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

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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