LEADER 04343nam 2200901z- 450 001 9910557554603321 005 20231214133218.0 035 $a(CKB)5400000000044060 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/76670 035 $a(EXLCZ)995400000000044060 100 $a20202201d2021 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aSensors for Vital Signs Monitoring 210 $aBasel, Switzerland$cMDPI - Multidisciplinary Digital Publishing Institute$d2021 215 $a1 electronic resource (141 p.) 311 $a3-0365-1766-9 311 $a3-0365-1765-0 330 $aSensor 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. 606 $aTechnology: general issues$2bicssc 606 $aEnergy industries & utilities$2bicssc 610 $acardiopulmonary resuscitation (CPR) 610 $aelectroencephalogram (EEG) 610 $ahemodynamic data 610 $acarotid blood flow (CBF) 610 $acerebral circulation 610 $afrequency-shift keying radar 610 $across-correlation 610 $aenvelope detection 610 $acontinuous-wave radar 610 $afrequency discrimination 610 $avital-signs monitoring 610 $aheartbeat accuracy improvement 610 $aheartbeat detection 610 $aabsolute distance measurement 610 $aradar signal processing 610 $a3D+t modeling 610 $acoronary artery 610 $anon-rigid registration 610 $acage deformation 610 $a4D CT 610 $apassenger detection 610 $aCW radar 610 $aradar feature vector 610 $aradar machine learning 610 $awearable sensors 610 $aphysiology 610 $amedical monitoring 610 $avital signs 610 $acompensatory reserve 610 $aultra-high resolution 610 $acone-beam computed tomography 610 $alow-contrast object 610 $aoptimal filter 610 $amodulation transfer function 610 $anoise power spectrum 610 $adoppler cardiogram 610 $awavelet transform 610 $adenoising 610 $amother wavelet function 610 $adecomposition level 610 $asignal decomposition 610 $asignal-to-noise-ratio 615 7$aTechnology: general issues 615 7$aEnergy industries & utilities 700 $aYang$b Jong-Ryul$4edt$01295515 702 $aHyun$b Eugin$4edt 702 $aKim$b Sun Kwon$4edt 702 $aYang$b Jong-Ryul$4oth 702 $aHyun$b Eugin$4oth 702 $aKim$b Sun Kwon$4oth 906 $aBOOK 912 $a9910557554603321 996 $aSensors for Vital Signs Monitoring$93025902 997 $aUNINA