CN100345526C - Multi-conduction brain biological information feedback instrument - Google Patents
Multi-conduction brain biological information feedback instrument Download PDFInfo
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Abstract
The present invention discloses a real-time EEG biofeedback training instrument based on DirectX 3D by adopting 3D auditory and visual stimulation as the feedback means. The instrument is provided with hardware which is composed of a plurality of scalp electrodes, an EEG signal extraction module, a hardware real-time EEG signal processing module and a computer, wherein EEG biofeedback training software is installed in the computer. The instrument eliminates real-time interference and physiological artifacts by adopting a method that wavelet packet analysis is realized by the hardware while adopting a digital signal processing method such as a data fusion algorithm, spectral analysis, etc. to select the precise characteristic information so as to obtain the accurate real-time feedback of treatment information. The instrument adopts the 3D auditory and visual stimulation as the feedback training means so that the feedback stimulation is more individualized and truer. The instrument adopts a 3D scene which has very strong reality and background music so that a patient can successfully complete the feedback training. The instrument has the advantages of simple operation and friendly interface, and can be easily accepted by doctors and patients without requiring that a user has programming experience and without complicated operation.
Description
Technical field
The present invention relates to a kind of medical supplementary instrument, particularly a kind of real-time brain biological information feedback instrument, this feedback apparatus can be handled in real time to EEG signals, and is support with the psychology, adopts three-dimensional audiovisual to stimulate as the real-time brain biological information feedback instrument of leading of feedback means more.
Background technology
Biofeedback technology is to grow up according to Pavlov's classical conditioned reflex is theoretical the earliest.Western countries' discovering over nearly 40 years, the foundation of the classical conditioned reflex of regulating by the central nervous system, be not only effective to voluntary muscle, and the viscera function that autonomic nervous system is controlled, as blood vessel, tracheal smooth muscle tensity, the rhythm and pace of moving things of breathing, pulse is so that effective equally to the form and the rhythm and pace of moving things of brain electricity.By advanced person's instrument, by study and training, the autonomic nervous system of human body can be set up operant conditioned reflex, thereby changes its function status.
The brain function biofeedback is that EEG (electroencephalogram) biofeedback is a kind of method that is used to remove the physiology and the biofeedback therapy of psychology discomfort.It is by the EEG signals of gathering the experimenter and shows in some way, controls self brain wave pattern consciously with the training experimenter, reaches the purpose of treatment.Brain function biofeedback therapy technique functions comes from the seventies, form second peak in nineteen nineties, have 21 biofeedback association in the U.S. at present, be widely used in medical treatment, education sector, obtained obvious effects, in European Union, also extensively carried out biofeedback therapy, but in China substantially for the stage of beginning one's study.
The researcheres of EEG biofeedback are thought, by training constantly, the experimenter can the regulated at will brain wave rhythm and pace of moving things increase or minimizing, the purpose of this feedback therapy is exactly to induce with nerve to loosen relevant brain wave, and produce lasting effect by repetition training, make brain form a kind of " custom ", henceforth it just can constantly produce healthy brain wave pattern.
The A620 brain electricity biological feedback treatment system that existing brain electricity bio-feedback therapeutic apparatus mainly is a U.S. Rui Feier company, the BioGraph biological feedback system of European Mai Yingde-Si Biruite company etc., the domestic like product that yet there are no.But these several bio-feedback therapeutic apparatus devices all are to adopt software to finish treatment, but also exist more defective, and it mainly is:
1), all be with the unitary electrode signal as feedback information, and it places mostly in top area, and does not meet the prior theory basis, can't bring into play the sharpest edges of brain electricity biofeedback therapy, and specific aim is not strong;
2), instrument all be with single-frequency information as feedback signal, quantity of information is smaller, and feature is very not clear and definite, can not obtain accordingly carrying out feedback treating at patient's characteristic information;
3), Feedback Design all is based on the plane recreation, it is more single to play, and can not well cause experimenter's attention, influences the result of feedback treating.In addition, these a few money instruments all are foreign brand names, the complete westernization of software, and be not suitable for China's actual conditions, its complicated operation costs an arm and a leg, and is not fit to the model of domestic.
Summary of the invention
The objective of the invention is to, providing a kind of is support with the psychology, adopts the multi-conduction brain biological information feedback instrument of three-dimensional audiovisual stimulation as feedback means.
For achieving the above object, the present invention takes following technical solution: a kind of multi-conduction brain biological information feedback instrument is characterized in that the hardware of this instrument comprises:
A plurality of scalp electrodes are used for eeg signal acquisition, and sample frequency is 128Hz or 256Hz, and the EEG signals of gathering is sent into the EEG signals extraction module;
The EEG signals extraction module is used for electroencephalograpsignal signal extraction, amplification and Filtering Processing, and amplifying signal is sent into the real-time EEG Processing module of hardware after converting digital signal to by 16 A/D;
The real-time EEG Processing module of hardware, be used for the digital signal of A/D conversion is carried out pretreatment, adopt the method for WAVELET PACKET DECOMPOSITION, wavelet threshold further to eliminate interference and physiology artifact, and utilize neutral net, spectrum analysis and data anastomosing algorithm that signal is carried out real-time characteristic information and extract, and the EEG signals after will handling and in real time the characteristic information bag send into computer by the USB coffret, be provided with the software that is used to support brain electricity biofeedback training in the computer.
The software of described support brain electricity biofeedback training is by constituting with lower module;
One administration module is used for training process and experimenter's information are managed, and comprises establishment, inquiry, modification, the deletion of trainer's information, and the selection of training program, and the storage of the desired index of feedback training scheme and form and data is set;
One data base is used to store training program, trainer's the information and the process storage of training thereof;
One feedback training module, predefined training quota is arranged in this module, the scheme that is used for selecting according to the trainer is carried out three-dimensional audio-visual information feedback training to the trainer, and read desired characteristic information the feedback training scheme and pre-set training quota compares from the communication logic module, if reach training quota, then feedback training is proceeded, otherwise, wait for that then characteristic information meets training quota and trains, or reset the feedback training index;
One display module is made up of printing as a result, brain electricity analytical, brain electricity demonstration three parts, is used for showing in real time trainer's Active electroencephalogram (EEG), monitors trainer's brain electricity situation of change in real time;
One off-line analysis module is used for the EEG signals data that obtain after the pretreatment of real-time EEG Processing module are carried out feature analysis at time-frequency domain, for the experimenter provides feedback training scheme correctly;
One communication logic module is used to solve the source synchronous visit between a plurality of threads, makes thread can correctly visit shared resource;
One data acquisition module is used to gather the real-time characteristic information bag of the pretreated EEG signals of the process of being transmitted up by USB and this signal, and the data of collection are sent into EEG signals after-treatment module;
One EEG signals after-treatment module is used for the data of the real-time EEG Processing module of hardware are further processed, and eliminates the distorted signals in the transmission course, and the information in the characteristic information bag extracted sends into the communication logic module;
Administration module is connected with off-line analysis module, data acquisition module, feedback training module, data base, display module respectively, the feedback training module is connected with the communication logic module, the communication logic module also is connected with display module, and data acquisition module is communicated with the communication logic module by EEG signals after-treatment module
Instrument of the present invention has following technical characterstic:
1. gather the EEG signals extraction feedback treating information of leading that a plurality of scalp electrodes obtain more, can place different positions, extract EEG signals with treatment dependency maximum according to different needs;
2. adopt the method for wavelet packet analysis to eliminate interference and physiology artifact and adopt data anastomosing algorithm and new digital signal processing methods such as neutral net, spectrum analysis, extract more accurate characteristic information, thereby obtain feedback treating information more accurately;
3. adopt hardware to realize the pretreatment and the feature extraction of real-time EEG signals, improve arithmetic speed greatly, thereby better guarantee the real-time of feedback training.
4. the design of three-dimensional audio-visual information feedback relies on the design psychology from patient's angle, and the design on content and form all takes into full account the disease of patient type, the age, and sex, personality makes every effort to targetedly the patient be trained.
5. adopt three-dimensional audiovisual to stimulate, feedback is stimulated more be added with personalization and sense of reality as the feedback training means.Aspect the exploitation of audio-visual information feedback form, the DirectX of employing Microsoft company develops the audio-visual information feedback of three-dimensional scenic.The powerful DirectX of language function can render the very strong three-dimensional scenic of sense of reality, is equipped with suitable background music, makes the trainee that sensation on the spot in person can be arranged, and wherein interspersed special audio effect is focused one's attention on the patient and finished the feedback training task.
6. friendly simple man machine interface: medical apparatus of the present invention, the use of system is simple, and friendly interface is easy to doctor and patient and accepts simultaneously.System does not require that user has the programming experience, does not provide the complicated operations environment.
Description of drawings
Fig. 1 is the hardware block diagram of brain electricity bio-feedback therapeutic apparatus of the present invention;
Fig. 2 is the systems soft ware block diagram of brain electricity bio-feedback therapeutic apparatus;
Fig. 3 be eeg signal acquisition, with drawing subprogram flow graph;
Fig. 4 is the development process figure of whole audio-visual information feedback training;
Fig. 5 is an audio-visual information feedback training preliminary examination flow chart;
Fig. 6 is audio-visual information feedback training circulation process figure;
Fig. 7 plays up frame figure and display module particular flow sheet;
Fig. 8 is " space is roamed " audio-visual information feedback training surface chart;
Fig. 9 is brain electricity biofeedback therapy instantiation figure;
Figure 10 is the analog power of specific implementation of the present invention and a kind of circuit theory diagrams of isolation module.
Figure 11 is a kind of circuit theory diagrams of the pre-amplifying module of specific implementation of the present invention.
Figure 12 is a kind of circuit theory diagrams of the analog filter block module of specific implementation of the present invention.
Figure 13 is a kind of circuit theory diagrams that the alternating current of specific implementation of the present invention is converted to the DC voltage module.
Figure 14 is a kind of circuit theory diagrams of the generation 3V voltage module of specific implementation of the present invention.
Figure 15 is a kind of circuit theory diagrams of the generation 1.8V voltage module of specific implementation of the present invention.
Figure 16 is a kind of circuit theory diagrams of the reset circuit module of specific implementation of the present invention.
Figure 17 is a kind of circuit theory diagrams of the analog-to-digital conversion module of specific implementation of the present invention.
Figure 18 is a kind of circuit theory diagrams of the usb interface module of specific implementation of the present invention.
Figure 19 is a kind of circuit theory diagrams of the arm processor module of specific implementation of the present invention.
The present invention is described in further detail below in conjunction with accompanying drawing.
The specific embodiment
The present invention adopts three-dimensional audiovisual to stimulate as feedback means, brain electricity biofeedback training instrument based on DirectX3D, the hardware of this instrument is by a plurality of scalp electrodes, the EEG signals extraction module, the real-time EEG Processing module of hardware, form with computer, be provided with the software that is used to support brain electricity biofeedback training in the computer.
This instrument is at the audio-visual information feedback training type difference of patient's design of dissimilar diseases; be example now with hyperkinetic syndrome (ADHD) patient; the specific design process of audio-visual information feedback training is described: ADHD patient mostly is 5～12 years old child greatly; be characterized in that intelligence normally or normal substantially; have the attention that does not conform to the age and concentrate difficulty; how moving, emotion and dystropy.The exploitation of audio-visual information feedback training interface and form just need design at patient's age and psychology.
In design, the audio-visual information feedback training mainly is that the feature at attention designs, and mainly considers the following aspects: (1), the directivity of noting: mental activity selectively reflects certain object, and leaves remaining object.(2), the centrality of noting: mental activity rests on intensity or the tensity on the selecteed object, and it makes mental activity leave all irrelevant things, and suppresses unnecessary activity.(3), the stability of Zhu Yiing: refer to the time that attention can continue in same target or same activity.This is the feature of noting in time.(4), the distribution of Zhu Yiing: the same time is interior the different object of notice point.
We will be at each feature of noting, all ages and classes, and different symptoms, the experimenter of different personality designs dissimilar and audio-visual information feedback training difficulty.In therapeutic process, require the child to keep attention to concentrate, so require the audio-visual information feedback training very strong captivation and sensation on the spot in person will be arranged to the child as far as possible.
Concrete enforcement is as follows:
1. the hardware of system constitutes
Brain electricity bio-feedback therapeutic apparatus system hardware block diagram is seen Fig. 1.
1.1 EEG signals extraction module
EEG signals is led after the brain electrode pick off extracts into by 3, by EEG preamplifier faint EEG signals is amplified, by an analog filter original EEG signals is carried out the power frequency Filtering Processing, amplifying signal converts digital signal to by 16 A/D, sends into the real-time EEG Processing module of hardware.
1.2 EEG signals real-time processing module
In real time the EEG Processing module is to be that the LPC2104/2105/2106 microprocessor and the peripheral circuit thereof of core realized with ARM7-TDMI-S by PHILIPS Co..Though analogue signal is handled through analog filtering, amplify by amplifier, there are some interference in addition in the signal of being gathered into by A/D and have some physiology artifacts (for example: electrocardio, eye are electric, myoelectricity or the like).False judgment in feedback procedure, to occur in order reducing, need to carry out pretreatment the signal of gathering.We adopt technology such as WAVELET PACKET DECOMPOSITION, wavelet threshold that signal is carried out real-time pretreatment, with further elimination interference and physiology artifact, for further analyzing the brain electricity and carrying out feedback treating and prepare.Select for use suitable wavelet analysis can finely satisfy the requirement that on-line analysis system midbrain electricity artifact is removed.The particularly application of wavelet packet makes the meticulous division in frequency domain space more to help the removal of artifact and the extraction of signal characteristic.The method to the artifact signal subtraction that we propose can be eliminated the eye movement artifact at the EEG signal rapidly, effectively, and filtered signal is more suitable for extracting the EEG feature.Simultaneously, adopt methods such as data anastomosing algorithm, neutral net, spectrum analysis to carry out feature extraction for requirement to pretreated brain electricity digital signal according to the upper strata master computer.Because these algorithms all are to realize, have very fast arithmetic speed, can satisfy the requirement that we handle in real time on hardware.Relevant concrete WAVELET PACKET DECOMPOSITION, wavelet threshold rolled up for 12 phases referring to " XI AN JIAOTONG UNIVERSITY Subject Index " 38, " research of the method for EEG signals eye electricity artifact removal in real time ", author: Liu Mingyu, Wang Jue, Wei Na, Yan Nan, Zheng Chongxun.
1.3USB transmission
Adopt the computer USB interface to send into computer through pretreated EEG signals and the real-time characteristic information bag of this signal.
Computer adopts multithreading that the digital signal of transmission is carried out real-time signal acquisition and analysis, demonstration and feedback treating, promptly outside the management main thread, simultaneously collection, demonstration and the feedback treating worker thread of enabling signal, can be real-time signal is shown and carries out feedback treating.Can finish the back in signals collecting simultaneously electroencephalogram is stored and printed to data.
2. the software of system constitutes
2.1 operating system platform
With the Windows2000 of Microsoft company of Microsoft, WindowsXP, Windows2003 are first-selected, along with the update of microsoft operation system, also can consider other operating systems.
2.2 development platform and developing instrument
This system adopts the matured product Microsoft Visual Studio.Net2003 of Microsoft company as development platform.Adopt Visual C# as developing instrument, also in conjunction with SQL Server data base, Matlab
In the mathematical function library that provides develop.The design that three-dimensional audiovisual feedback stimulates adopts the DirectX 8.1 of Microsoft company as developing instrument.
2.3 the specific implementation of systems soft ware
The software of brain electricity bio information feedback treating instrument has mainly been realized dynamic demonstration, printing and the brain biological information feedback training module of the collection of brain electricity and processing, brain electricity.The structured flowchart of systems soft ware is seen accompanying drawing 2.
2.3.1 data acquisition module
The data acquisition module of EEG signals mainly is to be finished by the sub-thread of data acquisition, sample frequency is that 128Hz or 256Hz software are optional, owing to adopt multithreading to carry out data acquisition, gap in data acquisition, the real-time pretreatment module of EEG signals is done further pretreatment to the digital signal that collects host computer and is handled, and eliminates the interference that is produced in transmission course.
2.3.2 feedback training module
Predefined training quota is arranged in this module, the scheme that is used for selecting according to the trainer is carried out three-dimensional audio-visual information feedback training to the trainer, and read desired characteristic information the feedback training scheme and pre-set training quota compares from the communication logic module, if reach training quota, then feedback training is proceeded, otherwise, wait for that then characteristic information meets training quota and trains, or reset the feedback training index simultaneously, after the patient finishes a certain training, system can give the award of sound or image, carries out feedback training with this.
Shown in the development process of whole audio-visual information feedback training (seeing accompanying drawing 4), enter after the audio-visual information feedback training, at first to each object of program is carried out initialization, enter audio-visual information feedback training circulation module then, carry out the treatment of audio-visual information feedback training, after treatment finishes, withdraw from treatment.
Its specific implementation illustrates from the following aspects:
● audio-visual information feedback training initialization module: in this module, relate to acoustic processing, the initialization of input equipment etc. to Direct3D.Mainly be to carry out some Memory Allocation, collection of resources, be written into data etc. from disk, audio-visual information feedback training preliminary examination flow process (seeing accompanying drawing 5):
A) initial Direct three-dimensional: the three-dimensional equipment of Direct of creating us according to the display mode of different video cards.
B) initialization DirectAudio:DirectAudio is integrated by DirectSound and DirectMusic and forms.Needed sound, music in the audio-visual information feedback training are handled.
C) initialization DirectInput: in this module, need to inquire about the GUID of device therefor (mouse, keyboard), create mouse, keyboard equipment by corresponding GUID.After the basic initialization achievement of each module, just can use each assembly to develop the audio-visual information feedback training.
D) initialization lights: the simulation light that initialization needs in the audio-visual information feedback training.
● enter audio-visual information feedback training circulation module: in this module, this module mainly is to enter a circulation, responding system message, and the model in the audio-visual information feedback training played up.Audio-visual information feedback training circulation process.
● obtain input message and logic processing module: in this audio-visual information feedback training, input message mainly comes from the message whether electric index of the brain of setting in the therapeutic scheme reaches.If touch the mark, then obtain message, control audio-visual information feedback training carries out in the Message Processing pattern, simultaneously the message that obtains is counted, and judges whether to finish the audio-visual information feedback training.
● play up frame figure and display module: this module mainly is that the various models that occur in the audio-visual information feedback training are played up, the carrying out of control audio-visual information feedback training.Play up frame figure and display module idiographic flow (seeing accompanying drawing 7).The pictorial display process is: remove lookaside buffer (invisible) earlier, will objects displayed be plotted on this piece memory field again by certain logic, after having drawn, it is turned on the visible preceding relief area, the picture refreshing rate of general audio-visual information feedback training can reach for 30 frame/seconds, picture overturns with this speed, adds the delay effect of eyes, and it is successive that the image of seeing is become.
2.3.3 administration module
This module mainly is that therapeutic process is managed.After the user opened brain electricity bio-feedback therapeutic apparatus systems soft ware, the feedback training module of selecting the experimenter to carry out was provided with the function of the desired index of feedback training scheme and form and data on file.
2.3.4 show and results analyses module
This module mainly is to be finished by demonstration and the sub-thread of interpretation of result.Major function has: the brain electricity shows that brain electricity analytical and result print.
2.3.4.1 the brain electricity shows
It is the Active electroencephalogram (EEG) of making the patient who accepts feedback training that brain electricity shows, is that the EEG signals waveform dynamic real-time ground with the person of undergoing training is presented on the display, and native system has been realized that electroencephalogram does not dynamically have and traced.
2.3.4.2 brain electricity analytical
This module is by carrying out after-treatment to the EEG signals that obtains after the pretreatment, to obtain the histogrammic Real time dynamic display of index such as EEG power spectrum array of figure and brain electricity θ, α, β, realize brain electricity index real-time monitoring, the doctor changes by the every index of this function Real Time Observation patient brain electric information, grasp patient's brain function state intuitively, exactly, in order to the effect of monitoring feedback treating.
2.3.4.3 the result prints
No matter be all can export by PRN device at the dynamic demonstration or the electroencephalogram power spectrum array of brain wave.
2.3.5 off-line analysis module
This module is by carrying out after-treatment to the EEG signals that obtains after the pretreatment, adopt methods such as spectrum analysis, power spectrumanalysis, wavelet transformation, neutral net that eeg data is carried out feature analysis at time-frequency domain, work alone, be used to understand the rule and the pattern of a certain particular subject brain electrical acti, the feedback training scheme provides scientific basis for the experimenter provides correctly.
2.3.6 data base's support module
All data of native system are all stored by data base's back-up system (DBSS).Data storage mainly divides two classes, and the first kind is the person's of undergoing training a essential information, comprising: trainee's numbering, name, sex, age, the scheme of undergoing training, the number of times of undergoing training, contact address etc.Second class is the eeg data of this trainee when undergoing training in the last time.Except scheme of undergoing training and the number of times of being trained changed, primary sources were constant substantially.Secondary sources can often change, the EEG signals data when only storage the last time trains.In addition, native system can be the file of XML form with data storage also, to be used for later online transmission and far call.
Below be the concrete working method that example illustrates this invention with treatment attention deficit companion hyperkinetic syndrome patient.At first, start the brain bio-feedback therapeutic apparatus, accept the information of patient's registration earlier oneself of feedback training, comprising information such as trainee's numbering, name, sex, ages.Then, the doctor according to will at the symptom position of select placing multilead electrode, open real-time eeg recording, patient's EEG signals is by after leading the brain electrode pick off more and extracting into, by EEG preamplifier faint EEG signals is amplified, simultaneously original EEG signals is carried out the power frequency Filtering Processing, amplifying signal converts digital signal to by 16 A/D, by the preprocessor of calling in the EEG signals real-time processing module EEG signals is carried out pretreatment to reduce the interference of artifact, correctness when guaranteeing feedback treating, send into computer by USB interface then, be presented on the screen in real time then.The doctor calls corresponding signal process program in the brain electricity analytical signal of gathering is carried out after-treatment, obtains the eigenvalue of feedback information, and the relevant parameter of feedback treating is set according to eigenvalue.
Set after the relevant parameter, start the feedback treating program.After the amplification of EEG signals process, collection, the pretreatment, adopt new signal processing method that the EEG signals that reads is decomposed in real time, obtain the different frequency composition, then known multi-source feature fusion technology is handled, finally draw one at attention deficit training quota this individuality, that eliminate uncertain factor, be used to carry out feedback treating.The three-dimensional audio-visual information back-to-back running of feedback treating part is to control by the index that obtains of front.When patient's EEG signals reaches certain threshold value, three-dimensional audio-visual information feedback is according to feeding back to the patient by special sound effect or other award method, patient's EEG signals is changed by self regulating of a period of time, thereby regulate the functional status of brain.The design of three-dimensional audio-visual information feedback on psychologic angle, at all ages and classes, different symptoms, the experimenter of different personality designs the three-dimensional audio-visual informations feedback of dissimilar and difficulty.Aspect the exploitation of the three-dimensional audio-visual information feedback of recreation, the recreation that the DirectX of employing Microsoft company develops three-dimensional scenic.The powerful DirectX of language function can render the very strong three-dimensional scenic of sense of reality, be equipped with suitable background music, make the trainee that sensation on the spot in person can be arranged, wherein interspersed special audio effect helps the trainee that the patient is focused one's attention on and finishes the feedback training task.
Photopic vision listens the working method of information feedback training to have three airplanes to roam through space in this audio-visual information feedback training so that a kind of audio-visual information feedback training for the treatment of attention deficit companion hyperkinetic syndrome patient is example, control an airplane by the patient, detect patient's aircraft and whether can first reach home.In the audio-visual information feedback training, handle by brain electricity the patient, whether the brain wave of analyzing in the characteristic frequency reaches the speed that threshold value is controlled aircraft of rewarding, the speed of other two airplanes is by the computer setting, remain and the similar speed of air speed audio-visual information feedback training interface (seeing accompanying drawing 8) by the electric control of patient's brain.
After starting the audio-visual information feedback training,, enter audio-visual information feedback training circulation module then at first to each object initialization, responding system message, and the model in the audio-visual information feedback training played up the carrying out of control audio-visual information feedback training.The concrete operations of audio-visual information feedback training are such: the speed that aircraft is set is 1-15, in the time of initial, the aircraft starting velocity that the patient controls is 1, when patient's EEG signals reaching in special frequency channel rewarded threshold value when getting, the speed of aircraft adds 1, when patient's EEG signals was lower than continuous inhibition threshold value, the speed of aircraft subtracted 1.When air speed was 1, even patient's EEG signals is lower than the inhibition threshold value, or else the speed of aircraft also reduced; When air speed was 15, even patient's brain electricity reaches the award threshold value, the speed of aircraft also no longer raise.Airplane in addition adds the random number between-2 and 2 at random on the speed basis of the aircraft of patient's brain electric control.The persistent period of audio-visual information feedback training is 3 minutes.
In the process of audio-visual information feedback training, system can store patient's EEG signals get off automatically, and the doctor can be after the patient finishes feedback treating, and this EEG signals of playback is also analyzed, printed, in order to the therapeutic process of monitor patients.
Referring to Figure 10-19, Figure 10-the 19th, a kind of circuit theory diagrams of specific implementation of the present invention, the analogue signal of brain electrode collection at first enters pre-amplifying module, through being amplified into analog filter block, after handling through analog filtering, analogue signal is sent into analog-to-digital conversion module by photoelectric isolation module.Photoelectric isolation module mainly is to play simulation part and numerical portion is isolated mutually, and to prevent mutual interference, analog power is powered for the simulation part.Analog-to-digital conversion module carries out analog digital conversion to analogue signal, send into the arm processor module after changing into digital signal, the arm processor module is carried out pretreatment and feature extraction to brain electricity digital signal earlier, then signal after handling and real-time characteristic information bag are sent into usb interface module, send into master computer by USB interface.Alternating current is converted to the DC voltage module, produces the 3V voltage module, produces the 1.8V voltage module, the reset circuit module all is the needed peripheral circuit module of arm processor module.
Referring to Figure 10, Figure 10 is the analog power of specific implementation of the present invention and a kind of circuit theory diagrams of isolation module.Main chip is ISO122U among the figure, is applied to optocoupler amplifier usually.
Referring to Figure 11, Figure 11 is a kind of circuit theory diagrams of the pre-amplifying module of specific implementation of the present invention.Main chip is INA128U among the figure: this chip is a low noise, and low-power consumption is the amplifier that the high precision instrument is used, and is used for the preposition amplification of EEG signals.
Data:
1. amplification 1--10K
2.CMRR 100dB G＝10 120dB G＝100
3. noise 0.2uVp-p f=0.1-10Hz
Referring to Figure 12, Figure 12 is a kind of circuit theory diagrams of the analog filter block of specific implementation of the present invention.
Referring to Figure 13, Figure 13 is a kind of circuit theory diagrams that the alternating current of specific implementation of the present invention is converted to the DC voltage module.
Referring to Figure 14, Figure 14 is a kind of circuit theory diagrams of the generation 3V voltage module of specific implementation of the present invention.
Referring to Figure 15, Figure 15 is a kind of circuit theory diagrams of the generation 1.8V voltage module of specific implementation of the present invention.
Referring to Figure 16, Figure 16 is a kind of circuit theory diagrams of the reset circuit module of specific implementation of the present invention.
Referring to Figure 17, Figure 17 is a kind of circuit theory diagrams of the analog-to-digital conversion module of specific implementation of the present invention.
Main chip is the ADS7844E:AD switching device among the figure, and maximum speed 200K, supports 8 passages at most by 12.
Referring to Figure 18, Figure 18 is a kind of circuit theory diagrams of the usb interface module of specific implementation of the present invention.
Main chip is PDIUSBD12 among the figure: the USB interface chip that meets the USB1.1 agreement that PHILIPS Co. produces, use more extensive.
Referring to Figure 19, Figure 19 is a kind of circuit theory diagrams of the arm processor module of specific implementation of the present invention.Main chip is LPC2104/2105/2106 among the figure: be the processor of core with ARM7TDMI, the highest core work frequency 60M adopts risc instruction set, the treatment effeciency height.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101779955B (en) * | 2010-01-18 | 2012-01-04 | 南京大学 | Portable brain function biofeedback instrument |
Families Citing this family (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2045690A1 (en) * | 2007-10-04 | 2009-04-08 | Koninklijke Philips Electronics N.V. | Improvements relating to brain computer interfaces |
| WO2009155516A2 (en) * | 2008-06-20 | 2009-12-23 | Medrelief Inc. | Systems, apparatuses, and methods for providing non-transcranial electrotherapy |
| CN101862194B (en) * | 2010-06-17 | 2011-11-16 | 天津大学 | Imagination action EEG identification method based on fusion feature |
| CN102389306B (en) * | 2011-06-27 | 2013-06-12 | 北京高懋电子信息技术有限公司 | Automatic identification method of electroencephalogram artifact and automatic identification electroencephalograph using same |
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| CN106407733A (en) * | 2016-12-12 | 2017-02-15 | 兰州大学 | Depression risk screening system and method based on virtual reality scene electroencephalogram signal |
| CN108965625B (en) * | 2018-07-02 | 2020-07-31 | 昆明理工大学 | An automatic pager based on brain-computer interface and its training method |
| CN110478593A (en) * | 2019-05-15 | 2019-11-22 | 常州大学 | Brain electricity attention training system based on VR technology |
| CN111887845A (en) * | 2020-07-31 | 2020-11-06 | 昆明理工大学 | Attention regulation system based on EEG nerve feedback |
| CN113456087A (en) * | 2021-08-18 | 2021-10-01 | 乔月华 | Tinnitus diagnosis and treatment system based on neurobiological feedback therapy and use method thereof |
| CN118760842A (en) * | 2024-08-08 | 2024-10-11 | 佛山大学 | Music screening method and system for music therapy |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4195626A (en) * | 1977-03-29 | 1980-04-01 | Schweizer Helgi Jon | Device for the production and application of body stimuli structures |
| US4736751A (en) * | 1986-12-16 | 1988-04-12 | Eeg Systems Laboratory | Brain wave source network location scanning method and system |
| US4949725A (en) * | 1988-07-01 | 1990-08-21 | Bio-Logic Systems Corporation | Apparatus and method for displaying electrical activity generated within a living body |
| CN1196198A (en) * | 1998-03-26 | 1998-10-21 | 成都学成生物工程有限公司 | Earthworm lactate nutrient solution and preparation method thereof |
| CN2509681Y (en) * | 2001-11-23 | 2002-09-04 | 罗一峰 | Visible musical electroencephalic biological feedback instrument |
| US6507754B2 (en) * | 2000-04-27 | 2003-01-14 | Centre National De La Recherche Scientifique | Device for the medical monitoring in real time of a patient from the analysis of electroencephalograms |
| CN1564671A (en) * | 2001-10-05 | 2005-01-12 | 克林尼科特公司 | System utilizing noninvasive biofeedback signals |
-
2005
- 2005-12-15 CN CNB2005101245505A patent/CN100345526C/en not_active Expired - Fee Related
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4195626A (en) * | 1977-03-29 | 1980-04-01 | Schweizer Helgi Jon | Device for the production and application of body stimuli structures |
| US4736751A (en) * | 1986-12-16 | 1988-04-12 | Eeg Systems Laboratory | Brain wave source network location scanning method and system |
| US4949725A (en) * | 1988-07-01 | 1990-08-21 | Bio-Logic Systems Corporation | Apparatus and method for displaying electrical activity generated within a living body |
| CN1196198A (en) * | 1998-03-26 | 1998-10-21 | 成都学成生物工程有限公司 | Earthworm lactate nutrient solution and preparation method thereof |
| US6507754B2 (en) * | 2000-04-27 | 2003-01-14 | Centre National De La Recherche Scientifique | Device for the medical monitoring in real time of a patient from the analysis of electroencephalograms |
| CN1564671A (en) * | 2001-10-05 | 2005-01-12 | 克林尼科特公司 | System utilizing noninvasive biofeedback signals |
| CN2509681Y (en) * | 2001-11-23 | 2002-09-04 | 罗一峰 | Visible musical electroencephalic biological feedback instrument |
Non-Patent Citations (3)
| Title |
|---|
| 基于脑电信号的意识信息提取与表达：脑-机接口 刘海龙，王珏，中国康复理论与实践，第Vol.11卷第No.3期 2005 * |
| 基于非线性参数的意识任务分类 刘海龙，王珏，郑崇勋，西安交通大学学报，第Vol.39卷第No.8期 2005 * |
| 实时脑电信号电伪差去除方法的研究 刘明宇，王珏，魏娜，燕楠，郑崇勋，西安交通大学学报，第Vol.38卷第No.12期 2004 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101779955B (en) * | 2010-01-18 | 2012-01-04 | 南京大学 | Portable brain function biofeedback instrument |
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