Distributed embodied ePartners in a ubiquitous computing environment

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Distributed embodied ePartners in a ubiquitous
computing environment
Mark Neerincx et al.
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Introduction

• Environments with more networked information
  compilations and technical equipment.
• Add a collection of distributed connected
  personal electronic partners, ePartners, to
  support (distributed) human actors for specific
  tasks, like
• health-care actions by diabetics,
• technology use by elderly, and
• disclosure of feelings in high-demand missions

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ePartner Human-Machine Collaboration

• Predicting the actors momentary needs
• on-line gathering and modeling of human, machine,
  task and context information
• Attuning the interaction to these needs
• (semi-)automatic tailoring of support, content
  and dialogue to establish optimal human-machine
  performance
• Establishing natural H-M communication
• expressing and interpreting communicative acts
  based on a common reference

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Personal ePartner

• Sharing of experiences, learning and anticipation
• Common goal, but different roles and
  responsibilities
• Adequate distribution of workload
• Not copy of a human, but a complement
• Taking care of individual characteristics and
  context of operation
• Adequate level of trust and affection
• Quick understanding and natural communication
  (one word is enough)
• for specific goal and domain (e.g. self-care,
  daily activities)

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iCat as ePartner

• TNO and DUT use the iCat to develop
• models prototypes for effective social H-M
  communication.
• Research questions centre on
• the sensing and generation of affective
  expressions (face, voice),
• the application of different communication and
  assistance styles like motivational
  interviewing and cooperative anamnesis,
• the effects of the embodiment of an ePartner
  (e.g. compared to a virtual character).

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The SuperAssist Project
Personal assistants supporting distributed
supervision of complex task environments. Each
human actor has an assistant for anomaly
detection, diagnosis and communication
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Focus on Tele- and Self-Care

• More patients involvement in the care process
• Operating domestic medical instruments
• Management of a computer-based patient record
• Communication with medical technical
  specialists
• Increasing number of older people
• Chronic diseases 50 non-adherence
• Diabetes Type II
• Large, increasing group
• Typically older than 40
• Pancreas produces too little insulin
• Treatment involves diet, no-smoking, medication
  exercising

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Bottlenecks in Diabetes Care

• Shortage of diabetes nurses
• High No-Show in diabetes policlinic
• Lack of information during consultation
• Fixed consultation frequency (every 3 months)
• Lack of involvement/motivation of patients
• Too brief consult for adequate feedback to
  patients
• Large increase in patient numbers

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Supporting the Patient

• Usage of medical equipment
• Human-assistant cooperation
• Health and lifestyle
• Therapy adherence
• Automation of assistance
• Human vs synthetic assistant
• Embodiment of the Assistant
• Social behavior
• Tests should show improvements for
• Patient behavior and opinion (e.g. trust)
• Adequacy and richness of dialogue

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First iCat Experiment

• Goal
• Guidelines for adherence support
• iCat alternative for desk-top interface
• Background
• Health Buddy
• (Health Hero Network)

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Guidelines

• Personal assistants
• Fun
• Trust
• Cooperation
• Psychology/ motivational interviewing
• Express empathy
• Communicate respect
• Listen rather than tell
• Social robots
• Express and perceive emotions
• Communicate with high-level dialogue
• Use natural cues (gaze, gestures, etc.)

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Three User Interfaces

• Tiggie (Doellgroup)

iCat
Text (chat)
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Pilot Test

• Social non-social iCat or Tiggie, vs
  text-interface
• 6 participants
• Scenarios
• 3 types (diet, self-check, medication), but
  similar
• Both open and closed questions
• 4 question blocks Monday, Wednesday, Friday and
  Sunday
• First results Social iCat preferred
• Trust
• Acceptance
• Empathy
• Personality

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Conclusions

• Guidelines for Health Assistance
• Trust
• Fun
• Cooperation
• Express Empathy
• Communicate respect
• Listen rather than tell
• Future experiments
• Elderly
• Virtual iCat
• Personalization
• Dialogue management
• Long-term effects
• multi-Human multi-ePartner collaboration

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Acknowledgement

• SuperAssist is partially funded by IOP-MMI Senter
  a program of the Dutch Ministry of Economics
• Three research institutes participate in the
  SuperAssist project TNO, Delft University of
  Technology (DUT), and Leiden University Medical
  Center (LUMC)
• Four companies are involved Philips Research,
  Sigmax, Pemstar, Science Technology
• Specific contributions to this presentation
• Rosemarijn Looije (RUG/TNO)
• Amy Ahluwalia (LUMC)
• Olivier Blanson Henkemans (DUT/TNO)
• Jasper Lindenberg (TNO)
• Lennard Kuijten (UM/TNO)
• Vanessa Sawirjo (DUT)

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Questions?