Tojisha-Kenkyu of autism spectrum disorders

Accumulating evidence suggests behavioral and genetic fractionation of the autistic traits. Above it, ethnographic researches that document how the sociality of children with autism varies across different situational conditions, depict autistic sociality not as an oxymoron but, rather, as a reality. Given the discussion above, it is important to do case-based studies on the assumption of heterogeneity of sociality and of autism. In addition, subjective experience is an important outcome variable whenever considering support. As a candidate of the research methods that meet the above conditions, we would like to introduce Tojisha-Kenkyu. In a nutshell, ‘Tojisha-Kenkyu’ is studying oneself through communication with others who share similar experiences. We introduce Ayaya’s Tojisha-Kenkyu and Necco Tojisha-Kenkyu meeting as examples of Tojisha-Kenkyu on autism spectrum disorders (ASD), which illustrate that Tojisha-Kenkyu has not only recuperative effects but also academic potentials changing the concept of ASD.     

Towards co-design with users who have autism spectrum disorders

People with cognitive disorders, such as autism or Asperger’s syndrome, face many barriers when being involved in the co-design of information and communications technologies (ICT). Cognitive disorders may require that co-design techniques be modified to fit with individual abilities. Up until recently, with technology design, purpose and use being in the hands of ‘experts’ there was little opportunity for customisation. However, ICT bring together various threads that make open many new possibilities. Not only are technologies cheaper, more powerful and more available than ever, but now parents, support agencies and people with autism spectrum disorders expect information technologies to be part of their worlds, and they have the capacity to participate in co-design for customisation. However, co-design techniques have not evolved to the extent that they capture this potential democratisation of the ICT. This paper reports on an investigation of the potential to develop a set of guidelines for co-design techniques to enable people with autism spectrum disorders to participate in ICT design.     

Attention to the model's face when learning from video modeling examples in adolescents with and without autism spectrum disorder

We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate whether we would replicate this finding in adolescents (prevocational education) and to establish how adolescents with autism spectrum disorder, who have been found to look less at faces generally, would process video examples in which the model's face is visible. Results showed that typically developing adolescents who did see the model's face paid significantly less attention to the task area than typically developing adolescents who did not see the model's face. Adolescents with autism spectrum disorder paid less attention to the model's face and more to the task demonstration area than typically developing adolescents who saw the model's face. These differences in viewing behavior, however, did not affect learning outcomes. This study provides further evidence that seeing the model's face in video examples affects students' attention but not their learning outcomes.     

Towards physician's experience: Development of machine learning model for the diagnosis of autism spectrum disorders based on complex T-spherical fuzzy-weighted zero-inconsistency method

Autism spectrum disorders (ASD) are a diverse group of conditions characterized by difficulty with social interaction and communication. ASD is expected to be a high-risk disease. Recent studies have focused on the diagnosis based on sociodemographic and family characteristics factors. The development of a diagnosis model, which is primarily based on machine learning methods, has been carried out to alleviate the detection of autism. However, they neglected the importance of ASD features in a training dataset, especially because some features have different levels of contributions to the processing data and possess more relevancies to the classification information than others. Such limitations use preprocessing techniques for the construction of the machine learning model, but the role of the physician's experience towards feature contributions remains limited. However, for certain autism datasets, the relevancies of sociodemographic and family characteristic feature concerning the given class labels should be considered. Accordingly, this study developed a new machine learning model for the diagnosis of ASD based on multi-criteria decision-making (MCDM). By using three methodology phases, the model combines two representative theories, namely, MCDM and machine learning. The identification phase for imbalance ASD dataset and application of pre-possessing stages by imputing missing values, feature selection of sociodemographic and family characteristics, and data imbalanced approach resulted in balanced ASD dataset, including 107,573 cases. The development phase for the new model was achieved by the proposed complex T-spherical fuzzy-weighted zero-inconsistency (CT-SFWZIC) method. CT-SFWZIC was developed based on a new fuzzy set (i.e., complex T-spherical fuzzy) for weighting affected features, and then applied for training and testing the machine learning model considering various complex T-spherical fuzzy membership functions (i.e., T = 1, 2, 3, 5, 7, and 10). The results obtained from a 10-fold cross-validation test for all T values by using nine machine learning classifiers were measured under seven evaluation metrics, namely AUC, accuracy, F1, precision, recall, training time (s), and test time (s). Performance evaluation results reveal that AdaBoost can be used to boost the ASD diagnosis as the best machine learning algorithm for all T values based on all metrics to improve the diagnosis based on physician's assessment. Under the most extreme evaluation metric, which is accuracy, the results of the AdaBoost classifiers for T = 1, 2, 3, 5, 7, 10 have obtained 0.99948, 0.99934, 0.99930, 0.99939, 0.99910, and 0.99930, respectively.     

Multitouch tablet applications and activities to enhance the social skills of children with autism spectrum disorders

In spite of great improvements in early diagnosis and interventions, most children diagnosed with autism spectrum disorders (ASD) are unlikely to live independently when they reach adulthood. We have been conducting research on novel computer-based interventions with the goal of promoting social skills. Working with 26 children with ASD, their teachers, and other stakeholders, we have iteratively developed a set of activities based on applications that run on multitouch tablets. Our observations suggest these activities increased pro-social behaviors such as collaboration and coordination, augmented appreciation for social activities, and provided children with novel forms of expression.     

Educational and digital inclusion for subjects with autism spectrum disorders in 1:1 technological configuration

Focused on inclusive public policies, the relationship between students with Autism Spectrum Disorders and mobile devices was examined for discussing the limits and possibilities of the 1:1 technological configuration for supporting educational and digital inclusion programs in the Brazilian public schools. This was a qualitative research, with exploratory and explanatory approaches. Data collection was carried out through direct observation and document analysis, interviews and focus groups. From the data collected, we could observe the flaws and the potential of the interaction of three research subjects, all attending the first years of Elementary School, with mobile devices. The laptop is not user-friendly and not easy to understand, due to the complexity of the operational system, with its multiple choices and configurations. The interaction with the tablet showed a more friendly and intuitive use, since it is used more naturally, using fingers to touch the screen. The tablet can be used anywhere and in any position, which is good for students who are hyperactive and can quality strategies for pedagogical mediations.     

Pre-vocational skills laboratory: designing interventions to improve employment skills for students with autism spectrum disorders

Universal Access in the Information Society - The use of information and communication technologies in educating children with autism spectrum disorders (ASD) is a dynamic field linking both...     

Social media use among adults with autism spectrum disorders

Adults with autism spectrum disorders (ASD) are at risk for significant social and emotional difficulties, yet show strengths and interests in screen-based technology. Previous studies have found that screen-based social media use can enhance social functioning for adults in the general population, yet studies have not yet examined social media use among adults with ASD. The purpose of this study was to examine patterns and social–emotional correlates of social media use in a sample of 108 adults with ASD. Participants completed self-report measures of social media use, friendship quality and quantity, and loneliness. The results indicated that the majority of participants (79.6%) used social networking sites (SNS), and that the most commonly cited reason for using SNS was social connection. Adults with ASD who used SNS were more likely to have close friends, and those who used SNS for social engagement reported closer friendship relationships. However, greater offline friendship quality and quantity, not social media use, were associated with decreased loneliness in the current sample. This was the first study to explore patterns of social media use among adults with ASD, andthe findings suggest a need for further longitudinal research to examine the relations among these variables over time.     

Emo-mirror: a proposal to support emotion recognition in children with autism spectrum disorders

Neural Computing and Applications - Autism spectrum disorder (ASD) is a neurodevelopmental disorder defined as persistent difficulty in maturing the socialization process. Health professionals have...     

Computer-mediated intervention to foster prosocial ability among children with autism

The study refers to the social aspect of Autism Spectrum Disorder (ASD) and focuses on pro-social behaviour that has a positive effect on social adaptability. The first goal of the study was to determine whether there is a gap in prosocial-behaviour between children with High-Functioning ASD (HFASD) and children with typical-development; and secondly, to foster prosocial-behaviour with a computer-mediated intervention versus a non-computer-mediated intervention. The study comprises 58 preschool children, divided into three groups: HFASD experiencing a computer-mediated intervention, HFASD experiencing a non-computer-mediated intervention, and typically-developing children with no intervention. The 2-month intervention was based on the Cognitive Behavioural Therapy model, and pairs of children learned how to solve social-problems. Following preliminary screening tests (PPVT; SCQ), observations designed to evaluate prosocial-ability and Vineland questionnaires measuring prosocial-behaviour were conducted pre- and post-intervention. Pre-intervention findings indicated that children with typical-development exhibited higher prosocial-behaviour than children with HFASD. This changed however, post-intervention, as the gap between the two groups decreased. Additionally, the study found that the computer-mediated intervention group improved in some prosocial measures compared to the non-computer-mediated intervention.     

Studying the effects of computer serious games on people with intellectual disabilities or autism spectrum disorder: A systematic literature review

This study examines the available literature on the effects of serious games on people with intellectual disabilities or autism spectrum disorder. The studies were categorized based on the limitations in skills that these people address. Fifty‐four studies were selected, from different data sources. These studies address limitations in intellectual functioning and adaptive behaviour. The results showed that the majority of studies on the effects of serious games for people with intellectual disabilities or autism spectrum disorder had a positive impact. Also, most studies for people with autism aim to improve social and communicational skills, whereas conceptual and cognitive skills were mainly observed in studies for people with intellectual disabilities. Although this study covers serious games in all platforms or delivery systems, the overwhelming majority of the presented studies include computer serious games. Computer‐assisted learning through serious games is considered quite promising for people with intellectual disabilities or autism spectrum disorder.     

NAO机器人在自闭症干预中的应用

描述了自闭症谱系障碍（ASD）患儿基于人形机器人NAO人机互动情况下和在普通课堂环境下的行为反应,并给出其在干预治疗及普通课堂环境下的评估结果。大量实验结果表明,基于NAO机器人的人机互动干预过程中患儿自闭症状行为较普通课堂大大减少,其症状得到有效控制。因此可得出结论：人形机器人NAO可以作为帮助自闭症谱系障碍患儿干预治疗的平台。     

Using emotion recognition technologies to teach children with autism spectrum disorder how to identify and express emotions

Autism spectrum disorder (ASD), which since 2013 is considered as an umbrella term for several disorders such as autistic syndrome, Asperger’s disorder and pervasive developmental disorder, is characterized, among other aspects, by deficits in social-emotion reciprocity. This deficit manifests itself as a reduced sharing of emotions and an increased difficulty in interpreting emotions other people are feeling, which in the end leads to more impairments in social communication. Since it is possible to help a person with ASD (especially children) to improve their ability to understand and detect emotions, we have developed a proposal which integrates emotion recognition technologies, often used in the field of HCI, to try to overcome this difficulty. In this paper, we present a novel software application developed as a serious game to teach children with autism spectrum disorder (ASD) to identify and express emotions. The system incorporates cutting-edge technology to support novel interaction mechanisms based on tangible user interfaces (TUIs) and emotion recognition from facial expressions. In this way, children interact with the system in a natural way by simply grasping objects with their hands and using their faces. The system has been assessed on the premises of an association with children with ASD. The outcomes of the evaluation are very positive and support the validity of the proposal.

     

Universal access through accessible computer educational programs to develop the reading skills of children with autistic spectrum disorders

Finding the right research design, method and methodology for research in universal access can be a daunting process, as there are often no clearly laid down procedures on how to go about such work (Adams and Langdon, Universal access in HCI inclusive design in the information society. Lawrence Erlbaum, Mahwah, 2003). Researchers in the past have looked to other disciplines for guidance, or have followed the examples of other leading researchers. This problem is particularly acute when considering groups of individuals with very demanding and complex requirements. This paper evaluates research aimed at enabling children with autistic spectrum disorders (ASD) and severe learning difficulties to acquire early reading skills. In order to carry out research in this area, which contributes to a better understanding of the issues and to provide practical benefits, new methods are required to be developed on top of existing approaches.

Using multimedia to reveal the hidden code of everyday behaviour to children with autistic spectrum disorders (ASDs)

This paper describes a framework which was developed for carers (teachers and parents) to help them create personalised social stories for children with autistic spectrum disorders (ASDs). It explores the social challenges experienced by individuals with ASDs and outlines an intervention aimed at revealing the hidden code that underpins social interactions to them. It focuses on how technology can facilitate the implementation of this intervention by utilising multimedia-authoring tools. Findings from a case study, involving seven carers over a five-month period, are encouraging revealing that the participants quickly learned the basics of the intervention and either adapted or created social stories. They found the framework easy to use and sufficiently flexible to cater for children with social interaction, communication and behaviour problems.     

Effect of practice on similar and dissimilar skills in patient transfer through training with a robot patient

With the number of hospital stays increasing, nurses require more training to handle a variety of patients. However, time for training in nursing schools is limited, and students lack the opportunity to practice on a diverse variety of patients. Using a robot to simulate actual patients, this study observes the learning transfer effect of practice on practice-similar and practice-dissimilar skills from one patient to another, and investigates which types of practice suit which kinds of training. An experiment was conducted by administering a pre-test, practice, a post-test, and a transfer test to two groups (N?=?8), each with different practice-related skills. The evaluation used a checklist covering required skills that were either similar or dissimilar across groups, depending on their practice. The effect of practice can be observed through a comparison of skills similar to one group but dissimilar to the other. The results show that practice facilitates learning transfer on similar skills but not, or to a lesser degree, on dissimilar skills. Furthermore, if skills needed to handle given symptoms are unfamiliar or inaccessible to students, practice related to those symptoms should be emphasized through simulated training with robots.     

Tracking in nonlinear differential-algebraic control systems with applications to constrained robot systems

We consider the design of a feedback control law for control systems described by a class of nonlinear differential-algebraic equations so that certain desired outputs track given reference inputs. The nonlinear differential-algebraic control system being considered is not in state variable form. Assumptions are introduced and a procedure is developed such that an equivalent state realization of the control system described by nonlinear differential-algebraic equations is expressed in a familiar normal form. A nonlinear feedback control law is then proposed which ensures, under appropriate assumptions, that the tracking error in the closed loop differential-algebraic system approaches zero exponentially. Applications to simultaneous contact force and position tracking in constrained robot systems with rigid joints, constrained robot systems with joint flexibility, and constrained robot systems with significant actuator dynamics are discussed.     

Robonaut: a robot designed to work with humans in space

The Robotics Technology Branch at the NASA Johnson Space Center is developing robotic systems to assist astronauts in space. One such system, Robonaut, is a humanoid robot with the dexterity approaching that of a suited astronaut. Robonaut currently has two dexterous arms and hands, a three degree-of-freedom articulating waist, and a two degree-of-freedom neck used as a camera and sensor platform. In contrast to other space manipulator systems, Robonaut is designed to work within existing corridors and use the same tools as space walking astronauts. Robonaut is envisioned as working with astronauts, both autonomously and by teleoperation, performing a variety of tasks including, routine maintenance, setting up and breaking down worksites, assisting crew members while outside of spacecraft, and serving in a rapid response capacity.     

A fuzzy model to control the temperature in the cooling of metal molds with a spray robot

In a die-casting operation, the die spray is the key to quality and productivity, but the die-spray operation depends on parameter settings such as the spray volume and the operator's experience, even when a robot sprayer is used. The purpose of this study was to establish an intelligent system to control the surface temperature of a die with a water-based mist spray. A fuzzy model was applied to determine the optimum mist spray volume. The results generated show a good match with the actual measurements of the rate of the temperature drop versus the spray-mist volume. After the fuzzy analysis, the spray parameters calculated were used to control an actual die temperature experiment conducted on a heated plate model. The fuzzy model constructed by using fundamental experiments allowed the die spray operation to maintain a predetermined spray volume. This work was presented in part at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999