Human factors in mobile systems Lin Zhong ELEC424, Fall 2010.

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Human factors in mobile systems Lin Zhong ELEC424, Fall 2010

Transcript of Human factors in mobile systems Lin Zhong ELEC424, Fall 2010.

Page 1: Human factors in mobile systems Lin Zhong ELEC424, Fall 2010.

Human factors in mobile systems

Lin ZhongELEC424, Fall 2010

Page 2: Human factors in mobile systems Lin Zhong ELEC424, Fall 2010.

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Outline

• Psychology theories for mobile HCI

• Human limits

• Human factors and energy efficiency

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Model Human Processor

Cognitive process

Perceptual process

Motor process

Model Human Processor: Card, Moran & Newell’83

Three processes involved in the user reaction to a computer

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Perceptual process• Fixations and saccades– Fixation: information absorbed in

the fovea (60ms)– Saccades: quick movements

between fixations (30ms)– Each GUI object requires one

fixation and one saccade• Rauding rate– Raud: read with understanding– 30 letters/second (Carver, 1990)

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Cognitive process

• Hick-Hyman Law– N distinct and equally possible choices

• Applicable only to simple cognitive tasks– Selection: menu, buttons, list

(s) 1Nlog7

1delay Cognitive 2

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General form

• Hick-Hyman Law

– pi : the probability that the ith choice is selected

– pi can be estimated based on history

)1

(1 log7

1delay Cognitive

i1 pp

N

ii

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Motor process

• Stylus operation

• Fitts’ Law– A: distance to move– W: target dimension along the moving direction

– Parameters adopted from (MacKenzie and Buxton, 1992)

(s) )1(log166.023.0delayMotor 2 W

A

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Power Law of practice

• Speed on nth trial – Sn = S1 na, where a ≈0.4 – Applies to perceptual & motor processes– Does not apply to cognitive process or quality

Learning curve of text entry using Twiddler, Lyons, 2004

Power Law predictionMeasurement

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Human capacity limitations

Human capacity

• Perceptual• Cognitive• Motor• ……

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Perceptual limits

D

Ω

Visual and auditory output

Emin ≈ Ω·D2·10-13 (Joule)

About 10-14 (Joule) for most handheld usagePoint source

Minimal energy requirement for 1-bit changewith irreversible computing

10-21 (Joule) (Landauer, 1961)

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Insights for power reduction

D

ΩPoint source

P∝ Ω·D2

η(λ)·V(λ)

η(λ): conversion efficiency from electrical power

V(λ): relative human sensitivity factor

Reflective layer to control Ω

λ: wavelength of light/sound

Smaller D with head-mounted display and earphone

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Weight of electronic systems

Warwick, 1995

1 ounce ≈ 28.35

Weight decreased from 397 to 176 grams from 1996 to 2010

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137g

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540g

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680g

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Human thermal comfort

Starner & Maguire, 1999 and Kroemer et al, 1994

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A hot case: 3-Watt Nokia 3120

Phone case temperature will be 40 deg C higher.

Every One Watt increases surface temperature by about 13 deg C

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Motor limit: text entry speed

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Speaking mini hardware keyboard Virtual keyboard with stylus Handwriting

Spee

d (w

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min

ute)

Raw speed Corrected speed

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)The slow-user problem

• Energy efficiency – = (User productivity)/Average power consumption

• Fast computer vs. slow human userUsing Calculator on Sharp Zaurus PDA

99% time and 95% energy spent waiting during interaction

Reducing idle power most important

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Human factors & energy efficiency

• Energy efficiency– Energy consumption per task– # of tasks completed in the battery lifetime– User productivity/Avg. power consumption– or (User productivity) * (Power efficiency)

Human factors Low-power design

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Human factors & energy efficiency

Energy efficiency = User productivity

Avg. power consumption

It is all about tradeoffs between user productivity and power consumption

• Increase productivity without much power increase

• Reduce power consumption without much productivity decrease

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Comparison: Text entry

Handwriting recognition is inferior to alternatives

Speech recognition can be the most energy-efficient

Display off for speech recognition

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Speech recog. input rate (cwpm)

r inpu

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HW MKB VKB Letter Recog.HW MKB-Lighting VKB-Lighting Letter Recog.-Lighting

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Comparison: Command & control• Speech vs. GUI operation

Assume each stylus tap takes 750ms

Single-word voice command is more energy-efficient than GUI operation with 2 taps

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95% accurate

95% accurate/No LCD

95% accurate/No LCD/Lighting

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OLED display power management

• User productivity may decrease

2.5 times power reduction

HP Labs, MobileHCI 2004

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Predictive system shutdown

• About four eye fixations & saccades– 60*4 + 30*4 =360ms

• Four different choices– 286 ms

• Suppose A= 1/4 screen height– 615 ms

It takes more than 1 second for the user to respond

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Examples of energy-inefficient interfaces

Kyocera KX2325 LG VX 6100 Microsoft Voice Command 1.01

Buttons are protrusive. Often triggered accidentally in the pocket to activate the back lighting

The flip display uses the same back light as the main display

Display is on while not useful