Database system

The use of an on-line anthropometric database system for morphotype analysisand

sizing system adaptation for different world market apparel sportwear

WEAR Conference- Banff - Canada- July 31/August 1st, 2007

Régis Mollard

Paris Descartes UniversityBiomedical Research Center

Ergonomics-Behavior & Interactions (EA 4070)Laboratory of Applied Anthropology

45 rue des Saints-Pères75270 PARIS Cedex 06 - FRANCE

Local Area Networks

Web

Web

Wear End Users

Database 1

Database n

Database 3

Database 2

WEAR will bea distributed on-line Database system

Wear members

Database

Principle of a Database System

Synthesis sheets

Dictionary ofmeasurements

Aggregated Data(statistics)

Individual Data(raw data)

Bibliographical Data

1-D

3-D

Demographic data+

Quality Evaluation of

Anthropometric Data+ xxx xxxx

Data files

Additional files

Data processingDigital man-models Shape analysis Fit tests

+xx

SortingQuery

Pilotes Français

Jeune populationmilitaire

Années

(hommes)

Stature (cm)

1940 1950 1960 1970 1980 1990 2000 2010 2020

Evolution of the stature. Mean values for two french populations from 1940 to 1991.

Prediction up to 2020.

660 760 860 960460

560

660

Buttock - Knee Length (mm)

Eye - Seat Height (mm)

ANGLO-SAXON COUNTRIES

SCANDINAVIAN COUNTRIES

WESTERN EUROPE

ORIENTAL COUNTRIES

PROB. 05

Choice of well-adapted measurements

.

Eye height sittingButtock-knee length

Percentiles5%min.

5%max.

50%min.

50%max.

95%min.

95%max.

Buttock-knee (mm)

Eye seat(mm)

661.7

624.0

586.3

548.5

510.8

473.1

677.

9

728.

0

778.

0

828.

0

878.

1

928.

1

Choice of typical human body models using bivariate distributions.Example to create small, medium and large digital man models

Databases ApplicationsExamples of 1-D anthropometric data processing

using Databases of WEAR

Shape analysis

Survey 2

Survey 1

Survey n

//// Principal Component Analysis (PCA) &Hierarchical Classification

The use of an on-line anthropometric database system for :

Example 1 : Morphotypes analysis

Example 2 : Sizing system adaptation for different world market apparel sportwear(from France to USA & China for bathing suits, pants, jackets,…)

22,12,22,32,42,52,62,72,82,93

500 550 600 650 700 750 800

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 out Totalout 1 6 3 13 14 18 55S9S12 1 2 8 20 32 16 6 2 87S8 1 2 7 37 93 70 31 9 3 253S7 1 2 9 23 101 226 208 73 28 4 675S6 2 5 34 142 316 445 162 37 8 1 1152S5 3 14 44 240 493 720 368 94 15 2 1 1994S4 2 7 33 137 509 767 453 169 25 5 5 0 2112S3 1 8 75 219 499 363 171 62 6 3 2 1 1410S2 3 12 69 161 217 117 88 17 8 2 1 695S1 0 12 47 96 157 69 21 16 4 1 423S min 1 6 37 49 21 6 2 2 1 125

7 48 278 713 1687 1983 1881 1351 627 241 105 37 23 8981

Coverage / FitBivariate distribution / sizing

Log values

• Choice of a survey

Step 1

• Principal Component Analysis (PCA)

Step 2

• Hierarchical Classification

Step 3

• Interpretation and Morphotypes

Step 4

Example 1 : Morphotypes analysis

Survey 2Survey 1 Survey n

////

1 - Shortlisting of Surveys

2 - Search subjects corresponding to criteria

3 - Statistical calculationsmean, standard deviation, min, maxcoefficient of variation (Pearson)percentilescorrelationsGauss testcontingency tablehistogramplot of individual databivariate distributionsmorphological profilecomparison…

4 - Save the query

Men, Women, Aged >20France,…...

All surveysNorth America + Europe

Example using ERGODATA

Database Query

Sample 1 : French Army 1990 - n = 150

Step 1 : Database

38 measurements

150 subjects

Step 2 : PCA

Eigenvalues and percentages of the variance of the axes.

The first two axes explain 66% of the total variance

Morphotypes analysis for Females

Individual Data

Step 2 : PCA

21 measurements explain 65.8% of the variance of the axis 1.

The coordinates of the measurements on axis 1 are all positive. Axis 1 is a « size factor »

Step 2 : PCA

16 measurements explain 65.2% of the variance of the axis 2.

In axis 2, there is an opposition between height and width measurements

Sample 1 : French Army 1990 - n = 150Morphotypes analysis for Females

Step 2 : PCA

28 subjects explain 66.2% of the variance of the axis 1.

In axis 1, there is an opposition between Small&Slim and Tall&Wide

Step 2 : PCA

35 subjects explain 69.1% of the variance of the axis 2.

In axis 2, there is an opposition between Small&Wide and Tall&Slim

Sample 1 : French Army 1990 - n = 150Morphotypes analysis for Females

Step 3 : Hierarchical classification

Partition in 8 groups explains 69.7% of the total variance.

Sample 1 : French Army 1990 - n = 150Morphotypes analysis for Females

G1 G2 G3 G4 G5 G6 G7 G8

161.7 cm

64.7 kg

155.9 cm

58.4 kg

168.3 cm

64.4 kg

172.2 cm

73.2 kg

163.4 cm

56.7 kg

161.7 cm

50.7 kg

167.4 cm

53.2 kg

153.7 cm

47.1 kg

Step 4 : Morphotypes of the 8 groups

Sample 1 : French Army 1990 - n = 150

Small & Slim

Tall & Wide

Morphotypes analysis for Females

Medium & Large

Step 4 : Morphotypes of the 7 groups

Sample 2 : French Army 1990 - n = 275

Small & Slim

Tall & Wide

167.6 cm

60.9 kg

174.0 cm

58.8 kg

177.6 cm

66.1 kg

169.2 cm

71.8 kg

176.1 cm

73.0 kg

182.6 cm

77.4 kg

179.9 cm

94 kg

G1 G2 G3 G4 G5 G6 G7

Morphotypes analysis for Males

• Identify key measurements for garments and

convert value in log-value if necessary

Step 1

• Confirm and/or adjust the existing

french sizing for the updated data

Step 2

Step 3

Step 4

• Estimate the percentage of fit

• Adapt french sizing to other

populations - USA and China

Example 2 : Sizing system adaptationfor different world market apparel sportwear

22,12,22,32,42,52,62,72,82,93

500 550 600 650 700 750 800

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 out Totalout 1 6 3 13 14 18 55S9S12 1 2 8 20 32 16 6 2 87S8 1 2 7 37 93 70 31 9 3 253S7 1 2 9 23 101 226 208 73 28 4 675S6 2 5 34 142 316 445 162 37 8 1 1152S5 3 14 44 240 493 720 368 94 15 2 1 1994S4 2 7 33 137 509 767 453 169 25 5 5 0 2112S3 1 8 75 219 499 363 171 62 6 3 2 1 1410S2 3 12 69 161 217 117 88 17 8 2 1 695S1 0 12 47 96 157 69 21 16 4 1 423S min 1 6 37 49 21 6 2 2 1 125

7 48 278 713 1687 1983 1881 1351 627 241 105 37 23 8981

Step 1 : Identify key measurements for garments and convert value in log-value if necessary

Sizing system adaptation

Univariate distribution

The Stature and lengths have a gaussian distribution

The Weight and some perimeters (waist circumference,…) have not a gaussian distribution

Log

Step 1 : Identify key measurements for garments and convert value in log-value if necessary

Sizing system adaptation

Bivariate distribution

Values are converted in log when the distribution is not gaussianMostly the case for weight and related measures (perimeters)

Step 2 : Confirm and/or adjust the existing french sizing for the updated data

Sizing system adaptation

France - Bathing suits - Women

2

2,1

2,2

2,3

2,4

2,5

2,6

2,7

2,8

2,9

3

500 550 600 650 700 750 800

Trunk height (mm)

Pel

vis

peri

met

er (

log

valu

es)

Sizes notadapted

Need to adjust

Step 2 : Confirm and/or adjust the existing french sizing for the updated data

Sizing system adaptation

France - Jackets - Women

Sizes notadapted

Creat new sizes

2,1

2,2

2,3

2,4

2,5

2,6

2,7

2,8

2,9

3

3,1

420 470 520 570 620 670

Arm length(mm)

Pel

vis

peri

met

er (

log

valu

es)

1,5

1,7

1,9

2,1

2,3

2,5

2,7

2,9

3,1

1,5 1,7 1,9 2,1 2,3 2,5 2,7 2,9 3,1

Pel

vis

peri

met

er (

log

valu

es)

Thorax perimeter (log values)

Creat new sizes

Step 4 : Adapt french sizing to other populations -Sizing system adaptation

USA - Bathing suits - Women

Need to adjust

2,1

2,2

2,3

2,4

2,5

2,6

2,7

2,8

2,9

3

3,1

2,1 2,2 2,3 2,4 2,5 2,6 2,7 2,8 2,9 3

Pel

vis

peri

met

er (

log

valu

es)

Thorax perimeter (log values)

Delete 6 sizes

Step 4 : Adapt french sizing to other populations -Sizing system adaptation

China - Bathing suits - Women

2 new sizes

600

700

800

900

1000

1100

1200

1300

1400

700 800 900 1000 1100 1200 1300 1400 1500

Thorax perimeter (mm)

Pel

vis

peri

met

er (

log

valu

es)

Delete 4 sizes

Step 4 : Adapt french sizing to other populations -Sizing system adaptation

China - Jacket - Men

Step 4 : Adapt french sizing to other populations -Sizing system adaptation

China - Pants - Women

1. Delete 4 sizes

2,1

2,2

2,3

2,4

2,5

2,6

2,7

2,8

2,9

3

1,3 1,5 1,7 1,9 2,1 2,3 2,5 2,7 2,9

Natural waist perimeter (log values)

Pel

vis

peri

met

er (

log

valu

es)

2. Adjust the others

3. To creat a new sizing system

Synthesis

- Projects from manufacturers or apparel industry can beimproved using an on-line database system as WEAR

- From classical 1-D values as well as 3-D surface data extracted from different surveys it is possible to identify thedifferences of morphology according to the needs expressed in projects : design of equipments (mask, helmet, goggles,…), garments or workplaces,…..

Using WEAR database system,these results will be obtained very quicklyand all the data, methods, ergonomic rules, …will have been validated by the WEAR group