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Lower limb kinematic, kinetic, and EMG data from young healthy humans during walking at controlled speeds.

Luís MoreiraJoana FigueiredoPedro Filipe Pereira da FonsecaJoão Paulo Vila-BoasCristina Peixoto Santos
Published in: Scientific data (2021)
Understanding the lower limb kinematic, kinetic, and electromyography (EMG) data interrelation in controlled speeds is challenging for fully assessing human locomotion conditions. This paper provides a complete dataset with the above-mentioned raw and processed data simultaneously recorded for sixteen healthy participants walking on a 10 meter-flat surface at seven controlled speeds (1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 km/h). The raw data include 3D joint trajectories of 24 retro-reflective markers, ground reaction forces (GRF), force plate moments, center of pressures, and EMG signals from Tibialis Anterior, Gastrocnemius Lateralis, Biceps Femoris, and Vastus Lateralis. The processed data present gait cycle-normalized data including filtered EMG signals and their envelope, 3D GRF, joint angles, and torques. This study details the experimental setup and presents a brief validation of the data quality. The presented dataset may contribute to (i) validate and enhance human biomechanical gait models, and (ii) serve as a reference trajectory for personalized control of robotic assistive devices, aiming an adequate assistance level adjusted to the gait speed and user's anthropometry.
Keyphrases
  • lower limb
  • electronic health record
  • big data
  • endothelial cells
  • depressive symptoms
  • upper limb
  • magnetic resonance
  • computed tomography
  • data analysis
  • quality improvement