Smart Biosensors in Medical Care discusses the characteristics of biosensors and their potential applications in healthcare. This book is aimed at professionals, scientists and engineers who are interested in integrating biosensors into medical care systems for patients. It also provides fundamental and foundational knowledge for undergraduate and post graduate students. The book presents a comprehensive view of up-to-date requirements in hardware and communication, offers future perspectives on next-generation medical care systems, and includes global case studies of recent system operations in healthcare. Sections cover smart biosensors, such as wearable, implantable, patch based, and enzyme based for medical care.
Advances in ubiquitous sensing applications for healthcare is a series which covers new systems based on ubiquitous sensing for healthcare (USH). Volumes in this series cover a wide range of interdisciplinary areas, including wireless sensors networks, wireless body area networks, Big data, Internet-of-Things (IoT), security, monitoring, real time data collection, data management, systems design/analysis, and much more.
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Table of Contents
1. Prototype algorithm for three class motor imagery data classification: A step towards the development of human-computer interaction-based neuro-aid 2. Biosensor and its implementation in diagnosis of infectious diseases 3. Biosensors: A better biomarker for disease diagnosis 4. Smart biosensors for efficient point of care (PoC) health management 5. Energy harvesting via human body activities 6. BER performance comparison of EEG healthcare systems using 8-pixel, 16-pixel OLED screens and DSLR cameras 7. FBCC protocol for HBAN network for smart E-health application 8. Biofabrication of graphene QDs as a fluorescent nanosensor for detection of toxic and heavy metals in biological and environmental samples 9. Machine learning analysis of topic modeling reranking of clinical records 10. Smart sensing of medical disorder detection for physically impaired person 11. Speech-based automation system for patient in orthopedic trauma ward