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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.

Language --- English language teaching (ELT) --- 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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• Reference Manager
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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.

Language --- English language teaching (ELT) --- 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

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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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Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods.

Technology: general issues --- filter --- finite memory structure --- infinite memory structure --- smoother --- target tracking --- Indoor Positioning System --- WLAN --- C-Means --- K-Means --- Access Point Selection --- RSS-fingerprint --- smartphone --- pedestrian dead reckoning --- heading estimation --- autoregressive model --- adaptive Kalman filter --- indoor localization --- Wi-Fi received signal strength indicator (RSSI) --- semisupervised learning --- feature extraction --- mobile fingerprinting --- trajectory learning --- localization --- hybrid localization --- Bluetooth Low Energy --- extended kalman filter --- internet of things --- proximity sensors --- smartphone sensors --- pedestrian dead reckoning (PDR) --- Wi-Fi indoor positioning --- sensor fusion frameworks --- Kalman filter --- location fingerprinting --- trilateration --- received signal strength indication (RSSI) --- indoor positioning --- 5G system --- hybrid positioning --- geometric dilution of precision --- closed-form solution --- Cramer-Rao lower bound --- visually impaired (VI) --- computer vision --- deep learning --- multi-label convolutional support vector machine (M-CSVM) --- assistive technology --- visually impaired --- navigational system --- indoor navigation --- markers --- mobile robots --- wireless sensor network --- time of arrival (TOA) --- NLOS --- modified probabilistic data association (MPDA) --- indoor location recognition --- received signal strength (RSS) --- Wi-Fi fingerprint positioning --- deep neural network (DNN) --- optimization methods --- adaptive filter --- hidden Markov models (HMM) --- I/O detection --- GPS signal --- machine learning --- positioning applications. --- PDR --- geomagnetic positioning --- particle filter --- genetic algorithm --- Wi-Fi fine timing measurement --- NLOS identification --- Gaussian model --- carrier phase --- differential pseudolite system --- extended Kalman filter --- reliability --- integrity monitoring --- transparent obstacle recognition --- reflection noise --- laser range finder --- path planning --- mobile robot --- automated data acquisition --- remote sensing technologies --- automated progress reporting --- data fusion --- tracking resources --- bearing estimation --- azimuth estimation --- signal processing --- position estimation --- photodiode array --- indoor ranging algorithm --- channel state information --- received signal strength indicator --- VPR --- fusion navigation --- UWB --- multi-path detection --- NLOS and MP discrimination --- SVM --- random forest --- multilayer perceptron --- LOS --- DWM1000 --- fingerprinting --- smart buildings --- mobile devices --- indoor localization technologies --- model based techniques --- quality control

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods.

filter --- finite memory structure --- infinite memory structure --- smoother --- target tracking --- Indoor Positioning System --- WLAN --- C-Means --- K-Means --- Access Point Selection --- RSS-fingerprint --- smartphone --- pedestrian dead reckoning --- heading estimation --- autoregressive model --- adaptive Kalman filter --- indoor localization --- Wi-Fi received signal strength indicator (RSSI) --- semisupervised learning --- feature extraction --- mobile fingerprinting --- trajectory learning --- localization --- hybrid localization --- Bluetooth Low Energy --- extended kalman filter --- internet of things --- proximity sensors --- smartphone sensors --- pedestrian dead reckoning (PDR) --- Wi-Fi indoor positioning --- sensor fusion frameworks --- Kalman filter --- location fingerprinting --- trilateration --- received signal strength indication (RSSI) --- indoor positioning --- 5G system --- hybrid positioning --- geometric dilution of precision --- closed-form solution --- Cramer-Rao lower bound --- visually impaired (VI) --- computer vision --- deep learning --- multi-label convolutional support vector machine (M-CSVM) --- assistive technology --- visually impaired --- navigational system --- indoor navigation --- markers --- mobile robots --- wireless sensor network --- time of arrival (TOA) --- NLOS --- modified probabilistic data association (MPDA) --- indoor location recognition --- received signal strength (RSS) --- Wi-Fi fingerprint positioning --- deep neural network (DNN) --- optimization methods --- adaptive filter --- hidden Markov models (HMM) --- I/O detection --- GPS signal --- machine learning --- positioning applications. --- PDR --- geomagnetic positioning --- particle filter --- genetic algorithm --- Wi-Fi fine timing measurement --- NLOS identification --- Gaussian model --- carrier phase --- differential pseudolite system --- extended Kalman filter --- reliability --- integrity monitoring --- transparent obstacle recognition --- reflection noise --- laser range finder --- path planning --- mobile robot --- automated data acquisition --- remote sensing technologies --- automated progress reporting --- data fusion --- tracking resources --- bearing estimation --- azimuth estimation --- signal processing --- position estimation --- photodiode array --- indoor ranging algorithm --- channel state information --- received signal strength indicator --- VPR --- fusion navigation --- UWB --- multi-path detection --- NLOS and MP discrimination --- SVM --- random forest --- multilayer perceptron --- LOS --- DWM1000 --- fingerprinting --- smart buildings --- mobile devices --- indoor localization technologies --- model based techniques --- quality control