TY - BOOK ID - 145039427 TI - Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice AU - Ribbers, Gerard M AU - Regterschot, G.R.H. AU - Bussmann, J.B.J. PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - Technology: general issues KW - accelerometers KW - wearable sensors KW - exercise KW - measurement KW - GMFCS level KW - relative orientation estimation KW - IMU KW - magnetometer-free KW - gait analysis KW - machine learning KW - inertial measurement units KW - neurological disorders KW - falls KW - validity KW - 3-D motion analysis KW - single leg squat KW - motion capture KW - clinical KW - rehabilitation KW - motor function KW - outcomes KW - implementation KW - locomotion KW - assistive devices KW - embedded sensors KW - accelerometry KW - physical activity KW - Fourier transform KW - functional linear model KW - walking distance KW - lower limb amputation KW - gait KW - Lie group KW - constrained extended Kalman filter KW - pose estimation KW - wearable devices KW - distance measurement KW - gait planning KW - stride length KW - center of pressure KW - human-machine interaction KW - perinatal stroke KW - kinematics KW - upper extremity KW - cerebral palsy KW - hemiplegia KW - constraint KW - inertial measurement unit KW - wireless sensors network KW - motion tracking KW - range of motion KW - shoulder KW - goniometer KW - spinal cord injury KW - tetraplegia KW - clinical setting KW - circadian motor behavior KW - body-worn sensors KW - older adults KW - physically active workers KW - low back pain KW - inertial motion units KW - wearable sensor KW - real-time gait detection KW - insole pressure sensors KW - pathological gait KW - gait rehabilitation KW - assistive device KW - wearable technology KW - stroke KW - physical therapy KW - arm use KW - upper limb performance KW - accelerometer KW - sensor KW - walking KW - accelerometers KW - wearable sensors KW - exercise KW - measurement KW - GMFCS level KW - relative orientation estimation KW - IMU KW - magnetometer-free KW - gait analysis KW - machine learning KW - inertial measurement units KW - neurological disorders KW - falls KW - validity KW - 3-D motion analysis KW - single leg squat KW - motion capture KW - clinical KW - rehabilitation KW - motor function KW - outcomes KW - implementation KW - locomotion KW - assistive devices KW - embedded sensors KW - accelerometry KW - physical activity KW - Fourier transform KW - functional linear model KW - walking distance KW - lower limb amputation KW - gait KW - Lie group KW - constrained extended Kalman filter KW - pose estimation KW - wearable devices KW - distance measurement KW - gait planning KW - stride length KW - center of pressure KW - human-machine interaction KW - perinatal stroke KW - kinematics KW - upper extremity KW - cerebral palsy KW - hemiplegia KW - constraint KW - inertial measurement unit KW - wireless sensors network KW - motion tracking KW - range of motion KW - shoulder KW - goniometer KW - spinal cord injury KW - tetraplegia KW - clinical setting KW - circadian motor behavior KW - body-worn sensors KW - older adults KW - physically active workers KW - low back pain KW - inertial motion units KW - wearable sensor KW - real-time gait detection KW - insole pressure sensors KW - pathological gait KW - gait rehabilitation KW - assistive device KW - wearable technology KW - stroke KW - physical therapy KW - arm use KW - upper limb performance KW - accelerometer KW - sensor KW - walking UR - https://www.unicat.be/uniCat?func=search&query=sysid:145039427 AB - 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. ER -