Wireless Medical Sensor Networks for IoT-based eHealth (Healthcare Technologies)

Description

Internet of Things (IoT) enabled technology is evolving healthcare from conventional hub-based systems to more personalized eHealth systems, enabling faster and safer preventive care, lower overall cost, improved patient-centric practice and enhanced sustainability. Efficient IoT-enabled eHealth systems can be realized by providing highly customized access to rich medical information and efficient clinical decisions to each individual with unobtrusive monitoring. Wireless medical sensor networks (WMSNs) are at the heart of this concept, and their development is a key issue if such a concept is to achieve its potential. This book addresses the major challenges in realizing WMSNs in forthcoming IoT-based eHealth systems. Challenges vary from cost and energy efficiency to security and service quality, and to tackle such challenges WMSNs must meet certain expectations and requirements such as size constraints, manufacturing costs and resistance to environmental factors existing at deployment locations. Reflecting this the book focuses on both design and implementation aspects. Topics covered include the impact of medical sensor networks in smart-cities; an evaluation of mobile patient monitoring technologies; overview of wireless sensor devices in medical applications; cyber security issues in WMSNs and eHealth; smart hospital rooms and automated systems; medical sensor capabilities in smart cloud networks; swarm intelligence based medical diagnosis systems; and smart systems and device for the blind. Cover Contents About the editor Foreword 1 Sensor-enabled smart suit electronic IoT design platform with emergency services application 1.1 Introduction 1.2 System components 1.2.1 FLIR Lepton IR camera 1.2.2 IR camera software 1.2.3 Python-based flask web server 1.2.4 Raspberry Pi 3 Debian stretch operating system start 1.3 System hardware 1.3.1 Hardware data collection and transfer 1.4 Smart suit system 1.4.1 Thermal imager module 1.4.2 Flask server module 1.5 Wi-Fi setup and operation 1.6 Implementation 1.6.1 Components 1.6.2 Application 1.6.3 Mountain rescue services emergency response application 1.7 Conclusion Appendix A Software startup scripts and modules A.1 System startup detailed scripts A.2 Smart suit system application modules References 2 Medical sensor networks impact in smart cities 2.1 Introduction 2.2 Smart city 2.3 Smart healthcare in smart cities 2.4 Technologies used in smart healthcare 2.4.1 Artificial intelligence 2.4.2 Blockchain 2.4.3 Internet of Everything 2.5 IoT services in healthcare 2.5.1 Remote patient monitoring 2.5.2 Telehealth 2.5.3 Wearable devices for IoMT solutions 2.5.4 E-textiles in healthcare 2.5.5 Cancer treatment 2.5.6 Smart continuous glucose monitoring 2.5.7 Connected inhalers 2.5.8 Ingestible sensors 2.5.9 Connected contact lenses 2.5.10 Apple Watch app 2.5.11 Coagulation testing 2.5.12 Apple’s research kit 2.5.13 ADAMM asthma monitor 2.5.14 Wheelchair management 2.5.15 Electrocardiogram monitoring 2.5.16 Hand hygiene compliance 2.5.17 Blood pressure monitoring 2.5.18 Body temperature monitoring 2.6 IoT advantages in healthcare 2.7 Challenges 2.7.1 Security solutions 2.8 Conclusion References 3 The use of CRISPR as a diagnostic tool for healthcare in the IoT era 3.1 Introduction 3.1.1 Internet of Things in healthcare 3.1.2 CRISPR and CRISPR in nature 3.1.2.1 Stages 3.1.3 CRISPR in genetic engineering 3.2 The use of CRISPR-based biosensor as a diagnostic tool for point of care 3.2.1 CRISPR Cas9 and dCas9 3.2.2 Cas12 (Cpf1) 3.2.2.1 Mechanism of Cas12a as a sensor 3.2.3 Cas13a (C2C2) 3.2.3.1 Mechanism of Cas13a 3.2.3.2 Cas13a as biosensor 3.2.3.3 SHERLOCK 3.3 Conclusion References 4 Evaluation of mobile patient monitoring: a study in practice 4.1 Introduction 4.2 Literature review 4.3 Mobile health monitoring device approach 4.3.1 Components 4.3.2 Architecture 4.4 Discussions 4.5 Conclusions References 5 Image-based IoT measurement techniques in disease diagnosis 5.1 Introduction 5.2 Literature review 5.3 Applications of IoT with image processing in disease identification 5.3.1 Role of IoT in skin disease identification 5.3.2 Cancer detection by using image processing and IoT 5.3.3 IoT-powered plant disease and cassava identification 5.3.4 Malaria detection by using blood sample images with IoT 5.3.5 IoT-enabled plant disease detection 5.4 Fundamental steps of image-based IoT measurement system 5.5 IoT-based smartphone applications for disease detection 5.5.1 Leaf Doctor: an IoT-based expert system for plant disease detection 5.5.2 IoT-based Skin Vision app for skin disease detection 5.5.3 A smart way of anemia detection without taking blood sample 5.5.4 E-health monitoring system: iCare 5.5.5 Cancer detection by using IoT: DERMA/CARE 5.6 Smart E-health monitoring medical imaging modalities 5.6.1 Magnetic resonance imaging 5.6.2 X-ray 5.6.3 Ultrasound 5.6.4 Computed tomography 5.6.5 Nuclear medicine 5.7 Image-based IoT smart image analysis system 5.7.1 IoT-based smart plant root measurement: WinRHIZO system 5.7.2 Smart aquaculture IMAFISH system: real-time IoT-based smart system for fish disease identification References 6 The development of a blood infusion warmer device: a new device 6.1 Introduction 6.2 Related work 6.2.1 Water bath blood warmers 6.2.2 Intravenous (IV) tube warmers 6.2.3 Forced-air blood warmers 6.2.4 Dry-heat plate blood warmer 6.3 Methodology 6.3.1 Functionality 6.3.1.1 Architecture of the dry-heat plate blood warmer 6.3.2 Components of the in-line IV tube warmer 6.4 Discussions 6.5 Conclusions References 7 Wireless sensor devices in medical applications: an overview 7.1 Introduction 7.2 Medical applications of the WBAN 7.3 WBAN architecture 7.4 Sensor nodes 7.5 Standards of WBAN 7.6 WBAN layers 7.7 Wireless connection 7.7.1 Bluetooth 7.7.2 Zigbee and IEEE 802.15.4 7.7.3 Wi-Fi 7.8 Data delivery and intelligence in WBAN 7.9 Conclusion References 8 Toward a smart hospital room and automated systems 8.1 Introduction 8.2 Literature review 8.3 Methodology 8.3.1 Circuit design 8.4 System design 8.4.1 Voice recognition module 8.4.2 Arduino mega 8.4.3 Power supply circuit 8.5 Discussions 8.5.1 Breadboard layout 8.5.2 Soldering 8.5.3 Testing 8.6 Conclusion References 9 Security issues in wireless medical sensor networks 9.1 Introduction 9.1.1 Emergence of WMSNs 9.1.2 Wireless medical sensor devices: current trends and future directions 9.1.3 Growing aspect of WMSNs in healthcare applications 9.2 Related work 9.2.1 Privacy and security requirements: essential factor for use of WMSNs 9.2.2 Major security challenges and threats 9.2.2.1 Security issues/challenges 9.2.2.2 Security threats 9.2.3 Solutions to breach in security 9.3 Proposed work 9.4 Conclusion References 10 Acoustic glass for deaf people: a new device 10.1 Introduction 10.2 Literature review 10.3 Causes of hearing loss 10.4 Diagnosis and treatment of hearing loss 10.4.1 Diagnosis of hearing loss 10.4.2 The treatment of hearing loss 10.5 Methodology 10.6 Discussions 10.7 Conclusion References 11 A framework for blind people using wireless medical sensors network 11.1 Introduction 11.2 Related works 11.2.1 White cane 11.2.2 Ultrasonic-based blind assisting system 11.2.3 Infrared-based blind assisting system 11.2.4 Sensor-based blind assisting system with global positioning system 11.3 The method 11.3.1 The circuit 11.3.2 Connecting the circuit 11.3.3 Long cane (white cane) 11.3.4 Distance sensor 11.3.5 Buzzer 11.3.6 Switch 11.3.7 Vibration motor 11.3.8 Arduino Uno 11.3.9 Breadboard 11.3.10 Belt or bracelets 11.3.11 Servomotor 11.3.12 Resistors, cables, capacitors, and battery 11.4 Results and discussion 11.5 Conclusion References 12 Medical sensor capabilities in smart cloud networks: state-of-the-art approaches 12.1 Introduction 12.2 Background 12.3 Monitoring system architecture 12.3.1 Design issues and security challenges 12.3.1.1 Design issues 12.3.1.2 Topological challenges 12.3.1.3 Security challenges 12.3.2 Sensor node design 12.3.3 Security requirements 12.3.4 Hardware components 12.3.4.1 Gateway 12.3.4.2 Leaf node 12.3.4.3 Relay node 12.3.4.4 Sensor or actuator 12.3.4.5 Network topologies 12.3.5 Operating systems design specifications 12.4 Standard technologies in WMSN 12.4.1 Communication protocols 12.4.1.1 IoT data protocols 12.4.1.2 IoT network protocols 12.4.2 Programmable logic devices (PLDs) 12.4.3 Microcontroller unit 12.5 Applications of WMSN 12.5.1 Patient monitoring 12.5.2 Heart attack monitoring system 12.5.3 Handling COPD and PD patients 12.6 Conclusion References 13 Severity level classification and detection of breast cancer using computer-aided mammography techniques 13.1 Introduction 13.2 Related works 13.3 Problem definition 13.4 Proposed methodology 13.4.1 Preprocessing 13.4.2 Segmentation using modified region growing 13.4.3 Feature extraction 13.4.4 Two-stage classification 13.4.4.1 Optimized genetic fuzzy classification 13.4.4.2 Genetically optimized hybrid neural classification 13.5 Evaluation metrics 13.5.1 Sensitivity or true-positive rate 13.5.2 Specificity or false-positive rate 13.5.3 Accuracy 13.5.4 Positive predictive value or precision 13.5.5 Negative predictive value or recall 13.5.6 False-negative rate or miss rate 13.6 Discussions 13.7 Future enhancements 13.8 Conclusions References 14 Biosensors in healthcare: an overview 14.1 Introduction 14.2 Monitoring principles: transducers 14.3 Diabetes and the need for glucose monitoring 14.4 Biosensor for monitoring glucose 14.5 Historical perspectives of glucose biosensors 14.5.1 First generation of glucose biosensor 14.5.2 Second generation of glucose biosensors 14.5.3 Third generation of glucose biosensors 14.5.4 Continuous glucose monitoring systems 14.5.5 Noninvasive glucose monitoring system 14.6 Respiratory airflow monitoring sensor 14.6.1 Pressure and acoustic sensing devices 14.6.2 Thermal flow sensors 14.6.3 Humidity sensors 14.6.4 CO2 sensors 14.6.5 Indirect sensors 14.6.6 Torso devices 14.6.7 Magnetometry 14.6.8 Respiratory inductance plethysmograph 14.6.9 Strain gauge 14.6.10 Transthoracic impedance plethysmograph 14.6.11 Electrocardiographic sensor 14.6.12 Electromyographic sensors 14.6.13 Photoplethysmographic sensor 14.7 Conclusion References 15 Swarm intelligence-based medical diagnosis systems 15.1 Introduction 15.1.1 Particle swarm optimization 15.1.1.1 Particle swarm optimization for medical diagnosis 15.1.2 Ant colony optimization 15.1.2.1 Ant colony optimization for medical diagnosis 15.1.3 Artificial bee colony optimization 15.1.3.1 Artificial bee colony optimization for medical diagnosis 15.1.4 Bacterial foraging optimization 15.1.4.1 Bacterial foraging optimization-based medical diagnosis 15.2 Discussions 15.3 Conclusion References 16 An extraocular muscle stimulation system based on EOG and FES 16.1 Introduction 16.2 Literature review 16.2.1 Subjects and surgical procedures 16.2.2 Eye movement measurements 16.2.3 Stimulation procedures and experimental tools 16.2.4 Stimulation parameters 16.2.4.1 Frequency 16.2.4.2 Time 16.2.4.3 Amplitude 16.2.5 Experimental procedures 16.2.6 Comparison between related patent and our study 16.3 Methodology 16.3.1 Background of the study 16.3.2 Summary of the study 16.3.3 Detailed description of the device and system 16.4 Conclusions and future work References 17 Smart system for the blind 17.1 Introduction 17.1.1 Internet of Things 17.1.2 Definition of blindness 17.2 Related work 17.2.1 Comparisons 17.2.2 Results 17.2.2.1 Performance evaluation of Case Study 1 17.2.2.2 Performance evaluation of Case Study 2 17.3 Smart system for the blind 17.3.1 Overview 17.3.2 Methodology of the project 17.3.2.1 Arduino Uno 17.3.2.2 Arduino Nano 17.3.2.3 Global positioning system 17.3.2.4 Ultrasonic sensor 17.3.2.5 Vibration motor 17.3.2.6 LDR sensor and LED 17.3.2.7 Buzzers 17.3.2.8 Water sensor 17.3.2.9 Jumper wires 17.3.2.10 Breadboard 17.3.2.11 Battery 17.4 The working principle of the smart system materials 17.4.1 LDR sensor and LED circuit 17.4.2 Ultrasonic sensor and buzzer 17.4.3 Water sensor and vibration motor circuit 17.4.4 GPS circuit 17.5 The working principle of the smart system 17.5.1 Smart gloves circuit 17.5.2 Smart shoes circuit 17.6 The smart system design 17.6.1 Smart gloves design 17.6.2 Smart shoes design 17.7 Code of the smart system 17.7.1 Smart gloves code 17.7.2 Smart shoes code 17.8 Recognition 17.9 Future goals 17.10 Conclusion References Index Back Cover