, to improve computational speed.200Hz, 250Hz, 256Hz commonly used; The 512Hz sample rate is gathered the brain electricity all can satisfy the demand data that epilepsy detects; After each sampling period to the data point of last collection and before the data point in the certain hour do when focusing on and need start microprocessor, during the microprocessor operation during lower power consumption holding state power consumption can improve several magnitude.Therefore algorithm is fast more, and it is short more that then microprocessor is in time of running status, and the time that is in the low-power consumption standby state is long more, and overall power is low more.Calculate each detection factor constantly need current data point and before the data point in the certain hour calculate, the epilepsy whether judgement that the point of usefulness provides more at most is reliable more, but computational speed is slow more.Need meticulous with experience according to actual needs balanced algorithm efficient, algorithm effect, working environment, even want each patient independently to regulate and control.In the accompanying drawing 5, the r1 of algorithm one, two, three, r2, r3 need to compare with space threshold value T1, T2, T3 and time threshold value D, D2 respectively, and r represents r1 or r2 or r3, and T represents T1 or T2 or T3, D
R＜TRepresent the time of r, D less than T
R＞TRepresent the time of r greater than T.
Embodiment two:
With reference to accompanying drawing 2, a kind of epilepsy based on the brain electricity detects and comprises in the body and external two parts with tampering devic.Outer body comprises: recording electrode 13, brain wave acquisition circuit 2, brain electricity analytical module 3, wireless communication module 31 and memory module 6.Body comprises inner the branch: pulse generating circuit control unit 41, pulse generating circuit 4, stimulating electrode 14.
Different with first kind of embodiment, it is external that second kind of embodiment will need brain wave acquisition circuit and the brain electricity analytical module of strict low power dissipation design to move on to, and makes these two parts no longer receive the restriction of power consumption, and the element of part also reduces in the body.So, the circuit of outer body need not to select for use especially the high element of volume low power consumption low cost; Detection algorithm need not to carry out a large amount of computational efficiency optimization; And may operate in computational speed faster on the processor, can call more resources, judge whether epilepsy can be according to the more data that lead the brain electricity more; And then the raising judgment accuracy, reduce and detect delay; Simultaneously, the volume and the power consumption of part reduce greatly in the body, have prolonged the service life of implant part, have reduced the body and mind misery and the financial burden of corrective surgery.
The outer body acquiescence of said embodiment is operated in the eeg recording analysis state, and the part acquiescence is operated in the holding state of not providing electricity irritation in the body.The brain wave acquisition circuit 2 of said outer body is gathered the brain electricity through the recording electrode 13 that is arranged on the scalp, operation epilepsy detection algorithm and necessary control program on the brain electricity analytical module 3.Said epilepsy detection algorithm provides the judgement whether epilepsy is arranged, and again judged result is sent to part in the body with wireless.The pulse generating circuit 4 of part is transmitted to required neuronal target with the electric pulse that produces through stimulating electrode 14 in the body, and some basic controlling are carried out in the instruction that the external wireless communication module 31 of intravital control section 41 receptions is sent.If judging has epilepsy then the granting electricity irritation of pulse generating circuit 4, otherwise part is not worked in the body, keep holding state only to receive the wireless signal of outer body.It is external that this embodiment will need brain wave acquisition circuit and the brain electricity analytical module of strict low power dissipation design to move on to, and makes these two parts no longer receive the restriction of power consumption, and the element of part also reduces in the body.Therefore, the circuit of outer body need not to select for use especially the high element of volume low power consumption low cost; Detection algorithm need not to carry out a large amount of computational efficiency optimization; And may operate in computational speed faster on the processor, can call more resources, judge whether epilepsy can be according to the more data that lead the brain electricity more; And then the raising judgment accuracy, reduce and detect delay; Simultaneously, the volume and the power consumption of part reduce greatly in the body, have prolonged the service life of implant part, have reduced the body and mind misery and the financial burden of corrective surgery.
Said recording electrode 13; Can be to be arranged in the depth electrode that strip shaped electric poles, the gate-shaped electrode on skull endodermis surface maybe can implant below the cortical surface to be used to write down intracranial brain electricity (cortex brain electricity ECoG or brain deep local field potentials LFP), also can be the electrode cap of record scalp brain electricity and supporting cap-shaped electrode.Can dispose and be no less than two electrodes, the brain electricity of a plurality of region of interest is carried out monitoring analysis.
Said brain wave acquisition circuit 2 comprises: amplifying unit 21 is used for original EEG signals are carried out elementary amplification; Filter unit 22 carries out bandpass filtering to the brain electricity; A/D converter 23 converts EEG signals into digital form from analog form, and its outfan is through the microprocessor of chip chamber interface bus and signal processing module 3.The chip chamber interface bus is selected difference and the difference of chip for use according to A/D converter 23, and commonly used is I2C bus and spi bus.Embodiment two said brain wave acquisition circuit 2 are external owing to being positioned at, and obtain and change power supply easily, need not to select for use especially the low-power consumption element and carry out strict low power dissipation design.
The main body of said signal processing module 3 is processor chips, or with epilepsy detection algorithm and the solidified custom chip of control sequence, external owing to being positioned at, obtain and change power supply easily, need not to select for use especially the small volume low watt consumption element or carry out strict low power dissipation design.Said epilepsy detection algorithm adopts three kinds of diverse ways independently to have three types of different brain electrical features of extraction, forms three and detects the factor, and judged whether the epileptic electroencephalogram (eeg) outbreak in view of the above.
Said pulse generating circuit control unit 41 should adopt selects the low power consumption control chip, to adapt to the small volume low watt consumption designing requirement of battery powered implantation medical equipment.
Said pulse generating circuit 4 is consistent with traditional nerve stimulator, and non-the present invention is concerned about emphasis, does not do detailed description.
Said stimulating electrode 14 is implantable electrode, is used for stimulating the relevant neurological region of epilepsy, like brain deep nuclei, cerebral cortex, vagus nerve etc.
Said memory module 6 is a nonvolatile storage, is used for storing EEG signals, in needs, reads out to supply off-line analysis research to use.Be generally storage card or commercial memory block chip, through USB interface or chip chamber interface bus such as connections such as I2C bus, spi bus.
This embodiment carries out according to accompanying drawing 4 said steps according to the closed loop feedback method that the epilepsy testing result is implemented the epilepsy intervention, and preamble is stated, repeats no more.
With reference to accompanying drawing 5, the software flow pattern of embodiment of the present invention one integrated consideration low-power consumption in battery powered closed-loop feed-back type embedded nerve stimulator also can be used as the kernel program flow process framework of embodiment two said brain electricity analytical modules 3.
Embodiment three:
With reference to accompanying drawing 3, a kind of epilepsy based on the brain electricity detects with tampering devic and comprises: recording electrode 13, brain wave acquisition circuit 2, brain electricity analytical module 3, alarm module 5 and memory module 6.This device is gathered the brain electricity through the recording electrode 13 that is arranged on the scalp with brain wave acquisition circuit 2, and is recorded on the memory module 6 through the control of brain electricity analytical module 3.Brain electricity analytical module 3 operation epilepsy detection algorithms provide the judgement whether epilepsy is arranged, and the result is sent to alarm module 5, supply family numbers of patients, doctor, nurse to make a response the patient is intervened, and directly the patient are intervened without machine.
Different with preceding two kinds of embodiments, the third embodiment does not have full implantation parts, and the epilepsy detection algorithm is not directly intervened after detecting epilepsy yet, reports to the police but notify warning system to detect when epileptic electroencephalogram (eeg) shows effect.This invention can let routine carry out the bed in hospital of epilepsy location and write down the electric patient of brain unlike suitably activity of lasting bed; The patient wear that epilepsy is arranged in the time of also can letting non-being in hospital; In case sending epilepsy reports to the police; By family members, doctor, nurse the patient is intervened again, raising to a certain degree patient's quality of life.
Said recording electrode 13 can be to be arranged in the depth electrode that strip shaped electric poles, the gate-shaped electrode on skull endodermis surface maybe can implant below the cortical surface to be used to write down intracranial brain electricity, also can be the electrode cap of record scalp brain electricity and supporting cap-shaped electrode.Configurablely be no less than two electrodes, the brain electricity of a plurality of region of interest is carried out monitoring analysis.
Said brain wave acquisition circuit 2 comprises: amplifying unit 21 is used for original EEG signals are carried out elementary amplification; Filter unit 22 carries out bandpass filtering to the brain electricity; A/D converter 23 converts EEG signals into digital form from analog form, and its outfan is through the microprocessor of chip chamber interface bus and signal processing module 3.The chip chamber interface bus is selected difference and the difference of chip for use according to A/D converter 23, and commonly used is I2C bus and spi bus.The said brain wave acquisition circuit 2 of this embodiment is external owing to being positioned at, and obtains and change power supply easily, need not to select for use especially the low-power consumption element and carries out strict low power dissipation design.
The main body of said signal processing module 3 is processor chips, or with epilepsy detection algorithm and the solidified custom chip of control sequence, external owing to being positioned at, obtain and change power supply easily, need not to select for use especially the low-power consumption element and carry out strict low power dissipation design.Said epilepsy detection algorithm adopts three kinds of diverse ways independently to have three types of different brain electrical features of extraction, forms three and detects the factor, and set corresponding threshold value, and judged whether the epileptic electroencephalogram (eeg) outbreak in view of the above.
Said alarm module 5 can be a display lamp, and sound etc. can cause the signal that others notes, also can combine the computer visualization technology, even network technology realizes the effect of remote alarms, prompting.
Said memory module 6 is a nonvolatile storage, is used for storing EEG signals, in needs, reads out to supply off-line analysis research to use.Be generally storage card or commercial memory block chip, through USB interface or chip chamber interface bus such as connections such as I2C bus, spi bus.
This embodiment carries out according to accompanying drawing 4 said steps according to the closed loop feedback method that the epilepsy testing result is implemented the epilepsy intervention, and preamble is stated, repeats no more.
With reference to accompanying drawing 5, the software flow pattern of embodiment of the present invention one integrated consideration low-power consumption in battery powered closed-loop feed-back type embedded nerve stimulator also can be used as the kernel program flow process framework of embodiment three said brain electricity analytical modules 3.
Claims (10)
1. the epilepsy based on the brain electricity detects and tampering devic, comprising: brain wave acquisition module, brain electricity analytical module, memory module and intervention module;
Said brain wave acquisition module can be carried out brain wave acquisition, and said brain electricity analytical module can be carried out epilepsy according to the EEG signals that collect and detected, and according to the result of said detection the mode of operation of said intervention module is set; And,
Said brain electricity analytical module is configured to carry out following steps:
(1) eeg data of reception measurand;
(2) from said eeg data, extract the brain electro-detection factor;
(3) whether epileptic electroencephalogram (eeg) shows effect with the corresponding said object of threshold decision according to the said brain electro-detection factor.
2. device according to claim 1 is characterized in that, the said brain electro-detection factor does
X wherein
1, x
2...,
Be the N in the said eeg data
IIndividual continuous or interval sampling data point.
3. device according to claim 1 is characterized in that, the said brain electro-detection factor does
Wherein
4. device according to claim 1 is characterized in that, the extraction of the said brain electro-detection factor may further comprise the steps:
N to continuous or interval sampling
2The point brain:
(1) finds Local Extremum
(2) duration and the amplitude between continuous two Local Extremum of calculating, and do suitable rolling average
(3) calculate detection factor r3=amplitude/duration
2
5. according to each described device among the claim 1-4, it is characterized in that said brain wave acquisition module comprises dual purpose electrodes, be used to switch the analog switch of said dual purpose electrodes record and stimulatory function, and the brain wave acquisition circuit.
6. device according to claim 5 is characterized in that, said brain wave acquisition circuit comprises:
Amplifying unit carries out elementary amplification with primary signal, and its input links to each other with said dual purpose electrodes through analog switch;
Filter unit, its input links to each other with the outfan of amplifying unit;
A/D converter, its input links to each other with the outfan of said filter unit, converts EEG signals into digital form from analog form.
7. according to each described device among the claim 1-4, it is characterized in that said brain wave acquisition module comprises recording electrode and brain wave acquisition circuit; Said intervention module comprises stimulating electrode, pulse generating circuit control unit, and pulse generating circuit;
Said device also comprises wireless communication module, and said brain electricity analytical module is controlled said intervention module through said wireless communication module.
8. device according to claim 7 is characterized in that, said recording electrode is an electrode in vitro, and said stimulating electrode is an implanted electrode.
9. according to each described device among the claim 1-4, it is characterized in that said brain wave acquisition module comprises recording electrode and brain wave acquisition circuit; Said intervention module comprises alarm module and memory module.
10. according to each described device among the claim 1-4, it is characterized in that said measurand is human epileptic or laboratory animal.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201210097716 CN102613971B (en) | 2012-03-30 | 2012-03-30 | Electroencephalograph (EEG)-based epilepsy detection and intervention device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 201210097716 CN102613971B (en) | 2012-03-30 | 2012-03-30 | Electroencephalograph (EEG)-based epilepsy detection and intervention device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102613971A true CN102613971A (en) | 2012-08-01 |
| CN102613971B CN102613971B (en) | 2013-10-30 |
Family
ID=46554439
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 201210097716 Active CN102613971B (en) | 2012-03-30 | 2012-03-30 | Electroencephalograph (EEG)-based epilepsy detection and intervention device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102613971B (en) |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103156603A (en) * | 2012-11-20 | 2013-06-19 | 中国人民解放军第四军医大学第一附属医院 | Epileptic seizure pre-warning device |
| CN104112066A (en) * | 2014-08-18 | 2014-10-22 | 天津大学 | Epilepsy state closed-loop control experiment platform based on FPGA |
| CN104173044A (en) * | 2014-08-15 | 2014-12-03 | 浙江大学医学院附属第二医院 | Closed-loop system used for epilepsy treatment |
| CN104225790A (en) * | 2014-09-19 | 2014-12-24 | 清华大学 | Closed loop nerve stimulation system |
| CN104623808A (en) * | 2013-11-14 | 2015-05-20 | 先健科技(深圳)有限公司 | Deep brain stimulation system |
| CN104799841A (en) * | 2015-04-27 | 2015-07-29 | 成都腾悦科技有限公司 | Biological electrical signal double-closed loop system |
| CN105561474A (en) * | 2015-02-20 | 2016-05-11 | 邵志辉 | Device for treating epilepsy by stimulating vagus nerves of human body |
| CN105999544A (en) * | 2016-05-04 | 2016-10-12 | 浙江大学 | Recording-stimulating mode switching device and application |
| CN106726091A (en) * | 2016-12-22 | 2017-05-31 | 北京品驰医疗设备有限公司 | A kind of epilepsy sleep apnea prevention system of quickly-chargeable |
| CN107714035A (en) * | 2017-09-14 | 2018-02-23 | 中国人民解放军第四军医大学 | A kind of wearable digitlization eeg monitoring helmet |
| CN107981860A (en) * | 2017-12-08 | 2018-05-04 | 浙江大学 | A kind of undamaged epilepsy path of non-contact non-intruding is up to mode monitoring and warning interfering system and the method for obtaining interference brain electricity distribution |
| CN108158579A (en) * | 2017-12-08 | 2018-06-15 | 浙江大学 | A kind of undamaged epilepsy self-organizing monitoring and warning interfering system of non-contact non-intruding and the method for obtaining the electricity distribution of interference brain |
| CN108175401A (en) * | 2017-12-08 | 2018-06-19 | 浙江大学 | A kind of undamaged epilepsy antithesis complimentary fashion monitoring and warning interfering system of non-contact non-intruding and the method for obtaining the electricity distribution of interference brain |
| CN109363668A (en) * | 2018-09-03 | 2019-02-22 | 北京邮电大学 | Cerebral disease forecasting system |
| CN109621152A (en) * | 2019-01-28 | 2019-04-16 | 邹珍友 | A method of without Interventional intervening animal cognition conscious activity and behavior with high field pulse laser |
| CN109875553A (en) * | 2019-03-27 | 2019-06-14 | 北京脑陆科技有限公司 | A kind of extensive epilepsy automatic detection early warning based on EEG equipment and treatment intelligence system |
| WO2019200918A1 (en) * | 2018-04-16 | 2019-10-24 | 顾继炎 | Medical device, algorithm updating method, medical system and external monitoring device |
| CN112674782A (en) * | 2020-12-22 | 2021-04-20 | 北京航空航天大学 | Device and method for detecting epileptic-like electrical activity of epileptic during inter-seizure period |
| CN113577559A (en) * | 2021-09-03 | 2021-11-02 | 复旦大学 | Closed-loop deep brain stimulation method, device, system and equipment based on multiple signals |
| WO2022166686A1 (en) * | 2021-02-05 | 2022-08-11 | 杭州诺为医疗技术有限公司 | Bioelectrical signal processing method and device in implantable closed-loop system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1255320A (en) * | 1999-12-03 | 2000-06-07 | 中国科学院上海生理研究所 | Method and equipment for automatically determining epileptic discharge threshould recognized by artificial nerve network |
| CN1260160A (en) * | 1998-12-30 | 2000-07-19 | 中国科学院上海生理研究所 | Full-automatic judging device for whether there is epileptic character discharge or not in electroencephalograph |
| CN2922792Y (en) * | 2005-07-21 | 2007-07-18 | 高春平 | Automatic epilepsia electroencephalo monitoring and diagnosis system |
| CN101569778A (en) * | 2009-03-10 | 2009-11-04 | 深圳先进技术研究院 | Biofeedback simulation system and biofeedback simulation method |
| CN201840480U (en) * | 2010-10-26 | 2011-05-25 | 东北大学 | Portable dynamic electroencephalogram monitor |
| US20110295332A1 (en) * | 2010-05-26 | 2011-12-01 | Flint Hills Scientific, L.L.C. | Quantitative multivariate analysis of seizures |
-
2012
- 2012-03-30 CN CN 201210097716 patent/CN102613971B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1260160A (en) * | 1998-12-30 | 2000-07-19 | 中国科学院上海生理研究所 | Full-automatic judging device for whether there is epileptic character discharge or not in electroencephalograph |
| CN1255320A (en) * | 1999-12-03 | 2000-06-07 | 中国科学院上海生理研究所 | Method and equipment for automatically determining epileptic discharge threshould recognized by artificial nerve network |
| CN2922792Y (en) * | 2005-07-21 | 2007-07-18 | 高春平 | Automatic epilepsia electroencephalo monitoring and diagnosis system |
| CN101569778A (en) * | 2009-03-10 | 2009-11-04 | 深圳先进技术研究院 | Biofeedback simulation system and biofeedback simulation method |
| US20110295332A1 (en) * | 2010-05-26 | 2011-12-01 | Flint Hills Scientific, L.L.C. | Quantitative multivariate analysis of seizures |
| CN201840480U (en) * | 2010-10-26 | 2011-05-25 | 东北大学 | Portable dynamic electroencephalogram monitor |
Cited By (29)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103156603A (en) * | 2012-11-20 | 2013-06-19 | 中国人民解放军第四军医大学第一附属医院 | Epileptic seizure pre-warning device |
| CN104623808A (en) * | 2013-11-14 | 2015-05-20 | 先健科技(深圳)有限公司 | Deep brain stimulation system |
| CN104623808B (en) * | 2013-11-14 | 2019-02-01 | 先健科技(深圳)有限公司 | Deep brain stimulation system |
| CN104173044A (en) * | 2014-08-15 | 2014-12-03 | 浙江大学医学院附属第二医院 | Closed-loop system used for epilepsy treatment |
| CN104112066B (en) * | 2014-08-18 | 2017-02-22 | 天津大学 | Epilepsy state closed-loop control experiment platform based on FPGA |
| CN104112066A (en) * | 2014-08-18 | 2014-10-22 | 天津大学 | Epilepsy state closed-loop control experiment platform based on FPGA |
| CN104225790B (en) * | 2014-09-19 | 2017-06-16 | 清华大学 | Closed loop neural stimulation system |
| CN104225790A (en) * | 2014-09-19 | 2014-12-24 | 清华大学 | Closed loop nerve stimulation system |
| CN105561474A (en) * | 2015-02-20 | 2016-05-11 | 邵志辉 | Device for treating epilepsy by stimulating vagus nerves of human body |
| CN105561474B (en) * | 2015-02-20 | 2019-05-17 | 泰州市人民医院 | A kind of device for treating epilepsy by stimulation human body vagus nerve |
| CN104799841A (en) * | 2015-04-27 | 2015-07-29 | 成都腾悦科技有限公司 | Biological electrical signal double-closed loop system |
| CN105999544A (en) * | 2016-05-04 | 2016-10-12 | 浙江大学 | Recording-stimulating mode switching device and application |
| CN105999544B (en) * | 2016-05-04 | 2019-10-18 | 浙江大学 | A kind of record-stimulus modality switching device and application |
| CN106726091A (en) * | 2016-12-22 | 2017-05-31 | 北京品驰医疗设备有限公司 | A kind of epilepsy sleep apnea prevention system of quickly-chargeable |
| CN106726091B (en) * | 2016-12-22 | 2021-11-23 | 北京品驰医疗设备有限公司 | Epileptic sleep apnea prevention system capable of achieving quick charging |
| CN107714035A (en) * | 2017-09-14 | 2018-02-23 | 中国人民解放军第四军医大学 | A kind of wearable digitlization eeg monitoring helmet |
| CN108175401A (en) * | 2017-12-08 | 2018-06-19 | 浙江大学 | A kind of undamaged epilepsy antithesis complimentary fashion monitoring and warning interfering system of non-contact non-intruding and the method for obtaining the electricity distribution of interference brain |
| CN108158579A (en) * | 2017-12-08 | 2018-06-15 | 浙江大学 | A kind of undamaged epilepsy self-organizing monitoring and warning interfering system of non-contact non-intruding and the method for obtaining the electricity distribution of interference brain |
| CN107981860B (en) * | 2017-12-08 | 2019-12-31 | 浙江大学 | Non-contact non-invasive nondestructive epilepsy path accessible mode monitoring and early warning intervention system and method for acquiring interference electroencephalogram distribution |
| CN107981860A (en) * | 2017-12-08 | 2018-05-04 | 浙江大学 | A kind of undamaged epilepsy path of non-contact non-intruding is up to mode monitoring and warning interfering system and the method for obtaining interference brain electricity distribution |
| WO2019200918A1 (en) * | 2018-04-16 | 2019-10-24 | 顾继炎 | Medical device, algorithm updating method, medical system and external monitoring device |
| US11317850B2 (en) | 2018-04-16 | 2022-05-03 | JV Scientific, Inc. | Medical device, algorithm updating method, medical system and external monitoring device |
| CN109363668A (en) * | 2018-09-03 | 2019-02-22 | 北京邮电大学 | Cerebral disease forecasting system |
| CN109621152A (en) * | 2019-01-28 | 2019-04-16 | 邹珍友 | A method of without Interventional intervening animal cognition conscious activity and behavior with high field pulse laser |
| CN109875553A (en) * | 2019-03-27 | 2019-06-14 | 北京脑陆科技有限公司 | A kind of extensive epilepsy automatic detection early warning based on EEG equipment and treatment intelligence system |
| CN112674782A (en) * | 2020-12-22 | 2021-04-20 | 北京航空航天大学 | Device and method for detecting epileptic-like electrical activity of epileptic during inter-seizure period |
| WO2022166686A1 (en) * | 2021-02-05 | 2022-08-11 | 杭州诺为医疗技术有限公司 | Bioelectrical signal processing method and device in implantable closed-loop system |
| CN113577559A (en) * | 2021-09-03 | 2021-11-02 | 复旦大学 | Closed-loop deep brain stimulation method, device, system and equipment based on multiple signals |
| CN113577559B (en) * | 2021-09-03 | 2022-07-26 | 复旦大学 | Closed-loop deep brain stimulation device, system and equipment based on multiple signals |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102613971B (en) | 2013-10-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102613971B (en) | Electroencephalograph (EEG)-based epilepsy detection and intervention device | |
| EP2429643B1 (en) | Patient state detection based on support vector machine based algorithm | |
| US8812098B2 (en) | Seizure probability metrics | |
| US8886323B2 (en) | Electrical brain stimulation in gamma band | |
| US20110009922A1 (en) | Systems and methods for improving a cognitive function | |
| CN207071165U (en) | A kind of Intelligent Composite waveform electrical transcranial stimulation system | |
| US20070244407A1 (en) | Evoked Response to Stimulation | |
| US20100121215A1 (en) | Seizure detection algorithm adjustment | |
| US8577470B2 (en) | Systems and methods for improving memory in Alzheimer's patients | |
| CN104622468B (en) | Deep brain stimulation system with external prediction function | |
| Liang et al. | A closed-loop brain computer interface for real-time seizure detection and control | |
| Bigelow et al. | Neural stimulation systems for the control of refractory epilepsy: a review | |
| CN203328702U (en) | Cap with brain wave and sign collecting function | |
| CN104623808A (en) | Deep brain stimulation system | |
| CN110327547A (en) | A kind of lesions located in deep brain system of multichannel thorniness stimulus | |
| CN202020792U (en) | Reaction type nerve electric stimulation system with external sleep detection device | |
| CN203763087U (en) | Sleep monitoring device | |
| CN114783585B (en) | Program control device, program control system, electronic device, and computer-readable storage medium | |
| CN105125186A (en) | Method and system for determining intervention treatment mode | |
| WO2021197267A1 (en) | Method and device for neuro-stimulation | |
| Chang et al. | A versatile wireless portable monitoring system for brain–behavior approaches | |
| US20240017069A1 (en) | Systems and methods for measuring and altering brain activity related to flexible behavior | |
| CN115430050A (en) | Charging reminding device, implantable nerve stimulation system and storage medium | |
| CN113180702A (en) | Alzheimer's disease nerve regulation and control method and system based on EEG signal | |
| CN111493896A (en) | Automatic early warning of sieve and intervention intelligent system of large-scale depression based on EEG equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |