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A fascinating challenge in the field of human–robot interaction is the possibility to endow robots with emotional intelligence in order to make the interaction more intuitive, genuine, and natural. To achieve this, a critical point is the capability of the robot to infer and interpret human emotions. Emotion recognition has been widely explored in the broader fields of human–machine interaction and affective computing. Here, we report recent advances in emotion recognition, with particular regard to the human–robot interaction context. Our aim is to review the state of the art of currently adopted emotional models, interaction modalities, and classification strategies and offer our point of view on future developments and critical issues. We focus on facial expressions, body poses and kinematics, voice, brain activity, and peripheral physiological responses, also providing a list of available datasets containing data from these modalities.

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Robotic psychological assessment is a novel field of research that explores social robots as psychometric tools for providing quick and reliable screening exams. In this study, we involved elderly participants to compare the prototype of a robotic cognitive test with a traditional paper-and-pencil psychometric tool. Moreover, we explored the influence of personality factors and technology acceptance on the testing. Results demonstrate the validity of the robotic assessment conducted under professional supervision. Additionally, results show the positive influence of Openness to experience on the interaction with robot's interfaces, and that some factors influencing technology acceptance, such as Anxiety, Trust, and Intention to use, correlate with the performance in the psychometric tests. Technical feasibility and user acceptance of the robotic platform are also discussed.