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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