AUTISM CONFERENCE


Autism Conference is one of the leading research topics in the international research conference domain. Autism is a conference track under the Psychology Conference which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of Psychology.

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Autism is not just a call for academic papers on the topic; it can also include a conference, event, symposium, scientific meeting, academic, or workshop.

You are welcome to SUBMIT your research paper or manuscript to Autism Conference Track will be held at .

Autism is also a leading research topic on Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, Elsevier, Scopus, Web of Science.

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I. INTERNATIONAL PSYCHOLOGY CONFERENCE

MARCH 19 - 20, 2019
ISTANBUL, TURKEY

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II. INTERNATIONAL PSYCHOLOGY CONFERENCE

JUNE 26 - 27, 2019
PARIS, FRANCE

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III. INTERNATIONAL PSYCHOLOGY CONFERENCE

AUGUST 21 - 22, 2019
LONDON, UNITED KINGDOM

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IV. INTERNATIONAL PSYCHOLOGY CONFERENCE

OCTOBER 08 - 09, 2019
NEW YORK, UNITED STATES

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V. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 12 - 13, 2019
ROME, ITALY

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VI. INTERNATIONAL PSYCHOLOGY CONFERENCE

FEBRUARY 13 - 14, 2020
LONDON, UNITED KINGDOM

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VII. INTERNATIONAL PSYCHOLOGY CONFERENCE

APRIL 15 - 16, 2020
BARCELONA, SPAIN

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VIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

MAY 11 - 12, 2020
ISTANBUL, TURKEY

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IX. INTERNATIONAL PSYCHOLOGY CONFERENCE

JUNE 05 - 06, 2020
SAN FRANCISCO, UNITED STATES

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X. INTERNATIONAL PSYCHOLOGY CONFERENCE

JULY 20 - 21, 2020
PARIS, FRANCE

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XI. INTERNATIONAL PSYCHOLOGY CONFERENCE

AUGUST 10 - 11, 2020
NEW YORK, UNITED STATES

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XII. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 10 - 11, 2020
TOKYO, JAPAN

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XIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 16 - 17, 2020
ZÜRICH, SWITZERLAND

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XIV. INTERNATIONAL PSYCHOLOGY CONFERENCE

OCTOBER 21 - 22, 2020
BARCELONA, SPAIN

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XV. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 02 - 03, 2020
SAN FRANCISCO, UNITED STATES

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XVI. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 12 - 13, 2020
ISTANBUL, TURKEY

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XVII. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 19 - 20, 2020
SINGAPORE, SINGAPORE

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XVIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 15 - 16, 2020
BANGKOK, THAILAND

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XIX. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 28 - 29, 2020
PARIS, FRANCE

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XX. INTERNATIONAL PSYCHOLOGY CONFERENCE

FEBRUARY 13 - 14, 2021
LONDON, UNITED KINGDOM

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XXI. INTERNATIONAL PSYCHOLOGY CONFERENCE

APRIL 15 - 16, 2021
BARCELONA, SPAIN

FINISHED

XXII. INTERNATIONAL PSYCHOLOGY CONFERENCE

MAY 11 - 12, 2021
ISTANBUL, TURKEY

FINISHED

XXIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

JUNE 05 - 06, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXIV. INTERNATIONAL PSYCHOLOGY CONFERENCE

JULY 20 - 21, 2021
PARIS, FRANCE

FINISHED

XXV. INTERNATIONAL PSYCHOLOGY CONFERENCE

AUGUST 10 - 11, 2021
NEW YORK, UNITED STATES

FINISHED

XXVI. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 10 - 11, 2021
TOKYO, JAPAN

FINISHED

XXVII. INTERNATIONAL PSYCHOLOGY CONFERENCE

SEPTEMBER 16 - 17, 2021
ZÜRICH, SWITZERLAND

FINISHED

XXVIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

OCTOBER 21 - 22, 2021
BARCELONA, SPAIN

FINISHED

XXIX. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 02 - 03, 2021
SAN FRANCISCO, UNITED STATES

FINISHED

XXX. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 12 - 13, 2021
ISTANBUL, TURKEY

FINISHED

XXXI. INTERNATIONAL PSYCHOLOGY CONFERENCE

NOVEMBER 19 - 20, 2021
SINGAPORE, SINGAPORE

FINISHED

XXXII. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 15 - 16, 2021
BANGKOK, THAILAND

FINISHED

XXXIII. INTERNATIONAL PSYCHOLOGY CONFERENCE

DECEMBER 28 - 29, 2021
PARIS, FRANCE

Psychology Conference Call For Papers are listed below:

Previously Published Papers on "Autism Conference"

  • Voice Features as the Diagnostic Marker of Autism
    Authors: Elena Lyakso, Olga Frolova, Yuri Matveev, Keywords: Autism spectrum disorders, biomarker of autism, child speech, voice features. DOI:10.5281/zenodo. Abstract: The aim of the study is to determine the acoustic features of voice and speech of children with autism spectrum disorders (ASD) as a possible additional diagnostic criterion. The participants in the study were 95 children with ASD aged 5-16 years, 150 typically development (TD) children, and 103 adults – listening to children’s speech samples. Three types of experimental methods for speech analysis were performed: spectrographic, perceptual by listeners, and automatic recognition. In the speech of children with ASD, the pitch values, pitch range, values of frequency and intensity of the third formant (emotional) leading to the “atypical” spectrogram of vowels are higher than corresponding parameters in the speech of TD children. High values of vowel articulation index (VAI) are specific for ASD children’s speech signals. These acoustic features can be considered as diagnostic marker of autism. The ability of humans and automatic recognition of the psychoneurological state of children via their speech is determined.
  • Robot-assisted Relaxation Training for Children with Autism Spectrum Disorders
    Authors: V. Holeva, V. Aliki Nikopoulou, P. Kechayas, M. Dialechti Kerasidou, M. Papadopoulou, G. A. Papakostas, V. G. Kaburlasos, A. Evangeliou, Keywords: Autism spectrum disorders, CBT, children relaxation training, robot-assisted therapy. DOI:10.5281/zenodo. Abstract: Cognitive Behavioral Therapy (CBT) has been proven an effective tool to address anger and anxiety issues in children and adolescents with Autism Spectrum Disorders (ASD). Robot-enhanced therapy has been used in psychosocial and educational interventions for children with ASD with promising results. Whenever CBT-based techniques were incorporated in robot-based interventions, they were mainly performed in group sessions. Objectives: The study’s main objective was the implementation and evaluation of the effectiveness of a relaxation training intervention for children with ASD, delivered by the social robot NAO. Methods: 20 children (aged 7–12 years) were randomly assigned to 16 sessions of relaxation training implemented twice a week. Two groups were formed: the NAO group (children participated in individual sessions with the support of NAO) and the control group (children participated in individual sessions with the support of the therapist only). Participants received three different relaxation scenarios of increasing difficulty (a breathing scenario, a progressive muscle relaxation scenario and a body scan medication scenario), as well as related homework sheets for practicing. Pre- and post-intervention assessments were conducted using the Child Behavior Checklist (CBCL) and the Strengths and Difficulties Questionnaire for parents (SDQ-P). Participants were also asked to complete an open-ended questionnaire to evaluate the effectiveness of the training. Parents’ satisfaction was evaluated via a questionnaire and children satisfaction was assessed by a thermometer scale. Results: The study supports the use of relaxation training with the NAO robot as instructor for children with ASD. Parents of enrolled children reported high levels of satisfaction and provided positive ratings of the training acceptability. Children in the NAO group presented greater motivation to complete homework and adopt the learned techniques at home. Conclusions: Relaxation training could be effectively integrated in robot-assisted protocols to help children with ASD regulate emotions and develop self-control.
  • Using Project MIND - Math Is Not Difficult Strategies to Help Children with Autism Improve Mathematics Skills
    Authors: Hui Fang Huang Su, Leanne Lai, Pei-Fen Li, Mei-Hwei Ho, Yu-Wen Chiu, Keywords: Young Children, Autism, Mathematics, Curriculum, teaching and learning, children with special needs, Project MIND. DOI:10.5281/zenodo. Abstract: This study aimed to provide a practical, systematic, and comprehensive intervention for children with Autism Spectrum Disorder (ASD). A pilot study of quasi-experimental pre-post intervention with control group design was conducted to evaluate if the mathematical intervention (Project MIND - Math Is Not Difficult) increases the math comprehension of children with ASD Children with ASD in the primary grades (K-1, 2) participated in math interventions to enhance their math comprehension and cognitive ability. The Bracken basic concept scale was used to evaluate subjects’ language skills, cognitive development, and school readiness. The study found that our systemic interventions of Project MIND significantly improved the mathematical and cognitive abilities in children with autism. The results of this study may lead to a major change in effective and adequate health care services for children with ASD and their families. All statistical analyses were performed with the IBM SPSS Statistics Version 25 for Windows. The significant level was set at 0.05 P-value.
  • Management Directions towards Social Responsibility in Special Population Groups by Airport Enterprises: The Case of Autism
    Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki, Simoni K. Lintzerakou, Keywords: Social responsibility, special groups, airport enterprises. DOI:10.5281/zenodo.3462067 Abstract: Air transport links markets and individuals, promoting social and economic development. The review of management direction towards social responsibility and especially for the enhancement of passengers with autism is the key objective of this paper. According to a top-down approach, the key dimensions that affect the basic principles and directions of airport enterprises management towards social responsibility for the case of passengers with autism are presented. Conventional wisdom is to present actions undertaken in improving accessibility for special population groups and highlight the social dimension in the management of transport hubs. The target is to focus on transport hubs serving special groups of passengers such as passengers with autism and highlight good practices and motivate transport infrastructure management authorities and decision makers to promote the social footprint of transport. The highlights and key findings are essential for managers and decision makers to support actions and plans towards management of airport enterprises towards social responsibility, focusing on the case of passengers traveling with Autism Spectrum Disorder (ASD).
  • The Use of Music Therapy to Improve Non-Verbal Communication Skills for Children with Autism
    Authors: Maria Vinca Novenia, Keywords: Autism, non-verbal communication, microanalysis, music therapy, school-aged children. DOI:10.5281/zenodo.2643506 Abstract: The number of school-aged children with autism in Indonesia has been increasing each year. Autism is a developmental disorder which can be diagnosed in childhood. One of the symptoms is the lack of communication skills. Music therapy is known as an effective treatment for children with autism. Music elements and structures create a good space for children with autism to express their feelings and communicate their thoughts. School-aged children are expected to be able to communicate non-verbally very well, but children with autism experience the difficulties of communicating non-verbally. The aim of this research is to analyze the significance of music therapy treatment to improve non-verbal communication tools for children with autism. This research informs teachers and parents on how music can be used as a media to communicate with children with autism. The qualitative method is used to analyze this research, while the result is described with the microanalysis technique. The result is measured specifically from the whole experiment, hours of every week, minutes of every session, and second of every moment. The samples taken are four school-aged children with autism in the age range of six to 11 years old. This research is conducted within four months started with observation, interview, literature research, and direct experiment. The result demonstrates that music therapy could be effectively used as a non-verbal communication tool for children with autism, such as changes of body gesture, eye contact, and facial expression.
  • Architecture and Students with Autism: Exploring Strategies for Their Inclusion in Society Mainstream
    Authors: Safaa Mahmoud Issa, Keywords: Architecture, inclusion, students with autism, mainstream society. DOI:10.5281/zenodo.1131876 Abstract: Architecture, as an art and science of designing, has always been the medium to create environments that fulfill their users’ needs. It could create an inclusive environment that would not isolate any individual regardless of his /her disabilities. It could help, hopefully, in setting the strategies that provide a supportive, educational environment that would allow the inclusion of students with autism. Architects could help in the battle against this neuro-developmental disorder by providing the accommodating environment, at home and at school, in order to prevent institutionalizing these children. Through a theoretical approach and a review of literature, this study will explore and analyze best practices in autism-friendly, supportive, teaching environments. Additionally, it would provide the range of measures, and set the strategies to deal with the students with autism sensory peculiarities, and that, in order to allow them to concentrate in the school environment, and be able to succeed, and to be integrated as an important addition to society and the social mainstream. Architects should take into consideration the general guidelines for an autism-friendly built environment, and apply them to specific buildings systems. And that, as certain design elements have great effect on children’s behavior, by appropriating architecture to provide inclusive accommodating environments, the basis for equalization of opportunities is set allowing these individuals a better, normal, non-institutional life, as the discussion presented in this study would reveal.
  • Checklist for Autism Spectrum Disorder as an In-class Observation Tool for Teachers
    Authors: W. Król-Gierat, Keywords: Autism Spectrum Disorders, case study, checklist, observation tool. DOI:10.5281/zenodo.1092611 Abstract: The majority of Special Educational Needs checklists are intended for preliminary screening in the special education disability process. The aim of the present paper is to present their potential usefulness as in-class observation tools for teachers working with students who have already been diagnosed with a disorder. A checklist may complement and organize information about a given child, which is indispensable to improve his or her condition. The case of a Polish boy with autism will serve as an example. Last but not least, alternative uses of checklists are suggested in the article.
  • Talent in Autism: Cognitive Style based on Weak Central Coherence and Special Sensory Characteristics in State of Kuwait: Case Study
    Authors: Mariam Abdulaziz Y.Esmaeel, Keywords: Autism, Central Coherence, Savant, Sensory characteristics, Talent. DOI:10.5281/zenodo.1075485 Abstract: The study aimed to identify the nature of autistic talent, the manifestations of their weak central coherence, and their sensory characteristics. The case study consisted of four talented autistic males. Two of them in drawing, one in clay formation and one in jigsaw puzzle. Tools of data collection were Group Embedded Figures Test, Block Design Test, Sensory Profile Checklist Revised, Interview forms and direct observation. Results indicated that talent among autistics emerges in limited domain and being extraordinary for each case. Also overlapping construction properties. Indeed, they show three perceptual aspects of weak central coherence: The weak in visual spatial-constructional coherence, the weak in perceptual coherence and the weak in verbal – semantic coherence. Moreover, the majority of the study cases used the three strategies of weak central coherence (segmentation, obliqueness and rotation). As for the sensory characteristics, all study cases have numbers of that characteristics that especially emerges in the visual system.
  • Exploration of Autistic Children using Case Based Reasoning System with Cognitive Map
    Authors: Ebtehal Alawi Alsaggaf, Shehab A. Gamalel-Din, Keywords: Autism, Cognitive Maps (CM), Case Based Reasoning technique (CBR). DOI:10.5281/zenodo.1073575 Abstract: Exploring an autistic child in Elementary school is a difficult task that must be fully thought out and the teachers should be aware of the many challenges they face raising their child especially the behavioral problems of autistic children. Hence there arises a need for developing Artificial intelligence (AI) Contemporary Techniques to help diagnosis to discover autistic people. In this research, we suggest designing architecture of expert system that combine Cognitive Maps (CM) with Case Based Reasoning technique (CBR) in order to reduce time and costs of traditional diagnosis process for the early detection to discover autistic children. The teacher is supposed to enter child's information for analyzing by CM module. Then, the reasoning processor would translate the output into a case to be solved a current problem by CBR module. We will implement a prototype for the model as a proof of concept using java and MYSQL. This will be provided a new hybrid approach that will achieve new synergies and improve problem solving capabilities in AI. And we will predict that will reduce time, costs, the number of human errors and make expertise available to more people who want who want to serve autistic children and their families.
  • Emotion Classification for Students with Autism in Mathematics E-learning using Physiological and Facial Expression Measures
    Authors: Hui-Chuan Chu, Min-Ju Liao, Wei-Kai Cheng, William Wei-Jen Tsai, Yuh-Min Chen, Keywords: Emotion classification, Physiological and facial Expression measures, Students with autism, Mathematics e-learning. DOI:10.5281/zenodo.1072169 Abstract: Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.

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