Citation
Terrell Bennett, Roozbeh Jafari, Nicholas Gans. "An Extended Kalman Filter to Estimate Human Gait Parameters and Walking Distance". American Control Conference, 17, June, 2013.

Abstract
In this work, we present a novel method to estimate joint angles and distance traveled by a human while walking. We model the human leg as a two-link revolute robot. Inertial measurement sensors placed on the thigh and shin provide the required measurement inputs. The model and inputs are then used to estimate the desired state parameters associated with forward motion using an extended Kalman filter (EKF). Experimental results with subjects walking in a straight line show that distance walked can be measured with accuracy comparable to a state of the art motion tracking systems. The EKF had an average RMSE of 7 cm over the trials with an average accuracy of greater than 97% for linear displacement.

Electronic downloads

• http://www.essp.utdallas.edu/uploads/Main/Publications/ACC13.pdf

• HTML

  Terrell Bennett, Roozbeh Jafari, Nicholas Gans. <a
  href="http://www.terraswarm.org/pubs/40.html"
  >An Extended Kalman Filter to Estimate Human Gait
  Parameters and Walking Distance</a>, American Control
  Conference, 17, June, 2013.

• Plain text

  Terrell Bennett, Roozbeh Jafari, Nicholas Gans. "An
  Extended Kalman Filter to Estimate Human Gait Parameters and
  Walking Distance". American Control Conference, 17,
  June, 2013.

• BibTeX

  @inproceedings{BennettJafariGans13_ExtendedKalmanFilterToEstimateHumanGaitParametersWalking,
      author = {Terrell Bennett and Roozbeh Jafari and Nicholas
                Gans},
      title = {An Extended Kalman Filter to Estimate Human Gait
                Parameters and Walking Distance},
      booktitle = {American Control Conference},
      day = {17},
      month = {June},
      year = {2013},
      abstract = {In this work, we present a novel method to
                estimate joint angles and distance traveled by a
                human while walking. We model the human leg as a
                two-link revolute robot. Inertial measurement
                sensors placed on the thigh and shin provide the
                required measurement inputs. The model and inputs
                are then used to estimate the desired state
                parameters associated with forward motion using an
                extended Kalman filter (EKF). Experimental results
                with subjects walking in a straight line show that
                distance walked can be measured with accuracy
                comparable to a state of the art motion tracking
                systems. The EKF had an average RMSE of 7 cm over
                the trials with an average accuracy of greater
                than 97% for linear displacement.},
      URL = {http://terraswarm.org/pubs/40.html}
  }
  

Posted by Christopher Brooks on 28 Feb 2013.
Groups: tools