Ergonomics

1. ERGONOMICS
Milind A. Pelagade

2. • “Ergonomics is an applied science concerned with the design
of workplaces, tools, and tasks that match the physiological,
anatomical, and psychological characteristics and capabilities
of the worker.” Vern Putz-Anderson
• “The Goal of ergonomics is to ‘fit the job to the person,’
rather than making the person fit the job.” Ergotech
• “If it hurts when you are doing something, don’t do it.” Bill
Black
What is Ergonomics?

3. • Dates back to Ramazzini 1700’s
• Gained significance during WWII for airplane
cockpit layout
• Progressed slowly until the 80’s and 90’s with
the advent of the computer and more efficient
workplace design
• Now, guidelines are in place and greater use
of technology
Evolution of Ergonomics

4. Why do we care about Ergonomics?

6. MSDs
Contact with Objects
Transportation Related
Falls
All Other
Workplace Violence
Source: Bureau of Labor Statistics Annual Survey, 1996
MUSCULOSKELATAL DISORDERS
(MSDS)
REPRESENT 1 IN 3 LOST TIME INJURIES

7. TYPES OF INJURIES
• Muscle pain
• Joint pain
• Swelling
• Numbness
• Restricted motion
• Repetitive stress injury
• Repetitive motion
injury
• Cumulative trauma
disorder
• Musculoskeletal
disorder

8. TARGET REGIONS
• Back
• Upper extremities
• Lower extremities

9. 0 2000 4000 6000 8000 10000
MSDs of the Back
Upper Extremity
MSDs
Average Claim
Average Costs per Claim ($)
MSDS COST TWICE THE AVERAGE
WORKERS’ COMPENSATION CLAIM
Source: Workers’ Compensation data from Insurance Companies 1993

10. METHODS AND TOOLS IN ERGONOMICS
The study of measurement of human body is called anthropometry.
Product design must consider: ease of use, comfort and safety in use
Optimization for ergonomics  understanding how human body works
Design parameters = f( physical measurement)
e.g. Chair seat height
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
Human size variations  need to know the statistics of anthropometric data

11. ERGONOMICS:METHODOLOGY
1. Optimal product is designed based on anthropometric measurements;
2. Statistical variations of expected users are estimated;
3a. Design is modified to allow critical parameters to be adjusted by user
so as to ‘fit’ the individual need
3b. Size variations are provided to cover estimated market (e.g. shoe sizes)
or

12. DESIGN PRINCIPLES AND RULES
OF THUMB
• Provide Adequate Space to Turn the Whole Body
• Do Not Reach Behind
• Avoid Extremes of Joint Movement
• Avoid Postural Extremes
• Allow Natural, But Changing Postures
• Avoid Static Loading of Muscles
• Preserve the Natural Curves of the Spine

13. DESIGN PRINCIPLES
• Apply Force Dynamically, Conserve Momentum
• The Lower the Reach Target, The Better the Shoulder Posture
• Work Should Be 2 - 4 Inches Below Elbow Height, In General
• Do Not Lift the Elbow
• If Workers Must Reach Up and Out, Keep the Reach Below
Heart Level
• Pivot Movement About the Elbow
• Keep Arm Motions Within the “Normal” Working Area

14. DESIGN PRINCIPLES
• Apply Force Dynamically, Conserve Momentum
• The Lower the Reach Target, The Better the Shoulder Posture
• Work Should Be 2 - 4 Inches Below Elbow Height, In General
• Do Not Lift the Elbow
• If Workers Must Reach Up and Out, Keep the Reach Below
Heart Level
• Pivot Movement About the Elbow
• Keep Arm Motions Within the “Normal” Working Area

15. DESIGN PRINCIPLES
• Give Support To the Body
• Avoid Contact Stresses
• Reduce Repetition (enlarge jobs, rotate, mechanize)
• Reduce Force
• Power With Motors - Not With Muscles
• Avoid Vibration - Especially Resonate Frequency Ranges

16. Ergonomics
Focus:
Interaction of humans with “devices”
Objective:
To understand, evaluate, and thereby, to improve
the interface between the human and the device
Ergonomics == Human Factors

17. Outline
1. Examples of product design related to ergonomics issues
2. Case Study: digital images and JPEG
3. Methodology and tools useful for HF

18. Example 1. Office desk and Chair
Question: How do we decide the height of the desk?
Depends on:
(a) the height of the chair
(b) the size of the person who will use them
…

19. Example 1. Chair ergonomics..
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
(i) Seat pan length
calf clearance (> 5cm) to 95% women
(ii) The chair height
contact lower thigh with both feet on floor
(iii) The seat pan angle: ± 6
(v) Backrest lumbar support
~15-25 cm above seat level
(iv) The arm rests height  elbow height at rest

20. Example 1. Chair ergonomics...
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
(i) Seat pan length: calf clearance (> 5cm) to 95% women
(ii) The chair height: contact lower thigh with both feet on floor
IMPLICATIONS
1. Need for adjustability
2. Design of a “good” chair depends on the statistics of the users

21. Example 1. Chair ergonomics – user statistics
Design of a “good” chair depends on the statistics of the users
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
USA Germany Japan Netherlands
Males 175.5 174.5 165.5 182.5
Females 162.5 163.5 153.0 169.6
Problem 1. What statistics are sufficient?
Problem 2. How to collect such statistics?
Problem 3. Statistics are time dependent:
e.g. height of urban Chinese males: increased by 6 cm over the last 20 yrs

22. Example 2. Keyboard design
Extended periods of use of a computer in the wrong posture
 repetitive stress injury (RSI)

23. Example 2. Keyboards: Carpal Tunnel Syndrome
why
compression of the median nerve as it enters the hand.
symptoms
numbness of thumb and fingers,
pain along the median nerve including hand, wrist, elbow,
weakness of thumb.
treatment
rest, surgery
main cause
flexed or extended wrists when keying!

24. Example 3. How to turn on the shower
Pull down this ring to turn shower on
tub-faucet
Non-intuitive design  wasted time/user-discomfort

25. Example 4. Toilet flush (airport)
Non-intuitive design  discomfort (for next user?!)

26. Example 5. Is the water too hot? Too cold?

27. Ergonomics
(i) Understanding of human physiology
(ii) Understanding of human psychology
(iii) Statistical data about populations
Goal:
-- Improve design (more efficient)
-- Improve design (safety, comfort)

28. Ergonomics Case Study: Improve design
Digital Image Files
What is the data composed of ? The “RGB-pixel model”
Digital Cameras (digicams)  pictures in a digital “memory”

29. Digital image files: pixels
An image of a lion fish
What is the image made of ?

30. Digital image files: pixels
4x
4x
4x
4x
pixel
PICture ELements

31. Digital image files: The RGB model
What is a color?
 Store the wavelength, intensity at each pixel
Problem ? (Technical: how to display?)
The primary color theory: any color  combination of primary colors (R, G, B)
 at each pixel, decompose into primary color values, store R, G, B.

32. Digital image files: The RGB model
R = Red level: 8 bit number = 1 byte
G = Green level: 8 bit number = 1 byte
B = Blue level: 8 bit number = 1 byte
Original lionfish file: 1920x2560 = 4,915,200 pixels ( 5 Megapixel digicam)
1 Byte per color per pixel  4,915,200 x 3 x 1= 14,745,600 ~= 15 Mbytes
PROBLEMS:
1. Large memory requirement
2. Slow transfer speed
 need for COMPRESSION

33. Digital Image Files: compression
Strategy 1. Compress data without losing any information
LOSSLESS compression  No need to understand human vision
Example: run-length-encoding
raster model: each pixel: 0 or 1
run-length-encoding: 0203,1403…,
203x191 pixels

34. Digital Image Files: compression
How we compress image files depends on how we “see” images
 Understanding of human vision
 more efficient compression technique
Strategy 2. Compress data by throwing away parts that we cannot see
 Needs a good understanding of human vision

35. Digital Image Files: compression
Uncompressed: BMP (bitmap) 14 MByte
“Lossy” compression: JPG (JPEG)
High quality 3.67 MByte
0.8 quality 0.83 MByte
0.6 quality 0.5 MByte
0.2 quality 0.2 MByte
Lossless compression: PNG 7.9 MByte
http://iesu5.ieem.ust.hk/dfaculty/ajay/courses/ieem101/lecs/hf/lionfish.html

36. JPG: How do we “see”
Do you believe what you see?
The Koffka ring

37. JPG: How do we “see”..
Do you believe what you see?

38. JPG: How do we “see”…
Do you believe what you see?

39. JPG: How do we “see” -- the eye
RODS: scotopic vision (in dark)
only ‘on’ in darkness
only distinguish “lightness”
CONES: photopic vision

40. JPG: How do we “see” -- the eye..
Trichromacy theory:
different intensities of R- G- B- cones allows brain to “estimate”
frequency of the spectral light striking a zone

41. JPG: How do we “see” -- the eye...
Hue discrimination:
ability to distinguish between two different wavelength’s of light
Lightness discrimination:
ability to distinguish between two different levels of “lightness”
Lightness ~~ grey level
Lightness discrimination is MUCH more sensitive than Hue discrimination
Reasons:
(a) lightness is estimated by (R+G) response of cones, and also from RODS
(b) many more rods than cones

42. JPG: How do we “see” -- the eye….
Weber’s law:
Our ability to discriminate “levels of lightness” depends n the ratio of lightness
Shades that are in geometric series “look” equally spaced in lightness.
arithmetic geometric

43. JPG: How do we “see” -- the eye…..
Hue discrimination vs Lightness discrimination
ncycles
n cycles

both patterns are n/ cycles per degree
eye
ncycles
n cycles

both patterns are n/ cycles per degree
eye

44. JPG: How to eliminate what we cannot see?
1. Intensity changes are much more significant than hue changes
2. Intensity change steps are logarithmic
PROBLEM: Technically, it is easier to handle R- G- B- shades
Why ?
(a) Recording instruments (digicams) sensors can sense “colors”
(b) Display instruments can handle RGB values better

45. JPG: How to eliminate what we cannot see..
Converting R G B  Y Cb Cr
Luminance
(lightness)
Chrominance
(chroma) components
must be invertible mapping
Y
Cb
Cr
0.299 0.587 0.114
-0.169 -0.331 0.5
0.5 -0.419 -0.0813
R
G
B
=

46. JPG: How to eliminate what we cannot see…
Y
Cb
Cr
0.299 0.587 0.114
-0.169 -0.331 0.5
0.5 -0.419 -0.0813
R
G
B
=
JPEG compression:
Step 1. Convert RGB data into YCbCr data
Step 2. Sub-sample and quantize Cb and Cr data
Step 3. Compress resulting stream (run-length encoding)
file-size reduction
Higher compression: Step 2  sub-sample more, sub-sample Y also

47. JPG: Details -- How to Sample, Sub-sample?
Break the image into “tiles” of NxN pixels.
Store data of each tile
8
10 6
4 7
7 7
7
Example:
2x2 tile: 4 values  average = 7  combine tiles into ‘block’ with value 7.

48. JPG: Details -- How to Sample, Sub-sample..
Sub-sampling and quantization basics
-2
-1
0
1
2
3
4
5
0 2 4 6 8
y1=2
y2=cos(x)
y3=.5cos(2x)
y4=.25cos(4x)
y5=.125cos(8x)
T=y1+..+y5
T2=y1+..+y4
How Fourier analysis works for 1-D functions

49. JPG: Details -- The Discrete Cosine Transform
DCT function:












 




)2/1(cos)2/1(cos),(4),(
1
0
1
0
j
n
q
i
n
p
jiAqpf
n
i
n
j

8x8 pixel blocks
rows
0
1
…
7
columns: 0 1 … 7

50. DCT
DCT
DCT
Quantization
(Larger lookup)
Quantization
(Sub-sampled)
Quantization
(Sub-sampled)
run-length-encoding
(lossless compression)
JPEG
JPG: Details -- Quantization and encoding

51. JPG: Conclusions
1. Understanding of human sensory system is important for
better product designs
2. Levels of adjustability useful for variations among users
-- older person with poor sight might prefer higher compression
NOTE:
You don’t need to know details of DCT, and the exact mathematics
of the transformation
Important ideas:
sub-sampling: ignore some data, or replace multiple values by the average
quantization: instead of storing exact value, round up/down to nearest step

52. Methods and tools in Ergonomics
The study of measurement of human body is called anthropometry.
Product design must consider: ease of use, comfort and safety in use
Optimization for ergonomics  understanding how human body works
Design parameters = f( physical measurement)
e.g. Chair seat height
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
LUMBAR SUPPORT
SEAT PANCHAIR HEIGHT
CALF CLEARANCE
FOOT REST
Human size variations  need to know the statistics of anthropometric data