LEADER 04509nam 2201189z- 450 001 9910576872303321 005 20231214133228.0 035 $a(CKB)5720000000008453 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/84536 035 $a(EXLCZ)995720000000008453 100 $a20202206d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aWearables for Movement Analysis in Healthcare 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 electronic resource (252 p.) 311 $a3-0365-4019-9 311 $a3-0365-4020-2 330 $aQuantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients? capabilities, unobtrusively and continuously, for clinical purposes. 606 $aResearch & information: general$2bicssc 606 $aBiology, life sciences$2bicssc 606 $aBiochemistry$2bicssc 610 $agait 610 $asmoothness 610 $aolder adults 610 $aaccelerometer 610 $ainertial measurement unit (IMU) 610 $aupper extremity 610 $astroke 610 $abiomechanical phenomena 610 $akinematics 610 $ainertial measurement systems 610 $amotion analysis 610 $awearable devices 610 $ae-textile 610 $agait analysis 610 $am-health 610 $aplantar pressure 610 $avalidation 610 $aInternet of Things 610 $abody sensor network 610 $ainertial sensors 610 $aground reaction force 610 $aspatio-temporal parameters 610 $awearable sensors 610 $adecision trees 610 $afoot drop stimulation 610 $asymmetry 610 $ainertial measurement sensor 610 $awearable inertial sensors 610 $amarker-based optoelectronic system 610 $aACL 610 $arehabilitation 610 $amotion capture validation 610 $aupper limb 610 $aParkinson's disease 610 $aBox and Block test 610 $ainertial sensors network 610 $abiomechanics analysis 610 $akinematic data 610 $ahand trajectories 610 $akinematic 610 $ainertial measurement units 610 $aangle-angle diagrams 610 $acyclograms 610 $aobesity 610 $abradykinesia 610 $areal-life 610 $anaturalistic monitoring 610 $amotor fluctuation 610 $awearable movement sensor 610 $aIMU 610 $amotion capture 610 $areliability 610 $aclinical 610 $aorthopedic 610 $asensory-motor gait disorders 610 $alimb prosthesis 610 $aspatial-temporal analysis 610 $asymmetry index 610 $awalking 610 $a6-min walking test 610 $awearable system 610 $ainertial sensor 610 $aRGB-D sensors 610 $aoptoelectronic system 610 $amovement analysis 610 $ahemiparesis 615 7$aResearch & information: general 615 7$aBiology, life sciences 615 7$aBiochemistry 700 $aCapodaglio$b Paolo$4edt$01296667 702 $aCimolin$b Veronica$4edt 702 $aCapodaglio$b Paolo$4oth 702 $aCimolin$b Veronica$4oth 906 $aBOOK 912 $a9910576872303321 996 $aWearables for Movement Analysis in Healthcare$93024199 997 $aUNINA