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Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice
| Wearable Movement Sensors for Rehabilitation: From Technology to Clinical Practice |
| Autore | Ribbers Gerard M |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (328 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
3-D motion analysis
accelerometer accelerometers accelerometry arm use assistive device assistive devices body-worn sensors center of pressure cerebral palsy circadian motor behavior clinical clinical setting constrained extended Kalman filter constraint distance measurement embedded sensors exercise falls Fourier transform functional linear model gait gait analysis gait planning gait rehabilitation GMFCS level goniometer hemiplegia human-machine interaction implementation IMU inertial measurement unit inertial measurement units inertial motion units insole pressure sensors kinematics Lie group locomotion low back pain lower limb amputation machine learning magnetometer-free measurement motion capture motion tracking motor function n/a neurological disorders older adults outcomes pathological gait perinatal stroke physical activity physical therapy physically active workers pose estimation range of motion real-time gait detection rehabilitation relative orientation estimation sensor shoulder single leg squat spinal cord injury stride length stroke tetraplegia upper extremity upper limb performance validity walking walking distance wearable devices wearable sensor wearable sensors wearable technology wireless sensors network |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Wearable Movement Sensors for Rehabilitation |
| Record Nr. | UNINA-9910557359503321 |
Ribbers Gerard M
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders
| Wearable Sensors in the Evaluation of Gait and Balance in Neurological Disorders |
| Autore | Suppa Antonio |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (274 p.) |
| Soggetto topico | History of engineering and technology |
| Soggetto non controllato |
acceleration
accelerometer accelerometry activities of daily life aging Alzheimer's disease asymmetry autocorrelation back school balance bio-signals biomedical signal processing cerebellar ataxia classification cueing CV diagnosis dynamic balance dynamic posturography dynamic time warping EEG EMG gait gait analysis gait assessment gait disorders gait metrics gait patterns gait smoothness gait symmetry GAITRite harmonic ratio head injury healthy subjects home-monitoring IMUs inertial measurement units inertial sensor inertial sensors kinematics loss of balance lower back pain machine learning mobile gait analysis movement analysis multi-regression normalization multiple sclerosis near falls Parkinson's disease pathological gait pattern recognition pedestrian dead-reckoning personalized medicine physiological signals postural stability posture posturography pre-impact fall detection random forest classifier reactive postural responses rehabilitation reliability sampling frequency six-minute walk stability step detection stride segmentation stroke SVM symptoms monitoring test-retest test-retest reliability timed up and go test trajectory reconstruction transcranial direct current stimulation traumatic brain injury tri-axial accelerometer trunk turning analysis validity vestibular syndrome wearable wearable electronics wearable sensors wearables wireless sensors yaw perturbation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557446403321 |
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Suppa Antonio
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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