Recent Advances in Motion Analysis

• Muut tekijät: Di Nardo, Francesco (Toimittaja), Fioretti, Sandro (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Aiheet: Technology: general issues; falls; slips; trips; postural perturbations; wearables; stretch-sensors; ankle kinematics; rowing; technology; inertial sensor; accelerometer; performance; signal processing; sEMG; knee; random forest; principal component analysis; back propagation; estimation model; knee angle; deep learning; neural networks; gait-phase classification; electrogoniometer; EMG sensors; walking; gait-event detection; automotive radar; machine learning; walking analysis; seated posture; cognitive engagement; stress level; load cells; embedded systems; sensorized seat; flexion-relaxation phenomenon; surface electromyography; wearable device; WBSN; automatic detection of the FRP; Internet of Things (IoT); human activity recognition (HAR); motion analysis; wearable sensors; cerebral palsy; hemiplegia; motor disorders; gait variability; coefficient of variation; surface EMG; statistical gait analysis; activation patterns; co-activation; Parkinson's disease; activity recognition; rate invariance; Lie group
• Linkit: DOAB: download the publication; DOAB: description of the publication

The advances in the technology and methodology for human movement capture and analysis over the last decade have been remarkable. Besides acknowledged approaches for kinematic, dynamic, and electromyographic (EMG) analysis carried out in the laboratory, more recently developed devices, such as weara...