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Electronics 2019, 8(1), 18; https://doi.org/10.3390/electronics8010018

Spline Function Simulation Data Generation for Walking Motion Using Foot-Mounted Inertial Sensors

Electrical Engineering Department, University of Ulsan, Ulsan 44610, Korea
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Received: 22 October 2018 / Revised: 19 December 2018 / Accepted: 20 December 2018 / Published: 23 December 2018
(This article belongs to the Special Issue Sensing and Signal Processing in Smart Healthcare)
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Abstract

This paper investigates the generation of simulation data for motion estimation using inertial sensors. The smoothing algorithm with waypoint-based map matching is proposed using foot-mounted inertial sensors to estimate position and attitude. The simulation data are generated using spline functions, where the estimated position and attitude are used as control points. The attitude is represented using B-spline quaternion and the position is represented by eighth-order algebraic splines. The simulation data can be generated using inertial sensors (accelerometer and gyroscope) without using any additional sensors. Through indoor experiments, two scenarios were examined include 2D walking path (rectangular) and 3D walking path (corridor and stairs) for simulation data generation. The proposed simulation data is used to evaluate the estimation performance with different parameters such as different noise levels and sampling periods. View Full-Text
Keywords: motion estimation; inertial sensors; simulation; spline function; Kalman filter motion estimation; inertial sensors; simulation; spline function; Kalman filter
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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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Pham, T.T.; Suh, Y.S. Spline Function Simulation Data Generation for Walking Motion Using Foot-Mounted Inertial Sensors. Electronics 2019, 8, 18.

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