Biomedical Engineering Applications For People With Disabilities And Elderly In A New Covid 19 Pandemic And Beyond

Biomedical Engineering Applications for People with Disabilities and the Elderly in the COVID-19 Pandemic and Beyond presents biomedical engineering applications used to manage people’s disabilities and care for the elderly to improve their quality of life and extend life expectancy. This edited book covers all aspects of assistive technologies, including the Internet of Things (IoT), telemedicine, e-Health, m-Health, smart sensors, robotics, devices for rehabilitation, and "serious" games. This book will prove useful for bioengineers, computer science undergraduate and postgraduate students, researchers, practitioners, biomedical engineering students, healthcare workers, and medical doctors. This volume introduces recent advances in biomaterials, sensors, cellular engineering, biomedical devices, nanotechnology, and biomechanics applied in caring for the elderly and people with disabilities. The unique focus of this book is on the needs of this user base during emergency and disaster situations. The content includes risk reduction, emergency planning, response, disaster recovery, and needs assessment. This book offers readers multiple perspectives on a wide range of topics from a variety of disciplines. This book answers two key questions: What challenges will the elderly and people with disabilities face during a pandemic? How can new (or emerging) advances in biomedical engineering help with these challenges? Includes coverage of smart protective care tools, disinfectants, sterilization equipment and equipment for rapid and accurate COVID-19 diagnosis Focuses on the limitations and challenges faced by the elderly and people with disabilities in pandemic situations, such as limitations on leaving their homes and having caregivers and family visit their homes. How can technology help? Discusses tools, platforms and techniques for managing patients with COVID-19

EXPLAINABLE MACHINE LEARNING MODELS AND ARCHITECTURES This cutting-edge new volume covers the hardware architecture implementation, the software implementation approach, and the efficient hardware of machine learning applications. Machine learning and deep learning modules are now an integral part of many smart and automated systems where signal processing is performed at different levels. Signal processing in the form of text, images, or video needs large data computational operations at the desired data rate and accuracy. Large data requires more use of integrated circuit (IC) area with embedded bulk memories that further lead to more IC area. Trade-offs between power consumption, delay and IC area are always a concern of designers and researchers. New hardware architectures and accelerators are needed to explore and experiment with efficient machine-learning models. Many real-time applications like the processing of biomedical data in healthcare, smart transportation, satellite image analysis, and IoT-enabled systems have a lot of scope for improvements in terms of accuracy, speed, computational powers, and overall power consumption. This book deals with the efficient machine and deep learning models that support high-speed processors with reconfigurable architectures like graphic processing units (GPUs) and field programmable gate arrays (FPGAs), or any hybrid system. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.

MULTIMODAL BIOMETRIC AND MACHINE LEARNING TECHNOLOGIES With an increasing demand for biometric systems in various industries, this book on multimodal biometric systems, answers the call for increased resources to help researchers, developers, and practitioners. Multimodal biometric and machine learning technologies have revolutionized the field of security and authentication. These technologies utilize multiple sources of information, such as facial recognition, voice recognition, and fingerprint scanning, to verify an individual???s identity. The need for enhanced security and authentication has become increasingly important, and with the rise of digital technologies, cyber-attacks and identity theft have increased exponentially. Traditional authentication methods, such as passwords and PINs, have become less secure as hackers devise new ways to bypass them. In this context, multimodal biometric and machine learning technologies offer a more secure and reliable approach to authentication. This book provides relevant information on multimodal biometric and machine learning technologies and focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of multimodal biometric design, evaluation, and user diversity, and explains the underlying causes of the social and organizational problems that are typically devoted to descriptions of rehabilitation methods for specific processes. Furthermore, the book describes new algorithms for modeling accessible to scientists of all varieties. Audience Researchers in computer science and biometrics, developers who are designing and implementing biometric systems, and practitioners who are using biometric systems in their work, such as law enforcement personnel or healthcare professionals.

The fast-growing number of patients suffering from various ailments has overstretched the carrying capacity of traditional healthcare systems. This handbook addresses the increased need to tackle security issues and preserve patients’ privacy concerns in Artificial Intelligence of Medical Things (AIoMT) devices and systems. Handbook of Security and Privacy of AI-Enabled Healthcare Systems and the Internet of Medical Things provides new insights into the deployment, application, management, and benefits of AIoMT by examining real-world scenarios. The handbook takes a critical look at existing security designs and offers solutions to revamp traditional security architecture, including the new design of effi cient intrusion detection algorithms, attack prevention techniques, and both cryptographic and noncryptographic solutions. The handbook goes on to discuss the critical security and privacy issues that affect all parties in the healthcare ecosystem and provides practical AI-based solutions. This handbook offers new and valuable information that will be highly beneficial to educators, researchers, and others.

Quantum computers have demonstrated that they have the inherent potential to outperform classical computers in many areas. One of the major impacts is that the currently available cryptography algorithms are bound to no longer hold once quantum computers are able to compute at full speed. This book presents an overview of all the cross-disciplinary developments in cybersecurity that are being generated by the advancements in quantum computing.

The book Advances in Distance Learning in Times of Pandemic is devoted to the issues and challenges faced by universities in the field of distance learning in COVID-19 times. It covers both the theoretical and practical aspects connected to distance education. It elaborates on issues regarding distance learning, its challenges, assessment by students and their expectations, the use of tools to improve distance learning, and the functioning of e-learning in the industry 4.0 and society 5.0 eras. The book also devotes a lot of space to the issues of Web 3.0 in university e-learning, quality assurance, and knowledge management. The aim and scope of this book is to draw a holistic picture of ongoing online teaching-activities before and during the lockdown period and present the meaning and future of e-learning from students’ points of view, taking into consideration their attitudes and expectations as well as industry 4.0 and society 5.0 aspects. The book presents the approach to distance learning and how it has changed, especially during a pandemic that revolutionized education. It highlights • the function of online education and how that has changed before and during the pandemic. • how e-learning is beneficial in promoting digital citizenship. • distance learning characteristic in the era of industry 4.0 and society 5.0. • how the era of industry 4.0 treats distance learning as a desirable form of education. The book covers both scientific and educational aspects and can be useful for university-level undergraduate, postgraduate and research-grade courses and can be referred to by anyone interested in exploring the diverse aspects of distance learning.

In today's landscape of leadership and management, a pressing issue confronts professionals at all levels. Traditional leadership paradigms, including emotional intelligence, are proving insufficient in meeting the demands of the dynamic professional environment. Leaders, both aspiring and experienced, grapple with the challenge of establishing deeper, more meaningful connections in both personal and professional spheres. What exacerbates this issue is the lack of awareness regarding the untapped potential residing at the intersection of neuroscience, cognitive psychology, and social sciences. Building Organizational Resilience With Neuroleadership serves as a beacon of knowledge and a solution to this enduring challenge. This thought-provoking book embarks on an illuminating journey through the emerging field of neuroleadership, seamlessly integrating insights from neuroscience, cognitive psychology, and leadership studies. It offers a comprehensive solution, meticulously crafted for academic scholars, researchers, management students, and seasoned professionals who aspire to transcend their leadership abilities. This groundbreaking book propels emotional intelligence to new heights, empowering leaders to forge more profound connections within their teams and organizations. By unraveling the neural underpinnings of effective leadership, it equips readers with the tools to recognize and manage emotions, thereby fostering authenticity in their interactions. It also reveals the profound influence of neurons, encouraging both budding and seasoned leaders to embrace the extraordinary role of brain functions in shaping magnetic organizational cultures and teams. By bringing together the collaborative efforts of pioneering researchers, social scientists, and behavioral experts, a wholistic solution is prepared within the pages of this text.

Biomedical Engineering Tools for Management of Patients with COVID-19 presents biomedical engineering tools under research (and in development) that can be used for the management of COVID-19 patients, along with BME tools in the global environment that curtail and prevent the spread of the virus. BME tools covered in the book include new disinfectants and sterilization equipment, testing devices for rapid and accurate COVID-19 diagnosis, Internet of Things applications in COVID-19 hospitals, analytics, Data Science and statistical modeling applied to COVID-19 tracking, Smart City instruments and applications, and more. Later sections discuss smart tools in telemedicine and e-health. Biomedical engineering tools can provide engineers, computer scientists, clinicians and other policymakers with solutions for managing patient treatment, applying data analysis techniques, and applying tools to help the general population curtail spread of the virus. Provides leading-edge biomedical engineering tools and techniques for the treatment of patients with the COVID-19 virus Integrates a variety of case studies as a resource for COVID-19 researchers and clinicians around the world, including both positive and negative research findings Provides insights into innovative Biomedical Engineering techniques and devices from COVID-19 researchers around the world