Fitts

1
Fitts Law

• Rob Diaz-Marino

2
Overview

• The Basics
• Who invented it?
• What does it model?
• How is it used in HCI?
• Fitts Adaptation
• The Formula
• Drawbacks
• A Standardized Test
• An Example
• Synthesis
• Conclusion

3
Who invented it?

• Paul Fitts (in 1954)
• Psychologist at Ohio State University
• US Air Force
• Aviation safety

4
What does it Model?

• Info Capacity of Human Motor system
• Ability to guide pointing device to target
• Coarse movement
• Overshoot / Undershoot
• Adjustment
• Based on Shannons Theorem 17

5
How is it used in HCI?

• Predictive Formula
• Rapid aimed motion with a Pointing Device
• Mouse, trackball, stylus, finger (on touch
  screen) etc.
• Estimates
• Time to acquire target
• Difficulty of acquiring target

6
Shannons Theorem 17

• Formula (From CPSC 441)
• Maximum effective transmission capacity
• Applied in Networking

Capacity Maximum effective transmission
capacity for a medium Bandwidth Physical
transmission capacity Signal Power Strength of
the signal being carried Noise Power Strength
of noise interference over the medium Log base 2
because transmitting binary (2 signal levels 0
and 1)
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Fitts Adaptation

• Human Motor System Medium
• Human Perception Channel
• Target Distance Signal
• Target Width Noise
• Bandwidth Index of Performance
• Log base 2?

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The Formula
Movement Time (s)
(constant) Index of Performance (Time/bit)
Index of Difficulty (bits)
(constant) Minimum reaction time (s)
Amplitude
Width
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Variations
Welford (1960 1968, p. 147)
MacKenzie (1989, p. 324)
10
Amplitude and Width
A
W
11
Amplitude and Width
W
A
12
Amplitude and Width
A
W
13
Drawbacks

• Formula doesnt always work
• Ex. For easy tasks, sometimes MT lt 0
• Not always accurate
• Different people, different bandwidths
• Learning effects

14
Drawbacks (2)

• Different pointing devices, different times
• Mouse vs. Trackball
• Solution
• Adjust with constants a b

15
A Standardized Test
Regression line used on empirical results to
determine a and b.
ISO 9241-9 Picture from Gutwin (2002)
16
An Example

• Which interface is more efficient for browsing?

17
An Example

• Which interface is more efficient for browsing?

18
An Example (2)
W 2cm
W 2cm
A 25cm
From previous experiments with a mouse a
230ms, b 166 ms/bit
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An Example (3)
A 5cm
W 2cm
W 2cm
From previous experiments with a mouse a
230ms, b 166 ms/bit
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An Example (3)

• Difference of 357.3 ms
• Worst case Delete every 2nd photo
• 35.73 sec / 100 photos
• 5 min 57 sec / 1000 photos
• Is redesign worth it?

21
Synthesis

• To reduce target acquisition time
• Decrease target distance
• Increase target size
• Consider direction of approach

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Conclusion

• Cheap quantitative metric
• Judges GUI design efficiency
• Not exact rough estimate
• Applicable to pointing devices
• Models hand-to-eye coordination