Reprint

Wearables for Movement Analysis in Healthcare

Edited by
May 2022
252 pages
  • ISBN978-3-0365-4019-1 (Hardback)
  • ISBN978-3-0365-4020-7 (PDF)

This is a Reprint of the Special Issue Wearables for Movement Analysis in Healthcare that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

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. 

Format
  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
Keywords
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; gait analysis; inertial sensors; ground reaction force; gait analysis; spatio-temporal parameters; wearable sensors; decision trees; foot drop stimulation; gait; symmetry; stroke; inertial measurement sensor; wearable inertial sensors; marker-based optoelectronic system; ACL; rehabilitation; motion capture validation; kinematics; upper limb; Parkinson’s disease; Box and Block test; inertial sensors network; biomechanics analysis; kinematic data; hand trajectories; validation; kinematic; inertial measurement units; motion analysis; gait; angle-angle diagrams; cyclograms; gait; kinematics; obesity; symmetry; Parkinson’s disease; bradykinesia; real-life; naturalistic monitoring; wearable sensors; accelerometer; motor fluctuation; wearable movement sensor; IMU; motion capture; reliability; clinical; orthopedic; sensory–motor gait disorders; limb prosthesis; spatial–temporal analysis; kinematics; symmetry index; obesity; walking; 6-min walking test; wearable system; inertial sensor; rehabilitation; RGB-D sensors; optoelectronic system; movement analysis; gait; Parkinson’s disease; hemiparesis; spatio-temporal parameters; n/a

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