LEADER 04359nam 22006015 450 001 9910366608803321 005 20200701094727.0 010 $a3-030-21726-4 024 7 $a10.1007/978-3-030-21726-6 035 $a(CKB)4100000008785941 035 $a(MiAaPQ)EBC5843016 035 $a(DE-He213)978-3-030-21726-6 035 $a(PPN)23849005X 035 $a(EXLCZ)994100000008785941 100 $a20190729d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBiomedical Engineering and Computational Intelligence$b[electronic resource] $eProceedings of The World Thematic Conference?Biomedical Engineering and Computational Intelligence, BIOCOM 2018 /$fedited by Joćo Manuel R. S. Tavares, Nilanjan Dey, Amit Joshi 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (xiv, 112 pages) $cillustrations 225 1 $aLecture Notes in Computational Vision and Biomechanics,$x2212-9391 ;$v32 311 $a3-030-21725-6 327 $aChapter 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. 330 $aThis book reports on timely research at the interface between biomedical engineering and intelligence technologies applied to biology and healthcare. It covers cutting-edge methods applied to biomechanics and robotics, EEG time series analysis, blood glucose prediction models, among others. It includes ten chapters, which were selected upon a rigorous peer-review process and presented at the 1st World Thematic Conference - Biomedical Engineering and Computational Intelligence, BIOCOM 2018, held in London, United Kingdom, during October 30?31, 2018. 410 0$aLecture Notes in Computational Vision and Biomechanics,$x2212-9391 ;$v32 606 $aBiomedical engineering 606 $aOptical data processing 606 $aArtificial intelligence 606 $aComputer-aided engineering 606 $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputer-Aided Engineering (CAD, CAE) and Design$3https://scigraph.springernature.com/ontologies/product-market-codes/I23044 615 0$aBiomedical engineering. 615 0$aOptical data processing. 615 0$aArtificial intelligence. 615 0$aComputer-aided engineering. 615 14$aBiomedical Engineering and Bioengineering. 615 24$aImage Processing and Computer Vision. 615 24$aArtificial Intelligence. 615 24$aComputer-Aided Engineering (CAD, CAE) and Design. 676 $a006.3 702 $aTavares$b Joćo Manuel R. S$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aDey$b Nilanjan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJoshi$b Amit$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a9910366608803321 996 $aBiomedical Engineering and Computational Intelligence$92104204 997 $aUNINA