Therapeutic and educational objectives in robot assisted play for children with autism

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ROMAN.2009.5326251This article is a methodological paper that describes the therapeutic and educational objectives that were identified during the design process of a robot aimed at robot assisted play. The work described in this paper is part of the IROMEC project (Interactive Robotic Social Mediators as Companions) that recognizes the important role of play in child development and targets children who are prevented from or inhibited in playing. The project investigates the role of an interactive, autonomous robotic toy in therapy and education for children with special needs. This paper specifically addresses the therapeutic and educational objectives related to children with autism. In recent years, robots have already been used to teach basic social interaction skills to children with autism. The added value of the IROMEC robot is that play scenarios have been developed taking children's specific strengths and needs into consideration and covering a wide range of objectives in children's development areas (sensory, communicational and interaction, motor, cognitive and social and emotional). The paper describes children's developmental areas and illustrates how different experiences and interactions with the IROMEC robot are designed to target objectives in these areas

Therapeutic and educational objectives in robot assisted play for children with autism

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ROMAN.2009.5326251This article is a methodological paper that describes the therapeutic and educational objectives that were identified during the design process of a robot aimed at robot assisted play. The work described in this paper is part of the IROMEC project (Interactive Robotic Social Mediators as Companions) that recognizes the important role of play in child development and targets children who are prevented from or inhibited in playing. The project investigates the role of an interactive, autonomous robotic toy in therapy and education for children with special needs. This paper specifically addresses the therapeutic and educational objectives related to children with autism. In recent years, robots have already been used to teach basic social interaction skills to children with autism. The added value of the IROMEC robot is that play scenarios have been developed taking children's specific strengths and needs into consideration and covering a wide range of objectives in children's development areas (sensory, communicational and interaction, motor, cognitive and social and emotional). The paper describes children's developmental areas and illustrates how different experiences and interactions with the IROMEC robot are designed to target objectives in these areas.Final Published versio

Tactile Interactions with a Humanoid Robot : Novel Play Scenario Implementations with Children with Autism

Acknowledgments: This work has been partially supported by the European Commission under contract number FP7-231500-ROBOSKIN. Open Access: This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.The work presented in this paper was part of our investigation in the ROBOSKIN project. The project has developed new robot capabilities based on the tactile feedback provided by novel robotic skin, with the aim to provide cognitive mechanisms to improve human-robot interaction capabilities. This article presents two novel tactile play scenarios developed for robot-assisted play for children with autism. The play scenarios were developed against specific educational and therapeutic objectives that were discussed with teachers and therapists. These objectives were classified with reference to the ICF-CY, the International Classification of Functioning – version for Children and Youth. The article presents a detailed description of the play scenarios, and case study examples of their implementation in HRI studies with children with autism and the humanoid robot KASPAR.Peer reviewedFinal Published versio

The power of affective touch within social robotics

There have been many leaps and bounds within social robotics, especially within human-robot interaction and how to make it a more meaningful relationship. This is traditionally accomplished through communicating via vision and sound. It has been shown that humans naturally seek interaction through touch yet the implications on emotions is unknown both in human-human interaction and social human-robot interaction. This thesis unpacks the social robotics community and the research undertaken to show a significant gap in the use of touch as a form of communication. The meaning behind touch will be investigated and what implication it has on emotions. A simplistic prototype was developed focusing on texture and breathing. This was used to carry out experiments to find out which combination of texture and movement felt natural. This proved to be a combination of synthetic fur and 14 breaths per minute. For human’s touch is said to be the most natural way of communicating emotions, this is the first step in achieving successful human-robot interaction in a more natural human-like way

Enhance the Language Ability of Humanoid Robot NAO through Deep Learning to Interact with Autistic Children

Autism spectrum disorder (ASD) is a life-long neurological disability, and a cure has not yet been found. ASD begins early in childhood and lasts throughout a person’s life. Through early intervention, many actions can be taken to improve the quality of life of children. Robots are one of the best choices for accompanying children with autism. However, for most robots, the dialogue system uses traditional techniques to produce responses. Robots cannot produce meaningful answers when the conversations have not been recorded in a database. The main contribution of our work is the incorporation of a conversation model into an actual robot system for supporting children with autism. We present the use a neural network model as the generative conversational agent, which aimed at generating meaningful and coherent dialogue responses given the dialogue history. The proposed model shares an embedding layer between the encoding and decoding processes through adoption. The model is different from the canonical Seq2Seq model in which the encoder output is used only to set-up the initial state of the decoder to avoid favoring short and unconditional responses with high prior probability. In order to improve the sensitivity to context, we changed the input method of the model to better adapt to the utterances of children with autism. We adopted transfer learning to make the proposed model learn the characteristics of dialogue with autistic children and to solve the problem of the insufficient corpus of dialogue. Experiments showed that the proposed method was superior to the canonical Seq2sSeq model and the GAN-based dialogue model in both automatic evaluation indicators and human evaluation, including pushing the BLEU precision to 0.23, the greedy matching score to 0.69, the embedding average score to 0.82, the vector extrema score to 0.55, the skip-thought score to 0.65, the KL divergence score to 5.73, and the EMD score to 12.21

Trust in Human-Robot Interaction Within Healthcare Services: A Review Study

There has always been a dilemma of the extent to which human can rely on machines in different activities of daily living. Ranging from riding on a self-driving car to having an iRobot vacuum clean the living room. However, when it comes to healthcare settings where robots are intended to work next to human, making decision gets difficult because repercussions may jeopardize people’s life. That has led scientists and engineers to take one step back and think out of the box. Having concept of trust under scrutiny, this study helps deciphering complex human-robot interaction (HRI) attributes. Screening essential constituents of what shapes the trust in human mind as s/he is working with a robot will provide a more in-depth insight through how to build and consolidate the trust. In physiotherapeutic realm, this feeds into improving safety protocols and level of comfort; as well as increasing the efficacy of robot-assisted physical therapy and rehabilitation. This paper provides a comprehensive framework for measuring trust through introducing several scenarios that are prevalent in rehabilitation environment. This proposed framework highlights importance of clear communication between physicians and how they expect robot to intervene in a human centered task. In addition, it reflects on patients’ perception of robot assistance. Ultimately, recommendations are made in order to maximize trust earned from the patients which then feeds into enhancing efficacy of the therapy. This is an ongoing study; authors are working with a local hospital to implement the know in a real-world application