Wearable Sensing and Intelligent Data Analysis for Respiratory Management

Wearable Sensing and Intelligent Data Analysis for Respiratory Management
Copyright
Preface
Contributors
Acknowledgments
1. Respiration: physiology, pathology, and treatment
Introduction
Part A: physiology of respiration
Overview of respiration
The respiratory system (physiology)
Volumes and capacities related to the lung function
Ventilation
Respiratory movements
Perfusion
Diffusion
Neural control of respiration
Pulmonary defense mechanisms
Part B: pathology and treatment of lung diseases
Lung diseases affecting the airways
Asthma
Diagnosis
Treatment [10–14]
Chronic obstructive pulmonary disease (COPD)
Diagnosis [15,16]
Therapy
Lung diseases affecting the air sacs (alveoli)
Lung diseases affecting the interstitium
Lung diseases affecting blood vessels
Lung diseases affecting the pleura
Lung diseases affecting the chest wall
References
2. Respiratory management in daily life: needs and gaps
Introduction
Daily needs of those living with chronic respiratory diseases
Comprehensive assessment for meaningful daily management
Symptoms beyond dyspnea
Functional status
Patient-centric assessment for daily management
Meaningful daily management
Self-management
Healthy lifestyles and target therapies
Comprehensive nonpharmacological intervention—pulmonary rehabilitation
Future avenues for daily assessment and management
References
3. Sensor technologies for mobile and wearable applications in mobile respiratory management
Introduction
Assessment of respiratory functions through monitoring of the lungs
Optical methods
Methods that measure changes of the circumference of the chest and the abdomen
Impedance-based methods
Measurement principle and safety considerations
Single versus multichannel bioimpedance measurement modalities
Single-channel: impedance pneumography
Multichannel: electrical impedance tomography
Technological challenges of bioimpedance measurements for electrical impedance tomography
Wearable electrical impedance tomography systems
Cooperative sensors for electrical impedance tomography
Assessment of respiratory functions through monitoring of the airways
Acoustic methods
Air microphones
Contact microphones
Spirometers
Closed-circuit spirometers
Open-circuit spirometers
Assessment of respiratory functions through monitoring of the cardiovascular system
Electrocardiogram
Electrocardiogram measurement basics
Processing of electrocardiogram signals to assess respiratory function
Photoplethysmography
Pulse oximetry
Multimodal systems for parallel monitoring of several organs
Conclusion
References
4. Textiles and smart materials for wearable monitoring systems
Introduction
Fabric sensing functionality, a combination of conductivity and elasticity
Textile materials for sensing
Respiratory monitoring, measurement methodologies compatible with wearable applications
Fabric sensors and electrodes for respiratory monitoring
Textile platforms for cardiopulmonary monitoring based on fabric sensor components
From Wealthy to HealthWear platforms
Garment design improvement
Textile platform for cardiopulmonary monitoring based on hardware components
From WELCOME to WELMO monitoring system
Vest design
Differences between the male and the female models
Conductive interconnections
Interconnection through snap buttons
Standard textile tests
WELMO
The concept of the vest
Vest design
Conclusions
References
5. Automated respiratory sound analysis
Introduction
Description of respiratory sounds
Breath sounds
Adventitious sounds
Lung sounds
Normal respiratory sounds
Lung or vesicular sounds
Tracheal sounds
Bronchial sounds
Mouth sounds
Adventitious respiratory sounds
Continuous adventitious sounds
Wheezes and rhonchi
Stridors
Squawk
Gasp
Discontinuous adventitious sounds
Fine crackle
Coarse crackle
Pleural rub
Diagnostic value of respiratory sounds
Respiratory sound acquisition
Sensors and placement
Challenges in data collection and future perspectives
Respiratory sound databases
Current methods
Pioneering works in respiratory sound analysis
Preprocessing
Time–frequency representations
Feature extraction
MFCC features
LPCC features
Spectral features
Melodic features
Classifiers
Evaluation
Evaluation metrics
Common tasks and current results
Adventitious respiratory sounds event detection
Adventitious respiratory sound event classification
Respiratory phase segmentation
Respiratory cycle classification
Respiratory disease classification
Conclusion
List of Acronyms
References
6. Respiratory image analysis
Introduction
Primary image reconstruction
Forward model
Inverse model
EIT image reconstruction for wearable sensors
Functional EIT images and measures
Ventilation distribution during tidal breathing – volume changes
Ventilation distribution during tidal breathing – time (phase) shift
Ventilation distribution during tidal breathing – regional compliance
Combination of amplitude and time
Summarizing fEITs – various measures
Assumptions and limitations of the fEIT imaging and EIT measures
Challenges of data acquisition and analysis using wearable EIT
Electrode plane location
Electrode contact
Body movement
Missing/faulty electrodes
Posture
Type of ventilation
Ventilation type detection
Current experience with wearable EIT for ventilation monitoring
Use of wearable EIT beyond ventilation monitoring
Cardiovascular parameter estimation
Pulmonary artery pressure
Aortic blood pressure
Stroke volume and cardiac output
Lung perfusion
Challenges of cardiovascular monitoring using wearable EIT devices
The future of EIT-based cardiovascular monitoring
Integration of EIT findings with other biosignals
Conclusions
References
7. Respiratory data management
Introduction
What can go wrong?
Ambiguity of concepts
Loss of data integrity
Unstable or poor performance
Inefficiency of interfaces
Inadequate data security
Lack of sustainability
Respiratory disease management data
Modeling respiratory data
A semantic data model for respiratory data management
Overview
Semantic data model implementation steps
Representing primitive data types
Representing HL7 FHIR complex data types
Representing HL7 FHIR resources
Adding the semantics for data integrity
Transition to SHACL
Persistent storage and data integrity
Achieving compliance to regulations
Conclusions
Abbreviations
References
8. The edge-cloud continuum in wearable sensing for respiratory analysis
Introduction
The P4 health-care revolution
Edge-cloud continuum
Cloud computing
Computing models
Cloud services
Data and information fusion
Edge computing
Recent artificial intelligence trends for the edge-cloud continuum
Trustworthy and explainable artificial intelligence
Artificial intelligence in adversarial environments
Artificial intelligence for blockchain
ML-based fusion engine
Explorable and explainable AI for data quality and causal reasoning
Explainable information and decision fusions
Tiny machine learning and energy-efficient artificial intelligence algorithms
AI-based solutions for respiratory analysis
Conclusions
References
9. Strategies for long-term adherence
Introduction
Materials and methods
Results
Applications/websites with integrated tools
Messaging services
Informative Videos/Text
Medication taking schedule/schedule
Social media
Discussion
Recommendations
SMS sending
Patient diaries/Reports
Medication taking schedule
Informational videos/text
Wearables/EMD
Apps/web portals
Use cases
Use case 1: young person
Strategy
Step 1: activation
Step 2: take over
Step 3: participation
Use case 2: adult
Strategy
Step 1: activation
Step 2: take over
Step 3: participation
Use case 3: elderly person
Strategy
Step 1: activation
Step 2: take over
Step 3: participation
Conclusions
References
10. Respiratory decision support systems
Introduction
Overview of the RDSS domain
Emergency and intensive care
ARDS diagnosis
Mechanical ventilation optimization
ARDS treatment
ICU-telemedicine
Chronic care
Lung cancer diagnosis and management
COPD and asthma diagnosis and management
Obstructive sleep apnea diagnosis and management
Methods for respiratory DSS
Biomedical data for respiratory DSS
Respiratory rhythm and content
Lung function and structure
Biological and clinical data
Intervention and treatment related data and interaction with other organs/signals
RDSS enabling technologies
Databases and knowledge bases
Systems medicine and computational models in RDSS
Connected health technologies in RDSS
DSS technology
Model-based DSS
Computerized guidelines and rule-based/expert systems as RDSS
ML/AI and data-driven RDSS
New approaches improving scoring and classification
AI in pandemics and emergency
Treatment optimization and reinforcement learning
A detailed RDSS example
Discussion: unmet needs and challenges for the future
References
11. Integrated care in respiratory function management
An overview of integrated care
Understanding integrated care versus fragmented care
Rationale for integrated care
Aging society
Increased chronic disease prevalence
Need for more personalized and connected care
Types, levels, and forms of integrated care
Importance and benefits of integrated care in chronic respiratory conditions: Chronic Obstructive Pulmonary Disease
Evidence supporting benefits of integrated care
Respiratory disease management: current state of care and care pathways
COPD care pathways
Diagnostic parameters and guidelines
Follow-up services
COPD and comorbidities
Adherence and nonpharmacological interventions
Current state of COPD care
Health-care professionals' perceptions
Patients' perceptions
Carers' perceptions
Information and communication technology to support integrated care
What is technology enabled care?
E-health
Telehealth
Telemedicine/teleconsultations
Telecare
Tele-coaching
Remote patient monitoring/telemonitoring
mHealth
How can technology enabled care support integrated care?
Perceptions of different stakeholders toward technology enabled care
Health-care professionals' perceptions
Patients and carers perceptions
Barriers for technology enabled care
Factors related to the technology itself
Individual factors: knowledge, attitude, and sociodemographic characteristics
External factors: human environment
External factors: organizational environment
Conclusion
References
Index
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