• DocumentCode
    1985085
  • Title

    VRACK: Measuring pedal kinematics during stationary bike cycling

  • Author

    Farjadian, Amir B. ; Kong, Qing-Jie ; Gade, Venkata K. ; Deutsch, Judith E. ; Mavroidis, Constantinos

  • Author_Institution
    Dept. of Mech. & Ind. Eng., Northeastern Univ., Boston, MA, USA
  • fYear
    2013
  • fDate
    24-26 June 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Ankle impairment and lower limb asymmetries in strength and coordination are common symptoms for individuals with selected musculoskeletal and neurological impairments. The virtual reality augmented cycling kit (VRACK) was designed as a compact mechatronics system for lower limb and mobility rehabilitation. The system measures interaction forces and cardiac activity during cycling in a virtual environment. The kinematics measurement was added to the system. Due to the constrained problem definition, the combination of inertial measurement unit (IMU) and Kalman filtering was recruited to compute the optimal pedal angular displacement during dynamic cycling exercise. Using a novel benchmarking method the accuracy of IMU-based kinematics measurement was evaluated. Relatively accurate angular measurements were achieved. The enhanced VRACK system can serve as a rehabilitation device to monitor biomechanical and physiological variables during cycling on a stationary bike.
  • Keywords
    Kalman filters; augmented reality; benchmark testing; biomechanics; biomedical equipment; biomedical measurement; cardiology; force measurement; kinematics; mechatronics; medical disorders; medical signal processing; neurophysiology; patient rehabilitation; Kalman filtering; VRACK; accurate angular measurements; ankle impairment; biomechanical variables; cardiac activity; compact mechatronics system; constrained problem definition; dynamic cycling exercise; inertial measurement unit; interaction force measurement; lower limb asymmetries; mobility rehabilitation; musculoskeletal impairments; neurological impairments; novel benchmarking method; optimal pedal angular displacement; pedal kinematics measurement; physiological variables; rehabilitation device; stationary bike cycling; virtual environment; virtual reality augmented cycling kit; Acceleration; Accuracy; Biomedical monitoring; Kalman filters; Kinematics; Monitoring; Virtual reality; Inertial measurement unit; Kalman Filter; Kinematics measurement; Lower limb rehabilitation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Rehabilitation Robotics (ICORR), 2013 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • ISSN
    1945-7898
  • Print_ISBN
    978-1-4673-6022-7
  • Type

    conf

  • DOI
    10.1109/ICORR.2013.6650453
  • Filename
    6650453