Smart Distributed Embedded Systems for Healthcare Applications

Description:

This book discusses the applications and optimization of emerging smart technologies in the field of healthcare. It further explains different modeling scenarios of the latest technologies in the healthcare system and compares the results to better understand the nature and progress of diseases in the human body, which would ultimately lead to early diagnosis and better treatment and cure of diseases with the help of distributed technology.

• Covers the implementation models using technologies such as artificial intelligence, machine learning, and deep learning with distributed systems for better diagnosis and treatment of diseases.
• Gives in-depth review of technological advancements like advanced sensing technologies such as plasmonic sensors, usage of RFIDs, and electronic diagnostic tools in the field of healthcare engineering.
• Discusses possibilities of augmented reality and virtual reality interventions for providing unique solutions in medical science, clinical research, psychology, and neurological disorders.
• Highlights the future challenges and risks involved in the application of smart technologies such as cloud computing, fog computing, IOT, and distributed computing in healthcare.
• Confers to utilize the AI and ML and associated aids in healthcare sectors in the post-Covid 19 period to revitalize the medical setup.

Contributions included in the book will motivate technological developers and researchers to develop new algorithms and protocols in the healthcare field. It will serve as a vast platform for gaining knowledge regarding healthcare delivery, health- care management, healthcare in governance, and health monitoring approaches using distributed environments. It will serve as an ideal reference text for graduate students and researchers in diverse engineering fields including electrical, electronics and communication, computer, and biomedical fields.

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Preface

Embedded systems is the smart integration of hardware and software, which has many applications. Initially, embedded systems were introduced in the field of healthcare to cater to medical issues. Now, the amalgamation of smart distributed embedded systems with digital technologies such as artificial intelligence, cloud computing, IOT, NLP, augmented reality, virtual reality, and fog computing are used, and they prove to be a boon in the field of health and medicine. The new features offered by smart distributed technologies have accelerated the growth in the health industry. This book would be helpful to academicians, researchers, students, and technology developers for the development of better and optimized methods in healthcare.

This book provides in-depth comprehensive information on the latest research in the area of health and medicine on smart distributed embedded technologies. Chapter 1, “Healthcare Engineering Using AI and Distributed Technologies”, discusses the transformation of healthcare with distributed computing. The chapter highlights the impact, challenges, benefits, and limitations of AI in the healthcare industry. The chapter also features AI-based robots in the healthcare ecosystem. Chapter 2, “Cloud Computing in Healthcare: A Systematic Study”, elaborates on medicinal solutions provided by cloud computing using cloud-based molecular simulation tools and cloud-based medical imaging solutions. Application of fog computing in healthcare is also discussed.

Chapter 3, “Medical Information Extraction of Clinical Notes and Pictorial Visualization of Electronic Medical Records Summary Interface”, highlights the NLP technique that enables users to quickly fetch and comprehend the patient’s medical history and current data using Open NLP-trained Time-Entity model. Chapter 4, “Investigations on RFID-Enabled Healthcare Usage and Adoption Issues”, highlights that RFID has the potential for monitoring, tracking, and storing read data in real time. The chapter discusses various advantages provided by RFID technology. When RFID is linked, it can provide valuable process-integrated decision support based on current medical knowledge. It can also use patient data for research and healthcare reporting in a variety of ways. The chapter anticipates an RFID-enabled smart hospital in the future, which will combine RFID and wireless technology to provide a variety of healthcare services.

Chapter 5, “Photonic Crystal Fiber Plasmonic Sensor for Applications in Medicine”, elaborates on how newly developed plasmonic materials/meta-materials can be a part of the overall development of sensing technology and can be used in medical equipment. Chapter 6, “Augmented Reality as a Boon to Disability”, provides comprehensive coverage on the application of augmented reality for physically challenged, visually impaired, mentally challenged people, and other special children.

Chapter 7, “Augmented and Virtual Reality: Transforming the Future of Psychological and Medical Sciences”, elaborates on immersive technologies, such as virtual reality and augmented reality, that play a significant role in developing a stimulating environment to help doctors perform surgeries, children with autism disorder develop their communication skills, and psychologists provide simulated situations to patients suffering from different neurological disorders. Chapter 8, “Artificial Intelligence in Healthcare: Perspectives from Post-Pandemic Times”, emphasizes to best utilize the AI algorithms, ML techniques, and associated aids in healthcare sectors in the post-pandemic times to revitalize the medical setup. Chapter 9, “Bioweapons v/s Computer-Based Counter Measure Techniques and Mathematical Modelling for the Prediction of COVID-19”, provides an in-depth study of genetically engineered pathogens and their countermeasure techniques based on computer and artificial intelligence. The chapter examines several genetically engineered i llnesses as well as the impact of biological agents. In the instance of a pandemic, artificial intelligence, big data, computer vision, computer-aided systems, and IoT-based systems are offering solutions. Computer-assisted surgery is extremely beneficial to doctors.

Chapter 10, “Evolution of Healthcare Sector and Evolving Cyber Attacks—A Summary”, summarizes the evolution of the healthcare industry from healthcare 1.0 to healthcare 4.0. The chapter also highlights the need of Healthcare 4.0 from cyberattacks, as it is necessary to secure patients’ information in healthcare organizations. Chapter 11, “Improving Cardiovascular Health by Deep Learning”, highlights the next-generation machine learning and applications of artificial intelligence for cardiovascular health.