Smart Health Systems: Emerging Trends

✍ Scribed by Sonali Vyas, Deepshikha Bhargava

• Publisher: Springer
• Year: 2021
• Tongue: English
• Leaves: 131
• Category: Library

✦ Synopsis

The upcoming trends in healthcare are intended towards improving the overall quality of life. In the past,management of health issues were limited to clinics and hospitals and managing patient’s data and analyzing it. This procedure was difficult and time consuming. A great effort was also needed in diagnosing the cause and type of disease, but this all has changed now. As advancement in research and technologies, a positive impact on healthcare is seen. This book assesses the need and era of smart healthcare and delivers content relevant to current age and time. It describes the trend, usage and practicality of IWMDs i.e. Wearable Medical Device or Sensors (WMSs) and Implantable Medical Devices (IMDs) and how they enhance the awareness of daily healthcare.It establishes a relation and conjunction of daily healthcare monitoring with clinical healthcare. A healthcare system is called smart when there is an ability to make decisions, which comes from data analytics. Smart healthcare systems possess capability of data analytics and IoT based services which can be implemented on smart phones using cloud technology. This book discusses various research trends and technologies related to innovations and advancements for smart healthcare systems. It also elaborates challenges, scope upcoming techniques, devices and future directions for smart healthcare systems.The proposed book would in particular benefit researchers interested in interdisciplinary sciences, It would also be of value to faculty, research communities, and researchers from diverse disciplines who aspire to create new and innovative research initiatives.

✦ Table of Contents

Contents
About the Authors
1: Smart Health: An Introduction
1.1 What Is Smart Health?
1.2 Objectives of Smart Healthcare
1.3 Requirements of Smart Healthcare
1.4 Characteristics and Classification of Smart Healthcare
1.5 Components of a Smart Healthcare System
1.6 Key Concepts in Smart Healthcare
1.6.1 eHealth
1.6.2 Digital Health
1.6.3 mHealth
1.6.4 Smart Health IT
1.6.5 Smart Hospitals
1.7 Concluding Remarks
References
2: Technologies for Smart Health
2.1 Impacts of Technologies on Smart Healthcare
2.2 Next-Generation Technologies for Smart Healthcare
2.2.1 RFID Technology
2.2.2 IoT Technology and 5G Networks
2.2.2.1 Impacts of 5G Technology
2.2.3 Big Data
2.2.4 The Cloud
2.2.5 Augmented Reality/Virtual Reality
2.2.6 Mobile Technologies
2.2.7 Pervasive and Personalized Healthcare
2.2.8 Biosensors and Bioelectronics on Smartphones
2.3 Smart Healthcare Applications and Products
2.3.1 Assistance with Diagnosis and Treatment
2.3.2 Health Management
2.3.3 Disease Prevention and Risk Monitoring
2.3.4 Virtual Assistants
2.3.5 Smart Hospitals, Rooms and Homes
2.3.6 Assistance with Drug Research
2.3.7 Telemedicine/Telehealth
2.4 Positive and Negative Effects of Technology
References
3: Telehealth
3.1 What Is Telehealth?
3.2 The Needs and Goals of Telehealth
3.3 Telemedicine Trends
3.4 Issues Related to Telehealth
3.5 Differences Between Telemedicine, Telecare and Telehealth
3.6 Examples and Uses of Telehealth and Telemedicine
3.7 Telemedicine Apps
3.8 Technology Requirements in Telemedicine
3.9 Features and Functionality of Telehealth Apps
3.10 Setting Up a Telemedicine Program
3.10.1 Step 1: Select the Platform(s)
3.10.2 Step 2: Design an Appropriate App
3.10.3 Step 3: Choose APIs to Integrate into the App
3.10.4 Step 4: Test the App and Perform Quality Assurance
3.10.5 Step 5: Deploy and Maintain the App
3.11 Potentials and Limitations of Telehealth
References
4: Algorithms and Software for Smart Health
4.1 Software for Telehealth
4.1.1 Security Regulations and Laws
4.1.2 Technology Stack for Telehealth App Development
4.1.2.1 WebRTC
4.1.2.2 Electronic Health and Medical Records Built on Rails and GraphQL
4.1.2.3 Interactive Voice Response
4.1.2.4 Cloud-Based Server Solutions
4.1.2.5 HealthKit Integration
4.1.3 Technologies Used in Telehealth Apps
4.1.4 Guidelines for Building a Telehealth App
4.2 Softermii: Smart Healthcare App Development
4.2.1 HIPAA Video
4.2.2 Near Pharmacy
4.2.3 PetRealTime
4.2.4 Telehealth Apps and WebRTC
4.2.5 mHealth Apps
4.2.6 IoT Firmware
4.2.7 Medical Enterprise Apps
4.2.8 Health Insurance Management
4.2.9 Healthcare Data Security and Privacy Compliance
4.2.10 Blockchain Ledger and EHRs
4.3 Practice Management Solutions: Medical Practice Management Software
4.4 Problem-Specific Medical Algorithms Used in Smart Health
4.4.1 Virtual Visit Algorithm for COVID-19 Patients
4.4.2 Telehealth Algorithm for Management of Dizzy Patients
4.4.3 QRS Detection Algorithm for Telehealth ECG Recordings
4.4.4 Other Medical Algorithms
4.5 Algorithms Used to Transform Healthcare
4.5.1 Fourier Transform
4.5.2 TCP/IP
4.5.3 RSA Encryption Algorithm
4.5.4 MUMPS
4.5.5 Probabilistic Data-Matching Algorithm
4.5.6 BLAST
4.5.7 Neighbour-Joining Algorithm
4.5.8 Medical Algorithms
4.5.9 Health Scores
4.5.10 Big Data Analytics Tools and Techniques
4.5.11 Quantum Algorithms
4.5.12 Bioinformatics Tools for Medical Image Processing and Analysis
4.5.13 Data Science Approaches
4.5.14 AI and ML Approaches
References
5: Scalable Smart Health Systems
5.1 Scalable and Emerging Smart Healthcare Systems
5.1.1 IBM Watson
5.1.1.1 Oncology
5.1.1.2 Drug Discovery
5.1.1.3 Genomics
5.1.2 Open mHealth
5.1.3 Health Decision Support Systems
5.1.4 SoDA Stress Detection and Alleviation System
5.1.5 Energy-Efficient Health Monitoring System
5.2 Secure and Scalable Architecture Using Mist Computing
5.3 Large-Scale Distributed Computing in Smart Healthcare
5.4 Scalable Cognitive IoT–Based Smart City Network Architecture
5.5 Cloud-Enabled WBANs for Pervasive Healthcare
5.6 Blockchain-Based Distributed Architecture for a Scalable Smart City Network
5.7 Edge Computing for Scalable Smart Health
5.8 Structural Health Monitoring System for a Scalable Smart Sensor Network
5.9 Fog Computing for Scalable Smart Healthcare
References
6: Devices, Systems and Infrastructures for Smart Health
6.1 Smart Health Infrastructures
6.1.1 Smart Healthcare Infrastructure Challenges
6.1.1.1 Risk Management
6.1.1.2 Best-Performance Networks
6.1.1.3 Power Optimization
6.1.1.4 Communication Efficiency
6.1.1.5 IoMT Enablement
6.2 Smart Healthcare Structures
6.2.1 Protective Systems
6.2.2 Preventive Systems
6.2.3 Responsive Systems
6.2.4 Medical Automation Systems
6.3 Smart Healthcare Devices
6.3.1 Sensor-Based Smart Healthcare Devices
6.3.2 Smartphone-Based Smart Healthcare Devices
6.3.3 Microcontroller-Based Smart Healthcare Devices
6.3.4 IoT/IoMT/Sensor-Based Healthcare Devices
References
7: Cyber-physical Systems for Healthcare
7.1 Necessity of CPSs
7.2 CPS Standards
7.2.1 Standard Model to Synergic Model
7.2.2 Distinctive and Conceptual Realization Characteristics of CPSs
7.3 CPS Architecture
7.4 Technologies Related to CPSs
7.4.1 Advances in Macro-robotic Technologies
7.4.2 Synergic Technologies
7.4.2.1 Digital Microchip Technologies
7.4.2.2 Sensor Network Technologies
7.4.2.3 Sub-microscale Electrochemical Technologies
7.5 Benefits and Applications of CPS
7.5.1 Automobiles and Transportation
7.5.2 Healthcare and Medicines
7.5.3 Manufacturing
7.5.4 Security and Surveillance
7.5.5 Power and Thermal Energy Management
7.5.6 Smart Homes and Buildings
7.5.7 Construction
7.6 CPSs for Healthcare (CPSsH)
7.7 CPSs Issues and Challenges
7.7.1 Software Consistency
7.7.2 Medical Device Interactions
7.7.3 Data Mining
7.7.4 Privacy and Security
7.7.5 Program Response
7.7.6 Processing of Complex Queries
7.7.7 Absence of a Prototype Structure
7.8 CPSs and Future Medical Devices
References
8: Big Data Analytics and Cognitive Computing in Smart Health Systems
8.1 Big Data Analytics
8.1.1 Characteristics of Big Data
8.1.2 The ‘Four V’s’ of Big Data Analytics in Healthcare
8.1.3 Architecture of Big Data Analytics in Healthcare
8.1.4 Process of Big Data Analytics
8.1.4.1 Phases of Big Data Processing
8.1.5 Need for Big Data in Healthcare
8.1.6 Big Data Framework for Smart Healthcare
8.1.7 Big Data Applications for Healthcare
8.2 Cognitive Computing for Healthcare
8.2.1 Cognitive Analytics Architecture
8.3 Healthcare and Data Management Role Players
8.4 Impact of Cognitive Computing Systems on Healthcare
8.5 Smart Healthcare Approaches
8.6 Big Data Challenges in Healthcare Systems
8.7 Big Data and Cognitive Technology Future Plans for Healthcare
References
9: Values and Risks Associated with Smart Health
9.1 Goals of Smart Health Systems
9.2 Principles of Smart Health Systems
9.3 Classification of Smart Healthcare
9.4 Smart Health System Essentials
9.5 Security Requirements of Smart Healthcare
9.6 Major Risks Related to Smart Healthcare
9.7 Security Solution of Smart Health Applications
9.8 Smart Health System Services
References
10: Challenges, Opportunities and Future Trends in Smart Health
10.1 Challenges in Adoption of Smart Healthcare Systems
10.1.1 Collection or Gathering Information
10.1.2 Storage and Recovery of Data
10.1.3 Knowledge Acquisition
10.1.4 Smart Healthcare Applications
10.2 Transformational Challenges for Smart Healthcare Centres
10.2.1 Systems for Patient Monitoring in Smart Healthcare Systems
10.2.2 Data Accuracy in Smart Healthcare Systems
10.2.3 Cyber-security in Smart Healthcare Systems
10.2.4 Reducing the Costs of Devices and Sensors in Smart Healthcare Systems
10.2.5 Data Processing and Validation in Smart Healthcare Systems
10.2.6 Tuning and Interoperability of Smart Healthcare Systems
10.3 Opportunities in Smart Healthcare
10.3.1 Remote Monitoring
10.3.2 Chronic Self-Management
10.3.3 Performance Improvement
10.3.4 Behaviour Modification
10.3.5 Detection and Diagnosis
10.4 Trends Shaping the Future of Smart Healthcare
References