Visual Inertial Odometry-Based Gait Analysis Using Waist-Attached RGB-D Camera and Inertial Sensors

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Abstract
In this paper, a visual inertial odometry algorithm is proposed to estimate walking stride length and reconstruct walking trajectory. Depth and color image data from a downward-looking waist-mounted RGB-D camera is fused with its internal Inertial Measurement Unit (IMU) data in an estimation algorithm to perform foot detection and position estimation. Floor plane and foot positions in stance phases are calculated and used as landmarks to construct measurement equations for updating in the filter. A smoothing problem is formulated as a linear optimization problem to improve filter result. Experiments are performed to evaluate the walking trajectory reconstruction and the overall root mean square errors (RMSE) of walking stride length estimation is about 3.8 centimeters.
Funding Information
  • Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2019R1I1A3A01057414)

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