Reprint
Intelligent Sensors for Human Motion Analysis
Edited by
September 2022
382 pages
- ISBN978-3-0365-5073-2 (Hardback)
- ISBN978-3-0365-5074-9 (PDF)
This book is a reprint of the Special Issue Intelligent Sensors for Human Motion Analysis that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary
The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
gait recognition; biometrics; regularized discriminant analysis; particle swarm optimization; grey wolf optimization; whale optimization algorithm; FMCW; vital sign; XGBoost; MFCC; COVID-19; 3D human pose estimation; deep learning; generalization; optical sensing principle; modular sensing unit; plantar pressure measurement; gait parameters; 3D human mesh reconstruction; 3D human pose estimation; deep neural network; motion capture; neural networks; reconstruction; gap filling; FFNN; LSTM; BILSTM; GRU; pose estimation; movement tracking; computer vision; artificial intelligence; markerless motion capture; assessment; kinematics; development; machine learning; human action recognition; deep learning; features fusion; features selection; recognition; fall risk detection; balance; Berg Balance Scale; human tracking; elderly; telemedicine; diagnosis; precedence indicator; knowledge measure; fuzzy inference; rule induction; posture detection; aggregation function; markerless; human motion analysis; gait analysis; computer vision; deep learning; data augmentation; skeletal data; human action recognition; time series classification; EMG; pattern recognition; machine learning; robot; cyber-physical systems; RGB-D sensors; human motion modelling; F-Formation; Kinect v2; Azure Kinect; Zed 2i; socially occupied space; facial expression recognition; facial landmarks; action units; convolutional neural networks; graph convolutional networks; motion capture; artifact classification; artifact detection; reconstruction; anomaly detection; 3D multi-person pose estimation; absolute poses; camera-centric coordinates; computer vision; artificial intelligence; deep-learning; n/a