Interaction development for personal daily support : design of conversational agent for activity tracking

Interaction

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development

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for

personal

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daily

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support

Design

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of

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conversational

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agent

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for

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activity

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tracking

By_​​Chris_​​ter_​​Beke

Abstract

This_​​report_​​is_​​the_​​result_​​for_​​the_​​final_​​project_​​of_​the_{​ ​​}Creative_​​Technology_​​Bachelor’s programme._​​The_​​primary_​​goal_​​is_​​assisting_​​Roessingh_​​Research_​​&_​​Development_​​on_​​the redesign_​​of_​​an_​​activity_​​tracking_​​application_​in_{​ ​​}a_​​larger_​“home_{​ ​​}caring_​​environment”_​​called eWALL,_​​which_​​is_​​in_​​the_​​process_​​of_​being_{​ ​​}moved_​​into_​​an_​​autonomous_​​tablet_​​solution._​​The major_​​steps_​​to_​​execute_​​were_​​background_​research,_{​ ​​}creating_​​a_​prototype_{​ ​​}and_​​validation_​​it through_​​user_​​testing._​​The_​​user_​​test_​​entailed_​​a_​​4_​​part_​questionnaire_{​ ​​}and_​​23_​​people

1_​​Introduction 4

1.1​​eWALL 4

1.1.1_​​Design 5

1.1.2_​​Activity_​​application 6

1.2_​​Problem_​​description 7

1.2.1​​Challenges 8

2_​​Research_​​questions 9

3_​​State_​​of_​​the_​​Art 10

3.1_​​Activity_​​tracking 10

3.1.1_​​Goal_​​setting 11

3.2​​Conversational​​agents 12

3.2.1_​​Embodied_​​Virtual_​​Agents 12

3.2.2_​​Scripted_​​vs_​​relational_​​agents 13

3.2.3_​​Why_​​an_​​agent? 14

4_​​Ideation 15

4.1_​​Domain 15

4.2_​​Robin_​​the_​​Robot 15

4.3_​​Interaction 16

4.3.1_​​Example 16

4.4_​​Scenarios 17

5_​​Method 18

5.1_​​Reporting 18

5.2_​​Evaluation 18

5.3​​User​​test​​setup 18

5.4_​​User_​​test_​​process 19

6_​​Realisation 20

6.1_​​Criteria 20

6.2_​​Prototype_​​development 21

6.3_​​Prototype_​​decisions 22

6.4_​​Prototype_​​screenshots 23

7_​​Evaluation 24

7.1_​​Hypotheses 24

7.2​​Results 24

7.2.1_​​General_​​questions 25

7.2.3_​​Scenario_​​using_​​the_​​virtual_​​agent 27

7.2.4_​​Evaluation 28

8_​​Conclusion_​​and_​​discussion 29

8.1​​Recommendations 30

9_​​Acknowledgements 31

10_​​Bibliography 32

11_​​Appendices 33

Appendix_​​I:_​​Terminology 33

1

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Introduction

Roessingh Research and Development (RRD) is a center for research on rehabilitation, psychology, biomedical science and computer science . They position themselves between1 university and healthcare practice. RRD works on tools to help people manage their own health, focussing on innovative and user friendly applications that offer monitoring of health data​​and​​coaching.

1.1

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eWALL

One of the projects RRD is working on is the eWALL - Home Caring Environment , an 2 European Union funded project designed to contribute to the prolongation of independent living for various types of patients and elderly. The distinction between typical healthcare systems and eWALL is that eWALL tries to do this in an unobtrusive way by using advanced sensing technologies. Current target groups of eWALL are people with age related impairments (ARI), mild cognitive impairments (MCI, or early-stage dementia), and COPD and_​​asthma_​​patients.

The eWALL system consists of 2 major components: the eWALL Cloud and eWALL Sensing Environment. The Sensing Environment is installed in the patient's home to gather data about activity, or help them with their daily routine. The eWALL Cloud connects the Sensing Environment with other stakeholders like hospitals, government health care systems_​​and_​​relatives.

1_{​​http://www.rrd.nl/}

Figure_​​1:_​​System_​​architecture_​​of_​​eWALL

1.1.1

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Design

Figure_​​2:_​​The_​​dashboard_​​of_​​eWALL

1.1.2

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Activity

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application

An_​​important_​​application_​​on_​​eWALL_​​for_​​everyone_​​who_​​needs_​​coaching_​​with_​​everyday physical_​​activity_​​is_​​the_​​activity_​​tracker._​​This_​​app_​​shows_​​daily_​​activity_​​like_​​step_​​count,_​​but_​​also change_​​over_​​time.

1.2

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Problem

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description

Roessingh_​​Research_​​&_​​Development_​​is_​​working_​​on_​​a_​​continuation_​​of_​​eWALL,_​​named

CloudCare2U ,3_​that_{​ ​​}has_​​significant_​changes_{​ ​​}compared_​​to_​the_{​ ​}original_{​ ​​}project._​​One_​of_{​ ​​}these_​​is that_​​eWALL_​​will_​​now_​​be_​​running_​​on_​​a_​​tablet_​​in_​​people’s_​​own_​​home._​​This_​​brings_​​two

challenges_​​to_​​the_​​table_​​regarding_​​the_​​redesign_​of_{​ ​​}the_​​activity_​​app:_​​screen_​​size_​​and_​​domain. The_​​change_​​in_​​screen_​​size_​​​​will_​​affect_​​the_​​entire_​​system,_​​not_​​only_​​the_​activity_{​ ​​}app,_​​but_​​for_​​the scope_​​of_​​this_​​project_​​we_​will_{​ ​​}focus_​​only_​​on_​​this_​​part.

An_​​outstanding_​​issue_​​is_​​that_​​the_​​current_​​activity_​​app_​​does_​​not_​​fall_​​in_​line_{​ ​​}with_​​the_​​design_​​of eWALL;_​​it_​​is_​​flat_​​as_​​opposed_​​to_​​the_​real-world_{​ ​​}imitating_​​design_​​of_​the_{​ ​​}home_​​screen._​​In_​​order to_​​make_​​it_​​fit_​​with_​​the_​​rest_​​of_​​eWALL_​​so_​​that_​​it_​​feels_​​like_​​a_​​single_​​product,_​​the_​​redesign_​​should use_​​these_​​imitation_​​design_​​elements.

Furthermore,_​​the_​​redesigned_​​app_​​should_​​allow_​​users_​to_{​ ​​}look_​​both_​​at_​​their_​​current_​​activity_​​to see_​​if_​​their_​​daily_​​target_​​is_​​met,_​​but_​​also_​​show_​​them_​​how_​​they’re_​doing_{​ ​​}over_​​time._​​This_​​trend analysis_​​is_​​important_​​to_​​let_​​people_​​be_​​aware_​​of_​​their_​​behaviour_​​and_​​hopefully_​​change_​​it_​​to meet_​​their_​​goals.

Lastly,_​​the_​​activity_​​app_​​should_​​be_​​connected_​​to_​​the_​​system’s_​conversational_{​ ​​}agent_​​“Robin_​​the Robot”._​​It_​​should_​​become_​​clear_​​in_​​the_​research_{​ ​​}and_​​testing_​​what_​​type_​​of_​​information_​​people would_​​want_​​to_​​use_​​the_​​conversational_​​agent_​​to_​retrieve,_{​ ​​}but_​​also_​​which_​tasks_{​ ​​}are_​​better_​​to_​​be performed_​​by_​​the_​​user_​​interface.

1.2.1

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Challenges

Next​​to​​these​​design​​specifications,​​there​​are​​a​​number​​of​smaller​ ​​challenges​​that​​became apparent_​​from_​​interviews_​​with_​​the_​​client.

First_​​of_​​all,_​​the_​​system_​​is_​​not_​​in_​​use_​​in_​​it’s_​​current_​​form_​​(a_​​large_​​touch_​​display_​​on_​​the_​​wall), making​​is​​hard​​to​​answer​​questions​​related​​to​​comparisons​​between​the​ ​​original​​and​​new domain_​​(a_​​tablet_​​in_​​the_​​user’s_​​own_​​home)._​​Therefore_​​the_​​project_​​will_​​be_​​focussed_​​solely_​​on validating_​​the_​​tablet_​​sized_​​redesign.

2

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Research

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questions

In_​​order_​​to_​​solve_​​the_​​aforementioned_​​problem_​​for_​​the_​​client,_​the_{​ ​​}following_​​research_​​questions have_​​been_​​defined:

Primary_​​research_​​question

“Which_​​tasks_​​are_​​better_​​to_​​be_​​executed_​via_{​ ​​}an_​​embodied_​​conversational_​​agent_​​instead_​​of_​​the user_​​interface?”

Secondary_​​research_​​question

3

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State

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of

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the

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Art

This_​​project_​​focuses_​​on_​​the_​​application_​​of_​embodied_{​ ​​}agents_​​and_​​how_​​they_​​can_​​assist_​​in providing_​​feedback_​​and_​​coaching_​​on_​​daily_​​physical_​​activity,_​​activity_​​goal_​​setting_​​and motivational​​support.​​Therefore​​relevant​​background​​information​​is​​provided​​on​​the subjects_​​of_​​activity_​​tracking,_​​goal_​​setting,_​​conversational_​​agents_​​and_​​human-computer relationships.

3.1

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Activity

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tracking

Activity_​​trackers_​​are_​​widely_​​used_​​nowadays._​Most_{​ ​​}of_​​these_​trackers_{​ ​​}feature_​​a_​​smartphone application_​​combined_​​with_​​a_​​small_​​wristband_​or_{​ ​​}wrist_​​worn_​sensing_{​ ​​}device._​​These_​​devices have​​sensors​​that​​keep​​track​​of​​movement​​and​​they​​feed​​this​​data​​back​​into​​the​​smartphone application._​​The_​​app_​​then_​​translates_​​that_​​data_​into_{​ ​​}something_​​that_​​can_​​be_​​understood_​​by_​​the wearer._​​This_​​often_​​happens_​​in_​​the_​​form_​​of_​graphs_{​ ​​}to_​​indicate_​​whether_​a_{​ ​​}certain_​​daily_​​goal_​​was met._​​The_​​representation_​​of_​​these_​​statistics_​​are_​​different_​​per_​​brand,_​​but_​​most_​​of_​​them_​​are_​​very similar.​​Currently​​popular​​brands​​for​​personal​​fitness​​tracking​​are​​FitBit,​​Jawbone​​and Apple_​​Watch,_​​but_​​there_​​are_​​many_​​more_​​similar_​​devices_​​on_​​the_​​market.

3.1.1

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Goal

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setting

When_​​activity_​​goals_​​are_​​properly_​​set,_​​they_​​can_​​increase_​​motivation,_​​self-regulation_​​and promote_​​a_​​sense_​​of_​​achievement._​​This_​​can_​be_{​ ​​}improved_​​by_​​setting_​​meaningful_​​goals_​​using_​​a method_​​called_​​SMART_​​(Specific,_​​Measurable,_​​Attainable,_​​Relevant,_​​Timely)_​​4.

Fitness_​​solutions_​​like_​​FitBit_​​allow_​​users_​​to_​​set_​goals_{​ ​​}in_​​the_​​app._​The_{​ ​​}idea_​​behind_​​setting_​​these goals_​​is_​​to_​​motivate_​​people_​​to_​​use_​​the_​device_{​ ​​}more_​​and_​​become_​healthier_{​ ​​}in_​​the_​​process._​​By allowing_​​to_​​set_​​personalized_​​goals,_​​the_​​user_​​feels_​​more_​​attached_​​to_​​the_​​goals_​​and_​​is_​​more inclined_​​to_​​follow_​​the_​​needed_​​workouts_​​to_​​reach_​​them._​​This_​satisfies_{​ ​​}Specific_​​and_​​Relevant components_​​of_​​SMART._​​The_​​app_​​allows_​​you_​to_{​ ​​}track_​​your_​​progress_​​over_​​time,_​​giving_​​an indication_​​if_​​you_​​will_​​reach_​​your_​​goal_​​or_​if_{​ ​​}you_​​need_​​increase_​your_{​ ​​}efforts._​​This_​​helps_​​users with_​​the_​​Measurable_​​and_​​Attainable_​​parts._​The_{​ ​​}timely,_​​or_​proximal,_{​ ​​}component_​​of_​​SMART can_​​also_​​be_​​covered_​​by_​​the_​​app,_​​as_​​the_​​user_​​is_​​totally_​​free_​​in_​​selecting_​​when_​​to_​​reach_​​a_​​certain goal_​​(short-_​​or_​​long_​​term_​​goals).

A_​​study_​​performed_​​by_​​​Stavros_​​Asimakopoulos,_​​​​Grigorios_​​Asimakopoulos_​​​and_​​​Frank_​​Spillers

in_​​2017_​​for_​​Informatics_​​goes_​​in_​​depth_​into_{​ ​​}the_​​motivation_​​and_​​user_​​engagement_​​involved_​​with personal_​​fitness_​​trackers._​​For_​​their_​​study,_​wearables_{​ ​​}and_​​smartphone_​apps_{​ ​​}from_​​FitBit_​​and Jawbone_​​were_​​used._​​They_​​conclude_​​that_​​the_​success_{​ ​​}of_​​reaching_​​these_​​goals_​​relies_​​greatly_​​on data_​​accuracy,_​​gamification_​and_{​ ​​}the_​​design_​​of_​​the_​​application_​​itself .5_​Users_{​ ​​}felt_​​motivational value_​​from_​​seeing_​​steps_​​and_​​advice_​​in_​​the_​​user_​​interface._​​They_​​also_​​liked_​​the_​​level_​​of

autonomy_​​the_​​smartphone_​apps_{​ ​​}were_​​giving_​​them.

Another_​​element_​​in_​​getting_​​users_​​to_​​stick_​to_{​ ​​}their_​​workouts_​​is_​​gamification._​​Most_​​of_​​the popular_​​apps_​​have_​​a_​​badge_​​​​system,_​​where_​​each_​​time_​​the_​​user_​​reaches_​​a_​​certain_​​milestone,_​​a small_​​award_​​is_​​presented_​​to_​​indicate_​​that_​​the_​user_{​ ​​}is_​​doing_​​a_​good_{​ ​​}job._​​Often_​​the_​​next milestone_​​is_​​visible_​​within_​​the_​​app,_​​allowing_​​users_​​to_​​have_​​a_​​new_​​target_​​to_​​work_​​towards.

4_{​​https://vpal.harvard.edu/publications/setting-goals-who-why-how}

The_​​second_​​option_​​in_​​gamification_​​is_​​rankings._​Users_{​ ​​}are_​​listed_​​in_​​high_​​score_​​lists_​​together with_​​people_​​they_​​invite_​​in_​​the_​​app,_​usually_{​ ​​}friends_​​or_​​family_​​members._​​This_​​brings_​​a

competition_​​element_​​into_​​the_​​fitness_​​tracker_​​and_​​motivates_​users_{​ ​​}to_​​get_​​or_​stay_{​ ​​}on_​​top_​​of_​​the list._​​An_​​example_​​of_​​this_​​is_​​the_​​smartphone_​​app_​​Runkeeper._​​Unlike_​​other_​​solutions_​​it_​​does_​​not require_​​the_​​purchase_​​of_​​a_​​wristband_​​device,_​​but_​​simply_​​uses_​the_{​ ​​}phone’s_​​location_​​to

determine_​​the_​​distance_​​and_​​speed_​​of_​​each_​run._{​ ​​}These_​​are_​​then_​​compared_​​to_​​similar_​​workouts from_​​friends,_​​or_​​even_​​share_​​your_​​progress_​​on_​​social_​​media . 6

3.2

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Conversational

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agents

A_​​conversational_​​agent_​​or_​​dialog_​​system_​​is_​​a_​​software_​​system_​designed_{​ ​​}to_​​interact_​​with humans_​​in_​​a_​​structured_​​way._​​These_​​systems_​can_{​ ​​}use_​​text,_​​speech,_​​graphics_​​or_​​other_​​methods of_​​communicating_​​with_​​a_​​human.

Well-known_​​conversational_​​agents_​​nowadays_​​are_​the_{​ ​​}personal_​​assistant_​​type_​​programs_​​that smartphones_​​and_​​domotics_​​systems_​​have._​​Examples_​​of_​​these_​​are_​​Apple’s_​Siri,_{​ ​​}Google_​​Now,_​​or Amazon_​​Alexa.

3.2.1

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Embodied

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Virtual

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Agents

When_​​integrating_​​a_​​conversational_​​agent_​​into_​​a_​​system_​​in_​​such_​​a_​​way_​​that_​it_{​ ​​}has_​​a_​​digital_​​or physical_​​representation_​​in_​​the_​​environment_​​that_​​is_​​uses_​​to_​​interact_​​with_​​it,_​​we_​​call_​​it_​​an embodied_​​virtual_​​agent._​​The_​​current_​​eWALL_​​system_​​has_​​such_​​an_​agent;_{​ ​​}Robin_​​the_​​Robot.

The_​​biggest_​​difference_​​between_​​embodied_​​virtual_​agents_{​ ​​}and_​​other_​dialog_{​ ​​}systems_​​is_​​the amount_​​of_​​interaction_​​that_​​is_​​possible._​​It_​can_{​ ​​}provide_​​a_​​much_​​richer_​​way_​​of_​​communication, for_​​example_​​using_​​gestures_​​or_​​facial_​expressions_{​ ​​}to_​​convey_​a_{​ ​​}message._​​When_​​humans communicate,_​​much_​​of_​​our_​​meaning_​​and_​​intentions_​​are_​​expressed_​​via_​​body_​​language. Bringing_​​this_​​trait_​​to_​​a_​​conversational_​agent_{​ ​​}greatly_​​enhances_​its_{​ ​​}capability_​​to_​​communicate with_​​humans_​​in_​​a_​​natural_​​way.

The_​​current_​​agent_​​in_​​eWALL_​​is_​​designed_​​like_​​a_​​1950’s_​​robot_​​that_​​fits_​​the_​​living_​​room

environment_​​of_​​the_​​system._​​It_​​is_​​important_​​for_​​an_​​embodied_​​agent_​​to_​​fit_​​in_​​it’s_​​surroundings, so_​​the_​​eWALL_​​designers_​​chose_​​to_​make_{​ ​​}a_​​character_​that_{​ ​​}fits_​​their_​​theme.

An_​​example_​​of_​​an_​​embodied_​​virtual_​​agent_​​can_​​be_​​found_​​in_​​​​Non-player_​​characters_​​(or_​​NPCs) in_​​games._​​In_​​the_​​game_​​Civilization,_​​NPCs_​are_{​ ​​}used_​​for_​​enemies_​​and_​​council_​​members._​​You can_​​have_​​a_​​dialogue_​​with_​​them_​​that_​changes_{​ ​​}depending_​​on_​​your_​​answers_​​or_​​trade_​​offers. These_​​conversation_​​flows_​​are_​​pre-scripted._​However,_{​ ​​}these_​​unexpected_​​responses_​​keep_​​the game_​​interesting._​​The_​​characters_​​are_​​historical_​​figures_​​that_​​lead_​​one_​of_{​ ​​}the_​​enemy_​​computer players,_​​making_​​them_​​real_​​embodied_​​agents.

Figure_​​5:_​​Examples_​​of_​​embodied_​​agents_​as_{​ ​​}NPCs_​​in_​the_{​ ​​}game_​​Civilization_​​V.

3.2.2

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Scripted

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vs

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relational

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agents

A_​​conversational_​​agents_​​is_​​a_​​type_​​of_​Human-Computer_{​ ​​}interaction_​​that_​​is_​​designed_​​to_​​have_​​a long-term_​​relationship_​​with_​​the_​​user._​​The_​interaction_{​ ​​}between_​​the_​human_{​ ​​}and_​​computer_​​over time_​​can_​​be_​​seen_​​as_​​a_​​relationship,_​​making_​a_{​ ​​}conversational_​​agent_​​in_​the_{​ ​​}role_​​of_​​a_​​personal assistant​​a​​relational​​agent.​​This​​area​​of​​research​​was​​first​​discussed​​by​​T.​​Bickmore​​and​​R. Picard_​​[Bickmore,_​​Picard,_​​2005]._​​This_​​relational_​​aspect_​of_{​ ​​}an_​​agent_​​sets_​​it_​​apart_​​from_​​the mostly_​​scripted_​​agents_​​that_​​are_​​used_​​in_​the_{​ ​​}games_​​mentioned_​​above._​​Over_​​time,_​​the_​​computer learns_​​more_​​about_​​the_​​user_​​and_​​builds_​​up_​​a_​​context_​​to_​​give_​​more_​​meaning_​​to_​​the

3.2.3

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Why

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an

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agent?

Why_​​would_​​any_​​system,_​​eWALL_​​or_​​otherwise,_​use_{​ ​​}an_​​embodied_​​agent_​​to_​​interact_​​with_​​users even_​​though_​​it_​​is_​perceived_{​ ​​}as_​​burdensome_​​on_​​smartphones?

The_​​best_​​application_​​for_​​virtual_​​assistants_​​lies_​​in_​​the_​​execution_​​of_​​complex_​​tasks._​​On_​​a_​​typical smartphone_​​these_​​are_​​tasks_​​like_​​setting_​​alarms,_​​finding_​​and_​​playing_​music,_{​ ​​}or_​​asking_​​for weather_​​forecasts .7_​​All_​​these_​​tasks_​​normally_​​require_​​multiple_​​actions_​​in_​​the_​​user_​​interface._​​It is_​​difficult_​​to_​​determine_​​which_​​task_​​is_​​difficult_​and_{​ ​​}which_​​task_​​is_​easy,_{​ ​​}but_​​generally_​​the_​​line lies_​​at_​​the_​​point_​​where_​​using_​​the_​​assistant_​to_{​ ​​}do_​​it_​​takes_​less_{​ ​​}time_​​and_​​less_​​steps.

When_​​it_​​comes_​​to_​​personal_​​daily_​​support,_​activity_{​ ​​}tracking_​​and_​​goal_​​setting,_​​the_​​amount_​​of data_​​that_​​is_​​gathered_​​overtime_​​might_​​overwhelm_​the_{​ ​​}user_​​resulting_​​in_​​the_​​inability_​​to_​​make decisions_​​based_​​on_​​this_​​data._​​A_​​virtual_​​assistant_​​can_​​help_​organize_{​ ​​}this_​​information_​​by intelligently_​​translating_​​the_​​data_​​set_​​into_​​actionable_​​goals.

4

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_​

Ideation

During_​​the_​​ideation_​​phase,_​​several_​​brainstorm_​feedback_{​ ​​}sessions_​​were_​held_{​ ​​}with_​​RRD_​​to make_​​sure_​​the_​​project_​​was_​​going_​​in_​​the_​direction_{​ ​​}the_​​client_​​wanted._​An_{​ ​​}important_​​step_​​in_​​the process​​was​​pivoting​​from​​a​​design​​focussed​​prototype​​to​​a​virtual​ ​​agent​​focussed​​prototype. The_​​virtual_​​assistant_​​was_​​more_​​interesting_​​to_​​work_​​on_​​as_​​it_​​is_​​using_​​modern_​​technologies_​​and will_​​probably_​​have_​​a_​​larger_​​impact_​​on_​daily_{​ ​​}support_​​systems_​​like_​​eWALL_​​in_​​the_​​future.

4.1

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_​

Domain

The_​​original_​​eWALL_​​was_​​displayed_​​on_​​a_​large_{​ ​​}monitor_​​installed_​​in_​​a_​​living_​​room_​​environment in_​​a_​​nursing_​​home._​​Going_​​forward,_​​RRD_​​decided_​​to_​​use_​​tablets_​​that_​​can_​be_{​ ​​}put_​​in_​​user’s_​​own homes.​​This​​domain​​change​​must​​be​​taken​​into​​account​​when​designing​ ​​the​​prototype.​​With a_​​smaller_​​screen,_​​it_​​is_​​harder_​​to_​​see_​​from_​​a_​​distance_​​what_​​is_​displayed._{​ ​​}The_​​user_​​either_​​needs to_​​come_​​closer_​​to_​​the_​​device,_​​or_​​an_​​alternative_​​method_​​for_​​interaction_​​is_​​required._​​This_​​brings us_​​to_​​the_​​implementation_​​of_​Robin_{​ ​​}the_​​Robot_​​in_​​the_​​prototype.

4.2

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Robin

_​

_​

the

_​

_​

Robot

The_​​virtual_​​agent_​​in_​​the_​​original_​​eWALL_​​project_​​is_​​called_​​Robin_​​the_​​Robot._​​Robin_​​is_​​displayed on​​the​​home​​screen​​and​​when​​clicked​​on​it​ ​​opens​​a​​dialog​that​ ​​showed​​questions​​that​​you can_​​ask._​​However_​​there_​​was_​​no_​​real_​​intelligence_​​in_​​Robin_​​so_​​only_​​these_​​specific_​​questions_​​can be_​​asked._​​Also_​​the_​​questions_​​need_​​to_​​be_​​clicked_​​as_​​there_​​is_​​no_​​voice_​​recognition_​​or

text-to-speech_​​available._​​This_​​makes_​​interacting_​​with_​​Robin_​​not_​​as_​​seamless_​as_{​ ​​}it_​​should_​​be when​​we​​work​​with​​embodied​​agents.

A_​​few_​​things_​​from_​​the_​​original_​​Robin_​​were_​found_{​ ​​}to_​​be_​​interesting_​to_{​ ​​}use_​​in_​​the_​​prototype. Those_​​were_​​the_​​50’s_​​robot_​​design_​​and_​​the_​​awareness_​​of_​​which_​​user_​​was_​​interacting_​​with_​​the system​​by​​display​​the​​name​​when​​opening​​the​​Robin​​dialog.

New_​​ideas_​​were_​​created_​​as_​​well_​​for_​​the_​​prototype._​​We_​​wanted_​​to_​​see_​​if_​​adding_​​voice

on_​​the_​​smaller_​​screen._​​This_​​means_​​that_​​the_​​user_​​can_​​talk_​​to_​​Robin_​using_{​ ​​}their_​​voice_​​and_​​Robin would_​​talk_​​back_​​with_​​the_​​answers_​​that_​​were_​found_{​ ​​}in_​​the_​​system,_​bringing_{​ ​​}it_​​closer_​​to_​​other assistants_​​like_​​Siri_​​and_​​Google_​​Now._​​By_​​adding_​this_{​ ​​}type_​​of_​​interaction,_​we_{​ ​​}hoped_​​to_​​see_​​a reduction_​​of_​​information_​​displayed_​​in_​​the_​​user_​​interface.

4.3

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Interaction

The_​​most_​​important_​​part_​​of_​​the_​​prototype_​is_{​ ​​}the_​​interaction_​​with_​​Robin_​​the_​​Robot._​​There were_​​several_​​discussions_​​about_​​how_​​deep_​​the_​​interaction_​​with_​​Robin_​should_{​ ​​}go._​​For_​​example whether_​​Robin_​​should_​​be_​​able_​​to_​​understand_​​small_​​talk_​​about_​topics_{​ ​​}other_​​than_​​activity tracking,_​​or_​​if_​​Robin_​​should_​​be_​​able_​​to_​ask_{​ ​​}follow_​​up_​​questions_​when_{​ ​​}pieces_​​of_​​context_​​are missing._​​These_​​types_​​of_​​behaviours_​​would_​​result_​​in_​​a_​​more_​human-like_{​ ​​}interaction,_​​but_​​they also_​​complicate_​​the_​​prototype_​​development.

The_​​second_​​point_​​of_​​attention_​​in_​​the_​​interaction_​​is_​​the_​​difficulty_​​of_​​the_​​questions_​​being_​​asked. Simple_​​questions_​​like_​​“How_​​far_​​do_​​I_​​need_​​to_​​walk_​​today?”_​​or_​​“What_​is_{​ ​​}my_​​daily_​​step_​​goal?” can_​​be_​​asked,_​​but_​​those_​​would_​​be_​​just_​​as_​​easy_​​to_​​find_​​in_​the_{​ ​​}user_​​interface._​​More_​​difficult questions_​​like_​​“Will_​​I_​​reach_​​my_​​goal_​​this_​week?”_{​ ​​}would_​​be_​​harder_​to_{​ ​​}read_​​from_​​the_​​interface because_​​multiple_​​pieces_​​of_​​information_​​are_​needed_{​ ​​}to_​​construct_​an_{​ ​​}answer._​​The_​​answers given_​​by_​​Robin_​​t0_​​questions_​​like_​​these_​​should_​​be_​​constructed_​​in_​​such_​​a_​way_{​ ​​}that_​​the_​​user_​​will be_​​able_​​to_​interpret_{​ ​​}this_​​information_​​easily.

4.3.1

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Example