Teaching communication behaviour through dance and movement to children with Autism Spectrum Disorder (ASD) in Sarawak / Teo Jing Xin...[et al.]

This paper highlights the struggles of parents in Sarawak that have children with autism spectrum disorders (ASD), and introduces the authors’ proposed intervention programme for this population. With the belief that parental buy-in to an intervention would result in a higher level of follow-through and therefore improvement to the benefit of their children, the Fun, Inclusive, and Tolerant (FIT) dance and movement based behavioural intervention was designed and developed for Sarawakian children on the spectrum, specifically with the objective to acknowledge and address parental cultural narratives, desires, and expectations; while teaching appropriate behaviours to their children. The focus of this paper is two-fold. Firstly, to demonstrate how dances in this programme were created, by explaining the formulation of an individual dance which was developed for a child with an expressive speech delay; and secondly, to present parental feedback regarding the programme. Concluding remarks touch upon the authors’ future directions in this research

Assessing Trustworthy AI in times of COVID-19. Deep Learning for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients

Abstract—The paper's main contributions are twofold: to demonstrate how to apply the general European Union’s High-Level Expert Group’s (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare; and to investigate the research question of what does “trustworthy AI” mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multi-regional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient’s lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia (Italy) since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses socio-technical scenarios to identify ethical, technical and domain-specific issues in the use of the AI system in the context of the pandemic.</p

Spatial query retrieval model by single measure similarity (SMSS)

Structural spatial query is an active research area in spatial databases. The assessment of structural spatial query similarity is called structural similarity, also known as configuration similarity. This research developed a structural Spatial Query Retrieval Model for spatial databases by Spiral Web representation. The Spiral Web representation model is able to represent the unique relations among query objects in a structural spatial query like neighborhood relation, relative distance, relative direction and object geometry

Intelligent citrus seed identification

Feature extraction in image processing is a research domain that changes rapidly. [4] introduces a model for identifying seeds from citrus MRI imagery for fruit packaging industry. Hence this research proposed a model for identifying seeds from MRI imagery preprocessed with wavelet transformation and active region identification. The proposed approach segments a citrus imagery into circular layers and wedges to identify the area of interest for seeds. This reduces searching space (in number of pixels) to find out whether a fruit contain seeds. This paper presents the conceptual design and findings from the research on seed identification from citrus imagery segmentation. The improvement might be suitable for bio systems engineering to differentiate fruits with and without seeds

Portable real time needs expression for people with communication disabilities

This paper discusses a research on biometrics information recognition in real time for expressing needs of the people with communication disabilities. They have facial expression ability and incomprehensible speech that can be interpreted to communicate their needs. We utilized the real time detected face features in the pattern recognition process. Their facial expressions for a specific need may not be identical but have some similarities that can be identified through pattern recognition and trained using artificial intelligence. EmoCom has achieved a recognition rate of 85% in both cluttered indoor and outdoor environment

Portable real time emotion detection system for the disabled

This paper discusses the development of a portable real time emotion detection system for the use of disabled. This system allows the user to train the system with his/her profile comprising of expressions shown on the faces when different emotions occur. With a trained profile that can be updated flexibly, a user can detect his/her behaviour on real time basis. It utilizes the state of the art of face detection and recognition algorithms. The combination of Viola-Jones is used to detect frontal face from video which integrates Haar like features, integral image and AdaBoost learning rule. Principal Component Analysis that uses Eigenfaces to detect emotion shown on the faces is applied. For portability, it requires only a laptop or palmtop with built in camera and speaker that can be mounted on wheelchair easily. It works well in both indoor and outdoor environment day and night

Assistive technologies for physical and cognitive disabilities / Lau Bee Theng (ed.)

Research on assistive technologies is undergoing many developments in its effectiveness in helping those with varying impairments. New technologies are constantly being created, researched, and implemented for those who need these technological aides in daily life. Assistive Technologies for Physical and Cognitive Disabilities combines worldwide cases on people with physical and cognitive disabilities with the latest applications in assistive technologies. This reference work brings different researchers together under one title to discuss current findings, developments, and ongoing research in the area of rehabilitative technology. This reference book is of critical use to professionals, researchers, healthcare practitioners, caretakers, academicians, and students

Gabor neural network based facial expression recognition for assistive speech expression

This research focuses on utilizing the biometrics recognition to trigger the speech expresser. Our selected biometric is facial expression. Though CPC have no verbal language ability, they have facial expression ability that can be interpreted to relate to their voice speech needs. However facial expression of a CPC may not be exactly identical at all times. Furthermore CPC are unique and require special speech profiles. After a thorough research in face recognition and artificial intelligence domain, neural network coupled with Gabor feature extraction is found to outperform others. A Neural Network with Gabor filters is built to train the facial expression classifiers. This research has proven successful to help CPC to express their voice speech through software with 98% successful facial recognition rate

Learn with me: collaborative virtual learning for the special children

Collaborative learning environment is regarded as stimulating and engaging for normal learners. The main aim of our research is to investigate its effectiveness in assisting the learning of children with disabilities. We developed a prototype, Learn with Me and conducted a testing on 6 children who have been diagnosed with cerebral palsy and 7 children who have been diagnosed with autism spectrum disorders. Participants were invited to take part in two tests. Result showed participants learn better with responsive virtual tutor as compared to non-responsive virtual learning