Mostafizur Rahman Swaron

Bio: Mostafizur Rahman Swaron is an academic researcher from Independent University, Bangladesh. The author has contributed to research in topics: Autism & Autism spectrum disorder. The author has co-authored 1 publications.

Improvement of Verbal and Non-Verbal Communication Skills of Children with Autism Spectrum Disorder using Human Robot Interaction

Abstract: This paper shows the primary feedback of children with Autism Spectrum Disorder (ASD) interacting with Humanoid Robot NAO. Four autistic children from Society for the Welfare of Autistic Children (SWAC) is being picked based on their neurological and physical limitations which has been identified by specialist teachers, ASD specialist researchers, and faculty members. Their Intelligence Quotient depends on question-answer based Intelligence Test has been first carried out and they have undergone the autism diagnoses based on Autism Diagnostic Observation sessions by autism specialist teachers from Society for the Welfare of Autistic Children (SWAC). The four of Children with ASD will then involve in the Robot-based Interaction Program, which started from session 1 to session 4. The interaction between Children with ASD and Humanoid Robot NAO is being recorded with Android Phone Video Camera and one mini camera included on the middle of Humanoid Robot NAO for initial feedback analysis based on verbal and non-verbal communications. The interaction session between the children and robot has been developed by using the software named choreographe of Humanoid Robot NAO.

IoT and AI-Based Application for Automatic Interpretation of the Affective State of Children Diagnosed with Autism

Abstract: In the context in which it was demonstrated that humanoid robots are efficient in helping children diagnosed with autism in exploring their affective state, this paper underlines and proves the efficiency of a previously developed machine learning-based mobile application called PandaSays, which was improved and integrated with an Alpha 1 Pro robot, and discusses performance evaluations using deep convolutional neural networks and residual neural networks. The model trained with MobileNet convolutional neural network had an accuracy of 56.25%, performing better than ResNet50 and VGG16. A strategy for commanding the Alpha 1 Pro robot without its native application was also established and a robot module was developed that includes the communication protocols with the application PandaSays. The output of the machine learning algorithm involved in PandaSays is sent to the humanoid robot to execute some actions as singing, dancing, and so on. Alpha 1 Pro has its own programming language—Blockly—and, in order to give the robot specific commands, Bluetooth programming is used, with the help of a Raspberry Pi. Therefore, the robot motions can be controlled based on the corresponding protocols. The tests have proved the robustness of the whole solution.

Autism Spectrum Disorder detection using AI Algorithm

Abstract: The primary objective of this systematic review is to examine how computer vision analysis has been useful in diagnosis, therapy, and autism research in general. Thus in the most of the developing nation and developed nation the ASD among the kids and adults has become a major concerns, where immediate intervention is required to cure these disorder at the early stage. The research paper is all about using OpenCV concepts with cosine theorem for images of counting fingers problem faced by an autism victim, where tracking their hand pose movements is a very difficult process. The normal human hand pose image is compared with the images of the autism patients and the difference between the images is analyzed to determine the ASD.

Drawing Interpretation Using Neural Networks and Accessibility Implementation in Mobile Application

Abstract: This paper continues the research of the previous work, regarding PandaSays mobile application, having its main purpose to detect the affective state of the child from his drawings, using MobileNet neural network. Children diagnosed with autism spectrum disorder, have difficulties in expressing their feelings and communicating with others. The purpose of PandaSays mobile application, is to help parents and tutors that have children diagnosed with autism, to communicate better with them and to understand their feelings. The main goal was to improve the model’s accuracy, trained with MobileNet neural network, which reached the value of 84.583%. For training the model, it was used Python programming language. The study focuses further on accessibility and its importance to children diagnosed with autism. Relevant screenshots of the mobile application are presented, in order to indicate that the application follows the accessibility guidelines and rules. Finally, there is presented the interaction with Marty robot and the efficiency of mobile application’s drawing prediction.

Exploring the Potential of Social Robots for Speech and Language Therapy: A Review and Analysis of Interactive Scenarios

Abstract: The use of innovative technology in the field of Speech and Language Therapy (SLT) has gained significant attention nowadays. Despite being a promising research area, Socially Assistive Robots (SARs) have not been thoroughly studied and used in SLT. This paper makes two main contributions: firstly, providing a comprehensive review of existing research on the use of SARs to enhance communication skills in children and adolescents. Secondly, organizing the information into tables that categorize the interactive play scenarios described in the surveyed papers. The inclusion criteria for play scenarios in the tables are based only on their effectiveness for SLT proven by experimental findings. The data, systematically presented in a table format, allow readers to easily find relevant information based on various factors, such as disorder type, age, treatment technique, robot type, etc. The study concludes that the despite limited research on the use of social robots for children and adolescents with communication disorders (CD), promising outcomes have been reported. The authors discuss the methodological, technical, and ethical limitations related to the use of SARs for SLT in clinical or home environments, as well as the huge potential of conversational Artificial Intelligence (AI) as a secondary assistive technology to facilitate speech and language interventions.

A systematic literature review on the internet of things applications used by people with autism spectrum disorder

Abstract: Abstract In this paper, we provide a systematic literature review that explores the Internet of Things (IoT) application to support people affected by Autism Spectrum Disorder (ASD). This disorder represents several limitations to learning, interacting with others, and communicating. Research has shown the great potential of the IoT in providing approaches that target individuals with ASD and help them in learning and their daily activities. Several studies on the topic of IoT were reviewed. The main aim of this review is to recognize relevant studies about the use of IoT to support people affected by ASD, particularly children. In addition, a classification is presented to classify the existing papers.