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Anthropometry
A.H. Mehrparvar
Occupational Medicine Department
Yazd University of Medical Sciences
Definitions

Anthropology:
The science of human beings

Physical anthropology:
The study of physical characteristics of human beings

Antropometry:
A branch of physical anthropology dealing with body
dimensions and measurements.
Introduction
the science that deals with the
measurement of size, mass, shape, and
inertial properties of the human body
 the measure of physical human traits to:



determine allowable space and equipment size
and shape used for the work
The results are statistical data describing
human size, mass and form.

Considered Factors:






agility and mobility
Age
Sex
body size
Strength
disabilities

Engineering anthropometry:


Application of these data to tools, equipment,
workplaces, chairs and other consumer
products.
The goal:

to provide a workplace that is efficient, safe
and comfortable for the worker
Divisions of anthropometry
Static anthropometry –body
measurement without motion
 Dynamic anthropometry -body
measurement with motion
 Newtonian anthropometry -body
segment measures for use in
biomechanical analyses

Static Anthropometric Measurements
Static = Fixed or not moving
 Between joint centers
 Body lengths and contours
 Measuring tools: Laser (computer),
measuring tape, calipers

Dynamic Anthropometric Measurements

Dynamic = Functional or with movement
 No exact conversions for static to dynamic


Somatography



Kromer (1983) offers some rough estimates for
converting static to dynamic
x e.g. Reduce height (stature, eye, shoulder,
hip, etc.) by 3%.
e.g. A CAD program named SAMMIE
e.g. A virtual reality program named dv/Maniken
Scale model mock-up
Designing for 90 to 95 percent of
anthropometric dimensions.
 Designing for the “average person” is a
serious error and should be avoided
 Designing for the tallest individuals (95th
percentile): leg room under a table
 designing for the shortest individuals (5th
percentile): reach capability.
 Designing “average person”: Supermarket
counters and shopping carts

Design Principles

Designing for extreme individuals
 Design for the maximum population value
when a maximum value must accommodate
almost everyone. E.g. Doorways, escape
apparatus, ladders, etc.


This value is commonly the 95th percentile male
for the target population.
Design for the minimum population value
when a minimum value must accommodate
almost everyone. E.g. Control panel buttons
and the forces to operate them.

This value is commonly the 5th percentile female
for the target population.
Design Principles, continued

Designing for an Adjustable Range
 Designing for the 5th female/95th male of
the target population will accommodate
95% of the population.



95% because of the overlap in female/male body
dimensions (if the male/female ratio is 50/50).
Examples are auto seats, stocking hats
Designing for the Average
 Use where adjustability is impractical, e.g.
auto steering wheel, supermarket check-out
counter, etc.
 Where the design is non-critical, e.g. door
knob, etc.
Designing for Motion
Select the major body joints involved
 Adjust your measured body dimensions to
real world conditions



e.g. relaxed standing/sitting postures, shoes,
clothing, hand tool reach, forward bend, etc.
Select appropriate motion ranges in the
body joints, e.g. knee angle between 60105 degrees, or as a motion envelope.

Avoid twisting, forward bending, prolonged
static postures, and holding the arms raised
7 Steps to Apply Anthropometric Data

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Identify important dimensions, e.g. hip breadth for a
chair seat
Identify user population, e.g. children, women, Iran
population
Determine principles to use (e.g. extremes, average,
adjustable)
Select the range to accommodate, e.g any%, 90%,
95%
Find the relevant data, e.g. from anthropometric data
tables.
Make modifications, e.g. adult heavy clothing adds ~4-6
linear inches.
Test critical dimensions with a mock-up, user
testing, or a virtual model
Variability - three areas
 Anthropometric
data show
considerable variability stemming
from the following sources:
 Poor data
 Interindividual variability
 Intraindividual variability
Poor data
Variability in measurements arise from:
 Population samples
 Using measuring instruments
 Storing the measured data
 Applying statistical treatments

Intraindividual variability
Changes in time
 Size and body segment size, change with
a person’s age -some dimensions increase
while others decrease

Interindividual variability
Individual people differ in:
 arm length
 stature and weight
 therefore population samples are usually
collected from cross sectional studies

Long-term trends

Change in body size by time and in
different generations
Areas of anthropometry

Anthropometry can include just general
measurements of dimension of body segments

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Lengths
Circumferences (girths)
Breadths (width)
depths
Body composition
In biomechanics, mostly concerned with BSIPs
(Body Segment Inertial Parameters)
 Segment mass
 Center of mass
 Moment of inertia
Inertial Parameters

Typical biomechanical analyses require the
following:


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
Segment mass
Location of center of mass
Moment of inertia
These properties of a rigid body are often
referred to as Inertial Parameters
Body Segments

Divide the body into defined rigid bodies, for
which we know or can determine the inertial
properties
Many different ways to divide the body
 Most common (14 segments):

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

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Head
Trunk
Upper arm
Forearm
Hand
Thigh
Shank
Foot
Body Segment Model
Y
(XH,YH)
“Digitizing”
(XK,YK)
(XA,YA)
(XT,YT)
(Xheel, Yheel)
X
Rigid Body Analysis

Rigid Body


A body made of particles (points), the
distances between which are fixed
What is the basic assumption?


The human body segments are rigid links
Therefore human body can be modeled as a
series of rigid bodies (link segments)
Rigid Body Model
The human body is modeled as a linked system of rigid bodies
Air Resistance
Body Weight (N) = mg
Friction
VGRF
Free Body Diagram

Diagram of the essential elements of the
system

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Segments and Axes of interest
Forces acting on the system
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Force Arms (moment arms)

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Effort and resistance forces
Weights of limbs or segments
Line and point of application for each force
Perpendicular distance from line of force
application to axis of rotation
Moment Direction (+/-)
Equilibrium and Static Analysis

System is not moving or acceleration is
constant

Static Equilibrium

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No motion, thus no acceleration
So opposing forces are equal
Rigid Body Diagram

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
Free Body Diagram
Drawing a mechanical picture of the system or
object
Example: Muscle-Lever Diagram
Muscle-Lever Diagram

Muscle Diagram




Bones
Muscles
Motion
Lever Diagram

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Direction
Force (direction)
Axis
Resistance (direction)
Static Analysis

Uses the equations of equilibrium across
various postural positions

Allows the determination of:


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Maximum or minimum muscle forces or
moments for a given posture or joint position
and load
Shear or injurious forces across joints in a given
positional load or task (e.g. lifting)
How body postures affect joint loads
Resultant joint moments and forces
Conditions for Equilibrium
Sum of all horizontal forces must be zero
Fy = 0 Fx = 0
Sum of all vertical forces must be zero
Fz = 0
Sum of all moments about the axis (joint)
in each plane must be zero
M = 0
Free-body Diagram – The System
The Free-body Diagram
Illustration of the essential
elements of a system
Upper Arm Segment
Forearm Segment
More Key Terms

Moment of Inertia

The resistance of a body to rotation about a
given axis
i = np
I = Σ mi · ri2
i=1

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I – moment of inertia about a given axis
np – number of particles making up rigid body
mi – mass of particle
ri – distance between particle and axis
Whole Body Center of Mass

Mass – measure of the amount of matter
comprising an object (kg)
Center of Mass – location for which mass
of a body is evenly distributed
 It is the point about which the sum of
torques is equal to zero
 The point about which objects rotate when
in flight
 Allows simplification of entire mass
particles into a mass acting through a
single point

Center of Mass
 M cm  0
Calculation of Segment Mass
n
m = Σ mi
i=1
m is the total mass
 mi is the mass of a segment or part
 Ex. If we have 3 parts or sections, then

3
m = Σ mi
i=1
= m 1 + m 2 + m3

Mass of segment

mi = ρi·Vi (density times volume)

So…
m=ρ
n
Σ Vi (assumes uniform density)
Multi-segment Systems

x0 = (m1x1 + m2x2 + m3x3) / M

y0 = (m1y1 + m2y2 + m3y3) / M

(x0,y0) is the COM position for the
whole
Mass Moment of Inertia

M = I·α

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M is moment (Nm)
α is the angular acceleration
I is constant of proportionality (inertia)



Resistance to change in angular velocity
Recall: I = m.r2 (r is the moment arm)
I = m1·x12 + m2·x22 + m3·x32
I=


Σ mi·xi2
A mass closer to the axis – Less effect
A mass further from the axis – Greater effect
Segment and WBCOM Relation
♀ ~ 55% BH
♂ ~ 56-57% BH
Benefits of Understanding COM

Parabolic flight of a projectile

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Running performance

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Vertical oscillation of COM
Manipulation of COM for greater impulse

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Jump, aerials, hang time
Long jump, leap
Mechanical Stability

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Base of Support (BOS)
Low COM - STABILITY
High COM - MOBILITY
Stability

Factors that influence stability

Base of Support

Center of Mass Location

Mass
Whole Body Center of Mass

Computation of whole body COM

Where:

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CMWB x or y : Location of whole body COM in x or y
plane
MWB : Mass of whole body
Mi : Mass of ith segment
CM xi or yi : Location of COM of ith segment in x or y
Whole Body Center of Mass
For analysis…the person is often divided
into many parts (each considered a rigid
body)
 We may want to know the center of mass
of the entire system
 Need:



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Masses of each of the segments
Locations of the centers of mass of each
segment
Whole body center of mass position is
equivalent to a weighted mean of all the
Whole Body Moment of Inertia

May have moments of inertia of segments


Want moment of inertia of the whole body
about it’s COM

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Useful when analyzing aerials (flight)
What we need:

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
From tables or whatever
Masses of the segments
Locations of segment COM
Location of whole body (system) COM
Moments of inertia of each segment about the
whole body COM
The moments of inertia can be summed
once they are all about the same axis
Problem

So…how do we determine inertial
parameters of limb segments in a live
subject?

Answer:
Amputate
Determination of COM Position

So, since we can’t just lop off peoples
limbs…

Typically use tables and regression
equations from previous studies:
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Dempster, 1955
Clauser et al., 1969
Chandler et al., 1975
Vaughan et al., 1992
Measures

Mostly simple measures do the trick

Some are more complicated if the
measures serve as a guide for manmachine interface requiring a person to
perform a task

Kinetics and kinematics are typically needed


Get an idea of ROM, height requirements etc.
Masses, moments of inertia and their locations
Locating the COM of a Body Segment
In case you can’t get permission to
amputate…
 Early Methods:

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Suspension
Segmentation (uses tables of regression
equations)
Reaction (balance) Board
Advantages and disadvantages for each?
Methods of Measurement

Model segments as sticks (1D)
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Model segments as rectangles (2D)
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2 measures (length and breadth)
Model segments as geometric solids (3D)
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1 measure (length)
2-3 measures (length and circumference at ends)
Model segments as series of geometric
solids

More measures (segmented lengths and
circumferences)
Suspension


Cut off limb
Sever, Suspend and Swing

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Advantage:


Limb is amputated, weighed (mass), and measured
Hung and swung, an object will behave as a pendulum
The farther away or greater the moment of inertia, the
slower the swing…
Do this enough times and you create data sets that you
can do statistics on and create regression tables
Extremely accurate
Disadvantage:


Potentially painful, as you would have to amputate the
limb
Not to mention the difficulty in getting institutional
permission to cut off peoples legs…
Segmentation

Uses regression equations based on various
segmentation techniques (e.g. cadaver studies
or imaging)

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Use anatomical landmarks to mark segment ends
Measure distance up from origin point (e.g. foot
sole)
Segmentation



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Could involve amputation, but typically just
involves the use of the regression tables
Such tables are created from all kinds of previous
study and data sources:
 Cadaver
 Imaging
 Modeling
Advantages:
 Simple, quick and easy
 Everyone does it (popular and accepted)
Disadvantages:
 Not necessarily accurate to individual or groups
of different gender (e.g. females), ethnicity
(e.g. blacks, Asian), age (e.g. young), or status
Classic Cadaver Studies

Dempster (1955)
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Clauser et al. (1969)
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8 male cadavers
Age (52-83y), Mass (49-72kg), Stature (1.59-1.86m)
Segment COM as % segment length or body height
Segment mass as % body mass
Tissue density
13 male cadavers
Age (28-74y), Mass (54-88kg), Stature (1.62-1.85m)
Segment COM as % segment length or body height
Segment mass as % body mass
Segmental moments of inertia
Chandler et al. (1975)

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6 male cadavers
Age (45-65), Mass (51-89kg), Stature (1.64-1.81m)
Segment COM as % segment length
Segment mass as % body mass
Major Cadaver Studies
Author(s)
Cadavers
(#, gender)
Age
(y)
Body Mass
(kg)
Stature
(m)
Dempster
(1955)
8 male
52 – 83
49 - 72
1.59 - 1.86
Clauser et al.
(1969)
13 male
28 - 74
54 – 88
1.62 - 1.85
Chandler et al.
(1975)
6 male
45 - 65
51 - 89
1.64 - 1.81
* There are other cadaver studies – but these are the classics
Problems with Using Cadaver Data
Storage
 Age range
 Cause of death
 Applicability to live population (especially
sports or athletic populations)
 Applicability to other genders and ethnic
populations
 Variation in dissection techniques

Reaction Board

Scale and Balance (Reaction) Board


Measure and weigh board (upright)
Place board end on pivot (axis) and the other end on the
scale (reaction)


Person lays on board with feet at the axis end and head
towards scale


Get scale reading (reaction force of board)
Get new scale reading (reaction force of board and body)
Calculate COM of person and board from summing the
moments about the axis, with scale reading as a reaction
force

Advantages:




Accurate to your subject
Not too complicated calculations
Not dependent upon cadaver data for density values
Disadvantages:




Need a few people to do it
Equipment required
A bit time consuming
Can’t get small limb masses or COM’s (scale sensitivity)
Reaction Board - Concept
Mass Moment of Inertia

M = I·α



M is moment (Nm)
α is the angular acceleration
I is moment of inertia (constant of
proportionality)



Resistance to change in angular velocity
Recall: I = m·r2 (r is the moment arm)
I = m1·x12 + m2·x22 + m3·x32
I=


Σ mi·xi2
A mass closer to the axis – Less effect
A mass further from the axis – Greater effect
Moments and Center of Mass

Moment of Force

Measure of the tendency of a force to cause
rotation of an object about an axis
M = F · ┴d
F
┴d

Recall: ┴d is called the “moment arm”

Perpendicular distance from the axis of rotation to
the line of force application
Moments and Center of Mass

Positive Moment


Negative Moment


Counterclockwise (CCW) rotation about an axis
Clockwise (CW) rotation about an axis
Static Equilibrium
No rotation about an axis
1.
2.
No moments acting on the object
Minimum of 2 moments, which summed equal 0 Nm.
ΣM=0
Σ F=0
Reaction Board

Based on moments of force in static equilibrium
-+
Ms
MB
Ms
+
+
MB MP
Determination of Whole Body COM
1.
2.
Suspension
Segmentation (Regression Equations)



Imaging techniques (e.g. Zatsiorsky et al.,
1990)
Cadaver experiments (e.g. Dempster, 1955)
Geometric solid modeling (e.g. Hinrichs,
1985)
3.
Reaction Board Technique

Advantages and disadvantages of each
Other BSIP Techniques
1. Simple statistical model (e.g. Dempster,
1955)
2. Complex statistical model (e.g. Hinrichs,
1985)
3. Geometric models (e.g. Hanavan, 1964)
4. Imaging Techniques (e.g. Martin et al.,
1989)
COM Techniques
Based on Cadaver Studies
 Suspension





Amputate limbs
Weigh
Suspend and swing to obtain moment of
inertia about all 3 axes.
Segmentation



Amputate limbs (or somehow isolate limbs –
imaging)
Weigh (mass) and submerge in water (volume
and density)
Balance or hang to determine center of mass
Simple Statistical Model

Dempster (1955) dissected 8 male
cadavers ranging in age from 52 to 83
years

Measures:
1.
Masses of body segments expressed as % of
total body mass

2.
e.g. mass of foot is 1.45% body mass
Location of center of mass expressed as a %
of segment length

e.g. com of thigh is located 43.3% along the length
of the thigh from the proximal end
Complex Statistical Model

Hinrichs (1985) based his equations on
the data from the 6 male cadavers
dissected by Chandler et al. (1975)

Moments of inertia of body segments
computed using regression equations
containing one or more measurements on
segment of interest

e.g. Transverse moment of inertia of shank
about com
Geometric Solid Models

To avoid dependence
on cadaver data, model
segments as series of
geometric solids

Although we are still
dependent upon
cadaver studies for the
tissue density
Geometric Solid Models

So a cylinder is a
simple shape which
can represent the
thigh or foot…
Geometric Solid Models

Hanavan (1964) was one of the first to
develop such a model



Truncated cones (e.g. limbs)
Spheres (e.g. hands)
Cylinders (e.g. trunk)
Hanavan’s Geometric Model

15 segments



Cones
Spheres
Cylinders
Geometric Solid Modeling
Geometric Solid Modeling
Imaging Techniques
Medical imaging
 Basis (theory):




Beam (e.g. radiation) passes through
substance (tissue), beam diminishes in relation
to the density of the tissue
Thus, get shape of the segments and tissues
Techniques:



Gamma mass scanning (slight dose of
radiation)
Computer Tomography (CT)
Magnetic Resonance Imaging (MRI)
Imaging Techniques

Martin et al. (1989) used MRI to
determine the inertial parameters of 8
baboon cadaver arm segments, then
compared these values with physical
measures.
Parameter
SD
Volume (m3 or l)
Density (kg/volume)
Mean
Difference
6.3
0.0
Mass (kg)
COM (m)
I (transverse, kgm2)
6.7
-2.4
4.4
2.8
8.2
3.0
5.0
3.1
Imaging Techniques

Problems:





Equipment not generally available
Expensive
Possible exposure to radiation (e.g. gamma
mass)
Data reduction is time consuming
Advantages:


Subject specific parameters
Equipment is becoming more generally
available
Segment Length

Winter, 1990
% body
height
Segment Mass and COP
Winter, 1990
Segment Mass and COP
Winter, 1990
Segment Mass and COP
Winter, 1990
Important body dimensions