Gait analysis using 3D motion reconstruction with an activity-specific tracking protocol

In this paper, we present a new gait analysis method using 3D body motion reconstruction with an activity-specific tracking protocol. A kinematic chain modeling the movement of lower extremities was constructed for general lower body activity monitoring. By exploring the nature of walking, a constrained forward-backward statistical linearized sigma-point Kalman Smoother with periodic state vector resetting was developed. This tracks the dynamic joint configuration during walking. Direct experimental evaluation was provided by step length computation as well as complete motion reconstruction. This method has demonstrated stable long term tracking of walking and yields greater than 95% accuracy for step length estimation.

[1]  L. Imsland,et al.  Constrained state estimation using the Unscented Kalman Filter , 2008, 2008 16th Mediterranean Conference on Control and Automation.

[2]  Roozbeh Jafari,et al.  Modeling human gait using a Kalman filter to measure walking distance , 2011, Wireless Health.

[3]  Mingyu Gao,et al.  Improved unscented kalman filter for bounded state estimation , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).

[4]  Eric A. Wan,et al.  A new formulation for nonlinear forward-backward smoothing , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[5]  Angelo M. Sabatini,et al.  Assessment of walking features from foot inertial sensing , 2005, IEEE Transactions on Biomedical Engineering.

[6]  James McNames,et al.  Upper limb joint angle tracking with inertial sensors , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  Mark W. Spong,et al.  Robot dynamics and control , 1989 .

[8]  E. Roth,et al.  Physical activity and exercise recommendations for stroke survivors: an American Heart Association scientific statement from the Council on Clinical Cardiology, Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention; the Council on Cardiovascular Nursing; the Council on Nutrition, Physical , 2004, Circulation.

[9]  E. Taub,et al.  The reliability of the wolf motor function test for assessing upper extremity function after stroke. , 2001, Archives of physical medicine and rehabilitation.

[10]  Yu-Liang Hsu,et al.  Gait analysis for patients with Alzheimer'S disease using a triaxial accelerometer , 2012, 2012 IEEE International Symposium on Circuits and Systems.

[11]  Hou Jian,et al.  Gait recognition based on MEMS accelerometer , 2010, IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS.