Wearables for Movement Analysis in Healthcare
Quantitative 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...
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Year of Publication: | 2022 |
Language: | English |
Physical Description: | 1 electronic resource (252 p.) |
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Capodaglio, Paolo edt Wearables for Movement Analysis in Healthcare Basel MDPI - Multidisciplinary Digital Publishing Institute 2022 1 electronic resource (252 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier Quantitative 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. English Research & information: general bicssc Biology, life sciences bicssc Biochemistry bicssc gait smoothness older adults accelerometer inertial measurement unit (IMU) upper extremity stroke biomechanical phenomena kinematics inertial measurement systems motion analysis wearable devices e-textile gait analysis m-health plantar pressure validation Internet of Things body sensor network inertial sensors ground reaction force spatio-temporal parameters wearable sensors decision trees foot drop stimulation symmetry inertial measurement sensor wearable inertial sensors marker-based optoelectronic system ACL rehabilitation motion capture validation upper limb Parkinson's disease Box and Block test inertial sensors network biomechanics analysis kinematic data hand trajectories kinematic inertial measurement units angle-angle diagrams cyclograms obesity bradykinesia real-life naturalistic monitoring motor fluctuation wearable movement sensor IMU motion capture reliability clinical orthopedic sensory-motor gait disorders limb prosthesis spatial-temporal analysis symmetry index walking 6-min walking test wearable system inertial sensor RGB-D sensors optoelectronic system movement analysis hemiparesis 3-0365-4019-9 3-0365-4020-2 Cimolin, Veronica edt Capodaglio, Paolo oth Cimolin, Veronica oth |
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English |
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Cimolin, Veronica Capodaglio, Paolo Cimolin, Veronica |
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Cimolin, Veronica Capodaglio, Paolo Cimolin, Veronica |
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HerausgeberIn Sonstige Sonstige |
title |
Wearables for Movement Analysis in Healthcare |
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Wearables for Movement Analysis in Healthcare |
title_full |
Wearables for Movement Analysis in Healthcare |
title_fullStr |
Wearables for Movement Analysis in Healthcare |
title_full_unstemmed |
Wearables for Movement Analysis in Healthcare |
title_auth |
Wearables for Movement Analysis in Healthcare |
title_new |
Wearables for Movement Analysis in Healthcare |
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wearables for movement analysis in healthcare |
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MDPI - Multidisciplinary Digital Publishing Institute |
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2022 |
physical |
1 electronic resource (252 p.) |
isbn |
3-0365-4019-9 3-0365-4020-2 |
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Not Illustrated |
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AT capodagliopaolo wearablesformovementanalysisinhealthcare AT cimolinveronica wearablesformovementanalysisinhealthcare |
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(CKB)5720000000008453 (oapen)https://directory.doabooks.org/handle/20.500.12854/84536 (EXLCZ)995720000000008453 |
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Wearables for Movement Analysis in Healthcare |
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