Remote health monitoring using wearable sensors is an important research area involving several key steps: physiological parameter sensing and data acquisition, data analysis, data security, data transmission to caregivers, and clinical intervention, all of which play a significant role to form a closed loop system. Subject-specific behavioral and clinical traits, coupled with individual physiological differences, necessitate a personalized healthcare delivery model for around-the-clock monitoring within the home environment. Cardiovascular disease monitoring is an illustrative application domain where research has been instrumental in enabling a personalized closed-loop monitoring system, which has been showcased in this book.
Health Monitoring Systems: An Enabling Technology for Patient Care provides a holistic overview of state-of-the-art monitoring systems facilitated by Internet of Things (IoT) technology. The book lists out the details on biomedical signal acquisition, processing, and data security, the fundamental building blocks towards an ambulatory health monitoring infrastructure. The fundamentals have been complimented with other relevant topics including applications which provide an in-depth view on remote health monitoring systems.
Key Features:
- Presents examples of state-of-the-art health monitoring systems using IoT infrastructure
- Covers the full spectrum of physiological sensing, data acquisition, processing, and data security
- Provides relevant example applications demonstrating the benefits of technological advancements aiding disease prognosis
This book serves as a beginner's guide for engineering students of electrical and computer science, practicing engineers, researchers, and scientists who are interested in having an overview of pervasive health monitoring systems using body-worn sensors operating outside the hospital environment. It could also be recommended as a reference for a graduate or master's level course on biomedical instrumentation and signal processing.
About the Author: Rajarshi Gupta received his M.Tech and PhD (Tech) in Instrumentation Engineering from University of Calcutta, India in 2002 and 2012 respectively. He is currently an Associate Professor with the Electrical Engineering Section, Department of Applied Physics, University of Calcutta, India. His research interests include cardiovascular signal measurements, and intelligent health monitoring. He has published 50 papers in peer reviewed international journals and conferences, 3 book/book chapters, with a Google Scholar Citation of 523, h-index of 12 and i-10 index of 12. He is currently associated as principal investigator/ co-principal investigator of 5 funded projects, with total funding of INR 62 lakhs in the area of biomedical devices and systems development. He has guided one PhD student and currently guiding five PhD students. Rajarshi is an active volunteer in IEEE and IET professional activities and has been associated with many flagship conferences in key positions.
Dwaipayan Biswas received his MSc in System on Chip, 2011 and his PhD in Electrical Engineering, 2015, from University of Southampton (UoS), UK. During this period, he was involved with three European Union funded projects, namely Chiron (https: //artemis-ia.eu/project/17-chiron.html), StrokeBack (https: //www.strokeback.eu/) and PLEASED (https: //www.physense.eu/pleased-project/). His research focused on developing low-complexity algorithm and architecture design targeting low-power VLSI implementation. He went on to work as a post-doctoral research fellow at UoS, 2015 - 2016, on Engineering and Physical Sciences Research Council (EPSRC) funded projects - Refresh (http: //www.refresh-project.org.uk/) and Prime (http: //www.prime-project.org/). He worked on smart office design based on cognitive monitoring and energy optimization for many-core embedded platforms. On November, 2016, he joined IMEC, Belgium, as a researcher on digital IC design for biomedical applications. He has been working on digital front-ends for low-power biomedical sensor readouts aimed at pervasive health monitoring. Further he has been actively involved in embedded algorithm-architecture development for motion artifact reduction during ambulatory sensing. His research interests include low-power VLSI design, biomedical signal processing, machine learning, brain computer interface and computer architecture. He has authored over 40 peer reviewed articles including journals, conference publications and book chapters.
