{"product_id":"the-internet-of-medical-things-iomt-9781119768838","title":"The Internet of Medical Things Iomt","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 \u003ci\u003eIn Silico \u003c\/i\u003eMolecular Modeling and Docking Analysis in Lung Cancer Cell Proteins 1\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eManisha Sritharan and Asita Elengoe\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Methodology 4\u003c\/p\u003e \u003cp\u003e1.2.1 Sequence of Protein 4\u003c\/p\u003e \u003cp\u003e1.2.2 Homology Modeling 4\u003c\/p\u003e \u003cp\u003e1.2.3 Physiochemical Characterization 4\u003c\/p\u003e \u003cp\u003e1.2.4 Determination of Secondary Models 4\u003c\/p\u003e \u003cp\u003e1.2.5 Determination of Stability of Protein Structures 4\u003c\/p\u003e \u003cp\u003e1.2.6 Identification of Active Site 4\u003c\/p\u003e \u003cp\u003e1.2.7 Preparation of Ligand Model 5\u003c\/p\u003e \u003cp\u003e1.2.8 Docking of Target Protein and Phytocompound 5\u003c\/p\u003e \u003cp\u003e1.3 Results and Discussion 5\u003c\/p\u003e \u003cp\u003e1.3.1 Determination of Physiochemical Characters 5\u003c\/p\u003e \u003cp\u003e1.3.2 Prediction of Secondary Structures 7\u003c\/p\u003e \u003cp\u003e1.3.3 Verification of Stability of Protein Structures 7\u003c\/p\u003e \u003cp\u003e1.3.4 Identification of Active Sites 14\u003c\/p\u003e \u003cp\u003e1.3.5 Target Protein-Ligand Docking 14\u003c\/p\u003e \u003cp\u003e1.4 Conclusion 18\u003c\/p\u003e \u003cp\u003eReferences 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Medical Data Classification in Cloud Computing Using Soft Computing With Voting Classifier: A Review 23\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSaurabh Sharma, Harish K. Shakya and Ashish Mishra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 24\u003c\/p\u003e \u003cp\u003e2.1.1 Security in Medical Big Data Analytics 24\u003c\/p\u003e \u003cp\u003e2.1.1.1 Capture 24\u003c\/p\u003e \u003cp\u003e2.1.1.2 Cleaning 25\u003c\/p\u003e \u003cp\u003e2.1.1.3 Storage 25\u003c\/p\u003e \u003cp\u003e2.1.1.4 Security 26\u003c\/p\u003e \u003cp\u003e2.1.1.5 Stewardship 26\u003c\/p\u003e \u003cp\u003e2.2 Access Control–Based Security 27\u003c\/p\u003e \u003cp\u003e2.2.1 Authentication 27\u003c\/p\u003e \u003cp\u003e2.2.1.1 User Password Authentication 28\u003c\/p\u003e \u003cp\u003e2.2.1.2 Windows-Based User Authentication 28\u003c\/p\u003e \u003cp\u003e2.2.1.3 Directory-Based Authentication 28\u003c\/p\u003e \u003cp\u003e2.2.1.4 Certificate-Based Authentication 28\u003c\/p\u003e \u003cp\u003e2.2.1.5 Smart Card–Based Authentication 29\u003c\/p\u003e \u003cp\u003e2.2.1.6 Biometrics 29\u003c\/p\u003e \u003cp\u003e2.2.1.7 Grid-Based Authentication 29\u003c\/p\u003e \u003cp\u003e2.2.1.8 Knowledge-Based Authentication 29\u003c\/p\u003e \u003cp\u003e2.2.1.9 Machine Authentication 29\u003c\/p\u003e \u003cp\u003e2.2.1.10 One-Time Password (OTP) 30\u003c\/p\u003e \u003cp\u003e2.2.1.11 Authority 30\u003c\/p\u003e \u003cp\u003e2.2.1.12 Global Authorization 30\u003c\/p\u003e \u003cp\u003e2.3 System Model 30\u003c\/p\u003e \u003cp\u003e2.3.1 Role and Purpose of Design 31\u003c\/p\u003e \u003cp\u003e2.3.1.1 Patients 31\u003c\/p\u003e \u003cp\u003e2.3.1.2 Cloud Server 31\u003c\/p\u003e \u003cp\u003e2.3.1.3 Doctor 31\u003c\/p\u003e \u003cp\u003e2.4 Data Classification 32\u003c\/p\u003e \u003cp\u003e2.4.1 Access Control 32\u003c\/p\u003e \u003cp\u003e2.4.2 Content 33\u003c\/p\u003e \u003cp\u003e2.4.3 Storage 33\u003c\/p\u003e \u003cp\u003e2.4.4 Soft Computing Techniques for Data Classification 34\u003c\/p\u003e \u003cp\u003e2.5 Related Work 36\u003c\/p\u003e \u003cp\u003e2.6 Conclusion 42\u003c\/p\u003e \u003cp\u003eReferences 43\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Research Challenges in Pre-Copy Virtual Machine Migration in Cloud Environment 45\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eNirmala Devi N. and Vengatesh Kumar S.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 46\u003c\/p\u003e \u003cp\u003e3.1.1 Cloud Computing 46\u003c\/p\u003e \u003cp\u003e3.1.1.1 Cloud Service Provider 47\u003c\/p\u003e \u003cp\u003e3.1.1.2 Data Storage and Security 47\u003c\/p\u003e \u003cp\u003e3.1.2 Virtualization 48\u003c\/p\u003e \u003cp\u003e3.1.2.1 Virtualization Terminology 49\u003c\/p\u003e \u003cp\u003e3.1.3 Approach to Virtualization 50\u003c\/p\u003e \u003cp\u003e3.1.4 Processor Issues 51\u003c\/p\u003e \u003cp\u003e3.1.5 Memory Management 51\u003c\/p\u003e \u003cp\u003e3.1.6 Benefits of Virtualization 51\u003c\/p\u003e \u003cp\u003e3.1.7 Virtual Machine Migration 51\u003c\/p\u003e \u003cp\u003e3.1.7.1 Pre-Copy 52\u003c\/p\u003e \u003cp\u003e3.1.7.2 Post-Copy 52\u003c\/p\u003e \u003cp\u003e3.1.7.3 Stop and Copy 53\u003c\/p\u003e \u003cp\u003e3.2 Existing Technology and Its Review 54\u003c\/p\u003e \u003cp\u003e3.3 Research Design 56\u003c\/p\u003e \u003cp\u003e3.3.1 Basic Overview of VM Pre-Copy Live Migration 57\u003c\/p\u003e \u003cp\u003e3.3.2 Improved Pre-Copy Approach 58\u003c\/p\u003e \u003cp\u003e3.3.3 Time Series–Based Pre-Copy Approach 60\u003c\/p\u003e \u003cp\u003e3.3.4 Memory-Bound Pre-Copy Live Migration 62\u003c\/p\u003e \u003cp\u003e3.3.5 Three-Phase Optimization Method (TPO) 62\u003c\/p\u003e \u003cp\u003e3.3.6 Multiphase Pre-Copy Strategy 64\u003c\/p\u003e \u003cp\u003e3.4 Results 65\u003c\/p\u003e \u003cp\u003e3.4.1 Finding 65\u003c\/p\u003e \u003cp\u003e3.5 Discussion 69\u003c\/p\u003e \u003cp\u003e3.5.1 Limitation 69\u003c\/p\u003e \u003cp\u003e3.5.2 Future Scope 70\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 70\u003c\/p\u003e \u003cp\u003eReferences 71\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Estimation and Analysis of Prediction Rate of Pre-Trained Deep Learning Network in Classification of Brain Tumor MRI Images 73\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKrishnamoorthy Raghavan Narasu, Anima Nanda, Marshiana D., Bestley Joe and Vinoth Kumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 74\u003c\/p\u003e \u003cp\u003e4.2 Classes of Brain Tumors 75\u003c\/p\u003e \u003cp\u003e4.3 Literature Survey 76\u003c\/p\u003e \u003cp\u003e4.4 Methodology 78\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 93\u003c\/p\u003e \u003cp\u003eReferences 95\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 An Intelligent Healthcare Monitoring System for Coma Patients 99\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBethanney Janney J., T. Sudhakar, Sindu Divakaran, Chandana H. and Caroline Chriselda L.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 100\u003c\/p\u003e \u003cp\u003e5.2 Related Works 102\u003c\/p\u003e \u003cp\u003e5.3 Materials and Methods 104\u003c\/p\u003e \u003cp\u003e5.3.1 Existing System 104\u003c\/p\u003e \u003cp\u003e5.3.2 Proposed System 105\u003c\/p\u003e \u003cp\u003e5.3.3 Working 105\u003c\/p\u003e \u003cp\u003e5.3.4 Module Description 106\u003c\/p\u003e \u003cp\u003e5.3.4.1 Pulse Sensor 106\u003c\/p\u003e \u003cp\u003e5.3.4.2 Temperature Sensor 107\u003c\/p\u003e \u003cp\u003e5.3.4.3 Spirometer 107\u003c\/p\u003e \u003cp\u003e5.3.4.4 OpenCV (Open Source Computer Vision) 108\u003c\/p\u003e \u003cp\u003e5.3.4.5 Raspberry Pi 108\u003c\/p\u003e \u003cp\u003e5.3.4.6 USB Camera 109\u003c\/p\u003e \u003cp\u003e5.3.4.7 AVR Module 109\u003c\/p\u003e \u003cp\u003e5.3.4.8 Power Supply 109\u003c\/p\u003e \u003cp\u003e5.3.4.9 USB to TTL Converter 110\u003c\/p\u003e \u003cp\u003e5.3.4.10 EEG of Comatose Patients 110\u003c\/p\u003e \u003cp\u003e5.4 Results and Discussion 111\u003c\/p\u003e \u003cp\u003e5.5 Conclusion 116\u003c\/p\u003e \u003cp\u003eReferences 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Deep Learning Interpretation of Biomedical Data 121\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eT.R. Thamizhvani, R. Chandrasekaran and T.R. Ineyathendral\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 122\u003c\/p\u003e \u003cp\u003e6.2 Deep Learning Models 125\u003c\/p\u003e \u003cp\u003e6.2.1 Recurrent Neural Networks 125\u003c\/p\u003e \u003cp\u003e6.2.2 LSTM\/GRU Networks 127\u003c\/p\u003e \u003cp\u003e6.2.3 Convolutional Neural Networks 128\u003c\/p\u003e \u003cp\u003e6.2.4 Deep Belief Networks 130\u003c\/p\u003e \u003cp\u003e6.2.5 Deep Stacking Networks 131\u003c\/p\u003e \u003cp\u003e6.3 Interpretation of Deep Learning With Biomedical Data 132\u003c\/p\u003e \u003cp\u003e6.4 Conclusion 139\u003c\/p\u003e \u003cp\u003eReferences 140\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Evolution of Electronic Health Records 143\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eG. Umashankar, Abinaya P., J. Premkumar, T. Sudhakar and S. Krishnakumar\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 143\u003c\/p\u003e \u003cp\u003e7.2 Traditional Paper Method 144\u003c\/p\u003e \u003cp\u003e7.3 IoMT 144\u003c\/p\u003e \u003cp\u003e7.4 Telemedicine and IoMT 145\u003c\/p\u003e \u003cp\u003e7.4.1 Advantages of Telemedicine 145\u003c\/p\u003e \u003cp\u003e7.4.2 Drawbacks 146\u003c\/p\u003e \u003cp\u003e7.4.3 IoMT Advantages with Telemedicine 146\u003c\/p\u003e \u003cp\u003e7.4.4 Limitations of IoMT With Telemedicine 147\u003c\/p\u003e \u003cp\u003e7.5 Cyber Security 147\u003c\/p\u003e \u003cp\u003e7.6 Materials and Methods 147\u003c\/p\u003e \u003cp\u003e7.6.1 General Method 147\u003c\/p\u003e \u003cp\u003e7.6.2 Data Security 148\u003c\/p\u003e \u003cp\u003e7.7 Literature Review 148\u003c\/p\u003e \u003cp\u003e7.8 Applications of Electronic Health Records 150\u003c\/p\u003e \u003cp\u003e7.8.1 Clinical Research 150\u003c\/p\u003e \u003cp\u003e7.8.1.1 Introduction 150\u003c\/p\u003e \u003cp\u003e7.8.1.2 Data Significance and Evaluation 151\u003c\/p\u003e \u003cp\u003e7.8.1.3 Conclusion 151\u003c\/p\u003e \u003cp\u003e7.8.2 Diagnosis and Monitoring 151\u003c\/p\u003e \u003cp\u003e7.8.2.1 Introduction 151\u003c\/p\u003e \u003cp\u003e7.8.2.2 Contributions 152\u003c\/p\u003e \u003cp\u003e7.8.2.3 Applications 152\u003c\/p\u003e \u003cp\u003e7.8.3 Track Medical Progression 153\u003c\/p\u003e \u003cp\u003e7.8.3.1 Introduction 153\u003c\/p\u003e \u003cp\u003e7.8.3.2 Method Used 153\u003c\/p\u003e \u003cp\u003e7.8.3.3 Conclusion 154\u003c\/p\u003e \u003cp\u003e7.8.4 Wearable Devices 154\u003c\/p\u003e \u003cp\u003e7.8.4.1 Introduction 154\u003c\/p\u003e \u003cp\u003e7.8.4.2 Proposed Method 155\u003c\/p\u003e \u003cp\u003e7.8.4.3 Conclusion 155\u003c\/p\u003e \u003cp\u003e7.9 Results and Discussion 155\u003c\/p\u003e \u003cp\u003e7.10 Challenges Ahead 157\u003c\/p\u003e \u003cp\u003e7.11 Conclusion 158\u003c\/p\u003e \u003cp\u003eReferences 158\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Architecture of IoMT in Healthcare 161\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eA. Josephin Arockia Dhiyya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 161\u003c\/p\u003e \u003cp\u003e8.1.1 On-Body Segment 162\u003c\/p\u003e \u003cp\u003e8.1.2 In-Home Segment 162\u003c\/p\u003e \u003cp\u003e8.1.3 Network Segment Layer 163\u003c\/p\u003e \u003cp\u003e8.1.4 In-Clinic Segment 163\u003c\/p\u003e \u003cp\u003e8.1.5 In-Hospital Segment 163\u003c\/p\u003e \u003cp\u003e8.1.6 Future of IoMT? 164\u003c\/p\u003e \u003cp\u003e8.2 Preferences of the Internet of Things 165\u003c\/p\u003e \u003cp\u003e8.2.1 Cost Decrease 165\u003c\/p\u003e \u003cp\u003e8.2.2 Proficiency and Efficiency 165\u003c\/p\u003e \u003cp\u003e8.2.3 Business Openings 165\u003c\/p\u003e \u003cp\u003e8.2.4 Client Experience 166\u003c\/p\u003e \u003cp\u003e8.2.5 Portability and Nimbleness 166\u003c\/p\u003e \u003cp\u003e8.3 loMT Progress in COVID-19 Situations: Presentation 167\u003c\/p\u003e \u003cp\u003e8.3.1 The IoMT Environment 168\u003c\/p\u003e \u003cp\u003e8.3.2 IoMT Pandemic Alleviation Design 169\u003c\/p\u003e \u003cp\u003e8.3.3 Man-Made Consciousness and Large Information Innovation in IoMT 170\u003c\/p\u003e \u003cp\u003e8.4 Major Applications of IoMT 171\u003c\/p\u003e \u003cp\u003eReferences 172\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Performance Assessment of IoMT Services and Protocols 173\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eA. Keerthana and Karthiga\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 174\u003c\/p\u003e \u003cp\u003e9.2 IoMT Architecture and Platform 175\u003c\/p\u003e \u003cp\u003e9.2.1 Architecture 176\u003c\/p\u003e \u003cp\u003e9.2.2 Devices Integration Layer 177\u003c\/p\u003e \u003cp\u003e9.3 Types of Protocols 177\u003c\/p\u003e \u003cp\u003e9.3.1 Internet Protocol for Medical IoT Smart Devices 177\u003c\/p\u003e \u003cp\u003e9.3.1.1 HTTP 178\u003c\/p\u003e \u003cp\u003e9.3.1.2 Message Queue Telemetry Transport (MQTT) 179\u003c\/p\u003e \u003cp\u003e9.3.1.3 Constrained Application Protocol (CoAP) 180\u003c\/p\u003e \u003cp\u003e9.3.1.4 AMQP: Advanced Message Queuing Protocol (AMQP) 181\u003c\/p\u003e \u003cp\u003e9.3.1.5 Extensible Message and Presence Protocol (XMPP) 181\u003c\/p\u003e \u003cp\u003e9.3.1.6 DDS 183\u003c\/p\u003e \u003cp\u003e9.4 Testing Process in IoMT 183\u003c\/p\u003e \u003cp\u003e9.5 Issues and Challenges 185\u003c\/p\u003e \u003cp\u003e9.6 Conclusion 185\u003c\/p\u003e \u003cp\u003eReferences 185\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Performance Evaluation of Wearable IoT-Enabled Mesh Network for Rural Health Monitoring 187\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eG. Merlin Sheeba and Y. Bevish Jinila\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 188\u003c\/p\u003e \u003cp\u003e10.2 Proposed System Framework 190\u003c\/p\u003e \u003cp\u003e10.2.1 System Description 190\u003c\/p\u003e \u003cp\u003e10.2.2 Health Monitoring Center 192\u003c\/p\u003e \u003cp\u003e10.2.2.1 Body Sensor 192\u003c\/p\u003e \u003cp\u003e10.2.2.2 Wireless Sensor Coordinator\/Transceiver 192\u003c\/p\u003e \u003cp\u003e10.2.2.3 Ontology Information Center 195\u003c\/p\u003e \u003cp\u003e10.2.2.4 Mesh Backbone-Placement and Routing 196\u003c\/p\u003e \u003cp\u003e10.3 Experimental Evaluation 200\u003c\/p\u003e \u003cp\u003e10.4 Performance Evaluation 201\u003c\/p\u003e \u003cp\u003e10.4.1 Energy Consumption 201\u003c\/p\u003e \u003cp\u003e10.4.2 Survival Rate 201\u003c\/p\u003e \u003cp\u003e10.4.3 End-to-End Delay 202\u003c\/p\u003e \u003cp\u003e10.5 Conclusion 204\u003c\/p\u003e \u003cp\u003eReferences 204\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Management of Diabetes Mellitus (DM) for Children and Adults Based on Internet of Things (IoT) 207\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eKrishnakumar S., Umashankar G., Lumen Christy V., Vikas and Hemalatha R.J.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 208\u003c\/p\u003e \u003cp\u003e11.1.1 Prevalence 209\u003c\/p\u003e \u003cp\u003e11.1.2 Management of Diabetes 209\u003c\/p\u003e \u003cp\u003e11.1.3 Blood Glucose Monitoring 210\u003c\/p\u003e \u003cp\u003e11.1.4 Continuous Glucose Monitors 211\u003c\/p\u003e \u003cp\u003e11.1.5 Minimally Invasive Glucose Monitors 211\u003c\/p\u003e \u003cp\u003e11.1.6 Non-Invasive Glucose Monitors 211\u003c\/p\u003e \u003cp\u003e11.1.7 Existing System 211\u003c\/p\u003e \u003cp\u003e11.2 Materials and Methods 212\u003c\/p\u003e \u003cp\u003e11.2.1 Artificial Neural Network 212\u003c\/p\u003e \u003cp\u003e11.2.2 Data Acquisition 213\u003c\/p\u003e \u003cp\u003e11.2.3 Histogram Calculation 213\u003c\/p\u003e \u003cp\u003e11.2.4 IoT Cloud Computing 214\u003c\/p\u003e \u003cp\u003e11.2.5 Proposed System 215\u003c\/p\u003e \u003cp\u003e11.2.6 Advantages 215\u003c\/p\u003e \u003cp\u003e11.2.7 Disadvantages 215\u003c\/p\u003e \u003cp\u003e11.2.8 Applications 216\u003c\/p\u003e \u003cp\u003e11.2.9 Arduino Pro Mini 216\u003c\/p\u003e \u003cp\u003e11.2.10 LM78XX 217\u003c\/p\u003e \u003cp\u003e11.2.11 MAX30100 218\u003c\/p\u003e \u003cp\u003e11.2.12 LM35 Temperature Sensors 218\u003c\/p\u003e \u003cp\u003e11.3 Results and Discussion 219\u003c\/p\u003e \u003cp\u003e11.4 Summary 222\u003c\/p\u003e \u003cp\u003e11.5 Conclusion 222\u003c\/p\u003e \u003cp\u003eReferences 223\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Wearable Health Monitoring Systems Using IoMT 225\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJaya Rubi and A. Josephin Arockia Dhivya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 225\u003c\/p\u003e \u003cp\u003e12.2 IoMT in Developing Wearable Health Surveillance System 226\u003c\/p\u003e \u003cp\u003e12.2.1 A Wearable Health Monitoring System with Multi-Parameters 227\u003c\/p\u003e \u003cp\u003e12.2.2 Wearable Input Device for Smart Glasses Based on a Wristband-Type Motion-Aware Touch Panel 228\u003c\/p\u003e \u003cp\u003e12.2.3 Smart Belt: A Wearable Device for Managing Abdominal Obesity 228\u003c\/p\u003e \u003cp\u003e12.2.4 Smart Bracelets: Automating the Personal Safety Using Wearable Smart Jewelry 228\u003c\/p\u003e \u003cp\u003e12.3 Vital Parameters That Can Be Monitored Using Wearable Devices 229\u003c\/p\u003e \u003cp\u003e12.3.1 Electrocardiogram 230\u003c\/p\u003e \u003cp\u003e12.3.2 Heart Rate 231\u003c\/p\u003e \u003cp\u003e12.3.3 Blood Pressure 232\u003c\/p\u003e \u003cp\u003e12.3.4 Respiration Rate 232\u003c\/p\u003e \u003cp\u003e12.3.5 Blood Oxygen Saturation 234\u003c\/p\u003e \u003cp\u003e12.3.6 Blood Glucose 235\u003c\/p\u003e \u003cp\u003e12.3.7 Skin Perspiration 236\u003c\/p\u003e \u003cp\u003e12.3.8 Capnography 238\u003c\/p\u003e \u003cp\u003e12.3.9 Body Temperature 239\u003c\/p\u003e \u003cp\u003e12.4 Challenges Faced in Customizing Wearable Devices 240\u003c\/p\u003e \u003cp\u003e12.4.1 Data Privacy 240\u003c\/p\u003e \u003cp\u003e12.4.2 Data Exchange 240\u003c\/p\u003e \u003cp\u003e12.4.3 Availability of Resources 241\u003c\/p\u003e \u003cp\u003e12.4.4 Storage Capacity 241\u003c\/p\u003e \u003cp\u003e12.4.5 Modeling the Relationship Between Acquired Measurement and Diseases 242\u003c\/p\u003e \u003cp\u003e12.4.6 Real-Time Processing 242\u003c\/p\u003e \u003cp\u003e12.4.7 Intelligence in Medical Care 242\u003c\/p\u003e \u003cp\u003e12.5 Conclusion 243\u003c\/p\u003e \u003cp\u003eReferences 244\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Future of Healthcare: Biomedical Big Data Analysis and IoMT 247\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eTamiziniyan G. and Keerthana A.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 248\u003c\/p\u003e \u003cp\u003e13.2 Big Data and IoT in Healthcare Industry 250\u003c\/p\u003e \u003cp\u003e13.3 Biomedical Big Data Types 251\u003c\/p\u003e \u003cp\u003e13.3.1 Electronic Health Records 252\u003c\/p\u003e \u003cp\u003e13.3.2 Administrative and Claims Data 252\u003c\/p\u003e \u003cp\u003e13.3.3 International Patient Disease Registries 252\u003c\/p\u003e \u003cp\u003e13.3.4 National Health Surveys 253\u003c\/p\u003e \u003cp\u003e13.3.5 Clinical Research and Trials Data 254\u003c\/p\u003e \u003cp\u003e13.4 Biomedical Data Acquisition Using IoT 254\u003c\/p\u003e \u003cp\u003e13.4.1 Wearable Sensor Suit 254\u003c\/p\u003e \u003cp\u003e13.4.2 Smartphones 255\u003c\/p\u003e \u003cp\u003e13.4.3 Smart Watches 255\u003c\/p\u003e \u003cp\u003e13.5 Biomedical Data Management Using IoT 256\u003c\/p\u003e \u003cp\u003e13.5.1 Apache Spark Framework 257\u003c\/p\u003e \u003cp\u003e13.5.2 MapReduce 258\u003c\/p\u003e \u003cp\u003e13.5.3 Apache Hadoop 258\u003c\/p\u003e \u003cp\u003e13.5.4 Clustering Algorithms 259\u003c\/p\u003e \u003cp\u003e13.5.5 K-Means Clustering 259\u003c\/p\u003e \u003cp\u003e13.5.6 Fuzzy C-Means Clustering 260\u003c\/p\u003e \u003cp\u003e13.5.7 DBSCAN 261\u003c\/p\u003e \u003cp\u003e13.6 Impact of Big Data and IoMT in Healthcare 262\u003c\/p\u003e \u003cp\u003e13.7 Discussions and Conclusions 263\u003c\/p\u003e \u003cp\u003eReferences 264\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Medical Data Security Using Blockchain With Soft Computing Techniques: A Review 269\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSaurabh Sharma, Harish K. Shakya and Ashish Mishra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 270\u003c\/p\u003e \u003cp\u003e14.2 Blockchain 272\u003c\/p\u003e \u003cp\u003e14.2.1 Blockchain Architecture 272\u003c\/p\u003e \u003cp\u003e14.2.2 Types of Blockchain Architecture 273\u003c\/p\u003e \u003cp\u003e14.2.3 Blockchain Applications 274\u003c\/p\u003e \u003cp\u003e14.2.4 General Applications of the Blockchain 276\u003c\/p\u003e \u003cp\u003e14.3 Blockchain as a Decentralized Security Framework 277\u003c\/p\u003e \u003cp\u003e14.3.1 Characteristics of Blockchain 278\u003c\/p\u003e \u003cp\u003e14.3.2 Limitations of Blockchain Technology 280\u003c\/p\u003e \u003cp\u003e14.4 Existing Healthcare Data Predictive Analytics Using Soft Computing Techniques in Data Science 281\u003c\/p\u003e \u003cp\u003e14.4.1 Data Science in Healthcare 281\u003c\/p\u003e \u003cp\u003e14.5 Literature Review: Medical Data Security in Cloud Storage 281\u003c\/p\u003e \u003cp\u003e14.6 Conclusion 286\u003c\/p\u003e \u003cp\u003eReferences 287\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Electronic Health Records: A Transitional View 289\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSrividhya G.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 289\u003c\/p\u003e \u003cp\u003e15.2 Ancient Medical Record, 1600 BC 290\u003c\/p\u003e \u003cp\u003e15.3 Greek Medical Record 291\u003c\/p\u003e \u003cp\u003e15.4 Islamic Medical Record 291\u003c\/p\u003e \u003cp\u003e15.5 European Civilization 292\u003c\/p\u003e \u003cp\u003e15.6 Swedish Health Record System 292\u003c\/p\u003e \u003cp\u003e15.7 French and German Contributions 293\u003c\/p\u003e \u003cp\u003e15.8 American Descriptions 293\u003c\/p\u003e \u003cp\u003e15.9 Beginning of Electronic Health Recording 297\u003c\/p\u003e \u003cp\u003e15.10 Conclusion 298\u003c\/p\u003e \u003cp\u003eReferences 298\u003c\/p\u003e \u003cp\u003eIndex 301\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49371826422103,"sku":"9781119768838","price":169.16,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119768838.jpg?v=1730154714","url":"https:\/\/bookcurl.com\/products\/the-internet-of-medical-things-iomt-9781119768838","provider":"Book Curl","version":"1.0","type":"link"}