Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

Research & information: general --- Biology, life sciences --- Biochemistry --- 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 --- n/a --- Parkinson's disease --- sensory-motor gait disorders --- spatial-temporal analysis

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

Research & information: general --- Biology, life sciences --- Biochemistry --- 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