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Inertial Sensor-Based Smoother for Gait Analysis

Department of Electrical Engineering, University of Ulsan, Mugeo, Namgu, Ulsan 680-749, Korea
Sensors 2014, 14(12), 24338-24357;
Received: 17 October 2014 / Revised: 5 December 2014 / Accepted: 9 December 2014 / Published: 17 December 2014
(This article belongs to the Special Issue Inertial Sensors and Systems)
PDF [771 KB, uploaded 17 December 2014]


An off-line smoother algorithm is proposed to estimate foot motion using an inertial sensor unit (three-axis gyroscopes and accelerometers) attached to a shoe. The smoother gives more accurate foot motion estimation than filter-based algorithms by using all of the sensor data instead of using the current sensor data. The algorithm consists of two parts. In the first part, a Kalman filter is used to obtain initial foot motion estimation. In the second part, the error in the initial estimation is compensated using a smoother, where the problem is formulated in the quadratic optimization problem. An efficient solution of the quadratic optimization problem is given using the sparse structure. Through experiments, it is shown that the proposed algorithm can estimate foot motion more accurately than a filter-based algorithm with reasonable computation time. In particular, there is significant improvement in the foot motion estimation when the foot is moving off the floor: the z-axis position error squared sum (total time: 3.47 s) when the foot is in the air is 0.0807 m2 (Kalman filter) and 0.0020 m2 (the proposed smoother). View Full-Text
Keywords: gait analysis; smoother; inertial sensors; inertial navigation algorithm gait analysis; smoother; inertial sensors; inertial navigation algorithm

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Suh, Y.S. Inertial Sensor-Based Smoother for Gait Analysis. Sensors 2014, 14, 24338-24357.

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