Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

doi:10.3390/books978-3-0365-2064-3

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Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice

Edited by

September 2021

328 pages

ISBN978-3-0365-2063-6 (Hardback)
ISBN978-3-0365-2064-3 (PDF)

https://doi.org/10.3390/books978-3-0365-2064-3

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This book is a reprint of the Special Issue Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice that was published in

Chemistry & Materials Science

Engineering

Environmental & Earth Sciences

Summary

This Special Issue shows a range of potential opportunities for the application of wearable movement sensors in motor rehabilitation. However, the papers surely do not cover the whole field of physical behavior monitoring in motor rehabilitation. Most studies in this Special Issue focused on the technical validation of wearable sensors and the development of algorithms. Clinical validation studies, studies applying wearable sensors for the monitoring of physical behavior in daily life conditions, and papers about the implementation of wearable sensors in motor rehabilitation are under-represented in this Special Issue. Studies investigating the usability and feasibility of wearable movement sensors in clinical populations were lacking. We encourage researchers to investigate the usability, acceptance, feasibility, reliability, and clinical validity of wearable sensors in clinical populations to facilitate the application of wearable movement sensors in motor rehabilitation.

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Keywords

accelerometers; wearable sensors; exercise; measurement; GMFCS level; relative orientation estimation; IMU; magnetometer-free; gait analysis; machine learning; inertial measurement units; neurological disorders; falls; validity; 3-D motion analysis; single leg squat; motion capture; clinical; rehabilitation; motor function; wearable sensors; outcomes; measurement; implementation; machine learning; locomotion; assistive devices; embedded sensors; accelerometry; physical activity; Fourier transform; functional linear model; inertial measurement units; walking distance; lower limb amputation; rehabilitation; gait; Lie group; constrained extended Kalman filter; gait analysis; motion capture; pose estimation; wearable devices; IMU; distance measurement; gait planning; stride length; center of pressure; human–machine interaction; perinatal stroke; kinematics; upper extremity; cerebral palsy; hemiplegia; constraint; inertial measurement unit; wireless sensors network; motion tracking; kinematics; range of motion; shoulder; goniometer; spinal cord injury; tetraplegia; clinical setting; circadian motor behavior; body-worn sensors; older adults; physically active workers; low back pain; inertial motion units; wearable sensor; real-time gait detection; gait analysis; insole pressure sensors; inertial measurement unit; pathological gait; gait rehabilitation; assistive device; wearable technology; rehabilitation; stroke; implementation; physical therapy; stroke; upper extremity; arm use; upper limb performance; accelerometer; sensor; walking; rehabilitation; n/a