Developing a robot-guided interactive simon game for physical and cognitive training

Enveloping cognitive or physical rehabilitation into a game highly increases the patients' commitment with their treatment. Specially with children, keeping them motivated is a very time-consuming work, so therapists are demanding tools to help them with this task. NAOTherapist is a generic robotic architecture that uses Automated Planning techniques to autonomously drive noncontact upper-limb rehabilitation sessions for children with a humanoid NAO robot. Our aim is to develop more robotic games for this platform to enrich its variability and possibilities of interaction. The goal of this work is to present our first attempt to develop a different, more complex game that reuses the previous architecture. We contribute with the design description of a novel robotic Simon game that employs upper-limb poses instead of colors and could qualify as a cognitive and physical training. Statistics of evaluation tests with 14 adults and 56 children are displayed and the outcomes are analyzed in terms of human-robot interaction (HRI) quality. The results demonstrate the application-domain generalization capabilities of the NAOTherapist architecture and give an insight to further analyze the therapeutic benefits of the new developed Simon game.This work is partially funded by grant TIN2012-38079-C03-02 and TIN2015-65686- C5-1-R of Spanish Ministerio de Economía y Competitividad. We also want to thank the Joan Miró school of Leganés for their assistance with the evaluations, to the teachers and the management team for their support, and specially to all the children who kindly participated in the evaluation and enjoyed playing with our robots

Embodied conversations: Performance and the design of a robotic dancing partner

This paper reports insights gained from an exploration of performance-based techniques to improve the design of relationships between people and responsive machines. It draws on the Emergent Objects project and specifically addresses notions of embodiment as employed in the field of performance as a means to prototype and develop a robotic agent, SpiderCrab, designed to promote expressive interaction of device and human dancer, in order to achieve ‘performative merging’. The significance of the work is to bring further knowledge of embodiment to bear on the development of human-technological interaction in general. In doing so, it draws on discursive and interpretive methods of research widely used in the field of performance but not yet obviously aligned with some orthodox paradigms and practices within design research. It also posits the design outcome as an ‘objectile’ in the sense that a continuous and potentially divergent iteration of prototypes is envisaged, rather than a singular final product. The focus on performative merging draws in notions of complexity and user experience. Keywords: Embodiment; Performance; Tacit Knowledge; Practice-As-Research; Habitus.</p

Reinforcement Learning Approaches in Social Robotics

This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which an agent interacts through trial-and-error with its environment to discover an optimal behavior. Since interaction is a key component in both reinforcement learning and social robotics, it can be a well-suited approach for real-world interactions with physically embodied social robots. The scope of the paper is focused particularly on studies that include social physical robots and real-world human-robot interactions with users. We present a thorough analysis of reinforcement learning approaches in social robotics. In addition to a survey, we categorize existent reinforcement learning approaches based on the used method and the design of the reward mechanisms. Moreover, since communication capability is a prominent feature of social robots, we discuss and group the papers based on the communication medium used for reward formulation. Considering the importance of designing the reward function, we also provide a categorization of the papers based on the nature of the reward. This categorization includes three major themes: interactive reinforcement learning, intrinsically motivated methods, and task performance-driven methods. The benefits and challenges of reinforcement learning in social robotics, evaluation methods of the papers regarding whether or not they use subjective and algorithmic measures, a discussion in the view of real-world reinforcement learning challenges and proposed solutions, the points that remain to be explored, including the approaches that have thus far received less attention is also given in the paper. Thus, this paper aims to become a starting point for researchers interested in using and applying reinforcement learning methods in this particular research field

The development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research

Numerical cognition is a distinctive component of human intelligence such that the observation of its practice provides a window into high-level brain function. The modelling of numerical abilities in artificial cognitive systems can help to confirm existing child development hypotheses and define new ones by means of computational simulations. Meanwhile, new research will help to discover innovative principles for the design of artificial agents with advanced reasoning capabilities and clarify the underlying algorithms (e.g. deep learning) that can be highly effective but difficult to understand for humans. This article promotes new investigation by providing a common resource for researchers with different backgrounds, including computer science, robotics, neuroscience, psychology, and education, who are interested in pursuing scientific collaboration on mutually stimulating research on this topic. The article emphasises the fundamental role of embodiment in the initial development of numerical cognition in children. This strong relationship with the body motivates the Cognitive Developmental Robotics (CDR) approach for new research that can (among others) help to standardise data collection and provide open databases for benchmarking computational models. Furthermore, we discuss the potential application of robots in classrooms and argue that the CDR approach can be extended to assist educators and favour mathematical education

Exploring multimedia and interactive technologies

The goal of multimedia design strategies and innovation is to produce meaningful learning environments that relate to and build upon what the learner already knows and what the learner seeks. The multimedia tools used to achieve knowledge transfer should activate recall or prior knowledge and help the learner alter and encode new structures. Traditionally, multimedia has been localized to specific delivery systems and demographics based on the government, industry, or academic concentration. The presenter will explore the introduction of immersive telecommunications technologies, constructivist learning methodologies, and adult learning models to standardize networking and multimedia-based services and products capable of adapting to wired and wireless environments, different devices and conditions on a global scale

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Current Rehabilitation Methods for Cerebral Palsy

In rehabilitation of children with cerebral palsy (CP), varying approaches and techniques are used, ranging from very conservative and conventional techniques, such as muscle strengthening, manual stretching, and massage, to more complex motor learning-based theories, such as neurodevelopmental treatment, conductive education, and several others. The motor disorders seen in CP are frequently accompanied by disturbances of sensation, cognition, communication, perception, and/or behavior disorders; thus, therapy approaches are arranged to meet the individual child’s needs. The approaches can be divided into two groups as with equipment and without equipment. Examples for without equipment rehabilitation approaches are neurodevelopmental treatment, conductive education constraint-induced movement therapy, and task-oriented therapy, whereas robotic therapy, virtual reality, and horse-back riding therapy are the examples of rehabilitation approaches with equipment. CP is a prevalent, disabling condition. Application of evidence-based methods ensures maximum gains in children. The concept that intense, task-specific exercises capitalize on the potential plasticity of the CNS and thus improve motor recovery has led to the development of several successful interventions for children with CP. Also approaches that improve the patient’s motivation and target the activities of daily living and participation are the most effective approaches for functional recovery of the children with CP