CN110058691A - Based on Embedded wearable wireless dry electrode brain wave acquisition processing system and method - Google Patents
Based on Embedded wearable wireless dry electrode brain wave acquisition processing system and method Download PDFInfo
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- CN110058691A CN110058691A CN201910314954.2A CN201910314954A CN110058691A CN 110058691 A CN110058691 A CN 110058691A CN 201910314954 A CN201910314954 A CN 201910314954A CN 110058691 A CN110058691 A CN 110058691A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/6803—Head-worn items, e.g. helmets, masks, headphones or goggles
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
- G06F3/015—Input arrangements based on nervous system activity detection, e.g. brain waves [EEG] detection, electromyograms [EMG] detection, electrodermal response detection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2203/00—Indexing scheme relating to G06F3/00 - G06F3/048
- G06F2203/01—Indexing scheme relating to G06F3/01
- G06F2203/011—Emotion or mood input determined on the basis of sensed human body parameters such as pulse, heart rate or beat, temperature of skin, facial expressions, iris, voice pitch, brain activity patterns
Abstract
The invention discloses one kind based on Embedded wearable wireless dry electrode brain wave acquisition processing system and method, including adjustable one, brain electricity cap, one piece of data acquisition processing circuit plate, outside stimulus module one.The acquisition for increasing head acceleration signal, using adaptive-filtering and acceleration signal and noise signal have the characteristics that correlation this, obtain the EEG signals of removal artefact, reduce influence of the motion artifacts to EEG signals.The system can handle EEG signals on line real time, obtain control instruction and control external equipment, solve current most brain wave acquisition equipment dependence computers and be analyzed and processed to collected data, the problem of portability difference.
Description
[technical field]
The invention belongs to eeg signal acquisition process fields, are related to a kind of based on Embedded wearable wireless dry electrode brain
Electric acquisition processing system and method.
[background technique]
Brain-computer interface technology (Brain Computer Interface, BCI) is as a kind of independently of organism itself
Bioelectricity man-machine interactive interface realizes information Direct Communication between brain and external equipment (computer or external environment etc.), should
Technology have with brain two-way interactive ability, can not only perceive external environment to the stimuli responsive information of cerebral nerve maincenter,
The command information that brain issues can also be directly decoded into the order of driving external equipment.
Existing acquisition equipment such as Neuroscan, what the companies such as Brain Products released a series of 32 leads/64 and leads and adopt
Collect multiplying arrangement, it is general only with basic data acquisition and simple preprocessing function, later by wired or wireless
By treated, EEG information is sent to host computer to mode, is further divided by research staff using the program in host computer
Analysis processing, but it is limited to the position of host computer, brain wave acquisition range can only also be limited in smaller range, in portability, side
Just there is very big limitation in property.From the point of view of the development trend of BCI, although having been realized in the control and friendship of people and robot
Stream, but still needs to solve following problems: first, the electrode on brain electricity cap is vibrated with the movement of people, is also easy to produce a large amount of fortune
Dynamic artefact；Second, it needs to handle collected data using computer, portability is poor.
[summary of the invention]
It is an object of the invention to overcome the above-mentioned prior art, provide a kind of based on Embedded wearable wireless
Dry electrode brain wave acquisition processing system and method, in the case where being detached from computer, by the way that embedded processing is written in brain computator method
Device filters EEG signals online, Feature extraction and recognition, compensates for the deficiency of previous brain electric equipment, improves portability
And ease for use.
In order to achieve the above objectives, the present invention is achieved by the following scheme:
One kind is based on Embedded wearable wireless dry electrode brain wave acquisition processing system, comprising:
Adjustable brain electricity cap, for acquiring EEG signals；The adjustable brain electricity cap includes wearing component, described to wear
It wears and is provided with acquisition electrode and reference electrode on component, the acquisition electrode and the reference electrode are dry electrode；It is described to adopt
Collected EEG signals are sent to signal acquisition process module by collector and the reference electrode；And
Signal acquisition process module, the signal acquisition process module are installed on the adjustable brain electricity crown end, use
In to collected EEG signals, and EEG signals are pre-processed, analog-to-digital conversion, is then acquired according to acceleration transducer
The acceleration signal for the synchronization arrived goes artefact algorithm to obtain the eeg data of removal artefact using acceleration, finally utilizes brain electricity
Parser is analyzed and processed the eeg data of removal artefact, obtains recognition result, then converts control for recognition result
System instruction is sent to external equipment by bluetooth module.
A further improvement of the present invention lies in that:
Dressing component includes adjustable hatband, the adjustable cap beam of vertical direction and elastic band；Hatband and cap beam
Middle part is disposed with several electrode straps, offers several electrode holes or fixation hole in cap beam, hatband and intermediate fixing belt；Cap
The junction for enclosing rear portion, hatband and cap beam, is provided with the strainer for adjusting hatband and cap beam size.
Signal acquisition process module includes that pretreatment circuit, analog to digital conversion circuit, embeded processor and acceleration pass
Sensor；EEG signals pass sequentially through pretreatment circuit, analog to digital conversion circuit and enter embeded processor by SPI serial line interface,
Acceleration signal enters embeded processor by SPI serial line interface, and it is outer that embeded processor controls the progress of outside stimulus module
Portion's visual stimulus.
One reference axis of acceleration transducer is perpendicular to the ground.
Pre-processing circuit includes protection circuit, low-pass filter circuit and notch filter circuit, and EEG signals are via protection
Circuit, low-pass filter circuit and notch filter circuit enter analog to digital conversion circuit.
Outside stimulus module is made of light emitting diode matrix, for prompting the beginning and end of Mental imagery, outside thorn
Swash module to be controlled simultaneously by way of multithreading with signal acquisition process by embeded processor.
One kind is based on Embedded wearable wireless dry electrode brain wave acquisition processing method, comprising the following steps:
Step 1: EEG signals are acquired by the acquisition electrode being worn on the adjustable brain electricity cap on head in real time；
Step 2: EEG signals pass sequentially through pretreatment circuit, obtain pretreated EEG signals；
Step 3: while acquiring EEG signals, the acceleration signal of synchronous acquisition acceleration transducer, outside stimulus
Module synchronization operation handles pretreated eeg data in real time, and realizes brain using the brain computator method in embeded processor
The identification of electricity condition；
Step 4: the result that step 3 identifies being transmitted to external equipment by bluetooth module, realizes the control to external equipment
System.
Itself further improvement is that
In the step 3, brain computator method is ssvep or Mental imagery.
In step 3, embeded processor, for a cycle, every 2 seconds, intercepted n-2 seconds data, wherein n >=6 with n seconds；
It goes artefact algorithm to obtain the eeg data of removal artefact using acceleration, then eeg data is carried out using brain electricity analytical algorithm
Analysis processing, obtains recognition result；It finally converts recognition result to the control instruction of control external equipment, is sent to bluetooth mould
Block.
Control instruction is sent to bluetooth module by serial ports by embeded processor, and bluetooth module wirelessly passes control instruction
Transport to external equipment.
Compared with prior art, the invention has the following advantages:
One kind provided by the invention is based on Embedded wearable wireless dry electrode brain wave acquisition processing system, including adjustable
Section formula brain electricity one, cap, outside stimulus module one, does not depend on computer by one piece of data acquisition processing circuit plate.The present invention can
It solves most brain wave acquisition equipment dependence computers at present to handle collected data, the problem of portability difference.The present invention
Be utilized adaptive-filtering and acceleration signal and noise signal have the characteristics that correlation this, obtain removal artefact brain electricity
Signal.Use the influence the method reduce motion artifacts to EEG signals.
[Detailed description of the invention]
Fig. 1 is wearable wireless dry electrode brain wave acquisition processing system functional block diagram；
Fig. 2 is adjustable brain electricity cap structure schematic diagram；Wherein, (a) is main view, (b) is top view；
Fig. 3 is protection, filter circuit schematic diagram；
Fig. 4 is embeded processor circuit diagram；
Fig. 5 is acceleration module circuit diagram；
Fig. 6 is analog-to-digital conversion module circuit diagram；
Fig. 7 is wearable wireless dry electrode brain wave acquisition processing system algorithm flow chart；
Fig. 8 is that adaptive artefact removes system schematic；
Fig. 9 is data frame structure figure.
[specific embodiment]
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, the embodiment being not all of, and it is not intended to limit range disclosed by the invention.In addition, with
In lower explanation, descriptions of well-known structures and technologies are omitted, obscures concept disclosed by the invention to avoid unnecessary.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment should fall within the scope of the present invention.
The various structural schematic diagrams for disclosing embodiment according to the present invention are shown in the attached drawings.These figures are not in proportion
It draws, wherein some details are magnified for the purpose of clear expression, and some details may be omitted.As shown in the figure
The shape in various regions, layer and relative size, the positional relationship between them out is merely exemplary, in practice may be due to
Manufacturing tolerance or technical restriction and be deviated, and those skilled in the art may be additionally designed as required have not
Similar shape, size, the regions/layers of relative position.
In context disclosed by the invention, when one layer/element is referred to as located at another layer/element "upper", the layer/element
Can may exist intermediate layer/element on another layer/element or between them.In addition, if in a kind of court
One layer/element is located at another layer/element "upper" in, then when turn towards when, the layer/element can be located at another layer/
Element "lower".
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to the embodiment of the present invention described herein can in addition to illustrating herein or
Sequence other than those of description is implemented.In addition, term " includes " and " having " and their any deformation, it is intended that cover
Cover it is non-exclusive include, for example, the process, method, system, product or equipment for containing a series of steps or units are not necessarily limited to
Step or unit those of is clearly listed, but may include be not clearly listed or for these process, methods, product
Or other step or units that equipment is intrinsic.
The invention will be described in further detail with reference to the accompanying drawing:
Referring to Fig. 1 and Fig. 2, the present invention is based on Embedded wearable wireless dry electrode brain wave acquisition processing systems, comprising:
Adjustable brain electricity cap, signal acquisition process module, bluetooth module, outside stimulus module.Pass through view using outside stimulus module
Feel that stimulation makes EEG signals generate corresponding variation, passes through the electrode and signal acquisition on adjustable brain electricity cap at the same time
Acceleration transducer in processing module acquires signal in real time, and signal is controlled after signal acquisition process module decoding process
System instruction, control instruction is sent to the external equipment with the module pairs by bluetooth module, to realize adopting for EEG signals
Collection handles and is detached from computer to the real-time control of external equipment.
As shown in Fig. 2, the hardware components of present system include: adjustable brain electricity cap, signal acquisition process module with
And outside stimulus module.
Adjustable brain electricity cap appearance of soft material as shown in Fig. 2, made, and overall structure is by the adjustable of horizontal direction
The elastic band 4 of hatband 3, the adjustable cap beam 2 of vertical direction and fixed cap is constituted.
The middle section of hatband 3 and cap beam 2 can according to need the configuration for carrying out electrode strap 1, cap beam 2, hatband 3 with
Have the electrode hole 5 or fixation hole 6 accomplished fluently in intermediate fixing belt 1, operator can according to different experiments or test purpose into
The configuration of row fixing belt 1 shows only the position of part fixing belt 1 to illustrate in figure.Entire cap can all be dismantled, be adjusted
Section, embodies good portability and adaptability.It can be in hatband 3 and cap for the adjusting of the level of head size, vertical direction
It is carried out at the strainer 7 of beam 2, length that can be as needed for the length of intermediate fixing belt 1 is adjusted at fixation hole 6.
In order to uniformly process the portability with operation, fixation hole 6 and electrode hole 5 will be designed to same size, these electrodes
Hole 5 is arranged according to 10-20 system standard, meets the primary demand of eeg signal acquisition.
Acquisition electrode used in brain electricity cap, reference electrode are dry electrode.
Signal acquisition process module is fixed on the top of brain electricity cap, guarantees wherein the one of acceleration transducer thereon as far as possible
A reference axis is perpendicular to the ground, and internal structure is as shown in Figure 1, by pretreatment circuit, analog to digital conversion circuit, embeded processor
And acceleration transducer composition.EEG signals pass sequentially through pretreatment circuit, analog to digital conversion circuit by SPI serial line interface into
Enter embeded processor, and acceleration signal directly passes through SPI serial line interface and enters embeded processor, it is embedded at the same time
Processor controls outside stimulus module and carries out external view stimulation.
As shown in figure 3, pre-processing electric route protection circuit, low-pass filter circuit and notch filter circuit composition.
Protection circuit is realized that this is a 4 channel bidirectional transient voltage suppressor by electrostatic protection device TPD4E1B06
(TVS) diode array.The ESD protection of this device can be more than 4 grades of IEC 61000-4-2 requirements, and ultralow Leakage Current
(0.5nA) and down to 0.7pF line electricity capacitance the interference of analog signal is dropped to it is extremely low, meet precision analog measurement want
It asks.Electrostatic protection device is added between brain electrode and pretreatment circuit, the electrostatic for preventing human body from generating is incoming pre- by brain electrode
Processing circuit, and then reach the function of protection subsequent conditioning circuit.
It pre-processes circuit and low-pass filtering is realized using RC filter, 50Hz power frequency is realized using the twin-T network of adjustable Q value
Trap realizes analog-to-digital conversion using 8 channel modulus conversion chip ADS1299 of high-precision.RC filter is arranged using capacitor and resistance
Row is constituted, and is reduced filter circuit volume and is realized low-pass filtering, according to cutoff frequency formula:
F in formulacCutoff frequency refers to that cutoff frequency, R refer to that resistance parameter, C refer to capacitance parameter.
According to the cutoff frequency f of EEG signalsc, an any given R value can calculate C value.
Notch filter circuit realizes 50Hz notch filter, the twin-T network of adjustable Q value using the twin-T network of adjustable Q value
It is constituted using capacitor row and resistor chain, reduce filter circuit volume and realizes notch filter, parameter selection:
Centre frequency50Hz is taken, C is taken1=C2=1 μ F, C3=2 μ F；R can be obtained1=R2=3184 Ω, R3=
1592Ω；Quality factor:Q value be not easy choosing it is too big, prevent self-excitation phenomena, therefore
Take Q=20, K=0.975, Ra+Rb=10K Ω, can be calculated Ra=9.75K Ω, Rb=0.25K Ω.
As shown in figure 4, embeded processor uses STM32L476RG, which is a based on high-performance Arm
The super low-power consumption microcontroller of 32 RISC cores of Cortex-M4.With floating point unit (FPU) single precision, all Arm are supported
Single precision data processing instructions and data type.Possess a whole set of DSP instruction set and a memory protection location (MPU), enhances
The safety of program.Possess interface resource abundant, facilitates the exploitation of embedded system；Lower power consumption ensure that this can wear
Wear the cruise duration of formula equipment；Possess complete DSP instruction, improves the treatment effeciency of data.
Embeded processor obtains pretreated brain telecommunications by carrying out SPI serial port communication with analog to digital conversion circuit
Number；At the same time, embeded processor is same with EEG signals by obtaining with acceleration transducer progress SPI serial port communication
The acceleration signal of step.Embeded processor, for a cycle, every 2 seconds, intercepted n-2 seconds data, wherein n >=6 with n seconds；
Artefact algorithm is gone to obtain the eeg data of removal artefact using acceleration, then brain electricity analytical algorithm carries out at analysis data
Reason is analyzed as a result, last embeded processor converts recognition result to the control instruction of control external equipment.
As shown in figure 5, acceleration transducer is LIS3DHTR, which is a kind of three axis of super low-power consumption high-performance
Acceleration transducer has number I2C/SPI standard output.Gather around there are two programmable Interrupt output pin, for freely falling body and
Motion detection.The sensor has super low-power consumption operational mode, and operating current is down to 2 μ A；And in the normal mode of operation it is 11 μ
A。
Acceleration transducer configures in signal acquisition process module, and SPI serial line interface is supported conveniently to carry out data transmission；
Extremely low operating current ensure that the cruise duration of the wearable device；Motion detection may be implemented to click/double-click identification etc.
Function has expanded the control means of embedded device.
As shown in fig. 6, analog to digital conversion circuit realizes analog-to-digital conversion using 8 channel modulus conversion chip ADS1299 of high-precision,
Supply voltage AVDD=+2.5V, DVDD=+3.3V, AVSS=-2.5V.It is a eight channel low noise, the sampling of 24 bit synchronizations
Delta-sigma adc (ADC).Built-in chip type programmable gain amplifier (PGA), internal reference and the onboard oscillator,
Have the outer electroencephalogram (EEG) of cranium and applies required whole common functions.The chip possesses high integration and outstanding performance substantially contracts
Small size significantly reduces power consumption and overall cost.
Outside stimulus module is made of light emitting diode matrix, for induced in SSVEP is tested specific EEG signals or
For prompting the beginning and end of Mental imagery, the side which passes through multithreading by embeded processor in Mental imagery experiment
Formula is controlled simultaneously with signal acquisition process.
Above-mentioned control mode ensure that the real-time of stimulation or prompt, and does not need additional screen when in use and pierced
Swash or prompt, improves the portability of equipment.
Bluetooth module use HC-08 bluetooth BLE4.0 serial port module, Full-Speed mode and do not use LED light the case where
Under, slave operating current be no more than 10mA, host work electric current 20mA or so, therefore the present invention use the bluetooth module as from
Machine is connected with external equipment, further ensures the cruise duration of the wearable device.Specific working mode is as follows:
Control instruction is sent to bluetooth module by UART by embeded processor, and bluetooth module wirelessly passes control instruction
External equipment is transported to, realization directly controls external equipment, for supporting that it is additional that the external equipment of bluetooth communication does not need
Patchcord can combine carry out real-time control with the present invention.
The present invention is based on Embedded wireless wearable dry electrode brain electricity acquisition and recognition methods, including following step in real time
It is rapid:
Step 1: EEG signals are acquired by the brain electrode being worn on the electrode cap on head in real time.
Step 2: the EEG signals that brain electrode acquires in real time pass sequentially through the pretreatment circuit such as protection, filtering, amplifying circuit,
Obtain pretreated EEG signals.
Step 3: while acquiring EEG signals, acceleration transducer synchronous acquisition acceleration signal, outside stimulus mould
Block synchronous operation handles pretreated eeg data in real time and utilizes the specific brain computator method in embeded processor
The identification of (ssvep, Mental imagery etc.) realization brain electricity condition.
The method for obtaining brain electricity and acceleration synchronization signal is as follows:
After the completion of boot system initialization, EEG signals and acceleration signal are started simultaneously in the way of multithreading and are adopted
Collection, sample frequency are disposed as 250Hz, will merge into one after each frame alignment of data in main thread and include 8 channel brain electricity
The data frame of data and 3 axle acceleration datas guarantees good synchronism in software view.
Acceleration goes artefact algorithm principle as follows:
Using the three-dimensional acceleration signals of the acceleration transducer record head movement in step 2, head movement model is established,
Head three-dimensional is obtained from model using motion analysis software and accelerates parameter (X-direction, Y-direction, Z-direction, angular speed
Deng), and export the time series data of the kinematics parameters comprising head and remove motion artifacts using adaptive-filtering.
Adaptive filtration theory is as follows:
Removal motion artifacts are the removal motion artifacts relevant to movement from the EEG containing motion artifacts, and adaptive
Filtering is inhibited or with the filtering method for the noise signal that decays to the greatest extent.Adaptive artefact removal system is as shown in Figure 8.
Adaptive noise interference offset device has two-way input signal, is signal source s (t) all the way, and another way is reference noise signal n1.It will
S (t) regards pure ideal signal x (t) and interference noise n as0The mixed signal of composition.Wherein n1Be with x (t) it is incoherent,
But with n0There is certain correlation.Signal n1Become signal y after sef-adapting filter filters, if y and n0It is very much like, then
The signal formula of system output are as follows:
ε=x (t)+n0-y≈x(t) (2)
The purpose of adaptive noise interference offset device is exactly the weight arrow that sef-adapting filter is adjusted using error signal
Amount, so that filter exports desired y value and carrys out the noise n in offseting signal0.As shown in Figure 8, signal x (t)+n0With adaptive filter
The output y of wave device obtains the output error of system by adder-subtractor are as follows:
ε=x (t)+n0-y (3)
By equation (3) both sides square, obtain:
s2=x2+(n0-y)2+2x(n0-y) (4)
Mathematic expectaion is taken to formula (4) both sides, because of x and n0, y is uncorrelated, i.e. E [x (n0- y)]=0, so that
The purpose of adaptive cancellation device is by the noise n in signal x (t)0It filters out, but the ENERGY E [x of x (t) cannot be influenced2]
Size, even if Emin[x2] minimize, minimum output power are as follows:
Emin[ε2]=E [x2]+Emin[(n0-y)2] (6)
By formula (6) it is found that making E when adjusting sef-adapting filter parametermin[ε2] minimize when, due to E [x2] constant, quite
In making Emin[(n0-y)2] minimize.The output y of sef-adapting filter is motion artifacts signal n0Minimum variance estimate, this meaning
Taste work as E [(n0-y)2] minimize when, E [(ε-y)2] minimum.So that
ε-y=n0-y (7)
By formula (7) it is found that inputting for given sef-adapting filter and constant reference, sef-adapting filter is adjusted
Parameter minimizes the output power of white adaptive filter, this is equivalent to the minimum variance estimate for making output error ε signal x.
Output error accounts for mainly comprising signal x and noise n0- y, x be in the output signal it is constant, as E [x2] and E [(n0-y)2] most
When smallization, output noise n0The power of-y will also minimize, and the signal-to-noise ratio of signal is maximum at this time.As n in formula (7)0When-y ≈ 0,
ε=x.At this point, not only output power is minimum, and noise is entirely free of in output signal, this is the adaptive noise canceling
Most ideal situation.
Adaptive LMS filtering algorithm is fairly simple, it does not only need to calculate the correlation function of input signal, but also is not required to require
Inverse of a matrix matrix, calculation amount is small, thus is used widely.
Step 4: recognition result is wirelessly transmitted to external equipment by communication module, realizes the control to external equipment.
Control instruction is sent to bluetooth module by serial ports by embeded processor, and bluetooth module wirelessly passes control instruction
External equipment is transported to, realization directly controls external equipment, for supporting that it is additional that the external equipment of bluetooth communication does not need
Patchcord can combine carry out real-time control with the present invention.
Invention software part is as shown in fig. 7, embeded processor mainly needs to complete three tasks:
I. it communicates to obtain pretreated EEG signals and acceleration signal by SPI, the identification for carrying out brain electricity condition is raw
At control instruction；
Ii. the transmitting-receiving instructed is communicated by UART；
Iii. outside stimulus module is controlled.
Therefore software section mainly includes SPI communication program, UART communication program, brain electricity condition recognizer and outside
Stimulating module controls program.Brain electricity condition recognizer therein is to write and be converted into C code by matlab, remaining program exists
It is developed under Keil uVision5 (MDK 5) environment.
SPI communication program and UART communication program are write using the MBED kit of ARM company, Speeding up development process.Ginseng
Examine Fig. 4, Fig. 5, Fig. 6, in program A/D chip and acceleration transducer as slave and the embeded processor as host into
Row SPI communication, the pin DIN (34) of ADS1299, DOUT (43), SCLK (40), CS (39), DRDY (47) respectively with it is embedded
Pin MOSI (23), MISO (22), SCLK (21), PA0 (14), the PC3 (11) of processor are connected；The pin of acceleration chip
MISO (7), SCK (4), CS (8), INT1 (11) respectively with the pin MISO (22) of embeded processor, SCLK (21), PA0
(14), PB10 (29) is connected, and the pin MOSI (23) of embeded processor and PA0 (14) by one or and acceleration
The pin MOSI (6) of chip is connected.In program initialization, SPI communication is initialized according to above-mentioned connection type, is realized
One main two from SPI communication.
Initialization procedure includes the transmission rate setting to UART, and the configuration of SPI, the configuration of interruption, each pin inputs defeated
The initialization of the configuration of mode, ADS1299 and LIS3DHTR and the initialization of program variable out.
It is 24 times, sample frequency 250Hz that the initialization of ADS1299, which needs to be arranged gain factor, turn-on data ready interrupt；
The range that the initialization of LIS3DHTR needs to be arranged acceleration is 4g, and resolution ratio is set as high-resolution, turn-on data ready interrupt.
Embeded processor is communicated with outside stimulus module and bluetooth module by UART, embeded processor
Pin PA9 (42), PA10 (43) are connected with pin RXD (2) TXD (1) of bluetooth module HC-08 respectively as TXD, RXD；Insertion
Pin PC12 (53), the PD2 (54) of formula processor are connected with RXD, TXD of outside stimulus module respectively as TXD, RXD.In journey
When sequence initializes, UART communication is initialized according to above-mentioned connection type, realizes two-way UART communication.
As shown in Figure 8 is that adaptive artefact removal network system realization is as follows:
In order to improve the stability of adaptive speed and system, selecting suitable step-size parameter mu is adaptive filter algorithm
Key, using the dynamic EEG of the collected multichannel of human body as signal source s (t), s (t) be ideal dynamic EEG x (t) and fortune
Dynamic artefact n0Combination, using 3-axis acceleration sensor acquisition three road acceleration signals square root as sef-adapting filter
Reference signal n1It is compared with motion artifacts, forms error signal, error signal is adaptively calculated by lowest mean square (LMS)
Method is adjusted filter parameter, and the step-length for choosing sef-adapting filter is 0.000002, finally makes the square of error signal
Value is minimum, to inhibit motion artifacts.
Outside stimulus program realizes that process is as follows by taking stable state vision inducting (SSVEP) as an example:
After the commencing signal for receiving embeded processor transmission, transmission mark shown in Fig. 7 can be set to 1, external at this time
Stimulating module is stimulated by LED, and the stimulation of LED continues 4s, stops 2s, is a circulation with 6s, be can configure muti-piece LED screen
The flash stimulation for carrying out different frequency, realizes the identification of multiple instructions.Outside stimulus program controls external thorn using individual thread
Swash module, guarantees the accuracy of frequency of stimulation, and the frequency of above-mentioned flash of light can be by user setting, range is between 8~20.
Brain electricity condition recognizer realizes that process is as follows by taking stable state vision inducting (SSVEP) as an example:
Eeg data by pre-processing and being converted into digital signal realizes brain electricity shape by carrying out CCA with template data
The identification of state.Detailed process is as follows:
Take two frequency of stimulation X1=10, X2=15Hz, template Y should include: the sinusoidal template of 10,15Hz fundamental frequency and frequency multiplication,
2 CCA are carried out to each section of eeg data to calculate, are Y using the fundamental frequency frequency multiplication of 10,15Hz respectively, calculate the typical phase of X and Y
Relationship number ρ, and the maximum value of retention factor ρ, in 2 ρ that 2 CCA are obtained, the maximum is recognition result.
User, which can choose, to be passed brain electricity and acceleration information back host computer and analyzes, the format of data frame such as Fig. 9 institute
Show.
The above content is merely illustrative of the invention's technical idea, and this does not limit the scope of protection of the present invention, all to press
According to technical idea proposed by the present invention, any changes made on the basis of the technical scheme each falls within claims of the present invention
Protection scope within.
Claims (10)
1. one kind is based on Embedded wearable wireless dry electrode brain wave acquisition processing system characterized by comprising
Adjustable brain electricity cap, for acquiring EEG signals；The adjustable brain electricity cap includes wearing component, the wearing group
Acquisition electrode and reference electrode are provided on part, the acquisition electrode and the reference electrode are dry electrode；The acquisition electricity
Collected EEG signals are sent to signal acquisition process module by pole and the reference electrode；And
Signal acquisition process module, the signal acquisition process module are installed on the adjustable brain electricity crown end, for pair
Collected EEG signals, and EEG signals are pre-processed, analog-to-digital conversion, it is then collected according to acceleration transducer
Synchronous acceleration signal goes artefact algorithm to obtain the eeg data of removal artefact, finally utilizes brain electricity analytical using acceleration
Algorithm is analyzed and processed the eeg data of removal artefact, obtains recognition result, then converts control for recognition result and refer to
It enables and external equipment is sent to by bluetooth module.
2. according to claim 1 based on Embedded wearable wireless dry electrode brain wave acquisition processing system, feature
It is, wearing component includes adjustable hatband (3), the adjustable cap beam of vertical direction (2) and elastic band (4)；Hatband (3)
With several electrode straps (1) is disposed in the middle part of cap beam (2), opened up in cap beam (2), hatband (3) and intermediate fixing belt (1)
There are several electrode holes (5) or fixation hole (6)；Hatband (3) rear portion, hatband (3) and cap beam (2) junction, be provided with for adjusting
Save the strainer (7) of hatband (3) and cap beam (2) size.
3. according to claim 1 based on Embedded wearable wireless dry electrode brain wave acquisition processing system, feature
It is, signal acquisition process module includes pretreatment circuit, analog to digital conversion circuit, embeded processor and acceleration sensing
Device；EEG signals pass sequentially through pretreatment circuit, analog to digital conversion circuit and enter embeded processor by SPI serial line interface, add
Speed signal enters embeded processor by SPI serial line interface, and embeded processor controls outside stimulus module and carries out outside
Visual stimulus.
4. it is according to claim 1 or 3 based on Embedded wearable wireless dry electrode brain wave acquisition processing system, it is special
Sign is that a reference axis of acceleration transducer is perpendicular to the ground.
5. according to claim 3 based on Embedded wearable wireless dry electrode brain wave acquisition processing system, feature
It is, pretreatment circuit includes protection circuit, low-pass filter circuit and notch filter circuit, and EEG signals are via protection electricity
Road, low-pass filter circuit and notch filter circuit enter analog to digital conversion circuit.
6. according to claim 3 based on Embedded wearable wireless dry electrode brain wave acquisition processing system, feature
It is, outside stimulus module is made of light emitting diode matrix, for prompting the beginning and end of Mental imagery, outside stimulus mould
Block is controlled by way of multithreading with signal acquisition process simultaneously by embeded processor.
7. it is a kind of using system described in claim 3 based on Embedded wearable wireless dry electrode brain wave acquisition processing side
Method, which comprises the following steps:
Step 1: EEG signals are acquired by the acquisition electrode being worn on the adjustable brain electricity cap on head in real time；
Step 2: EEG signals pass sequentially through pretreatment circuit, obtain pretreated EEG signals；
Step 3: while acquiring EEG signals, the acceleration signal of synchronous acquisition acceleration transducer, outside stimulus module
Synchronous operation handles pretreated eeg data in real time, and realizes brain electricity shape using the brain computator method in embeded processor
The identification of state；
Step 4: the result that step 3 identifies being transmitted to external equipment by bluetooth module, realizes the control to external equipment.
8. according to claim 7 based on Embedded wearable wireless dry electrode brain wave acquisition processing method, feature
It is, in the step 3, brain computator method is ssvep or Mental imagery.
9. according to claim 7 based on Embedded wearable wireless dry electrode brain wave acquisition processing method, feature
It is, in step 3, embeded processor, for a cycle, every 2 seconds, intercepted n-2 seconds data, wherein n >=6 with n seconds；Benefit
It goes artefact algorithm to obtain the eeg data of removal artefact with acceleration, then eeg data is divided using brain electricity analytical algorithm
Analysis processing, obtains recognition result；It finally converts recognition result to the control instruction of control external equipment, is sent to bluetooth mould
Block.
10. based on Embedded wearable wireless dry electrode brain wave acquisition processing method according to claim 7 or 9,
It is characterized in that, control instruction is sent to bluetooth module by serial ports by embeded processor, and bluetooth module is wireless by control instruction
It is transmitted to external equipment.
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Application publication date: 20190726 |