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Palabras clave – provistas por la editorial

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; 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; 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; data augmentation; skeletal data; time series classification; EMG; pattern recognition; 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; artifact classification; artifact detection; anomaly detection; 3D multi-person pose estimation; absolute poses; camera-centric coordinates; deep-learning; n/a