Overview

This book reports on timely research at the interface between biomedical engineering and intelligence technologies applied to biology and healthcare. It covers cutting-edge methods applied to biomechanics and robotics, EEG time series analysis, blood glucose prediction models, among others. It includes ten chapters, which were selected upon a rigorous peer-review process and presented at the 1st World Thematic Conference - Biomedical Engineering and Computational Intelligence, BIOCOM 2018, held in London, United Kingdom, during October 30–31, 2018.

Full Product Details

Author:   João Manuel R. S. Tavares ,  Nilanjan Dey ,  Amit Joshi
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   32
Weight:   0.454kg
ISBN:  

9783030217259

ISBN 10:   3030217256
Pages:   112
Publication Date:   30 July 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Chapter 1. Bioinspired Approach to Inverse Kinematic Problem.- Chapter 2. Assessment of Two Musculoskeletal Models in Children with Crouch Gait.- Chapter 3. Low-Complexity Classi cation Algorithm to Identify Drivers' Stress using Electrodermal Activity (EDA) Measurements.- Chapter 4. 3D Model of Blood Flow for Magnetohydrodynamics Study.- Chapter 5. Nonlinear Autoregressive Model Design and Optimization based on ANN for the Prediction of Chaotic Patterns in EEG Time Series.- Chapter 6. Using a coupled MDOF biodynamic model to study the effect of curvature of spine on lumbar spine compression under axial loads.- Chapter 7. Applied logics to develop ontology model of complex-structured domains: organic chemistry and biochemistry.- Chapter 8. Analysis of HD-sEMG signals using Channel Clustering Based on Time Domain Features For Functional Assessment with Ageing.- Chapter 9. Effect of reduced point NIR spectroscopy on glucose prediction error in human blood tissue.- Chapter 10. Data augmentation for Signature Images in On-line Verification Systems.

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