Biomedical Engineering and Computational Intelligence
Proceedings of The World Thematic Conference-Biomedical Engineering and Computational Intelligence, BIOCOM 2018
Published on 15. August 2020
Book
Paperback/Softback
XIV, 112 pages
978-3-030-21728-0 (ISBN)
Description
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 1 st World Thematic Conference - Biomedical Engineering and Computational Intelligence, BIOCOM 2018, held in London, United Kingdom, during October 30-31, 2018.
More details
Series
Edition
2020 ed.
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
33 farbige Abbildungen, 18 s/w Abbildungen
XIV, 112 p. 51 illus., 33 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 7 mm
Weight
234 gr
ISBN-13
978-3-030-21728-0 (9783030217280)
DOI
10.1007/978-3-030-21726-6
Schweitzer Classification
Other editions
Additional editions
João Manuel R. S. Tavares | Nilanjan Dey | Amit Joshi
Biomedical Engineering and Computational Intelligence
Proceedings of The World Thematic Conference-Biomedical Engineering and Computational Intelligence, BIOCOM 2018
Book
07/2019
Springer
€106.99
Shipment within 7-9 days
Content
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.