This book focuses on recent advances in the Internet of Things (IoT) in biomedical and healthcare technologies, presenting theoretical, methodological, well-established, and validated empirical work in these fields. Artificial intelligence and IoT are set to revolutionize all industries, but perhaps none so much as health care. Both biomedicine and machine learning applications are capable of analyzing data stored in national health databases in order to identify potential health problems, complications and effective protocols, and a range of wearable devices for biomedical and healthcare applications far beyond tracking individuals' steps each day has emerged. These prosthetic technologies have made significant strides in recent decades with the advances in materials and development. As a result, more flexible, more mobile chip-enabled prosthetics or other robotic devices are on the horizon. For example, IoT-enabled wireless ECG sensors that reduce healthcare cost, and lead to betterquality of life for cardiac patients. This book focuses on three current trends that are likely to have a significant impact on future healthcare: Advanced Medical Imaging and Signal Processing; Biomedical Sensors; and Biotechnological and Healthcare Advances. It also presents new methods of evaluating medical data, and diagnosing diseases in order to improve general quality of life.

Presents recent advances in biomedical and healthcare technologies in IoT Discusses in detail experimental and application aspects of the latest technologies Presents innovative solutions to potential research problems

Autorentext

Dr. Chinmay Chakraborty is an Assistant Professor at the Department of Electronics and Communication Engineering, BIT Mesra. His primary areas of research include wireless body area networks, the Internet of Medical Things, energy-efficient wireless communications and networking, and point-of-care diagnosis. He received an Outstanding Researcher Award from TESFA in 2016, a Global Peer Review Award from Publons in 2018, and also a Young Faculty Award from VIFA in 2018. He is also the recipient of a Young Research Excellence Award, and a Global Peer-Review Award. Dr. Amit Banerjee worked as a Scientific Researcher at the Research Institute of Electronics, Japan, from 2016, and became a Scientist at the Department of Electrical and Computer Engineering of the prestigious National University of Singapore in 2018. Amit has worked extensively on Terahertz devices for biomedical applications.

Dr. Mahesh Kumar H. Kolekar is an Associate Professor at the Indian Institute of Technology Patna. His research interests include digital image and video processing, video surveillance, and medical image processing. He was a recipient of the Best Paper Award from the Computer Society of India and was a DAAD fellow at TU Berlin, Germany, from May to July 2017, where he pursued research in the area of biomedical signal processing.

Dr. Lalit Garg is a Senior Lecturer in Computer Information Systems at the University of Malta, and an Honorary Lecturer at the University of Liverpool, UK. He has also worked as a researcher at Nanyang Technological University, Singapore, and at the University of Ulster, UK. His research interests include handling missing data, machine learning, data mining, mathematical and stochastic modeling, and operational research, and their applications, especially in the healthcare domain.

Dr. Basabi Chakraborty holds B.Tech., M.Tech., and Ph.D. degrees in Radio Physics and Electronics from Calcutta University, India, andworked at the Indian Statistical Institute, Calcutta, India, until 1990. From 1991 to 1993, she worked as a researcher at the Advanced Intelligent Communication Systems Laboratory in Sendai, Japan. Her main research interests include pattern recognition, machine learning, soft computing techniques, biometrics, data mining and social media data mining.

Inhalt
Introduction to Technological advances in Healthcare.- Role of Big data analysis and Bio-electronics for upgrading healthcare technologies.- Automated Epileptic Seizure Detection in Clinical EEG using Frequency-Time Domain Features and Hidden Markov Model.- ECG Data Compression for IoT in Healthcare.- Prospects of Bioelectronics (IC enabled, flexible electronics, sensors, systems etc) for Biomedical Engineering and Healthcare in the information age.- Security and Privacy concerns in Healthcare.- Internet of Medical Things.- THz Sources and Detectors for Biomedical Application.- Big data analytics for Internet of Medical Things.- Biomedical Image Analysis: A Predictive Approach.- Missing data handling in medical questionnaires using hybrid methods.