Database system. Régis Mollard

Transcription

1 Database system The use of an on-line anthropometric database system for morphotype analysis and sizing system adaptation for different world market apparel sportwear Régis Mollard Paris Descartes University Biomedical Research Center Ergonomics-Behavior & Interactions (EA 4070) Laboratory of Applied Anthropology 45 rue des Saints-Pères PARIS Cedex 06 - FRANCE WEAR Conference - Banff - Canada - July 31/August 1st, 2007

2 WEAR will be a distributed on-line Database system Database 1 Database 3 Database 2 Wear members Web Database n Wear Web End Users Database Local Area Networks

3 Principle of a Database System Data files Additional files 1-D Dictionary of measurements Individual Data (raw data) Aggregated Data (statistics) Synthesis sheets Bibliographical Data Demographic data + Quality Evaluation of Anthropometric Data + xxx xxxx Sorting Query Data processing 3-D + xx Digital man-models Shape analysis Fit tests

4 Databases Applications. Examples of 1-D anthropometric data processing using Databases of WEAR Stature (cm) Buttock - Knee Length (mm) Pilotes Français (hommes) Jeune population militaire 660 ANGLO-SAXON COUNTRIES SCANDINAVIAN COUNTRIES WESTERN EUROPE 560 ORIENTAL COUNTRIES Années Evolution of the stature. Mean values for two french populations from 1940 to Prediction up to Buttock-knee (mm) 460 PROB Eye - Seat Height (mm) Choice of well-adapted measurements Eye seat (mm) Eye height sitting Buttock-knee length 5% min. 5% max. 50% min. 50% max. 95% min. 95% Percentiles max. Choice of typical human body models using bivariate distributions. Example to create small, medium and large digital man models

5 Shape analysis

6 The use of an on-line anthropometric database system for : Example 1 : Morphotypes analysis Survey 1 //// Principal Component Analysis (PCA) & Hierarchical Classification Survey 2 Survey n Example 2 : Sizing system adaptation for different world market apparel sportwear (from France to USA & China for bathing suits, pants, jackets, ) Log values 2,9 3 Bivariate distribution / sizing 2,8 2,7 2,6 2,5 2,4 2,3 2,2 2, Coverage / Fit S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 out Total out S9S S S S S S S S S S min

7 Example 1 : Morphotypes analysis Step 1 //// Choice of a survey Survey 1 Survey 2 Survey n Step 2 Principal Component Analysis (PCA) Step 3 Hierarchical Classification Step 4 Interpretation and Morphotypes

8 Database Query Example using ERGODATA 1 - Shortlisting of Surveys 2 - Search subjects corresponding to criteria 3 - Statistical calculations mean, standard deviation, min, max coefficient of variation (Pearson) percentiles correlations Gauss test contingency table histogram plot of individual data bivariate distributions morphological profile comparison 4 - Save the query All surveys North America + Europe Men, Women, Aged >20 France,...

9 Morphotypes analysis for Females Sample 1 : French Army n = 150 Step 1 : Database 38 measurements 150 subjects Individual Data Step 2 : PCA Eigenvalues and percentages of the variance of the axes. The first two axes explain 66% of the total variance

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

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

12 Morphotypes analysis for Females Sample 1 : French Army n = 150 Step 3 : Hierarchical classification Partition in 8 groups explains 69.7% of the total variance.

13 Morphotypes analysis for Females Sample 1 : French Army n = 150 Step 4 : Morphotypes of the 8 groups G1 G2 G3 G4 G5 G6 G7 G cm cm cm cm cm cm cm cm 64.7 kg 58.4 kg 64.4 kg 73.2 kg 56.7 kg 50.7 kg 53.2 kg 47.1 kg Medium & Large Tall & Wide Small & Slim

14 Morphotypes analysis for Males Sample 2 : French Army n = 275 Step 4 : Morphotypes of the 7 groups G1 G2 G3 G4 G5 G6 G cm cm cm cm cm cm cm 60.9 kg 58.8 kg 66.1 kg 71.8 kg 73.0 kg 77.4 kg 94 kg Small & Slim Tall & Wide

15 Example 2 : Sizing system adaptation for different world market apparel sportwear Step 1 Identify key measurements for garments and convert value in log-value if necessary Step 2 Confirm and/or adjust the existing french sizing for the updated data Step 3 2,9 3 2,8 2,7 2,6 2,5 2,4 2,3 2,2 2, Estimate the percentage of fit Step 4 Adapt french sizing to other populations - USA and China S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 out Total out S9S S S S S S S S S S min

16 Sizing system adaptation Step 1 : Identify key measurements for garments and convert value in log-value if necessary Univariate distribution The Stature and lengths have a gaussian distribution The Weight and some perimeters (waist circumference, ) have not a gaussian distribution Log

17 Sizing system adaptation Step 1 : Identify key measurements for garments and convert value in log-value if necessary Bivariate distribution Values are converted in log when the distribution is not gaussian Mostly the case for weight and related measures (perimeters)

18 Pelvis perimeter (log values) Sizing system adaptation Step 2 : Confirm and/or adjust the existing french sizing for the updated data France - Bathing suits - Women 3 2,9 2,8 2,7 Sizes not adapted 2,6 2,5 2,4 2,3 2,2 2,1 Need to adjust Trunk height (mm)

19 Sizing system adaptation Step 2 : Confirm and/or adjust the existing french sizing for the updated data France - Jackets - Women 3,1 Pelvis perimeter (log values) 3 2,9 2,8 2,7 2,6 2,5 2,4 Creat new sizes Sizes not adapted 2,3 2,2 2, Arm length(mm)

20 Sizing system adaptation Step 4 : Adapt french sizing to other populations - USA - Bathing suits - Women 3,1 2,9 Creat new sizes 2,7 2,5 2,3 2,1 Pelvis perimeter (log values) 1,9 1,7 Need to adjust 1,5 1,5 1,7 1,9 2,1 2,3 2,5 2,7 2,9 3,1 Thorax perimeter (log values)

21 Sizing system adaptation Step 4 : Adapt french sizing to other populations - China - Bathing suits - Women Pelvis perimeter (log values) 3,1 3 2,9 2,8 2,7 2,6 2,5 2,4 2,3 2,2 2 new sizes Delete 6 sizes 2,1 2,1 2,2 2,3 2,4 2,5 2,6 2,7 2,8 2,9 3 Thorax perimeter (log values)

22 Sizing system adaptation Step 4 : Adapt french sizing to other populations - China - Jacket - Men 1400 Pelvis perimeter (log values) Delete 4 sizes Thorax perimeter (mm)

23 Sizing system adaptation Step 4 : Adapt french sizing to other populations - China - Pants - Women 3 2. Adjust the others Pelvis perimeter (log values) 2,9 2,8 1. Delete 4 sizes 2,7 2,6 2,5 2,4 2,3 2,2 3. To creat a new sizing system 2,1 1,3 1,5 1,7 1,9 2,1 2,3 2,5 2,7 2,9 Natural waist perimeter (log values)

24 Synthesis - Projects from manufacturers or apparel industry can be improved 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 the differences 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 quickly and all the data, methods, ergonomic rules, will have been validated by the WEAR group