TY - BOOK ID - 146063817 TI - Sensors for Vital Signs Monitoring AU - Yang, Jong-Ryul AU - Hyun, Eugin AU - Kim, Sun Kwon PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Technology: general issues KW - Energy industries & utilities KW - cardiopulmonary resuscitation (CPR) KW - electroencephalogram (EEG) KW - hemodynamic data KW - carotid blood flow (CBF) KW - cerebral circulation KW - frequency-shift keying radar KW - cross-correlation KW - envelope detection KW - continuous-wave radar KW - frequency discrimination KW - vital-signs monitoring KW - heartbeat accuracy improvement KW - heartbeat detection KW - absolute distance measurement KW - radar signal processing KW - 3D+t modeling KW - coronary artery KW - non-rigid registration KW - cage deformation KW - 4D CT KW - passenger detection KW - CW radar KW - radar feature vector KW - radar machine learning KW - wearable sensors KW - physiology KW - medical monitoring KW - vital signs KW - compensatory reserve KW - ultra-high resolution KW - cone-beam computed tomography KW - low-contrast object KW - optimal filter KW - modulation transfer function KW - noise power spectrum KW - doppler cardiogram KW - wavelet transform KW - denoising KW - mother wavelet function KW - decomposition level KW - signal decomposition KW - signal-to-noise-ratio KW - cardiopulmonary resuscitation (CPR) KW - electroencephalogram (EEG) KW - hemodynamic data KW - carotid blood flow (CBF) KW - cerebral circulation KW - frequency-shift keying radar KW - cross-correlation KW - envelope detection KW - continuous-wave radar KW - frequency discrimination KW - vital-signs monitoring KW - heartbeat accuracy improvement KW - heartbeat detection KW - absolute distance measurement KW - radar signal processing KW - 3D+t modeling KW - coronary artery KW - non-rigid registration KW - cage deformation KW - 4D CT KW - passenger detection KW - CW radar KW - radar feature vector KW - radar machine learning KW - wearable sensors KW - physiology KW - medical monitoring KW - vital signs KW - compensatory reserve KW - ultra-high resolution KW - cone-beam computed tomography KW - low-contrast object KW - optimal filter KW - modulation transfer function KW - noise power spectrum KW - doppler cardiogram KW - wavelet transform KW - denoising KW - mother wavelet function KW - decomposition level KW - signal decomposition KW - signal-to-noise-ratio UR - https://www.unicat.be/uniCat?func=search&query=sysid:146063817 AB - 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. ER -