Autistic traits, personality, and evaluations of humanoid robots by young and older adults
ویژگی های اوتیستیک ، شخصیت و ارزیابی ربات های انسان دوستانه توسط افراد جوان و بزرگتر-2020
While research with individuals on the autistic spectrum has increased strongly, there is still a lack of research on autism/autistic traits in older adults. Children with autism have been proposed to benefit from interactions with social robots; for older adults, the potential role of robotics is currently being discussed. We combined these topics by assessing both young and older (Mean age ¼ 22 vs. 69 years) neurotypical adults’ evaluations of various humanoid robots presented in video clips, on multiple dimensions (likeability, companionship, dominance, threat, human-likeness). We additionally assessed autistic traits (Autism Spectrum Questionnaire – AQ) and Big- Five personality traits. Remarkably, older adults evaluated robots as more likeable. Compared to young adults, older adults also showed significantly higher levels of autistic traits (particularly in the AQ social interaction subscale), higher levels of conscientiousness, and lower levels of openness. We found strong positive correlations between ratings of likeability and human-likeness of robots across groups, and particularly in participants with high levels of autistic trait. Across robots, data also provided evidence for the uncanny valley phenomenon. Favourable evaluations of robots by older adults suggest potential for older adults on the autistic spectrum to benefit from social robots.
Keywords: Humanoid robots | Old adults | Autistic traits | Personality | Visual appearance
Identification and analysis of behavioral phenotypes in autism spectrum disorder via unsupervised machine learning
شناسایی و تجزیه و تحلیل فنوتیپ های رفتاری در اختلال طیف اوتیسم از طریق یادگیری ماشین بدون نظارت-2019
Background and objective: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has explored potential ASD subgroups with preliminary evidence supporting the existence of behaviorally and genetically distinct subgroups; however, research has yet to leverage machine learning to identify phenotypes on a scale large enough to robustly examine treatment response across such subgroups. The purpose of the present study was to apply Gaussian Mixture Models and Hierarchical Clustering to identify behavioral phenotypes of ASD and examine treatment response across the learned phenotypes. Materials and methods: The present study included a sample of children with ASD (N = 2400), the largest of its kind to date. Unsupervised machine learning was applied to model ASD subgroups as well as their taxonomic relationships. Retrospective treatment data were available for a portion of the sample (n =1034). Treatment response was examined within each subgroup via regression. Results: The application of a Gaussian Mixture Model revealed 16 subgroups. Further examination of the subgroups through Hierarchical Agglomerative Clustering suggested 2 overlying behavioral phenotypes with unique deficit profiles each composed of subgroups that differed in severity of those deficits. Furthermore, differentiated response to treatment was found across subtypes, with a substantially higher amount of variance accounted for due to the homogenization effect of the clustering. Discussion: The high amount of variance explained by the regression models indicates that clustering provides a basis for homogenization, and thus an opportunity to tailor treatment based on cluster memberships. These findings have significant implications on prognosis and targeted treatment of ASD, and pave the way for personalized intervention based on unsupervised machine learning.
Keywords: Machine learning | Autism spectrum disorder | Behavioral phenotypes | Cluster analysis | Treatment response
Heritable genotype contrast mining reveals novel gene associations specific to autism subgroups
معادله کنتراست ژنتیکی انتزاعی نشان می دهد که ژن های جدید ژن خاص برای زیرگروه های اوتیسم هستند-2018
Though the genetic etiology of autism is complex, our understanding can be improved by identifying genes and gene-gene interactions that contribute to the development of specific autism subtypes. Identifying such gene groupings will allow individuals to be diagnosed and treated according to their precise characteristics. To this end, we developed a method to associate gene combinations with groups with shared autism traits, targeting genetic elements that distinguish patient populations with opposing phenotypes. Our computational method prioritizes genetic variants for genome-wide association, then utilizes Frequent Pattern Mining to highlight potential interactions between variants. We introduce a novel genotype assessment metric, the Unique Inherited Combination support, which accounts for inheritance patterns observed in the nuclear family while estimating the impact of genetic variation on phenotype manifestation at the individual level. High-contrast variant combinations are tested for significant subgroup associations. We apply this method by contrasting autism subgroups defined by severe or mild manifestations of a phenotype. Significant associations connected 286 genes to the subgroups, including 193 novel autism candidates. 71 pairs of genes have joint associations with sub groups, presenting opportunities to investigate interacting functions. This study analyzed 12 autism subgroups, but our informatics method can explore other meaningful divisions of autism patients, and can further be applied to reveal precise genetic associations within other phenotypically heterogeneous disorders, such as Alzheimer’s disease.
Keywords: Data mining ، Autistic disorder ، Genetics ، Frequent pattern mining
General and specific factors in the processing of faces
عوامل عمومی و خاص در پردازش چهره-2017
The ability to recognize faces varies considerably between individuals, but does performance co-vary for tests of different aspects of face processing? For 397 participants (of whom the majority were university students) we obtained scores on the Mooney Face Test, Glasgow Face Matching Test (GFMT), Cambridge Face Memory Test (CFMT) and Composite Face Test. Overall performance was significantly correlated for each pair of tests, and we suggest the term f for the factor underlying this pattern of positive correlations. However, there were large variations in the amount of variance shared by individual tests: The GFMT and CFMT are strongly related, whereas the GFMT and the Mooney test tap largely independent abilities. We do not replicate a frequently reported relationship between holistic processing (from the Composite test) and face recognition (from the CFMT)—indeed, holistic processing does not correlate with any of our tests. We report associations of performance with digit ratio and autism-spectrum quotient (AQ), and from our genome-wide association study we include a list of suggestive genetic associations with perfor mance on the four face tests, as well as with f.
Keywords: Face perception | Face recognition | f | Holistic processing | Individual differences | Autism-spectrum quotient (AQ) | Genome-wide association study (GWAS)
Tourism and autism: Journeys of mixed emotions
گردشگری و اوتیسم: سفرهای ترکیبی از احساسات-2017
There is an evolving tourism literature around psychological wellbeing, social exclusion and disability. This paper advances tourism knowledge into the terrain of psychological health and developmental complexities, and psychological distress. It draws on a phe nomenological position to understand the lived experiences of mothers of children with developmental difficulties, in this case diagnosed with autism spectrum disorder (ASD). It discusses the emotional and everyday challenges of caring for a child diagnosed with ASD on holiday, discusses the perceived benefits holidays offer and outlines care-giving strategies adopted by mothers to manage their children’s tourism experiences. The paper discusses the uniqueness of the context of autism and problematizes popular discourses, which predominantly frame tourism as pleasurable settings of escape, stimulation, novelty and relaxation.
Keywords: Disability | Care-giving | Mothers | Children | Well-being | Mental health
HRI Assessment of ASKNAO Intervention Framework via Typically Developed Child
ارزیابی HRI از لحاظ چارچوب مداخله ASKNAO نوعا از طریق کودک توسعه یافته-2017
This paper discuss about mock experiment on a typically developed child. The mock experiment is based on the previous work of the experimental framework on ASKNAO intervention. This is conducted as a preparation for the main experiment and to fine-tune the framework so that undesirable elements from the framework can be avoided. A typically developed child is used rather than an autism child because the typically developed child is able to handle the stress that occurs and capable of expressing his emotions freely. The findings of the experiment shows that the several adjustment need to be made on the previous framework in order to achieve a better result for the main experiment on an autism child.© 2016 The Authors. Published by Elsevier B.V.Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS 2016).© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors(IRIS 2016).
Keywords: Humanoid Robot Nao | Autism | Social Interaction | ASKNAO | Rehabilitation Robotics
Religious Perceptions on Use of Humanoid for Spiritual Augmentation of Children With Autism
ادراک مذهبی در استفاده از ربات های انسان نما برای تقویت معنوی کودکان مبتلا به اوتیسم-2017
© 2016 The Authors. Published by Elsevier B.V.Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS 2016).In the study of theology relevant to contemporary advances in science and technology, the underpinnings with regards to the religious and spiritual outcomes have to be considered. In the case of humanoids for spiritual augmentation of children with various brain impairments, the religious implications to the children and their families require adequate support prior to the sessions. Hence, this paper provides a review of a monotheistic religion, Islam, that is, the perceptions on the use of robots for spiritual augmentation of special-needs children within the context of the Islamic faith. This is important to teachers and researchers in anticipating better outcomes and in contradicting the debate on psychedelic consequences.© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors(IRIS 2016).
Keywords: humanoid | religion | spirituality | Islam | autism
Humanizing Humanoids Towards Social Inclusiveness for Children with Autism
جنبه انسانی ربات های انسان نما به سوی جامعیت اجتماعی برای کودکان مبتلا به درخودماندگی-2017
Assistive technologies in the form of humanoids have gained mileage in the area of rehabilitation, in particular, for children with various mental disabilities such as autism. The extent of the use of humanoids in augmenting these children are numerous yet, the social inclusiveness in the form of religious values, spirituality and ethics have hardly been explored. In these new and ambiguous dimensions, evidences of inclusiveness through repeated observations and interviews as well as secondary data analyses formed the hybrid methodology for this research project. The findings revealed a positive influence by humanizing humanoids in the social skill augmentation, religious and spiritual enhance of the scope. In attempting such a sensitive project, proper ethical procedures have to be in place because of the focus group. The implications of the findings are important in drafting relevant policies not just in educating the children, but to improve their quality of life, enriching the family well-being and enhance societal awareness for social inclusiveness.© 2016 The Authors. Published by Elsevier B.V.Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors (IRIS 2016).© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Peer-review under responsibility of organizing committee of the 2016 IEEE International Symposium on Robotics and Intelligent Sensors(IRIS 2016).
Keywords: humanoid | social inclusiveness | human-robot interaction | autism
تحلیل تقارن راه رفتن برای کودکان مبتلا به اختلالات طیف اوتیسم حین قدم زدن روی زمین
سال انتشار: 2017 - تعداد صفحات فایل pdf انگلیسی: 5 - تعداد صفحات فایل doc فارسی: 18
تقارن راه رفتن به عنوان شاخصی برای عملکرد عصبی مورد استفاده قرار می گیرد. راه رفتن سالم غالباً حداقل عدم تقارن را به همراه دارد، در حالیکه راه رفتن بیمارگونه، عدم تقارن شدیدی را بروز می دهد. هدف از این پژوهش، آزمودن تقارن پارامترهای مکانیکی راه رفتن طی قدم زدن روی زمین در کودکان مبتلا به اختلالات طیف اوتیسم (ASD) است. داده های حرکتی و حرکت شناختی از 10 کودک (سنین 5 تا 12 سال) مبتلا به ASD به دست آمد. به منظور مقایسه ی پارامترهای بین اندام های حرکتی در ارتباط با راه رفتن از روش آماری مدل (α=0.05) استفاده شد. تحلیل ها نشان داد کودکان مبتلا به ADS، در نیروی عکس العمل زمین و وضعیت مفاصل اندام های تحتانی، عدم تقارن قابل ملاحظه ای در سراسر مدت زمان راه رفتن از خود نشان می دهند. عدم تقارن مشاهده شده برای هر کدام از آنها، منحصر بفرد بود. این داده ها با پژوهش پیشین در ارتباط با تقارن راه رفتن در کودکان مبتلا به ADS، همخوانی نداشت. بسیاری از افراد مبتلا به ADS، مداخلات درمانی فیزیکی دریافت نمی کنند، با اینحال، مداخلات دقیق پزشکی با تمرکز بر عدم تقارن اندام-های تحتانی می تواند موجب بهبود عملکرد راه رفتن و ارتقای عملکرد حین فعالیت های روزمره شود.
کلیدواژه ها: بیومکانیک | راه رفتن | حرکت شناسی | تحرک.
|مقاله ترجمه شده|
Autistic traits in the general population do not correlate with a preference for associative information
صفات مبتلا به اوتیسم در جمعیت عمومی غیر وابسته با اولویت برای اطلاعاتی انجمنی-2017
Background: Associations and regularities in our environment can foster expectations and thereby help create a perceptually predictable world (e.g., a knife next to a plate predicts with high certainty a fork on the other side). Based on several observations, it has been suggested that individuals with autism spectrum disorder (ASD) have an above average tendency to prefer well-organized information or structured environments. Surprisingly, however, this tendency has not yet been tested under controlled experimental conditions. Method: A recent study suggested that neurotypical adults prefer associative information, regardless of their semantic content. Therefore, in this study, we examined the relation of this preference bias to the scores of 123 neurotypical adults on questionnaires that measure autistic traits, known to co-vary with typical autism spectrum characteristics. Participants were presented with different configurations of meaningless abstract shapes. Some shapes were always presented in the exact same fixed configuration, and other shapes were always presented in different random configurations. In an unannounced subsequent evaluation task, participants were required to indicate which shapes they preferred. Results: We replicate the observation that people exhibit a general preference for shapes that were presented in fixed configurations. However, there were no correlations between autistic traits and this general preference. Conclusions: Our findings suggest the preference for associative information in ASD might be less general than first thought, or restricted to more complex (social) situations or other levels of information processing. We outline specific guidelines for future systematic investigations into the hypothesized increased preference for associative information in ASD.
Keywords: Autism spectrum | Preference | Associative information | Predictive | Sameness