Human-centred design methods : developing scenarios for robot assisted play informed by user panels and field trials

Original article can be found at: http://www.sciencedirect.com/ Copyright ElsevierThis article describes the user-centred development of play scenarios for robot assisted play, as part of the multidisciplinary IROMEC1 project that develops a novel robotic toy for children with special needs. The project investigates how robotic toys can become social mediators, encouraging children with special needs to discover a range of play styles, from solitary to collaborative play (with peers, carers/teachers, parents, etc.). This article explains the developmental process of constructing relevant play scenarios for children with different special needs. Results are presented from consultation with panel of experts (therapists, teachers, parents) who advised on the play needs for the various target user groups and who helped investigate how robotic toys could be used as a play tool to assist in the children’s development. Examples from experimental investigations are provided which have informed the development of scenarios throughout the design process. We conclude by pointing out the potential benefit of this work to a variety of research projects and applications involving human–robot interactions.Peer reviewe

Psychophysiological analysis of a pedagogical agent and robotic peer for individuals with autism spectrum disorders.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by ongoing problems in social interaction and communication, and engagement in repetitive behaviors. According to Centers for Disease Control and Prevention, an estimated 1 in 68 children in the United States has ASD. Mounting evidence shows that many of these individuals display an interest in social interaction with computers and robots and, in general, feel comfortable spending time in such environments. It is known that the subtlety and unpredictability of people’s social behavior are intimidating and confusing for many individuals with ASD. Computerized learning environments and robots, however, prepare a predictable, dependable, and less complicated environment, where the interaction complexity can be adjusted so as to account for these individuals’ needs. The first phase of this dissertation presents an artificial-intelligence-based tutoring system which uses an interactive computer character as a pedagogical agent (PA) that simulates a human tutor teaching sight word reading to individuals with ASD. This phase examines the efficacy of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and an evidence-based instructional procedure referred to as constant time delay (CTD). A concurrent multiple-baseline across-participants design is used to evaluate the efficacy of intervention. Additionally, post-treatment probes are conducted to assess maintenance and generalization. The results suggest that all three participants acquired and maintained new sight words and demonstrated generalized responding. The second phase of this dissertation describes the augmentation of the tutoring system developed in the first phase with an autonomous humanoid robot which serves the instructional role of a peer for the student. In this tutoring paradigm, the robot adopts a peer metaphor, where its function is to act as a peer. With the introduction of the robotic peer (RP), the traditional dyadic interaction in tutoring systems is augmented to a novel triadic interaction in order to enhance the social richness of the tutoring system, and to facilitate learning through peer observation. This phase evaluates the feasibility and effects of using PA-delivered sight word instruction, based on a CTD procedure, within a small-group arrangement including a student with ASD and the robotic peer. A multiple-probe design across word sets, replicated across three participants, is used to evaluate the efficacy of intervention. The findings illustrate that all three participants acquired, maintained, and generalized all the words targeted for instruction. Furthermore, they learned a high percentage (94.44% on average) of the non-target words exclusively instructed to the RP. The data show that not only did the participants learn nontargeted words by observing the instruction to the RP but they also acquired their target words more efficiently and with less errors by the addition of an observational component to the direct instruction. The third and fourth phases of this dissertation focus on physiology-based modeling of the participants’ affective experiences during naturalistic interaction with the developed tutoring system. While computers and robots have begun to co-exist with humans and cooperatively share various tasks; they are still deficient in interpreting and responding to humans as emotional beings. Wearable biosensors that can be used for computerized emotion recognition offer great potential for addressing this issue. The third phase presents a Bluetooth-enabled eyewear – EmotiGO – for unobtrusive acquisition of a set of physiological signals, i.e., skin conductivity, photoplethysmography, and skin temperature, which can be used as autonomic readouts of emotions. EmotiGO is unobtrusive and sufficiently lightweight to be worn comfortably without interfering with the users’ usual activities. This phase presents the architecture of the device and results from testing that verify its effectiveness against an FDA-approved system for physiological measurement. The fourth and final phase attempts to model the students’ engagement levels using their physiological signals collected with EmotiGO during naturalistic interaction with the tutoring system developed in the second phase. Several physiological indices are extracted from each of the signals. The students’ engagement levels during the interaction with the tutoring system are rated by two trained coders using the video recordings of the instructional sessions. Supervised pattern recognition algorithms are subsequently used to map the physiological indices to the engagement scores. The results indicate that the trained models are successful at classifying participants’ engagement levels with the mean classification accuracy of 86.50%. These models are an important step toward an intelligent tutoring system that can dynamically adapt its pedagogical strategies to the affective needs of learners with ASD

Robot-assisted therapy for upper limb impairments in cerebral palsy:A scoping review and suggestions for future research

A growing number of studies investigate the use of robotics therapy for motor (re)habilitation with children with cerebral palsy (CP). Most of these studies use functional robots in very repetitive sessions. While the therapy is effective, very few studies employ social robots, which appears to be a missed opportunity to design more compelling and enjoyable sessions for the children. In this article, we will review robot-assisted upper limb motor (re)habilitation for children with CP. Previous reviews of robot-assisted therapy for CP had mostly focused on lower limbs, or the review was made from a medical point of view, with the sole concern being the therapy's effectiveness. Here, we focus our review on robot-assisted upper limb (re)habilitation and address human-robot interaction considerations. We searched PubMed, Scopus, and IEEE databases and argue that although this area of research is promising and already effective, it would benefit from the inclusion of social robots for a more engaging and enjoyable experience. We suggest four scenarios that could be developed in this direction. The goal of this article is to highlight the relevance of the past work and encourage the development of new ideas where therapy will socially engage and motivate children.</p

Emerging issues and current trends in assistive technology use 2007-1010: practising, assisting and enabling learning for all

Following an earlier review in 2007, a further review of the academic literature relating to the uses of assistive technology (AT) by children and young people was completed, covering the period 2007-2011. As in the earlier review, a tripartite taxonomy: technology uses to train or practise, technology uses to assist learning and technology uses to enable learning, was used in order to structure the findings. The key markers for research in this field and during these three years were user involvement, AT on mobile mainstream devices, the visibility of AT, technology for interaction and collaboration, new and developing interfaces and inclusive design principles. The paper concludes by locating these developments within the broader framework of the Digital Divide

Electromechanical and robotic devices for gait and balance rehabilitation of children with neurological disability: a systematic review

In the last two decades, a growing interest has been focused on gait and balance robot-assisted rehabilitation in children with neurological disabilities. Robotic devices allow the implementation of intensive, task-specific training fostering functional recovery and neuroplasticity phenomena. However, limited attention has been paid to the protocols used in this research framework. This systematic review aims to provide an overview of the existing literature on robotic systems for the rehabilitation of gait and balance in children with neurological disabilities and their rehabilitation applications. The literature search was carried out independently and synchronously by three authors on the following databases: MEDLINE, Cochrane Library, PeDro, Institute of Electrical and Electronics Engineers, ScienceDirect, and Google Scholar. The data collected included three subsections referring to clinical, technical, and regulatory aspects. Thirty-one articles out of 81 found on the primary literature search were included in the systematic review. Most studies involved children with cerebral palsy. Only one-third of the studies were randomized controlled trials. Overall, 17 devices (nine end-effector systems and eight exoskeletons) were investigated, among which only 4 (24%) were bore the CE mark. Studies differ on rehabilitation protocols duration, intensity, and outcome measures. Future research should improve both rehabilitation protocols\u2019 and devices\u2019 descriptions

Design strategies to improve patient motivation during robot-aided rehabilitation

BACKGROUND: Motivation is an important factor in rehabilitation and frequently used as a determinant of rehabilitation outcome. Several factors can influence patient motivation and so improve exercise adherence. This paper presents the design of two robot devices for use in the rehabilitation of upper limb movements, that can motivate patients during the execution of the assigned motor tasks by enhancing the gaming aspects of rehabilitation. In addition, a regular review of the obtained performance can reinforce in patients' minds the importance of exercising and encourage them to continue, so improving their motivation and consequently adherence to the program. In view of this, we also developed an evaluation metric that could characterize the rate of improvement and quantify the changes in the obtained performance. METHODS: Two groups (G1, n = 8 and G2, n = 12) of patients with chronic stroke were enrolled in a 3-week rehabilitation program including standard physical therapy (45 min. daily) plus treatment by means of robot devices (40 min., twice daily) respectively for wrist (G1) and elbow-shoulder movements (G2). Both groups were evaluated by means of standard clinical assessment scales and the new robot measured evaluation metric. Patients' motivation was assessed in 9/12 G2 patients by means of the Intrinsic Motivation Inventory (IMI) questionnaire. RESULTS: Both groups reduced their motor deficit and showed a significant improvement in clinical scales and the robot measured parameters. The IMI assessed in G2 patients showed high scores for interest, usefulness and importance subscales and low values for tension and pain subscales. CONCLUSION: Thanks to the design features of the two robot devices the therapist could easily adapt training to the individual by selecting different difficulty levels of the motor task tailored to each patient's disability. The gaming aspects incorporated in the two rehabilitation robots helped maintain patients' interest high during execution of the assigned tasks by providing feedback on performance. The evaluation metric gave a precise measure of patients' performance and thus provides a tool to help therapists promote patient motivation and hence adherence to the training program