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Biomedical Engineering and Computational Intelligence: Proceedings of The World Thematic ConferenceBiomedical Engineering and Computational Intelligence, BIOCOM 2018 2020 ed. [Hardback]

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  • Formāts: Hardback, 112 pages, height x width: 235x155 mm, weight: 454 g, 33 Illustrations, color; 18 Illustrations, black and white; XIV, 112 p. 51 illus., 33 illus. in color., 1 Hardback
  • Sērija : Lecture Notes in Computational Vision and Biomechanics 32
  • Izdošanas datums: 30-Jul-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030217256
  • ISBN-13: 9783030217259
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Biomedical Engineering and Computational Intelligence: Proceedings of The World Thematic ConferenceBiomedical Engineering and Computational Intelligence, BIOCOM 2018 2020 ed.Palielināt
  • Formāts: Hardback, 112 pages, height x width: 235x155 mm, weight: 454 g, 33 Illustrations, color; 18 Illustrations, black and white; XIV, 112 p. 51 illus., 33 illus. in color., 1 Hardback
  • Sērija : Lecture Notes in Computational Vision and Biomechanics 32
  • Izdošanas datums: 30-Jul-2019
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030217256
  • ISBN-13: 9783030217259
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030217259.html

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 in London, United Kingdom, during October 30 - 31, 2018.

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.