Digital human modeling and medicine : the digital twin /

Digital Human Modeling and Medicine: The Digital Twin explores the body of knowledge and state-of-the-art in Digital Human Modeling (DHM) and its applications in medicine.DHM is the science of representing humans with their physical properties, characteristics and behaviors in computerized, virtual...

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Bibliographic Details
Corporate Author:	ScienceDirect (Online service)
Other Authors:	Paul, Gunther (Editor), Doweidar, Mohamed H. (Editor)
Format:	eBook
Language:	English
Published:	London ; San Diego, CA : Academic Press, an imprint of Elsevier, 2023.
Subjects:	Human body > Computer simulation. Human mechanics > Computer simulation. Digital computer simulation. Biomedical Engineering > methods Computer Simulation Corps humain > Simulation par ordinateur. Mécanique humaine > Simulation par ordinateur. Simulation par ordinateur. simulation. Digital computer simulation Human body > Computer simulation Human mechanics > Computer simulation Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Front Cover
Digital Human Modeling and Medicine
Digital Human Modeling and Medicine The Digital Twin
Copyright
Contents
Contributors
1
Modeling methods
1
From the visible human project to the digital twin
Introduction
The visible human project
Anatomography
Virtual physiological human
The digital twin
References
Further reading
2
Massive data probabilistic framework for parameter estimation in biological problems
Introduction
General framework
About modeling
About experiments: smart experiments
Strategy 1: in one stroke
Strategy 2: divide and conquer
Strategy 3: the general situation
Model separability
Including model uncertainty
Mathematical tools and concepts
Managing data uncertainty
Estimation of probabilistic models
Parametric methods
Method of moments
Method of moments
Maximum likelihood method
Maximum likelihood method
Nonparametric methods
Design of experiments
Copulas
Mathematical definition
Theorem 1: Sklar's theorem
Parametric copulas
Nonparametric copulas
Methodology
Model adjustment
Model analysis and applications
Parameter estimation
A case study: GBM evolution
Mathematical model
Data generation
Results
Model adjustment
Model validation
Parameter estimation
Experimental design
Conclusions
References
3
Deep learning applied to detection of the vulnerable atherosclerotic plaque
Introduction
The atheroma plaque problem
3D parametric study
Source data
Mathematical methods for regression
Artificial neural network
Support vector machine
Assuring the quality of the machine
Validation with a real geometry
How the decision support system works
Finite element models
Results
Discussion
References.
4
Computational stability of human musculoskeletal systems
Introduction
Methods
Criteria of structural stability
Stability of human MS systems
Stability of the human spine
Role of posture and passive ligamentous stiffness
Role of load orientation and elevation
Role of coactivity
Stability-based multicriteria simulations
Stability of human knee joint
Summary
References
5
Techniques for automatic landmark detection of human tissue
Introduction
Machine learning techniques
Artificial neural networks
Decision trees
Support vector machines
Knowledge-based techniques
Shape analysis
Approximation to simple shapes
Curvature analysis
Template-based approaches
Atlas-based templates
Statistical shape modeling
Patient-specific templates
Spatial coherence
Conclusion
References
6
Multibody modeling of the musculoskeletal system
Introduction
Fundamentals of multibody modeling
Motion capture-based model
Cadaver-based lower extremity model
Scaling of the template model to subject-specific data
Linear geometric scaling law
Parameter identification
Mass and inertial properties
Mass-fat muscle strength scaling law
Over-determinate kinematic analysis
Inverse dynamic analysis
Analysis of gait modifications
Other applications
Concluding remarks
References
7
AnyBody modeling system
Background and context
Software design choices
AnyScript
Multibody system formulation
The model repository
Structuring principles
Applications
Fundamental science applications
Orthopedic applications
Industrial product design
Sports
Workplace ergonomics
Digital human models and the digital patient
References
8
The NEUROiD neuromusculoskeletal movement simulation platform
Introduction.
The NEUROiD movement simulation platform
Design philosophy and architecture
Multiscale, multidiscipline, and multifunction platform
Workflow in NEUROiD
Model definition, simulation, and visualization
Curation and definition
Model specification to the definition
Model specification to the definition
Definition across scale and discipline
Definition across scale and discipline
Neuromusculoskeletal interface design
Neuromusculoskeletal interface design
Experiment and simulation
Experiment specification to the definition
Experiment specification to the definition
Parallelization
Parallelization
Visualization
Integrative model development
Choosing a musculoskeletal model
Design and characterization of limbs in silico
Upper limb
Lower limb
Movement training of virtual limbs
Machine learning setup
NEUROiD in medicine
NEUROiD models
NEUROiD activities
Twinning in NEUROiD
Clinical trials and experimentation in silico with NEUROiD
Clinical triage for spasticity
Design and test of prostheses
Diabetic neuropathy-induced diabetic foot
Stroke: cross-sectional modeling of stroke severity and corticospinal residuum
Stroke: longitudinal modeling of recovery and computational neurorehabilitation
Spinal cord stimulation
Motor neuron disease (amyotrophic lateral Sclerosis, spinal muscular atrophy, familial spastic paraplegia)
Peripheral neuropathies
Mechanisms and consequences of aging-induced changes in motor unit structure
Limitations
Medical education and training
Conclusion and future landscapes
References
9
HumMod: a modeling environment for the simulation of integrative human physiology
Disclosures
History
Model content
HumMod for testing physiological concepts and hypotheses in pathophysiology.
Example 1: salt sensitivity
Example 2: baroreceptor activation therapy
Example 3: arteriovenous fistula
The future of modeling: virtual populations
Conclusion, limitations, and future considerations
References
2
Organs
10
Computational biomechanics as a tool to improve surgical procedures for Uterine Prolapse
Introduction
Mechanism of the development of POP
Biomechanical uterine prolapse simulation
Isotropic constitutive model-simulating the passive behavior
Computational model of the pelvic cavity
Computational model of the implant
Biomechanical properties of the soft tissues and mesh implant
Uterine prolapse simulation
Personalized models to repair the uterine prolapse
Conclusions
References
11
Computational Modeling of aerosol particle transport and deposition in the healthy and stented human airways c ...
Clinical background
Materials and methods
Geometries
Numerical model and boundary conditions
Continuous phase: airflow
Discrete phase: particle transport and deposition modeling
Results
Airflow patterns in healthy and stented airways
Airflow turbulent patterns in healthy and stented airways
Particle deposition and transport
Validation of the numerical findings
Comparison between healthy and stented human upper airways
Total deposition fractions
Total deposition fractions
Regional deposition fractions
Conclusions and final remarks
Funding
References
12
Ultrafine particle transport to the lower airways: airway diameter reduction effects
Introduction
Geometrical development
Numerical methods
Result and discussion
Velocity functions
Pressure variations
Particle deposition fraction
Escaped particles
Conclusions
Limitations of the approach
References.
13
Aerosolized airborne bacteria and viruses inhalation: Micro-bioaerosols deposition effects through upper nasal ...
Introduction
Materials and method
Computational model
Governing equations
Results
Discussion
Conclusion
Declaration of competing interest
References
14
Numerical simulation of the aortic arch behavior∗
Nomenclature
Introduction
Methods
Geometry reconstruction and grid generation
Governing equations
Boundary conditions and numerical solution
Results
Discussion
Conclusion
Disclosure of interest
References
15
Modern placental imaging methods
Introduction
Ultrasound
Doppler
Volume rendering
Sonoelastography
Placental elastography
Magnetic resonance imaging
Conclusion
References
3
Body parts
16
Foot digital twin and in silico clinical applications
Where a foot digital twin can help
Key aspects of foot biomechanics
Main foot pathologies by volume
Foot digital twin-scope of interest
The potential of foot CM&amp
S
How to build a foot digital twin
Anatomy reconstruction
Loading and boundary conditions
Tissue properties
Verification and validation
Initiatives to improve model credibility in healthcare
Foot digital twin: a look into the future
In silico trials
What level of anatomical detail is required for clinical applications?
Foot CM&amp
S for clinical applications
Foot CM&amp
S for the footwear industry
Why foot and ankle CM&amp
S is not yet in the clinic
References
17
Flow processes occurring within the body but still external to the body's epithelial layer (gastrointestinal a ...
Introduction
Computational methods
SPH for fluids and foods
DEM for motion and collisions of particles
Collisions and rigid body dynamics in SPH.