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Sensor technology for monitoring vital signs is an important topic for various service applications, such as entertainment and personalization platforms and Internet of Things (IoT) systems, as well as traditional medical purposes, such as disease indication judgments and predictions. Vital signs for monitoring include respiration and heart rates, body temperature, blood pressure, oxygen saturation, electrocardiogram, blood glucose concentration, brain waves, etc. Gait and walking length can also be regarded as vital signs because they can indirectly indicate human activity and status. Sensing technologies include contact sensors such as electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG), non-contact sensors such as ballistocardiography (BCG), and invasive/non-invasive sensors for diagnoses of variations in blood characteristics or body fluids. Radar, vision, and infrared sensors can also be useful technologies for detecting vital signs from the movement of humans or organs. Signal processing, extraction, and analysis techniques are important in industrial applications along with hardware implementation techniques. Battery management and wireless power transmission technologies, the design and optimization of low-power circuits, and systems for continuous monitoring and data collection/transmission should also be considered with sensor technologies. In addition, machine-learning-based diagnostic technology can be used for extracting meaningful information from continuous monitoring data.

Technology: general issues --- Energy industries & utilities --- cardiopulmonary resuscitation (CPR) --- electroencephalogram (EEG) --- hemodynamic data --- carotid blood flow (CBF) --- cerebral circulation --- frequency-shift keying radar --- cross-correlation --- envelope detection --- continuous-wave radar --- frequency discrimination --- vital-signs monitoring --- heartbeat accuracy improvement --- heartbeat detection --- absolute distance measurement --- radar signal processing --- 3D+t modeling --- coronary artery --- non-rigid registration --- cage deformation --- 4D CT --- passenger detection --- CW radar --- radar feature vector --- radar machine learning --- wearable sensors --- physiology --- medical monitoring --- vital signs --- compensatory reserve --- ultra-high resolution --- cone-beam computed tomography --- low-contrast object --- optimal filter --- modulation transfer function --- noise power spectrum --- doppler cardiogram --- wavelet transform --- denoising --- mother wavelet function --- decomposition level --- signal decomposition --- signal-to-noise-ratio

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Sensor technology for monitoring vital signs is an important topic for various service applications, such as entertainment and personalization platforms and Internet of Things (IoT) systems, as well as traditional medical purposes, such as disease indication judgments and predictions. Vital signs for monitoring include respiration and heart rates, body temperature, blood pressure, oxygen saturation, electrocardiogram, blood glucose concentration, brain waves, etc. Gait and walking length can also be regarded as vital signs because they can indirectly indicate human activity and status. Sensing technologies include contact sensors such as electrocardiogram (ECG), electroencephalogram (EEG), photoplethysmogram (PPG), non-contact sensors such as ballistocardiography (BCG), and invasive/non-invasive sensors for diagnoses of variations in blood characteristics or body fluids. Radar, vision, and infrared sensors can also be useful technologies for detecting vital signs from the movement of humans or organs. Signal processing, extraction, and analysis techniques are important in industrial applications along with hardware implementation techniques. Battery management and wireless power transmission technologies, the design and optimization of low-power circuits, and systems for continuous monitoring and data collection/transmission should also be considered with sensor technologies. In addition, machine-learning-based diagnostic technology can be used for extracting meaningful information from continuous monitoring data.

Technology: general issues --- Energy industries & utilities --- cardiopulmonary resuscitation (CPR) --- electroencephalogram (EEG) --- hemodynamic data --- carotid blood flow (CBF) --- cerebral circulation --- frequency-shift keying radar --- cross-correlation --- envelope detection --- continuous-wave radar --- frequency discrimination --- vital-signs monitoring --- heartbeat accuracy improvement --- heartbeat detection --- absolute distance measurement --- radar signal processing --- 3D+t modeling --- coronary artery --- non-rigid registration --- cage deformation --- 4D CT --- passenger detection --- CW radar --- radar feature vector --- radar machine learning --- wearable sensors --- physiology --- medical monitoring --- vital signs --- compensatory reserve --- ultra-high resolution --- cone-beam computed tomography --- low-contrast object --- optimal filter --- modulation transfer function --- noise power spectrum --- doppler cardiogram --- wavelet transform --- denoising --- mother wavelet function --- decomposition level --- signal decomposition --- signal-to-noise-ratio --- cardiopulmonary resuscitation (CPR) --- electroencephalogram (EEG) --- hemodynamic data --- carotid blood flow (CBF) --- cerebral circulation --- frequency-shift keying radar --- cross-correlation --- envelope detection --- continuous-wave radar --- frequency discrimination --- vital-signs monitoring --- heartbeat accuracy improvement --- heartbeat detection --- absolute distance measurement --- radar signal processing --- 3D+t modeling --- coronary artery --- non-rigid registration --- cage deformation --- 4D CT --- passenger detection --- CW radar --- radar feature vector --- radar machine learning --- wearable sensors --- physiology --- medical monitoring --- vital signs --- compensatory reserve --- ultra-high resolution --- cone-beam computed tomography --- low-contrast object --- optimal filter --- modulation transfer function --- noise power spectrum --- doppler cardiogram --- wavelet transform --- denoising --- mother wavelet function --- decomposition level --- signal decomposition --- signal-to-noise-ratio

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Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens.

Technology: general issues --- History of engineering & technology --- star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance --- star image --- image denoising --- reinforcement learning --- maximum likelihood estimation --- mixed Poisson–Gaussian likelihood --- machine learning-based classification --- non-uniform foundation --- stochastic analysis --- vehicle–pavement–foundation interaction --- forest growing stem volume --- coniferous plantations --- variable selection --- texture feature --- random forest --- red-edge band --- on-shelf availability --- semi-supervised learning --- deep learning --- image classification --- machine learning --- explainable artificial intelligence --- wildfire --- risk assessment --- Naïve bayes --- transmission-line corridors --- image encryption --- compressive sensing --- plaintext related --- chaotic system --- convolutional neural network --- color prior model --- object detection --- piston error detection --- segmented telescope --- BP artificial neural network --- modulation transfer function --- computer vision --- intelligent vehicles --- extrinsic camera calibration --- structure from motion --- convex optimization --- temperature estimation --- BLDC --- electric machine protection --- touchscreen --- capacitive --- display --- SNR --- stylus --- laser cutting --- quality monitoring --- artificial neural network --- burr formation --- cut interruption --- fiber laser --- semi-supervised --- fuzzy --- noisy --- real-world --- plankton --- marine --- activity recognition --- wearable sensors --- imbalanced activities --- sampling methods --- path planning --- Q-learning --- neural network --- YOLO algorithm --- robot arm --- target reaching --- obstacle avoidance