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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.

Technology: general issues --- 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 --- outcomes --- implementation --- locomotion --- assistive devices --- embedded sensors --- accelerometry --- physical activity --- Fourier transform --- functional linear model --- walking distance --- lower limb amputation --- gait --- Lie group --- constrained extended Kalman filter --- pose estimation --- wearable devices --- 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 --- 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 --- insole pressure sensors --- pathological gait --- gait rehabilitation --- assistive device --- wearable technology --- stroke --- physical therapy --- arm use --- upper limb performance --- accelerometer --- sensor --- walking --- n/a --- human-machine interaction

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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.

Technology: general issues --- 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 --- outcomes --- implementation --- locomotion --- assistive devices --- embedded sensors --- accelerometry --- physical activity --- Fourier transform --- functional linear model --- walking distance --- lower limb amputation --- gait --- Lie group --- constrained extended Kalman filter --- pose estimation --- wearable devices --- 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 --- 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 --- insole pressure sensors --- pathological gait --- gait rehabilitation --- assistive device --- wearable technology --- stroke --- physical therapy --- arm use --- upper limb performance --- accelerometer --- sensor --- walking --- 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 --- outcomes --- implementation --- locomotion --- assistive devices --- embedded sensors --- accelerometry --- physical activity --- Fourier transform --- functional linear model --- walking distance --- lower limb amputation --- gait --- Lie group --- constrained extended Kalman filter --- pose estimation --- wearable devices --- 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 --- 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 --- insole pressure sensors --- pathological gait --- gait rehabilitation --- assistive device --- wearable technology --- stroke --- physical therapy --- arm use --- upper limb performance --- accelerometer --- sensor --- walking

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The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders.

History of engineering & technology --- inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring --- inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring

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• Reference Manager
• EndNote
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The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders.

History of engineering & technology --- inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring

Choose an application

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

The aging population and the increased prevalence of neurological diseases have raised the issue of gait and balance disorders as a major public concern worldwide. Indeed, gait and balance disorders are responsible for a high healthcare and economic burden on society, thus, requiring new solutions to prevent harmful consequences. Recently, wearable sensors have provided new challenges and opportunities to address this issue through innovative diagnostic and therapeutic strategies. Accordingly, the book “Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders” collects the most up-to-date information about the objective evaluation of gait and balance disorders, by means of wearable biosensors, in patients with various types of neurological diseases, including Parkinson’s disease, multiple sclerosis, stroke, traumatic brain injury, and cerebellar ataxia. By adopting wearable technologies, the sixteen original research articles and reviews included in this book offer an updated overview of the most recent approaches for the objective evaluation of gait and balance disorders.

inertial measurement units --- gait analysis --- biomedical signal processing --- pattern recognition --- step detection --- physiological signals --- Parkinson’s disease --- pathological gait --- turning analysis --- wearable sensors --- mobile gait analysis --- wearables --- inertial sensors --- traumatic brain injury --- dynamic balance --- gait disorders --- gait patterns --- head injury --- gait symmetry --- gait smoothness --- acceleration --- machine learning --- classification --- accelerometer --- GAITRite --- multi-regression normalization --- SVM --- random forest classifier --- balance --- gait --- transcranial direct current stimulation --- wearable electronics --- IMUs --- cueing --- posture --- rehabilitation --- cerebellar ataxia --- movement analysis --- personalized medicine --- stroke --- asymmetry --- trunk --- reliability --- validity --- aging --- reactive postural responses --- yaw perturbation --- kinematics --- postural stability --- dynamic posturography --- multiple sclerosis --- gait metrics --- test-retest reliability --- sampling frequency --- accelerometry --- autocorrelation --- harmonic ratio --- six-minute walk --- back school --- inertial sensor --- lower back pain --- stability --- timed up and go test --- gait assessment --- tri-axial accelerometer --- CV --- healthy subjects --- test-retest --- trajectory reconstruction --- stride segmentation --- dynamic time warping --- pedestrian dead-reckoning --- near falls --- loss of balance --- pre-impact fall detection --- activities of daily life --- bio-signals --- EEG --- EMG --- wireless sensors --- posturography --- Alzheimer’s disease --- vestibular syndrome --- diagnosis --- symptoms monitoring --- wearable --- home-monitoring