Introduction to HCI

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					Interaction Devices
 User Interfaces and Usability
           CS 5153
          Interaction Performance
►   60s vs. Today
     Performance
        ► Hz   -> GHz
     Memory
        ►k   -> GB
     Storage
        ►k   -> TB
     Input
        ► punch cards ->
        ► Keyboards, Pens, tablets, mobile
          phones, mice, cameras, web cams
     Output
        ► 10 character/sec ->
        ► Megapixel displays, HD capture and
          display, color laser, surround sound,
          force feedback, VR
►   Substantial bandwidth increase!
       http://www.dreamfabric.com/c64/#
              Interaction Performance
►   Future?
      Gestural input
      Two-handed input
      3D/6D I/O
      Others: voice, wearable, whole
       body, eye trackers, data gloves,
       haptics, force feedback
      Engineering research!
      Entire companies created
       around one single technology
►   Current trend:
      Multimodal (using car
       navigation via buttons or voice)
      Helps disabled (esp. those w/
       different levels of disability)
               Keyboard and Keypads
  ►   QWERTY keyboards been
      around for a long time
         (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)
  ►   Is it possible to do better?
http://www.youtube.com/watch?v=gS8wG
    ePlknM&feature=player_embedded
               Keyboard and Keypads
►   Look at the piano for possible
    inspiration
►   Court reporter keyboards (one
    keypress = multiple letters or a
    word)
      300 wpm, requires extensive
       training and use
►   How important is:
      Accuracy
      Training
►   Keyboard properties that matter
      Size
      Adjustability
         ►   Reduces RSI, better
             performance and comfort
      Mobile phone keyboards,
       blackberry devices, etc.
  ►   QWERTY
                        Keyboard Layouts
        Frequently used pairs far apart
        Fewer typewriter jams
        Electronic approaches don’t jam.. why
         use it?
  ►   DVOARK (1920s)
          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
  ►   Number pads
        What’s in the top row?
        Look at phones (slight faster), then look
         at calculators, keypads
  ►   Those for disabled
          Split keyboards
          KeyBowl’s orbiTouch
          Eyetrackers, mice
          Dasher - 2d motion with word prediction
http://www.youtube.com/watch?v=TzqCrB
                                    Keys
►   Current keyboards have
    been extensively tested
       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
                     Keys Guidelines
►   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)
►   Two thinking points:
      Why are home keys fastest to
       type?
      Why are certain keys larger?
       (Enter, Shift, Space bar)
►   This is called Fitt’s Law
          Keypads for small devices
►   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
►   Draw keyboard on screen and tap w/ pen
      Speed: 20 to 30 wpm (Sears ’93)
►   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
►   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
►   First device – lightpen
      Point to a place on screen and press a
       button
      Pros:
         ►   Easy to understand and use
         ►   Very fast for some operations (e.g.
             drawing)
      Cons:
         ►   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
         ►   1600x1600 res with acoustic wave
      Must be careful about software design
       for selection (land-on strategy).
         ►   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
►   Pros:
     Reduces hand-fatigue
     Reduces obscuration problems
►   Cons:
     Increases cognitive load
     Spatial ability comes more into play
►   Mouse
     Pros:
        ►   Familiarity
        ►   Wide availability
        ►   Low cost
        ►   Easy to use
        ►   Accurate
     Cons:
        ►   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:
        ► Smallphysical footprint
        ► Good for kiosks
►   Joystick
     Easy to use, lots of buttons
     Good for tracking (guide or
      follow an on screen object)
     Does it map well to your
      app?
►   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    Tablet
     Screen shot
     comfort
     good for cad, artists
     Limited data entry
       Comparing pointing devices
►   Direct pointing
     Study: Faster but less accurate than indirect (Haller ’84)
►   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   cursors
        ► Read Vanderheiden ’04 for a case study
►   Designers should smooth out trajectories
►   Large targets reduce time and frustration
                 Example
     fastest places to click on for a right-
► Five
 handed 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?
        D – distance to target
        W – size of target
►   Just from your own experience, is this function linear?
        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
►   T = a + b log2(D/W + 1)
      T = mean time
      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
      Really a slope-intercept model
                              Fitts’s Law
►   T = a + b log2(D/W + 1)
     T = mean time
     a = time to start/stop in seconds (empirically measured per device)
     b = inherent speed of the device (empirically measured per device)
      [time/bit or ms/bit]
     Ex. a = 300 ms, b = 200 ms/bit, D = 14 cm, W = 2 cm
              300 + 200 log2(14/2 + 1) = 900 ms
         ► Ans:
     Question: If I wanted to half the pointing time (on average), how much do
      I change the size?
►   Proven to provide good timings for most age groups
►   Newer versions taken into account
       Direction (we are faster horizontally than vertically)
       Device weight
       Target shape
       Arm position (resting or midair)
       2D and 3D (Zhai ’96)
                                  Examples
►T          = a + b log2(D/W + 1)
                              a=300, b= 200, X, W = 10

            800
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            600
Time (ms)




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                                            Distance (cm)
                                 Examples
►T           = a + b log2(D/W + 1)
                               a=300, b= 200, D=30, X

            1400

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Time (ms)




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                                                 width
                                             Distance (cm)
                                Examples
                        BLUE a=300, b=200, D=15, W=[1-30]
                       PURPLE a=300, b=200, D=[1-30], W=15

            1200

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Time (ms)




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                                              Variable
               Fitts’s Law
►T   = a + b log2(D/W + 1)
  T = mean time
  a = time to start/stop in seconds
   (empirically measured per device)
  b = inherent speed of the device
   (empirically measured per device)
   [time/bit or ms/bit]
  First part is device characteristics
  Second part is target difficulty
         Very Successfully Studied
►   Applies to
     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
►   Limitations
     Dimensionality
     Software accelerated pointer motion
     Training
     Trajectory Tasks (Accot-Zhai Steering
      Law is a good predictor and joins Fitt’s
      Law)
     Decision Making (Hick’s Law)
          Very Successfully Studied
►   Results (what does it say about)
       Buttons and widget size?
       Edges?
       Popup vs. pull-down menus
       Pie vs. Linear menus
       iPhone/web pages (real borders) vs.
        monitor+mouse (virtual borders)
►   Interesting readings:
     http://particletree.com/features/visual
      izing-fittss-law/
     http://www.asktog.com/columns/022
      DesignedToGiveFitts.html
     http://www.yorku.ca/mack/GI92.html
    Precision Pointing Movement Time
►   Study: Sears and Shneiderman ’91
     Broke down task into gross and fine components for small targets
     Precision Point Mean Time = 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.
►   Other factors
     Age (Pg. 369)
►   Research: How can we design devices that produce smaller
    constants for the predictive equation
     Two handed
     Zooming
                Affordance
► Quality  of an object, or an environment,
  that allows an individual to perform an
  action.
► Gibson (’77) – perceived action possibilities
► Norman – The Design of Everyday Things
Affordance Examples
Affordance Examples




           http://jareddonovan.com/blog/
          Affordances Matter?
► When   would affordances matter?
  Languages
  Emergencies




                         http://jareddonovan.com/blog/
                       Novel Devices
►   Themes:
      Make device more diverse
         ► Users
         ► Task
      Improve match between task
       and device
      Improve affordance
      Refine input
      Feedback strategies
►   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
►   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
►   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)
►   DataGlove
     Pinch glove
     Gesture recognition
     American Sign Language,
      musical director
     Pros: Natural
     Cons: Size, hygiene,
      accuracy, durability
                          Novel Devices
►   Haptic Feedback
     Why is resistance useful?
     SensAble Technology’s
      Phantom
     Cons: limited applications
     Sound and vibration are
      easier and can be a good
      approximation
        ► Rumble   pack
►   Two-Handed input
     Different hands have
      different precision
     Non-dominant hand selects
      fill, the other selects objects
        Ubiquitous Computing and
         Tangible User Interfaces
► 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
►   Paper/Whiteboards
     Video capture of annotations
     Record notes (special tracked pens
      Logitech digital pen)
►   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
►   Ray Kurzweil (’87) – first commercial
    speech recognition software
►   Bandwidth is much lower than visual
    displays
►   Ephemeral nature of speech (tone, etc.)
►   Difficulty in parsing/searching (Box 9.2)
►   Types
        Discrete-word recognition
        Continuous speech
        Voice information
        Speech generation
        Non-speech auditory
►   If you want to do research here, review
    research in:
      Audio
      Audio psychology
      Digital signal processing
                                        http://www.kurzweiltech.com/raybio.html
         Discrete-Word Recognition
►   Individual words spoken by a specific person
►   Command and control
►   90-98% for 100-10000 word vocabularies
►   Training
     Speaker speaks the vocabulary
     Speaker-independent
►   Still requires
       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
►   Helps:
        Disabled
        Elderly
        Cognitive challenged
        User is visually distracted
        Mobility or space restrictions
►   Apps:
      Telephone-based info
►   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)
►   Toys are successful (dolls, robots). Accuracy isn’t as important
►   Feedback is difficult
    Continuous Speech Recognition
►   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”
►   Much training
►   Specialized vocabularies (like medical or legal)
►   Apps:
        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:
      Tourist info
      Museum audio tours
      Voice menus (Interactive Voice Response IVR
       systems)
►   Use speech recognition to also cut through
    menus
      If menus are too long, users get frustrated
      Cheaper than hiring 24 hr/day reps
►   Voice mail systems
      Interface isn’t the best
►   Get email in your car
      Also helps with non-tech savvy like the elderly
►   Potentially aides with
      Learning (engage more senses)
      Cognitive load (hypothesize each sense has a
       limited ‘bandwidth’)
          ►   Think ER, or fighter jets
              Speech Generation
► Playback 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
     ► Thuscockpits and control rooms need speech
     ► Competes w/ human-human communication
                   Speech Generation
►   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
►   Apps: TTS for blind, JAWS
►   Web-based voice apps: VoiceXML and SALT (tagged web pages).
      Good for disabled, and also for mobile devices
►   Use if
      Message is short
      Requires dynamic responses
      Events in time
►   Good when visual displays aren’t that useful. When?
      Bad lighting, vibrations (say liftoff)
  Non-speech Auditory Interface
► Audio   tones that provide information
► Major   Research Area
   Sonification – converting information into audio
   Audiolization
   Auditory Interfaces
► Browsers    produced a click when you clicked on a
 link
     Increases confidence
     Can do tasks without visual cognitive load
     Helps figure out when things are wrong
     Greatly helps visually impaired
    Non-speech Auditory Interface
►   Terms:
     Auditory icons – familiar sounds
      (record real world sound and
      play it in your app)
     Earcons – new learned sounds
      (door ajar)
►   Role in video games is huge
     Emotions, Tension, set mood
►   To create 3D sound
     Need to do more than stereo
     Take into account Head-related
      transfer function (HRTF)
        ►    Ear and head shape
►   New musical instruments
     Theremin
►   New ways to arrange music
          Displays
► Primary Source of
  feedback
► Properties:
       Physical Dimension
       Resolution
       Color Depth and correctness
       Brightness, contrast, glare
       Power
       Refresh rate
       Cost
       Reliability
       # of users
          Display
        Technology
►   Monochrome displays
    (single color)
     Low cost
     Greater intensity range
      (medical)
►   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
                    Large Displays
► Wall   displays
   Informational
     ► Control rooms, military, flight
       control rooms, emergency
       response
     ► Provides
           System overview
           Increases situational awareness
           Effective team review
   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?
► Eventually   -> Every surface a
  pixel
              Mobile device displays
►   Personal
     Reprogrammable picture
      frames
                family portrait
        ► Digital
          (GaTech)
►   Medical
     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 guidlines
►   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)
                    3D Printing
► Create custom objects from
  3D models
► Create physical models for
   Design review
   Construction

				
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