Nanosensors as Robust Non-Invasive Diagnostic Tools for Remote Health Monitoring
eBook - ePub

Nanosensors as Robust Non-Invasive Diagnostic Tools for Remote Health Monitoring

  1. 216 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Nanosensors as Robust Non-Invasive Diagnostic Tools for Remote Health Monitoring

About this book

This book addresses advancement in nanomaterials to design and develop non-invasive healthcare sensors including a combination of hybrid nanocomposites to design non-invasive devices for diagnosing human diseases. The cost-effectiveness is addressed with the methodologies to increase the scalability of the fabrication process. It aims to provide a complete end-to-end solution for smart non-invasive diagnosis developed indigenously and is a cost-effective complete guide to implement a deployable healthcare solution in real-time scenarios.

Key Features:

  • Focuses on the design and development of healthcare sensor devices.
  • Reviews different AI techniques using senors for healthcare.
  • Focuses on the application of nanomaterials in different biosensing applications.
  • Explores non-invasive and painless diagnosis with remote healthcare.
  • Discusses remote healthcare with IoMT integration and smart app communication.

This book is aimed at graduate students and researchers in biomedical engineering, medical devices, machine learning/pattern recognition, and nanotechnology.

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Yes, you can access Nanosensors as Robust Non-Invasive Diagnostic Tools for Remote Health Monitoring by Priyanka Dwivedi,Chinmay Chakraborty,Gwanggil Jeon,Yan Zhang in PDF and/or ePUB format. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Series Page
  4. Title Page
  5. Copyright Page
  6. Table of Contents
  7. Preface
  8. About the Editors
  9. Contributors
  10. Chapter 1 Machine Learning-Based Intelligent Smart Embedded Sensors for Automatic Detection and Classification of Neuromuscular Disorders Using EMG Signals
  11. Chapter 2 Connectivity Attributes for Remote Insulin Therapy
  12. Chapter 3 Deep Learning-Driven Human Activity Recognition for Remote Health Applications in Internet of Things-Enabled Smart Cities
  13. Chapter 4 Gas Sensors as a Non-Invasive Diagnostic Device for Smart Life Applications
  14. Chapter 5 Revolutionizing Personalized Healthcare: The Role of Nanosensors in NonInvasive Monitoring
  15. Chapter 6 Robust Non-Invasive Support System for Blood Cell Image Classification Using Generative Adversarial Networks
  16. Chapter 7 Impact of Channel Thickness on the MoS2 FET Performance Metrics and Their Application in Biosensing
  17. Chapter 8 Nanodiagnostics for Precision Breast Cancer Classification in Remote Health—A Comprehensive Study Employing Various Machine Learning Models
  18. Index