This dataset contains leg joint kinematics, kinetics, and EMG activity from an experimental protocol approved by the Institutional Review Board at the University of Texas at Dallas. Ten able-bodied subjects walked at steady speeds and inclines on a Bertec instrumented treadmill for one minute per trial. Each subject walked at every combination of the speeds 0.8 m/s, 1.0 m/s, and 1.2 m/s and inclines from -10 degrees to +10 degrees at 2.5 degree increments, for a total of 27 trials.

  • Biomedical and Health Sciences
  • Last Updated On: 
    Wed, 10/31/2018 - 15:15

    This dataset is a highly versatile and precisely annotated large-scale dataset of smartphone sensor data for multimodal locomotion and transportation analytics of mobile users.

    The dataset comprises 7 months of measurements, collected from all sensors of 4 smartphones carried at typical body locations, including the images of a body-worn camera, while 3 participants used 8 different modes of transportation in the southeast of the United Kingdom, including in London.

  • Computational Intelligence
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34
    Citation Author(s): 
    Hristijan Gjoreski, Mathias Ciliberto, Lin Wang, Francisco Javier Ordoñez Morales, Sami Mekki, Stefan Valentin, Daniel Roggen

    Previous neuroimaging research has been traditionally confined to strict laboratory environments due to the limits of technology. Only recently have more studies emerged exploring the use of mobile brain imaging outside the laboratory. This study uses electroencephalography (EEG) and signal processing techniques to provide new opportunities for studying mobile subjects moving outside of the laboratory and in real world settings. The purpose of this study was to document the current viability of using high density EEG for mobile brain imaging both indoors and outdoors.

  • Neuroscience
  • Last Updated On: 
    Sat, 06/16/2018 - 23:16