11047nam 22005173 450 991104801690332120250901084506.00-443-33515-X0-443-33514-1(CKB)40430910800041(MiAaPQ)EBC32274138(Au-PeEL)EBL32274138(OCoLC)1534820981(EXLCZ)994043091080004120250901d2025 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierApplied Mathematical Modeling for Biomedical Robotics and Wearable Devices1st ed.Chantilly :Elsevier Science & Technology,2025.©2025.1 online resource (301 pages)Medical Robots and Devices: New Developments and Advances SeriesFront 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 -- Introduction -- 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 -- References -- 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 -- Motion planning -- 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 -- Analysis of stability -- 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 -- Motion regulation -- Kinematic modeling -- Analysis of stability -- 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 -- Motion planning -- Regulatory systems -- Analysis of stability -- 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) -- Mathematical concepts -- 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 -- Mathematical concepts -- System dynamics and control -- State-space representation -- Optimization techniques -- Sensor fusion and estimation -- Dynamic balancing -- Future directions -- Conclusion -- References -- 4 Advanced biosignal processing and emotion recognition through artificial intelligence -- Introduction -- Related works -- Methodology -- 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 -- Signal acquisition and preprocessing -- 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 -- Conclusion -- References -- 5 Optimization algorithms for design and control -- Introduction -- 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).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.Medical Robots and Devices: New Developments and Advances Series610.28Sountharrajan S1840494Karthiga M1882711Balasamy Balamurugan1882712Bashir Ali Kashif1762152MiAaPQMiAaPQMiAaPQBOOK9911048016903321Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices4498085UNINA