Social robots as psychometric tools for cognitive assessment: a pilot test

Recent research demonstrated the benefits of employing robots as therapeutic assistants and caregivers, but very little is known on the use of robots as a tool for psychological assessment. Socially capable robots can provide many advantages to diagnostic practice: engage people, guarantee standardized administration and assessor neutrality, perform automatic recording of subject behaviors for further analysis by practitioners. In this paper, we present a pilot study on testing people’s cognitive functioning via social interaction with a humanoid robot. To this end, we programmed a social robot to administer a psychometric tool for detecting Mild Cognitive Impairment, a risk factor for dementia, implementing the first prototype of robotic assistant for mass screening of elderly population. Finally, we present a pilot test of the robotic procedure with healthy adults that show promising results of the robotic test, also compared to its traditional paper version

Abstract concept learning in cognitive robots

Purpose of Review Understanding and manipulating abstract concepts is a fundamental characteristic of human intelligence that is currently missing in artificial agents. Without it, the ability of these robots to interact socially with humans while performing their tasks would be hindered. However, what is needed to empower our robots with such a capability? In this article, we discuss some recent attempts on cognitive robot modeling of these concepts underpinned by some neurophysiological principles. Recent Findings For advanced learning of abstract concepts, an artificial agent needs a (robotic) body, because abstract and concrete concepts are considered a continuum, and abstract concepts can be learned by linking them to concrete embodied perceptions. Pioneering studies provided valuable information about the simulation of artificial learning and demonstrated the value of the cognitive robotics approach to study aspects of abstract cognition. Summary There are a few successful examples of cognitive models of abstract knowledge based on connectionist and probabilistic modeling techniques. However, the modeling of abstract concept learning in robots is currently limited at narrow tasks. To make further progress, we argue that closer collaboration among multiple disciplines is required to share expertise and co-design future studies. Particularly important is to create and share benchmark datasets of human learning behavior

Analyzing Cognitive Flexibility in Older Adults Through Playing with Robotic Cubes

International audienceCognitive flexibility is an important ability to adapt to changing situations. We consider the evolution of technologies in the digital era as a changing situation requiring the individuals to maintain a certain cognitive flexibility. Across the lifespan, cognitive flexibility is an essential ability to adapt to a continuous evolution of human-computer interactions (HCI). In this study, we observe older adults in a playful robotic task aiming to observe their cognitive flexibility in order to consider if older adults shows an adequate level of cognitive flexibility to solve a problem solving task with unknown robotic cubes. The playful robotic task engages the participants individually in problem solving a puzzle-based challenge with modular robotics