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Smart Health Systems: Emerging Trends 2021 ed. [Kõva köide]

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  • Formaat: Hardback, 125 pages, kõrgus x laius: 235x155 mm, kaal: 409 g, 34 Illustrations, color; 1 Illustrations, black and white; XII, 125 p. 35 illus., 34 illus. in color., 1 Hardback
  • Ilmumisaeg: 26-Aug-2021
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811642001
  • ISBN-13: 9789811642005
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Smart Health Systems: Emerging Trends 2021 ed.Suurem pilt
  • Formaat: Hardback, 125 pages, kõrgus x laius: 235x155 mm, kaal: 409 g, 34 Illustrations, color; 1 Illustrations, black and white; XII, 125 p. 35 illus., 34 illus. in color., 1 Hardback
  • Ilmumisaeg: 26-Aug-2021
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811642001
  • ISBN-13: 9789811642005
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789811642005.html
Märksõnad:
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.
1 Smart Health: An Introduction
1(10)
1.1 What Is Smart Health?
2(1)
1.2 Objectives of Smart Healthcare
3(1)
1.3 Requirements of Smart Healthcare
3(1)
1.4 Characteristics and Classification of Smart Healthcare
4(1)
1.5 Components of a Smart Healthcare System
4(2)
1.6 Key Concepts in Smart Healthcare
6(2)
1.6.1 eHealth
6(1)
1.6.2 Digital Health
7(1)
1.6.3 mHealth
7(1)
1.6.4 Smart Health IT
8(1)
1.6.5 Smart Hospitals
8(1)
1.7 Concluding Remarks
8(3)
References
9(2)
2 Technologies for Smart Health
11(12)
2.1 Impacts of Technologies on Smart Healthcare
11(1)
2.2 Next-Generation Technologies for Smart Healthcare
12(6)
2.2.1 RHD Technology
12(1)
2.2.2 IoT Technology and 5G Networks
13(1)
2.2.3 Big Data
14(1)
2.2.4 The Cloud
15(1)
2.2.5 Augmented Reality/Virtual Reality
15(1)
2.2.6 Mobile Technologies
15(3)
2.2.7 Pervasive and Personalized Healthcare
18(1)
2.2.8 Biosensors and Bioelectronics on Smartphones
18(1)
2.3 Smart Healthcare Applications and Products
18(1)
2.3.1 Assistance with Diagnosis and Treatment
18(1)
2.3.2 Health Management
18(1)
2.3.3 Disease Prevention and Risk Monitoring
19(1)
2.3.4 Virtual Assistants
19(1)
2.3.5 Smart Hospitals, Rooms and Homes
19(1)
2.3.6 Assistance with Drug Research
19(1)
2.3.7 Telemedicine/Telehealth
19(1)
2.4 Positive and Negative Effects of Technology
19(4)
References
20(3)
3 Telehealth
23(14)
3.1 What Is Telehealth?
23(1)
3.2 The Needs and Goals of Telehealth
24(1)
3.3 Telemedicine Trends
25(1)
3.4 Issues Related to Telehealth
25(1)
3.5 Differences Between Telemedicine, Telecare and Telehealth
25(1)
3.6 Examples and Uses of Telehealth and Telemedicine
26(1)
3.7 Telemedicine Apps
27(1)
3.8 Technology Requirements in Telemedicine
27(2)
3.9 Features and Functionality of Telehealth Apps
29(1)
3.10 Setting Up a Telemedicine Program
30(3)
3.10.1 Step 1: Select the Platform(s)
30(1)
3.10.2 Step 2: Design an Appropriate App
31(1)
3.10.3 Step 3: Choose APIs to Integrate into the App
32(1)
3.10.4 Step 4: Test the App and Perform Quality Assurance
33(1)
3.10.5 Step 5: Deploy and Maintain the App
33(1)
3.11 Potentials and Limitations of Telehealth
33(4)
References
34(3)
4 Algorithms and Software for Smart Health
37(12)
4.1 Software for Telehealth
37(3)
4.1.1 Security Regulations and Laws
37(1)
4.1.2 Technology Stack for Telehealth App Development
38(1)
4.1.3 Technologies Used in Telehealth Apps
39(1)
4.1.4 Guidelines for Building a Telehealth App
39(1)
4.2 Softermii: Smart Healthcare App Development
40(2)
4.2.1 HIPAA Video
40(1)
4.2.2 Near Pharmacy
40(1)
4.2.3 PetReal Time
40(1)
4.2.4 Telehealth Apps and WebRTC
41(1)
4.2.5 mHealth Apps
41(1)
4.2.6 IoT Firmware
41(1)
4.2.7 Medical Enterprise Apps
41(1)
4.2.8 Health Insurance Management
41(1)
4.2.9 Healthcare Data Security and Privacy Compliance
41(1)
4.2.10 Blockchain Ledger and EHRs
42(1)
4.3 Practice Management Solutions: Medical Practice Management Software
42(1)
4.4 Problem-Specific Medical Algorithms Used in Smart Health
43(1)
4.4.1 Virtual Visit Algorithm for COVID-19 Patients
43(1)
4.4.2 Telehealth Algorithm for Management of Dizzy Patients
43(1)
4.4.3 QRS Detection Algorithm for Telehealth ECG Recordings
43(1)
4.4.4 Other Medical Algorithms
44(1)
4.5 Algorithms Used to Transform Healthcare
44(5)
4.5.1 Fourier Transform
44(1)
4.5.2 TCP/IP
44(1)
4.5.3 RSA Encryption Algorithm
44(1)
4.5.4 MUMPS
44(1)
4.5.5 Probabilistic Data-Matching Algorithm
45(1)
4.5.6 BLAST
45(1)
4.5.7 Neighbour-Joining Algorithm
45(1)
4.5.8 Medical Algorithms
45(1)
4.5.9 Health Scores
45(1)
4.5.10 Big Data Analytics Tools and Techniques
45(1)
4.5.11 Quantum Algorithms
46(1)
4.5.12 Bioinformatics Tools for Medical Image Processing and Analysis
46(1)
4.5.13 Data Science Approaches
46(1)
4.5.14 AI and ML Approaches
46(1)
References
47(2)
5 Scalable Smart Health Systems
49(12)
5.1 Scalable and Emerging Smart Healthcare Systems
49(5)
5.1.1 IBM Watson
49(2)
5.1.2 OpenmHealth
51(1)
5.1.3 Health Decision Support Systems
52(1)
5.1.4 SoDA Stress Detection and Alleviation System
53(1)
5.1.5 Energy-Efficient Health Monitoring System
53(1)
5.2 Secure and Scalable Architecture Using Mist Computing
54(1)
5.3 Large-Scale Distributed Computing in Smart Healthcare
54(1)
5.4 Scalable Cognitive IoT-Based Smart City Network Architecture
55(1)
5.5 Cloud-Enabled WBANs for Pervasive Healthcare
55(1)
5.6 Blockchain-Based Distributed Architecture for a Scalable Smart City Network
56(1)
5.7 Edge Computing for Scalable Smart Health
56(1)
5.8 Structural Health Monitoring System for a Scalable Smart Sensor Network
56(1)
5.9 Fog Computing for Scalable Smart Healthcare
56(5)
References
57(4)
6 Devices, Systems and Infrastructures for Smart Health
61(10)
6.1 Smart Health Infrastructures
62(3)
6.1.1 Smart Healthcare Infrastructure Challenges
64(1)
6.2 Smart Healthcare Structures
65(2)
6.2.1 Protective Systems
66(1)
6.2.2 Preventive Systems
66(1)
6.2.3 Responsive Systems
66(1)
6.2.4 Medical Automation Systems
66(1)
6.3 Smart Healthcare Devices
67(4)
6.3.1 Sensor-Based Smart Healthcare Devices
67(1)
6.3.2 Smartphone-Based Smart Healthcare Devices
68(1)
6.3.3 Microcontroller-Based Smart Healthcare Devices
68(1)
6.3.4 IoT/IoMT/Sensor-Based Healthcare Devices
68(1)
References
69(2)
7 Cyber-physical Systems for Healthcare
71(16)
7.1 Necessity of CPSs
72(1)
7.2 CPS Standards
73(1)
7.2.1 Standard Model to Synergic Model
73(1)
7.2.2 Distinctive and Conceptual Realization Characteristics of CPSs
74(1)
7.3 CPS Architecture
74(1)
7.4 Technologies Related to CPSs
75(4)
7.4.1 Advances in Macro-robotic Technologies
76(1)
7.4.2 Synergic Technologies
76(3)
7.5 Benefits and Applications of CPS
79(3)
7.5.1 Automobiles and Transportation
79(1)
7.5.2 Healthcare and Medicines
79(1)
7.5.3 Manufacturing
80(1)
7.5.4 Security and Surveillance
80(1)
7.5.5 Power and Thermal Energy Management
81(1)
7.5.6 Smart Homes and Buildings
81(1)
7.5.7 Construction
81(1)
7.6 CPSs for Healthcare (CPSsH)
82(1)
7.7 CPSs Issues and Challenges
82(3)
7.7.1 Software Consistency
83(1)
7.7.2 Medical Device Interactions
83(1)
7.7.3 Data Mining
83(1)
7.7.4 Privacy and Security
84(1)
7.7.5 Program Response
84(1)
7.7.6 Processing of Complex Queries
84(1)
7.7.7 Absence of a Prototype Structure
84(1)
7.8 CPSs and Future Medical Devices
85(2)
References
86(1)
8 Big Data Analytics and Cognitive Computing in Smart Health Systems
87(14)
8.1 Big Data Analytics
89(5)
8.1.1 Characteristics of Big Data
89(1)
8.1.2 The `Four V's' of Big Data Analytics in Healthcare
90(1)
8.1.3 Architecture of Big Data Analytics in Healthcare
91(1)
8.1.4 Process of Big Data Analytics
91(2)
8.1.5 Need for Big Data in Healthcare
93(1)
8.1.6 Big Data Framework for Smart Healthcare
93(1)
8.1.7 Big Data Applications for Healthcare
94(1)
8.2 Cognitive Computing for Healthcare
94(2)
8.2.1 Cognitive Analytics Architecture
95(1)
8.3 Healthcare and Data Management Role Players
96(1)
8.4 Impact of Cognitive Computing Systems on Healthcare
97(1)
8.5 Smart Healthcare Approaches
97(1)
8.6 Big Data Challenges in Healthcare Systems
98(1)
8.7 Big Data and Cognitive Technology Future Plans for Healthcare 98 References
99(2)
9 Values and Risks Associated with Smart Health
101(12)
9.1 Goals of Smart Health Systems
103(1)
9.2 Principles of Smart Health Systems
104(1)
9.3 Classification of Smart Healthcare
105(1)
9.4 Smart Health System Essentials
105(2)
9.5 Security Requirements of Smart Healthcare
107(2)
9.6 Major Risks Related to Smart Healthcare
109(1)
9.7 Security Solution of Smart Health Applications
109(1)
9.8 Smart Health System Services
109(4)
References
110(3)
10 Challenges, Opportunities and Future Trends in Smart Health
113
10.1 Challenges in Adoption of Smart Healthcare Systems
115(2)
10.1.1 Collection or Gathering Information
115(1)
10.1.2 Storage and Recovery of Data
116(1)
10.1.3 Knowledge Acquisition
117(1)
10.1.4 Smart Healthcare Applications
117(1)
10.2 Transformational Challenges for Smart Healthcare Centres
117(2)
10.2.1 Systems for Patient Monitoring in Smart Healthcare Systems
118(1)
10.2.2 Data Accuracy in Smart Healthcare Systems
118(1)
10.2.3 Cyber-security in Smart Healthcare Systems
118(1)
10.2.4 Reducing the Costs of Devices and Sensors in Smart Healthcare Systems
118(1)
10.2.5 Data Processing and Validation in Smart Healthcare Systems
119(1)
10.2.6 Tuning and Interoperability of Smart Healthcare Systems
119(1)
10.3 Opportunities in Smart Healthcare
119(2)
10.3.1 Remote Monitoring
120(1)
10.3.2 Chronic Self-Management
120(1)
10.3.3 Performance Improvement
120(1)
10.3.4 Behaviour Modification
120(1)
10.3.5 Detection and Diagnosis
121(1)
10.4 Trends Shaping the Future of Smart Healthcare
121
References
124
Dr. Sonali Vyas is serving as an academician and researcher for around a decade. Currently, she is working as assistant professor (Senior Scale) at the University of Petroleum and Energy Studies, Uttarakhand.





She is a professional member of CSI, IEEE, ACM-India, IFERP, IAENG, ISOC, SCRS and IJERT.





She has been awarded as Best Academician of the Year Award (Female) in "Global Education and Corporate Leadership Awards (GECL-2018).





Her research interest includes Database Virtualization, Data Mining, and Big Data Analytics. She has authored an ample number of research papers, articles and chapters in refereed journals/conference proceedings and books. She is an editor of Pervasive Computing: A Networking Perspective and Future Directions, Springer Nature and Smart Farming Technologies for Sustainable Agricultural Development, IGI Global. She acted as a guest editor in a special issue of Elsevier International Journal of Computer and Electrical Engineering (CAEE) and Machine Learning and Software Systems in Journal of Statistics & Management Systems (JSMS) (Thomson Reuters). She is also a member of the editorial board and reviewer board in many referred national and international journals.





She is an active member of the Organizing Committee, National Advisory Board and Technical Program Committee at many International and National conferences. She has also chaired sessions in various reputed international and national conferences.





Prof. (Dr) Deepshikha Bhargava has rich experience of around 20+ years as an academician. Currently, she is working as a professor and HoD- Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun.





She is also presiding officer at the Internal Complaints Committee of the university. She had been chairman, gender cell for three years at Amity University Jaipur.





She has published 16 books and 70+ research papers in journalsand conference proceedings. She served as visiting professor at Université des Mascareignes (UDM), Ministry of Education and Human Resources, Tertiary Education and Scientific Research, Mauritius.





She is a member of Institute of Engineers (IE), ACM-W, IEEE, Computer Science Teachers Association (CSTA), USA; Computer Society of India (CSI); Project Management Institute (PMI), Indian Society of Lightening Engineers (ISLE) and Vigyan Bharti (Vibha). Prof Bhargava has received the award Active Participation Woman Award, Best Faculty of the year under the subcategory Authoring Books on Contemporary Subjects to name a few. She has also awarded by MHRD, Govt. of India in the year 1992 for academic excellence.





Her research area includes soft computing, bio-inspired computation and software agents.