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"Every time an artist portrays a human subject, a decision has to be made about the posture of the figure. Will they be standing, sitting or reclining? Smiling, screaming or weeping? Will they be clasping their hands, crossing their arms or raising their fist? For the first time, celebrated surrealist and bestselling author Desmond Morris brings together his two fields of expertise - art and science - in a single volume. As well as exploring such familiar actions as the handshake, the nose-thumb and the dominant elbow, he draws us into an absorbing story of art detection, tracing the roots of a number of gestures that have baffled and intrigued the art world for years. Why, for example, did Napoleon pose for official portraits with his right hand thrust into his waistcoat, and what is the meaning of the double-split hand gesture displayed in El Greco's The Nobleman with his Hand on his Chest? Encompassing a vast range of visual creativity, from prehistoric figurines, Roman artefacts and Renaissance frescoes to contemporary art and graffiti, Postures: Body Language in Art unlocks new ways of looking at art. Surprising similarities are uncovered, as well as now rarely used gestures, so that even the most familiar works are suddenly seen in a new light."--Publisher's description.

Art --- humanities --- social history --- pose --- lichaamstaal (kunst) --- Body language in art --- Art and society

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The classification of human action or behavior patterns is very important for analyzing situations in the field and maintaining social safety. This book focuses on recent research findings on recognizing human action patterns. Technology for the recognition of human action pattern includes the processing technology of human behavior data for learning, technology of expressing feature values ​​of images, technology of extracting spatiotemporal information of images, technology of recognizing human posture, and technology of gesture recognition. Research on these technologies has recently been conducted using general deep learning network modeling of artificial intelligence technology, and excellent research results have been included in this edition.

Technology: general issues --- History of engineering & technology --- human action recognition --- graph convolution --- high-order feature --- spatio-temporal feature --- feature fusion --- dynamic gesture recognition --- multi-modalities network --- class regularization --- 3D-CNN --- spatiotemporal activations --- class-specific features --- Dynamic Hand Gesture Recognition --- human-computer interaction --- hand shape features --- pose estimation --- stacked hourglass network --- deep learning --- convolutional receptive field --- hand gesture recognition --- human–machine interface --- artificial intelligence --- feedforward neural networks --- spatio-temporal image formation --- human activity recognition --- fusion strategies --- transfer learning --- activity recognition --- data augmentation --- multi-person pose estimation --- partitioned centerpose network --- partition pose representation --- continuous hand gesture recognition --- gesture spotting --- gesture classification --- multi-modal features --- 3D skeletal --- CNN --- spatiotemporal feature --- embedded system --- real-time --- action recognition --- Long Short-Term Memory --- spatio–temporal differential --- n/a --- human-machine interface --- spatio-temporal differential

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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.

Technology: general issues --- History of engineering & technology --- 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

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In the last decade, we have witnessed the rapid development of electronic technologies that are transforming our daily lives. Such technologies are often integrated with various sensors that facilitate the collection of human motion and physiological data and are equipped with wireless communication modules such as Bluetooth, radio frequency identification, and near-field communication. In smart healthcare applications, designing ergonomic and intuitive human–computer interfaces is crucial because a system that is not easy to use will create a huge obstacle to adoption and may significantly reduce the efficacy of the solution. Signal and data processing is another important consideration in smart healthcare applications because it must ensure high accuracy with a high level of confidence in order for the applications to be useful for clinicians in making diagnosis and treatment decisions. This Special Issue is a collection of 10 articles selected from a total of 26 contributions. These contributions span the areas of signal processing and smart healthcare systems mostly contributed by authors from Europe, including Italy, Spain, France, Portugal, Romania, Sweden, and Netherlands. Authors from China, Korea, Taiwan, Indonesia, and Ecuador are also included.

smart homes --- Internet of Things (IoT) --- Wi-Fi --- human monitoring --- behavioral analysis --- ambient assisted living --- intelligent luminaires --- wireless sensor network --- indoor localisation --- indoor monitoring --- Graphics Processing Units (GPUs) --- CUDA --- OpenMP --- OpenCL --- K-means --- brain cancer detection --- hyperspectral imaging --- unsupervised clustering --- impaired sensor --- Structural Health Monitoring --- Time of Flight --- subharmonics --- Cascaded-Integrator-Comb (CIC) filter --- FPGA --- fixed point math --- data adaptive demodulator --- motion estimation --- inertial sensors --- simulation --- spline function --- Kalman filter --- eHealth --- software engineering --- gesture recognition --- Dynamic Time Warping --- Hidden Markov Model --- usability --- Cramér–Rao lower bound (CRLB) --- human motion --- Inertial Measurement Unit (IMU) --- Time of Arrival (TOA) --- wearable sensors --- endothelial dysfunction --- photoplethysmography --- machine learning --- computer-assisted screening --- sleep pose recognition --- keypoints feature matching --- Bayesian inference --- near-infrared images --- scale invariant feature transform --- heartbeat classification --- arrhythmia --- denoising autoencoder --- autoencoder --- deep learning --- auditory perception --- biometrics --- computer vision --- web control access --- web security --- human–computer interaction --- n/a --- Cramér-Rao lower bound (CRLB) --- human-computer interaction

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This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation.

accelerometers --- wearable sensors --- exercise --- measurement --- GMFCS level --- relative orientation estimation --- IMU --- magnetometer-free --- gait analysis --- machine learning --- inertial measurement units --- neurological disorders --- falls --- validity --- 3-D motion analysis --- single leg squat --- motion capture --- clinical --- rehabilitation --- motor function --- outcomes --- implementation --- locomotion --- assistive devices --- embedded sensors --- accelerometry --- physical activity --- Fourier transform --- functional linear model --- walking distance --- lower limb amputation --- gait --- Lie group --- constrained extended Kalman filter --- pose estimation --- wearable devices --- distance measurement --- gait planning --- stride length --- center of pressure --- human–machine interaction --- perinatal stroke --- kinematics --- upper extremity --- cerebral palsy --- hemiplegia --- constraint --- inertial measurement unit --- wireless sensors network --- motion tracking --- range of motion --- shoulder --- goniometer --- spinal cord injury --- tetraplegia --- clinical setting --- circadian motor behavior --- body-worn sensors --- older adults --- physically active workers --- low back pain --- inertial motion units --- wearable sensor --- real-time gait detection --- insole pressure sensors --- pathological gait --- gait rehabilitation --- assistive device --- wearable technology --- stroke --- physical therapy --- arm use --- upper limb performance --- accelerometer --- sensor --- walking --- n/a --- human-machine interaction