Shape Analysis of 3D Head Scan Data for U.S. Respirator Users
<p/> <p>In 2003, the National Institute for Occupational Safety and Health (NIOSH) conducted a head-and-face anthropometric survey of diverse, civilian respirator users. Of the 3,997 subjects measured using traditional anthropometric techniques, surface scans and 26 three-dimensional (3D...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2010-01-01
|
Series: | EURASIP Journal on Advances in Signal Processing |
Online Access: | http://asp.eurasipjournals.com/content/2010/248954 |
id |
doaj-9442ed0c5745474ea37432e8f04c61dc |
---|---|
record_format |
Article |
spelling |
doaj-9442ed0c5745474ea37432e8f04c61dc2020-11-24T22:50:02ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802010-01-0120101248954Shape Analysis of 3D Head Scan Data for U.S. Respirator UsersSlice DennisEBenson StaceyZhuang ZiqingLynch StephanieViscusi DennisJ<p/> <p>In 2003, the National Institute for Occupational Safety and Health (NIOSH) conducted a head-and-face anthropometric survey of diverse, civilian respirator users. Of the 3,997 subjects measured using traditional anthropometric techniques, surface scans and 26 three-dimensional (3D) landmark locations were collected for 947 subjects. The objective of this study was to report the size and shape variation of the survey participants using the 3D data. Generalized Procrustes Analysis (GPA) was conducted to standardize configurations of landmarks associated with individuals into a common coordinate system. The superimposed coordinates for each individual were used as commensurate variables that describe individual shape and were analyzed using Principal Component Analysis (PCA) to identify population variation. The first four principal components (PC) account for 49% of the total sample variation. The first PC indicates that overall size is an important component of facial variability. The second PC accounts for long and narrow or short and wide faces. Longer narrow orbits versus shorter wider orbits can be described by PC3, and PC4 represents variation in the degree of ortho/prognathism. Geometric Morphometrics provides a detailed and interpretable assessment of morphological variation that may be useful in assessing respirators and devising new test and certification standards. </p>http://asp.eurasipjournals.com/content/2010/248954 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Slice DennisE Benson Stacey Zhuang Ziqing Lynch Stephanie Viscusi DennisJ |
spellingShingle |
Slice DennisE Benson Stacey Zhuang Ziqing Lynch Stephanie Viscusi DennisJ Shape Analysis of 3D Head Scan Data for U.S. Respirator Users EURASIP Journal on Advances in Signal Processing |
author_facet |
Slice DennisE Benson Stacey Zhuang Ziqing Lynch Stephanie Viscusi DennisJ |
author_sort |
Slice DennisE |
title |
Shape Analysis of 3D Head Scan Data for U.S. Respirator Users |
title_short |
Shape Analysis of 3D Head Scan Data for U.S. Respirator Users |
title_full |
Shape Analysis of 3D Head Scan Data for U.S. Respirator Users |
title_fullStr |
Shape Analysis of 3D Head Scan Data for U.S. Respirator Users |
title_full_unstemmed |
Shape Analysis of 3D Head Scan Data for U.S. Respirator Users |
title_sort |
shape analysis of 3d head scan data for u.s. respirator users |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6172 1687-6180 |
publishDate |
2010-01-01 |
description |
<p/> <p>In 2003, the National Institute for Occupational Safety and Health (NIOSH) conducted a head-and-face anthropometric survey of diverse, civilian respirator users. Of the 3,997 subjects measured using traditional anthropometric techniques, surface scans and 26 three-dimensional (3D) landmark locations were collected for 947 subjects. The objective of this study was to report the size and shape variation of the survey participants using the 3D data. Generalized Procrustes Analysis (GPA) was conducted to standardize configurations of landmarks associated with individuals into a common coordinate system. The superimposed coordinates for each individual were used as commensurate variables that describe individual shape and were analyzed using Principal Component Analysis (PCA) to identify population variation. The first four principal components (PC) account for 49% of the total sample variation. The first PC indicates that overall size is an important component of facial variability. The second PC accounts for long and narrow or short and wide faces. Longer narrow orbits versus shorter wider orbits can be described by PC3, and PC4 represents variation in the degree of ortho/prognathism. Geometric Morphometrics provides a detailed and interpretable assessment of morphological variation that may be useful in assessing respirators and devising new test and certification standards. </p> |
url |
http://asp.eurasipjournals.com/content/2010/248954 |
work_keys_str_mv |
AT slicedennise shapeanalysisof3dheadscandataforusrespiratorusers AT bensonstacey shapeanalysisof3dheadscandataforusrespiratorusers AT zhuangziqing shapeanalysisof3dheadscandataforusrespiratorusers AT lynchstephanie shapeanalysisof3dheadscandataforusrespiratorusers AT viscusidennisj shapeanalysisof3dheadscandataforusrespiratorusers |
_version_ |
1725673740841254912 |