Cornell University Ergonomics Web
Cornell University Ergonomics Web
DEA 3250/6510 CLASS NOTES
Anthropometry
Anthropometrics
- measurement of the dimensions of the body and other physical characteristics.
There are two types of measurement: static and dynamic.
1. Static (structural) anthropometry
a. Characteristics - measures distance of bones between joint centers
including some soft tissue measures in contour dimensions (includes the
wobbly stuff that covers our bodies - muscle, fat, skin, bulk). Doesn't
include clothing or packages. Measures refer to a naked person.
b. Birth of static anthropometry - First measurements were done by
a Belgian mathematician (Quetelet) who worked for Napoleon. He was asked
to develop better-fitting uniforms for the troops. He measured chests to
get an idea of standard sizes.
2. Dynamic (functional) anthropometry - distances are measured when
the body is in motion or engaged in a physical activity. It includes
reach (ex. could be arm plus extended torso); clearance (ex. two people
through a doorway); and volumetric data.
3. Distribution of Measurements - Any distribution (set of measurements)
can be represented by three statistics: mean (the average); median (midpoint
at which 50% >, 50%< than that point); and the mode (most frequently
occurring number).
a. Kurtosis - relates to the shape of the distribution. It's important
to plot the data, as it's crucial to know it's shape for analysis. There
are many types of shapes. A "normal distribution" is also known as a Bell curve,
or Gaussian curve (named after Gauss,
a physicist). Other distributions include Bimodal (two peaks), Leptokurtic (thin
peak curve), Platykurtic (flatter, rounder curve), Positive skew (more instances
at the upper extreme of the variable), and Negative skew (more instances
at the lower extreme of the variable).
b. Normal distribution - in a normal distribution all three statistics,
the mean, median, and mode are the same. 68% of values in a normal distribution
are within a standard deviation (SD) of either side of the mean, 95% are
within two SD, and 99% are within 3 SD.
Example: X = 60", SD =4", 56-64"= 2/3 of everyone in the
class
+ 2 SD's, 52-68" = 95% of sample
+ 3 SD's, 42-72" = pretty well covered the sample
c. Coefficient of variation (CV) - useful index of variability of
a dimension. A low value means that the data are normally distributed (<10).
A high value indicates increasing skewness of data.