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Internet of Things and Personalized Healthcare Systems 2019 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 132 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 44 Illustrations, color; 17 Illustrations, black and white; IX, 132 p. 61 illus., 44 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Forensic and Medical Bioinformatics
  • Ilmumisaeg: 13-Nov-2018
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811308659
  • ISBN-13: 9789811308659
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Internet of Things and Personalized Healthcare Systems 2019 ed.Suurem pilt
  • Formaat: Paperback / softback, 132 pages, kõrgus x laius: 235x155 mm, kaal: 454 g, 44 Illustrations, color; 17 Illustrations, black and white; IX, 132 p. 61 illus., 44 illus. in color., 1 Paperback / softback
  • Sari: SpringerBriefs in Forensic and Medical Bioinformatics
  • Ilmumisaeg: 13-Nov-2018
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811308659
  • ISBN-13: 9789811308659
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789811308659.html

This book highlights the issues and challenges in personalised healthcare systems. The individual chapters address different aspects of such systems, including the novel Internet of Things (IoT) system architectures in healthcare and emerging e-health based IoT applications. Moreover, the book investigates the impact of cutting-edge innovations on the IoT.

1 Sensitivity Analysis of Micro Mass Optical MEMS Sensor for Biomedical IoT Devices 1(12)
Mala Serene
Rajasekhara Babu
Zachariah C. Alex
1.1 Introduction
1(1)
1.2 Modeling and Simulation
2(1)
1.3 Different Shapes of Cantilever
3(1)
1.4 Rectangular-Shaped Micro Mass Optical MEMS Sensor
4(1)
1.5 Trapezoidal/Triangular-Shaped Micro Mass Optical MEMS Sensor
5(2)
1.6 Step Profile-Shaped Micro Mass Optical MEMS Sensor
7(1)
1.7 Results and Discussion
8(3)
1.8 Conclusion
11(1)
References
11(2)
2 Enhancing the Performance of Decision Tree Using NSUM Technique for Diabetes Patients 13(8)
Nithya Semi
M. Rajasekhara Babu
2.1 Introduction
13(3)
2.2 Related Work
16(1)
2.3 Mutual Information
17(1)
2.3.1 Symmetric Uncertainty
17(1)
2.3.2 Proposed Algorithm
18(1)
2.4 Experimental Result and Discussion
18(1)
2.5 Conclusion and Future Scope
19(1)
References
19(2)
3 A Novel Framework for Healthcare Monitoring System Through Cyber-Physical System 21(16)
K. Monisha
M. Rajasekhara Babu
3.1 Introduction
22(1)
3.2 Related Work
23(4)
3.2.1 Wireless Body Area Network (WBAN) in Healthcare System
23(1)
3.2.2 Electronic Health Record (EHR) Assisted by Cloud
24(2)
3.2.3 Data Security in Healthcare Application
26(1)
3.3 Framework for Healthcare Application Through CPS
27(2)
3.4 Internet of Medical Things (IoMT)
29(1)
3.5 Proposed Method
30(2)
3.6 Result and Discussion
32(1)
3.7 Conclusion
33(1)
References
34(3)
4 An IoT Model to Improve Cognitive Skills of Student Learning Experience Using Neurosensors 37(14)
Abhishek Padhi
M. Rajasekhara Babu
Bhasker Jha
Shrutisha Joshi
4.1 Introduction
37(4)
4.1.1 Needs or Requirements
37(1)
4.1.2 Why This Work?
38(2)
4.1.3 ThinkGear Measurements (MindSet Pro/TGEM)
40(1)
4.2 Existing Methods
41(4)
4.3 Proposed Method
45(2)
4.4 Result and Discussion
47(1)
4.5 Conclusion
48(1)
References
49(2)
5 AdaBoost with Feature Selection Using IoT to Bring the Paths for Somatic Mutations Evaluation in Cancer 51(14)
Anuradha Chokka
K. Sandhya Rani
5.1 Introduction
51(3)
5.1.1 AdaBoost Technique
52(1)
5.1.2 Feature Selection Techniques
52(1)
5.1.3 Internet of Things (IoT)
53(1)
5.1.4 Challenges in Sequencing
53(1)
5.2 Existing Models
54(1)
5.3 Methodology
55(6)
5.3.1 Redundancy and Relevancy Analysis Approach
55(1)
5.3.2 Feature Redundancy and Feature Relevancy
56(1)
5.3.3 Defining a Framework of AdaBoost Technique with Feature Selection
56(1)
5.3.4 Schematic Representation for the Proposed Algorithm
57(1)
5.3.5 Algorithm and Analysis
57(1)
5.3.6 IoT Wearables to Detect Cancer
58(3)
5.4 Conclusions
61(1)
References
62(3)
6 A Fuzzy-Based Expert System to Diagnose Alzheimer's Disease 65(10)
R.M. Mallika
K. UshaRani
K. Hemalatha
6.1 Introduction
65(1)
6.2 Literature Survey
66(1)
6.3 Materials and Methods
67(5)
6.3.1 Dataset
67(1)
6.3.2 Proposed Methodology
67(5)
6.4 Experimental Results
72(1)
6.5 Conclusion
73(1)
References
73(2)
7 Secured Architecture for Internet of Things-Enabled Personalized Healthcare Systems 75(6)
Vikram Neerugatti
A. Rama Mohan Reddy
7.1 Introduction
75(2)
7.2 Related Work
77(1)
7.3 Proposed Architecture
77(2)
7.4 Conclusion
79(1)
References
79(2)
8 Role of Imaging Modality in Premature Detection of Bosom Irregularity 81(12)
Modepalli Kavitha
P. Venkata Krishna
V. Saritha
8.1 Introduction
81(2)
8.2 Mammography
83(2)
8.3 Thermography
85(3)
8.4 Result Analysis
88(2)
8.5 Conclusion
90(1)
8.6 Future Work
91(1)
References
91(2)
9 Healthcare Application Development in Mobile and Cloud Environments 93(12)
B. Mallikarjuna
D. Arun Kumar Reddy
9.1 Introduction
93(1)
9.2 Related Work
94(1)
9.3 Analysis of Health Diseases
95(2)
9.4 Proposed Application Overview
97(2)
9.5 Experimental Evaluation
99(3)
9.6 Conclusion
102(1)
References
103(2)
10 A Computational Approach to Predict Diabetic Retinopathy Through Data Analytics 105(8)
Ashraf Ali Shaik
Ch Prathima
Naresh Babu Muppalaneni
10.1 Introduction
105(2)
10.1.1 Steps in Algorithm
107(1)
10.2 Methodology
107(2)
10.2.1 Description of Dataset
107(1)
10.2.2 Attribute Information
108(1)
10.2.3 Cross-Validation
108(1)
10.2.4 Classification Matrix
108(1)
10.2.5 Bagging and Boosting
109(1)
10.3 Performance Measures
109(1)
10.3.1 Accuracy
109(1)
10.3.2 Sensitivity
109(1)
10.3.3 Specificity
110(1)
10.3.4 Classification Matrix
110(1)
10.4 Tools Used and Results Discussion
110(1)
10.5 Conclusion
111(1)
References
112(1)
11 Diagnosis of Chest Diseases Using Artificial Neural Networks 113(8)
Himaja Gadi
G. Lavanya Devi
N. Ramesh
11.1 Introduction
113(1)
11.2 Method
114(1)
11.3 Neural Networks
114(1)
11.4 Types of Neural Networks
114(2)
11.5 Back-Propagation Algorithm
116(1)
11.6 Architecture
117(1)
11.7 Validation Checks
117(1)
11.8 Results and Description
117(2)
11.9 Conclusion
119(1)
References
119(2)
12 Study on Efficient and Adaptive Reproducing Management in Hadoop Distributed File System 121
P. Satheesh
B. Srinivas
P.R.S. Naidu
B. Prasanth Kumar
12.1 Introduction
121(1)
12.2 Related Work
122(5)
12.2.1 Distributed Storage
123(1)
12.2.2 Information Replication
124(1)
12.2.3 Replica Placement
125(2)
12.3 Existing System
127(1)
12.3.1 Data Locality Problem
127(1)
12.4 Proposed System
127(3)
12.4.1 System Description
127(2)
12.4.2 Replication Management
129(1)
12.5 Results
130(1)
12.6 Conclusion
131(1)
References
131
Dr. Sasikumar Gurumoorthy is a Professor at the Department of Computer Science and Systems Engineering, Sree Vidyanikethan Engineering College in Tirupati, India. With 12 years of teaching and 9 years of research experience, he has held various senior positions such as Head of the Department, Chief Superintendent, and Assistant Chief Superintendent of University Exams. His current interests include soft computing and artificial intelligence in biomedical engineering, human and machine interaction and applications of intelligent system techniques, new user interfaces, brain-based interactions, human-centric computing, fuzzy sets and systems, image processing, cloud computing, content-based learning and social network analysis. He has published more than 90 technical papers in various international journals, conference proceedings, and book chapters. He serves on the editorial board of several international journals like AIRCC, NCICT, MAT Journals, IFERP and IJERCSE, and is a reviewer for 11 international journals. For his outstanding contributions in the Wipro-Misson10X, he was awarded the In Pursuit of Excellence in Engineering Education through Innovation Prize (in 2009). He has received a Research Grant from DST-CSRI to work on an Intelligent System to Classify Human Brain Signals for Finding Brain Diseases and is currently associated with many professional bodies, including the CSI, IEEE, ACM, ISTE, IAENG, AIRCC, IACSIT and INEER.





Dr. P. Venkata Krishna is currently a Professor of Computer Science and Director at Sri Padmavati Mahila University, Tirupati, India. He received his Ph.D. from VIT University, Vellore, India. Dr. Krishna has several years of experience working in academia, research, teaching, consultancy, academic administration and project management roles. His current research interests include mobile and wireless systems, cross-layer wireless network design, QoS and cloud computing.







Dr. Mohammad S. Obaidat (Fellow of IEEE and Fellow of SCS) is an internationally respected academic/researcher/scientist. He received his Ph.D. and M.S. degrees in Computer Engineering with a minor in Computer Science from The Ohio State University, Columbus, Ohio, USA. His previous positions include Advisor to the President of Philadelphia University for Research, Development and Information Technology; President of the Society for Molding and Simulation International, SCS; Senior Vice President of SCS; Dean of the College of Engineering at Prince Sultan University; Chair and Professor of the Department of Computer and Information Science and Director of the MS Graduate Program in Data Analytics at Fordham University; Chair and Professor of the Department of Computer Science and Director of the Graduate Program at Monmouth University. Dr. Obaidat is currently a Full Professor at the King Abdullah II School of Information Technology at the University of Jordan.