The aim of this book is to identify some of the challenges that need to be addressed to accelerate the deployment and adoption of smart health technologies for ubiquitous healthcare access especially in wearable devices. These wearable devices may include pacemakers, defibrillators, RFID devices, assistive devices for the visually impaired, magnifiers, and talking assistants. It also explores how Internet of Things (IoT) and big data technologies can be combined with these wearable devices to provide better healthcare solutions.
Features:
- Focuses on real-time implementation of deep and machine learning techniques as well as novel algorithms for smart healthcare.
- Explores innovative challenges and solutions to complex problems in assistive devices with Medical 4.0 technologies.
- Presents an overview of challenges in the design of medical wearable devices.
- Discusses different techniques on VLSI for medical devices.
- Includes a case study on an AI-tuned cardiac pacemaker.
This book is aimed at graduate students and researchers in biomedical, electrical, computer engineering, and medical technologies.
Table of Contents:
1. Secured Smart Devices for Medical 4.0 Technologies: Threats and Approaches 2. Low-Cost Versatile Remote Healthcare Monitoring of Bedridden Patients 3. Transfer Learning and Domain-Specific Adoption Algorithms for Image Classification 4. Artificial Intelligence and Internet of Things Mechanism for Smart Healthcare 4.0 5. Significance of Quality Attributes of IoT-Based Smart Devices in Healthcare Monitoring Systems: Leading Towards Success or Failure 6. Smart Paralysis Revolution: BCI Virtual Keyboards Unleashed in Healthcare 7. Hardware Enhanced Secure Data Forwarding Protocol for Optimized Throughput in Wireless Body Area Networks 8. HealthCoin: Solidity-Backed Blockchain Ventures in Smart Healthcare Technologies 9. AI-Driven Smart Healthcare System for Monitoring Drought and Analyzing Climate Change: Impacts in Healthcare for Medical 4.0 10. Fortifying Healthcare Cybersecurity: A Sturdiness-Based Approach to Threat Modeling and Risk Analysis
About the Author :
Manisha Guduri, PhD, is full-time teaching faculty at the University of Louisiana at Lafayette, USA. She is the author/coauthor of more than 65 research papers in reputed journals, book chapters, and international conferences. Her research interests include Artificial Intelligence, Biomedical Applications and VLSI/ CAD design. She is currently working on VLSI and AI in the biomedical field. She has published five patents, two of which are under FER. She has received one patent grant and is a reviewer for IEEE TVLSI, Microelectronics Journal, IET Digital Circuits, IEEE Journal of Biomedical and Health Informatics, and other journals. She has one ongoing funded project from the Department of Science and Technology. She is a senior member of IEEE, USA. She is also currently member of various IEEE Societies such as IEEE Young Professionals, IEEE Women in Engineering, Circuits and Systems, Computer Society and the Sensor Council. She is appointed as IEEE WiE CASS representative for 2023 and 2024. She was executive committee member in Women in Engineering Affinity Group IEEE Hyderabad Section 2022. She is IEEE WiE DL Program Coordinator and 2024 IEEE Computer Society Lafayette Section Vice Chair. She has delivered more than 35 talks at international conferences, technical programs and various other platforms. She has helped to organize ten international conferences across different roles.
Chinmay Chakraborty, PhD, SMIEEE, MACM, is an Associate Professor at Birla Institute of Technology, Mesra, India. He completed a Post-Doctoral fellowship at the Federal University of Piauí, Brazil. He worked as a Senior Lecturer at the ICFAI University, Tripura, India. He worked as a Research Consultant in the Coal India project at Industrial Engineering and Management, IIT Kharagpur. He worked as a Project Coordinator of the Telecommunication Convergence Switch project under the Indo-US joint initiative. He also worked as a Network Engineer in System Administration at MISPL, India. His main research interests include the Internet of Medical Things (IoMT), AI/ML, Communication and Computing, Telemedicine, m-Health/e-health, and Medical Imaging. Dr. Chakraborty has widely published 200+ articles in peer reviewed international journals, conferences, book chapters, 25+ books, 4+ patents, and 20+ special issues in the field (Google h-index 35/i10-index 88, Scopus h-index 26, ISI-WoS h-index 22). He is an Editorial BoardMember for several journals and conferences. Dr. Chakraborty has co-edited severalbooks on IoMT, Healthcare Technology, and Sensor Data Analytics. He has servedas a Publicity Chair member at renowned international conferences, including IEEE Healthcom, IEEE SP-DLT. He is a member of ACM and a senior member of IEEE. He received a Best Session Runner-up Award, Young Research Excellence Award, Global Peer Review Award, Young Faculty Award, Outstanding Researcher Award, and Outstanding Paper in the 2022 Emerald Literati Awards and secured rank #1 from amongst 500 authors at BIT Mesra in Scival-Elsevier published by Scopus.com in 2023. He was selected as one of the top 2% of scientists in the world in the fields of Artificial Intelligence and Image Processing Stanford University, USA, 2021, 2022. He was the speaker for AICTE, DST-sponsored FDP, and CEP short-term course.
Martin Margala, PhD, joined the School of Computing and Informatics as Professor and Director in August 2021. Before joining UL Lafayette, from September 2011 to July 2021, Dr. Margala was Professor and Chair of the Electrical and Computer Engineering Department at the University of Massachusetts Lowell and a Co-Director of the Center for Smart Cyber-Physical Systems (SCyPS). He received his PhD degree in Electrical and Computer Engineering from the University of Alberta, Canada (#61 in Global Ranking in North America region; #13 in Global subject-specific ranking Electrical and Electronic Engineering in North America region US News) in the spring of 1998. He is a senior member of ACM, IEEE, and SPIE with more than 50 journal and 200 peer-reviewed conference publications in the areas of Design for Testability for Energy Efficient Architectures and Systems, High-Performance Reliable Low-Power Architectures and Reconfigurable Secure Architectures and Systems. Dr. Margala has directed 22 PhD students and 19 MS students, many of whom now hold leading positions in academia and industry. He has served on numerous program committees of international conferences and on workgroups (such as the International Technology Roadmap for Semiconductors) that have a great impact on the future direction of academia and industry.
