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The number of patient health data has been estimated to have reached 2314 exabytes by 2020. Traditional data analysis techniques are unsuitable to extract useful information from such a vast quantity of data. Thus, intelligent data analysis methods combining human expertise and computational models for accurate and in-depth data analysis are necessary. The technological revolution and medical advances made by combining vast quantities of available data, cloud computing services, and AI-based solutions can provide expert insight and analysis on a mass scale and at a relatively low cost. Computational intelligence (CI) methods, such as fuzzy models, artificial neural networks, evolutionary algorithms, and probabilistic methods, have recently emerged as promising tools for the development and application of intelligent systems in healthcare practice. CI-based systems can learn from data and evolve according to changes in the environments by taking into account the uncertainty characterizing health data, including omics data, clinical data, sensor, and imaging data. The use of CI in healthcare can improve the processing of such data to develop intelligent solutions for prevention, diagnosis, treatment, and follow-up, as well as for the analysis of administrative processes. The present Special Issue on computational intelligence for healthcare is intended to show the potential and the practical impacts of CI techniques in challenging healthcare applications.

Information technology industries --- sEMG --- deep learning --- neural networks --- gait phase --- classification --- everyday walking --- convolutional neural network --- CRISPR --- leukemia nucleus image --- segmentation --- soft covering rough set --- clustering --- machine learning algorithm --- soft computing --- multistage support vector machine model --- multiple imputation by chained equations --- SVM-based recursive feature elimination --- unipolar depression --- diabetic retinopathy (DR) --- pre-trained deep ConvNet --- uni-modal deep features --- multi-modal deep features --- transfer learning --- 1D pooling --- cross pooling --- IMU --- gait analysis --- long-term monitoring --- multi-unit --- multi-sensor --- time synchronization --- Internet of Medical Things --- body area network --- MIMU --- early detection --- sepsis --- evaluation metrics --- machine learning --- medical informatics --- feature extraction --- physionet challenge --- electrocardiogram --- Premature ventricular contraction --- sparse autoencoder --- unsupervised learning --- Softmax regression --- medical diagnosis --- artificial neural network --- e-health --- Tri-Fog Health System --- fault data elimination --- health status prediction --- health status detection --- health off --- diffusion tensor imaging --- ensemble learning --- decision support systems --- healthcare --- computational intelligence --- Alzheimer's disease --- fuzzy inference systems --- genetic algorithms --- next-generation sequencing --- ovarian cancer --- interpretable models

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In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.

Technology: general issues --- History of engineering & technology --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network

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The rapid development of advanced, arguably, intelligent sensors and their massive deployment provide a foundation for new paradigms to combat the challenges that arise in significant tasks such as positioning, tracking, navigation, and smart sensing in various environments. Relevant advances in artificial intelligence (AI) and machine learning (ML) are also finding rapid adoption by industry and fan the fire. Consequently, research on intelligent sensing systems and technologies has attracted considerable attention during the past decade, leading to a variety of effective applications related to intelligent transportation, autonomous vehicles, wearable computing, wireless sensor networks (WSN), and the internet of things (IoT). In particular, the sensors community has a great interest in novel, intelligent information fusion, and data mining methods coupling AI and ML for substantial performance enhancement, especially for the challenging scenarios that make traditional approaches inappropriate. This reprint book has collected 14 excellent papers that represent state-of-the-art achievements in the relevant topics and provides cutting-edge coverage of recent advances in sensor signal and data mining techniques, algorithms, and approaches, particularly applied for positioning, tracking, navigation, and smart sensing.

clustering --- data fusion --- target detection --- Grey Wolf Optimizer --- Fireworks Algorithm --- hybrid algorithm --- exploitation and exploration --- GNSS --- MIMU --- odometer --- state constraints --- simultaneous localization and mapping (SLAM) --- range-only SLAM --- sum of Gaussian (SoG) filter --- cooperative approach --- automatic fare collection system --- passenger flow forecasting --- time series decomposition --- singular spectrum analysis --- ensemble learning --- extreme learning machine --- wheeled mobile robot --- path panning --- laser simulator --- fuzzy logic --- laser range finder --- Wi-Fi camera --- sensor fusion --- local map --- odometry --- deep learning --- softmax --- decision-making --- classification --- sensor data --- Internet of Things --- extended target tracking --- gamma-Gaussian-inverse Wishart --- Poisson multi-Bernoulli mixture --- 5G IoT --- indoor positioning --- tracking --- localization --- navigation --- positioning accuracy --- single access point positioning --- fuzzy inference --- calibration --- car-following --- Takagi–Sugeno --- Kalman filter --- microscopic traffic model --- continuous-time model --- LoRa --- positioning --- LoRaWAN --- TDoA --- map matching --- compass --- automotive LFMCW radar --- radial velocity --- lateral velocity --- Doppler-frequency estimation --- waveform --- signal model --- tensor modeling --- smart community system --- power efficiency --- object-detection coprocessor --- histogram of oriented gradient --- support vector machine --- block-level once sliding detection window --- multi-shape detection-window

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In this Special Issue on symmetry, we mainly discuss the application of symmetry in various structural health monitoring. For example, considering the health monitoring of a known structure, by obtaining the static or dynamic response of the structure, using different signal processing methods, including some advanced filtering methods, to remove the influence of environmental noise, and extract structural feature parameters to determine the safety of the structure. These damage diagnosis methods can also be effectively applied to various types of infrastructure and mechanical equipment. For this reason, the vibration control of various structures and the knowledge of random structure dynamics should be considered, which will promote the rapid development of the structural health monitoring. Among them, signal extraction and evaluation methods are also worthy of study. The improvement of signal acquisition instruments and acquisition methods improves the accuracy of data. A good evaluation method will help to correctly understand the performance with different types of infrastructure and mechanical equipment.

Technology: general issues --- History of engineering & technology --- real-time hybrid simulation --- H∞ control --- time delay --- mixed sensitivity --- structural health monitoring --- deep learning --- data anomaly detection --- convolutional neural network --- time–frequency extraction --- micro inertial measurement unit (MIMU) --- variational mode decomposition (VMD) --- Hilbert–Huang transform (HHT) --- frequency-domain integration approach (FDIA) --- torsion angle calculation --- offshore oil platform --- self-anchored suspension bridge --- cable clamp --- slippage --- force analysis --- high formwork --- ARMA --- BPNN --- stress trend prediction --- crack detection --- improved YOLOv4 --- concrete surface --- substructure shake table testing --- integration algorithm --- finite element method --- damper --- digital twin --- prestressed steel structure --- construction process --- safety assessment --- intelligent construction --- structural health monitoring (SHM) --- vibration --- frequency domain --- time domain --- time-frequency domain --- technical codes --- multiple square loops (MSL)-string --- seismic excitation --- dynamic response --- seismic pulse --- near and far field --- three-dimensional laser scanning --- surface flatness of initial support of tunnel --- curved surface fitting --- flatness calculation datum --- curvedcontinuous girder bridge --- collision response --- seismic mitigation --- pounding mitigation and unseating prevention --- heavy-duty vehicle --- road --- coupling model --- terrestrial laser scanning --- RGB --- genetic algorithm --- artificial neutral network

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This book provides a collection of comprehensive research articles on data analytics and applications of wearable devices in healthcare. This Special Issue presents 28 research studies from 137 authors representing 37 institutions from 19 countries. To facilitate the understanding of the research articles, we have organized the book to show various aspects covered in this field, such as eHealth, technology-integrated research, prediction models, rehabilitation studies, prototype systems, community health studies, ergonomics design systems, technology acceptance model evaluation studies, telemonitoring systems, warning systems, application of sensors in sports studies, clinical systems, feasibility studies, geographical location based systems, tracking systems, observational studies, risk assessment studies, human activity recognition systems, impact measurement systems, and a systematic review. We would like to take this opportunity to invite high quality research articles for our next Special Issue entitled “Digital Health and Smart Sensors for Better Management of Cancer and Chronic Diseases” as a part of Sensors journal.

Humanities --- Social interaction --- eHealth --- wearable --- monitoring --- services --- integration --- IoT --- Telemedicine --- wearable sensors --- multivariate analysis --- longitudinal study --- functional decline --- exercise intervention --- accidental falls --- fall detection --- real-world --- signal analysis --- performance measures --- non-wearable sensors --- accelerometers --- cameras --- machine learning --- smart textiles --- healthcare --- talking detection --- activity recognition and monitoring --- patient health and state monitoring --- wearable sensing --- orientation-invariant sensing --- motion sensors --- accelerometer --- gyroscope --- magnetometer --- pattern classification --- artificial intelligence --- supervised machine learning --- predictive analytics --- hemodialysis --- non-contact sensor --- heart rate --- respiration rate --- heart rate variability --- time-domain features --- frequency-domain features --- principal component analysis --- behaviour analysis --- classifier efficiency --- personal risk detection --- one-class classification --- actigraphy --- encoding --- data compression --- denoising --- edge computing --- signal processing --- wearables --- activity monitoring --- citizen science --- cluster analysis --- physical activity --- sedentary behavior --- walking --- energy expenditure --- wearable device --- impedance pneumography --- neural network --- mechanocardiogram (MCG) --- smart clothes --- heart failure (HF) --- left ventricular ejection fraction (LVEF) --- technology acceptance model (TAM) --- physical activity classification --- free-living --- GENEactiv accelerometer --- Gaussian mixture model --- hidden Markov model --- wavelets --- skill assessment --- deep learning --- LSTM --- state space model --- probabilistic inference --- latent features --- human activity recognition --- MIMU --- genetic algorithm --- feature selection --- classifier optimization --- bispectrum --- entropy --- feature extraction --- heat stroke --- filtering algorithm --- physiological parameters --- exercise experiment --- biomedical signal processing --- wearable biomedical sensors --- wireless sensor network --- respiratory monitoring --- optoelectronic plethysmography --- biofeedback --- biomedical technology --- exercise therapy --- orthopedics --- mobile health --- qualitative --- human factors --- inertial measurement unit --- disease prevention --- occupational healthcare --- P-Ergonomics --- precision ergonomics --- musculoskeletal disorders --- wellbeing at work --- electrocardiogram --- conductive gels --- noncontact electrode --- myocardial ischemia --- pacemaker --- ventricular premature contraction --- upper extremity --- motion --- action research arm test --- activities of daily living --- IoT wearable monitor --- health --- posture analysis --- spinal posture --- wearable sensor --- embedded system --- recurrent neural networks --- physical workload --- wearable systems for healthcare --- machine learning for real-time applications --- actigraph --- body worn sensors --- clothing sensors --- cross correlation analysis --- healthcare movement sensing --- wearable devices --- calibration --- inertial measurement units --- human movement --- physical activity type --- real-life --- GPS --- GIS --- n/a