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  • Interactive Robotics in Medicine and Care

    Person holding Nao
    Person holding Nao
    © Bielefeld University / Patrick Pollmeier

Adaptive Interaction for Self-efficacy (AI4self)

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Prof. Dr.-Ing. Anna-Lisa Vollmer

Professorship of Interactive Robotics in Medicine and Nursing

Dr.-Ing. Mara Brandt

Research assistant

Cooperation partners

 

Logo SAIL
© 2024 SAIL

Medical examinations can be particularly challenging for shy children and individuals with disabilities. Additionally, a child's temperament may influence examination results or even prevent a proper examination from being conducted. One way to address these challenges is by strengthening the child's perceived self-efficacy.

The AI4self project explores how a targeted warm-up phase with a robot can increase self-efficacy before a medical examination. The interaction with the robot is individually adapted to the child's temperament.

Several studies are being conducted to examine the effectiveness of different warm-up strategies with preschool and primary school children:

  • Task-independent warm-up: Interactive storytelling with the Nao robot.
  • Task-related warm-up: Interactive storytelling with the Nao robot, incorporating elements of the upcoming medical examination.
  • Play-based warm-up: Playing with the Nao robot using colorful buttons.
  • Teaching-based warm-up: The child teaches the Nao robot something.

Adaptive interaction

Robot Nao with tablet in the background
© Bielefeld University

The interaction with the robot is adaptive to account for individual differences in children's temperament. This is achieved by detecting various behavioral indicators, including distance from the robot, emotions, eye gaze, gestures and posture. The project focuses particularly on detecting and adaptively responding to shyness.

Research questions

  • How can interaction with a robot be tailored to a child's temperament to enable an optimal warm-up?
  • Can teaching a robot enhance a child's perceived self-efficacy?
  • Which warm-up method with a robot is most effective?

Platforms and systems

  • Grey NAO
    © Bielefeld University

    NAO

  • Pepper
    © Bielefeld University / Patrick Pollmeier
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