Role of Artificial Intelligence in Modeling Psychometrics to Detect Neurodevelopmental Disorders

The objective of the present chapter is to highlight applications of machine learning and artificial intelligence (AI) in clinical diagnosis of neurodevelopmental disorders. The proposed approach aims at recognizing behavioral traits and other cognitive aspects. The availability of numerous data and high processing power, such as graphic processing units (GPUs) or cloud computing, enabled the study of micro-patterns hundreds of times faster compared to manual analysis. AI, being a new technological breakthrough, enables study of human behavior patterns, which are hidden in millions of micro-patterns originating from human actions, reactions, and gestures. The chapter will also focus on the challenges in existing machine learning techniques and the best possible solution addressing those problems. In the future, more AI-based expert systems can enhance the accuracy of the diagnosis and prognosis process.

Brain-Computer Interface and Neurofeedback for Brain Training

AT liberty and open correspondence is central to present day life. Human cerebrum PC interfaces (BCIs), which interpret estimations of the client's mind movement into PC directions, present developing types of without hands correspondence. BCI correspondence frameworks have since quite a while ago been utilized in clinical settings for patients with loss of motion and other engine issue and have not been executed with the expectation of complimentary correspondence between solid, BCI-gullible clients. Brain PC interface innovation speaks to an exceptionally developing field of research with application frameworks. Its commitments in therapeutic fields extend from avoidance to neuronal restoration for genuine wounds. Human intellect perusing and remote correspondence have their exceptional unique mark in various fields, for example, instructive, self-guideline, creation, advertising, security, just as games and excitement. It makes a shared comprehension among clients and the encompassing frameworks.

Yoga Therapy on Cognitive Function in Neurodevelopmental Disorders

Neurodevelopmental disorders (NDDs) are birth imperfections that cause dysfunction in cognitive and sensory processes and impairment in motor function, communication, and behavior. The major factors responsible for increasing incidence of NDDs are genetic, psychosocial, and excessive use of drugs. Yoga alleviates neurological problems and NDDs. Asana is a physical movement with breath awareness that facilitates the development of body awareness, concentration, and memory and provides vital energy for children with neurodevelopmental disability. Yoga therapy improves sensory coordination and motor imitations that enable persons with cognitive disabilities to make meaningful response by the integration of senses and functions of central nervous system.

Enhancing Life Skills of Children and Adolescents With Autism Spectrum Disorder and Intellectual Disabilities Through Technological Supports

This chapter provides the reader with the newest empirical contributions available on the use of assistive technology-based interventions aimed at enhancing life skills of children and adolescents with autism spectrum disorders and developmental or intellectual disabilities. A selective overview along the last decade was carried out. Eighteen studies were reviewed, and 155 participants were involved. Five main categories of studies were identified, namely (1) emotional regulation, (2) communication skills, (3) academic performance, (4) social inclusion, and (5) challenging behavior. Results were fairly positive, although occasional failures occurred. Clinical, educational, psychological, and rehabilitative implications of the findings were critically discussed. Some useful guidelines for future research and practice were highlighted.

Design Thinking for Technology Supporting Individuals With Neurodevelopmental Disorders in Developing Countries

This research is concerned with analysing the value of using participatory design, and in particular the design thinking methodology, as a basis for the participative development of interfacing technology for use by individuals with neuro-developmental disorders, with a particular focus on developing economies with restrictions in budget and know-how. It becomes crucial as our knowledge expands to ensure that tools developed to assist individuals with neurological disorders to live a full and independent life are designed in conjunction with the users concerned. Inclusive design, however, is not limited to the technology itself, but rather taking into account the individual as well as the wider community in the design. Design needs to also be based in social accessibility to counter stigmas and ableism views. This study found that design thinking has proven to be an effective framework for involving individuals with neuro-developmental disorders to come up with solutions that address their needs and should be used in future implementations in order to assess the results.

The Adult Transition Challenge of Autistic Individuals and the Way Ahead

Autism is a life-long neurodevelopmental condition characterized by difficulties in social communication, restricted and repetitive behaviors, and sensory processing issues. In India, there is a huge question mark regarding autistic individuals after they transition into adulthood, more specifically in housing and work options. In this chapter, beginning from the general considerations for upbringing of an autistic individual, attention is given to the need for future planning of autistic adults, more specifically in residential options. Some of the major residential centres are described followed by projections on establishing residential facilities. Following this, examples of life skills training, employment, and inclusion initiatives taking place in India are mentioned. Finally, research directions and other expectations aimed at increasing support for parents and siblings and also improving the lives of individuals on spectrum are discussed.

Big Data-Based System

In the health domain, the move of generating big data is opening new methodologies in detection as well as prediction of various diseases and disorders. The first phase of the present chapter has provided insights into the role of big data analytics in the detection of one such neuro-disorder, that is, autism spectrum disorder (ASD). The data lake concept has provided a direction to resolve the issue by providing a common platform for storing tremendous amount of data in all formats (structured, unstructured, or raw). However, if the entire data have potential value, the data lakes need to be strategically designed as otherwise it can lead to data swamps. Therefore, in the second phase, data lake based on Hadoop architecture and Apache Spark engine has been provided for the analysis of the health data. The proposed system has resolved the data storage issue, management, and analytics on a single platform. Hence, the novelty of the chapter is that it is pointing towards the faster exploration as well as management of data so that the timely generation of hypothesis can help in analyzing ASD.

Activity Recognition System Through Deep Learning Analysis as an Early Biomarker of ASD Characteristics

Autism spectrum disorder (ASD) is a very high-flying area of research in the current era owing to its limited and on-going exploration. This chapter aims to bridge the gap of such late realization of autistic feature through machine intervention commonly known as computer vision. In this chapter, basic summarization of important characteristic features of autism and how those features could be measured and altered before a human could recognize are proposed. The chapter proposes a model for activity identification of the autistic child through video recordings. The approach is modelled in a way that consists of two phases: 1) Optical flow method detects the unusual frames based on motion pattern. 2) Each of these detected frames are fed to convolution neural network, which is trained to extract features and exactly classify if the particular frame under consideration belongs to usual or unusual class. This examines the various activities, time delay, and factors influencing the motion of the autistic child under constrained scenarios proving maximum accuracy and performance.

21st Century Education for Special Needs Students

Education is a human right—including students who have conditions requiring special education services. The purpose of this chapter is to promote inclusive education for students with learning disabilities due to diagnoses such as attention deficit hyperactivity disorder, autism, and more. A literature review includes a discussion pertaining to the elements of appropriate teaching methods compatible with developing 21st-century competencies for general education and special education students within the same classroom setting. Relative to employing strategies of differentiation and scaffolding while increasing cognition through experience-based lessons, this chapter provides examples from the author's classroom instructional plans. The content through action (CTA) method is presented as an ideal approach conducive to integrating 21st-century competencies through experiential lessons to teach the required content to students of various abilities. The chapter ends with recommendations on creating systemic change through building a support system at an organizational level.

Aided Augmentative and Alternative Communication (AAC) Systems for Individuals With Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are complex neuro-developmental disorders. They demonstrate pervasive deficits in social communication, restricted and repetitive behaviors, cognitive impairments, etc. Most often individuals with ASDs are often considered “non-verbal” and they require comprehensive intervention to improve their functional communication skills. Augmentative and alternative communication (AAC) was always viewed as a “last resort” for people with complex communication needs when all other interventions failed to achieve the potential benefit. However, with growing evidence, AAC has been implemented even in children with communication difficulties to augment spoken language development. Thus, this chapter aims to discuss the characteristics of ASD, to describe the need for AAC intervention in children with ASD, challenges and practices of AAC in ASD, to review implementation of aided AAC systems for children with ASD in different contexts, to indicate the gaps and future prospective in AAC intervention for people with ASDs.