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Biosensing the Future : Wearable, Ingestible and Implantable Technologies for Health and Wellness Monitoring Part B.

Biosensing the Future: Wearable, Ingestible and Implantable Technologies for Health and Wellness Monitoring, Part B, Volume 216 covers the rapidly evolving field of biosensors, highlighting their transformative role in modern healthcare, disease monitoring, and personalized medicine.

Bibliographic Details
Main Author: Pandya, Alok
Corporate Author: ScienceDirect (Online service)
Other Authors: Mahato, Kuldeep
Format: eBook
Language:English
Published: Chantilly : Elsevier Science & Technology, 2026.
Edition:1st ed.
Series:Progress in Molecular Biology and Translational Science Series.
Subjects:
Biosensors.
Wearable technology.
Biocapteurs.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Front Cover
  • Progress in Molecular Biology and Translational Science
  • Copyright
  • Contents
  • Contributors
  • Preface
  • Chapter One: Artificial intelligence in wearable biosensing: Enhancing data analysis and decision-making
  • 1 Introduction
  • 2 AI-integrated wearable biosensors
  • 2.1 Wearable biosensors
  • 2.2 Combination AI with wearable biosensors
  • 2.3 Applications
  • 3 Collection and processing of health indicators
  • 3.1 Data acquisition
  • 3.2 Data processing
  • 3.3 Privacy and security
  • 4 Real-time monitoring mechanisms
  • 4.1 Real-time monitoring and early warning
  • 4.2 AI algorithms for wearable biosensors
  • 4.2.1 Machine learning techniques
  • 4.2.2 Deep learning techniques
  • 4.2.2.1 Convolutional neural networks
  • 4.2.2.2 Long-short-term-memory
  • 4.2.2.3 Multimodal large language models
  • 4.3 Edge computing
  • 5 Decision support system
  • 5.1 Clinical decision support system
  • 5.2 How AI enhances decision support systems
  • 6 Personalized health management and assessment
  • 6.1 Personalized health management
  • 6.2 Health risk assessment
  • 7 Future prospects: Integrating digital persons, metaverse, and world models with wearable biosensors
  • 7.1 From digital twins to digital persons
  • 7.2 Integrating digital persons with the metaverse and world models
  • 8 Conclusion
  • References
  • Chapter Two: Wearable privacy
  • 1 Introduction
  • wearable privacy
  • 1.1 Privacy
  • 1.2 Wearable devices
  • 1.3 Trends and population
  • 1.4 Breaches
  • 1.5 Privacy threats
  • 1.6 Privacy solutions
  • 1.6.1 Privacy regulations
  • 1.6.2 End users' behaviors
  • 1.6.3 Technology
  • 1.6.4 Policies
  • 1.6.5 AI role to enable privacy
  • 1.7 Discussion
  • 1.7.1 Considerations for design
  • 1.7.2 Usable privacy
  • 1.7.3 Multidimensional privacy and ethics
  • 1.8 Concluding remarks
  • Acknowledgments
  • References.
  • Chapter Three: The ethical and regulatory landscape of wearable, ingestible, and implantable technologies in the United States
  • 1 Introduction
  • 2 The regulatory landscape of biosensing technologies
  • 2.1 Regulatory approval pathways and key insights
  • 2.1.1 Overview of FDA approval processes
  • 2.1.2 Breakthrough therapy and rare disease incentives
  • 2.1.3 Expanded access
  • 2.1.4 Drug-device combination products
  • 2.2 Regulatory landscape through case studies
  • 2.2.1 Wearables devices
  • 2.2.1.1 Dexcom G7 continuous glucose monitoring (CGM) system
  • 2.2.2 Philips biosensor BX100
  • 2.2.3 Ingestibles
  • 2.2.3.1 Proteus ingestible sensor
  • 2.2.3.2 PillCam
  • 2.2.4 Implantables
  • 2.2.4.1 Eversense E3 continuous glucose monitoring (CGM) system
  • 2.2.4.2 Inspire upper airway stimulation system
  • 2.3 Post-market surveillance and looking forward
  • 2.3.1 Importance of post-market monitoring
  • 2.3.2 Recalls
  • 2.3.3 Looking forward
  • 3 The ethical landscape of biosensing technologies
  • 3.1 Data protection and security
  • 3.2 Informed consent
  • 3.3 Patient data ownership
  • 3.4 Social determinants
  • 4 Conclusion
  • Declaration of generative AI and AI-assisted technologies in the writing process
  • References
  • Chapter Four: Characterization of skeletal muscle contraction using a flexible and wearable ultrasonic sensor
  • 1 Introduction
  • 1.1 Muscle contraction
  • 1.2 Muscle monitoring and characterization
  • 1.3 Wearable ultrasound
  • 2 Ultrasound method for monitoring muscle contraction
  • 2.1 Single-element wearable ultrasonic sensor
  • 2.2 Ultrasound pulse-echo technique for tissue thickness measurement
  • 3 In-vivo experiments
  • 3.1 Ultrasound signal acquisition and processing
  • 3.2 Estimation of tissue displacements due to muscle contraction
  • 4 Discussions
  • 4.1 Muscle contractile parameters
  • 4.2 Fusion index.
  • 4.3 Unfused and fused tetanus frequencies
  • 5 Conclusion
  • Acknowledgment
  • References
  • Chapter Five: Climate change, health, and wearable biosensors: Harnessing emerging technologies to bridge environmental exposures and physiological responses
  • 1 Introduction
  • 1.1 Overview of climate change and its impact on human health
  • 1.2 The role of wearable biosensors for climate change and health research
  • 1.3 Wearables as tools for monitoring health and environmental exposures
  • 2 Applications of wearables in climate change and health research
  • 2.1 Heat stress monitoring
  • 2.1.1 Cardiovascular and thermoregulatory responses to heat
  • 2.1.2 Occupational heat stress monitoring
  • 2.1.3 Non-invasive heat illness detection
  • 2.2 Behavioural adaptations to climate extremes
  • 2.2.1 Sleep monitoring under high temperatures
  • 2.2.2 Physical activity assessment in hot environments
  • 2.3 Environmental health monitoring
  • 2.3.1 Wearables for monitoring health impacts of air pollution
  • 2.3.2 Integrated environmental and biosensor wearables
  • 3 Validation and accuracy of wearables in extreme weather
  • 4 Conclusion
  • Declaration of generative AI and AI-assisted technologies in the writing process
  • References
  • Chapter Six: Wearable sensors for animal health and wellness monitoring
  • 1 Introduction
  • 2 Advanced technology integration in wearable biosensor development
  • 2.1 Microfluidics
  • 2.2 FRET
  • 2.3 Quantum dots
  • 2.4 Surface plasmon resonance
  • 2.5 Electrochemical sensors
  • 2.6 Wireless technologies
  • 2.7 Micro and nano-cantilevers-based sensing
  • 2.8 Field-effect transistors
  • 2.9 Other nanoparticles-based biosensors
  • 3 Digital animal health
  • 3.1 The Internet of Things for animal health management
  • 3.2 Acquiring and analyzing data in real time
  • 3.3 Food and feed characterisation.
  • 3.4 Analyzing animal traits and selection of resilient breeds
  • 3.5 Mathematical algorithms for animal health management
  • 4 Types of wearable sensors
  • 4.1 Wearable accelerometers
  • 4.2 Nose band sensors
  • 4.3 Radio-frequency identification tags
  • 4.4 Pedometers
  • 4.5 Thermal infrared sensors
  • 4.6 Ear tag and halter type
  • 4.7 Neck collars
  • 4.8 Reticulo-Rumen bolus sensors
  • 5 Applications of wearable sensors in livestock sector
  • 5.1 Biological fluid analyzers
  • 5.2 Disease detection
  • 5.3 Stress detection
  • 5.4 Movement and behavior
  • 5.5 Determination of metabolic activity
  • 5.6 Assessment of reproductive performance
  • 6 Limitations of wearable biosensing technologies
  • 7 Conclusion and future perspectives
  • Acknowledgement
  • Data availability
  • CRediT authorship contribution statement
  • Declaration of competing interest
  • References
  • Chapter Seven: Emerging biosensor technologies for obstructive sleep apnea: A comprehensive overview and future prospects
  • 1 Background: OSA prevalence, clinical significance, and economic burden
  • 2 OSA testing technologies
  • 2.1 Polysomnography (PSG): Multi-channel comprehensive sensing in sleep
  • 2.2 Home sleep apnea testing (HSAT): Multi-channel sleep apnea testing at home
  • 2.2.1 Airflow sensing in sleep
  • 2.2.2 Respiratory effort sensing in sleep
  • 2.2.3 Oxygen saturation sensing in sleep
  • 2.3 AASM sleep monitoring categories and type 3 flow-based HSAT
  • 2.4 WatchPAT HSAT: Pioneering non-flow-based sensing technology utilizing PAT signals
  • 2.5 Cutting-edge OSA-detecting wearables sensing technologies
  • 2.5.1 PPG/PAT-based wearables
  • 2.5.2 Non-PPG-based wearables
  • 2.6 Emerging non-wearable OSA detecting sensing technologies
  • 2.7 Nearable sensing technologies
  • 2.7.1 Bed/mattress biosensors
  • 2.7.2 Airable biosensors
  • 2.7.3 Smartphone biosensors.
  • 2.8 Future sensing technologies
  • 2.8.1 Earables
  • 2.8.2 Remote PPG
  • 3 Summary
  • Conflict of interest
  • References
  • Chapter Eight: Wearable biosensing devices for mental health, wellness, and stress management
  • 1 Introduction
  • 1.1 Wearable computing
  • 1.1.1 Features of wearable devices
  • 1.2 Applications of wearable in mental health
  • 2 Motivations
  • 3 Wearable technology in research: Devices, data, population and methods
  • 3.1 Devices
  • 3.2 Data
  • 3.3 Population
  • 3.4 Methods
  • experimental design
  • 3.4.1 Qualitative analysis
  • 3.4.2 Quantitative analysis
  • 3.4.3 Mixed method approaches
  • 3.5 Current applications and products
  • 4 Research contributions in wearable mental health
  • 5 Discussion
  • 5.1 Design considerations
  • 5.2 Ethical considerations
  • 6 Concluding remarks
  • Acknowledgements
  • References
  • Further reading
  • Chapter Nine: Technologies and emerging trends in wearable biosensing
  • 1 Introduction
  • 2 Artificial intelligence and machine learning integration
  • 2.1 Real-time data processing and analysis
  • 2.2 Predictive analytics for personalized health
  • 3 Internet of Things (IoT) and wireless connectivity
  • 3.1 Bluetooth low energy (BLE) and NFC in wearables
  • 3.2 5G technology for remote health monitoring
  • 4 Graphene-based and nano-biosensors
  • 4.1 Nano-electrodes for high sensitivity sensing
  • 4.2 Applications in disease diagnostics
  • 5 Quantum dots and photonic biosensors
  • 6 Lab-on-skin technologies
  • 7 Wearable biodegradable and self-healing biosensors
  • 8 Augmented and virtual reality (ar/vr) applications
  • 8.1 Biofeedback and neurostimulation wearables
  • 8.2 Rehabilitation and therapeutic uses
  • 9 Remote patient monitoring and smart clothing
  • 10 Challenges
  • 10.1 Scalability and commercialization challenges
  • 10.2 Interference and noise reduction in biosensing.