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1 Human Computer Interaction Case Study – EU GUIDE Project Dr Pradipta Biswas, PhD (Cantab) Assistant Professor Indian Institute of Science http://cpdm.iisc.ernet.in/PBiswas.htm Contents Scope User study Design Development 2 Scope 4 Users and new markets 4 Ageing-related impairments and preferences Need for targeted services and adaptation, but limited technology and knowledge support for developers New Business opportinities around „Senior TV“ services ( © Copyright OceanBlueSoftware) Companies already start to address needs of elderly society (→ “Senior TV”), but face lack of development support in addressing ageing- related issues.

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  • 1

    Human Computer InteractionCase Study – EU GUIDE Project

    Dr Pradipta Biswas, PhD (Cantab)Assistant ProfessorIndian Institute of Sciencehttp://cpdm.iisc.ernet.in/PBiswas.htm

    Contents• Scope• User study• Design• Development

    2

    Scope

    4

    Users and new markets

    4

    Ageing-related impairments and preferences

    Need for targeted services and adaptation, but limited technology and knowledge support for

    developersNew Business opportinities around „Senior TV“

    services ( © Copyright OceanBlueSoftware)

    Companies already start to address needs of elderly

    society (→ “Senior TV”), but face lack of development

    support in addressing ageing-related issues.

  • 2

    5

    Technical developments - Platforms

    5

    Hybrid Web- und TV services

    Video communication & social media Apps on TV

    Adds complexity to established and accepted concepts, but

    could support services fostering social inclusion.

    6

    Technical developments - Devices

    6

    Integration of TV and mobile devices

    Gesture control and speech recognition (e.g. Microsoft‘s KINECT)

    Smart Remote Controls

    Second screen: Tablet PCs

    Not immediately targeting elderly users’ needs, but a technical opportunity for

    personalized experiences and support in managed

    interaction.

    Problem in accessibility

    7

    GUIDE objectives

    8

  • 3

    User Study

    Users

    10

    Survey – Social status• Education• Profession• Number of people living with

    11

    Survey – Functional ability• Contrast sensitivity• Colour blindness• Audiogram• Digit symbol test• Trail making test• Grip strength• Active range of motion of wrist

    12

  • 4

    Survey – Attitude towards technology• I think that I need to use new technology• I consider myself having the necessary skills to manage to use new technology tools• I have problems to use these technologies properly even with practice• The problems of technology devices are impossible to understand, so it is hard to find a solution• When there is a problem with a new technology tool, it is because there is something wrong with that device• I’m afraid to touch a new technology tool in case I’ll break it• I don’t get advantage of using new technology tools• I prefer to use an old fashion tool with fewer functions than a new one

    Agree Disagree Neutral13

    Clusters

    14

    Interfaces can be optimized for different types of users

    Usability requirements• Response time• Screen layout

    • Home button• Home screen

    • Help screen• Interface personalization

    15

    Personalization

    16

    One size fits allIndividualization

  • 5

    Our work

    17

    UserModel

    Simulator

    RuntimeUM

    Design Optimization

    Runtime Adaptation

    Design

    User centred design process

    19Users Clusters Simulation Optimized interfaces

    Simulation Example

    20

  • 6

    Simulation result

    21

    Development

    Developing runtime user model0

    2000

    4000

    6000

    8000

    10000

    12000

    14000

    0 10 20 30 40 50 60GS (in KG)

    MT (in

    msec

    )

    TouchStylusTrackball

    Mouse

    02000400060008000

    100001200014000

    50 70 90 110 130 150 170 190ROMW (in degree)

    MT (in

    msec

    )

    Mouse

    23

    GSGS

    ROMW

    CB

    CS

    Range of User Parameters Simulation Rules

    User modelling web services• User Sign Up

    • Interface Parameter Prediction

    • Examples24

  • 7

    User model predictionProfileCode

    GS Tremor ROMW

    MinimumFontSize

    ColourBlindness

    Adaptation

    Predicted BestModality

    Colour Contrast

    ButtonSpacing

    (inkg)

    (indegre

    e)(inpoint)

    A 16 YES 71 14 Protanopia Gravity Well Pointing/Screen Blue White 20*B 25 NO 52 14 Protanopia Damping Pointing/Gesture/ Screen Blue White 20C 59 NO 66 12 Deuteranopia Damping Pointing/Gesture/ Screen Blue White 20D 59 NO 66 0 N/A Damping Speech/Audio N/A 20E 25 YES 52 14 None Gravity Well Pointing/Screen Any 20F 59 NO 120 14 Tritanopia Damping Pointing/Gesture/ Screen White Black 5*G 9 NO 63 14 None Gravity Well Pointing/Screen Any 20

    25

    *20 means: 0.2 *distance of target from centre of screen5 means: 0.05 * length of diagonal of the screen

    26

    Multimodal adaptation

    GUIDE Core

    26

    Input devicesMotion sensor(pointing, gestures)Speech recog. (speech)Remote control (button selection)…

    Output devicesBrowserAvatarVideo streamAudio stream

    GUIDE Profile

    User ModelContext Model

    Dialog manager

    Multimodal Fusion

    Multimodal Fission

    UserUser

    Input Interpretation

    and Adaptation

    System ResponseUser Input

    27

    Framework application interface

    2nd Annual Review Meeting, Brussels, March 21st 201227

    Personalized Interfaces

    28

  • 8

    New Interaction Technologies

    29

    Demonstration

    30

    31

    Take away points• Lifecycle of a project

    • User study → Design → Development • Validation will be discussed in next session

    • Practical use of user modelling• Multimodal interaction• Interface personalization

    32