23/4/19 1

Study Effects that Factors Have On Human`s Vision Capability

Study Effects that Factors Have On Human`s Vision Capability

DOE

JI Xiaocong Huang FeiWang Mingqiang Mei Lin

23/4/19 2

Introduction Introduction

DOE

23/4/19 3

We are thinking about…We are thinking about…

Under what condition can he see it clearly?

23/4/19 4

• Measure the effects of aimed environmental factors on human’s vision – luminance, color, shape and contrast

Objectives of the experimentObjectives of the experiment

preliminary work:• Indentify the response factor: vision ability• Indentify the degrees to which these factors contributeReference:• Based on National standard vision chart - the standard logarithmic visual acuity chart [GB 11533-1989]

23/4/19 5

• Control variables – Screen luminance– Character color & Screen background color– Character shape– Screen contrast – Character shape

Variables(1/3) Variables(1/3)

23/4/19 6

• "held constant" variables– Subjects’ age– Subjects’ vision– Subjects’ health condition– Subjects’ environmental adaptability– Subjects’ visual angle– Illumination of the test environment– Testing time– The interval between vision table and subjects

Variables(2/3) Variables(2/3)

23/4/19 7

• Nuisance factor (units) – Gene – Gender – Psychological state

Variables(3/3) Variables(3/3)

23/4/19 8

• Focus on the environmental factors that affect the vision capability & Ignore the individual differences between anticipants

• Restricted by the experiment conditions, some of the control variables are difficult to adjust.

RestrictionsRestrictions

23/4/19 9

MethodologyMethodology

DOE

23/4/19 10

Analysis of the factors(1/2) Analysis of the factors(1/2)

Two LevelTwo Level

23/4/19 11

Analysis of the factors(2/2) Analysis of the factors(2/2)

23/4/19 12

Analysis of the Response Analysis of the Response

• Based on National standard vision chart - the standard logarithmic visual acuity chart 【 GB 11533-1989 】

• The ability to recognize the different layout (12 degrees )

23/4/19 13

Full Factorial VS Fractional Factorial

Full Factorial VS Fractional Factorial

• Full factorial design – 5 factorials– 2^5=32

• Full factorial design – 5 factorials– 2^5=32

• Full factorial design – 4 factorials– 2^4=16

• Full factorial design – 4 factorials– 2^4=16

• Fractional Factorial – 5 factorials – 2^(5-1)=16

• Fractional Factorial – 5 factorials – 2^(5-1)=16

• Not easy to actualize

• Lead the tiredness

• Not easy to actualize

• Lead the tiredness

• All the factors is important

• All the factors is important

Which one is better??Which one is better??

23/4/19 14

Fractional Factorial DesignFractional Factorial Design

Alias StructureI + A*B*C*D*E

Blocks =A + B*C*D*EB + A*C*D*EC + A*B*D*ED + A*B*C*EE + A*B*C*D

Alias StructureI + A*B*C*D*E

Blocks =A + B*C*D*EB + A*C*D*EC + A*B*D*ED + A*B*C*EE + A*B*C*D

Blocks(Con’t)=A*B + C*D*EA*C + B*D*EA*D + B*C*EA*E + B*C*DB*C + A*D*EB*D + A*C*EB*E + A*C*DC*D + A*B*EC*E + A*B*DD*E + A*B*C

Blocks(Con’t)=A*B + C*D*EA*C + B*D*EA*D + B*C*EA*E + B*C*DB*C + A*D*EB*D + A*C*EB*E + A*C*DC*D + A*B*EC*E + A*B*DD*E + A*B*C

23/4/19 15

• We shall select candidates with almost the same eyesight level, and other gene conditions looking similar.

• We will make some preparation for the experiment to make candidates have similar mental conditions.

Block Block

ONE BLOCK ONE PERSON ONE BLOCK ONE PERSON

23/4/19 16

Methodology sum-upMethodology sum-up

• Two levels fractional factorial design • 5 factorials 2^(5-1)=16 one block one person Factors LOW LEVEL HIGH LEVEL

Color(latter) PURPLE YELLOW

Color(background) BLUE RED

Shape C E

Contrast 30 70

Luminance 50 90

Response 12 DEGREES

23/4/19 17

Preparation & PerformingPreparation & Performing

DOE

23/4/19 18

PreparationPreparation

• Response variableVision Capability

• Known StudyColorInverse colors increase the Vision CapabilityColors with long wavelength decrease the VC

23/4/19 19

PreparationPreparation

• Known StudyShape

Generally, Shape E is easier to identify than C.Contrast

High contrast lead to high visual capacity.Luminance

In a certain range, High luminance level increase the visual capacity.

23/4/19 20

PreparationPreparation

Factor Level CodeNO. Factors Actual Level Coded Level

1 Color(Foreground)

Yellow -1

Purple +1

2 Color(Background)

Red -1

Blue +1

3 Shape C -1

E +1

4 Contrast 30 -1

70 +1

5 Luminance 50 -1

90 +1

23/4/19 21

PreparationPreparation

Held-constant factors

Candidate’s Physical Conditions

Distance from Vision Chart

Light Color & Luminance etc.

23/4/19 22

Experiment PerformingExperiment Performing

Experiment Environment– ZJ12#510A– Vision Chart

• Made by PowerPoint• 8 Versions with different Foreground,

Background color, and Symbol Shape• Presented on the Computer Monitor

in order to change the contrast and luminance

– Distance from Vision Chart: 5 meters.

23/4/19 23

Data AnalysisData Analysis

DOE

23/4/19 24

DATA ANALYSISDATA ANALYSIS5 1

2V

Fractional factorial experiment

Var Factors Actual Level Coded Level

A Luminance 50 -1

90 +1

B Color(Background)

Red -1

Blue +1

C Color(Foreground)

Yellow -1

Purple +1

D Shape C -1

E +1

E Contrast 30 -1

70 +1

23/4/19 25

DATA ANALYSISDATA ANALYSIS5 1

2V

Fractional factorial experiment

Standardized Effect

Perc

ent

50-5-10-15

99

95

90

80

70

605040

30

20

10

5

1

Factor

DE E

NameA AB BC C

D

Effect TypeNot SignificantSignificant

BC

D

C

B

Normal Probability Plot of the Standardized Effects(response is re, Alpha = .05)

Normal probability plot

23/4/19 26

DATA ANALYSISDATA ANALYSIS5 1

2V Fractional factorial experiment

ANOVATerm Effect Coef SE Coef T PConstant 10.1719 0.05842 174.13 0.000Block 1 0.0781 0.10118 0.77 0.444Block 2 -0.1094 0.10118 -1.08 0.285Block 3 -0.2969 0.10118 -2.93 0.005A 0.2187 0.1094 0.05842 1.87 0.068B -1.7813 -0.8906 0.05842 -15.25 0.000C -0.9688 -0.4844 0.05842 -8.29 0.000D 0.5938 0.2969 0.05842 5.08 0.000E 0.0313 0.0156 0.05842 0.27 0.790A*B -0.0313 -0.0156 0.05842 -0.27 0.790A*C -0.0938 -0.0469 0.05842 -0.80 0.427A*D -0.0312 -0.0156 0.05842 -0.27 0.790A*E 0.0313 0.0156 0.05842 0.27 0.790B*C -1.2188 -0.6094 0.05842 -10.43 0.000B*D 0.0937 0.0469 0.05842 0.80 0.427B*E -0.2187 -0.1094 0.05842 -1.87 0.068C*D 0.1563 0.0781 0.05842 1.34 0.188C*E -0.1562 -0.0781 0.05842 -1.34 0.188D*E 0.0312 0.0156 0.05842 0.27 0.790S = 0.467336 R-Sq = 91.15% R-Sq(adj) = 87.62%

23/4/19 27

DATA ANALYSISDATA ANALYSIS5 1

2V

Fractional factorial experiment

Model check

Residual

Perc

ent

1.00.50.0-0.5-1.0

99.9

99

90

50

10

1

0.1

Fitted Value

Resi

dual

12108

1.0

0.5

0.0

-0.5

-1.0

Residual

Fre

quency

0.80.40.0-0.4-0.8

16

12

8

4

0

Observation Order

Resi

dual

605550454035302520151051

1.0

0.5

0.0

-0.5

-1.0

Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

Histogram of the Residuals Residuals Versus the Order of the Data

Residual Plots for re

23/4/19 28

DATA ANALYSISDATA ANALYSIS5 1

2V

Fractional factorial experiment

Further analysis:

Factor A and E are not significant

Ignore A and E,

Three factor two level and two replicates and four blocks full factorial design:

background color

letter color

letter shape

four blocks: four people

5 1

2V 3

2 Full factorial experiment

23/4/19 29

DATA ANALYSISDATA ANALYSISFull factorial experiment

3

2

Standardized Effect

Perc

ent

50-5-10-15

99

95

90

80

70

605040

30

20

10

5

1

Factor NameA BB CC D

Effect TypeNot SignificantSignificant

AB

C

B

A

Normal Probability Plot of the Standardized Effects(response is C8, Alpha = .05)

23/4/19 30

DATA ANALYSISDATA ANALYSISFull factorial experiment

3

2

Term Effect Coef SE Coef T PConstant 10.1719 0.05936 171.35 0.000Block 1 0.0781 0.10282 0.76 0.451Block 2 -0.1094 0.10282 -1.06 0.292Block 3 -0.2969 0.10282 -2.89 0.006B -1.7813 -0.8906 0.05936 -15.00 0.000C -0.9688 -0.4844 0.05936 -8.16 0.000D 0.5938 0.2969 0.05936 5.00 0.000B*C -1.2188 -0.6094 0.05936 -10.27 0.000B*D 0.0937 0.0469 0.05936 0.79 0.433C*D 0.1563 0.0781 0.05936 1.32 0.194B*C*D 0.0312 0.0156 0.05936 0.26 0.793S = 0.474901 R-Sq = 89.24% R-Sq(adj) = 87.21%

23/4/19 31

DATA ANALYSISDATA ANALYSIS3

2 Full factorial experiment

Residual

Perc

ent

10-1

99.9

99

90

50

10

1

0.1

Fitted Value

Resi

dual

12111098

1.0

0.5

0.0

-0.5

-1.0

Residual

Fre

quency

1.00.50.0-0.5-1.0

16

12

8

4

0

Observation Order

Resi

dual

605550454035302520151051

1.0

0.5

0.0

-0.5

-1.0

Normal Probability Plot of the Residuals Residuals Versus the Fitted Values

Histogram of the Residuals Residuals Versus the Order of the Data

Residual Plots for C8

23/4/19 32

DATA ANALYSISDATA ANALYSIS3

2 Full factorial experiment

Me

an

of

C8

1-1

11.0

10.5

10.0

9.5

1-1

1-1

11.0

10.5

10.0

9.5

B C

D

Main Effects Plot (data means) for C8

C

Me

an

1-1

11.5

11.0

10.5

10.0

9.5

9.0

8.5

8.0

B-11

Interaction Plot (data means) for C8

23/4/19 33

DATA ANALYSISDATA ANALYSIS3

2 Full factorial experiment

10.17 0.89 0.48 0.30 0.61VC BC LC Shape BC LC

From the analysis, we get such conclusion:

For background color: warm color (red) will lead to better performance.

For letter color: warm color (yellow) will lead to better performance.

For color interaction: inverse color will to better performance

• blue/ yellow and red/ purple is better than blue/purple and red/yellow

For letter shape: E shape will lead to better performance than C shape.

For other factors: under given condition not significant.

23/4/19 34

DATA ANALYSISDATA ANALYSIS

• Check list to improve vision capability:– Red background color, purple letter color, E shape– Inverse color pairs do better– Warm color improve performance

23/4/19 35

TO BE IMPROVEDTO BE IMPROVED

• Why other factors are not significant?– luminance and

contrast– caused by device

• Response level is not very sensitive.

• Design method– not linear, center points?– not serious.

1

C8

8

0

9

C

10

11

-10 -1

1B

Hold ValuesD -1

Surface Plot of C8 vs C, B

23/4/19 36

ReferenceReference 对比度因素对彩色 CRT 视觉工效的影响 曹立人、朱祖祥 人类工效学 1995 第 1 卷第 1 期 VDT 界面颜色视觉工效：色调因素对视觉绩效的影响 张德乾 张智君 心理科学 2008 31(2)

标准化 LogMAR 视力表与 C 形对数视力表一致性与稳定性分析

李刚等， 海军总医院学报 2007 20 （ 4 ） 影响视力检测的因素 刘建军，中国眼镜科技杂志 2005.7

正常人亮暗背景下不同对比度的视力变化 史胜 柳林， 第二军医大学学报 2007 28 （ 7 ）

23/4/19 37

AcknowledgementAcknowledgement

Dr. Kaibo Wang TA Song XU People involved in the experiment Other team who help us in project

23/4/19 38

Thank You ! Thank You !