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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 book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of sophisticated fault diagnosis techniques. The deep learning methods for analyzing and testing complex mechanical systems are of particular interest. Special attention is given to the representation and analysis of system information, operating condition monitoring, the establishment of technical standards, and scientific support of machinery fault diagnosis.

Technology: general issues --- History of engineering & technology --- process monitoring --- dynamics --- variable time lag --- dynamic autoregressive latent variables model --- sintering process --- hammerstein output-error systems --- auxiliary model --- multi-innovation identification theory --- fractional-order calculus theory --- canonical variate analysis --- disturbance detection --- power transmission system --- k-nearest neighbor analysis --- statistical local analysis --- intelligent fault diagnosis --- stacked pruning sparse denoising autoencoder --- convolutional neural network --- anti-noise --- flywheel fault diagnosis --- belief rule base --- fuzzy fault tree analysis --- Bayesian network --- evidential reasoning --- aluminum reduction process --- alumina concentration --- subspace identification --- distributed predictive control --- spatiotemporal feature fusion --- gated recurrent unit --- attention mechanism --- fault diagnosis --- evidential reasoning rule --- system modelling --- information transformation --- parameter optimization --- event-triggered control --- interval type-2 Takagi–Sugeno fuzzy model --- nonlinear networked systems --- filter --- gearbox fault diagnosis --- convolution fusion --- state identification --- PSO --- wavelet mutation --- LSSVM --- data-driven --- operational optimization --- case-based reasoning --- local outlier factor --- abnormal case removal --- bearing fault detection --- deep residual network --- data augmentation --- canonical correlation analysis --- just-in-time learning --- fault detection --- high-speed trains --- autonomous underwater vehicle --- thruster fault diagnostics --- fault tolerant control --- robust optimization --- ocean currents --- n/a --- interval type-2 Takagi-Sugeno fuzzy model