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    Social robots and teaching music to autistic children: Myth or reality?

    , Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1 November 2016 through 3 November 2016 ; Volume 9979 LNAI , 2016 , Pages 541-550 ; 03029743 (ISSN) ; 9783319474366 (ISBN) Taheri, A ; Meghdari, A ; Alemi, M ; Pouretemad, Hr ; Poorgoldooz, P ; Roohbakhsh, M ; Sharif University of Technology
    Springer Verlag  2016
    Abstract
    Music-based therapy is an appropriate tool to facilitate multisystem development in children with autism. The focus of this study is to implement a systematic and hierarchical music-based scenario in order to teach the fundamentals of music to children with autism through a social robot. To this end, we have programmed a NAO robot to play the xylophone and the drum. After running our designed robot-assisted clinical interventions on three high-functioning and one low functioning autistic children, fairly promising results have been observed. We indicated that the high-functioning participants have learned how to play the musical notes, short sentences, and simple rhythms. Moreover, the... 

    “Xylotism”: A tablet-based application to teach music to children with autism

    , Article 9th International Conference on Social Robotics, ICSR 2017, 22 November 2017 through 24 November 2017 ; Volume 10652 LNAI , 2017 , Pages 728-738 ; 03029743 (ISSN); 9783319700212 (ISBN) Tavakol Elahi, M ; Habibnejad Korayem, A ; Shariati, A ; Meghdari, A ; Alemi, M ; Ahmadi, E ; Taheri, A ; Heidari, R ; Sharif University of Technology
    Springer Verlag  2017
    Abstract
    Technology is inevitable, and its role for clinical therapists and specialists cannot be ignored. The promising movement towards computer-based interventions, specifically the use of tablets as an effective and newly developed learning device for children with autism spectral disorder (ASD) highlights the role of technology in addressing the shortcomings of conventional therapy methods. In this paper, we present a new application, named as Xylotism, which is an interactive game to improve learning and teach music to children with autism spectrum disorder. The game can be played with/without parents/therapists’ involvement, which increases its usefulness and effectiveness. We have... 

    Social robots as assistants for autism therapy in Iran: Research in progress

    , Article 2014 2nd RSI/ISM International Conference on Robotics and Mechatronics, ICRoM 2014 ; Oct , 2014 , p. 760-766 Taheri, A. R ; Alemi, M ; Meghdari, A ; Pouretemad, H. R ; Basiri, N. M ; Sharif University of Technology
    Abstract
    Autistic children are often impaired in initiating and responding to Joint Attention. In recent years, there has been an increase in the application of robots in diagnosis and treatment of autism. The purpose of the current research has been primarily to originate the proper therapeutic scenarios and to implement two interactive humanoid robots as therapy assistants in autism treatment in Iran. To this end, the humanoid robots were programmed and teleoperated via Microsoft Kinect Sensor and PhantomOmni Haptic Robot to elicit reactions consisting of imitation of humans by the humanoid robots and vice versa. In this paper, we elaborate on the therapeutic items that we have designed to improve... 

    Impacts of using a social robot to teach music to children with low-functioning autism

    , Article Paladyn ; Volume 12, Issue 1 , 2021 , Pages 256-275 ; 20814836 (ISSN) Taheri, A ; Shariati, A ; Heidari, R ; Shahab, M ; Alemi, M ; Meghdari, A ; Sharif University of Technology
    De Gruyter Open Ltd  2021
    Abstract
    This article endeavors to present the impact of conducting robot-assisted music-based intervention sessions for children with low-functioning (LF) autism. To this end, a drum/xylophone playing robot is used to teach basic concepts of how to play the instruments to four participants with LF autism during nine educational sessions. The main findings of this study are compared to similar studies conducted with children with high-functioning autism. Our main findings indicated that the stereotyped behaviors of all the subjects decreased during the course of the program with an approximate large Cohen’s d effect size. Moreover, the children showed some improvement in imitation, joint attention,... 

    Utilizing social virtual reality robot (V2R) for music education to children with high-functioning autism

    , Article Education and Information Technologies ; Volume 27, Issue 1 , 2022 , Pages 819-843 ; 13602357 (ISSN) Shahab, M ; Taheri, A ; Mokhtari, M ; Shariati, A ; Heidari, R ; Meghdari, A ; Alemi, M ; Sharif University of Technology
    Springer  2022
    Abstract
    Virtual Reality (VR) technology is a growing technology that has been used in various fields of psychology, education, and therapy. One group of potential users of VR are children with autism who need education and have poor social interactions; this technology could help them improve their social skills through real-world simulation. In this study, we evaluated the feasibility of conducting virtual music education programs with automatic assessment system for children with autism at treatment/research centers without the need to purchase a robot, resulting in the possibility of offering schedules on a larger scale and at a lower cost. Intervention sessions were conducted for five children... 

    Common Areas of Language Impairment in Persian-speaking Autistic Children

    , M.Sc. Thesis Sharif University of Technology Mahabadi, Sara (Author) ; Khosravizadeh, Parvaneh (Supervisor)
    Abstract
    In qualitative content analysis research with the aim of identifying areas of language impairmenthigh-functioning Persian-speaking autistic children, ten subjects were observed during fifteen training sessions which were the cognitive block of a three-block training program. Each session lasted 90 minutes and was video recorded. Prior to this, focus group interviews with specialists and semi-structured interviews with mothers and parallel to that focus group interviews with mothers were handled all of which were audio recorded. After two levels of initial and second coding, a final list of areas of impairment in the language of high-functioning Persian-speaking autistic children, that... 

    Analysis of Functional Connectivity Among Brain Networks Using FMRI

    , M.Sc. Thesis Sharif University of Technology Rahmati Kargar, Behnam (Author) ; Vosughi Vahdat, Bijan (Supervisor) ; Amini, Arash (Supervisor)
    Abstract
    Development of the fMRI imaging method gives the scientists the opportunity to record functional images from the brain with high spatial resolution and several researches were conducted on this field. Autistic people’s brain has functional differences with normal people. In this paper these differences have been studied. At first fMRI datasets from autistic subjects and control have been recorded and preprocessed. Then the independent components from these datasets have been extracted using group ICA method. Any independent component is an image depicting a brain network. There is a time series for each image which shows the temporal variations of each component. In the next step, the... 

    Social virtual reality robot (V2R): a novel concept for education and rehabilitation of children with autism

    , Article 5th RSI International Conference on Robotics and Mechatronics, IcRoM 2017, 25 October 2017 through 27 October 2017 ; 2018 , Pages 82-87 ; 9781538657034 (ISBN) Shahab, M ; Taheri, A ; Hosseini, S. R ; Mokhtari, M ; Meghdari, A ; Alemi, M ; Pouretemad, H ; Shariati, A ; Pour, A. G ; Sharif University of Technology
    Abstract
    In this paper, we have presented a novel virtual reality setup with the ability to teach music to children with autism as well as perform automatic assessment of their behaviors. This setup contains Social Virtual Reality Robots (V2Rs) and virtual musical instruments (i.e. xylophone and drum). After conducting a game-session pilot study, we observed that the acceptance rate of the virtual reality headset is about 65% among children with autism, while all of the typically developing children attending the session used the headset. Furthermore, using statistical analysis, it is indicated that the performance of children with autism in music assignments was significantly weaker than their... 

    Human–robot interaction in autism treatment: a case study on three pairs of autistic children as twins, siblings, and classmates

    , Article International Journal of Social Robotics ; Volume 10, Issue 1 , January , 2018 , Pages 93-113 ; 18754791 (ISSN) Taheri, A ; Meghdari, A ; Alemi, M ; Pouretemad, H ; Sharif University of Technology
    Springer Netherlands  2018
    Abstract
    In this paper, three pairs of children with autism include a pair of twins, two siblings, and two classmates were enrolled in a 12-session robot-assisted group-games program. As many environmental factors were for the most part the same for the siblings as well as genetic factors for the twins, we were able to observe/compare the effect of the designed games on the participants individually and in paired-groups. The results indicated that all participants’ autism severity decreased after the course of the program. Improvement in social skills, social participation/avoidance, and detrimental social behaviors were also observed in the participants with high-functioning autism with close to... 

    The Effects of Robot Assisted Language Learning (RALL)on Iranian High-functioning Autistic Children’s Social Skills and English Vocabulary Learning and Retention

    , M.Sc. Thesis Sharif University of Technology Mahboub Basiri, Nasim (Author) ; Alemi, Minoo (Supervisor) ; Meghdari, Ali (Co-Advisor)
    Abstract
    The present case study investigates the effect of applying a humanoid robot as a teacher- assistant to teach a foreign language (English in this case) to Iranian children with autism. Two groups of three male high-functioning autistic students (6-10 years old) with little or no background in English participated in the current study. The humanoid robot NAO made by Aldebaran Robotics was used as a teacher assistant to teach English to the Robot Assisted Language Learning (RALL) group. The non-RALL group received the same lessons simply without the presence of the robot in teaching sessions. However, the non-RALL group also had the chance to interact with the robot through some robotic games... 

    Modeling, Design, and the Application of Humanoid Robots in the Treatment of Children with Autism

    , Ph.D. Dissertation Sharif University of Technology Taheri, Alireza (Author) ; Meghdari, Ali (Supervisor) ; Pouretemad, Hamid Reza (Co-Advisor) ; Alemi, Minoo (Co-Advisor)
    Abstract
    Statistics have shown an endemic worldwide increase of Autistic Spectrum Disorders (ASD) since the 1960s, Iran also faces the same problem. Autistic disorders are characterized by three major behavioral disorders: impaired social interaction, impaired communication, and impaired imagination and social creativity. The usage of robots in autism diagnosis and treatment has been increasing in recent years. In this study, our objective (as one of the pioneers in Iran) is to explore the clinical application of two interactive social humanoid robots (NAO and ALICE with the Iranian names of NIMA and MINA) as medical assistants in the treatment and education of children with autism in order to... 

    Multilayer Network Approach to Brain Connectivity Analysis in Cognitive Disorder

    , M.Sc. Thesis Sharif University of Technology Talezade Lari, Emran (Author) ; Rabiee, Hamid Reza (Supervisor) ; Manzori, Mohammad Taghi (Supervisor)
    Abstract
    Brain is the most complex part of the human body. This three pound organ acting as seed of intelligence, database of memories, interpreter of the senses, and managing our movement. Network neuroscience plays an important role in revealing hidden aspects of brain functions. Recently, multilayer network models have been proposed to achieve a deeper analysis on the brain networks. Multilayer network is a framework that can represent multiple relations between nodes. In a single layer brain network, different shared information methods can be used to find connection between Regions of Interests (ROIs), but in a multilayer approach, ROIs can have multiple connections in different domains such as... 

    A Systematic Approach for Biomarker Identification in Autism Spectrum Disorder based on Machine learning

    , M.Sc. Thesis Sharif University of Technology Ashraf Talesh, Mahdi (Author) ; Jafari Siavoshani, Mahdi (Supervisor) ; Kavousi, Kaveh (Co-Supervisor) ; Ohadi, Mina (Co-Supervisor)
    Abstract
    Autism spectrum disorder (ASD) is a strong genetic perturbation that encompasses a wide range of clinical symptoms, including functional at different regions of the brain, repetitive behaviors, and interests, weaknesses in social relationships, some sensitivities to environmental factors and etc. Genetic complexity and the impact of environmental factors put the disease in the category of Level 1 complex developmental disorders.We proposed a pilot, combined, and highly effective structure to identify biomarkers in the autism spectrum disorder that could be extended to other diseases that have a similar genetic architecture with autism. We also develop a Gene-tissue interaction network to... 

    Dynamic Functional Connectivity in Autism Spectrum Disorder Using Resting-State fMRI

    , M.Sc. Thesis Sharif University of Technology Jalil Piran, Fardin (Author) ; Fatemizadeh, Emadeddin (Supervisor)
    Abstract
    Autism Spectrum Disorder (ASD) is a group of neurodevelopmental disorders that cause repetitive behaviors and social and communication skills abnormalities. Autistic Disorder(AD) is one of the disorders in ASD that is being investigated in this study. There has been an increase in research about AD in recent years due to the increasing AD prevalence and the high autistic living costs. The dynamic functional connectivity between healthy and autistic groups has been analyzed by using graph theory. The brain is modeled as a dynamic graph using resting-state fMRI. The graph theory metric is calculated in the dynamic graph of each subject, and the distinction of the two groups is checked using... 

    Investigation of brain default network's activation in autism spectrum disorders using group independent component analysis

    , Article 2014 21st Iranian Conference on Biomedical Engineering, ICBME 2014 ; 2014 , p. 177-180 Alizadeh, A ; Fatemizadeh, E ; Deevband, M. R ; Sharif University of Technology
    Abstract
    Autism Spectrum Disorders (ADS), with unknown etiology, is one of the most understudy fields of research worldwide that requires complicated and delicate analytical study methods. The purpose of this study was to compare active regions of Brain Default Mode Network (DMN) using Group Independent Component Analysis (6ICA) among resting state patients with Autism Disorder and healthy subjects. Default Mode Network consists of posterior cingulate cortex (PCC), lateral parietal cortex/angular gyrus retrosplenial cortex, medial prefrontal cortex, superior frontal gyrus, parahippocampal gyrus and temporal lobe shows more prominent activity in passive resting conditions. The diagnosis of autism... 

    Investigation of Brain Default Network's activation in autism spectrum disorders using Group Independent Component Analysis

    , Article 2014 21st Iranian Conference on Biomedical Engineering, ICBME 2014, 26 November 2014 through 28 November 2014 ; Nov , 2014 , Pages 177-180 ; 9781479974177 (ISBN) Alizadeh, A ; Fatemizadeh, E ; Deevband, M. R ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2014
    Abstract
    Autism Spectrum Disorders (ADS), with unknown etiology, is one of the most understudy fields of research worldwide that requires complicated and delicate analytical study methods. The purpose of this study was to compare active regions of Brain Default Mode Network (DMN) using Group Independent Component Analysis (6ICA) among resting state patients with Autism Disorder and healthy subjects. Default Mode Network consists of posterior cingulate cortex (PCC), lateral parietal cortex/angular gyrus retrosplenial cortex, medial prefrontal cortex, superior frontal gyrus, parahippocampal gyrus and temporal lobe shows more prominent activity in passive resting conditions. The diagnosis of autism... 

    Functional Connectivity Network in Rest-State fMRI Baseline in High Functioning Autism Disorder

    , M.Sc. Thesis Sharif University of Technology Akbarian Aghdam, Amir (Author) ; Fatemizadeh, Emad (Supervisor)
    Abstract
    Autism spectrum disorders (ASD) have been defined as developmental disorders characterized by abnormalities in social interaction, communication skills, and behavioral flexibility. Over the past decades, studies using various genetic, neurobiological, cognitive and behavioral approaches have sought a single explanation for the heterogeneous manifestations of ASD, but no consensus on the etiology of ASD has emerged. Further studies aim to clarify the mechanism of disease.
    Functional Magnetic Resonance Imaging (fMRI) is a new way of imaging which evaluates activity of brain by measuring magnetic difference caused by oscillation in blood oxygen level. fMRI has been widely used in recent... 

    Design and Impacts of Virtual Reality Games on Social and Cognitive Skills of Children with Autism Spectrum Disorder

    , M.Sc. Thesis Sharif University of Technology Abbasi, Sajjad (Author) ; Taheri, Alireza (Supervisor) ; Meghdari, Ali (Supervisor)
    Abstract
    Autism is a neurodevelopmental disorder for which there is no definitive cure and it is increasing every year for people with this disorder. In the last decade, the use of virtual environment to improve the skills of people on the autism spectrum has increased. In this research, a semi-intelligent algorithm was designed for a virtual reality game that could provide a more appropriate step to the user according to the user's responses. Our focus is on designing games to strengthen the child in terms of shared attention and eye contact. In other words, we seek to create a virtual environment with the ability to intelligently adapt to interact with our user and turn it into a suitable coaching... 

    Human-Robot Facial Expression Interaction Using Kinect and Humanoid

    , M.Sc. Thesis Sharif University of Technology Ghorbandaei Pour, Ali (Author) ; Meghdari, Ali (Supervisor) ; Alemi, Minoo (Co-Supervisor)
    Abstract
    From the creation of the first robots, researchers have been fascinated by the possibility of interaction between a robot and its environment, by the possibility of robots interacting with each other and with humans. The common, underlying assumption is that humans prefer to interact with machines in the same way that they interact with other people. In this work, an assistant robot is developed based on a commercial platform, known as Alice R-50 (with the Iranian name of Mina). Alice is designed specifically for human-robot social interaction and has been used widely for studies on developmental and social robotics. It is used to improve and encourage the development of communication and... 

    Automated detection of autism spectrum disorder using a convolutional neural network

    , Article Frontiers in Neuroscience ; Volume 13 , 2020 Sherkatghanad, Z ; Akhondzadeh, M ; Salari, S ; Zomorodi Moghadam, M ; Abdar, M ; Acharya, U. R ; Khosrowabadi, R ; Salari, V ; Sharif University of Technology
    Frontiers Media S.A  2020
    Abstract
    Background: Convolutional neural networks (CNN) have enabled significant progress in speech recognition, image classification, automotive software engineering, and neuroscience. This impressive progress is largely due to a combination of algorithmic breakthroughs, computation resource improvements, and access to a large amount of data. Method: In this paper, we focus on the automated detection of autism spectrum disorder (ASD) using CNN with a brain imaging dataset. We detected ASD patients using most common resting-state functional magnetic resonance imaging (fMRI) data from a multi-site dataset named the Autism Brain Imaging Exchange (ABIDE). The proposed approach was able to classify ASD...