CN103356164A - Measurement system and measurement method for vision health comfort degree - Google Patents
Measurement system and measurement method for vision health comfort degree Download PDFInfo
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Abstract
The invention relates to a measurement system and a measurement method for vision health comfort degree, and provides a set of perfect measurement and evaluation system and method by testing human eye physical indexes and giving objective vision fatigue indexes for the emerging industries of LED illumination, 3-dimensional televisions and the like and the field of vision health. The measurement system comprises a main testing system and a testing environment analog device. The measurement method comprises the following steps: obtaining the objective vision fatigue index by testing multiple terms of human eye physical indexes; establishing mapping relation between multiple terms of complex objective indexes and subjective evaluation according to the characteristics such as self study, organization, self adapting and nonlinear dynamic treatment of a BP neural network so as to establish a BP neural network model based on the human eye physical indexes and related to a subjective fatigue evaluation degree, wherein the objective indexes are used for evaluating vision fatigue, and nonlinear relation exists among the objective indexes; through the establishing of the model, the subjective indexes are replaced by the objective indexes during the impact evaluation of light source on human eye vision health.
Description
Technical field
The present invention relates to a kind of measuring system and measuring method of Vision Health comfort level, by the test to the human eye physical index, provide the objective indicator of visual fatigue, for the new industry such as LED illumination, 3D TV and Vision Health field provide a cover perfect measurement for Evaluation system and method.
Background technology
The people obtain external information 90% from vision, so one of healthy main mechanism of impact illumination derives from the visual channel.Human through long-term evolution, also formed the corresponding with it system that accepts light, experiences light.Light passes pupil, crystalline lens, vitreous body arrival retina, is then received by cone cell and staff cell, converts electrical signal transfer to the visual cortex of brain, becomes visual signal in the brain internal conversion at last.In this process, eyes have occupied extremely important position, become the entrance of reception information.And eyes are very fragile organs, are in for a long time uncomfortable lighting environment, such as inappropriate illumination, inhomogeneous light distribute, strong stroboscopic, dazzle etc., be very serious to the injury of health.The existence that studies show that stroboscopic can cause migraine, discomfort glare can cause visual fatigue etc.Scientific research also shows, uses up improperly the biorhythm that can have influence on the people, may cause the increase of cancer prevalence.Good lighting environment can help people to stablize physiology, psychology and the mental status, increases work efficiency, reduces the generation of mistake and accident.On the contrary, the bad easier fatigue of human eye that not only causes of lighting condition more can increase myopia degree.According to the data show of Chinese Medical Association, rise nearly one times in the adolescents in China child myopia ratio 5 years, Chinese high school student's myopia ratio is up to 74%, and student enrollment's myopia ratio surpassed 80%! And according to the statistical result showed of World Health Organization (WHO), the anisometropia problem has become world's second largest disabling disease.
A kind of quality of illumination had both depended on the reasonability of its economic and technical norms, depended on again its visual effect, and visual fatigue is one of standard of estimating the visual effect of throwing light on.Owing to defining and measuring the difficulty of two aspects, visual fatigue is one of problem of many psychologists avoidances with general fatigue for many years always.Yet fatigue problem, especially sensation-sports fatigue remain the important topic that psychologist must be faced in today.
For visual fatigue, can't directly measure at present and the impact that can only measure it.Tired impact is mainly manifested in three interrelated aspects.Aspect is the variation in the operation, comprises that the decline of quality and quantity, increase and the movable harmony aspect time relationship of each part of operation variability destroys.These can be united and be referred to as " objective fatigue ".Second aspect is physiological variation or infringement, is referred to as " physiological fatigue ".The impact of the third aspect refers to subjective impression or experience, is referred to as " Subjective fatigue ".
Existing research all concentrates on the subjective assessment to visual fatigue, lacks the support of objective indicator, and this has just limited the formulation of evaluating standard of visual fatigue and healthy comfort level and the popularization of authentication checks greatly.
For the problems referred to above, it is auxiliary the present invention is based on subjective assessment, the objective examination is main research method, utilize the cutting edge technology of human eye optometry and opticianry, mode by all kinds of objective indicators of quantitative measurement human eye, make up all kinds of Lighting Luminous Environment and carry out the people because of experiment, on the basis of determining every photoelectric parameter (reducing photoelectricity index related), by strict vision examination, determine tested sample, test as support take subjective assessment and objective indicator again, utilize neutral net that the experimental result of subjective and objective each parameter is comprehensive, construct mathematical model, make up the healthy comfort level of human eye and quantize staging hierarchy, use this system, the people that not only can realize existing all kinds of illuminations and show product can also provide the technical solution of all kinds of Related products based on " people is because of Design of healthy " for enterprise because of healthy comfort level quantitatively evaluating.
The present invention has proposed a kind of measuring system and method for appraiser's optics of the eye physical characteristic and visual fatigue dependency first, for the great development of Vision Health field provides effective means, it also is the very important meaning that played of new forms of energy (LED illumination) and novel industry (3D TV etc.).
Summary of the invention
The invention provides a kind of measuring system and measuring method of estimating the Vision Health comfort level, by the test to the multinomial physical signs of human eye, draw the objective indicator of visual fatigue, rely on the BP neutral net to have self study, tissue, the characteristic such as self adaptation and nonlinear dynamic processing, mapping relations are set up in the objective indicator that has non-linear relation and the subjective assessment of estimating the multinomial complexity of visual fatigue, thereby set up one based on the human eye physical signs BP neural network model relevant with the Subjective fatigue opinion rating, be the LED illumination, the new industry such as 3D TV and Vision Health field provide a cover perfect measurement for Evaluation system and method.
The technical problem to be solved in the present invention is to replace subjectively carrying out light source or display device to the evaluation and test of human eye comfort degree with objective indicator.
For solving the problems of the technologies described above, the invention provides a kind of measuring system of euphoropsia degree, comprise test main system and test lighting environment generator.
According to measuring system of the present invention, described test main system comprises middle control computer, comprehensive optometry platform, wavefront aberrometer and tonometer; Middle control computer is connected with comprehensive optometry platform, wavefront aberrometer and tonometer respectively, is used for the test data of record comprehensive optometry platform, wavefront aberrometer and tonometer; The human eye objective indicator that comprehensive optometry platform is used for obtaining has basic refractive, converge like the spokes of a wheel at the hub and color identification; Wavefront aberrometer is used for obtaining aberration and optical transfer function; Tonometer is used for obtaining intraocular pressure.
According to measuring system of the present invention, described test lighting environment generator comprises individual light sources test lamp box; This individual light sources test lamp case comprises measured light, acrylic board light shield layer, reading area and illumination meter.
According to measuring system of the present invention, described test lighting environment generator comprises the highway street lamp illuminating device; This highway street lamp illuminating device comprises road, street lamp post, street lamp, traffic street lamp indicating card sheet, a slide rail of finishing the expressway graticule; Sliding rail frame can slide between two lamp stands to guarantee the indication card between two lamp stands.
Carry out the method that the Vision Health comfort level is measured according to measuring system of the present invention, wherein measured light is the LED lamp, may further comprise the steps:
According to measuring method of the present invention, before step 1, also comprise the step that makes up the BP neural network model, specific as follows:
Step (a), optimize 40 in tested sample according to step 1, should close one's eyes rest under the environment of darkroom after 20 minutes before each test sample, carry out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as base state;
Step (b), the visual stimulus that tested sample is continued, visual stimulus continues after 90 minutes, carry out user's Subjective fatigue scoring, grading system is divided into Pyatyi, be respectively very comfortable, namely 1 grade, pleasant namely 2 grades, general, namely 3 grades, not too comfortable, namely 4 grades, very uncomfortable, namely 5 grades; The tester records subjects's Subjective fatigue scoring, with 40 people's sample typing master control computer; Carry out simultaneously 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments in this, i.e. basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as state behind the visual stimulus;
Step (c), the input layer of determining neutral net and output layer.Input layer is the changing value Δ P of human eye physical index between twice test, and P represents 6 class physical indexs, i.e. basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, wherein
ΔR＝R2-R1?(1)
ΔCA＝CA2-CA1?(2)
ΔDOC＝DOC2-DOC1?(3)
ΔZ＝Zi2-Zi1(i＝3-35)?(4)
ΔMTF＝MTF2-MTF1?(5)
ΔIOP＝IOP2-IOP1?(6)
Wherein: R1, CA1, DOC1, Zi1, M1, IOP1 represent respectively basic refractive under the base state, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure test result in the formula, R2, CA2, DOC2, Zi2, MTF2, IOP2 distribute basic refractive under the state behind the visual stimulus of representing, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure test result;
As input layer, namely the input neuron number is 38 according to 38 physical index parameters that obtain in formula (1)-(6), with the Subjective fatigue the most output layer of marking, be that the output neuron number is 1, the neuron number n of hidden layer, n=10-30 determines by trial and error procedure;
Step (d), for improving the generalization ability of network model, and eliminate the impact that numerical value differs greatly neutral net is caused, need to carry out normalized to initial data, make data all [0,1] in the interval, input layer and output layer data are processed according to formula (7), and x represents the index of all input layer and output layer in the formula, i.e. R, CA, DOC, Zi, MTF, IOP and subjective scoring grade;
Utilize matlab to set up the three-layer neural network of described 38-n (10-30)-1;
Step (e), with 34 people carry out network simulation make up, with the data of 6 personal accomplishments checking network.If the BP neural network model that makes up satisfies the relative error of training output valve and subjective assessment less than 3%, just can receive this network, and the marking of alternative Subjective fatigue, be used for estimating different visual stimulus signal sources to the impact of Vision Health comfort level.
Carry out the method that the Vision Health comfort level is measured according to measuring system of the present invention, specifically measure the Vision Health comfort level of street lamp, may further comprise the steps:
According to the method for the Vision Health comfort level of measurement TV of the present invention, need that TV is positioned over specific darkroom and watch under the condition and carrying out, may further comprise the steps:
Darkroom illumination≤150lux;
Ratio≤0.02 of the brightness of un-activation telescreen and peak brightness;
When in complete dark room, showing, only show the screen intensity and the corresponding ratio ≈ 0.01 that only shows the screen intensity of peak white level of black level;
Maximum viewing angle with respect to nominal value should be 30 °;
The ratio ≈ 0.15 of the background luminance behind the telescreen and image peak brightness;
According to the method for the Vision Health comfort level of above-mentioned measurement TV of the present invention, wherein tested TV is the 3D TV.
Beneficial effect of the present invention is that the present invention can be used in effective evaluation various types of light sources or display device to the impact of the healthy comfort level of human eye.
Figure of description
Fig. 1 is test evaluation overall system design key diagram
Fig. 2 is individual light sources test lamp box
Fig. 3 is simulation Highway Lighting device
Fig. 4 is BP neural network prediction result and actual value comparative result schematic diagram
The specific embodiment
As shown in Figure 1, measuring system of the present invention comprises: measurement for Evaluation main system (1) and measure analog environmental device (2).
The measurement for Evaluation main system contains in (a) one in control computer, is used for record (b), (c) and (d) test data of three kind equipments; (b) comprehensive optometry platform, the human eye objective indicator (3) that can obtain has 1. basic refractive (Refraction, R), 2. converge like the spokes of a wheel at the hub (Convergence Angle, CA) and 3. color identification (Discrimination of Colour, DOC); (c) wavefront aberrometer, aberration are present in all optical systems, and human eye is a kind of extremely complicated optical system, and there is aberration equally in it.The amphiblestroid image quality of these aberration effects, so that be not a desirable picture point on amphiblestroid corresponding point a bit on the object, but a hot spot of dispersing, consequently whole optogram contrast descends the dimness of vision.The obtainable objective indicator of this instrument has 4. aberration (1th-35th rank, Zernike, Z) and 5. optical transfer function (Modulation Transfer Function, MTF); (d) tonometer can obtain parameter and be 6. intraocular pressure (intraocular pressure, IOP).
Test environment analog (2) can provide multiple lighting condition, for example Interior Illumination Environment, outdoor lighting environment and special lighting condition.Individual light sources test lamp case shown in Figure 2 comprises that (4) are spot, convertible different model (electric filament lamp, LED etc.), illumination and colour temperature, be used for estimating the healthy comfort level of human eye under different model, illumination and the colour temperature, (5) acrylic board light shield layer, can add/reduce the illumination adjusting that acrylic board carries out reading area, (6) reading area, the subjects finishes the visual stimulus (read, read newspaper etc.) of varying strength in reading area, the in addition built-in illumination meter of lamp box can real-time digital shows the illumination of reading area.The volume of this lamp box is 800mm * 1000mm * 1200mm.Outdoor lighting environment shown in Figure 3 comprises (7) roads of finishing the expressway graticule for the Highway Lighting device of simulation, vehicle can be placed on this road, is convenient to the test needs; (8) street lamp post is consistent with street lamp height and the material of actual highway, (9) street lamp, this road-light light-source can be changed different model (sodium vapor lamp, LED etc.), illumination etc., for providing test required lighting environment, (10) be traffic street lamp indicating card sheet, be used for providing visual stimulus, kind contains the common symbol of existing traffic law, (11) be slide rail, frame is between two lamp stands (8), can guarantee that (10) indication card can slide between two lamp stands, sliding speed is adjustable.In the test process, there is the special messenger constantly to change the effectiveness that card guarantees visual stimulus.
To estimate certain LED spot as example, using measuring system of the present invention, to carry out the method that the Vision Health comfort level measures as follows:
At first, under this LED tubular lighting environment, make up the BP neural network model, input layer is that (P represents 6 class physical indexs to the changing value Δ P of human eye physical index between twice test, see formula 1-6), mark as output layer with the Subjective fatigue of tested sample.Carry out light source to human eye vision impact assessment process by what the structure of model can realize that objective indicator replaces subjective index.
The 1st step, by the comprehensive optometry platform (a) in the measurement main system shown in Figure 1 and tonometer (b) human eye of tested sample is carried out the physical index test, the screening vision is between the 0-400 degree, the human eye of intraocular pressure in 11～21mmHg carries out test and the evaluation in later stage, avoids the deviation of the test result that the disease of eye own brings.
Optimize 40 in tested sample, prepare to test.Should close one's eyes rest under the environment of darkroom after 20 minutes before everyone tests, carry out (b), (c) and (d) the 6 class physical indexs tests (R1, CA1, DOC1, Ai1, MTF1, IOP1) of 3 kind equipments, this test result is recorded as base state.
In the 2nd step, the visual stimulus that allows the experimenter continue in lamp box is such as reading, read newspaper etc.Visual stimulus continued after 90 minutes, carried out user's Subjective fatigue scoring, and grading system is divided into Pyatyi, is respectively very comfortable (1 grade), pleasant (2 grades), general (3 grades), not too comfortable (4 grades), very uncomfortable (5 grades).The tester records subjects's Subjective fatigue scoring, with 40 people's sample typing master control computer (1a).
Test simultaneously (b), (c) and (d) the 6 class physical indexs tests (R2, CA2, DOC2, Zi2, MTF2, IOP2) of 3 kind equipments in this, this test result is recorded as state behind the visual stimulus.
Input layer is the changing value Δ P (P represent 6 class physical indexs) of human eye physical index between twice test, wherein
ΔR＝R2-R1?(1)
ΔCA＝CA2-CA1?(2)
ΔDOC＝DOC2-DOC1?(3)
ΔZ＝Zi2-Zi1(i＝3-35)?(4)
ΔMTF＝MTF2-MTF1?(5)
ΔIOP＝IOP2-IOP1?(6)
As input layer, namely the input neuron number is 38 according to 38 physical index parameters that obtain in formula (1)-(6).With the Subjective fatigue the most output layer of marking, namely the output neuron number is 1.The neuron number n (n=10-30) of hidden layer determines by trial and error procedure.
Feedforwadnet is chosen in the order of BP neural network function, the training function is trainFcn, set up aforesaid three layers of BP neutral net, the neural network model of setting up is carried out simulation training with the weights of map network, the output of threshold value, preserve for the network model that trains, when again carrying out other visual stimulus conditioned measurements, only need input 38 physiological parameters in corresponding 6 physical indexs of human eye, just can individually predict that different visual stimulus conditions are to the fatigue loading grade of human eye.
The 3rd step was the generalization ability of raising network model, and eliminated the impact that numerical value differs greatly neutral net is caused, need to carry out normalized to initial data, make data all in [0,1] interval, input layer and output layer data are processed according to formula (7).
Utilize the feedforwadnet order of matlab to set up the three-layer neural network of aforesaid 38-n (10-30)-1, program code can be with reference to as follows:
The P=input layer;
The T=output layer;
% is used for the basis of formation state network take 34 people's data as input
The input of Ptest=verification msg;
The output of Ttest=verification msg;
% is used for the network Output rusults of checking
net＝feedforwardnet(n)；
net＝train(net，p，t)；
y＝net(p)；
perf＝perform(net，y，t)；
y1＝sim(net，Ptest)；
The data of %6 personal accomplishment checking network
figure
plot(1:6，y1)；
hold?on；
plot(1:6，Ttest，’--’)；
hold?off
The 4th step, with 34 people carry out network simulation make up, with the data Ptest of 6 personal accomplishments checking network, the gained the result is illustrated in fig. 4 shown below, solid line be the result that truly gives a mark among Fig. 4, dotted line is the neural network forecast result.
The training output valve of BP neural network model and the relative error of subjective assessment can receive and be used for substituting Subjective fatigue and give a mark less than 3%, have suitable accuracy.
By above-mentioned steps (1-4 step), successfully make up neural network model, can begin to carry out the measurement of certain LED spot, this LED spot is installed in the individual light sources test lamp box shown in Figure 2.
According to the testing process in the 1st step, filter out preferred 10 test effective samples and carry out the test of this LED spot.Each sample before test, should close one's eyes under the environment of darkroom had a rest 20 minutes after, carry out (b), (c) and (d) 6 class physical indexs of 3 kind equipments test (R1, CA1, DOC1, Ai1, MTF1, IOP1), this test result is recorded as base state.
Secondly, the visual stimulus that allows the experimenter continue in lamp box is such as reading, read newspaper etc.Visual stimulus continued after 90 minutes, and the tester carries out (b), (c) and (d) test (R2, the CA2 of 6 class physical indexs of 3 kind equipments to tested sample, DOC2, Zi2, MTF2, IOP2), this test result is recorded as state behind the visual stimulus.
BP neutral net input layer is that the human eye physical index is the changing value Δ P behind the visual stimulus and between base state (P represents 6 class physical indexs), wherein
ΔR＝R2-R1?(1)
ΔCA＝CA2-CA1?(2)
ΔDOC＝DOC2-DOC1?(3)
ΔZ＝Zi2-Zi1(i＝3-35)?(4)
ΔMTF＝MTF2-MTF1?(5)
ΔIOP＝IOP2-IOP1?(6)
In Matlab, the test result of above-mentioned 10 effective samples is imported the BP neural network model that the 3rd step successfully constructed as input layer, calculate the tired score value (Fatigue Score, FS) of 10 samples through network analog, calculate the average of its 10 sample FS
If
Then drawing this LED spot can not exert an influence to the healthy comfort level of human eye within the testing time; If
Then draw this LED spot and within the testing time, can exert an influence to the healthy comfort level of human eye, not this LED spot light source of recommendation.
To estimate certain 3D TV as example, using measuring system of the present invention, to carry out the method that the Vision Health comfort level measures as follows:
At first, should be tested sample arranges following darkroom and watches condition:
Darkroom illumination≤150lux
Ratio≤0.02 of un-activation screen intensity and peak brightness;
When in complete dark room, showing, only show the screen intensity and the corresponding ratio ≈ 0.01 that only shows the screen intensity of peak white level of black level;
Maximum viewing angle with respect to nominal value should be 30 °;
The ratio ≈ 0.15 of the background luminance behind the screen and image peak brightness.
With reference to embodiment 1, the neural network model that makes up take success is as the basis, and the evaluation that begins to carry out this 3D TV is measured, and this 3D TV is positioned over above-mentioned darkroom watches under the condition and testing.
According to the testing process in the 1st step among the embodiment 1, filter out preferred 10 test effective samples and carry out the test of this 3D TV.Each sample before test, should close one's eyes under the environment of darkroom had a rest 20 minutes after, carry out (b), (c) and (d) 6 class physical indexs of 3 kind equipments test (R1, CA1, DOC1, Ai1, MTF1, IOP1), this test result is recorded as base state.
Secondly, the test film source (for example 3D film) that allows tested sample watch the 3D TV to play under watching condition in the darkroom.Visual stimulus continued after 90 minutes, and the tester carries out (b), (c) and (d) test (R2, the CA2 of 6 class physical indexs of 3 kind equipments to tested sample, DOC2, Zi2, MTF2, IOP2), this test result is recorded as state behind the visual stimulus.
BP neutral net input layer is that the human eye physical index is the changing value Δ P behind the visual stimulus and between base state (P represents 6 class physical indexs), wherein
ΔR＝R2-R1?(1)
ΔCA＝CA2-CA1?(2)
ΔDOC＝DOC2-DOC1?(3)
ΔZ＝Zi2-Zi1(i＝3-35)?(4)
ΔMTF＝MTF2-MTF1?(5)
ΔIOP＝IOP2-IOP1?(6)
In Matlab, the test result of above-mentioned 10 effective samples is imported the BP neural network model that the 3rd step successfully constructed as input layer, calculate the tired score value (Fatigue Score, FS) of 10 samples through network analog, calculate the average of its 10 sample FS
If
Then drawing this 3D TV can not exert an influence to the healthy comfort level of human eye within the testing time; If
Then draw this 3D TV and within the testing time, can exert an influence to the healthy comfort level of human eye, do not recommend to watch for a long time this 3D TV.
To estimate certain type highway street lamp as example, using measuring system of the present invention, to carry out the method that the Vision Health comfort level measures as follows:
At first, should be tested sample arranges under the analog shown in Figure 3 and measures.The type highway street lamp is installed on the street lamp shown in Figure 3.
With reference to embodiment 1, take the successful neural network model that makes up as the basis, begin to carry out the evaluation measurement of the type highway street lamp, the type highway street lamp is positioned under the above-mentioned analog condition tests.
According to the testing process in the 1st step among the embodiment 1, filter out preferred 10 test effective samples and carry out the test of the type highway street lamp.Each sample before test, should close one's eyes under the environment of darkroom had a rest 20 minutes after, carry out (b), (c) and (d) 6 class physical indexs of 3 kind equipments test (R1, CA1, DOC1, Ai1, MTF1, IOP1), this test result is recorded as base state.
Secondly, stop to a test sample car at the simulation highway, allow tested sample be sitting in the steering position of sample car, watching the transport information card (such as indication information, road information etc.) that constantly slips between two street lamps under the analog condition, the card frequency of occurrences guarantees 1/minute.Visual stimulus continued after 90 minutes, and the tester carries out (b), (c) and (d) test (R2, the CA2 of 6 class physical indexs of 3 kind equipments to tested sample, DOC2, Zi2, MTF2, IOP2), this test result is recorded as state behind the visual stimulus.
BP neutral net input layer is that the human eye physical index is the changing value Δ P behind the visual stimulus and between base state (P represents 6 class physical indexs), wherein
ΔR＝R2-R1?(1)
ΔCA＝CA2-CA1?(2)
ΔDOC＝DOC2-DOC1?(3)
ΔZ＝Zi2-Zi1(i＝3-35)?(4)
ΔMTF＝MTF2-MTF1?(5)
ΔIOP＝IOP2-IOP1?(6)
In Matlab, the test result of above-mentioned 10 effective samples is imported the BP neural network model that the 3rd step successfully constructed as input layer, calculate the tired score value (Fatigue Score, FS) of 10 samples through network analog, calculate the average of its 10 sample FS
Then drawing the type highway street lamp can not exert an influence to the healthy comfort level of human eye within the testing time; If
Then draw the type highway street lamp and within the testing time, can exert an influence to the healthy comfort level of human eye, do not recommend to watch for a long time this 3D TV.
Except above-mentioned implementation example, the present invention can also have other embodiments.All employings are equal to the technical scheme of replacement or equivalent transformation formation, all drop on the protection domain of requirement of the present invention.
Claims (9)
1. the measuring system of an euphoropsia degree is characterized in that comprising test main system and test lighting environment generator.
2. measuring system according to claim 1 is characterized in that, described test main system comprises middle control computer, comprehensive optometry platform, wavefront aberrometer and tonometer; Middle control computer is connected with comprehensive optometry platform, wavefront aberrometer and tonometer respectively, is used for the test data of record comprehensive optometry platform, wavefront aberrometer and tonometer; The human eye objective indicator that comprehensive optometry platform is used for obtaining has basic refractive, converge like the spokes of a wheel at the hub and color identification; Wavefront aberrometer is used for obtaining aberration and optical transfer function; Tonometer is used for obtaining intraocular pressure.
3. measuring system according to claim 2 is characterized in that, described test lighting environment generator comprises individual light sources test lamp box; This individual light sources test lamp case comprises measured light, acrylic board light shield layer, reading area and illumination meter.
4. measuring system according to claim 2 is characterized in that, described test lighting environment generator comprises the highway street lamp illuminating device; This highway street lamp illuminating device comprises road, street lamp post, street lamp, traffic street lamp indicating card sheet, a slide rail of finishing the expressway graticule; Sliding rail frame can slide between two lamp stands to guarantee the indication card between two lamp stands.
5. utilize measuring system as claimed in claim 3 to carry out the method that the Vision Health comfort level is measured, wherein measured light is the LED lamp, it is characterized in that may further comprise the steps:
Step 1, by comprehensive optometry platform and the tonometer of test in the main system human eye of tested sample is carried out the physical index test, filter out the vision of some between the 0-400 degree, the experimenter of intraocular pressure in 11～21mmHg; Before testing, each experimenter should close one's eyes rest under the environment of darkroom after 20 minutes, carry out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as base state;
Step 2, the visual stimulus that allows each experimenter in individual light sources test lamp box, continue, after visual stimulus continues the scheduled time, the tester carries out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments to each experimenter, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as state behind the visual stimulus;
Step 3, the difference of the test result of state behind above-mentioned base state and the visual stimulus is imported the BP neural network model as input layer, calculate tired score value through network analog, judge the Vision Health comfort level of measured light according to tired mark.
6. method according to claim 5 is characterized in that, also comprises the step that makes up the BP neural network model before step 1, and is specific as follows:
Step (a), optimize 40 in tested sample according to step 1, should close one's eyes rest under the environment of darkroom after 20 minutes before each test sample, carry out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as base state;
Step (b), the visual stimulus that tested sample is continued, visual stimulus continues after 90 minutes, carry out user's Subjective fatigue scoring, grading system is divided into Pyatyi, be respectively very comfortable, namely 1 grade, pleasant namely 2 grades, general, namely 3 grades, not too comfortable, namely 4 grades, very uncomfortable, namely 5 grades; The tester records subjects's Subjective fatigue scoring, with 40 people's sample typing master control computer; Carry out simultaneously 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments in this, i.e. basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as state behind the visual stimulus;
Step (c), the input layer of determining neutral net and output layer.Input layer is the changing value Δ P of human eye physical index between twice test, and P represents 6 class physical indexs, i.e. basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, wherein
ΔR＝R2-R1?(1)
ΔCA＝CA2-CA1?(2)
ΔDOC＝DOC2-DOC1?(3)
ΔZ＝Zi2-Zi1(i＝3-35)?(4)
ΔMTF＝MTF2-MTF1?(5)
ΔIOP＝IOP2-IOP1?(6)
Wherein: R1, CA1, DOC1, Zi1, M1, IOP1 represent respectively basic refractive under the base state, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure test result in the formula, R2, CA2, DOC2, Zi2, MTF2, IOP2 distribute basic refractive under the state behind the visual stimulus of representing, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure test result;
As input layer, namely the input neuron number is 38 according to 38 physical index parameters that obtain in formula (1)-(6), with the Subjective fatigue the most output layer of marking, be that the output neuron number is 1, the neuron number n of hidden layer, n=10-30 determines by trial and error procedure;
Step (d), for improving the generalization ability of network model, and eliminate the impact that numerical value differs greatly neutral net is caused, need to carry out normalized to initial data, make data all [0,1] in the interval, input layer and output layer data are processed according to formula (7), and x represents the index of all input layer and output layer in the formula;
Utilize matlab to set up the three-layer neural network of described 38-n (10-30)-1;
Step (e), with 34 people carry out network simulation make up, with the data of 6 personal accomplishments checking network.If the BP neural network model that makes up satisfies the relative error of training output valve and subjective assessment less than 3%, just can receive this network, and the marking of alternative Subjective fatigue, be used for estimating different visual stimulus signal sources to the impact of Vision Health comfort level.
7. utilize measuring system as claimed in claim 4 to carry out the method that the Vision Health comfort level is measured, specifically measure the Vision Health comfort level of street lamp, it is characterized in that may further comprise the steps:
Step 1, structure neural network model;
Step 2, filter out the tests that some test effective samples participate in the highway street lamps, should close one's eyes rest under the environment of darkroom after 20 minutes before each test sample, carry out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as base state;
Step 3, the simulation highway park one the test sample car, allow tested sample be sitting in the steering position of sample car, watching the transport information card that constantly slips between two street lamps under the analog condition, the card frequency of occurrences guarantees 1/minute, visual stimulus continues after 90 minutes, the tester carries out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments to tested sample, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure,, this test result is recorded as state behind the visual stimulus;
Step 4, the difference of the test result of state behind above-mentioned base state and the visual stimulus is imported the BP neural network model as input layer, calculate tired score value through network analog, judge the Vision Health comfort level of tested street lamp according to tired mark.
8. method of measuring the Vision Health comfort level of TV needs that TV is positioned over specific darkroom and watches under the condition and carrying out, and it is characterized in that may further comprise the steps:
Step 1, the specific darkroom condition of watching be set be:
Darkroom illumination≤150lux;
Ratio≤0.02 of the brightness of un-activation telescreen and peak brightness;
When in complete dark room, showing, only show the screen intensity and the corresponding ratio ≈ 0.01 that only shows the screen intensity of peak white level of black level;
Maximum viewing angle with respect to nominal value should be 30 °;
The ratio ≈ 0.15 of the background luminance behind the telescreen and image peak brightness;
Step 2, structure neural network model;
Step 3, filter out some test effective samples and participate in test, should close one's eyes rest under the environment of darkroom after 20 minutes before each test sample, carry out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as base state;
Step 4, the test film source that allows tested sample watch the 3D TV to play under watching condition in the darkroom, after visual stimulus continues the scheduled time, the tester carries out the 6 class physical indexs test of comprehensive optometry platform, wavefront aberrometer and tonometer 3 kind equipments to tested sample, be basic refractive, converge like the spokes of a wheel at the hub, color identification, aberration, optical transfer function and intraocular pressure, this test result is recorded as state behind the visual stimulus;
Step 5, the difference of the test result of state behind above-mentioned base state and the visual stimulus is imported the BP neural network model as input layer, calculate tired score value through network analog, judge the Vision Health comfort level of tested TV according to tired mark.
9. method according to claim 8, wherein tested TV is the 3D TV.
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