Transcript Interaction Devices Human Computer Interaction CIS 6930/4930 Section 4188/4186 Interaction Performance ► 60s vs. Today  Performance ► Hz -> GHz  Memory ►k -> GB  Storage ►k -> TB  Input ► punch cards -> ►

Interaction Devices
Human Computer Interaction
CIS 6930/4930
Section 4188/4186
Interaction Performance
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60s vs. Today
 Performance
► Hz
-> GHz
 Memory
►k
-> GB
 Storage
►k
-> TB
 Input
► punch
cards ->
► Keyboards, Pens, tablets, mobile
phones, mice, digital cameras, web
cams
 Output
► 10
character/sec
► Megapixel displays, color laser,
surround sound, force feedback, VR
►
Substantial bandwidth increase!
Interaction Performance
►
Future?
Gestural input
Two-handed input
3D I/O
Others: voice, wearable, whole
body, eye trackers, data gloves,
haptics, force feedback
 Engineering research!
 Entire companies created
around one single technology
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Current trend:
 Multimodal (using car
navigation via buttons or voice)
 Helps disabled (esp. those w/
different levels of disability)
Keyboard and Keypads
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QWERTY keyboards been
around for a long time
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(1870s – Christopher Sholes)
Cons: Not easy to learn
Pros: Familiarity
Stats:
► Beginners:
1 keystroke per
sec
► Average office worker: 5
keystrokes (50 wpm)
► Experts: 15 keystrokes per
sec (150 wpm)
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Is it possible to do better?
Suggestions?
Keyboard and Keypads
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Look at the piano for possible
inspiration
Court reporter keyboards (one
keypress = multiple letters or a
word)
 300 wpm, requires extensive
training and use
►
Keyboard properties that matter
 Size
large - imposing for novices,
appears more complex
► mobile devices
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 Adjustable
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Reduces RSI, better
performance and comfort
 Mobile phone keyboards,
blackberry devices, etc.
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QWERTY
Keyboard Layouts
 Frequently used pairs far apart
 Fewer typewriter jams
 Electronic approaches don’t jam.. why
use it?
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DVOARK (1920s)
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150 wpm->200 wpm
Reducing errors
Takes about one week to switch
Stops most from trying
ABCDE – style
 Easier for non-typists
 Studies show no improvement vs.
QWERTY
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Number pads
 What’s in the top row?
 Look at phones (slight faster), then look
at calculators, keypads
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Those for disabled
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Split keyboards
KeyBowl’s orbiTouch (screenshot)
Eyetrackers, mice
Dasher - 2d motion with word prediction
Keys
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Current keyboards have been
extensively tested
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Size
Shape
Required force
Spacing
Speed vs. error rates for
majority of users
Distinctive click gives audio
feedback
 Why membrane keyboards are
slow (Atari 400?)
Environment hazards might
necessitate
► Usually speed is not a factor
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Keys Guidelines
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Special keys should be denoted
State keys (such as caps, etc.)
should have easily noted states
Special curves or dots for home
keys for touch typists
Inverted T Cursor movement
keys are important (though
cross is easier for novices)
Auto-repeat feature
 Improves performance, but only
if repeat is customizable (motor
impaired, young, old)
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Two thinking points:
 Why are home keys fastest to
type?
 Why are certain keys larger?
(Enter, Shift, Space bar)
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This is called Fitt’s Law
Keypads for small devices
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PDAs, Cellphones, Game consoles
Fold out keyboards
Virtual keyboard
Cloth keyboards (ElekSen)
Haptic feedback?
Mobile phones
 Combine static keys with dynamic soft
keys
 Multi-tap a key to get to a character
 Study: Predictive techniques greatly
improve performance
 Ex. LetterWise = 20 wpm vs 15 wpm
multitap
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Draw keyboard on screen and tap w/ pen
 Speed: 20 to 30 wpm (Sears ’93)
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Handwriting recognition (still hard)
 Subset: Graffiti2 (uses unistrokes)
Pointing Devices
Direct manipulation needs some pointing device
► Factors:
►
 Size of device
 Accuracy
 Dimensionality
►
Interaction Tasks:
 Select – menu selection, from a list
 Position – 1D, 2D, 3D (ex. paint)
 Orientation – Control orientation or provide direct
3D orientation input
 Path – Multiple poses are recorded
►
ex. to draw a line
 Quantify – control widgets that affect variables
 Text – move text
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Faster w/ less error than keyboard
Two types (Box 9.1)
 Direct control – device is on the screen surface
(touchscreen, stylus)
 Indirect control – mouse, trackball, joystick,
touchpad
Direct-control pointing
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First device – lightpen
 Point to a place on screen and press a
button
 Pros:
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Easy to understand and use
Very fast for some operations (e.g.
drawing)
 Cons:
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Hand gets tired fast!
Hand and pen blocks view of screen
Fragile
Evolved into the touchscreen
 Pros: Very robust, no moving parts
 Cons: Depending on app, accuracy
could be an issue
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1600x1600 res with acoustic wave
 Must be careful about software design
for selection (land-on strategy).
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If you don’t show a cursor of where you
are selecting, users get confused
 User confidence is improved with a
good lift-off strategy
Direct-control pointing
► Primarily
for novice
users or large user
base
► Case study: Disney
World
► Need to consider those
who are: disabled,
illiterate, hard of
hearing, errors in
usage (two touch
points), etc.
Indirect-Control Pointing
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Pros:
 Reduces hand-fatigue
 Reduces obscuration problems
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Cons:
 Increases cognitive load
 Spatial ability comes more into play
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Mouse
 Pros:
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Familiarity
Wide availability
Low cost
Easy to use
Accurate
 Cons:
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Time to grab mouse
Desk space
Encumbrance (wire), dirt
Long motions aren’t easy or obvious (pick up and replace)
 Consider, weight, size, style, # of buttons, force feedback
Indirect-Control Pointing
► Trackball
 Pros:
► Small
physical footprint
► Good for kiosks
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Joystick
 Easy to use, lots of buttons
 Good for tracking (guide or
follow an on screen object)
 Does it map well to your
app?
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Touchpoint
 Pressure-sensitive ‘nubbin’ on
laptops
 Keep fingers on the home
position
Indirect-Control Pointing
► Touchpad
 Laptop mouse device
 Lack of moving parts,
and low profile
 Accuracy, esp. those w/
motor disabilities
► Graphics
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Tablet
Screen shot
comfort
good for cad, artists
Limited data entry
Comparing pointing devices
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Direct pointing
 Study: Faster but less accurate than indirect (Haller ’84)
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Lots of studies confirm mouse is best for most tasks for
speed and accuracy
Trackpoint < Trackballs & Touchpads < Mouse
Short distances – cursor keys are better
Disabled prefer joysticks and trackballs
 If force application is a problem, then touch sensitive is preferred
 Vision impaired have problems with most pointing devices
► Use multimodal approach or customizable
► Read Vanderheiden ’04 for a case study
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cursors
Designers should smooth out trajectories
Large targets reduce time and frustration
Example
► Five
fastest places to click on for a righthanded user?
Example
► What
affects time?
Fitts’s Law
Paul Fitts (1954) developed a model of human hand
movement
► Used to predict time to point at an object
► What are the factors to determine the time to point to
an object?
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Just from your own experience, is this function linear?
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D – distance to target
W – size of target
No, since if Target A is D distance and Target B is 2D
distance, it doesn’t take twice as long
What about target size? Not linear there either
MT = a + b log2(D/W + 1)
 a = time to start/stop in seconds (empirically
measured per device)
 b = inherent speed of the device (empirically
measured per device)
 Ex. a = 300 ms, b = 200 ms/bit, D = 14 cm, W =
2 cm
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Ans: 300 + 200 log2(14/2 + 1) = 900 ms
 Really a slope-intercept model
Fitts’s Law
► MT
= a + b log2(D/W + 1)
 a = time to start/stop in seconds (empirically measured
per device)
 b = inherent speed of the device (empirically measured
per device)
 Ex. a = 300 ms, b = 200 ms/bit, D = 14 cm, W = 2 cm
► Ans:
300 + 200 log2(14/2 + 1) = 900 ms
 Question: If I wanted to half the pointing time (on average), how
much do I change the size?
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Proven to provide good timings for most age groups
Newer versions taken into account
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Direction (we are faster horizontally than vertically)
Device weight
Target shape
Arm position (resting or midair)
2D and 3D (Zhai ’96)
Very Successfully Studied
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Applies to
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Limitations
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Feet, eye gaze, head mounted sights
Many types of input devices
Physical environments (underwater!)
User populations (even retarded and drugged)
Drag & Drop and Point & Click
Dimensionality
Software accelerated pointer motion
Training
Trajectory Tasks (Accot-Zhai Steering Law)
Decision Making (Hick’s Law)
Results (what does it say about)
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Buttons and widget size?
Edges?
Popup vs. pull-down menus
Pie vs. Linear menus
iPhone/web pages (real borders) vs. monitor+mouse (virtual borders)
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http://particletree.com/features/visualizing-fittss-law/
http://www.asktog.com/columns/022DesignedToGiveFitts.html
http://www.yorku.ca/mack/GI92.html
Interesting readings:
Precision Pointing Movement Time
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Study: Sears and Shneiderman ’91
 Broke down task into gross and fine components for small targets
 PPMT = a + b log2(D/W+1) + c log2(d/W)
►c
– speed for short distance movement
► d – minor distance
 Notice how the overall time changes with a smaller target.
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Other factors
 Age (Pg. 369)
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Research: How can we design devices that produce smaller
constants for the predictive equation
 Two handed
 Zooming
Novel Devices
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Themes:
 Make device more diverse
Users
► Task
►
 Improve match between task
and device
 Improve affordance
 Refine input
 Feedback strategies
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Foot controls
 Already used in music where
hands might be busy
 Cars
 Foot mouse was twice as slow
as hand mouse
 Could specify ‘modes’
Novel Devices
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Eye-tracking
 Accuracy 1-2 degrees
 selections are by constant
stare for 200-600 ms
 How do you distinguish w/ a
selection and a gaze?
 Combine w/ manual input
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Multiple degree of freedom
devices
 Logitech Spaceball and
SpaceMouse
 Ascension Bird
 Polhemus Liberty and
IsoTrack
Novel Devices
►
Boom Chameleon
 Pros: Natural, good spatial
understanding
 Cons: limited applications,
hard to interact (very
passive)
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DataGlove
 Pinch glove
 Gesture recognition
 American Sign Language,
musical director
 Pros: Natural
 Cons: Size, hygiene,
accuracy, durability
Novel Devices
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Haptic Feedback
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Why is resistance useful?
SensAble Technology’s Phantom
Cons: limited applications
Sound and vibration are easier and
can be a good approximation
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Rumble pack
Two-Handed input
 Different hands have different
precision
 Non-dominant hand selects fill, the
other selects objects
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Ubiquitous Computing and Tangible
User Interface
 Active Badges allows you to move
about the house w/ your profile
 Which sensors could you use?
 Elderly, disabled
 Research: Smart House
 Myron Kruger – novel user
participation in art (Lots of exhibit
art at siggraph)
Novel Devices
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Paper/Whiteboards
 Video capture of annotations
 Record notes (special tracked pens
Logitech digital pen)
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Handheld Devices
 PDA
 Universal remote
 Help disabled
► Read
LCD screens
► Rooms in building
► Maps
 Interesting body-context-sensitive.
► Ex.
hold PDA by ear = phone call
answer.
Novel Devices
► Miscellaneous
 Shapetape – reports 3D
shape.
► Tracks
limbs
► Engineer
for specific
app (like a gun trigger
connected to serial
port)
 Pros: good affordance
 Cons: Limited general
use, time
Speech and Auditory Interfaces
► There’s the dream
► Then there’s reality
► Practical apps don’t
really require freeform
discussions with a computer
 Goals:
► Low
cognitive load
► Low error rates
► Smaller
goals:
 Speech Store and Forward (voice mail)
 Speech Generation
 Currently not too bad, low cost, available
Speech and Auditory Interfaces
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Bandwidth is much lower than visual displays
Ephemeral nature of speech (tone, etc.)
Difficulty in parsing/searching (Box 9.2)
Types
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Discrete-word recognition
Continuous speech
Voice information
Speech generation
Non-speech auditory
If you want to do research here, lots of research in the
audio, audio psychology, and DSP field you should
understand
Discrete-Word Recognition
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Individual words spoken by a specific person
Command and control
90-98% for 100-10000 word vocabularies
Training
 Speaker speaks the vocabulary
 Speaker-independent
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Still requires
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Low noise operating environment
Microphones
Vocabulary choice
Clear voice (language disabled are hampered, stressed)
Reduce most questions to very distinct answers (yes/no)
Discrete-Word Recognition
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Helps:
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Disabled
Elderly
Cognitive challenged
User is visually distracted
Mobility or space restrictions
Apps:
 Telephone-based info
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Study: much slower for cursor movement than mouse or keyboard
(Christian ’00)
Study: choosing actions (such as drawing actions) improved
performance by 21% (Pausch ’91) and word processing (Karl ’93)
 However acoustic memory requires high cognitive load (> than hand/eye)
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Toys are successful (dolls, robots). Accuracy isn’t as important
Feedback is difficult
Continuous Speech Recognition
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Dictation
Error rates and error repair are still poor
Higher cognitive load, could lower overall quality
Why is it hard?
 Recognize boundaries (normal speech blurs them)
 Context sensitivity
 “How to wreck a nice beach”
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Much training
Specialized vocabularies (like medical or legal)
Apps:
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Dictate reports, notes, letters
Communication skills practice (virtual patient)
Automatic retrieval/transcription of audio content (like radio, CC)
Security/user ID
Voice Information Systems
Use human voice as a source of info
► Apps:
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 Tourist info
 Museum audio tours
 Voice menus (Interactive Voice Response IVR systems)
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Use speech recognition to also cut through menus
 If menus are too long, users get frustrated
 Cheaper than hiring 24 hr/day reps
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Voice mail systems
 Interface isn’t the best
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Get email in your car
 Also helps with non-tech savvy like the elderly
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Potentially aides with
 Learning (engage more senses)
 Cognitive load (hypothesize each sense has a limited ‘bandwidth’)
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Think ER, or fighter jets
Speech Generation
► Play
back speech (games)
► Combine text (navigation systems)
► Careful evaluation!
 Speech isn’t always great
► Door
is ajar – now just a tone
► Use flash
► Supermarket scanners
 Often times a simple tone is better
 Why? Cognitive load
► Thus
cockpits and control rooms need speech
► Competes w/ human-human communication
Speech Generation
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Ex: Text-to-Speech (TTS)
Latest TTS uses multiple syllabi to make generated speech sound
better
 Robotic speech could be desirable to get attention
 All depends on app
 Thus don’t assume one way is the best, you should user test
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Apps: TTS for blind, JAWS
Web-based voice apps: VoiceXML and SALT (tagged web pages).
 Good for disabled, and also for mobile devices
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Use if
 Message is short
 Requires dynamic responses
 Events in time
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Good when visual displays aren’t that useful. When?
 Bad lighting, vibrations (say liftoff)
Non-speech Auditory Interface
► Audio
► Major
tones that provide information
Research Area
 Sonification – converting information into audio
 Audiolization
 Auditory Interfaces
► Browsers
link
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produced a click when you clicked on a
Increases confidence
Can do tasks without visual cognitive load
Helps figure out when things are wrong
Greatly helps visually impaired
Non-speech Auditory Interface
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Terms:
 Auditory icons – familiar sounds
(record real world sound and
play it in your app)
 Earcons – new learned sounds
(door ajar)
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Role in video games is huge
 Emotions, Tension, set mood
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To create 3D sound
 Need to do more than stereo
 Take into account Head-related
transfer function (HRTF)
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Ear and head shape
New musical instruments
 Theremin
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New ways to arrange music
Displays
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Primary Source of
feedback
Properties:
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Physical Dimension
Resolution
Color Depth and correctness
Brightness, contrast, glare
Power
Refresh rate
Cost
Reliability
# of users
Display
Technology
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Monochrome displays
(single color)
 Low cost
 Greater intensity range
(medical)
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Color
Raster Scan CRT
LCD – thin, bright
Plasma – very bright, thin
LED – large public displays
Electronic Ink – new product
w/ tiny capsules of negative
black particles and positive
white
 Braille – refreshable cells
with dots that rise up
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Large Displays
► Wall
displays
 Informational
► Control
rooms, military, flight
control rooms, emergency
response
► Provides
 System overview
 Increases situational awareness
 Effective team review
► Old:
Array of CRTs
 Interactive
► Require
new interaction methods
(freehand sketch, PDAs)
► Local and remote collaboration
► Art, engineering
Large Displays
► Multiple
Desktop Displays
 Multiple CRTs or Flat panels for
large desktops
 Cheap
 Familiar
 Spatial divide up tasks
 Comparison tasks are easier
 Too much info?
► HMD
► Eventually
pixel
-> Every surface a
Mobile device displays
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Applications
 Personal
► Reprogrammable
frames
picture
 Digital family portrait
(GaTech)
 Business
► PDAs,
 Medical
cellphones
► Monitor
patients
 Research: Modality
Translation Services (Trace
Center – University of
Wisconsin)
► As
you move about it auto
converts data, info, etc. for
you
Mobile device displays
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Actions on mobile devices
 Monitor information and
alert (calendar)
 Gather then spread out
information (phone)
 Participate in groups and
relate to individual
(networked devices)
 Locate services and identify
objects (GPS car system)
 Capture and then share info
(phone)
Mobile device displays
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Guidelines for design
 Bergman ’00, Weiss, ’02
 Industry led research and design case studies
(Lindholm ’03)
 Typically short in time usage (except handheld
games)
 Optimize for repetitive tasks (rank functions
by frequency)
 Research: new ways to organize large
amounts of info on a small screen
 Study: Rapid Serial Visual Presentation
(RSVP) presents text at a constant speed
(33% improvement Oquist ’03)
 Searching and web browsing still very poor
performance
 Promising: Hierarchical representation (show
full document and allow user to select where
to zoom into)
Animation, Image, and Video
Content quality has also greatly
increased
► 3D rendering is near life-like
► Digital Photography is common
► Scanned documents
► Video compression
► Multimedia considerations for the
disabled
► Printers
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 3D Printers create custom objects
from 3D models