Analiza učinka programa glazbene terapije na vještine izmjenjivanja-dijeljenja i izražavanja osjećaja djece s poremećajem iz spektra autizma

This study aimed to reveal the influence of a music therapy program on the development of abilities to take turn-share and express feelings of an eight-year-old child with autism spectrum disorder (ASD). This research was designed using mixed research methods, and carried out in a state school which had a source class, in 2016-2017 academic year. The music therapy program was developed by the researcher and applied to the participant in individual format. The participant was involved in 70 individual music therapy sessions held in the previously prepared room and 19 lessons in the subject’s classroom observed by the researcher, i.e. lesson observations. Music therapy sessions and lesson observations were quantitatively analyzed with the use of Oldfield’s Video Analysis Method. The results of the analysis revealed that the participant’s social skills of taking turn-sharing and expressing feelings improved both in music therapy and in lesson observations. The results of the research were discussed alongside the related literature.Cilj je ove studije ispitati utjecaj glazbene terapije na razvoj sposobnosti izmjenjivanja-dijeljenja i izražavanja osjećaja osmogodišnjega djeteta s poremećajem iz spektra autizma (ASD). Dizajn istraživanja koristi miješanu istraživačku metodu. Studija je provedena u državnoj školi koja ima ciljani razred, školske godine 2016./2017. Istraživačica je kreirala program glazbene terapije i primijenila ga u radu s ispitanikom u individualnom obliku. Ispitanik je sudjelovao u 70 individualnih sati glazbene terapije održanih u unaprijed pripremljenoj prostoriji i 19 nastavnih sati održanih u njegovoj učionici, tj. opservacija nastave. Sati glazbene terapije i opservacije nastave kvantitativno su obrađeni upotrebom Oldfield metode videoanalize. Rezultati analize pokazuju da su se socijalne vještine ispitanika izmjenjivanja-dijeljenja i izražavanja osjećaja poboljšale u objema istraživanjima: glazbenoj terapiji i opservacijama nastave. U radu se raspravlja o rezultatima istraživanja u kontekstu relevantne literature

Engaging autistic children in imitation and turn-taking games with multiagent system of interactive lighting blocks

In this paper game scenarios that aim to establish elements of cooperative play such as imitation and turn taking between children with autism and a caregiver are investigated. Multiagent system of interactive blocks is used to facilitate the games. The training elements include verbal description followed by imitation of video-modeled play episodes. By combining this method with the tangible multiagent platform of interactive blocks (i-blocks) children with autism could imitate play episodes that involved turn taking with a caregiver. The experiment showed that most of the children managed to imitate the play scenarios after video modeling, and repeat the behaviors with the tangible and appealing block platform. When all the actions were well understood by the autistic children, they performed willingly turn taking cooperative behaviors, which they normally do not do

Engaging autistic children in imitation and turn-taking games with multiagent system of interactive lighting blocks

In this paper game scenarios that aim to establish elements of cooperative play such as imitation and turn taking between children with autism and a caregiver are investigated. Multiagent system of interactive blocks is used to facilitate the games. The training elements include verbal description followed by imitation of video-modeled play episodes. By combining this method with the tangible multiagent platform of interactive blocks (i-blocks) children with autism could imitate play episodes that involved turn taking with a caregiver. The experiment showed that most of the children managed to imitate the play scenarios after video modeling, and repeat the behaviors with the tangible and appealing block platform. When all the actions were well understood by the autistic children, they performed willingly turn taking cooperative behaviors, which they normally do not do

Charlie: A New Robot Prototype for Improving Communication and social Skills in Children with Autism and a New Single-point Infrared Sensor Technique for Detecting bBeathing and Heart Rate Remotely

This research delivers a new, interactive game-playing robot named CHARLIE and a novel technique for remotely detecting breathing and heart rate using a single-point, thermal infrared sensor (IR). The robot is equipped with a head and two arms, each with two degrees of freedom, and a camera. We trained a human hands classifier and used this classifier along with a standard face classifier to create two autonomous interactive games: single-player ( Imitate Me, Imitate You ) and two-player ( Pass the Pose ). Further, we developed and implemented a suite of new interactive games in which the robot is teleoperated by remote control. Each of these features has been tested and validated through a field study including eight children diagnosed with autism and speech delays. Results from that study show that significant improvements in speech and social skills can be obtained when using CHARLIE with the methodology described herein. Moreover, gains in communication and social interaction are observed to generalize from child-to-robot to co-present others through the scaffolding of communication skills with the systematic approach developed for the study. Additionally, we present a new IR system that continuously targets the sub-nasal region of the face and measures subtle temperature changes corresponding to breathing and cardiac pulse. This research makes four novel contributions: (1) A low-cost, field-tested robot for use in autism therapy, (2) a suite of interactive robot games, (3) a hand classifier created for performing hand detection during the interactive games, and (4) an IR sensor system which remotely collects temperatures and computes breathing and heart rate. Interactive robot CHARLIE is physically designed to be aesthetically appealing to young children between three and six years of age. The hard, wood and metal robot body is covered with a bright green, fuzzy material and additional padding so that it appears toylike and soft. Additionally, several structural features were included to ensure safety during interactive play and to enhance the robustness of the robot. Because children with autism spectrum disorder (ASD) often enjoy exploring new or interesting objects with their hands, the robot must be able to withstand a moderate amount of physical manipulation without causing injury to the child or damaging the robot or its components. CHARLIE plays five distinct interactive games that are designed to be entertaining to young children, appeal to children of varying developmental ability and promote increased speech and social skill through imitation and turn-taking. Remote breathing and heart rate detection Stress is a compounding factor in autism therapy which can inhibit progress toward specific therapeutic goals. The ability to non-invasively detect physical indicators of increasing stress, especially when they can be correlated to specific activities and measured in terms of length and frequency, can relay important metrics about the antecedents that cause stress for a particular child and can be used to help automate the evaluation of a child\u27s progress between sessions. Further, collecting and measuring critical physiological indicators such as breathing and heart rate can enable robots to adjust their behavior based on the perceived emotional, psychological or physical state of their user. The utility and acceptance of robots can be further increased when they are able to learn typical physiological patterns and use these patterns as a baseline for identifying anomalies or possible warning signs of various problems in their human users. We present a new technique for remotely collecting and analyzing breathing and heart rates in real time using an autonomous, low cost infrared (IR) sensor system. This is accomplished by continuously targeting a high precision IR sensor, tracking changes in the sub-nasal skin surface temperature and employing a sinusoidal curve-fitting function, Fast Fourier Transform (FFT), and Discrete Wavelet Transform (DWT) to extract the breathing and heart rate from recorded temperatures

Xylo-Bot: A Therapeutic Robot-Based Music Platform for Children with Autism

Children with Autism Spectrum Disorder (ASD) experience deficits in verbal and nonverbal communication skills, including motor control, emotional facial expressions, and eye gaze / joint attention. This Ph.D. dissertation focuses on studying the feasibility and effectiveness of using a social robot, called NAO, and a toy music instrument, xylophone, at modeling and improving the social responses and behaviors of children with ASD. In our investigation, we designed an autonomous social interactive music teaching system to fulfill this mission. A novel modular robot-music teaching system consisting of three modules is presented. Module 1 provides an autonomous self-awareness positioning system for the robot to localize the instrument and make a micro adjustment for the arm joints to play the note bars properly. Module 2 allows the robot to be able to play any customized song per user’s request. This design provides an opportunity to translate songs into C-major or a-minor with a set of hexadecimal numbers without music experience. After the music score converted robot should be able to play it immediately. Module 3 is designed for providing real-life music teaching experience for the users. Two key features of this module are a) music detection and b) smart scoring and feedback . Short-time Fourier transform and Levenshtein distance are adapted to fulfill the design requirements, which allow the robot to understand music and provide a proper dosage of practice and oral feedback to users. A new instrument has designed to present better emotions from music due to the limitation of the original xylophone. This new programmable xylophone can provide a more extensive frequency range of notes, easily switch between the Major and Minor keys, extensively easy to control, and have fun with it as an advanced music instrument. Because our initial intention has been to study emotion in children with autism, an automated method for emotion classification in children using electrodermal activity (EDA) signals. The time-frequency analysis of the acquired raw EDAs provides a feature space based on which different emotions can be recognized. To this end, the complex Morlet (C-Morlet) wavelet function is applied to the recorded EDA signals. The dataset used in this research includes a set of multimodal recordings of social and communicative behavior as well as EDA recordings of 100 children younger than 30 months old. The dataset is annotated by two experts to extract the time sequence corresponding to three primary emotions, including “Joy”, “Boredom”, and “Acceptance”. Various experiments are conducted on the annotated EDA signals to classify emotions using a support vector machine (SVM) classifier. The quantitative results show that emotion classification performance remarkably improves compared to other methods when the proposed wavelet-based features are used. By using this emotion classification, emotion engagement during sessions, and feelings between different music can be detected after data analysis. NAO music education platform will be thought-about as a decent tool to facilitate improving fine motor control, turn-taking skills, and social activities engagement. Most of the ASD youngsters began to develop the strike movement within the two initial intervention sessions; some even mastered the motor ability throughout the early events. More than half of the subjects could dominate proper turn-taking after few sessions. Music teaching is a good example for accomplishing social skill tasks by taking advantage of customized songs selected by individuals. According to researcher and video annotator, majority of the subjects showed high level of engagement for all music game activities, especially with the free play mode. Based on the conversation and music performance with NAO, subjects showed strong interest in challenging the robot with a friendly way

Influence of technology on social interaction and play in autistic children

The social and communication differences associated with autism can make engaging in social play difficult for autistic children. However, it has been suggested that digital technologies could motivate or inspire autistic children to communicate with other people and engage in collaborative play. This conflicts with the increasing concerns from parents and practitioners around the impact of technologies on social interaction in children and young people, which could be exacerbated in autistic children due to the aforementioned difficulties in social interaction. This thesis includes five studies which aim to explore whether and how technology can provide opportunities for autistic children to engage in social play with peers. Chapter 1 outlines the context and rationale for exploring the influence of technology on social play and interaction in autistic children. In neurotypical children, technology is likely to have small or negligible effects on social development. A number of studies have shown that features of technology, such as the interface and the software design, can encourage social interaction. Autism is associated with social differences and difficulties in social interaction, and a number of technologies have been designed to teach or mediate social interaction in autistic children, with relative success. A further number of studies have suggested that autistic children are more likely to engage in social play and interaction when using digital technologies. Chapter 2 provides a brief overview of key issues in autism research and justifies some of the research methodologies chosen in the remainder of the thesis. Chapter 3 explored how educational practitioners used technology in classrooms with autistic students. In an online survey, practitioners said that they more frequently used technology to teach social skills to autistic students, rather than to facilitate peer interactions. Respondents also said that technologies such as smart boards, tablets, and computers were used more widely than more recently developed technologies, such as tangibles and robotics. These results were followed up by focus groups, where practitioners highlighted that different features of interfaces made children more aware of social partners and could sometimes encourage or inhibit interactions depending on children’s social interaction style and technological preferences. According to practitioners, children who were interested in technology would be more likely to socially benefit from it, than others who were less interested in technology. Chapters 4 and 5 reported on a design-based research study, in collaboration with educational practitioners, to explore the influence of different technologies and classroom environments on children’s social interactions and play. The main finding was that children interacted differently both with technologies and with other people, and that different apps and technological interfaces produced unique patterns of social interactions. Children engaged in more social play with peers while using the iPad and Code-A-Pillar technologies, and more social play with adults while using Osmo. Novelty appeared to have the strongest environmental influence on social interactions in digital environments, even more than creating collaborative spaces and having practitioners directing children’s social play. Chapters 6 and 7 compared social play and joint engagement in pairs of children while they played with digital and non-digital toys and explored the effect of enforced collaboration. The results showed that children engaged in more social play and joint engagement when using digital toys. Enforcing collaboration led to more interactive play and joint engagement in both digital and non-digital conditions. This suggests that technology itself can strongly mediate social interaction in autistic children, perhaps more than the children’s own interests and social interaction styles. Together, the studies within this thesis highlight that there are many ways in which autistic children engage with other people while using digital technologies, and many opportunities to foster these interactions in classroom settings. In conclusion, as summarised in chapter 8, technologies do influence social interaction in autistic children, but so do children’s social interaction styles and preferences, the wider classroom environment including adult roles, and so do particular technological interfaces and software. In terms of how technology mediates interaction, it can provide a socially inclusive space where children can jointly engage with others on devices and activities which interest them, provide an engaging environment where others can scaffold interaction (i.e. practitioners), or the technology itself can mediate child-led interactions through children’s interests