Sensors for Gait, Posture, and Health Monitoring Volume 3
English[eng]
step detection||machine learning||outlier detection||transition matrices||autoencoders||ground reaction force (GRF)||micro electro mechanical systems (MEMS)||gait||walk||bipedal locomotion||3-axis force sensor||shoe||force distribution||multi-sensor gait classification||distributed compressed sensing||joint sparse representation classification||telemonitoring of gait||operating range||accelerometer||stride length||peak tibial acceleration||running velocity||wearable sensors||feedback technology||rehabilitation||motor control||cerebral palsy||inertial sensors||gait events||spatiotemporal parameters||postural control||falls in the elderly||fall risk assessment||low-cost instrumented insoles||foot plantar center of pressure||flexible sensor||gait recognition||piezoelectric material||wearable||adaptability||force sensitive resistors||self-tuning triple threshold algorithm||sweat sensor||sweat rate||dehydration||IoT||PDMS||surface electromyography||handgrip force||force-varying muscle contraction||nonlinear analysis||wavelet scale selection||inertial measurement unit||gyroscope||asymmetry||feature extraction||gait analysis||lower limb prosthesis||trans-femoral amputee||MR damper||knee damping control||inertial measurement units||motion analysis||kinematics||functional activity||repeatability||reliability||biomechanics||cognitive frailty||cognitive–motor impairment||Alzheimer’s disease||motor planning error||instrumented trail-making task||ankle reaching task||dual task walking||nondestructive||joint moment||partial weight loading||muscle contributions||sit-to-stand training||motion parameters||step length||self-adaptation||Parkinson’s disease (PD)||tremor dominant (TD)||postural instability and gait difficulty (PIGD)||center of pressure (COP)||fast Fourier transform (FFT)||wavelet transform (WT)||fall detection system||smartphones||accelerometers||machine learning algorithms||supervised learning||ANOVA analysis||Step-detection||ActiGraph||Pedometer||acceleration||physical activity||physical function||physical performance test||chair stand||sit to stand transfer||wearables||gyroscopes||e-Health application||physical rehabilitation||shear and plantar pressure sensor||biaxial optical fiber sensor||multiplexed fiber Bragg gratings||frailty||pre-frail||wearable sensor||sedentary behavior||moderate-to-vigorous activity||steps||fall detection||elderly people monitoring||telerehabilitation||virtual therapy||Kinect||eHealth||telemedicine||insole||injury prevention||biomechanical gait variable estimation||inertial gait variable||total knee arthroplasty||falls in healthy elderly||fall prevention||biometrics||human gait recognition||ground reaction forces||Microsoft Kinect||high heels||fusion data||ensemble classifiers||accidental falls||older adults||neural networks||convolutional neural network||long short-term memory||accelerometry||obesity||nonlinear||electrostatic field sensing||gait measurement||temporal parameters||artificial neural network||propulsion||aging||walking||smart footwear||frailty prediction||fall risk||smartphone based assessments||adverse post-operative outcome||intelligent surveillance systems||human fall detection||health and well-being||safety and security||n/a||movement control||anterior cruciate ligament||kinetics||real-time feedback||biomechanical gait features||impaired gait classification||pattern recognition||sensors||clinical||knee||osteoarthritis||shear stress||callus||woman||TUG||IMU||geriatric assessment||semi-unsupervised||self-assessment||domestic environment||functional decline||symmetry||trunk movement||autocorrelation||gait rehabilitation||wearable device||IMU sensors||gait classification||stroke patients||neurological disorders||scanning laser rangefinders (SLR), GAITRite||cadence||velocity and stride-length||power||angular velocity||human motion measurement||sensor fusion||complementary filter||fuzzy logic||inertial and magnetic sensors||ESOQ-2||Parkinson’s disease||UPDRS||movement disorders||human computer interface||RGB-Depth||hand tracking||automated assessment||at-home monitoring||Parkinson’s Diseases||motorized walker||haptic cue||gait pattern||statistics study||walk detection||step counting||signal processing||plantar pressure||flat foot||insoles||force sensors||arch index||sports analytics||deep learning||classification||inertial sensor||cross-country skiing||classical style||skating style||batteryless strain sensor||wireless strain sensor||resonant frequency modulation||Ecoflex||human activity recognition||smartphone||human daily activity||ensemble method||running||velocity||smart shoe||concussion||inertial motion units (IMUs)||vestibular exercises||validation||motion capture||user intent recognition||transfemoral prosthesis||multi-objective optimization||biogeography-based optimization||smart cane||weight-bearing||health monitoring||wearable/inertial sensors||regularity||variability||human||motion||locomotion||UPDRS tasks||posture||postural stability||center of mass||RGB-depth||neurorehabilitation||hallux abductus valgus||high heel||proximal phalanx of the hallux||abduction||valgus||ultrasonography||Achilles tendon||diagnostic||imaging||tendinopathy||foot insoles||electromyography||joint instability||muscle contractions||motorcycling||wearable electronic devices||validity||relative movement||lower limb prosthetics||biomechanic measurement tasks||quantifying socket fit||rehabilitation exercise||dynamic time warping||automatic coaching||exergame||fine-wire intramuscular EMG electrode||non-human primate model||traumatic spinal cord injury||wavelet transform||relative power||linear mixed model||VO2||calibration||MET||VO2net||speed||equivalent speed||free-living||children||adolescents||adults||gait event detection||hemiplegic gait||appropriate mother wavelet||acceleration signal||wavelet-selection criteria||conductive textile||stroke||hemiparetic||real-time monitoring||lower limb locomotion activity||triplet Markov model||semi-Markov model||on-line EM algorithm||human kinematics||phase difference angle