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Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices.
- Format:
- Book
- Author/Creator:
- Sountharrajan, S.
- Series:
- Medical Robots and Devices: New Developments and Advances Series
- Language:
- English
- Physical Description:
- 1 online resource (301 pages)
- Edition:
- 1st ed.
- Place of Publication:
- Chantilly : Elsevier Science & Technology, 2025.
- Summary:
- Applied Mathematical Modelling for Biomedical Robotics and Wearable Devices offers readers a comprehensive and practical exploration of the integration of mathematical modelling in biomedical engineering.
- Contents:
- Front Cover
- Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices
- Copyright Page
- Contents
- List of contributors
- About the editors
- Preface
- 1 Introduction to biomedical robotics and wearable devices in healthcare
- Introduction
- Literature survey
- Wearable devices in healthcare
- Medical robotics
- Flexible and wearable sensors
- Technology milestones of wearable triboelectric nanogenerators
- Implantable medical devices
- Reinforced life quality with flexible sensors and robotic exoskeletons
- Wearable devices for health monitoring
- Smartphone solutions for health monitoring
- Novel coronavirus (COVID-19)
- Heart disease
- Diabetes
- Smart homes
- Biomedical robotics
- Artificial intelligence for the Cyber-Physical Systems based Homecare Robotic System
- Flexible sensing for the Cyber-Physical Systems based Homecare Robotic System
- Artificial intelligence and Homecare Robotic Systems
- Limb robotic assistance: an example perspective
- Wearable robots for upper-limb assistance
- Wearable personal health monitoring
- Wearable personal health monitoring systems
- Computing architecture for Internet of Medical Things
- Cloud-based computing
- The rise of edge computing
- Cloud-edge artificial intelligence architecture for Internet of Medical Things
- Combining wearable Internet of Medical Things devices with 6G networks
- Optimizations of artificial intelligence techniques
- Summary
- References
- 2 Mathematical modeling in healthcare engineering
- Overview of mathematical models in medicine
- Introduction to mathematical modeling techniques
- Methodology
- Search strategy and criteria for selection
- Analysis and results of mathematical modeling research
- Quantitative data analysis
- Guidelines and recommendations summary
- Utilization of modeling.
- Fundamental principles and techniques of mathematical modeling
- Mathematical modeling: definition and classification
- Typical mathematical models and methods of mathematical modeling
- Utilization of mathematical models in medical sciences
- Computational models based on differential equations in biomedicine
- Models of growth and development
- Gompertz model
- The Bertalanffy model
- Models of tumor growth
- Models of the cardiovascular system
- Statistical frameworks for medical research
- Parametric survival analysis model
- Model for assessing risk
- Machine learning-based models for healthcare
- Analytical model for medical images
- Pathology analytical model
- Data collection and processing
- Extracting and selecting features
- Model training and evaluation
- Medical models based on network science
- Conclusion and summary
- Issues and challenges
- Future applications
- 3 Mathematical foundations and computational techniques for robotic motion: a unified approach
- Linear algebra and calculus for robotic motion
- The mathematics of robotics
- Integration with computational tools
- MATLAB and linear algebra
- Python and calculus
- Probability theory and statistics
- Linear algebra in robotics
- Calculus in robotics
- Linear algebra and optimization in robotics
- Optimization utilizing MATLAB and Python
- Linear algebra
- Optimization
- Mathematical modeling of robotic locomotion systems
- Challenges in the modeling of symmetric locomotion systems
- The function of symmetry and geometric mechanics
- Progress in geometric mechanics for locomotion
- Applications and prospective trajectories
- Configuration space and the notion of manifolds
- Definition of a manifold
- Illustration of manifolds
- Essential configuration blocks and operations in configuration pace.
- Lie groups and their significance in configuration space
- Utilization of Lie groups in configuration space
- Special Euclidean group [SE(2)]
- Definition and characteristics of SE(2)
- Utilization of SE(2) in robotics
- Motion planning
- Regulatory algorithms
- Robot localization
- Mathematical representation of SE(2)
- Local group velocities in SE(2)
- Function, curves, and trajectories on the manifold
- Functions on manifolds
- Curves on manifolds
- Utilizations of curves
- Vectors on manifolds
- Utilizations of vectors
- Velocity of mechanical equipment and curved spaces
- Characterization of velocities in mechanical machines
- Tangential spaces
- Visualizing tangential spaces
- Utilization of tangential spaces in robotics
- Regulatory approaches
- Analysis of stability
- Local group velocities and tangential spaces
- Elevated actions with vectors in the tangential manifold
- Definition of elevated actions
- Mathematical formulation of elevated actions
- Utilization of lifted events in robotics
- Motion regulation
- Kinematic modeling
- Velocities of a rigid body
- Definition of rigid body velocities
- Kinematics of rigid parts
- Dynamics of rigid objects
- Left and right elevated actions
- Characterization of left and right elevated actions
- Mathematical depiction of elevated actions
- Utilization of left- and right-lifted actions
- Spatial velocity and its calculation utilizing adjoint operators
- Formulation of spatial velocity
- Computation of spatial velocity
- Adjoint functions and spatial velocity
- Adjoint representation
- Utilization of spatial velocity in robotics
- Regulatory systems
- Case studies.
- Motion planning for serpentine robots
- Mathematical concepts
- Generalized Voronoi Graph (Henning et al., 1998)
- Follow-the-leader approach
- Optimization techniques
- Computational efficiency
- Collision detection and avoidance
- Two-wheeled robots
- Inverted pendulum hypothesis (Gadekar et al., 2024)
- System dynamics and control
- State-space representation
- Proportional-integral-derivative control
- Sensor fusion
- Torque generation
- Linear and angular velocity control
- Legged robots
- Importance of legged robots
- Sensor fusion and estimation
- Dynamic balancing
- Future directions
- Conclusion
- 4 Advanced biosignal processing and emotion recognition through artificial intelligence
- Related works
- Electroencephalography
- Electrocardiography
- Signal acquisition and preprocessing
- Extraction of features
- Detection of arrhythmia
- Detection of ischemia and infarction
- Risk stratification and prognosis
- Telemonitoring and remote healthcare
- Electromyography
- Analysis of muscle activity
- Evaluation of muscle fatigue
- Analysis of movement
- Prosthetic regulation and human-computer interaction
- Rehabilitation and assessment of motor function
- Positron emission tomography
- Pulse oximetry
- Monitoring of blood pressure
- Glucose surveillance
- Magnetic resonance imaging
- Ultrasonography
- Infrared thermography
- Autonomous emotional computation (Soares et al., 2013) utilizing biosignal analysis and deep learning techniques
- Techniques for emotion recognition
- Multisignal emotion recognition systems
- Utilization of machine learning in emotion recognition.
- Execution of the automated emotion recognition model
- Individuals involved
- Data set of emotional stimuli
- Protocol
- Acquisition and processing of physiological signals
- Cardiac characteristics: heart rate variability and blood volume pulse
- Measurement of blood volume pulse via photoplethysmography
- Characteristics of respiration
- Characteristics of thermal infrared imaging
- Classification algorithms
- Machine learning-Random ForestAalgorithm
- Deep learning-convolutional neural network and long- and short-term memory
- Results and discussion
- Analysis of the confusion matrix of Random Forest utilising heart rate variability and blood volume pulse
- Random Forest confusion matrix utilizing heart rate variability, blood volume pulse, and respiration
- Random Forest confusion matrix utilizing heart rate variability, blood volume pulse, respiration, and infrared
- Statistical significance
- Evaluation of the convolutional neural network-long- and short-term memorylstm model's performance
- 5 Optimization algorithms for design and control
- Utilization of advanced technologies for optimal design and control in wearable robots
- Integration of many sensory modalities to improve motor function
- Enhancing fusion techniques for wearable robotics
- Human-in-the-loop control: optimization algorithms for efficient design and control of wearable robots
- Control mechanisms and challenges of human-in-the-loop
- Optimization algorithms used in human-in-the-loop control
- Sensory reconstruction and flexible electronics in wearable robots: optimizing neuromuscular interfaces
- Flexible electronics for enhanced neuromuscular interfaces
- Biomechatronic chips: enabling efficient signal processing
- Soft robot design and control optimization algorithms
- Architectural design.
- Design objective (robotic behavior).
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 0-443-33515-X
- 0-443-33514-1
- OCLC:
- 1534820981
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