There are more than 80 different sleep disorders including insomnia, sleep apnea, restless leg syndrome, hypersomnia, circadian rhythm disorders, and parasomnia. Good sleep is necessary for optimal health and can affect hormone levels and weight. The use of artificial intelligence (AI) and biomedical signals and images can help in healthcare diagnostics that are related to these and other sleep disorders. Advancing the Investigation and Treatment of Sleep Disorders Using AI presents an overview of sleep disorders based on machine intelligence methods in order to learn and explore the latest advancements, developments, methods, systems, futuristic approaches, and algorithms towards sleep disorders and to address their challenges. This book also discusses recent and future advancements in various feature extraction techniques and machine learning methods. Covering topics such as biomedical signal processing, augmented reality for clinical investigation, and sleep disorder detection, this book is essential for sleep medicine practitioners, clinical psychologists, psychiatrists, medical technologists, doctors, IT specialists, biomedical engineers, researchers, graduate students, and academicians.

Artificial intelligence has become an invaluable tool in modern society and can be utilized across fields such as healthcare, travel, education, and construction. There are numerous benefits for companies, industries, and governments when adopting this technology into their daily operations as it continues to evolve to support the needs of society. Further study on the challenges and strategies of implementation is required in order to ensure the technology is employed to its full potential. Artificial Intelligence for Societal Development and Global Well-Being considers the various uses, best practices, and success factors of artificial intelligence across fields and industries and discusses critical ways in which the technology must be developed further for the good of society. Covering a range of topics such as smart devices, artificial neural networks, and natural intelligence, this reference work is crucial for scientists, librarians, business owners, government officials, entrepreneurs, scholars, researchers, practitioners, instructors, and students.

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks. Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

People with neurological disorders may experience significant problems, isolation, detachment, and passivity while dealing with environmental requests. They constantly rely on caregivers and family assistance, which can create negative outcomes on their quality of life. An emerging way to overcome these issues is assistive technology-based interventions (AT). AT-based programs are designed to fill the gap between human/individual capacities or skills and environmental requests. These technologies can also bring about independence and self-determination and provide people with neurological disorders an active role, positive participation, and an enhanced status in being able to achieve functional daily activities by reducing the roles of their families and caregivers. The positive impacts of this technology are an important area of research, and its usage for neurological disorders is critical for the assessment and recovery of patients. Assistive Technologies for Assessment and Recovery of Neurological Impairments explores the use of AT-based programs for promoting independence and self-determination of individuals with neurological disorders. The chapters discuss AT-based interventions in detail with the specific technologies that are being used, the positive effects on patients, and evidence-based practices. This book also focuses on specific technologies such as virtual reality (VR) setups and augmented reality (AR) as valid ecological environments for patients that ensure methodological control and behavioral tracking for both assessment and rehabilitation purposes. This book is essential for occupational therapists, speech therapists, physiotherapists, neurologists, caregivers, psychologists, practitioners, medical professionals, medical technologists, IT consultants, academicians, and students interested in assistive technology interventions for people with neurological impairments.

This book is the proceeding of the International Conference on Sustainable Engineering Development and Technological Innovation (ICSEDTI 2022) that was successfully held on 11-13 October 2022 using an hybrid platform. The conference is themed “Sustainable empowerment of innovative solutions through the development of integrated scientific researches to enhance the advanced technological world”, which represents our belief of how the sustainability is essential in our approach to solve problems through technological innovation. A total of 56 papers were submitted and presented within the sessions of the conference. The papers’ topics revolve around Informatics Technology, Electrical Technology, Marine Technology, Manufacturing System and Technology, Mechanical Engineering, And also Information Industry and Management. In addition to the technical paper presentations, there were also five keynote speeches featured, and eight plenary talks were delivered. Two of the keynote speeches were delivered in person by Professor Selo from Universitas Gajah Mada, Indonesia, and Professor Goib Wiranto from the National Research and Innovation Agency, Indonesia. The rest of the keynote speeches were delivered online by Professor Yvon Kermarrec from IMT Atlantique, France; Professor Ian Gibson from University of Twente, Netherlands; and Dr. Ilham Akbar Habibie from The Association of Indonesian Engineer, Indonesia. It was a great pleasure to work with the technical program committee led by Mr. Hilfi Pardi, who have completed the imperative process of peer-review on the technical papers submitted in this conference. We are also very fortunate to have on our side the excellent organizing committee team of the Faculty of Engineering of UMRAH who work very hard to organize and support the conference. Finally, our appreciation to all the authors who have participated in this conference with their amazing achievements and enthusiasm. We firmly believe that ICSEDTI is a suitable platform for researchers, engineers, and developers who are concerned with sustainability in engineering and technological development. We hope in the coming years ICSEDTI will be better in terms of the organization of the conference, the quantity and the quality of the researches submitted, and most importantly the impact on the sustainability of technological innovation.

Data analytics is proving to be an ally for epidemiologists as they join forces with data scientists to address the scale of crises. Analytics examined from many sources can derive insights and be used to study and fight global outbreaks. Pandemic analytics is a modern way to combat a problem as old as humanity itself: the proliferation of disease. Machine Learning and Data Analytics for Predicting, Managing, and Monitoring Disease explores different types of data and discusses how to prepare data for analysis, perform simple statistical analyses, create meaningful data visualizations, predict future trends from data, and more by applying cutting edge technology such as machine learning and data analytics in the wake of the COVID-19 pandemic. Covering a range of topics such as mental health analytics during COVID-19, data analysis and machine learning using Python, and statistical model development and deployment, it is ideal for researchers, academicians, data scientists, technologists, data analysts, diagnosticians, healthcare professionals, computer scientists, and students.

Within the last few years, devices that are increasingly capable of offering an immersive experience close to reality have emerged. As devices decrease in size, the interest and application possibilities for them increase. In the healthcare sector, there is an enormous potential for virtual reality development, as this technology allows, on the one hand, the execution of operations or processes at a distance, decoupling realities; and on the other hand, it offers the possibility of simulation for training purposes, whenever there are contexts of risk to the patient or to the health professional. However, virtual reality devices and immersion in virtual environments still requires some improvement as complaints such as headaches and nausea are still common among users, and so continuous research and development is critical to progress the technology. Emerging Advancements for Virtual and Augmented Reality in Healthcare synthesizes the trends, best practices, methodologies, languages, and tools used to implement virtual reality and create a positive user experience while also discussing how to implement virtual reality into day-to-day work with a focus on healthcare professionals and related areas. The application possibilities and their impact are transversal to all areas of health and fields such as education, training, surgery, pain management, physical rehabilitation, stroke rehabilitation, phobia therapy, and telemedicine. Covering topics such as mental health treatment and virtual simulations, it is ideal for medical professionals, engineers, computer scientists, researchers, practitioners, managers, academicians, teachers, and students.

Innovative and fusion technologies have shown an incredible ability to improve various aspects of society, such as healthcare systems. Nanobiotechnology is one such technology that is being applied to medical equipment and treatment approaches. Many pharmaceutical and medical companies have begun to count on medical nanotechnology due to its abundant applications and practical uses. Innovative Approaches for Nanobiotechnology in Healthcare Systems is a pivotal reference source that provides insights into a comprehensive collection of novel techniques used for the development of safe drugs using the available resources for diverse deadly diseases. This book discusses the various platforms of nanobiotechnology that are utilized in various fields. It is expected that bionanosytems will play a crucial role in the treatment of human diseases and the improvement of existing healthcare systems. This book is ideal for scientists, biotechnologists, microbiologists, medical professionals, entrepreneurs, policymakers, researchers, academicians, and students.

Each day, novel neuroscientific findings show that researchers are focusing on developing advanced smart hardware designs and intelligent computational models to imitate the human brain’s computational abilities. The advancements in smart materials provide a significant role in inventing intelligent bioelectronic device designs with smart features such as accuracy, low power consumption, and more. These advanced and intelligent computing models through machine and smart deep learning algorithms help to understand the information processing capabilities of the human brain with optimum accuracy. Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering highlights advanced computational models and hardware designs in neurology and integration of mathematical physical, biological, chemical, and engineering models to mimic brain functions; discovers new technological diagnosis techniques; and achieves high accuracy in learning models to better understand the functioning of the human brain. Providing rich information on brain-computer interfacing, gamification in children, and vestibular rehabilitation, this text acts as an essential resource for experts in electrophysiological studies, neurologists, neuro-physiotherapists, neuro-radiologists, intelligent system developers, bio-software and hardware developers, neuro database collectors, electro-physiologists, professors associated with neurology, psychiatrists, engineers, scientists, and students from academia and industry involved in interdisciplinary approaches to neurology.