CN109276227A - Based on EEG technology to visual fatigue analysis method caused by three-dimensional Depth Motion - Google Patents
Based on EEG technology to visual fatigue analysis method caused by three-dimensional Depth Motion Download PDFInfo
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Abstract
The present invention relates to one kind based on EEG technology to visual fatigue analysis method caused by three-dimensional Depth Motion, comprising the following steps: the production of the three-dimensional depth sport video of certain time length, movement velocity be divided into it is slow, in, it is three kinds fast；Subjective scoring standard is divided；The subjective evaluation result of subject is analyzed, is analyzed including every subjective scoring one-way analysis of variance and the generality of appearance；Acquire the EEG signals of each subject fatigue front and back, after pretreatment, 3 base bands of θ, α, β and relative energy and energy ratio (α+θ)/β, α/β, θ/β, (α+θ)/(alpha+beta), α/θ, θ/(alpha+beta) of EEG signals on each electrode are extracted respectively；Carry out the screening for being suitable for assessing visual fatigue brain electrical feature.
Description
Technical field:
The present invention relates to 3D visual fatigue evaluation areas.
Background technique:
With the development of stereo display technique, 3D display gradually comes into daily life.Due to existing in 3D image
The conflict that influx is adjusted, when viewing, will appear different degrees of vision discomfort, and with time integral, it is tired vision often occur
Labor[1]Subjective assessment is broadly divided into the evaluation of stereoscopic vision fatigue and objectively evaluates two classes[2].Subjective evaluation method passes through design
Corresponding evaluation of programme estimates that fatigue conditions, method for objectively evaluating is then based on algorithm, EEG signals
(ElectroencephalographyEEG) expansion such as[3].EEG signals are able to reflect the bioelectrical activity of cranial nerve cell,
In include Physiological Psychology information abundant, be a kind of effective method for objectively evaluating.By subjective experiment and the visitor based on EEG
It sees evaluation experimental to combine, more reasonable effective experimental result will be obtained.
[1]Nojiri Y,Yamanoue H,Hanazato A,et al.Measurement of Binocular
Parallax in Stereoscopic HDTV andVisual Comfort to View[J]
.JournaloftheInstitute ofImageInformation&TelevisionEngineers,2003,57(9):
1125-1134.
[2]Chen C,Li K,Wu Q,et al.EEG-based detection and evaluation
offatigue caused by watching3DTV[J].Displays,2013,34(2):81-88.
[3]Lambooij,Marc,Fortuin,Marten,Heynderickx,Ingrid,et al.Visual
Discomfort and Visual Fatigue of Stereoscopic Displays:A Review[J].Journal of
Imaging Science and Technology,2009,53(3):30201-1-30201-14(14).
Summary of the invention:
The object of the present invention is to provide a kind of analyses with brain power technology to visual fatigue caused by three-dimensional Depth Motion
Method is based on the analysis method, lays the foundation for rationally assessment visual fatigue.Technical solution of the present invention is as follows:
One kind is based on EEG technology to visual fatigue analysis method caused by three-dimensional Depth Motion, comprising the following steps:
1) production of the three-dimensional depth sport video of certain time length, movement velocity be divided into it is slow, in, it is three kinds fast, every kind each two
It is a, respectively 32cm/s, 52cm/s, 96cm/s, 128cm/s, 192cm/s, 256cm/s；
2) subjective scoring standard is divided, is divided into five grades 1: nothing；2: slight；3: general；4: serious；5: very
Seriously；
3) subjective evaluation result of subject is analyzed, including every subjective scoring one-way analysis of variance and go out
Existing generality analysis；
4) EEG signals for acquiring each subject fatigue front and back extract brain electricity on each electrode after pretreatment respectively
3 base bands of θ, α, β and relative energy and energy ratio (α+θ)/β, α/β, θ/β, (α+θ)/(alpha+beta), α/θ, θ of signal/
(α+β)；
5) screening for being suitable for assessing visual fatigue brain electrical feature is carried out
A. by 3 base bands (θ, α, β) of each electrode EEG signals of each subject fatigue front and back and 6 ratio fortune
The average relative energy for calculating (α/β, α/θ, θ/(alpha+beta), (α+θ)/β, θ/β, (α+θ)/(alpha+beta)) is divided using paired t-test
Analysis, obtains the index for significant difference occur；
B. the Fisher ratio for the index of significant difference occur is calculated, and according to its size to progress descending arrangement；
C. first 5,10 etc. are successively chosen than the result of sequence according to Fisher as feature vector, is utilized respectively SVM
Classify to the EEG signals of each subject, finds to the classification highest characteristic index collection of contribution rate；
D. the solid for being suitble to assessment three-dimensional depth movement to cause is focused to find out in characteristic index using grey relational grade analysis
The optimal parameter of visual fatigue are as follows: central area α, central area α/θ and top area's α/β；
E. the validity of verifying gained optimal parameter.
The assessment result of every symptom is exact before and after the viewing that subjective assessment obtains, the solid for watching certain time length is deep
Degree sport video can cause visual fatigue.The EEG signals of each subject in comparative analysis viewing front and back, obtain and are suitable for evaluation
The reasonable index of stereoscopic vision fatigue can do the evaluation work of the more stereoscopic vision fatigue based on brain electricity on this basis.
Detailed description of the invention:
By attached drawing, implementation steps and advantage of the invention can be made more to highlight, be also more conducive to the reason of user
Solution and operation.
Fig. 1 is experiment flow figure of the invention.
Fig. 2 is that the subjective scoring of 12 subjects stacks histogram.
Fig. 3 is each wave band relative energy brain electrical activity mapping before and after viewing three-dimensional video-frequency.Wherein (a), (b) are respectively to be tested
Tri- wave bands of θ, α, β be averaged relative energy brain electrical activity mapping before and after viewing three-dimensional video-frequency, and figure (c) is average even brain
Electrical activity mapping.
Fig. 4 is the Fisher ratio of 46 indexs.
Specific embodiment:
It is convenient to carry out to keep the solution of the present invention more clear, in order to more highlight advantages of the present invention and mesh
, detailed elaboration and explanation are made to embodiment.
101: building EEG acquisition platform
The composition of EEG experiment porch includes: high-performance computer 2, Neuroscan signal amplifier, stereoscopic display
(stimulation presentation device), 32 conductive polar caps (Ag-AgCl electrode is distributed according to international 10-20 system), polarization type anaglyph spectacles.
Stereoscopic display is that resolution ratio is 1366 × 768, and refreshing frequency is the Changhong stereotelevision of 60Hz, uses E-prime
2.0 image stimulation is presented.Subject is required to wear 64 conductive polar cap (resistances of polarization type anaglyph spectacles and Neuroscan company
It is anti-to be less than or equal to 5K Ω.Subject is at 3 times of display screen vertical height away from display screen distance.
Requirement and condition to subject are as follows: health, male to female ratio is suitable, and the age is 23~27 years old.All subjects
Normal visual acuity is corrected defects of vision normal.All subject state of mind are good, signature subject informed consent form before experiment starts, and obtain
It obtains and accordingly compensates, so that it is familiar with whole experiment process and points for attention in advance, but be not apprised of experiment purpose.
12 people of shared subject, 5 female, 7 male, the age is 23~27 years old.All subject normal visual acuities are corrected defects of vision normally,
All subject state of mind are good.
Moving target is a virtual stone in experimental material, and background is using dull blue sky and white cloud.Utilize grey ring
Parallax free position is marked, while limiting subject fixation range.Stone is with different movement velocitys along vertical screen direction positive and negative
Once do at the uniform velocity iterative motion in disparity range, movement velocity be divided into it is slow, in, it is three kinds fast, every kind each two, respectively
32cm/s,52cm/s,96cm/s,128cm/s,192cm/s,256cm/s.The movement of stone is since screen rear, every kind of speed
A length of 4s when the movement of degree.
Experiment stimulation is presented in a manner of side-by-side on stereoscopic display by E-prime program.To guarantee to see
See duration, 480 examinations time are arranged in entire experiment altogether, have 1s pause, the stereopsis of every kind of velocity mode between two adjacent examinations time
Frequency is random to be presented 80 times, and the entire presentation time is 40min.
102: the statistical analysis of subjective behavioral data
Table 1 is to every fatigue symptom subjective scoring progress one-way analysis of variance of 12 subjects as a result, can by table
Know, 12 fatigue symptoms significant difference occur before and after viewing three-dimensional video-frequency stimulation, demonstrate the reasonable of this experimental material
Property.
The generality that every fatigue symptom occurs further is probed into, makes every subject to the heap of every symptom score result
Folded histogram, as shown in Figure 2.As seen from the figure, different subjects have differences the appraisal result of different fatigue symptom, 12 subjects
The scoring of eye-blurred, the two dry and astringent fatigue symptoms of eyes is divided in 3-4, shows the severity of the two symptoms one
Determine that there is generality in situation；The mean scores of ghost image are equally higher, but the individual difference of its appraisal result is larger, the symptom or
Be can rapid recovery, it is not representative.
103: acquiring the EEG signals of subject, storage is used for off-line analysis
Eeg data is recorded by the electrode cap of 32 leads, world 10-20 system, data sampling frequency 1000Hz, filtering
Low-pass cut-off frequencies be 0.05Hz, high pass cut off frequency 100Hz.Reference electrode is right mastoid process electrode, each electrode electricity
Resistance value is not more than 5k Ω.
104: the EEG signals of each subject fatigue front and back are pre-processed
1. 1-30Hz bandpass filtering is carried out, to eliminate Hz noise.
2. removing artefact using independent component analysis (ICA).
3. pair EEG signal carries out Baseline wander, to eliminate baseline drift.
4. pair signal carries out segment processing, the brain telecommunications of 2min after extracting 2min before each electrode is watched respectively and watching
Number, the brain electricity segment that two class samples are respectively divided into 120 sections of 1s long is used for subsequent analysis.
105: the feature extraction and analysis of EEG signals
By Fast Fourier Transform (FFT) with the spectral resolution of 1Hz by pretreated brain electricity fragment map to θ, α, β tri-
A wave band, and calculate its relative energy.In addition to the relative energy of three base bands, the ratio and fatigue of different fast waves and slow wave
Degree of Accord Relation is close, therefore six energy ratio indexs of extraction simultaneously: (α+θ)/β, α/β, θ/β, (α+θ)/(alpha+beta), α/θ, θ/
(α+β).Fig. 3 (a), 3 (b) be respectively before and after subject viewing three-dimensional video-frequency tri- wave bands of θ, α, β be averaged relative energy brain electricity landform
Figure, Fig. 3 (c) are average even brain electrical activity mapping.As seen from the figure, subject θ wave band phase under awake and fatigue state
Anisotropic to energy difference little, then there is notable difference in α, beta band.Compared with waking state, under fatigue state the area α Bo Ding and its
The central area on periphery, temporo area obviously rise, and beta band is obvious in the decline of the area Zuo Nie, and top area is also declined slightly.
106: the screening suitable for assessing visual fatigue brain electrical feature
1. by 3 base bands (θ, α, β) of the 30 electrode EEG signals in each subject fatigue front and back and 6 ratio operations
The average relative energy of (α/β, α/θ, θ/(alpha+beta), (α+θ)/β, θ/β, (α+θ)/(alpha+beta)) is analyzed using paired t-test,
There are index totally 46 of significant difference (p < 0.05), shows that these indexs are very sensitive with the variation of degree of fatigue, the two
With certain relevance.
2. the Fisher ratio of 46 indexs is calculated, such as Fig. 4, and according to its size to progress descending arrangement.
3. successively choosing first 5,10 etc. as feature vector than the result of sequence according to Fisher, it is utilized respectively SVM
The EEG signals being tested to 12 are classified, and are found to the classification highest characteristic index collection of contribution rate.
4. the solid for being suitble to assessment three-dimensional depth movement to cause is focused to find out in characteristic index using grey relational grade analysis
The optimal parameter of visual fatigue are as follows: central area α, central area α/θ and top area's α/β.
5. the validity of verifying gained index.Respectively using three indexs as feature, using SVM classifier to before and after fatigue
Two class brain electricity samples are classified, and are verified according to separability of the size of classification rate to selected index.Three indexs it is flat
Equal nicety of grading shows that these three types of indexs all have good separability up to 70% or more.Wherein, this index of area's α/β is pushed up
Up to 90% or more in individual subjects, mean value illustrates that the separability of this index is best also above 80%, and the assessment that is more suitable is three-dimensional
Visual fatigue.
In conclusion the present invention utilizes EEG technology, designs objective experiment and combine subjective experiment data.It is subjective real
The three-dimensional depth sport video for showing to watch certain time length is tested, stereoscopic vision fatigue phenomenon generally occurs, wherein eyes are fuzzy, eye
The degree that both dry and astringent symptoms of eyeball occur is more serious.Three base bands θ, α, β are compared to regain consciousness and fatigue and phase under state
To the brain electrical activity mapping of energy, it is found that θ wave band does not occur significant change, α wave band is in the left side of central area, top area and temporo area
Divide and is decreased obviously, and the area β Bo Zenie is decreased obviously, top area also occurs declining phenomenon.Meanwhile pushing up area's α/β, central area α, center
Area α/θ shows good separability.Compare above three index nicety of grading, though there are individual difference, top area's α/β this
The nicety of grading that one index obtains is generally higher, shows that this index is tired most in the caused solid of assessment three-dimensional depth movement
Effectively.
Claims (1)
1. one kind is based on EEG technology to visual fatigue analysis method caused by three-dimensional Depth Motion, comprising the following steps:
1) production of the three-dimensional depth sport video of certain time length, movement velocity be divided into it is slow, in, it is three kinds fast, every kind each two, point
It Wei not 32cm/s, 52cm/s, 96cm/s, 128cm/s, 192cm/s, 256cm/s；
2) subjective scoring standard is divided, is divided into five grades 1: nothing；2: slight；3: general；4: serious；5: very tight
Weight；
3) subjective evaluation result of subject is analyzed, including every subjective scoring one-way analysis of variance and appearance
Generality analysis；
4) EEG signals for acquiring each subject fatigue front and back extract EEG signals on each electrode after pretreatment respectively
3 base bands of θ, α, β and relative energy and energy ratio (α+θ)/β, α/β, θ/β, (α+θ)/(alpha+beta), α/θ, θ/(α+
β)；
5) screening for being suitable for assessing visual fatigue brain electrical feature is carried out
A. by 3 base bands (θ, α, β) of each electrode EEG signals of each subject fatigue front and back and 6 ratio operations
The average relative energy of (α/β, α/θ, θ/(alpha+beta), (α+θ)/β, θ/β, (α+θ)/(alpha+beta)) is analyzed using paired t-test,
Obtain the index for significant difference occur；
B. the Fisher ratio for the index of significant difference occur is calculated, and according to its size to progress descending arrangement；
C. first 5,10 etc. are successively chosen than the result of sequence according to Fisher as feature vector, is utilized respectively SVM to each
The EEG signals of a subject are classified, and are found to the classification highest characteristic index collection of contribution rate；
D. the stereoscopic vision for being suitble to assessment three-dimensional depth movement to cause is focused to find out in characteristic index using grey relational grade analysis
The optimal parameter of fatigue are as follows: central area α, central area α/θ and top area's α/β；
E. the validity of verifying gained optimal parameter.
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Cited By (4)
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| CN110215206A (en) * | 2019-06-12 | 2019-09-10 | 中国科学院自动化研究所 | Stereoscopic display visual fatigue evaluation method, system, device based on EEG signals |
| CN112215057A (en) * | 2020-08-24 | 2021-01-12 | 天津大学 | Electroencephalogram signal classification method based on three-dimensional depth motion |
| CN112568915A (en) * | 2019-09-11 | 2021-03-30 | 中国科学院自动化研究所 | Stereo display visual fatigue evaluation method, system and device based on multi-task learning |
| CN115192043A (en) * | 2022-07-15 | 2022-10-18 | 中山大学中山眼科中心 | Training method and training device for classification model for predicting visual fatigue predictability |
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