CN103083014A - Method controlling vehicle by electroencephalogram and intelligent vehicle using method - Google Patents
Method controlling vehicle by electroencephalogram and intelligent vehicle using method Download PDFInfo
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Abstract
The invention provides a method controlling a vehicle by electroencephalogram and an intelligent vehicle using the method. The method includes that a destination which is expected to reach by a user is identified by collecting and analyzing an electroencephalogram signal when the user watches a corresponding destination and is stimulated, then the destination is transmitted to a self-navigation system of the intelligent vehicle, and a vehicle is moved to the destination by the self-navigation system. Any limb motion and language are not needed, only a task of a brain-machine interface needs conducting by the user, a command is obtained by analysis of the brain signal, and movement of the intelligent vehicle is achieved.
Description
Technical field
The present invention relates to a kind of intelligent vehicle that utilizes the method for brain electric control vehicle and utilize the method.Specifically refer to, utilize brain wave to carry out the method for destination choice and the intelligent vehicle that utilizes the method to control, EEG signals when this intelligent vehicle (the especially control system of intelligent vehicle) is watched destination's stimulation attentively by sensor collection and user, by analyzing EEG signals, identify user's intention, then user-selected destination information is sent to the autonomous navigation system of intelligent vehicle, and control thus intelligent vehicle and move and arrive destination.The method that the present invention proposes without any need for limb motion and language, only need the user to carry out the task of brain-computer interface, obtain order by the analysis to corresponding EEG signals, realize the movement of intelligent vehicle.The invention belongs to the integrated application of cognitive neuroscience, areas of information technology and automation field.
Background technology
For the patient of limb movement disturbance, can get at outdoor moving becomes a kind of dream of these patients.In the existing vehicle of helping the disabled, mainly take wheelchair (scooter) as main.Common wheelchair need to have external force promotion wheelchair to move, and perhaps the two-wheel by wheelchair user self rotation wheelchair moves; And intelligent wheel chair is take electric wheelchair as the basis, on the basis of traditional electric wheelchair, various calculation control unit have been increased, the smart machine such as sensing detection unit, the variable signal of handle being controlled voltage by calculation control unit is transferred to motor, realizes the control to intelligent wheel chair.Yet for extremity all can not the High Paraplegia of valid function, operating grip was also a very difficult thing.Therefore researcher is according to different crowds, develop different suitable various crowds' intelligent wheel chair, as: the modes such as key control are controlled, pressed to the suitable reasonable crowd's of limbs motility action bars, is fit to the poor crowd's of limbs motility the modes such as voice control, electromyographic signal control and brain electric control.
Based on the control mode of brain electricity, directly set up the communication between people's brain and controlled physical equipment (for example intelligent wheel chair), user's intention directly can be passed to motion control unit by brain.Realize not passing through fully the control of the physical equipment to external world of limb motion or other body kinematics.Can satisfy the demand that the serious dyskinesia person of limbs moves.But existing various intelligent mobility-aid apparatus is all take electric wheelchair as the basis.And wheelchair is seriously limited aspect speed and range of activity, so also just causes user's range of activity can only be confined to the range of activity of wheelchair, the self-care ability that can't further extend one's service and activity space.
Vehicle is as the manned mobile device of a high-speed cruising, all is being better than from far away wheelchair aspect the scope of activity and speed.But for the physical handicaps person, the control of vehicle be one more than many processes of wheelchair control complexity.For the control to vehicle, far mobility-aid apparatus higher than low cruises such as wheelchairs is wanted in the requirement aspect speed and safety.The limitation of brain-computer interface technology aspect real-time and accuracy is can't satisfy completely at a high speed and the requirement of safety.How according to the mode of brain-control wheelchair, realize by the brain electricity, the control of vehicle just being become a serious problem that the restriction brain-control vehicle develops.
In fact, the advantage of the aspects such as intelligent control function, intelligent navigation function and intelligent barrier avoiding function that existing intelligent vehicle can utilization itself has, under the rule that sets in advance, required completing of the task of autonomous completing user.That is to say that the user can set the control to intelligent vehicle in advance, remaining work can be completed by the intelligence part of intelligent vehicle itself fully.The user has just completed the work of selecting like this, and more work can realize by the function of vehicle itself, needs only the reaction user's that user's selection result can be correct purpose, and intelligent vehicle itself is the effective needs of completing user just.
Existing brain-computer interface mode is mainly P300, SSVEP and MI three classes, and wherein P300 is owing to can providing the multiple choices item, and P300 brain-computer interface mode has higher accuracy rate simultaneously, so this mode is having obvious advantage aspect multinomial selection control.Although the brain-computer interface mode of which kind of mode no matter, identification completely accurately can't realize, passes through confirmation repeatedly, but can well ensure the identification of intention.And the selection of intention is carried out under stationary vehicle, thus there is not the problem of moving process medium velocity and time, and the safety issue that causes thus, so the control of this kind form can realize that fully brain is to the direct control of vehicle.
The intelligent vehicle that carries out destination choice based on the brain electricity generally has the display system of stimulation, eeg signal acquisition and processing system and intelligent vehicle three parts compositions.And decision systems whether can trouble-free operation key be 3 points: the first, whether the required stimulation of brain-computer interface can embody all possible intention of user is fully selected; The second, whether EER corresponding to user-selected target can detect accurately; The 3rd, after intelligent vehicle obtains instruction, whether can effectively complete the task of instruction defined.Due to, existing brain-computer interface is mainly under the stimulation form that provides in advance, selects required object by the user according to the needs of self, so also just causes the limitation of selectable destination number.And for the collection and analysis of brain electricity, present most research is more under the condition of indoor laboratory.Indoor for the car steering that more interfere informations are arranged, existing method can not detect needed EEG signals reliably.Therefore, propose a kind of new intelligent vehicle that carries out destination choice based on the brain electricity and become purpose of the present invention.
Summary of the invention
the destination that the user of the present invention by prior setting often can occur is as stimulating element, consider the multiformity of destination, the present invention has designed a renewal formula of selecting stimulates display module (to reduce the visual angle and shift the aspect consideration that causes interference from car running process, stimulate display module to adopt the display mode of head-up-display system HUD), this stimulation display module is divided into grid with destination and shows, and when destination surpass to stimulate grid number on the page of display module, destination is divided into multipage (every page has identical grid number) and shows, present to the user.
The present invention relates to a kind of method of carrying out destination choice based on the brain electricity, described method comprises: gather the user due to the EEG signals of watching the stimulus information that shown by head-up-display system attentively and inducing by the brain wave acquisition module; Analyze described EEG signals to obtain the expectation destination information by the brain electricity analytical processing module; Through the repeatedly confirmation to the expectation destination information, obtain user's final true intention.
The step that gathers EEG signals by the brain wave acquisition module comprises: gather EEG signals by the electrode for encephalograms on the brain scalp that is placed in the user, and obtain and export pending EEG signals by eeg amplifier.
The step of analyzing described EEG signals by the brain electricity analytical processing module comprises: the first step, adopt two-wire journey mode record data, one of them thread record stimulates the time of flicker, when beginning to glimmer, and the EEG signals that another thread record gathers by the brain wave acquisition module; Second step if flicker continues the predetermined wheel number, carries out pretreatment to the EEG signals that gathers; The 3rd step, by PCA (PCA), the EEG signals after pretreatment is analyzed, obtain to characterize the main EEG signals feature of destination; The 4th step, by linear classification (LDA), described main EEG signals feature is classified, obtain destination's intention; At last, repeatedly confirm by the method that adopts four steps of the first step to the, obtain user's final true intention.The one-period that above 5 steps are confirmed as destination choice.
The step of repeatedly confirming to the expectation destination information comprises: to 3 confirmations of expectation destination information, if have in confirming for 3 times and be identified as confirmation more than twice, the final true intention that judges the user is expectation destination, otherwise enters the choice phase of next cycle.
Stimulus information is by stimulating display module to show, the display mode that stimulates is to realize by the display mode of head-up-display system, stimulus information comprises a plurality of destinatioies image of expecting destination, and each in described a plurality of destinatioies image repeatedly glimmered according to a definite sequence.
The predetermined wheel number that flicker continues is 10 to take turns.Described pretreatment comprises Filtering Processing and data division.
According to a further aspect in the invention, provide a kind of intelligent vehicle that utilizes said method, this intelligent vehicle utilizes the user's that said method obtains final true intention to carry out Autonomous Control by vehicle Autonomous Control module, to arrive destination.
Utilize the user's that said method obtains final true intention to output to the navigation module that is included in vehicle Autonomous Control module, user's final true intention is converted to the latitude and longitude information of destination, arrive destination thereby control intelligent vehicle.
Description of drawings
Fig. 1 is system block diagram of the present invention.
The display interface of Fig. 2 stimulation display module of the present invention.
Fig. 3 the present invention stimulates the selection flow process of display module.
Channel position corresponding to Fig. 4 EEG signals that will gather required for the present invention.
Fig. 5 is the eeg amplifier theory diagram.
Fig. 6 is the process chart of EEG signals.
Fig. 7 is the flow chart of destination selecting method of the present invention.
The specific embodiment
This invention is described to be carried out the method for destination choice and utilizes the Intelligent Vehicle System of the method to be specially adapted to handicapped person based on EEG signals, those skilled in the art can according to basic equipment and the principle of this invention, further expand other DAS (Driver Assistant System).
Ultimate principle of the present invention is when the user need to control vehicle, need not pass through limbs or speech action, only need to stimulate destination to be selected in display module 101 (getting the bid grid A black as Fig. 2) by watching attentively, in brain, corresponding P300 waveform will appear in the brain of correspondence electricity zone, gather the EEG signals on the correspondence position scalp and carry out analyzing and processing by the EEG signals of 103 pairs of collections of brain electricity analytical processing module by brain wave acquisition module 102, obtaining user's true intention; Then, adopt equally the P300 pattern to realize repeatedly confirming, realize that the accuracy of the identification of intention promotes; Can by message processing module 104, user view be sent to the navigation module 105 of being controlled vehicle at last, complete the autonomous driving task by vehicle control device by navigation module.
Specifically, as shown in Figure 7, method of the present invention comprises: gather users due to the EEG signals of watching stimulus information attentively and inducing by brain wave acquisition module 102; Analyze described EEG signals to obtain the expectation destination information by brain electricity analytical processing module 103; Through the repeatedly confirmation to the expectation destination information, obtain user's final true intention.Wherein, stimulus information is by stimulating display module 101 to show, stimulus information comprises a plurality of destinatioies image of expecting destination, and each in described a plurality of destinatioies image repeatedly glimmered according to a definite sequence.Stimulating display module 101 that a plurality of destinatioies image is divided into grid shows (as shown in Figure 2, being divided into 6 grids shows), when destination's image surpass to stimulate grid number on the page of display module 101, destination's image being divided into multipage shows, present to the user (as shown in Figure 2, utilize the left and right page turning to be good for page turning, every page has identical grid number).Utilize method shown in Figure 3 to confirm destination's (waiting a moment description) that the user selects.
Furtherly, the step (corresponding to the step 701-703 of Fig. 7) that gathers EEG signals by brain wave acquisition module 102 comprising: gather EEG signals by the electrode for encephalograms on the brain scalp that is placed in the user, and obtain and export pending EEG signals by the eeg amplifier (not shown).
The step (corresponding to the step 704-712 of Fig. 7) of analyzing described EEG signals by brain electricity analytical processing module 103 comprising: the first step, adopt two-wire journey mode record data (corresponding to step 704), one of them thread record stimulates the time (corresponding to step 705,706) of flicker, when beginning to glimmer, the EEG signals (corresponding to step 707,708) that another thread record gathers by brain wave acquisition module 102; Second step (corresponding to step 709) if flicker continues predetermined wheel number (for example, 10 take turns), carries out pretreatment (for example, Filtering Processing and data are divided) to the EEG signals that gathers; The 3rd step (corresponding to step 710), by PCA (PCA), the EEG signals after pretreatment is processed, obtain to characterize the main EEG signals feature of destination; The 4th step (corresponding to step 710), by linear classification (LDA), described main EEG signals feature is processed, obtain destination's intention; At last, (for example undertaken repeatedly by the method that adopts four steps of the first step to the, 3 times) confirm, obtain user's final true intention, if have in these 3 times are confirmed and confirm corresponding expectation destination information more than twice, the final true intention that judges the user is expectation destination, otherwise reenters selection and the confirmation (corresponding to step 711 and 712) that the step that selects your destination is carried out next cycle.
The intelligent vehicle that utilizes said method is described below with reference to Fig. 1 to Fig. 6, the vehicle Autonomous Control module of this intelligent vehicle comprises that the extended pattern destination choice stimulates display module 101, electroencephalogramsignal signal acquisition module 102, signal analysis and processing module 103, message processing module 104, navigation module 105 etc., final true intention in order to the user who obtains with said method, carry out Autonomous Control by vehicle Autonomous Control module, to arrive destination.Specifically, when the user watches stimulation display module 101 attentively, induce corresponding EEG signals; Brain wave acquisition analytical system 102 obtains user view by the analysis to EEG signals; Destination locations information (longitude and latitude) list by storing in central processing unit afterwards, position corresponding to acquisition user view, and by radio transmitting device with this information transmission to intelligent vehicle navigation module 105, independently completed the task of arriving destination by vehicle.
As shown in Figure 1, a kind of entire block diagram of carrying out the intelligent vehicle of destination choice based on the brain electricity comprises following part.
(1) the extended pattern destination choice stimulates display module 101
Described stimulation display module 101 can be realized different destination choices, and can according to user's requirement, increase new option.Then by the mode of head-up-display system (HUD), be presented at the place ahead of user.This stimulation display module 101 can carry out page turning according to user's request to be selected, but and then the more options of acquisition.See Fig. 2 at the stimulation display interface that stimulates demonstration on display module 101.The function of this stimulation display module 101 is to build the needed stimulus information of brain-computer interface.To seeing Fig. 3 in the selection flow process that stimulates the stimulus information that shows on display module 101.In step 301, the user selects your destination (as the A of destination), if having destination (as the A of destination) at current page, the user directly selects your destination and need not to carry out the page turning selection by right and left key; If do not have destination (as the A of destination) at current page, the user carries out page turning by right and left key, until select your destination.Be converted into concrete stimulus information by the destination that the user is selected.And possess the stimulus information of up and down page turning and confirmation.In step 302 and 303, when the user is selecting your destination (as: A of destination) or after page turning finishes, system after n identification/confirmation process in, only need to obtain " confirmations " identification more than 1 time, get final product this recognition result (as: A of destination) exported as control command.
The extended pattern destination choice stimulates display module 101, adopts the new line display mode as the final display mode that stimulates, and can reduce demonstration due to stimulus material and cause interference to the user.
(2) electroencephalogramsignal signal acquisition module 102
Described electroencephalogramsignal signal acquisition module 102 obtains EEG signals by the electrode for encephalograms collection that is placed on the brain scalp, in the process that gathers, the user is by watching stimulation corresponding to selected destination (as: A of destination) attentively, inducing corresponding EEG signals, and will amplify EEG signals afterwards by eeg amplifier and be transferred to brain electricity analytical processing module 103.The function of electroencephalogramsignal signal acquisition module 102 is by the EEG signals that stimulates display module 101 to induce, mainly by being placed on the electrode for encephalograms realization of scalp, the mode of electrode for encephalograms employing bipolar lead by the electrode for encephalograms collection.The concrete position of electrode for encephalograms is the P3 of international 64 ten-twenty electrode systems that lead, and P4, P7, P8, PZ, CZ be totally 6 positions, sees Fig. 4.
From the Portable practical angle, this intelligent vehicle has also designed a eeg amplifier, and to amplify the EEG signals that gathers by electrode for encephalograms, the eeg amplifier theory diagram as shown in Figure 5.EEG signals is through processing such as preposition amplification (step 501), high-pass filtering (step 502), 50Hz trap (step 503), low-pass filtering (step 504), rear amplifications (step 505).Concrete preamplifier employing BURR-BROWN(BB) the INA128 amplifier of company, this amplifier is a kind of other integration instrument table amplifier of war products level that is specifically designed to acquiring biological electric signals, has very high precision.Low-pass filtering is mainly removed High-frequency Interference, simultaneously signal is carried out intergrade and amplifies 100 times, selects the active low-pass filter mode, and integrated amplifier is selected general OP07.The rear class amplifying circuit, the structure for amplifying that adopts general purpose O P07 to form.
(3) the signal analysis and processing module 103
Described electroencephalogramsignal signal analyzing processing module 103 realizes the control of selection, flipping pages to destination and confirms to control, and after identifying result, the brain-computer interface mode by repeated multiple times confirmation improves its accuracy, finally obtains user's accurate intention.
In electroencephalogramsignal signal analyzing processing module 103, for the handling process of signal as shown in Figure 6:
(1) digital filtering (step 602).The EEG signals (step 601) that collects is carried out the bandpass filtering treatment of 0.53Hz-15Hz, remove the interfere informations such as myoelectricity, eye electricity and power frequency interference.The frequency of EEG signals mainly is positioned at the scope of 0-50Hz, and in gatherer process, also must be subject to the interference of electrocardio, myoelectricity noise, so, need to carry out Filtering Processing to the data that gather.Here the P300 brain electric potential of selecting mainly is positioned at low-frequency range, therefore the design band filter, free transmission range is 0.53-15Hz.
(2) data are divided (step 603).Utilize the stimulation displaying time that stimulates display module 101 records, the EEG signals correspondence that the location collects is cut apart EEG signals, and after each stimulation is begun to glimmer, the data of 512ms leave in respectively in corresponding spatial cache.
(3) utilize principal component analysis (PCA) to extract each characteristic information that stimulates corresponding EEG signals (include effective information 95%).(step 604)
(4) grader LDA design (step 604).Utilize linear analysis method (LDA) that the feature of extracting is classified, obtain user's selection intention (destination of perhaps selecting); According to the characteristic information of principal component analysis, on training data, by the LDA method, solve best mapping parameters.And this parameter is expanded in online detection, real-time EEG signals is carried out real-time identification;
(5) after the user selects a destination or flipping pages, the same implementation Process of [1]-[4] that adopts is to confirming the selection (step 605) of item.Continuous 3 times if (wherein have to be identified as more than twice confirming, can be considered to confirm), otherwise reenter the selection link of next cycle until select destination and carry out acknowledgement bit and put; If the result in choice phase identification is not user's true intention, the user need to watch attentively and removes the unexpected same key of " OK " key, to ensure the lower confirmation rate that obtains
The setting recognition accuracy is: P; Recognition cycle: N
The accuracy rate in each cycle:
P
accuracy＝P×(P
3+3×P
2×(1-P))
The error rate in each cycle:
Each cycle refuse to sentence rate:
P
rejection＝1-P
accuracy-P
error
Therefore from overall identifying be:
Along with cycle (time of identification is N * T(time used in single cycle)) variation, identification accuracy rate be changed to:
(recognition accuracy take 90% is example, can reach 99.8% success rate within continuous 3 cycles, along with the continuous passing of time will be substantially equal to 1-P
Error＜＜0.01%).
(4) message processing module 104
Message processing module 104 is mainly the Storage and Processing of being responsible for the every terms of information of whole system, as: the stimulus information storage of the provisional storage of EEG signals, stimulation display module 101 and the location coordinate information of the storage of brain-computer interface recognition result and transmission and all optional destinatioies.
(5) navigation module 105
Navigation module 105 is responsible for receiving the positional information that the user selects your destination, and according to this positional information, independent navigation is realized the working control to vehicle.
Navigation module 105 receives user view and the corresponding position coordinates that is obtained by message processing module 104, by with the target of particular geographic location coordinate as navigation, by autonomous navigation system, realizes the working control to vehicle.
As mentioned above, utilize the intelligent vehicle of said method and common vehicle to compare, have wireless receiving instruction system and independent navigation, the functions such as automatic obstacle avoiding can in the situation that target is definite, be completed the task of arriving destination smoothly.
Claims (8)
1. method based on brain electric control vehicle, described method comprises:
Because watching the destination that head-up-display system shows attentively, the user stimulates the EEG signals of bringing out by the collection of brain wave acquisition module;
Analyze described EEG signals to obtain the expectation destination information by the brain electricity analytical processing module;
Through the repeatedly confirmation to the expectation destination information, obtain user's final true intention.
2. method according to claim 1, wherein, the step that gathers EEG signals by the brain wave acquisition module comprises:
Gather EEG signals by the electrode for encephalograms on the brain scalp that is placed in the user, and obtain and export pending EEG signals by eeg amplifier.
3. method according to claim 1, wherein, the step of analyzing described EEG signals by the brain electricity analytical processing module comprises:
The first step adopts two-wire journey mode record data, and one of them thread record stimulates the time of flicker, when beginning to glimmer, and the EEG signals that another thread record gathers by the brain wave acquisition module;
Second step if flicker continues the predetermined wheel number, carries out pretreatment to the EEG signals that gathers;
The 3rd step, by PCA, the EEG signals after pretreatment is analyzed, obtain to characterize the main EEG signals feature of destination;
The 4th step, by linear classification, described main EEG signals feature is classified, obtain destination's intention;
At last, repeatedly confirm by the method that adopts four steps of the first step to the, obtain user's final true intention.
Above whole process is called one and selects the confirmation cycle.
4. method according to claim 1 wherein, comprises the step of repeatedly confirming of expectation destination information:
To 3 confirmations of expectation destination information,
Confirm corresponding expectation destination information more than twice if having in these 3 times are confirmed, judge that user's final true intention is hoped by a definite date destination; Otherwise the selection in this cycle is invalid, with the selection that enters next cycle.
5. method according to claim 1, wherein, stimulus information is by stimulating display module to show, the display mode that stimulates is to realize by the display mode of head-up-display system, stimulus information comprises a plurality of default destination image of expecting destination, and each in described a plurality of destinatioies image repeatedly glimmered according to a definite sequence.
6. method according to claim 3, wherein, the predetermined wheel number that flicker continues is 10 to take turns, described pretreatment comprises that Filtering Processing and data divide.
7. intelligent vehicle that utilizes the method for claim 1-6, described intelligent vehicle utilize the user's that the method for claim 1-6 obtains final true intention, and carry out Autonomous Control by vehicle Autonomous Control module, to arrive destination.
8. intelligent vehicle according to claim 7, wherein, utilize the user's that the method for claim 1-6 obtains final true intention to output to navigation module, user's final true intention is converted to the latitude and longitude information of destination, then arrive destination by vehicle Autonomous Control module controls intelligent vehicle.
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| CN104462716A (en) * | 2014-12-23 | 2015-03-25 | 北京理工大学 | Method for designing brain-computer interface parameters and kinetic parameters of brain controlled vehicle based on human-vehicle-road model |
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| CN108491071A (en) * | 2018-03-05 | 2018-09-04 | 东南大学 | A kind of brain control vehicle Compliance control method based on fuzzy control |
| CN108491071B (en) * | 2018-03-05 | 2021-05-04 | 东南大学 | Brain-controlled vehicle sharing control method based on fuzzy control |
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| CN112022152A (en) * | 2020-08-28 | 2020-12-04 | 江西脑虎科技有限公司 | Classification processing method and device for electroencephalogram signals, electronic equipment and storage medium |
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