CN109674467A - Single-lead-ear electroencephalogram signal acquisition device and method - Google Patents
Single-lead-ear electroencephalogram signal acquisition device and method Download PDFInfo
- Publication number
- CN109674467A CN109674467A CN201910017413.3A CN201910017413A CN109674467A CN 109674467 A CN109674467 A CN 109674467A CN 201910017413 A CN201910017413 A CN 201910017413A CN 109674467 A CN109674467 A CN 109674467A
- Authority
- CN
- China
- Prior art keywords
- module
- ear
- signal acquisition
- eeg
- eeg signals
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000005540 biological transmission Effects 0.000 claims abstract description 42
- 210000004556 brain Anatomy 0.000 claims description 27
- 238000001914 filtration Methods 0.000 claims description 15
- 230000000694 effects Effects 0.000 claims description 11
- 238000003672 processing method Methods 0.000 claims description 10
- BQCADISMDOOEFD-UHFFFAOYSA-N Silver Chemical compound [Ag] BQCADISMDOOEFD-UHFFFAOYSA-N 0.000 claims description 8
- 238000000354 decomposition reaction Methods 0.000 claims description 8
- 239000000835 fiber Substances 0.000 claims description 8
- 229910052709 silver Inorganic materials 0.000 claims description 8
- 239000004332 silver Substances 0.000 claims description 8
- 230000001360 synchronised effect Effects 0.000 claims description 7
- 239000004615 ingredient Substances 0.000 claims description 5
- 239000004020 conductor Substances 0.000 claims description 4
- 239000004744 fabric Substances 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims description 4
- 210000000613 ear canal Anatomy 0.000 claims description 3
- 230000001037 epileptic effect Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 claims description 3
- 230000001012 protector Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000001681 protective effect Effects 0.000 claims 1
- 230000008901 benefit Effects 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 abstract description 2
- 230000005611 electricity Effects 0.000 description 5
- 210000004761 scalp Anatomy 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 230000003321 amplification Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000004424 eye movement Effects 0.000 description 2
- 238000003199 nucleic acid amplification method Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000003745 diagnosis Methods 0.000 description 1
- 201000010099 disease Diseases 0.000 description 1
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 230000009977 dual effect Effects 0.000 description 1
- 239000007772 electrode material Substances 0.000 description 1
- 206010015037 epilepsy Diseases 0.000 description 1
- 238000003706 image smoothing Methods 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000001766 physiological effect Effects 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 208000019116 sleep disease Diseases 0.000 description 1
- 208000022925 sleep disturbance Diseases 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
Classifications
-
- 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]
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
- A61B5/0006—ECG or EEG signals
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4058—Detecting, measuring or recording for evaluating the nervous system for evaluating the central nervous system
- A61B5/4064—Evaluating the brain
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
- A61B5/4094—Diagnosing or monitoring seizure diseases, e.g. epilepsy
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4809—Sleep detection, i.e. determining whether a subject is asleep or not
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4812—Detecting sleep stages or cycles
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
- A61B5/4815—Sleep quality
-
- 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
-
- 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
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- Veterinary Medicine (AREA)
- Biophysics (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Animal Behavior & Ethology (AREA)
- Physics & Mathematics (AREA)
- Public Health (AREA)
- Pathology (AREA)
- Neurology (AREA)
- Physiology (AREA)
- Signal Processing (AREA)
- Psychiatry (AREA)
- Neurosurgery (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Psychology (AREA)
- Power Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Anesthesiology (AREA)
- Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
Abstract
The invention belongs to the technical field of electroencephalogram signal acquisition, and discloses a monaural electroencephalogram signal acquisition device and a method thereof, wherein the method comprises the following steps: (1) acquiring a single-lead ear electroencephalogram signal, (2) removing baseline drift, (3) removing power frequency interference, (4) removing non-electroencephalogram signal components, and (5) extracting effective components of the ear electroencephalogram signal. The device comprises an ear electroencephalogram collecting electrode, an ear electroencephalogram signal collecting module, a Bluetooth transmitting/receiving module 2 and an ear electroencephalogram signal processing and displaying module. Compared with the traditional electroencephalogram acquisition technology, the monaural electroencephalogram signal acquisition device has the advantages of low cost, portability, wireless data transmission, wearing comfort, real-time data processing, convenience in operation and use and the like while maintaining the quality of the high-ear electroencephalogram signal.
Description
Technical field
The present invention relates to a kind of single guide lug eeg signal acquisition devices and methods therefors, belong to eeg signal acquisition technology neck
Domain.
Background technique
EEG signals (Electroencephalograph, EEG) are the bioelectrical activities of brain nervous cell in scalp table
The overall reflection in face, can record this potential change fluctuated at any time by electrode.It include a large amount of in EEG signals
Nervous activity information, be clinically of great significance to, become diagnosis brain related disease important means,
Such as sleep disturbance, epilepsy, phrenoblabia.The acquisition technique of EEG signals is rapidly developing at present, and the lead number of acquisition is more next
It is more, it more emphasizes to realize the coupling between electrode and scalp by conductive paste.However, more lead numbers make EEG signals
The cost of acquisition and processing increases significantly, charges polar cap and beats conductive paste subject perception can be made very uncomfortable, thus for it is long when
Between the job requirements of continuous acquisition EEG signals then need using more convenient and fast acquisition device and method.It is replaced using dry electrode
Wet electrode is simultaneously designed to that wearable brain electrical signal collection device is one of developing direction.Ear brain electricity is in ear without hair skin portion
Position record a small number of leads or singly lead EEG signals, it is advantageous that acquisition signal when little effect on the human body, not vulnerable to eye movement because
Plain influence has and may be designed to wearable device, at present using dry electrode record stabilization with signal-to-noise ratio similar in scalp brain electricity
Rarely has relevant research.Faint for ear EEG signals, the low feature of signal-to-noise ratio needs in signal acquisition and transmission using suitable
When method handled.
Summary of the invention
In order to overcome the deficiencies in the prior art, it is an object of the present invention to provide a kind of single guide lug eeg signal acquisitions to fill
It sets and its method, including hardware configuration and signal processing method, it is comprehensive to be embodied in ear brain wave acquisition end and computer control processing
End.The ear EEG signals that dry electrode obtains are passed through bluetooth transmission/reception module 1 by ear brain wave acquisition end after filter and amplification samples
It is wirelessly transferred, computer control processing end is handled after receiving ear EEG signals by bluetooth transmission/reception module 2
Display and based on the analysis results Reverse Turning Control collection terminal adjusting parameter are to obtain more preferable effect.Single guide lug EEG signals of the invention
Acquisition device comfortable wearing does not influence the normal work and rest of subject, can be used for long-time continuous acquisition EEG signals.
In order to achieve the above-mentioned object of the invention, in the presence of solving the problems, such as prior art, technical solution that the present invention takes
It is: a kind of processing method of list guide lug EEG signals, comprising the following steps:
Step 1 acquires single guide lug EEG signals, and transmits wirelessly/receive eeg data and programming Control letter by bluetooth
Number；
Step 2, removal baseline drift, it is a kind of nonstationary random signal that baseline drift, which belongs to low-frequency noise, is based on small echo
The multiresolution property of transformation removes baseline drift using the method for Wavelet decomposing and recomposing；
Step 3, removal Hz noise, Hz noise intensity is high, and is ubiquitous in unshielded environments, it is necessary to
Hz noise is filtered out by trapper, good effect can be reached using the direct II mode filter of 4 ranks, trap frequency is set as
50Hz；
Step 4 is gone unless EEG signals ingredient, EEG signals include following several brain electrical feature waves: α wave frequency range 8
13~30Hz of~13Hz, β wave frequency range, 1~4Hz of δ wave frequency range, 4~8Hz of θ wave frequency range；For in these frequencies
Except signal component, be that other bioelectrical activities generate by human body, need to filter out, using the direct II type bandpass filtering of 6 ranks
Device, it is contemplated that bandpass filtering frequency is set as 0.2~40Hz by the effective component of EEG signals；
Step 5, ear EEG signals effective component are extracted, and detect mesh for sleep state monitoring, epileptic attack, phrenoblabia
, it needs selectively to extract ear EEG signals effective component, wavelet coefficient, small wavelength-division is extracted by wavelet decomposition, threshold method
Solution reconstruct realizes that ear EEG signals effective component is extracted.
The single guide lug eeg signal acquisition device used in the processing method, including ear brain wave acquisition electrode, ear brain electricity
Signal acquisition module, bluetooth transmission/reception module 2 and ear EEG Processing and display module, the ear brain wave acquisition electrode
Output end be connected with the input terminal of ear electroencephalogramsignal signal acquisition module, the ear electroencephalogramsignal signal acquisition module sends/connects with bluetooth
Receive wirelessly connection completion wireless data transmission, and the ear EEG signals progress by software to acquisition between module 2
Processing, finally obtains high-quality ear EEG signals；At the output end and ear EEG signals of the bluetooth transmission/reception module 2
Reason is connected with the input terminal of display module, the output end and bluetooth transmission/reception module 2 of ear EEG Processing and display module
Input terminal be connected, the ear electroencephalogramsignal signal acquisition module, including voltage protection module, low-pass filtering module, signal acquisition mould
Block, single chip processing module, SD memory module and bluetooth transmission/reception module 1, the output end of the voltage protection module with it is low
The input terminal of pass filtering module is connected, and the output end of low-pass filtering module is connected with the input terminal of signal acquisition module, the list
The input terminal of piece machine processing module respectively with the output end of signal acquisition module, the output end of SD memory module and bluetooth send/
The output end of receiving module 1 is connected, the output end of the single chip processing module also respectively with the input terminal of signal acquisition module,
The input terminal of SD memory module and the input terminal of bluetooth transmission/reception module 1 are connected；The ear brain wave acquisition electrode is sponge ear
Plug, surface has oval silver fiber conductive fabric and silver fiber conductor wire, for acquiring the ear EEG signals in ear canal.
The voltage protection module uses TPD4E1B06 chip, which is the ultralow leakage electro-static discharge protector in 4 channels
Part, for preventing from damaging device due to circuit voltage is excessively high.
The signal acquisition module uses ADS1299 chip, which supports 8 channel eeg data synchronous acquisitions, have
1,2,4,6,9,12,24 times of low-noise programmable gain amplifiers and 8 high-resolution synchronized sampling analog-digital converters.
The single chip processing module use PIC32MX25F128B chip, for connect and control signal acquisition module,
SD memory module and bluetooth transmission/reception module 1.
The bluetooth transmission/reception module 1 uses RFD22301 chip, is used to carry out nothing with bluetooth transmission/reception module 2
Line number is according to transmission and programming Control.
The medicine have the advantages that a kind of list guide lug eeg signal acquisition devices and methods therefor, wherein method includes following
Step: (1) acquiring single guide lug EEG signals, and (2) remove baseline drift, and (3) remove Hz noise, and (4) are gone unless EEG signals
Ingredient, (5) ear EEG signals effective component are extracted.Device includes the ear brain wave acquisition electrode at ear brain wave acquisition end, voltage protection
Module, low-pass filtering module, signal acquisition module, single chip processing module, SD memory module and bluetooth transmission/reception module 1
And the bluetooth transmission/reception module 2 and ear EEG Processing and display module of computer control processing end.Ear brain wave acquisition
Wirelessly data transmission and programming Control are completed in connection between end and computer control processing end, and by software to adopting
The ear EEG signals of collection are handled, and high-quality ear EEG signals are finally obtained；Compared with the prior art, the present invention have with
Lower advantage: (1) apparatus of the present invention are portable, low in cost, and collecting end device only needs 6V dry cell to be powered；(2) ear brain electricity is adopted
Current collection extremely sponge earplug, silver fiber conductive fabric and silver fiber conductor wire, electrode material are dry electrode, and comfortable wearing does not influence
People's rest and normal physiological activity；(3) acquisition device has built-in SD card, can carry out data storage, signal acquisition mould
Block is wirelessly connected by bluetooth and computer, can carry out wireless data transmission and data real-time display, real-time storage, in real time place
Reason；(4) device can at most acquire 8 channel signals, can both acquire single channel ear EEG signals, ear EEG signals also may be implemented
With scalp EEG signals synchronous acquisition；(5) Preprocessing Algorithm is devised, the preferable single channel ear EEG signals of quality are obtained,
These signals are compared with scalp EEG signals, and the interference of eye movement factor is few, with EEG signals correlation with higher；(6) this hair
Bright interchannel interference it is small, it can be achieved that single input and dual input, it can be achieved that brain electricity and other physiological signals synchronous acquisition.
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart of steps.
Fig. 2 is invention's principle block diagram.
Fig. 3 is the ear electroencephalogramsignal signal acquisition module functional block diagram in the present invention.
Fig. 4 is 3 layer scattering wavelet decomposition schematic diagrames.
Fig. 5 is 50Hz trapper frequency response curve figure.
Fig. 6 is 0.2~40Hz bandpass filter frequency response curve figure.
Fig. 7 is the flow chart that wavelet thresholding method extracts ear EEG signals effective component.
Fig. 8 is ear eeg data and data processed result schematic diagram.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings.
As shown in Figure 1, a kind of processing method of list guide lug EEG signals, comprising the following steps:
Step 1 acquires single guide lug EEG signals, and transmits wirelessly/receive eeg data and programming Control letter by bluetooth
Number；
Step 2, removal baseline drift, it is a kind of nonstationary random signal that baseline drift, which belongs to low-frequency noise, is based on small echo
The multiresolution property of transformation removes baseline drift using the method for Wavelet decomposing and recomposing；Fig. 4 is the signal of 3 layer scattering wavelet decompositions
Figure carries out discrete wavelet transformation to x (n), and first layer decomposes to obtain approximation coefficient A1With detail coefficients D1, wherein approximation coefficient master
It to be low frequency part, detail coefficients are mainly high frequency section, to A1Wavelet decomposition is carried out again, obtains approximation coefficient A2And details
Coefficient D2, and so on；The present invention carries out 8 layer scattering wavelet decompositions to x (n) using ' db4 ' wavelet basis, obtains approximation coefficient A8
With detail coefficients D1、D2、D3、D4、D5、D6、D7、D8, wherein A8Frequency range beIt is 250Hz's in sample frequency Fs
Under the conditions of can obtain A8Frequency range be 0~0.488Hz, this frequency range correspond to baseline drift；Ignore A8According only to D1~
D8It is reconstructed, the ear EEG signals after removal baseline drift can be obtained；
Step 3, removal Hz noise, Hz noise intensity is high, and is ubiquitous in unshielded environments, it is necessary to
Hz noise is filtered out by trapper, good effect can be reached using the direct II mode filter of 4 ranks, trap frequency is set as
The frequency response curve of 50Hz, designed notch filter are as shown in Figure 5.
Step 4 is gone unless EEG signals ingredient, EEG signals include following several brain electrical feature waves: α wave frequency range 8
13~30Hz of~13Hz, β wave frequency range, 1~4Hz of δ wave frequency range, 4~8Hz of θ wave frequency range；For in these frequencies
Except signal component, be that other bioelectrical activities generate by human body, need to filter out, using the direct II type bandpass filtering of 6 ranks
Device, it is contemplated that bandpass filtering frequency is set as 0.2~40Hz, designed bandpass filter by the effective component of EEG signals
Frequency response curve it is as shown in Figure 6.
Step 5, ear EEG signals effective component are extracted, and detect mesh for sleep state monitoring, epileptic attack, phrenoblabia
, it needs selectively to extract ear EEG signals effective component, wavelet coefficient, small wavelength-division is extracted by wavelet decomposition, threshold method
Solution reconstruct realizes that ear EEG signals effective component is extracted.Fig. 7 is the process that wavelet thresholding method extracts ear EEG signals effective component
Figure, wherein thr represents the threshold value of selection, and what sorh represented selection is hard -threshold or soft-threshold, and whether keepapp represents to close
Threshold process is carried out like component.Meanwhile appropriate wavelet basis is chosen according to effective component feature to be extracted, input signal is carried out small
Wave conversion obtains wavelet coefficient array C and wavelet coefficient length array L；Wavelet coefficient is handled by threshold method and is weighed again
Wavelet thresholding method can be obtained treated ear EEG signals in structure；Collected original ear EEG signals through removal baseline drift,
Removal Hz noise is gone unless signal change procedure such as Fig. 8 institute after the processing steps such as EEG signals ingredient and effective component are extracted
Show, it can be seen that original ear EEG signals are of poor quality, and drift is serious；After removing baseline drift, signal amplitude at 0 microvolt above and below
Fluctuation；After removing Hz noise using trap, signal becomes fine；The edge that makes signal using bandpass filtering, spike are more
Add protrusion；Finally, obtaining the apparent high quality ear EEG signals of image smoothing, feature by wavelet thresholding method.
As shown in Fig. 2, single guide lug eeg signal acquisition device, including ear brain wave acquisition electrode, ear eeg signal acquisition mould
Block, bluetooth transmission/reception module 2 and ear EEG Processing and display module, the output end of the ear brain wave acquisition electrode with
The input terminal of ear electroencephalogramsignal signal acquisition module is connected, between the ear electroencephalogramsignal signal acquisition module and bluetooth transmission/reception module 2
Wirelessly wireless data transmission is completed in connection, and is handled by ear EEG signals of the software to acquisition, is finally obtained
Obtain high-quality ear EEG signals；The output end and ear EEG Processing and display module of the bluetooth transmission/reception module 2
Input terminal be connected, ear EEG Processing and the output end of display module and the input terminal phase of bluetooth transmission/reception module 2
Even.The ear brain wave acquisition electrode is sponge earplug, and surface has oval silver fiber conductive fabric and silver fiber conductor wire, is used to
Acquire the ear EEG signals in ear canal.
As shown in figure 3, ear electroencephalogramsignal signal acquisition module, including voltage protection module, low-pass filtering module, signal acquisition mould
Block, single chip processing module, SD memory module and bluetooth transmission/reception module 1, the output end of the voltage protection module with it is low
The input terminal of pass filtering module is connected, and the output end of low-pass filtering module is connected with the input terminal of signal acquisition module, the list
The input terminal of piece machine processing module respectively with the output end of signal acquisition module, the output end of SD memory module and bluetooth send/
The output end of receiving module 1 is connected, the output end of the single chip processing module also respectively with the input terminal of signal acquisition module,
The input terminal of SD memory module and the input terminal of bluetooth transmission/reception module 1 are connected；The voltage protection module uses
TPD4E1B06 chip, which is the ultralow leakage electrostatic discharge protector in 4 channels, for preventing due to circuit voltage is excessively high
Device is damaged.The signal acquisition module uses ADS1299 chip, which supports 8 channel eeg datas synchronize to adopt
Collection has 1,2,4,6,9,12,24 times of low-noise programmable gain amplifier and 8 high-resolution synchronized sampling analog-to-digital conversions
Device.The single chip processing module uses PIC32MX25F128B chip, for connecting and controlling signal acquisition module, SD storage
Module and bluetooth transmission/reception module 1.The bluetooth transmission/reception module 1 uses RFD22301 chip, is used to send out with bluetooth
Give/receiving module 2 carries out wireless data transmission and programming Control.
The present invention is comprehensive to be embodied in ear brain wave acquisition end and computer control processing end, and dry electrode is obtained at ear brain wave acquisition end
The ear EEG signals taken are wirelessly transferred after filter and amplification samples by bluetooth transmission/reception module 1, at computer control
Reason end carries out processing display and based on the analysis results reversed control after receiving ear EEG signals by bluetooth transmission/reception module 2
Collection terminal adjusting parameter processed is to obtain more preferable effect.
Claims (6)
1. a kind of processing method of list guide lug EEG signals, it is characterised in that the following steps are included:
Step 1 acquires single guide lug EEG signals, and transmitted wirelessly by bluetooth/receive eeg data and programming control signal；
Step 2, removal baseline drift, it is a kind of nonstationary random signal that baseline drift, which belongs to low-frequency noise, is based on wavelet transformation
Multiresolution property using Wavelet decomposing and recomposing method remove baseline drift；
Step 3, removal Hz noise, Hz noise intensity is high, and is ubiquitous in unshielded environments, it is necessary to pass through
Trapper filters out Hz noise, can reach good effect using the direct II mode filter of 4 ranks, trap frequency is set as
50Hz；
Step 4 is gone unless EEG signals ingredient, EEG signals include following several brain electrical feature waves: α wave frequency range 8~
13~30Hz of 13Hz, β wave frequency range, 1~4Hz of δ wave frequency range, 4~8Hz of θ wave frequency range；For these frequencies it
Outer signal component is that other bioelectrical activities generate by human body, needs to filter out, using the direct II type bandpass filter of 6 ranks,
In view of the effective component of EEG signals, bandpass filtering frequency is set as 0.2~40Hz；
Step 5, ear EEG signals effective component are extracted, for sleep state monitoring, epileptic attack, phrenoblabia testing goal,
It needs selectively to extract ear EEG signals effective component, wavelet coefficient, wavelet decomposition weight is extracted by wavelet decomposition, threshold method
Structure realizes that ear EEG signals effective component is extracted.
2. the single guide lug eeg signal acquisition device used in processing method according to claim 1, including ear brain wave acquisition
Electrode, ear electroencephalogramsignal signal acquisition module, bluetooth transmission/reception module 2 and ear EEG Processing and display module, feature exist
In: the output end of the ear brain wave acquisition electrode is connected with the input terminal of ear electroencephalogramsignal signal acquisition module, the ear EEG signals
Wirelessly wireless data transmission is completed in connection between acquisition module and bluetooth transmission/reception module 2, and passes through software pair
The ear EEG signals of acquisition are handled, and high-quality ear EEG signals are finally obtained；The bluetooth transmission/reception module 2
Output end is connected with ear EEG Processing with the input terminal of display module, the output end of ear EEG Processing and display module
It is connected with the input terminal of bluetooth transmission/reception module 2, the ear electroencephalogramsignal signal acquisition module, including voltage protection module, low pass
Filter module, signal acquisition module, single chip processing module, SD memory module and bluetooth transmission/reception module 1, the voltage
The output end of protective module is connected with the input terminal of low-pass filtering module, the output end and signal acquisition module of low-pass filtering module
Input terminal be connected, the input terminal of the single chip processing module respectively with the output end of signal acquisition module, SD memory module
Output end and bluetooth transmission/reception module 1 output end be connected, the output end of the single chip processing module also respectively with letter
The input terminal of number input terminal of acquisition module, the input terminal of SD memory module and bluetooth transmission/reception module 1 is connected；The ear
Brain wave acquisition electrode is sponge earplug, and surface has oval silver fiber conductive fabric and silver fiber conductor wire, for acquiring ear canal
Interior ear EEG signals.
3. the single guide lug eeg signal acquisition device used in processing method according to claim 2, it is characterised in that: described
Voltage protection module uses TPD4E1B06 chip, which is the ultralow leakage electrostatic discharge protector in 4 channels, for preventing
Device is damaged due to circuit voltage is excessively high.
4. the single guide lug eeg signal acquisition device used in processing method according to claim 2, it is characterised in that: described
Signal acquisition module use ADS1299 chip, the chip support 8 channel eeg data synchronous acquisitions, have 1,2,4,6,9,12,
24 times of low-noise programmable gain amplifiers and 8 high-resolution synchronized sampling analog-digital converters.
5. the single guide lug eeg signal acquisition device used in processing method according to claim 2, it is characterised in that: described
Single chip processing module use PIC32MX25F128B chip, for connect and control signal acquisition module, SD memory module and
Bluetooth transmission/reception module 1.
6. the single guide lug eeg signal acquisition device used in processing method according to claim 2, it is characterised in that: described
Bluetooth transmission/reception module 1 use RFD22301 chip, be used to bluetooth transmission/reception module 2 carry out wireless data transmission and
Programming Control.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910017413.3A CN109674467A (en) | 2019-01-08 | 2019-01-08 | Single-lead-ear electroencephalogram signal acquisition device and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910017413.3A CN109674467A (en) | 2019-01-08 | 2019-01-08 | Single-lead-ear electroencephalogram signal acquisition device and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109674467A true CN109674467A (en) | 2019-04-26 |
Family
ID=66192167
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910017413.3A Pending CN109674467A (en) | 2019-01-08 | 2019-01-08 | Single-lead-ear electroencephalogram signal acquisition device and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109674467A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112472106A (en) * | 2019-09-10 | 2021-03-12 | 西安慧脑智能科技有限公司 | A method, chip, storage medium and device for analyzing brain electrical signals |
| CN113331842A (en) * | 2021-06-24 | 2021-09-03 | 中国人民解放军空军特色医学中心 | Human body electroencephalogram signal acquisition device and method of manned centrifuge |
| CN114403900A (en) * | 2022-02-08 | 2022-04-29 | 刘政博 | Electroencephalogram data automatic recording and analyzing system and method in electroencephalogram machine |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140171775A1 (en) * | 2011-08-24 | 2014-06-19 | Widex A/S | Eeg monitor with capactive electrodes and a method of monitoring brain waves |
| CN104000586A (en) * | 2014-05-12 | 2014-08-27 | 燕山大学 | Stroke patient rehabilitation training system and method based on brain myoelectricity and virtual scene |
| CN104042211A (en) * | 2013-03-15 | 2014-09-17 | 潘晶 | Non-fixed-contact-type electrocerebral acquisition system and information acquisition method thereof |
| CN105078448A (en) * | 2014-05-16 | 2015-11-25 | 上海理工大学 | Electroencephalogram acquisition and wireless transmission device |
| CN105982665A (en) * | 2015-02-12 | 2016-10-05 | 中国科学院上海高等研究院 | Method for collecting brain wave signals from human ear auditory meatus |
| CN106175673A (en) * | 2016-07-04 | 2016-12-07 | 西安交通大学 | A kind of method of spindle wave in automatic identification and extraction sleep cerebral electricity |
| CN106388818A (en) * | 2016-09-21 | 2017-02-15 | 广州视源电子科技股份有限公司 | Method and system for extracting characteristic information of sleep state monitoring model |
| CN106580306A (en) * | 2016-12-29 | 2017-04-26 | 深圳先进技术研究院 | Electrophysiological signal fabric collection device |
| CN207084818U (en) * | 2017-01-23 | 2018-03-13 | 深圳市和唯健康科技有限公司 | A kind of portable brain electric sleep monitor and system |
| US20180116514A1 (en) * | 2016-11-02 | 2018-05-03 | Bragi GmbH | Earpiece with in-ear electrodes |
| CN108236463A (en) * | 2016-12-23 | 2018-07-03 | 布朗诺科技(北京）有限公司 | Use the health monitoring systems of tack formula wearable device |
| CN108451505A (en) * | 2018-04-19 | 2018-08-28 | 广西欣歌拉科技有限公司 | The In-Ear sleep stage system of light weight |
-
2019
- 2019-01-08 CN CN201910017413.3A patent/CN109674467A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140171775A1 (en) * | 2011-08-24 | 2014-06-19 | Widex A/S | Eeg monitor with capactive electrodes and a method of monitoring brain waves |
| CN104042211A (en) * | 2013-03-15 | 2014-09-17 | 潘晶 | Non-fixed-contact-type electrocerebral acquisition system and information acquisition method thereof |
| CN104000586A (en) * | 2014-05-12 | 2014-08-27 | 燕山大学 | Stroke patient rehabilitation training system and method based on brain myoelectricity and virtual scene |
| CN105078448A (en) * | 2014-05-16 | 2015-11-25 | 上海理工大学 | Electroencephalogram acquisition and wireless transmission device |
| CN105982665A (en) * | 2015-02-12 | 2016-10-05 | 中国科学院上海高等研究院 | Method for collecting brain wave signals from human ear auditory meatus |
| CN106175673A (en) * | 2016-07-04 | 2016-12-07 | 西安交通大学 | A kind of method of spindle wave in automatic identification and extraction sleep cerebral electricity |
| CN106388818A (en) * | 2016-09-21 | 2017-02-15 | 广州视源电子科技股份有限公司 | Method and system for extracting characteristic information of sleep state monitoring model |
| US20180116514A1 (en) * | 2016-11-02 | 2018-05-03 | Bragi GmbH | Earpiece with in-ear electrodes |
| CN108236463A (en) * | 2016-12-23 | 2018-07-03 | 布朗诺科技(北京）有限公司 | Use the health monitoring systems of tack formula wearable device |
| CN106580306A (en) * | 2016-12-29 | 2017-04-26 | 深圳先进技术研究院 | Electrophysiological signal fabric collection device |
| CN207084818U (en) * | 2017-01-23 | 2018-03-13 | 深圳市和唯健康科技有限公司 | A kind of portable brain electric sleep monitor and system |
| CN108451505A (en) * | 2018-04-19 | 2018-08-28 | 广西欣歌拉科技有限公司 | The In-Ear sleep stage system of light weight |
Non-Patent Citations (7)
| Title |
|---|
| ANDREAS STOCHHOLM, KAARE MIKKELSEN, PREBEN KIDMOSE: "Automatic Sleep Stage Classification Using Ear-EEG", 《2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)》 * |
| C. B. CHRISTENSEN, ET AL: "Auditory Steady-State Responses across Chirp Repetition Rates for Ear-EEG and Scalp EEG", 《2018 40TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) 》 * |
| I.C. ZIBRANDTSEN, ET AL: "Ear-EEG detects ictal and interictal abnormalities in focal and generalized epilepsy – A comparison with scalp EEG monitoring", 《CLINICAL NEUROPHYSIOLOGY》 * |
| J. CHLADEK. ET AL: "Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domin", 《35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE EMBS》 * |
| KAARE B. MIKKELSEN, ET AL: "EEG Recorded from the Ear: Characterizing the Ear-EEG Method", 《FRONTIERS IN NEUROSCIENCE》 * |
| R. CHINMAYI.ET AL: "Extracting the Features of Emotion from EEG Signals and Classify Using Affective Computing", 《2017 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, SIGNAL PROCESSING AND NETWORKING (WISPNET)》 * |
| TAEHO HWANG,ET AL: "Driver Drowsiness Detection Using the In-Ear EEG", 《2016 38TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112472106A (en) * | 2019-09-10 | 2021-03-12 | 西安慧脑智能科技有限公司 | A method, chip, storage medium and device for analyzing brain electrical signals |
| CN113331842A (en) * | 2021-06-24 | 2021-09-03 | 中国人民解放军空军特色医学中心 | Human body electroencephalogram signal acquisition device and method of manned centrifuge |
| CN114403900A (en) * | 2022-02-08 | 2022-04-29 | 刘政博 | Electroencephalogram data automatic recording and analyzing system and method in electroencephalogram machine |
| CN114403900B (en) * | 2022-02-08 | 2024-04-05 | 周口市中心医院 | Electroencephalogram data automatic recording and analyzing system and method in electroencephalogram machine |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11980469B2 (en) | Systems and methods to gather and analyze electroencephalographic data | |
| CA2285354C (en) | System and method for enhancing and separating biopotential signals | |
| US8391967B2 (en) | Body-based monitoring of brain electrical activity | |
| EP2698099B1 (en) | Systems and methods to gather and analyze electroencephalographic data | |
| AU2010315490A1 (en) | Biomedical electrode | |
| CN109674467A (en) | Single-lead-ear electroencephalogram signal acquisition device and method | |
| CN107463249A (en) | Show the brain machine interface system and control method of VEP based on VR heads | |
| CN106037649A (en) | Wearable acquisition device | |
| CN102824171A (en) | Method for extracting electroencephalogram features of patients suffering from PSD (post-stroke depression) | |
| Yong et al. | Facial EMG contamination of EEG signals: Characteristics and effects of spatial filtering | |
| CN108836308A (en) | A kind of device removing wearable electrocardio motion artifacts | |
| Mandekar et al. | Earable design analysis for sleep EEG measurements | |
| CN106264570B (en) | Method, device and system for monitoring addiction status of drug addict in real time | |
| US20230240581A1 (en) | System and methods for biosignal detection and active noise cancellation | |
| US20230355156A1 (en) | High resolution electroencephalograph signal acquisition system | |
| CN112515680B (en) | Wearable brain electrical fatigue monitoring system | |
| CN210871574U (en) | A headphone type EEG signal acquisition device | |
| CN203988050U (en) | The program control amplification system of a kind of electricity multi channel signals of the brain for mancarried device | |
| Jiang et al. | Comparison of different shielding methods in acquisition of physiological signals | |
| CN206896336U (en) | A kind of device for being used to monitor brain wave feedback | |
| Vaid et al. | De-noising of EEG signal for emotion recognition | |
| Shaikh et al. | Advanced Technique for EEG and HRV Measurement Using Around-Ear Capacitive Electrodes | |
| Raj | A System For Automatic Recognition of Hand Gestures Based on Temporal Features and Feed Forward Neural Network By Using Electromyographic Data | |
| CN113407026A (en) | Brain-computer interface system and method for enhancing hairless area electroencephalogram response intensity | |
| CN117481667A (en) | Electroencephalogram signal acquisition system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190426 |